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Accountability Can Transform (ACT) Health

Baseline Report

July 27, 2015 (FINAL)

Contributors Paola Elice, IPA

Laura Schmucker, IPA

Kyle Holloway, IPA

Dan Posner, UCLA

Doug Parkerson, IPA

Pia Raffler, Yale

Angela Bailey, GOAL Uganda

Funded by

This material has been funded by UK aid from the UK Government, however the views ex-pressed do not necessarily reflect the UK Government’s official policies. Project title: Promoting Health Sector Accountability in Uganda through support to GOAL Uganda

DFID Component Code: 200779-113 Funding mechanism: Accountable Grant Arrangement Programme Implemented by: GOAL: an international humanitarian organisation Coalition for Health Promotion and Social Development (HEPS Uganda) Friends of Christ Revival Ministries (FOC REV)

Kabarole Research & Resource Centre (KRC) Multi-Community Based Development Initiative (MUCOBADI) Research by: Innovations for Poverty Action

ACT Health Baseline Report (July 2015) 2

Table of Contents Acronyms ....................................................................................................................... 4

Executive Summary ........................................................................................................ 5

I. Research Overview ...................................................................................................... 7

II. Research Design and Intervention ............................................................................ 8

Health System Context in Uganda ................................................................................... 8

Study Design ............................................................................................................... 9

Power Calculations ...................................................................................................... 11

III.Intervention Description ........................................................................................ 12

Intervention Description .............................................................................................. 12

Intervention – Illustrative Details.................................................................................. 12

P2P and ACT Health Intervention Comparison ................................................................ 13

IV. Survey Design and Administration .......................................................................... 16

Sampling Strategy ...................................................................................................... 16

Survey Tools .............................................................................................................. 20

V. Data Collection, Organisation and Challenges ......................................................... 21

Team Structure .......................................................................................................... 21

Data Management ...................................................................................................... 21

Major Data Collection Challenges .................................................................................. 22

VI. Balance Checks ....................................................................................................... 24

VII. Descriptive Statistics ............................................................................................. 25

A. Overview ............................................................................................................ 25

B. Rights & Responsibilities ....................................................................................... 26

C. Service Availability & Health Facility Resources ........................................................ 29

D. User Experiences – Access to & Perceived Quality of Services .................................... 32

E. ANC and Delivery ................................................................................................. 38

F. Family Planning ................................................................................................... 40

G. Fees at Health Facilities ........................................................................................ 42

H. Health Facility Staffing & Absenteeism .................................................................... 43

I. Drug Availability .................................................................................................. 45

J. Community Structures & Accountability Mechanisms ................................................ 48

K. Health Outcomes (<5 and maternal deaths) ............................................................ 50

VIII. Progress Update .................................................................................................. 53

IX. Next Steps .............................................................................................................. 53

Sharing the Baseline Report ......................................................................................... 53

Intervention Observation ............................................................................................. 53


Midline Data Collection ................................................................................................ 53

Endline Data Collection ................................................................................................ 54

Publication and Dissemination ...................................................................................... 55

Conclusion ................................................................................................................. 56

X. Appendices ............................................................................................................. 59

Appendix 1: Summary of Baseline Data for Key Indicators (DFID logframe) ....................... 59

Appendix 2: Listing Protocol ......................................................................................... 60

Appendix 3: Survey Tools ............................................................................................ 66

Appendix 4: Field team roles and structure .................................................................... 69

Appendix 5: Baseline Data Collection and Implementation Gantt Chart .............................. 76

Appendix 6: Intervention Resources .............................................................................. 77

Appendix 7: Midline Gantt Chart ................................................................................... 79

Appendix 8: Additional Balance Checks ......................................................................... 81


Acronyms

ACT Health Accountability Can Transform Health

ANC Antenatal Care

ARV Antiretroviral Drugs

BCG Bacille Calmette-Guerin (Tuberculosis) Vaccine

CAI Computer-Assisted Interviewing

CBO Community-Based Organisation

DHO District Health Officer

DPV Polio Vaccine

FOC-REV Friends of Christ Revival Ministries

GOAL GOAL Ireland

HC Health Centre

HMIS Health Management Information System

HCT HIV Counselling and Testing

HEPS Coalition for Health Promotion and Social Development

HH Household

HUMC Health Unit Management Committee

IPA Innovations for Poverty Action

KRC

LC

Kabarole Research and Resource Centre

Local Council

MOH Ministry of Health

MUCABODI Multi Community Based Development Initiative

NARC National HIV/AIDS Research Committee

ODK Open Data Kit

P2P Power to the People

PMTCT Prevention of Mother-to-Child Transmission

PHC Primary Health Care

QGIS Quantum Geographic Information System

RCT Randomised Control Trial

RDC Resident District Commissioner

UBOS Uganda Bureau of Statistics

UGX Ugandan Shillings

UNCST Uganda National Council for Science and Technology

VHT Village Health Team


Executive Summary

The Accountability Can Transform (ACT) Health study replicates and expands upon a successful

health accountability programme in rural Uganda. The programme collects information about the

performance of health providers in 377 rural health centres and the health outcomes in the

communities they serve. This information is then disseminated to both members of the local

community and the health care providers who staff the facilities, and action plans are developed

to outline concrete actions that can be taken in light of this information. In some communities,

interface meetings are held between members of the community and clinic staff to develop joint

plans of action. The goal of these activities is to increase community members’ awareness of the

quality of care they are (and should be) receiving according to Ministry of Health standards and

the Uganda National Minimum Health Care Package (UNMHCP). With this information (awareness)

and through the experience of working with fellow community members (and health workers), be

in a stronger position to demand better services (accountability). This approach is also theorised

to have a positive effect on health-seeking behaviours that are also essential for improved health

outcomes. In a setting where funds for increased public health spending are limited and where

top-down approaches to health care delivery improvements have had mixed results, previous re-

search on this community-based, bottom-up approach indicates real promise.

The design of the intervention requires the collection of baseline data on health care provision,

user experiences and health outcomes. This information is disseminated as part of the program-

ming and provides a reference point against which to measure changes generated by the inter-

vention (impact). Random assignment of health facilities to four groups, three treatment groups

and one control group, puts us in a strong position to compare baseline and midline measures to

ascertain the impact of the intervention.

This baseline report summarises key findings from the baseline data collected between Septem-

ber and December 2014 in 16 districts of Uganda. The baseline analysis includes data from 377

government health centres (226 HCIIs and 151 HCIIIs) and 15,457 households. The baseline

generated a large amount of data, which is presented thematically in section IV Descriptive Sta-

tistics. Each thematic section, as highlighted in the table below, juxtaposes responses from health

centres and households. Access to information is a running theme through each section. Our aim

is to present the complex supply and demand side dimensions and rich information gathered on

each thematic area so that we can understand each challenge holistically.

Rights &

Responsibilities

26% of households identified two or more health rights

94% of health centre representatives identified two or more health rights

Service

Availability

&

Health Facility

Resources

Majority of HCII and HCIII reported they and have infrastructure and provide

required to deliver Uganda National Minimum Health Care Package (UNMHP)

HCIIs provide services to an average of 674 clients per month

HCIIIs provide services to an average of 1,280 clients per month

HCIIIs received Primary Health Care (PHC) funds at an average of 12 mil-

lion UGX in the previous 12 months, HCIIs received an average of 1.7 mil-

lion UGX

User

Experiences –

94% of households reported that one or more member had visited the clos-

est HCII / HCIII in the previous 12 months

40% of total health visits reported in prior12 months were a government HC

33% of total health visits reported in prior12 months were ―self-treatment‖


Access to

&

Perceived

Quality of

Services

78% of households chose the facility because it was close to their home

53% of households reported waiting less than one hour on their last visit

83% of households reported that they were examined on their last visit

68% of households were satisfied or very satisfied by the quality of care re-

ceived on their last visit

73% of households are satisfied or very satisfied with their relationship with

HC staff

ANC

&

Delivery

40% of women who had given birth in previous 12 months reported going

for 4 or more ANC visits

83% of expectant mothers reported that they had received an HIV test

37% of women who had given birth in the previous 12 months delivered at

the closest MoH facility

Family

Planning

28% of households reported seeking family planning services in the previous

12 months from any location

18% of respondents reported that they fear side effects of family planning

12% report using natural methods (breastfeeding, beads, etc.)

70% of households reported receiving information about family planning

Fees at

Health

Facilities

8% of households reported cash payments at the HC on most recent visit –

most common for deliveries – median payment was 7,000 UGX (1.63 GBP)

36% of households reported that they had to bring items on their last visit

Health Facility

Staffing

&

Absenteeism

63% of medical staff assigned to HCII were present on survey day

58% of medical staff assigned to HCIII were present on survey day

52% of households say that staff are always at work

10% of households report that staff are rarely at work

Drug

Availability

42% of facilities had missing records for at least one drug

29% of health facilities had zero stock outs of the six tracer drugs in the

previous 3 months (based on HCs with available records)

82% of households reported that they received drugs on their last visit

47% of households report that they receive information when drugs are de-

livered to the health centre – mostly by reports from other community mem-

bers

11% of households report that drugs are always available

22% of households report that drugs are rarely available

Minimum drug storage conditions were partially met in most health centres,

but storage of drugs on the floor was observed in 29% of health centres

Community

Structures

&

Accountability

Mechanisms

66% of health centre respondents said that facility issues had been dis-

cussed at the most recent local council meeting

8% of health centre respondents could name two or more roles of the HUMC

4% of households said that they received information from the HUMC in the

past 12 months

48% reported that a VHT had visited their home within the past 12 months

Health

Outcomes

111 children (out of 1,000 live births) under the age of 5 died in the 12

months prior to the survey date

33% of health centres had records of live births and maternal deaths for the

12 months prior to the survey date


I. Research Overview

Health care delivery at the local level is weak in many developing countries. In many cases, citi-

zens have little information on how much health programming is actually being provided and al-

most no basis of comparing what they can observe with what they are supposed to be receiving.

They also have little sense of what they might do with the information they may have to improve

the quality of local health service delivery. Furthermore, frontline health providers themselves

may have little sense of how their performance, and the health of the community they serve,

compares to that of other health facilities and communities.

This project constitutes a scaled up replication of the extremely successful ―Power to the People‖

intervention (henceforth P2P) evaluated by Martina Björkman and Jakob Svensson (Björkman and

Svensson, 2009), which has served as a model for GOAL Uganda’s ACT Health (Accountability Can

Transform Health) programme. The P2P intervention aimed to overcome these information prob-

lems and to aid citizens in monitoring, and working with, their local health care providers to im-

prove the quality of care. The P2P intervention was evaluated using a randomised impact as-

sessment in Uganda. The results were striking: infant weights increased in treatment communi-

ties; under-5 mortality declined by 33%; immunisation rates rose; waiting times at clinics fell;

staff absenteeism dropped; and communities became more engaged and monitored clinics more

extensively. Given these extremely large reported effects, there has been strong interest in test-

ing whether the P2P findings replicate at a larger scale.

The objective of the ACT Health impact assessment is twofold. The first goal is to test whether

P2P replicates. The second goal is to figure out which part of the highly complex P2P intervention

may have been responsible for its strong results. To do this, we break the P2P programme into

two of its principal components: 1) the provision of information about health delivery quality to

citizens and clinic staff and the mobilisation of these actors in light of this information, and 2) the

holding of interface meetings between community members and clinic staff in which the action

plans they each developed could be discussed and coordinated. We then randomise which health

facilities (and associated catchment areas) receive which parts of the treatment (or, in some cas-

es, both together, as in the original P2P programme). This allows us to compare outcomes in the

units that received each treatment (or combination) and learn something about the relative power

of each component. Apart from this small departure from the P2P study, GOAL Uganda’s ACT

Health intervention mirrors the P2P intervention strategy as closely as possible. This includes

questionnaire design, the design of the report cards that summarise information about health fa-

cility-level performance, the organisation of interface meetings, the creation of a joint action plan,

and the timing of 6-month follow-up dialogues in treated communities.1

Baseline data collection was completed between September and December 2014 and included vis-

its to 377 health centres and over 18,000 households, a sample 11.5% greater than initially

planned.2 The survey was conducted in ten local languages with the help of a total of 279 field

staff. Data from the survey was cleaned and turned into health centre specific report cards for

use by the implementing partners within two weeks of collection. The following report describes

the research design and procedures used for data collection and summarises key findings from

the baseline survey. We conclude by discussing next steps.

1 The differences between the P2P and ACT interventions are summarised in Figure 3 (page 14 - 15 below). 2 There were originally 338 health centres in the sample, yet after the district exchange increased to 384 health centres. During data collection, several HCs were dropped because they did not meet the study criteria. The final sample size is 377 HCs, an 11.5% increase from the original sample size.


II. Research Design and Intervention

Health System Context in Uganda

Understanding the changes within the Ugandan health system policy and service delivery over the

past 10 years following the Power to the People study is essential to contextually interpreting the

baseline and midline findings of the ACT Health study. Areas in which changes occur are outlined

below and will include more detail in the post-midline report.

1. Health care service delivery structure

Services are offered at National Referral Hospitals at the national level, Regional Referral Hospi-

tals at the regional level, general hospitals and HC IVs at the district level, HCIIIs at the sub-

county level, HC IIs at the parish level.

2. Update of Uganda National Minimum Health Care Package3

The National Health Policy I was the standard in place between 1999 and 2009, and the second

national policy was published for 2010 to 2015. Major changes includes the mandate of additional

services centred around care for patients with HIV/AIDS and providing medicine for the Preven-

tion of Mother-to-Child Transmission (PMTCT).

3. Drug delivery to the health centre

Drug delivery has been largely standardised through the contracting of National Medical Stores as

the official supplier for government facilities. In 2011, MOH shifted from a ―pull system’’ where-

by health centres were to have made requisitions directly from the District Health Office (DHO),

to a ―push system‖ whereby the National Medical Stores and Joint Medical Stores put together

standard packages of drugs (essential medicines kit) for each health facility for distribution. This

system is applied only at lower health facilities (II’s and III’s) while the pull is applied at HCIV and

above. The MoH also launched the “Last mile” an initiative to deliver medicines directly to facili-

ties (rather than deliver to Districts for the onward distribution to lower level facilities) was initi-

ated via the National Medical Stores –In addition, the drugs are now labelled with a ―UG‖ sign to

indicate that they are supposed to be given out for free in government facilities and are not to be

sold. These changes were made to reduce stock-outs caused by slow planning and requisitions.

4. Community health structures (VHTs, HUMC)

First introduced in 2001, the Village Health Team (VHT), the Uganda MOH community health

worker programme has also been refined. The inclusion of Health Unit Management Committee

structures in the national community health monitoring structure was designed to communities

more opportunities to participate in local monitoring of the health care sector.

5. MOH Data collection and analysis (HMIS)

The Ministry of Health has continued to update and improve the way that the Health Management

Information System (HMIS) is used to collect data at health centres and how the data is used at a

district and national level. Most recent updates to HMIS were in August 2010.

3 Uganda Ministry of Health. ―The Second National Health Policy.‖ July 2010.

http://www.unicef.org/uganda/The_Second_National_Health_Policy.pdf

http://www.unicef.org/uganda/The_Second_National_Health_Policy.pdf


6. General decentralisation of district governance structures

Changes in the local governance structures in Uganda also influence the supervisory structures

within the health care system and the authority held by these institutions. Under the under the

Fiscal Decentralisation strategy, changes have also been made to health sector financing mecha-

nisms. The Primary Health Care (PHC) grants are made to districts to finance the key program

areas in the Uganda Minimum Health Care Package (UNMHCP). Initially, these funds were dis-

bursed to Health sub districts (HSD) then to the Health facility, however in 2009 changes were

made, all the funds are now from the District direct to the individual health units, and managed

by the health facility in charge. Previously funds for HCII and HCIII were accounted by the HSD in

charge.

7. Increased stability

Since the mid 1980’s, areas in northern Uganda have experienced political unrest and periods of

armed conflict, resulting in widespread insecurity, large populations of internally-displaced people

and refugees, high levels of poverty and a greater risk of contracting HIV/AIDs.4 This region has

largely stabilised in the past decade, shifting the focus from emergency relief to post-conflict de-

velopment and infrastructure strengthening. The districts included within the ACT Health study

most affected by this change are those located in the North region (Agago, Apac, Gulu, Kitgum,

Lamwo Lira and Pader) as well as the district of Bundibugyo located along the border of the Dem-

ocratic Republic of Congo.

8. Expansion of accountability programmes in Uganda

In the years since P2P was implemented, there has been an influx of funds for social accountabil-

ity and advocacy in health (and other sectors) in Uganda. A number of international and Ugandan

civil society organisations have been implementing various social accountability approaches and

methodologies at various scales.

Study Design

The theory of change underlying the original P2P intervention is simple: service delivery can be

improved by empowering citizens to monitor service providers and hold them accountable. GOAL

built from this P2P basic theory of change and the positive results measured from the P2P inter-

vention and further theorised that the specific methodology affects not only service delivery, but

health-seeking behaviours of community members.

The P2P intervention aims to achieve this end by collecting information about the quality of ser-

vices being provided at rural health centres, both in absolute terms and relative to the perfor-

mance of other district health facilities, and firstly distributing this information to members of the

community that these health centres serve. The provision of this information seeks to solve the

monitoring problem that undermines the ability of citizens to hold service providers and the politi-

cians who oversee them accountable for poor performance (Besley 2006; Fearon 1999; Ferejohn

1986). Mobilising citizens in light of this information—a second key aspect to the principal-agent

problem—is addressed by the additional components of the intervention, which goes beyond mere

information delivery in three important respects:

4 Uganda Ministry of Finance, Planning and Economic Development. Post-conflict Reconstruction: The Case of Northern

Uganda. April 2003. http://siteresources.worldbank.org/UGANDAEXTN/Resources/CG2003.pdf

http://siteresources.worldbank.org/UGANDAEXTN/Resources/CG2003.pdf


1) Information is provided both to community members and health facility staff.

This provides staff with knowledge about how its performance compares to other district

facilities and creates common knowledge among citizens. The information in the project is

unique in that it provides client / community member observations based on their direct

experiences with each health facility. This is objective information that health facility staff

would not otherwise have. Similarly, the Citizen Report Card includes information from the

Health Management Information System (HMIS) and additional information based on in-

terviews with health facility staff and observations. This information would also not have

been widely available to community members.

2) Simply providing information may not be enough (Lieberman et al 2014), howev-

er in order for community members to act on this knowledge, they must view this

as their responsibility, know what to do and have the sense of efficacy to believe in their

potential impact as well as believe in others in the community. The mobilisation meetings

target overcoming these barriers by the development of community action plan s that fa-

cilitate the creation of a specific delegated tasks to bring change.

3) The clinic staff meeting with community representatives to discuss how to col-

laboratively improve the quality of care is hypothesised to improve accountability by

breaking down status hierarchies that may prevent citizens from making demands on

health care providers. It also puts community members in a better position to ascertain

whether the service delivery shortfalls stem from weak effort on the part of clinic staff (in

which case pressure for improvements is appropriate) or from factors outside the staff’s

control.

As noted, the first question to be answered by the impact assessment is whether the ACT Health

intervention can deliver similar effects as the P2P intervention on both health service provision

and citizen mobilisation in a larger sample of health facilities and their respective catchment are-

as. The original P2P study was carried out in just 50 units; the ACT Health study is being carried

out in 377 units. The second question is which aspect of the P2P intervention is ―doing the work‖

in generating these effects. ACT Health’s factorial design (described further below) will allow us

to learn how much of the impact is influenced by the provision of health information compared to

and combined with the meetings between health clinic staff (service providers) and community

members (the clients).

Beyond these two meta-questions, the project should also help us answer the following:

Under what conditions (that is, in what sorts of communities) does the provision of infor-

mation to citizens and the development of action plans lead to increased bottom-up moni-

toring of health care delivery?5

For what types of citizens is the improvement in health outcomes most marked?

Which particular health outcomes are most strongly affected by the intervention?

For what types of citizens does the encouragement to monitor health care providers have

the strongest impact?

What are the longer-term effects of the P2P intervention (or its parts)?

5 For example, in a follow-up paper, Björkman and Svensson (2010) report that their treatment effects are stronger in—and, in fact, are driven entirely by—more the ethnically homogeneous communities in their sample. We will have a much larger set of communities in which to test the robustness of this finding.


The P2P intervention contains three key elements:

1) Information: The creation of Citizen Report Cards (CRCs) shared with frontline health

providers and communities.

2) Mobilisation: Development of action plans by the health providers or by community

members in light of this information.

3) Interface: The attendance of interface meetings between communities and clinic staff in-

cluding the creation of a collaboration action plan, or ―social contract.‖ This plan is not

necessarily dependent on the information.

The ACT Health study combines the information and mobilisation components into one treatment

group and the third interface into another treatment group in order to test their independent and

combined impact. Finally, both information and mobilisation and interface treatments are includ-

ed together in the full programme treatment group, which mirrors P2P most closely. The health

centres and their catchment areas were assigned one of the following treatment groups depicted

below in Figure 1.

Figure 1: ACT Health Treatment Groups

T2: Interface meetings are held between commu-

nity and health facility staff

No (T2=0) Yes (T2=1)

T1: Report card infor-mation is reported sepa-

rately to community and health facility staff and separate action plans are developed

No (T1=0)

A1 Control

A2 Interface Only

Yes (T1=1)

A3 Information and Mobili-

sation Only

A4 P2P Replication

Information and Mobilisation + Interface

Power Calculations

The original P2P study itself had relatively weak power, operating with just 50 units at the level of

the randomisation. Thus, results that are significant tend to be very large in magnitude and even

large results are only weakly significant. The headline health outcome result of a 33 percent drop

in child mortality is not in fact significant at the conventional 5% level. As we explain below, our

study is much more highly powered—both for the investigation of the impact of the main compo-

nents and for the replication of the full P2P intervention itself.6

Power calculations were conducted using the Optimal Design software. Due to the factorial ex-

perimental design, power was assessed for two types of questions including if the study is suita-

bly calibrated to detect 1) main effects (the main effect of T1 and T2) as well as 2) partial effects

– (interactive effects of T1 and T2). The inference for the main effects compares entire rows and

tables of Figure 1 above, while the partial compares individual cells. We also present power cal-

culations using two distinct levels of analysis: both the individual level (clustered by clinic catch-

ment area), and the clinic level (clustered by district), thus presenting four different calculations:

main-individual, main-clinic, partial-individual, and partial-clinic. We set the number of sampled

households per health centre to 40, which is the appropriately powered sample size given the as-

sumed effect size and intra-cluster correlation.

6 The detailed description of how power calculations were conducted can be found on page 13 of the Inception Report.


III. Intervention Description

Intervention Description In the interest of faithfully replicating the P2P study, the programme was designed to match the

P2P protocols as closely as possible. As noted, the P2P intervention involved providing infor-

mation to citizens about the quality of health care at their local health facility and working with

them to inform them of their rights and entitlements and to develop an action plan in light of this

information.

ACT Health was designed to collaborate with government structures like health workers, village

health teams (VHTs), health unit management committees (HUMCs) and the District Health Office

(DHO) to support active community engagement and participation in health services. GOAL’s

basic theory of change is that enhancing the state-society space (citizen participation and collec-

tive voice) will affect health services and health outcomes through improved:

Responsibility of individual community members and households (as observed in health-

seeking behaviour)

Responsiveness of health workers (in relation to effective use of resources and adher-

ence to Ministry of Health standards for service delivery)

Relationships between community and health workers (better understanding of each

other’s constraints, experiences and attitudes)

Improved responsibility, responsiveness and relationships are encouraged through various combi-

nations of activities depending on the RCT treatment group. The combination of these activities,

which are in many regards similar to the Power to the People intervention should enable us to

better understand the relative importance of 1) providing objective information through the crea-

tion and sharing of Citizen Report Cards and 2) the importance of the interface meeting, or the

space for health centre staff and community representatives to agree on solutions to their chal-

lenges. GOAL provides quality assurance through structured observations of programme activi-

ties and maintains a database for the analysis of action plans developed and implementation pro-

gress during six-monthly follow-up activities.

Intervention – Illustrative Details

Prior to any activities being implemented at the community level, the programme was launched at

a national level and introduced at a district level. Community-based activities commenced with

mobilisation activities including meeting with health centre staff and Village Health Team (VHT)

members and local leaders to explain the basic details of the programme. Health centre staff

then agree to host meetings and the VHTs and Local Councillors mobilise a diverse array of com-

munity participants. Community members are mobilised to ensure that representatives of differ-

ent perspectives (male/female, young/old, high/low income, etc.) are present. This is to ensure

that the meetings are not so large that they become too difficult to facilitate and or stimulate

meaningful discussions.

Based on a piloting of the ACT Health programme in one district (with funding from Irish Aid),

GOAL refined all tools and methods for implementing the programme. The structure and content

for each level of meeting (health centre, community and interface) was codified in procedure

manuals used in staff training and provided to implementation teams (see full treatment proce-

dure manual in Appendix 6). Depending on the assigned treatment group, the actual content of


the meetings is slightly different but the principles of participatory facilitation remain constant.7

To view a sample of the CRC, see Appendix 6.

Repeat engagements and follow-up to review the joint social contract are helpful to institutional-

ise the process. The half-day follow-up meetings every six months for community members and

health workers enable participants to track the implementation of the action plan, determine new

areas of concern, and come up with a new set of recommendations for improvement of local

health services. GOAL estimates that each community will have four (4) or five (5) follow-up

meetings in the project lifespan.

The programme also includes district and national level engagement (people-centred advocacy) to

address cross-cutting issues at a higher level than the intervention HC. The strategy for this is

still under development, and GOAL will ensure that the strategy and practices do not affect the

RCT study.

P2P and ACT Health Intervention Comparison

GOAL was established in Uganda in 1979

and works in emergency and recovery

programmes including livelihoods, water

and sanitation, behaviour change with an

increasing focus on health programmes.8

GOAL began implementing the ACT Health

programme in 2012 through a piloting

exercise motivated by the success of the

Power to the People intervention. The

pilot initiated discussions regarding a

larger scale implementation, building on

DFID’s commitment to funding social ac-

countability programmes, IPA’s expertise

in executing randomised impact assess-

ments and GOAL’s well-established pro-

grammes in Uganda.

GOAL Uganda is implementing the ACT

Health programme in partnership with the

following four Ugandan civil society or-

ganisations, each with an implementation

team composed of Officers and a Manager

that are responsible for implementing and

supporting programme activities.

Figure 2: Map ACT Health Intervention Districts

1. Coalition for Health Promotion and Social Development (HEPS – Uganda)

2. Friends of Christ Revival Ministries (FOC REV)

3. Multi-Community Based Development Initiative (MUCOBADI)

4. Kabarole Research & Resource Centre (KRC)

7 Table 1 in the Inception Report (page 3) offers a more detailed outline of the structure and general content of various

meetings for each treatment group. 8 ―GOAL Uganda: Building Resilience through Partnerships.‖ 2015. https://www.goalglobal.org/countries/uganda

https://www.goalglobal.org/countries/uganda


The ACT Health intervention closely replicates the P2P programme, however some differences in-

evitably exist given the different contexts since ACT Health is taking place ten years after P2P and

in a significantly larger number of units and districts. The main differences between the two pro-

grammes are outlined in Figure 3 below. We believe that these differences do not undermine

the comparability of the two interventions. At the same time, we will take them into account

when comparing the impact of the P2P and ACT programmes at a later stage.

Figure 3: P2P and ACT Health Intervention Comparison

Area Difference P2P Intervention ACT Health Intervention

Pro

gram

me I

nte

rven

tio

n D

esig

n

1. Number of programme

variations

Control

Intervention communities

Control

Treatment cell A2 Treatment cell A3 Treatment cell A4 (P2P replica-

tion)

2. Involvement of communi-ty-based organisations (CBOs)

Worked through 18 CBOs Work in consortium with 4 im-plementing partner organisations

3. Participant mobilisation and preparation time frame prior to implemen-tation activities

Several days

1 - 2 weeks

4. Location of community Meeting

Though it is not explicit, it implies that they were at a

community location

Meeting to be held at health fa-cility

5. Length of time of community meeting

2 half-days 1 half-day

6. Number of participants at

community dialogue meetings

150 community members 75 community members

7. Number of participants at interface meetings

Unclear, but implies less than 75 because participants were chosen at community meeting

Full programme interface: 27 community members (9 per vil-lage) vs. Interface only: 75 community members (25 per

village)

8. Participation of sub-county officials

The participation of sub-county officials is unclear

Sub-county chief, Community Development Officer (CDO) and Health Inspector invited to ob-serve

9. Announcement of 6 month follow-up

Unclear whether there was an announcement that there would be a 6 month follow up

Announced at the end of meeting that there will be a 6 month fol-low-up

R

esearch

stu

dy

desig

n

10. Survey administration Paper-based surveys utilized Surveys administered using tab-lets and web-based platform

11. Districts included in study 9 districts 16 districts

12. HC sample inclusion crite-ria

- Sampled across various re-gions -Included only ―rural‖ HCs (definition unclear) - HC IIIs only

- Government-funded - No security concerns - Maps available

- Sampled across various regions - Included all HCs in study dis-tricts - HC IIs and HCIIIs - Government-funded

- Functional HC


Area Difference P2P Intervention ACT Health Intervention

- 5 km catchment area lies outside of administrative bor-

ders

13. HC catchment area defini-tion

Defined as 5km radius around each HC

Included the nearest three vil-lages to each HC9

14. HC sample size 50 HCs (only HCIIIs) 377 HCs (HCIIs and HCIIIs)

15. HH sample Size A total of 5,000 households surveyed

More than 18,000 households surveyed (15,655 used in impact evaluation)

16. Secondary data sources used in HC surveys

- Monthly summaries - Drug stock cards - Outreach daily tally sheets

- NMS invoices - Issue vouchers - Daily patient registers - Maternity unit registers - Antenatal care register

- Family planning register

- Daily laboratory test register

- Health Information Manage-ment System (HMIS) monthly report

- Drug stock cards

Figure 1 above may be most interesting for an audience of technical researchers and it appears

in the Inception Report. The figure below is used by programme implementation teams to demon-

strate components of different treatment cells which are referred to in implementation as ―proce-

dures.‖

Figure 4: Programme Procedure Components

Data

collection

Citizen

Report

Cards

Health

Centre

Staff

Dialogue

Community

Dialogue

Interface

Meeting for

HC Staff and

Community

Members

Follow-Up

Every Six

Months

Control YES NO NO NO NO NO

Separate Dialogues

(Information & Mobi-

lisation)

YES YES YES YES NO YES

Interface Only YES NO NO NO YES YES

Full Programme

(P2P Replication) YES YES YES YES YES YES

9 This is an oversimplification, as the catchment area was determined using QGIS Mapping Software and several steps

described in more detail in the Sampling Strategy section. Further justification is included for choosing a different catch-ment area definition than in P2P.


IV. Survey Design and Administration During the ACT Health baseline data collection, extensive surveys were conducted at each of the

377 health centres. In addition, household surveys were conducted in a minimum of 40 house-

holds in the catchment area served by the health centre. In all, surveys were collected from

more than 18,000 households.

Sampling Strategy

The ACT Health sampling strategy included the district, sub-county, health centre, health centre

village catchment area and household level as described below.

District

Sixteen districts spread across the Eastern, Western/Central and Northern Regions of Uganda are

included in the study. These districts were selected because of GOAL’s strong pre-existing rela-

tionships with local partner organisations who would facilitate the village meetings, meet with

clinic staff and implement other aspects of the intervention on the ground to ensure that districts

within various regions were represented.

Two of the originally selected sixteen districts proved to be too small to be viable because their

health facilities were too close to one another. This posed a problem because the study design

requires a one-to-one mapping of communities onto health facilities, and when health centres are

too close together their catchment areas overlap. In such situations, it is therefore unclear which

health facility is responsible for the health outcomes observed in the community and which health

facility household members are referring to when they answer questions about the quality of care

they have received at their facility. We therefore replaced these two small districts with two larg-

er ones that contained a larger number of health centres and greater distances between their

health centres.

Health centre level

Following a similar strategy as P2P, our unit of randomisation was the health centre and its

catchment area. All HCII and HCIII facilities in the sixteen study districts that were a) functional

and b) funded by the Ministry of Health were included in the sample.10 Government health centres

funded by the military or prison departments were not included, because their funding structures

differ from the Ministry of Health model. The randomization of health centres to the four treat-

ment groups was blocked at the district and health centre level. During the baseline data collec-

tion, five health centres were dropped from the study sample because they were found to be pri-

vate, military health centres or health centres of level IV. Figure 5 shows the distribution of

health centres to the four treatment groups as it resulted from the randomization strategy just

described. The sampling procedure yielded a total of 377 health centres (226 HCIIs and 151

HCIIIs).

10 One notable exception to this rule is that we dropped health centres that were less than 2.5 km apart or overlapped in the three closest villages in order to avoid ―spillover‖ between the different treatment group conditions, as described in greater detail below. This resulted in the exclusion of 20 health centres from the sample.


Figure 5: Original randomisation of health centres to treatment groups

Region / District

A4

P2P

Replication

A3

Information

& Mobilisa-

tion

A2

Interface

A1

Control

HC II HC III HC II HC III HC II

HC III HC II

HC III All HCs

Nort

h

Lira 2 2 2 2 2 2 2 2 16

Apac 4 2 3 3 4 2 4 3 25

Pader 3 2 3 3 3 2 4 3 23

Gulu 7 3 8 2 7 3 8 3 41

Lamwo 2 2 3 1 3 2 3 1 17

Kitgum 2 2 2 2 2 2 2 3 17

Agago 6 2 6 2 6 2 5 2 31

East

Katakwi 3 1 3 1 3 1 3 2 17

Bukedea 0 1 1 1 0 1 0 2 6

Manafwa 0 2 1 2 1 2 1 2 11

Tororo 7 3 7 4 6 4 7 4 42

West

/ C

en-

tral

Kabarole 4 5 4 4 4 5 3 4 33

Mubende 9 3 9 2 9 2 8 2 44

Nakaseke 3 1 2 1 3 1 2 1 14

Kibaale 4 4 3 4 4 4 3 4 30

Bundibugyo 2 2 3 1 3 2 3 1 17

Total 58 37 60 35 60 37 58 39 384

The original randomisation included 384 HCs. During the baseline data collection, five (5) health

centres were dropped from the study sample because they were found to be ineligible (two health

centres were private, one was military, one was faith-based and one health centre was a HCIV).

The affected districts were respectively Gulu, Lira, Bundibugyo, Nakaseke and Kitgum. Figure 6

shows the distribution of health centres included in the final study sample as it results after these

five health centres were dropped. The final number of health centres included in the study sample

is 379, however health centre baseline summary statistics are drawn from a sample of 377, due

to two (2) health centre surveys whose data was incorrectly saved on the enumeration tablets.

While midline data will still be collected in these health centres, analysis will be conducted taking

into account that baseline data for these two health centres is unknown.


Figure 6: Health centres by district, level and treatment group

Region / District

A4

P2P

Replication

A3

Information

& Mobilisa-

tion

A2

Interface

A1

Control

HC II HC III HC II HC III HC II HC III HC II HC III

All

HCs

Nort

h

Lira 2 2 2 1 2 2 2 2 15

Apac 4 2 3 3 4 2 4 3 25

Pader 3 2 3 3 3 2 4 3 23

Gulu 7 3 7 2 7 3 8 3 40

Lamwo 2 2 3 1 3 2 3 1 17

Kitgum 2 1 2 2 2 2 2 3 16

Agago 6 2 6 2 6 2 5 2 31

East

Katakwi 3 1 3 1 3 1 3 2 17

Bukedea 0 1 1 1 0 1 0 2 6

Manafwa 0 2 1 2 1 2 1 2 11

Tororo 7 3 7 4 6 4 7 4 42

West

/ C

en-

tral

Kabarole 4 5 4 4 4 5 3 4 33

Mubende 9 3 9 2 9 2 8 2 44

Nakaseke 3 1 2 1 3 1 1 1 13

Kibaale 4 4 3 4 4 4 3 4 30

Bundibugyo 2 2 3 0 3 2 3 1 16

Total 58 37 60 35 60 37 58 39 379

Health centre catchment area villages

Blocking health centre randomisation by facility type is important in the Ugandan context because

sub-county level facilities (HCIIIs in the parlance of Uganda’s health system) are slightly different

from the parish-level facilities (HCIIs) in regards to the staff, equipment and services offered.

Potentially more important from a project design standpoint is that the two types of facilities are

also formally linked hierarchically in terms of administrative oversight, with parish-level HCIIs

nested below sub-county-level HCIIIs (and HCIIIs, in turn, nested below county-level HC IVs).

Around each health centre a ―catchment area‖ was defined from which the households to be sur-

veyed were randomly sampled. This catchment area included three villages. The first village was

the one in which the health centre was located and the remaining two villages were selected as

the two closest villages, located in the same parish (HCII) or sub-county (HCIII) as the health

centre, measured by straight line distance from the health centre to the village centroid. Catch-

ment areas were determined according to this algorithm using QGIS mapping software, village-

level shape files provided by the Uganda Bureau of Statistics (UBOS), and GPS coordinates col-

lected by GOAL.11 Selecting contiguous villages presented fewer obstacles to overcoming collec-

11 Aside from two districts in which we were able to utilise GIS data from the Uganda Bureau of Statistics (UBOS) health

centre points


tive action problems in the participating communities and less of a risk of spillover or catchment

area village overlap where one catchment area receiving a particular intervention may interact

with or influence another that receives a different intervention. This becomes particularly prob-

lematic when treatment and control groups are too near in proximity because the control group

may realise they are not receiving the intervention, or the intervention effects may ―spill over‖

into the control areas.

If a village was selected in the catchment area of more than one health centre, the following two

step strategy was applied to prevent spillover. One health centre was dropped if 1) one or more

of the three nearest villages to a HC overlapped with a neighbouring HC village or 2) if two health

centres were closer than 2.5km to one another. Determining which health centre to drop was

based on creating the greatest distance between HCs and if all else was considered equal, drop-

ping HCIIs rather than HCIIIs because less HCIIIs are represented in the sample. A total of 20

HCs were dropped using this strategy.

There were two exceptions when three villages were not included in the health centre catchment

area. Firstly, if only two villages were located within a parish or sub-county, only these two vil-

lages would be included in order to adhere to the parish and sub-county rule. Secondly, if a vil-

lage had been split into smaller subunit (typically the village subunit would be named with A and

B or 1 and 2) and field teams confirmed that this occurred a) within the last 12 months or b) and

had not been formally recognised by the appointment of local council, then each of these villages

were included and considered as a single village.

Household listing

In order to create a representative, random sub-sample of households in a catchment area,

households were first mapped using a village-level administrative listing conducted in each of the

three villages selected around the health centre. This involved recording an updated village

household list with the support of the Local Chairperson 1 (LC1) village, Village Health Team

members (VHT), Health Unit Management Committee Members (HUMC) and other local leaders.

Households with a pregnancy or any children under five years old were indicated and if a child

was four years of age, this information was verified by walking with a knowledgeable person from

the village from house to house to ensure that the child had not yet reached five years of age.

The listing protocol is included in Appendix 2.

Random assignment and random sampling

Sampled health centres were randomly assigned to one of the four treatment groups (see Figure

1), with the random assignment blocked by district and health facility level. In each health centre

catchment area, 40 households were randomly sampled for the full household survey. In health

centre catchment are assigned to receive Treatment 1 (―information and mobilisation + inter-

face‖) or Treatment 2 (―information and mobilisation‖) an additional 15 households were sur-

veyed using an abbreviated household survey. The purpose of collecting additional short surveys

in areas where findings would later be disseminated using Citizen Report Cards was to a) allow for

greater community buy-in and participation and b) include a larger sample for CRC calculations.

Citizen Report Card Only data from the 40 long household surveys per catchment area are in-

cluded in the baseline report, as this represents the data that will be used for the impact assess-

ment. All households who participated in the full household survey will be resurveyed at midline

and endline.


Figure 7 displays the number of surveys collected per health centre and overall. A total of

18,090 household surveys were collected, and with the 2,435 short surveys excluded, 15,655

surveys from 377 health centre catchment areas are included in this report.

Figure 7: Number of household surveys by type

Per HC

Long 40 Note: For health centres assigned to treatment groups receiving ―in-formation‖ in the form of the Citi-zen Report Card, a total of 55 sur-veys were collected. In the Inter-face treatment group and Control group, only 40 long surveys were

collected.

Short 15

Total 55

Overall

Long 15,457

Short 2,633

Total 18,090

Survey Tools

The Household Survey was administered to households that met the study inclusion criteria of

having a pregnancy or any children under the age of five. The surveys collected information

about household health seeking behaviour, experience at the health centre that serves the

catchment area, and maternal and child health. The primary respondent was the household

member who had visited the health centre most recently within the past 12 months. In addition,

an abbreviated (―short‖) survey was administered to another 15 households in units assigned to

Treatment groups 1 and 2, which required the production of the Citizen Report Card. All surveys

(―long‖ and ―short‖) included an Anthropometric Survey component in which we recorded the

weight, height and middle-upper arm circumference (MUAC) of each child under the age of five.

Health centre surveys were administered to the most senior health centre staff member at each

clinic, preferably the In-Charge. If unavailable, the next most highly ranked health centre staff

member according to the years of experience at the clinic was interviewed. A brief Health Cen-

tre Mobilisation Survey was administered by the team member responsible for scheduling the

main survey. Since this survey was unannounced, it provided an opportunity for the collection of

information about staff attendance, cleanliness, wait times and other clinic characteristics before

the staff was aware that a survey was going to take place. The main Health Centre Staff Sur-

vey collected information about the variety and quality of health services provided, utilisation

rates, staff structure and perceptions, funding mechanisms and drug stock-outs. Secondary data

was also collected from the Health Management Information System (HMIS) monthly

forms and Drug Stock Cards on file at the health facility. Physical checks of drug stocks and

storage conditions were also conducted to verify the health centre records. Secondary data

sources were also used in P2P (see Figure 3). These records were used to prevent introducing

health centre staff bias and over reporting. The survey tools were based on the original P2P sur-

veys, the GOAL pilot survey tools, as well as Uganda Ministry of Health policies and standards.


V. Data Collection, Organisation and Challenges The data collection occurred over five months from 18 August 2015 to 16 December 2015 (total-

ling 107 survey days). To train enumerators, we conducted three trainings, one within each re-

gion, each lasting eight to nine days. More details about the data collection timeline are included

in Appendix 5. Data collection began in the East with both the Research Coordinator and Re-

search Associate. Upon the completion of the data collection in the East region, the Research Co-

ordinator began overseeing data collection in the North and the Research Associate in the West

and Central regions, operating simultaneously to more efficiently complete the data collection.

Team Structure

The ACT Health team was led by Research Coordinator, Paola Elice, and Research Associate,

Laura Schmucker with guidance from Principal Investigators Dan Posner, Doug Parkerson and Pia

Raffler alongside Research Manager Kyle Holloway. Teams of 63 staff were recruited for the

North and West/Central Regions supervised by a Research Coordinator/Field Manager and Re-

search Associate/Field Manager team respectively. The East Region consisted of three teams, one

of 63 enumerators and two of 44, each supervised by a Research Associate/Field Manager team.

There were approximately 279 total staff recruited and the survey administered in 10 different

languages.

Each regional team was split into three smaller teams of 19 enumerators, whom were responsible

to collect all 120 household and anthropometric surveys required to complete the data collection

at each health centre each day. On average, 3.5 surveys were collected per enumerator per day.

Figure 1 displays the team structure. In the smaller teams that operated in the East region, there

were only two team leaders, as opposed to three.

Appendix 4 includes brief description of the roles and responsibilities of each field team position.

Data Management The P2P and ACT Health data collection are unique from other research studies in the sense that

the baseline data will not only be used as a means of comparison with the midline data, but it was

also used to produce the Citizen Report Cards that were shared with communities during the in-

tervention activities. Dissemination of baseline information directly to respondents, the frontline

service providers and the communities they serve, is unique, especially so soon after its collec-

tion. The IPA team has developed strict quality monitoring guidelines and internal review process-

es to ensure that survey development and subsequent data collection processes meet demanding

requirements regarding accuracy. This process begins with designing and piloting all survey tools

and extensive training of the enumeration team. Computer-Assisted Interviewing (CAI) was em-

ployed through the use of Samsung Galaxy Tab 4 tablets, selected because of their capability to

clearly display more answer choices and to ease usability among surveyors. The Open Data Kit

(ODK) based SurveyCTO platform was used to programme, administer, and host the data collect-

ed from electronic surveys. Following data collection each day, all surveys were uploaded to the

SurveyCTO’s cloud server.

The surveys were then downloaded the following day onto the RC/RA computers into folder en-

crypted using Boxcryptor where a set of high-frequency, statistical checks (HFCs) were conducted

to detect outliers, duplicate IDs or other logical inconsistencies in the survey data. The quality of

the data was also systematically verified through ―back-checking‖ (i.e. performing an audit by re-


surveying of a random 10% subset of individuals who were surveyed to ensure that responses

are consistent), which is done by a second, independent team of experienced surveyors. After

these initial checks were carried out, datasets were appended and merged and all variables nec-

essary to create the GOAL Citizen Report Cards were cleaned. An analysis file was created incor-

porating calculations and formatting that automatically generated the Citizen Report Cards in Ex-

cel.

This process from data collection to production of the CRCs was scheduled to take approximately

seven to ten days. Although the process often extended past the planned timeline at the begin-

ning of the data collection process, as the priority of ensuring that data collection protocol were in

place, this schedule was eventually adhered to after all data collection procedures were put in

place. IPA provided the data to GOAL, whose staff formatted and printed these for sharing with

targeted HC staff and communities (See Appendix 6).

Major Data Collection Challenges Inaccuracies in village administration listing

A number of issues associated with the village-level administration listing:

The health centre village catchment area selection relied heavily on the accuracy of the

QGIS village shape files shared by the Uganda Bureau of Statistics (UBOS). This source

proved to contain some errors, especially in the parish and sub-county that each village

was located in, the first criteria used to select the villages.

The GPS data for the health centres was collected by GOAL for all districts, aside from the

two that were added later from UBOS. Errors were found in the health centre location da-

ta from each source, however more issues arose within the UBOS dataset.

There were several scenarios where two or more villages within the same district had simi-

lar names, thus the listing was done in the incorrect village.

During the listing, the enumerator gathered together the most knowledgeable local lead-

ers, however not every village had an updated village roster and not all leaders were en-

gaged in creating a more updated list. In this case, the most knowledgeable representa-

tives were called together to reconstruct the list. If this was not possible, the traditional

listing method of walking through the village and mapping out the households was em-

ployed.

These concerns were dealt with by implementing checks conducted by mobilisers confirming that

the three villages within each catchment area were located within the same parish (for HCIIs) or

the same sub-county (for HCIIIs). Any villages found to not meet the criteria were dropped, and

then the appropriate villages were relisted prior to data collection. The parish and sub-county are

important administrative boundaries in Uganda’s decentralised structure.

Reaching households in peri-urban areas

While the ACT Health study was designed to operate in ―rural‖ areas, some villages considered

peri-urban12 including small towns or trader centres posed several challenges. In particular, local

officials and community members alike were less likely to know all village members in these areas

due to being more highly populated and the likelihood of shorter term rental homes. If respond-

12

Unlike P2P’s inclusion of only “rural” HCs, all health centres within each district meeting the study criteria were included in the ACT Health study. Thus, peri-urban refers to HCs located in or near medium-sized towns (20-100,000 people) such as Gulu town, Fort Portal or Mubende town.


ents were unable to be located, additional replacement households were randomly selected using

the listing database.

Poor transportation infrastructure

Areas that were very rural also posed their own challenges. Randomly selected households were

often far apart. In combination with poor road infrastructure and rainy season conditions, this

made collecting the target number of surveys challenging and time-consuming. In addition, the

large team of 65 staff could only find accommodation in a large enough town, thus often increas-

ing the distance from the more remote health centres. In these cases, enumerators were occa-

sionally allocated additional transport allowances to reach respondent households more quickly or

households were tracked.

Health centre staff presence on weekends

The data collection teams worked Monday through Saturday to conduct household and health

centre surveys. Staff absenteeism is an important indicator in the ACT Health study, however

surveys collected on Saturdays at health centres were found to misrepresent the number of staff

who regularly attend work. Thus, a re-survey for all health centres surveyed on Saturdays was

commissioned.

Tracking missing surveys

In order to adhere to the four-month timeline for the baseline data collection and successfully

meet the data collection target of more than 18,000 surveys, only up to one tracking visit was

budgeted for each household. If the respondent was not available on the day of the survey or on

the tracking day, the household was replaced with a household from a replacement list generated

during the randomisation. Days to track the anthropometric surveys had not been included in the

original timeline, however children were not always able to be measured on the day that the

household survey was collected. The solution included anthropometric survey tracking on Sun-

days and during December 2014 and January 2015, which effectively decreased the percentage of

missing anthropometric surveys from approximately 10% to 1%, albeit at increased cost.

Health facility records

As noted above, the survey included primary and secondary data sources. The secondary data

sources were largely standard records for the facility level – Health Management Information Sys-

tem records, drug stock cards and maternal death records. Numerous facilities had missing data

for one or more of the previous 12 months.


VI. Balance Checks Balance checks were conducted on variables that the P2P study selected to conduct balance

checks on. These checks seek to detect and significant differences between the averages for each

variable across the different treatment groups. Because the assignment of each health centre

catchment area was random, we assume that the pre-intervention averages would be similar.

Conducting this test prior to analysing midline data will allow for the clearest possible interpreta-

tion of the findings.

An extensive table comparing all differences between treatment groups for all outcome variables

and variables that P2P ran balance checks on is included in Appendix 8. These include four vari-

ables from the health centre survey and two from the household survey, as indicated.

The balance checks utilised t-tests and the statistical significance of differences in averages be-

tween treatment groups was observed at the conventional level (alpha = 0.05). A p-value of 0.05

or smaller would indicate an imbalance that is statistically significant. The t-tests run confirm that

there are no statistically significant differences in the chosen variables between treatment groups.


VII. Descriptive Statistics

A. Overview

We collected a total of 18,090 surveys: 15,457 long household surveys and 2,633 short

household surveys across the catchment areas of 377 health centres (table 1). While the

data from all surveys was included in the Citizen Report Cards shared with communities,

only the long surveys are analysed for comparability between data collection points under

the ACT Health RCT and eventually with P2P findings.

Table 1: Number of household and health centre surveys collected per district, treatment

group and health centre level

District /

Treatment

group and HC

level

A4

P2P

Replication

A3

Information

& Mobilisa-

tion

A2

Inter-

face

A1

Control

Total #

of HH

surveys

HC

II

HC

III

Total # of

HC surveys

No

rth

Lira 135 164 157 154 610 6 9 15

Apac 245 246 241 284 1016 15 10 25

Pader 208 254 200 279 941 12 11 23

Gulu 418 381 410 445 1654 27 13 40

Lamwo 171 169 201 160 701 11 6 17

Kitgum 121 165 160 201 647 8 8 16

Agago 326 327 326 285 1264 23 8 31

East

Katakwi 154 161 160 195 670 11 5 16

Bukedea 38 76 37 84 235 1 5 6

Manafwa 83 125 118 120 446 2 9 11

Tororo 403 443 398 443 1687 27 15 42

West/

Cen

tral

Kabarole 381 340 359 283 1363 14 19 33

Mubende 504 455 440 406 1805 34 9 43

Nakaseke 163 125 162 82 532 9 4 13

Kibaale 336 289 321 281 1227 15 15 30

Bundibugyo 170 128 201 160 659 11 5 16

Total 3856 3848 3891 3862 15457 226 151 377 Source: Household survey, Health Centre Staff Survey Note: Household surveys were collected in the three outlined regions. Each health centre and its respective health centre catchment area was randomly assigned to a treatment group: A4: Full Program, A3: Information and Mobilization, A2: Interface only, A1: Control.

The baseline generated a large amount of data, which is presented thematically (rights &

responsibilities, service availability & facility resources, user experiences, ANC & deliveries,

family planning, fees, staffing, drugs, community structures & accountability and finally

health impact indicators). Each thematic section juxtaposes responses from health centres

and households. Access to information is a running theme through each section. Our aim is

to present the complex supply and demand side dimensions and rich information gathered

on each thematic area so that we can understand each challenge holistically.


B. Rights & Responsibilities

Each respondent was asked to name as many patient health rights and responsibilities pos-

sible according to the Ministry of Health Patient’s Charter1. The survey included a total of

10 patient rights and three responsibilities. All rights and responsibilities are displayed in

the following table, and those that were included in the survey are indicated in bold.

Table 2: Rights & Responsibilities

Patient rights

1. Right to medical care 11. Medical care without consent

2. Prohibition of discrimination 12. Refusal of treatment

3. Participation in decision-making 13. Be referred for a second opinion

4. A healthy and safe environment 14. Continuity of care

5. Proper medical care 15. Confidentiality and privacy

6. Be treated by a named health centre

Provider

16. The patient’s right to medical infor-

mation

7. Training and research 17. Custody of medical records

8. Right to safety and security 18. Medical records retention

9. Receiving visitors 19. Right to redress

10. Informed consent

Responsibilities

Patient responsibilities Health worker responsibilities

1. Provision of information 1. Penalties

2. Compliance with instruction 2. Duration of admission

3. Refusal of treatment 3. Comments, suggestions and complaints

4. Respect and consideration

5. Will (in cases of death)

Comparing the number of rights and responsibilities named by health centre staff and

household members shows that health centre staff were more familiar with the charter and

the patient rights and responsibilities than household members.

Table 3: Knowledge of the patient rights and responsibilities

Patient rights Patient responsibilities

Household says HC says Household says HC says

Could not name any 35% 2% 27% 5%

Named 1 38% 3% 57% 34%

Named 2 18% 20% 15% 51%

Named 3 7% 40% 1% 9%

Named 4 1% 21% N/A N/A

Named 5 or more 0% 13% N/A N/A Source: Household Survey, Health Centre Staff Survey Note: There were 9 possible rights and 3 possible responsibilities listed in the survey an-

swer choices.


Table 4: Three most frequently named patient rights

Household says

1. Right to proper medical care 40%

2. Right to receive free medical care 35%

3. Right to no discrimination (race, religion, sex, age, disability, etc...) 8%

HC says

1. Right to proper medical care 80%

2. Right to receive adequate information in order to be able to give in-

formed consent 68%

3. Right to receive free medical care 64%

Source: Household Survey, Health Centre Staff Survey Note: All rights and responsibilities outlined in the Uganda MOH Patient’s Charter are displayed in Table 2 and those that were included as answer choices in the survey tools are indicated in bold.

The two tables below highlights that 60% of health centres report that the do share infor-

mation about health rights and responsibilities to patients. Of these, the majority (96%)

report sharing this verbally with patients. This indicates that community members may be

most likely to receive this information at the health facility, which contrasts slightly with ta-

ble 5 which shows that community members report hearing this primarily from other pa-

tients.

Table 5: How households report receiving information about rights & responsibil-

ities

HCII HCIII All HCs

Information on rights and responsibilities is disseminated to

the community 60% 60% 60%

Information on rights and responsibilities is disseminated to the community from

the following sources:

Spread verbally by staff and patients 96% 96% 96%

Through local councillors, headmen, religious leaders or

other community leaders 19% 22% 20%

Through the HUMC 8% 4% 7%

Posted outside the clinic 1% 6% 3%

Posted in the waiting room 1% 4% 3%

Through schools 2% 1% 2%

Posted in the villages 1% 0% 0%

Other 2% 7% 4%

Source: Household Survey Note: Among health centres that reported disseminating information on patient rights and responsi-bilities according to the Ministry of Health Patient's Charter, the methods in which this information

was disseminated was recorded. More than one method could be recorded for each health centre.


Table 6: Health centre staff described mechanisms for dissemination of infor-

mation about rights & responsibilities

HCII HCIII All HCs

HC says that they provide information to the commu-

nity on their rights and responsibilities 60% 59% 60%

How is information on patients’ rights and responsibilities provided publicly to

communities?

Posted outside clinic 18% 41% 27%

Posted in the waiting room 11% 28% 18%

Posted in the villages 3% 5% 4%

Spread verbally by patients 87% 92% 89%

Through the HUMC 11% 14% 14%

The local councillors, headmen or religious community

leaders 47% 54% 50%

Through schools 5% 6% 6%

Other 0% 1% 1%

Through media 4% 1% 4%

Through outreaches 4% 4% 5%

Source: Health Centre Staff Survey Note: Among health centre staff who report that they provide information to the community on their rights and responsibilities, they were asked how this information was shared.


C. Service Availability & Health Facility Resources

The Uganda Ministry of Health outlines what services are mandatory to be offered at each

level of health centre. Some more advanced services are only required to be provided at

HCIIIs, while other services are required to be provided at both. Some services that are not

required to be provided at health centre IIs for example are still offered including lab ser-

vices, HIV testing and counselling and oftentimes deliveries. Among the services that are

required at both levels, outpatient care, simple family planning services, family planning ed-

ucation, general health education and immunisation ranked the most highly. Prevention of

Mother-to-Child-Transmission of HIV (PMTCT) was the required service provided least fre-

quently.

Table 7: Services provided at the health centre

UNMHCP Services

% of HCII

providing

services

% of HCIII

providing

services

% of all

HCs provid-

ing services

HC III

Required

Services

Lab services 84% 99% 90%

HIV counselling and testing (HCT) 59% 100% 76%

Delivery 41% 92% 62%

Anti-retroviral therapy (ART) 6% 85% 38%

Family planning methods (ad-

vanced) 0% 87% 35%

HC II &

HCIII

Required

Services

Family planning methods (simple) 99% 100% 99%

Outpatient care 99% 100% 99%

Health education (at HC) 99% 99% 99%

Family planning education 99% 100% 99%

Immunisation 93% 100% 96%

Health Outreach (villages) 91% 100% 95%

Antenatal care 70% 99% 81%

Prevention of Mother to Child

Transmission (PMTCT) 38% 97% 62%

Additional

services

Growth monitoring 69% 92% 78%

Inpatient care 9% 69% 33%

VHT training 23% 40% 30%

Other services 11% 30% 19%

Dental services 1% 3% 2%

TBA training 0% 1% 1% Source: Health Centre Staff Survey Note: This information is self-reported by the health centre staff, thus has the potential to be biased

towards the health centre adhering to the MOH standards. The services are listed as those that the MOH requires at HCIIIs only, services that should be provided at both HCII and HCIIIs and services that are not required by either.

The average number of patients that visited the health centre per month for outpatient

care, antenatal care, delivery or family planning services is shown in table 8. The average

number of patients visiting HCIIIs appears to be greater because the HCIIIs generally have

larger catchment areas, receive referral patients from surrounding HCIIs and are often built


in more populated areas. Since there are more HCIIs than HCIIIs in this sample (which is

illustrative of the general situation in Uganda), overall HCIIs do account for more contacts

with the MoH service delivery infrastructure.

Table 8: Average number of patients per month

Type of service / HC level HCII HCIII All HCs

Male outpatients < 5 years old 72 123 92

Female outpatients < 5 years old 81 136 103

Male outpatients > 5 years old 151 258 194

Female outpatients > 5 years old 285 532 383

ANC patients 30 135 77

Delivery patients 5 22 13

Family planning patients (new) 27 41 33

Family planning patients (revisit) 23 33 27

Total (average OPD) 674 1280 922

Source: Health Management Information System (HMIS) monthly forms

Note: Outpatients includes any general service offered to patients who are not admitted. Deliveries includes all births occurring at the health centre. The data on outpatient is miss-ing for 4 health centres, ANC data is missing for 41 health centres, delivery data is missing

for 85 health centres and the family planning data is missing for 5 health centres.

When asked at each health facility about their source of water and the availability of a sepa-

rate maternity ward for deliveries, the following was recorded. These measures were in-

cluded in the P2P study as metrics of health facility quality. For information on drug storage

conditions, please see below ―Drug Availability‖ (section I).

Table 9: Health center infrastructure

Infrastructure / HC level HC II HC III All HCs

Safe water source 58% 69% 63%

Electricity 62% 87% 72%

Toilets for patients 2% 5% 3%

Placenta pit N/A 91% 91%

Maternity ward N/A 94% 94%

Staff houses 72% 94% 81%

Pharmacy 84% 91% 87%

Disinfectant soap 83% 83% 83% Source: Health Center Staff Survey

Notes: Safe water sources are piped/tap water or bore-hole water. Electricity is either so-lar, grid or from a generator. Toilets for patients are not latrines. The maternity ward and the pharmacy need to be separate units to be classified as such.

Health centre IIs and IIIs receive funding from the Ministry of Health through District in the

form Primary Health Care funds. While much of the PHC fund is pre-allocated, facilities do

receive direct fund transfers (PHC grants) for some operating costs at the health facility.

These include wages for non-medical staff and facilitation of outreach activities. The average


amount received during the 12 months prior to the survey date is displayed below in Table

10.

Table 10: Average amount of Primary Health Care (PHC) grant received by

HCs in the past 12 months

HCII HCIII

UGX 1,737,355 UGX 12,133,535

GBP 403 GBP 2,817

USD 648 USD 4,523 Source: PHC vouchers

Note: The average exchange rate USD/UGX during the survey period (18 August 2014 - 19

December 2014) is 2683. The average exchange rate GBP/UGX in the same period is 4307.13

13

OANDA Historical Exchange Rates. Period Average. August 2014 – December 2015. http://www.oanda.com/currency/historical-rates/

http://www.oanda.com/currency/historical-rates/


D. User Experiences – Access to & Perceived Quality of Services

This section is organised to assist in understanding how households access services, make

decisions about where to seek health services and also to understand the general quality

experienced by households who visited their closest HCII or HCIII in the 12 months prior to

the survey. It is important to note that the ACT Health programme does not measure ―quali-

ty of care‖ through auditing of patient charts, or mechanisms that the MoH might use to au-

dit service quality. The section first explores access, presents perceptions of quality accord-

ing to users of the services.

Access to Services

A total of 94% of households surveyed reported that one or more family member had visit-

ed the closest health centre within the past 12 months to seek for health care for self or to

accompany a patient. The number of visits to each health care provider was recorded for

each household member. The greatest proportions of health care visits were to a govern-

ment health facility or closest HCII/HCIII (40%) and self-treatment (33%).

Table 11: Use patterns – health contacts reported by households

Health care provider / HC level HCII HCIII All HCs

Closest HCII or HCIII a 33% 34% 33%

Self-treatment b 32% 34% 33%

Private clinic c 14% 15% 15%

Other government health facility d 9% 5% 7%

Village Health Team e 6% 7% 7%

NGO clinic f 3% 3% 3%

Traditional healer g 2% 2% 2% Source: Household Survey

Note: The question "How many times did you seek health care at ... in the past 12 months?" was asked for all household members of the interviewed households (N = 15457). a The closest HCII/HCIII refers to each health centre included in the sample. b Self-treatment refers to household members visiting pharmacies and self-prescribing themselves medicines. c Private clinics include for-profit clinics. d Other government clinics could include HC II, III, IV or hospitals or facilities funded by the military or

police. e Village Health Team (VHT) members are community health workers. f NGO clinic includes both non-governmental and faith-based health facilities. g Traditional healers are defined as local "healers" whose practice is not based on modern medicine, but instead either herbal or spiritual remedies.

All households that reported visiting the health centre at least once in the 12 months before

the survey date were asked the reasons for visiting. All households were also asked whether

they visited other health care providers in the past 12 months and the reasons for doing so.

Tables 13, 14 and 15 display the survey findings related to reasons for health-seeking

choices. Overall availability of drugs consistently influences this decision-making while prox-


imity, cost, wait time and providing the needed services were also highlighted as important

factors.

Table 12: Reasons for visiting the closest HCII or HCIII

Reason/HC level HCII HCIII All HCs

Facility close to where I live/Only facility in my area 80% 75% 78%

Free treatment 39% 43% 41%

Availability of drugs 18% 21% 19%

Provide the services/treatments I needed 13% 19% 16%

Good quality health services 4% 6% 5%

Short waiting time 3% 2% 2%

Good staff attitude 2% 2% 2%

Staff is available 1% 1% 1%

Staff is well trained 1% 2% 1%

Referral to this facility 0% 1% 0%

Know health workers 0% 1% 0%

Health facility is clean 0% 1% 0%

Don't know 0% 0% 0%

Other 0% 0% 0% Source: Household Survey

Note: Respondents in the catchment area of the closest government HCII or HCIII were asked why they chose to visit for health care services.

The 6% of households that reported never visiting the health centre in the previous 12

months were also asked the reasons why they made this decision. While the 6% sample is

small, but the table below offers some indication of reasons why households preferred op-

tions other than their closest HCII or HCIII.

Table 13: Reasons for not visiting the closest HCII or HCIII


Lack of drugs at facility 39% 47% 41%

Long distance to facility 34% 17% 29%

Long waiting time 12% 26% 17%

Poor quality of services 14% 20% 16%

Don’t provide the services/treatments I needed 16% 16% 16%

Person has not been sick 10% 17% 12%

Poor staff attitude 9% 10% 9%

Staff is not available 6% 3% 5%

Don’t know/Can't remember 4% 5% 4%

Have never heard about this health facility 3% 2% 2%

Cannot afford payment 1% 2% 2%

Lack of cleanliness 1% 1% 1%

Staff not well trained 1% 0% 0%

Other 0% 0% 0% Source: Household Survey Note: All households that reported not visiting the health centre in the past 12 months were asked the reasons why they made this decision.


All respondents were asked if they had visited other health care providers in addition or in

place of the nearest HCII or HCIII their reasons are displayed in Table 14.

Table 14: Reasons for visiting other health care providers


Availability of drugs 55% 56% 56%

Provides the services/treatments I needed 37% 32% 35%

Referral to this facility 19% 20% 19%

Good quality health services 19% 19% 19%

Health facility ―X‖ was closed 10% 10% 10%

Short waiting time 8% 12% 9%

Facility close to where I live 8% 9% 8%

Free/inexpensive treatment 4% 5% 4%

Good staff attitude 3% 4% 3%

Not attended to at health facility X 2% 3% 3%

Staff is well trained 2% 2% 2%

This health facility is closer than health facility X 2% 2% 2%

Know health workers 1% 1% 1%

Other 0% 1% 1%

Don't know/Can't remember 0% 1% 1%

Health facility is clean 0% 0% 0% Source: Household Survey Note: All respondents were asked if they had visited other health care providers in addition or in

place of the nearest HCII or HCII, and if they responded, ―Yes,‖ they were asked why.

Households who had visited a health facility were asked if the facility was open and queried

about their waiting time.

Table 15: Health centre open when patients arrived

HCII HCIII All HCs

Yes 84% 87% 85%

No 10% 7% 9%

No, the health facility was closed that day 1% 0% 1%

Yes, but patients were not attended to 5% 5% 5% Source: Household Survey Note: All respondents who reported visiting the health centre at least once within the past

12 months were asked if the health centre was open when they visited.

The waiting time from when a patient first arrived at the health centre until their first con-

sultation with health centre staff is displayed in Table 16, comparing the how the health

centre and household reported wait time. The average waiting time until opening for pa-

tients that found the health centre closed when they arrived is 84 minutes for HC II and 79

minutes for HC III. Table 16 displays the waiting time for first consultation at the health

centre.


Table 16: Patient Waiting Time from Arrival until First Consultation

HCII HCIII All HCs

Household

says HC says

Household

says HC says

Household

says HC says

Average time 52 minutes 23

minutes

69

minutes

26

minutes

59

minutes

25

minutes

Waited less

than 1 hour 58% 100% 46% 99% 53% 100%

Source: Household Survey, Health Centre Staff Survey Note: Wait time was measured using a definition of the time of arrival to the health centre until the first consultation, or when the health centre staff registers each patient assessing their condition and determining if an examination is necessary. In absence of clear standard, this has been derived from ―Waiting Time‖ as per the Uganda Ministry of Health 2012/2013 Annual Health Sector Performance

Report http://health.go.ug/docs/AHSPR_2013.pdf

Rates of household reported self-treatment are high (33%). Given the potentially negative

consequences of self-treatment, households were asked about whether they had received

information on the importance of going to the health centre as opposed to self-treatment. A

total of 48% of households reported that they received information about the importance of

visiting the clinic as opposed to self-medicating within the past 12 months.

Table 17: Information on the importance of visiting the health centre (and the dan-

gers of self-treatment)

HCII HCIII All HCs

Households who received information about the importance of vis-

iting the health centre

47% 50% 48%

Households received information about the importance of visiting the health centre from the

following sources:

Health facility staff 52% 55% 53%

Media (radio, newspaper, TV, SMS, etc…) 29% 30% 30%

Community members who visit the health facility (Word of mouth) 18% 18% 18%

VHTs 11% 12% 11%

LC1 3% 3% 3%

Information posted publicly in my village (or elsewhere) 2% 2% 2%

Information posted publicly at health centre 2% 2% 2%

Health Unit Management Committee (HUMC) 1% 1% 1%

Other 0% 0% 0% Source: Household Survey Note: Among households that reported receiving information about the importance of visiting the health centre and the dangers of self-treatment, the methods in which this information was shared is

displayed.

http://health.go.ug/docs/AHSPR_2013.pdf


Perceived Quality of Services

A variety of patient perceptions regarding the quality of the examination at the health cen-

tre were recorded. A total of 83% of respondents reported that they were examined during

their visit to the health centre. A total of 66% of respondents said that equipment was used

during their examination. Of these, 82% reported needles/finger prick/RDT had been used

and the next most common type of equipment identified was thermometer (by 16% of

those examined).

While patients generally reported feeling that they were treated well at the health centre,

only 60% confirmed that their medical condition had been clearly explained and 55% said

that the health centre staff wore a uniform.

Table 18: Quality of the examination

HCII HCIII All HCs

Staff who examined was wearing a uniform 51% 60% 55%

Test(s) were taken during the examination 57% 65% 60%

Staff who took the test(s) was wearing gloves 86% 94% 89% Source: Household Survey Note: This information was self-reported by the patients and answered questions regarding their

most recent visit to the health centre within the past 12 months.

Table 19: Patient's perceptions of staff attentiveness during examination

Patient's perception / HC level HCII HCIII All HCs

Staff listened to what the patient had to say a 91% 89% 90%

Staff clearly explained the patient's diagnosis b 59% 61% 60%

Patient had privacy during the examination c 90% 89% 90%

Patient felt free to express him/herself d 2% 4% 3% Source: Household Survey Note: Responses were taken from patient-reported perceptions from their most recent visit to the health facility among patients who had been examined at their last visit to the health centre. All ques-tions refer to the most recent visit to the health centre. a Percentage of patients who said the health worker listened to what they said during the examination.

Answer choices were read aloud; the percentage includes those whose responses were ―Yes‖ or ―Yes, the person was interested and asked questions‖ b Percentage of patients who said the staff clearly explained their medical condition. c Percentage of patients who said they had privacy during the examination at their last visit. d Percentage of patients who reported that the patient felt free to express themselves to the staff dur-ing the examination. Answer choices were read aloud; the percentage includes those whose response

was ―Yes, with no difficulty. The person encouraged me to express myself‖

Table 20: Politeness at health centre

HCII HCIII All HCs

Household

says

HC

says

Household

says

HC

says

Household

says

HC

says

Patients treated politely 90% 85% 89% 83% 90% 85% Source: Household Survey, Health Centre Staff Survey

Note: This question was asked to both household and health centre staff respondents using a scale of politeness that was read aloud. This percentage includes those who answered ―Yes, he/she was polite‖

or Yes, he/she was extremely polite.‖


Table 21: Satisfaction with relationship with HC staff/community

HC II HC III All HCs

Household

says

HC

says

Household

says

HC

says

Household

says

HC

says

Not satisfied 25% 8% 28% 11% 26% 9%

Satisfied 66% 69% 62% 56% 64% 63%

Very satisfied 9% 23% 9% 33% 9% 27% Source: Household Survey, Health Centre Staff Survey Note: Both households and health centre staff were asked if they were satisfied with your relation-ship with the community/HC staff. This question and answer choices were read aloud.

Table 22: Satisfaction with quality of care received


Not satisfied/Somehow satisfied 31% 34% 32%

Satisfied 57% 53% 56%

Very satisfied 12% 13% 12% Source: Household Survey Note: The survey question is "Were you satisfied with the quality of care you/the patient received during your visit at the health facility?" This question and answer choices were read aloud.


E. ANC and Delivery

Antenatal Care

Among the women who had given birth within the past 12 months, 40% of reporting com-

pleting 4 or more ANC visits to the health centre, a standard set forth by the Uganda Minis-

try of Health as the minimum recommended number of ANC visits for a pregnant woman.

The reasons why women chose not to visit the Health Centre for antenatal care are dis-

played in Table 23. The Ministry of Health mandates that women should receive and HIV

test during their first ANC visit. Among women who visited the health centre for antenatal

care, 83% reported that they were administered an HIV test.

Table 23: Reasons community members do not visit the health centre for ANC

HCII HCIII All HCs

Antenatal care services are not offered 26% 4% 20%

Too early in pregnancy 14% 19% 15%

Needed more advanced ANC 10% 8% 9%

Referred elsewhere 9% 3% 7%

Was elsewhere when needed services 4% 5% 5%


Staff is not available 5% 3% 4%

Poor staff attitude 3% 4% 3%

Was sent away 2% 2% 2%

Don’t know 1% 1% 1%

Feared midwife 1% 2% 1%

Could not afford 1% 1% 1%

Other 0% 0% 0% Source: Household Survey Note: Households with a pregnant woman in the past twelve months that reported not visiting the health centre for ANC care were asked to share why not.


Delivery

Among the women who gave birth within the past 12 months, 37% delivered at the closest

government health centre II or health centre III. The reasons that household members re-

ported not delivering at the health centre are displayed in Table 24.

Table 24: Reasons community members do not deliver at the health centre

HCII HCIII All HCs

Delivered abruptly 19% 15% 18%

Delivery services not offered at the health centre 19% 6% 15%

Other place provide better quality services 10% 11% 10%

Referred to another health centre 8% 12% 10%

Was elsewhere at the time of delivery 6% 8% 7%

Health centre was not open 5% 5% 5%

Used a traditional birth attendant 4% 4% 4%

Did not have the requirements 4% 2% 3%

Was not treated well at the health centre 2% 2% 2%

Impolite staff 1% 2% 1%

Feared midwife 1% 1% 1%


Other 0% 0% 0% Source: Household Survey Note: Women who had delivered in the past 12 months, but did not do so at the health centre

were asked to share the reason why they made this decision.


F. Family Planning

Within the study sample, 28% of all surveyed households reported seeking family planning

services within the past 12 months. The reasons for not visiting the health centre for family

planning are displayed below.

Table 25: Reasons community members do not visit the health centre for family

planning services

HCII HCIII All HCs

Did not need because too young, too old, single or want chil-

dren 32% 33% 32%

Side effects of family planning 18% 19% 18%

I was pregnant 19% 18% 18%

Use natural family planning (exclusively breastfeeding, cycle

beads, other) 12% 14% 12%

Go elsewhere for family planning 10% 8% 9%

My partner (husband, wife, other) does not allow me 7% 6% 6%

Already using a long-term family planning method a 4% 5% 4%

Refused to answer 1% 2% 1%

Did not know they performed family planning 1% 1% 1%

Health facility out of stock of prevention drugs 1% 1% 1%

Health facility does not provide family planning services 1% 0% 1%

Health facility does not provide education about family plan-

ning 1% 0% 1%

Religious reasons 1% 1% 1%

Staff is not polite 1% 1% 1%



Other 0% 0% 0%

Source: Household Survey Note: a Long-term family planning methods include IUDs, implants or sterilization (hysterectomy or vasectomy).


A total of 70% of households reported receiving information on the importance of family

planning within the past 12 months.

Table 26: Households that received information in the past 12 months regard-

ing the importance of using family planning

HCII HCIII All HCs

Households who received information about the importance of

visiting the health centre for family planning

68% 73% 70%

Households who received information about the importance of visiting the health centre

for family planning from the following sources:


Media (radio, newspaper, TV, SMS, etc…) 27% 27% 27%

Community members who visit the health facility (Word of

mouth)

16% 15% 16%

VHTs 7% 8% 7%


Information posted publicly in my village (or elsewhere) 2% 3% 2%

LC1 1% 2% 2%


Other 0% 0% 0% Source: Household Survey Note: Among the households that reported receiving information about the importance of visiting the health centre for family planning, the methods in which this information was shared was rec-orded. More than one method could be recorded by each household.


G. Fees at Health Facilities

More patients were required to pay in cash than in-kind for services at the health centre,

although only 8% reported making any type of cash payment and 36% of respondents re-

ported that they were required to bring items to the health centre in order to be examined.

The item most frequently reported being required was an exercise book for transcribing pre-

scriptions.

The most frequent service paid for in cash or kind was delivery – with 32% of respondents

reporting cash and 9% reporting in-kind payments for deliveries. The average amount paid

in cash for delivery was 11,720 UGX.

Table 27: Payments made at the health centre

HCII HCIII All HCs

Average

amount paid

/ value of in-

kind pay-

ment

Median

amount paid

/ value of

in-kind

payment

Cash payment during last visit

to the health centre 8% 8% 8% UGX 4160 UGX 1000

In-kind payment during last

visit to the health centre 0% 1% 1% UGX 8230 UGX 5000

Required to bring items during

the last visit to the health cen-

tre

37% 36% 36% N/A N/A

Cash payment for ANC 8% 6% 7% UGX 2570 UGX 1500

In-kind payment for ANC 0% 1% 0% UGX 4630 UGX 3500

Cash payment for delivery 32% 32% 32% UGX 11720 UGX 7000

In-kind payment for delivery 12% 7% 9% UGX 3950 UGX 2500

Cash payment for family plan-

ning 9% 6% 8% UGX 2730 UGX 1500

In-kind payment for family

planning 0% 0% 0% UGX 2540 UGX 1500

Cash payment for immuniza-

tion 6% 4% 5% UGX 1810 UGX 1000

In-kind payment for immuniza-

tion 0% 0% 0% UGX 4420 UGX 1500

Source: Household Survey Note: Cash payments during the last visit to the health centre include any cash payments for drugs, general treatment, injections, lab testing, immunisation, gloves, condoms, delivery sheets, cotton or other. Respondents were asked if they made ―any in-kind payments‖ at the health centre and specifically any payments for ANC services and delivery. Items that may have

been required to bring needles, IV fluid, gloves, cotton wool or gauze, finger pricks, exercise

book or immunisation/child health card.


H. Health Facility Staffing & Absenteeism

In the National Health Policy II, the Ministry of Health sets forth the standard number of

medical and non-medical staff that should be working at each level of health centre. The

categorization of staff is displayed below in Table 28. All full-time staff at the health centre

were included, including some staff that were hired by NGOs.

Table 28: Categorization of health centre staff as medical/non-medical

Medical

Clinical officer

Senior Clinical Officer

Enrolled midwife

Registered midwife

Enrolled nurse

Registered nurse

Nursing Aide/Assistant

Certified midwife

Senior Nursing Officer

Enrolled Comprehensive Nurse

Registered Comprehensive Nurse

Laboratory assistant

Nursing Officer

Non-medical

Health assistant

Records assistant

Guard/watchman

Gardener (outdoorman) or cleaner (indoor)

Intern

Other

Prior to the day of the survey, an enumerator visited the health centre and recorded if the

In-Charge was present and found that 43% were at the health centre on the mobilisation

day. Overall, 64% of the surveys conducted were with In-Charges as the respondent, the

preferred staff member to interview because of their knowledge of the health centre. How-

ever, if they were unavailable or had not worked at the health centre for more than twelve

months the next medical staff with the most experience was selected to participate in the

interview.

The average numbers of staff at each clinic visited is compared to this standard below in

Table 29, showing that the number of medical staff is near to the standard, but there are

less non-medical staff on average working in these health centres.

The absence rate at the health centre is measured by counting the number of medical staff

absent on the day of the survey for reasons other than being on-leave, on outreach or at a

staff training. The number of staff absent was greater in HCIIIs, however there are greater

numbers of medical staff at higher level health centres.


Table 29: Health centre staffing and absenteeism

HCII HCIII All HCs

Medical Staff

# of medical staff (MOH standard) 3 11 n/a

% of facilities with standard # medical

staff assigned 65% 40% 55%

Medical staff present on survey day 63% 58% 61%

Non-medical Staff

# of non-medical staff (MOH standard) 6 8 n/a

% of facilities with standard # non-

medical staff assigned 0% 2% 1%

Non-medical staff present on survey day 54% 56% 55%

Source: Health Centre Staff Survey Note: Absenteeism was measured by recording the number of staff at a health centre who had

an ―unexcused absence‖ on the day of the survey. The MOH defines this as a medical staff mem-ber who was not present at the clinic for reasons other than being on leave, on outreach or at a staff training. Calculations for staff presence are (# staff present) / (total # staff assigned)

When household respondents were asked how often health worker staff attended work,

52% said that they always attended work, 38% said they sometimes attend work and

10% reported that they rarely attend work.

Table 30: Community's perception of staff absenteeism

HCII HCIII All HCs

Staff are always at work 52% 53% 52%

Staff occasionally do not come to work 38% 38% 38%

Staff are rarely at work 10% 9% 10% Source: Household Survey Note: These three choices were read aloud by enumerators to household respondents.


I. Drug Availability

The Health Centre survey also took an inventory of any stockouts within the three months

prior to the survey of any of the six outlined key tracer drugs. The presence of these drugs

is an indicator of the level of functionality of a health centre and this list has been defined

by the Uganda Ministry of Health Essential Medicines and Health Suppliers List for Uganda

(EMHSLU).14 These key tracer drugs include First Line Malaria Drugs, Cotrimoxazole, Oral

Rehydration Solution (ORS), Depo-Provera, the Measles Vaccine and Sulfadoxine and Py-

rimethamine (SP).

In keeping with the MoH HSSIP indicator, we present the percent of facilities without stock-

outs (rather than those with stockouts) in table 31. More detailed information on stockouts

(by tracer item) was compiled from available stock cards. It is important to note that many

facilities also had missing stock cards for specific commodities or timeframes, which are also

shown in table 31 (below).

Table 31: Percentage of health centers with stockouts, without stockouts and no

records for tracer drugs


Without

stock-

outa

With

Stock

out

No

rec-

ord

Without

stock-

outa

With

Stock

out

No

rec-

ord

Without

stock-

outa

With

Stock-

out

No

rec-

ord

Depo Provera 67% 2% 31% 74% 2% 25% 69% 2% 28%

First Line Ma-

laria Drugs 65% 9% 26% 67% 13% 21% 66% 11% 24%

SPb 59% 11% 30% 67% 11% 22% 62% 11% 27%

Cotrimoxa-

zole 61% 12% 27% 64% 15% 21% 62% 13% 25%

Measles Vac-

cine 46% 11% 43% 59% 9% 32% 51% 10% 38%

ORS 49% 26% 25% 50% 30% 19% 50% 28% 23%

All drugs 27% 27% 46% 31% 34% 35% 29% 29% 42%

Source: Drug Stock Cards

Note: a Stock-outs are calculated only when records are available. In health facilities (or for specific items) when no stock record is available, we cannot conclude the stock availability. Among the health centres with available records, the % of health centres recording no stockouts within the past three months is displayed. b (Sulfadoxine / Pyrimethamine)

14

Uganda Ministry of Health. “Essential Medicines and Health Supplies List for Uganda” 2012


The minimum storage conditions of drugs were measured at each health centre. Table 32

below shows the results of each observation.

Table 32: Conditions of the location where drugs are kept

Observations / HC level HCII HCIII All HCs

There is a method in place to control temperature 89% 94% 91%

There are windows that can be opened or there are air vents 92% 95% 94%

There is no direct sunlight entering the area 73% 84% 77%

Area is free from moisture 90% 96% 93%

There is a cold storage in the facility 63% 88% 73%

No evidence of pests 79% 95% 86%

No medicines are stored on the floor 73% 68% 71% Source: Health Centre Staff Survey

Note: These questions were not asked aloud, but instead the conditions of the drug storage area

were observed.

Drug availability and prescriptions were measured in a variety of ways. Among the patients

who were examined, 82% reported that they were given drugs, 31% reported that they

had to go somewhere to get drugs, 24% reported that they were referred to a specific

place to buy drugs and 20% reported that they were given a prescription at the health cen-

tre to go and get drugs from elsewhere.

Table 33: Households' access to drugs at the health centre

HCII HCIII All HCs

Patients who were given drugs during their last visit to the

health centre a 85% 77% 82%

Patients who had to go somewhere else to get drugs b 29% 33% 31%

Patients who were referred to a specific place to buy drugs c 22% 25% 24%

Patients that were given a prescription at the HC to go and

buy drugs somewhere else d 18% 23% 20%

Source: Household Survey

Note: a Includes drugs (tablets or syrups), injections or other (eye drops, ointment, etc…) given to the

patient at the health centre. b Includes patients that may have obtained drugs at the health centre, but also had to look for

more drugs elsewhere. c Among patients who reported that they had to go elsewhere to get drugs, patients were asked if

they were referred to a specific place to obtain drugs. All others were not referred to a specific

place to find the drugs. d Among patients who reported that they had to go elsewhere to get drugs, patients were asked

if they were given a prescription to facilitate obtaining drugs somewhere else other than the

health centre.

A total of 89% of health centres (88% of HCII and 89% of HCIII) reported that communi-

ty members were informed when drugs were delivered to the health centre, yet fewer

community members (47% for HCII and 46% for HCIII) reported that they were informed

of such deliveries. Community members described the most common ways that they

learned of drug deliveries with word of mouth being the most frequently cited response.


Table 34: Information on drugs deliveries to the health centre

HCII HCIII All HCs

Community members who said they receive information on the

delivery of drugs to the HC

47% 46% 47%

Community members receive information on the delivery of drugs to the HC from the

following sources:

Community members who visit the health facility (Word of

mouth)

56% 59% 57%

I see the vehicle that carries the drugs 30% 28% 29%


LC1 9% 6% 8%

VHTs 4% 6% 5%


Information posted publicly/announced in my village (or else-

where)

2% 2% 2%


Community Based Organization (CBO) 0% 0% 0%

Other 2% 2% 2%

Source: Household Survey Note: Among community members who reported receiving information on the delivery of drugs to the health centre, the methods in which this information was shared was recorded. Responses from Household and Health Centre Surveys are compared when asking whether or not community members are informed about drug deliveries to the health centre. Household members who re-

sponded "Yes" that they know that drugs are delivered to the HC, then described how they learned of these deliveries as indicated above.

Despite information above that 82% of households reported receiving drugs on their last

visit to the MoH facility and 47% of all household respondents reporting to know when

drugs are delivered to the facility, Table 35 below shows that 22% of respondents believe

that drugs are rarely available.

Table 35: Household perception of the availability of drugs at the health centre

HCII HCIII All HCs

Drugs are always available 12% 10% 11%

Drugs are sometimes available 66% 67% 67%

Drugs are rarely available 21% 23% 22% Source: Household Survey Note: Household respondents who have visited the health centre were asked to assess the availa-bility of drugs at the health centre. This question and answer choices were read aloud.


J. Community Structures & Accountability Mechanisms

Health facilities use a variety of mechanisms to monitor patients including ways to deter-

mine the order that the patients are examined, ways to monitor complaints and suggestions

and ways to disseminate information to the community.

Table 36: Health centre monitoring mechanisms in place

HCII HCIII All HCs

Suggestion boxes a

Household respondent reported suggestion box was

observed during last examination 12% 17% 14%

Enumerator noticed suggestion box at HC 4% 8% 5%

HC staff reporting that suggestion boxes are used 3% 14% 7%

Waiting cards b

HH respondent reported that waiting cards were

utilised during last visit to HC 4% 5% 5%

HC Staff report that waiting cards or seating ar-

rangements are used 61% 63% 38%

Source: Household Survey, Health Centre Mobilisation Survey, Health Centre Staff Survey Note: aHousehold respondents reported observing the presence of suggestion boxes at the health centre during their last visit. Enumerators scheduling the health centre staff survey observed whether or not a suggestion box was present. Health centre staff were also read a list and asked if various tools were in place, included suggestion boxes and waiting cards. bHouseholds were read a list of possible methods that the health centre employed to ensure that patients were seen on a first-come first serve basis and those that reported that waiting cards were used to organise and triage patients are displayed here.

A total of 66% health centres reported that during the most recent local council meetings,

the health centre and its issues were discussed. In both the household and health centre

surveys, respondents were asked which roles of MoH community structures of Health Unit

Management Committees (HUMCs) and Village Health Team (VHT) Members

Table 37: HUMC and VHT roles and responsibilities included in survey answer

choices (NB: answer choices were not read aloud during the surveys)

HUMC

roles

Monitor general administration of health centre Monitor how health workers

manage the health centre

Instigate penalties for poorly performing health workers

Ensure annual work plans are drawn up based on priority needs

Assist health workers yearly in prioritizing community needs

Monitor the procurement, storage and utilisation of health centres' goods and

services

Monitor drug delivery to health centre/Count drugs

Monitor delivery of health equipment to health centre

Monitor safe storage of health equipment at health centre

Monitor health care service delivery

Supervise management of health centres finances

Advise upon, regulate and monitor allocation of funds from other sources

Foster improved communication with the community

Bring community and health workers together for meetings or discussions


Table 37: HUMC and VHT roles and responsibilities included in survey answer

choices (NB: answer choices were not read aloud during the surveys)

VHT

roles

Drugs distribution

Check households' hygiene

Registration of children/people in the community

Immunization

Health education

Family planning education

Treat minor illness

Provide Vitamin A to children

Provide deworming tablets

Distribution of condoms/mosquito nets

Antenatal and newborn care

Among health centre staff, 8% could name two or more roles and responsibilities of the

HUMC. A total of 10% of household members could name two or more roles and responsi-

bilities of the Health Unit Management Committee with the most frequently named role be-

ing to bring the community and health workers together for meetings or discussions.

Overall, 4% of households said that they received information from the HUMC in the past

12 months. Of all households, 48% reported that a Village Health Team (VHT) had visited

their home within the past 12 months and 11% of the households could name two or more

of the roles of the VHTs.

Table 38: Households knowledge of HUMC and VHT


Respondents that knew what the HUMC is 17% 14% 16%

Respondents that knew at least 2 HUMC roles 10% 9% 10%

Respondents that said they received a visit from a VHT 46% 52% 48%

Respondents that mentioned two or more VHT activities 12% 9% 11% Source: Household Survey Notes: Respondents that knew what the HUMC was were asked to name the roles and responsibilities of the HUMC. Respondents that reported receiving a visit from the VHT in the past 12 months were asked what the VHTs do when they visit their households and villages.


K. Health Outcomes (<5 and maternal deaths)

Among the households that were surveyed, 98% had a child under five, 43% had a preg-

nancy within the past 12 months and 41% had both a child under five and a pregnancy

within the past 12 months.

Evidence of immunization for children under the age of 5

During household interviews, enumerators viewed vaccination cards for children. Table 39

shows the rates of various immunisations.

Table 39: Immunisation

District BCG DPT

(All doses)

Polio

(All doses) Measles Rotavirus PCV

N

ort

h

Lira 87% 67% 63% 71% 19% 15%

Apac 97% 86% 85% 78% 31% 26%

Pader 89% 78% 77% 76% 30% 22%

Gulu 82% 73% 72% 68% 26% 22%

Lamwo 97% 88% 87% 81% 35% 27%

Kitgum 97% 87% 86% 80% 28% 23%

Agago 96% 84% 83% 76% 32% 27%

E

ast Katakwi 96% 80% 77% 71% 20% 13%

Bukedea 91% 69% 62% 72% 25% 14%

Manafwa 81% 61% 62% 69% 32% 21%

Tororo 83% 68% 65% 63% 24% 17%

West/

Centr

al Kabarole 88% 79% 74% 74% 23% 18%

Mubende 92% 79% 71% 69% 22% 16%

Nakaseke 96% 84% 80% 75% 24% 19%

Kibaale 95% 84% 80% 76% 26% 18%

Bundibugyo 98% 90% 88% 83% 27% 23% Source: Household survey and immunisation cards Notes: The BCG immunization is given at birth. The DPT immunization is given in 3 doses (at 6, 10 and 14 weeks). The Polio immunization is given in 4 doses (at birth, 6, 10 and 14 weeks). The Mea-sles immunization is given at 9 months. Rotavirus and PCV are not compulsory immunizations. Enu-merators viewed children’s immunization cards for 96% of children.


Under-five mortality rate

The following table shows under five mortality rate (U5MR)15 and neonatal, post neonatal

and infant mortality rates for the 12 months prior to the survey date.

Neonatal mortality is defined as the probability of dying within the first 28 days of life; post-

neonatal mortality is defined as the arithmetic difference between neonatal and infant mor-

tality; infant mortality is defined as the probability of dying before the first birthday; under-

five mortality is defined as the probability of dying between birth and the fifth birthday. The

indicators are calculated by dividing the number of deaths of children under the age of five,

children under a year of age, children under 28 days of life and children between 28 days of

life and one year, respectively, by the number of live births in the same time period and

multiplying by 1,000.16

Table 40: Under five mortality rate

District

Neonatal

deaths (per

1,000 live

births)

Post neonatal

deaths (per

1,000 live

births)

Infant deaths

(per 1,000 live

births)

Under-five

deaths (per

1,000 live births)

Manafwa 175 52 227 371

Lira 97 56 153 266

Tororo 84 33 117 179

Bukedea 85 28 113 169

Kabarole 71 27 98 145

Kibaale 78 8 85 128

Katakwi 70 5 75 125

Gulu 49 12 61 92

Pader 53 13 66 88

Nakaseke 66 11 77 88

Mubende 35 18 53 88

Bundibugyo 37 12 49 85

Agago 23 6 29 50

Apac 13 4 18 44

Kitgum 24 12 36 42

Lamwo 11 5 16 27

Total 54 17 71 111 Source: Household survey

Notes: Neonatal deaths are deaths of children below 28 days of life. Post neonatal deaths are

deaths of children between 28 days and 1 year of life. Infant deaths are deaths of children be-low 1 year of life. Under 5 deaths are deaths of children below 5 years of age. All deaths are expressed out of 1,000 live births in the 12 months before the survey date.

15

The under-five mortality rate (U5MR) is the probability for a child born in specified year to die before reaching the age of five, if subject to current age-specific mortality rates. This indicator is expressed as number of deaths per 1,000 live births. United Nations Foundation. Indicators for Monitoring the Millennium Development Goals: 4.1 Under-five mortality rate. http://mdgs.un.org/unsd/mi/wiki/4-1-Under-five-mortality-rate.ashx 16

Note that this standard approach of calculating mortality rates implicitly assumes a constant birth rate.

http://mdgs.un.org/unsd/mi/wiki/4-1-Under-five-mortality-rate.ashx


The study baseline under five mortality rate (111) is higher than the <5 mortality rate most

recently available in the Uganda Demographic Health Survey (90 in 2011) and the <5 mor-

tality rate most recently published by the United Nations (66 in 2013). The Power to the

People control group mean in 2005 was also higher than the United Nations figure of 144

for the same year.17 The following tables show time trends in Uganda for the under-five

mortality rates (at 5 year intervals). The year by year figures are available on the website.

Figure 8: Uganda Children <5 mortality rate per 1,000 live births (United Nations)

Year <5 mortality per 1,000 live births

1990 179

1995 165

2000 147

2005 109

2010 78

2013 66 Source: http://mdgs.un.org/unsd/mdg/SeriesDetail.aspx?srid=561

Figure 9: Uganda Children <5 mortality rate per 1,000 live births (UDHS)

Year <5 mortality per 1,000 live births

2000-1 152

2006 137

2011 90 Source: (2011 UDHS) http://www.ubos.org/onlinefiles/uploads/ubos/UDHS/UDHS2011.pdf

Maternal mortality rate

Maternal mortality rate is calculated by dividing the total number of deaths due to maternal

causes by the total number of live births for a given year and multiplying by 100,00018. The

number of maternal deaths and the number of live births at the health centre were recorded

for the 12 months prior to the survey date using the health centre HMIS records. We found

that maternal deaths and live births information is in general not well documented in HMIS

records. Only 33% of health centres had records on maternal deaths and live births for all

of the 12 months before the survey date. We are not including the data that we could draw

from this smaller sample in this report as it would not be representative. Because of the

high number of missing values in the HMIS records, we decided to change strategy and col-

lect data on baseline maternal mortality retrospectively in the household survey during the

midline. While collecting data retrospectively is usually a concern, the death of a household

member is such a major event that we are not concerned about recall error over a two year

time period in this case.

17

United Nations Foundation. Millennium Development Goals Indicators. Children under five mortality rate per 1,000 live births. http://mdgs.un.org/unsd/mdg/SeriesDetail.aspx?srid=561 18 http://mdgs.un.org/unsd/mi/wiki/5-1-Maternal-mortality-ratio.ashx

http://mdgs.un.org/unsd/mdg/SeriesDetail.aspx?srid=561

http://www.ubos.org/onlinefiles/uploads/ubos/UDHS/UDHS2011.pdf

http://mdgs.un.org/unsd/mdg/SeriesDetail.aspx?srid=561

http://mdgs.un.org/unsd/mi/wiki/5-1-Maternal-mortality-ratio.ashx


VIII. Progress Update The Inception Report listed out in the following 13 steps of the implementation planned. As

planned, IPA and GOAL have completed steps 1-6 including the project preparation, qualita-

tive follow-up, listing, sampling and baseline data collection. Step 7, or programme imple-

mentation is ongoing and steps 8-13 including midline and endline data collection and anal-

ysis and report synthesis and dissemination are yet to be carried out. A more nuanced Gantt

Chart outlining the remaining steps is included in Appendix 7.

Steps Status

1. Project preparation: project staffing, protocol and questionnaire develop-

ment, testing

Completed

2. Qualitative follow up of the original P2P study Completed

3. Catchment area identification and household listing Completed

4. Household sample selection Completed

5. Baseline survey of health centres and citizens Completed

6. Random assignment of health centres to treatment and control groups Completed

7. Programme implementation Ongoing

8. Midline surveys (12 months after launch) Anticipated

9. Endline surveys Anticipated

10. Data cleaning and preparation for analysis Anticipated

11. Data analysis Anticipated

12. Report writing Anticipated

13. Dissemination Anticipated

IX. Next Steps

Sharing the Baseline Report Selected variables from the baseline data collection have continually been shared with

communities selected to receive the Citizen Report Cards as a component of the programme

implementation. In addition, GOAL Uganda is preparing for disseminating the baseline re-

port in summer 2015 internally and with their partners through the dissemination of an ab-

breviated report summary. A joint meeting with GOAL, IPA and DFID will be initiated to

share and discuss the baseline report and respond to queries from the donor perspective.

Intervention Observation

Throughout April and May 2015, IPA conducted a structured series of intervention observa-

tions. IPA field staff observed the activities of each treatment group implemented by GOAL

and one of the affiliated local Community-Based Organisation and completed a detailed

standardised report on each observed activity. The main objective is to generate more con-

text for the interpretation of results from the impact assessment and to compare the health

centre dialogues, community dialogues and interface meetings between the various treat-

ment groups.

Midline Data Collection Preparations for the collection of midline data will begin in June 2015 with the submission of

an IRB amendment, procurement of equipment and supplies and the development of an up-


dated questionnaire. In July, field management staff will be recruited and trained on any

new financial procedures, updated survey manuals will be designed, surveys piloted, and a

data flow structure designed. In August, recruitment, training and data collection will begin

with the teams in the East Region. In September, the East region data collection will be

completed and the North team will be recruited, trained and the data collection launched.

In October, the West/Central team will be recruited, trained and data collection launched, as

data collection will continue in the North. In November and December, data collection in

the West/Central and North will continue. Upon the completion of the midline data collec-

tion, the focus will shift to the budget reconciliation in January and then data cleaning and

analysis will begin in February and continue through May 2016. The data cleaning and anal-

ysis of the midline data will be more extensive than for the baseline data. The data cleaning

will involve a similar data cleaning process that took place prior to the baseline report pro-

duction and will last from February through April. The data analysis will then will include

three phases.

Figure 10: Midline Analysis Phases and Timing

Analysis Primary Analysis / Purpose Timeframe

Phase I

Primary Treatment Outcomes will include

conducting regression analyses on the data to

detect significant effects among the treatment

outcomes. This information will be sufficient for

the midline report and will be shared with GOAL.

May 2016

Phase II

Theory/Mechanisms will begin to examine the

underlying factors associated with the results of

the significant tests and the way that the theory

the study and intervention are based on matches

with the findings. This information will be neces-

sary for publication and will last until July.

July 2016

Phase III

Comparison to P2P will be the last portion of

the paper to be written and will include an in-

depth comparison of the research and interven-

tion design, as well as comparisons of the find-

ings across both studies.

September 2016

(possibly later)

Endline Data Collection The endline is critical for detecting any longer term effects from the intervention. IPA and

GOAL Uganda propose conducting the endline 24 instead of 36 months after the baseline

data collection in order to have a rigorous assessment of the effectiveness of the interven-

tion two years in. The critical advantage of conducting the endline after 24 instead of 36

months is that we could work with the implementing partner organisations on an advocacy

plan that would preserve the internal validity of the randomised impact assessment until the

endline, thus creatively balancing research and practice. If the endline is only conducted af-

ter 36 months and after the rollout of full advocacy activities, the validity of the findings will

be compromised. With an earlier endline, we would structure implementation activities into

three phases:


Between baseline and

midline (year 1)

1. Implementation in randomly selected treatment

units

Between midline and end-

line (year 2)

1. Continued follow-up activities in treatment units

2. National advocacy work

After the endline (year 3) 1. Continued follow-up activities in treatment units

2. National advocacy campaign

3. District advocacy campaigns

Between the midline and endline, follow-up in the treatment units and controlled national

advocacy activities could occur. Following the endline data collection, the full advocacy cam-

paign would be rolled out including engagement at the district level. This timeline would

facilitate the use of the endline data to offer a greater understanding of the longer term im-

pact of the different components of the intervention before the district engagement advoca-

cy activities begin. We are working closely with GOAL and the implementing partners to de-

vise an advocacy plan that would facilitate a rigorous two-year follow-up while minimising

the burden for implementing partners.

Publication and Dissemination

The audience for the full post-midline data analysis includes civil society organisations work-

ing in the health and governance space – both in Uganda and beyond; the Ugandan gov-

ernment, in particular the Ministry of Health and local governments; other governments in

developing countries; as well as donors and academics. Given the attention the original

Björkman and Svensson paper has received in these circles, we expect the extension and

replication to meet similar interest.

At the local level, we will disseminate our findings summarised in a simple report to stake-

holders in the 16 study districts, including both local governments and civil society. This

activity could be combined with GOAL’s outreach activities to districts in the second phase of

the programme, i.e. between midline and endline data collection.

At the national level, IPA will host a dissemination event inviting implementing organisa-

tions, other NGOs and CBOs working in the governance and health space, as well as repre-

sentatives from government, in particular the Ministry of Health. In addition, we may pre-

sent the findings as part of one of IPA’s forthcoming dissemination events, which highlight

the findings from several studies on one theme. If there is interest, we will gladly present

the findings in donor-government working groups, such as for example the Accountability

Working Group and the relevant working groups in the health sector.

At the international level, we will disseminate the findings through presentations at aca-

demic and joint academic-policy conferences and fora, academic publication(s), and a policy

brief, which will also be featured on the IPA website. Furthermore, the findings will filter

into the outreach activities of IPA’s growing global policy team. We are hoping to be includ-

ed in an EGAP group on the replication of studies on political participation, which would pro-

vide another excellent forum not only for dissemination but also for using the findings from

this study to push the envelope on developing an analytical framework for more systematic

replication and knowledge accumulation.


Figure 11: Deliverables sharing timeline according to study phase

Target

audience Baseline (BL) Midline (ML) Endline (EL)

Community /

health centre staff

Citizen Report

Cards

(Sept 2014 – Jan

2015)

District officials Not shared

District

Summary

Report

(February 2016)

Use key data in ad-

vocacy work

National officials

(including Ministry of

Health)

Summary Report

(August 2015)

Summary

Report

(October 2016)

International

Academic journals,

institutions, confer-

ences and other in-

stitutions

Not shared

Report for Academ-

ic Circulation

(Possibly 2017)

Conferences, Work-

shops, Working Pa-

pers and Peer-

Reviewed pieces

(In 2018)

Conclusion

This baseline report summarises key findings from the baseline data collected between Sep-

tember and December 2014 in 16 districts of Uganda. The baseline analysis includes data

from 377 government health centres (226 HCIIs and 151 HCIIIs) and 15,457 households.

Comparing the summary statistics from the Power to the People baseline and endline to the

ACT Health baseline clearly shows that the context in which we are working has changed

from that in which P2P was operating: in line with national and global trends child mortality

rates have markedly declined over the past years, making it more challenging to measure a

significant impact. This trend validates the decision to have a significantly larger sample

size than the original P2P study. It also provides an additional argument to conduct the

endline after 24 instead of 36 months and to only engage in limited advocacy work until

then in order to improve the chances of measuring a significant impact on child mortality

rates and other health outcomes if there is one.

The summary statistics presented in this report inform both the midline data collection and

the implementing strategy. In consecutive rounds, data collection and cleaning will continue

to become more efficient as we integrate the learnings and infrastructure developed from

earlier rounds. At the same time, comparing health centre level and district level summary

statistics will allow the intervention teams to better understand the context in which they

have been working and will allow them to begin to formulate advocacy strategies targeting

indicators that scored lower overall, as well as health centres and catchment areas that

scored lower relative to others. However, no findings or conclusions on the impact of the

intervention can be drawn from this data, as it consists of only baseline measures. Following

the midline data collection we will be able to assess the one-year impact of the intervention.


Using the critical baseline data and disseminating it to affected communities, the pro-

gramme implementation is facilitated to ensure balance among three key domains explained

further in Figure 12: programming domains.

Figure 12: Programming Domains

Responsibility Responsiveness Relationships

Individuals have good

health-seeking behaviour.

They seek preventive care

(ANC, immunisations, test-

ing, etc.) and go early for

treatment of illness to avoid

complications.

Health Centre staff use re-

sources effectively and pro-

vide care as per Ministry of

Health standards in the

Uganda National Minimum

Health Care Package (UN-

MHCP).

Mutual understanding and

trust between community

members and health centre

staff. Includes better under-

standing of each other’s con-

straints.

A summary of the baseline insights regarding these domains is provided below.

Responsibility: Given the relationship between access to services and health outcomes

(reduced morbidity and mortality), it is critical to understand the health-seeking behaviour

in Ugandan communities. The most frequently utilized methods of health care were visits to

the closet HC and self-treatment. Decisions to visit health centres other than the govern-

ment facility were largely based upon perceived availability of drugs and proximity to the

facility. At times, community members may make health-seeking decisions based on per-

ceived situation in the health facility (lack of drugs) rather than the actual situation in the

HC.

While it is not mandatory to offer antenatal care and delivery services at HCIIs, patients still

visit and receive these services at both health centre levels. Offering services that are not

mandated may imply that health workers and facilities are stretched to provide services that

community members seek in close proximity to their homes. The main reasons why patients

described not visiting the health centre for antenatal care were not based on poor quality of

services, but instead of the ANC services not being available at the health centre, more ad-

vanced care was needed or they were referred elsewhere. The most frequently cited rea-

sons for choosing not to deliver at the health centre include delivering abruptly, other places

provided better quality of services, referral elsewhere or delivery services were not offered.

The data generated in the baseline on rates of ANC visits (40%), facility delivery (37%)

and modern family planning (28%) also need to be compared to available data used in

MoH.

Responsiveness: The majority of the services outlined by the Ministry of Health to be of-

fered at each health centre level were adhered to. However, Prevention of Mother to Child

Transmission services stood out as quite low in HC IIs. It was interesting to note that ser-


vices that were not mandatory to offer at HC IIs were offered, for example lab services, HIV

Counselling and Testing and delivery services. While the percentage of health centres charg-

ing for services was less than 10%, more than 36% of patients were required to bring

items to the examination. Attendance of assigned medical staff at the facility (63% for HCII

and 58% for HCIII) on survey days may indicate underutilisation of existing human re-

sources for health, which affects service availability. Facility HMIS records for the 12 months

prior to the survey were notably poor – only 33% of HCs had records on maternal deaths

and live births for all 12 months and 42% of facilities were missing at least one record for

the key tracer drugs of interest to the MoH. Without complete records, it is very difficult for

the facilities to document their outputs and could compromise decision-making on public

health resource allocation and policy decisions.

Relationships: Overall, the baseline identified generally good indications of positive rela-

tionships between health workers and community members. Overall, community members

were satisfied/very satisfied by the quality of care on their most recent visit (68%) and

were likely to report being satisfied / very satisfied (92%) with the relationship with health

workers. Di were sometimes found when the health centre staff and communities were

asked the same question. For example, when asked the average length of time a patient

spends waiting for their first consultation at the health centre, the health centre staff re-

ported much shorter waiting time than community members.

Access to Information: Given the central role of information in the programme Theory of

Change, the report does juxtapose areas of information delivery (from perspective of health

workers) and information received (as reported by households). These data points do indi-

cate disconnects between the mechanisms reported by health centre and the ways commu-

nity members report receiving information.

The ACT Health baseline data allows researchers and implementers alike to better under-

stand the context in which the study and program is taking place. While conclusions cannot

be drawn from this data, the value of this information should not be underestimated. The

midline and endline findings will be compared against the baseline, to assess the impacts of

the intervention on areas key to improving health outcomes in Uganda.


X. Appendices

Appendix 1: Summary of Baseline Data for Key Indicators (DFID logframe)

Note: GOAL is in the process of refining the outcome and impact level indicators from those originally approved. The table below high-

lights the indicators proposed as of this draft report, but it will be updated when DFID has confirmed the final indicators.

ALL DISTRICTS

# HCs # Health Centres 226 151 377

Type Indicator Data Source MoH Data HCII HCIII ALL

DFID - Impact < 5 mortality in target communities during previous 12 months

HH survey 90

(Source: UDHS 2011) n/a n/a 111

DFID - Impact Maternal Mortality Ration in target communities dur-ing previous 12 months

HH survey 438

(Source: UDHS 2011) n/a n/a n/a

DFID - Outcome % of deliveries that occurred at nearest government HCII or HC III

HH survey 57%

(Source: UDHS 2011) 26% 53% 37%

DFID - Outcome % of total household reported health care visits made to a to a government health facility or closest HCII/HCIII

HH survey No MoH indicator 42% 39% 40%

DFID - Outcome % of mothers visiting closest government HCII or HCIII for four (4) ANC visits

HH survey 47%

(Source: HMIS 2009/10) 23% 59% 40%

DFID - Outcome % of community members satisfied / very satisfied by care received during their last visit to closest gov-ernment HCII or HCIII


DFID - Outcome % of respondents who reported waiting < 1 hour until first consultation on last visit to HCII or HCIII


DFID - Outcome

% of health centre staff present on survey day (medi-cal)

HC survey (primary observa-

tion)

No MoH baseline 63% 58% 61%

% of health centre staff present on survey day (non-medical)

No MoH baseline 54% 56% 55%

DFID - Outcome % of surveyed government HCII and HCIII without stock outs of any tracer drug in previous quarter

HC survey (primary observation + HMIS records)

28% (Source: 2010 Panel Survey)

27% 31% 29%

DFID - Outcome % of married and co-habitating women between the age of 15 – 49 using modern contraceptives

HH survey 25.9%

(Source: UDHS 2011) 25% 29% 27%


Appendix 2: Listing Protocol

Accountability Can Transform Health

Listing Protocol

OBJECTIVE: The objective of the ACT Health listing exercise is to identify all the house-

holds who live in a certain village and determine whether they have children under the age

of 5.

ENUMERATOR DELIVERABLES: As an enumerator for the ACT Health listing exercise, you

are expected to complete the listing of all households in a given village.

TIME TO COMPLETE THE EXERCISE: One full day. Depending on the number of house-

holds in a village, the first phase of the listing exercise (compiling the households list with

the help of LC1 and VHTs) might take up to four hours. DO NOT rush informants through

the exercise. It is important to leave them time to think.

PERMISSION: Your Field Manager will present an official introduction letter to the RDC

(Resident District Commissioner) prior to the exercise. You can show a copy of this letter to

the LC1 if he has any questions about your credibility (just show the letter to him, do not

leave it with him).

PURPOSE: If you are asked why you are collecting data about each household in the village

or what the purpose of the exercise is, answer by saying: ―We are a research organisation

and want to conduct a research study about health services in your community. The first

step is for us to get to know who lives in this village and who has children under the age of

five. We will go back to our offices and randomly select some households that we will inter-

view in some weeks from now. We want to make sure that everybody gets the same chance

of being interviewed, even if the interview does not bring any benefits. We are choosing

randomly who to interview because we don’t have resources to interview every household in

your community. We are asking about the households who have children under the age of

five because we want to make sure we interview those, but we will not only interview

those.‖

DEFINITION OF HOUSEHOLD: A household is a group of people who live in the same

dwelling and/or share meals.

Examples:

1. In the villages at times a household has many houses (grass thatched houses). But

since they all eat out of the same pot, they constitute a household.

2. In case the son doesn’t live with the parents as he married and moved in with his

wife, but still goes to the parents’ place for meals, these are two different households

since they do not share the same roof.

HOW TO CONDUCT THE LISTING EXERCISE – STEP BY STEP INSTRUCTIONS

Step 1: In the morning, your FM will give you a folder containing all the material needed for

the listing exercise.

Step 2: Before leaving to the field, MAKE SURE that the folder contains all the sheets that

are needed. These are: cover sheet, sheet for the village map, listing sheets and receipts

sheet. It is very important to write very clearly when filling out every sheet.

Step 3: Take a boda boda to the assigned village.


Step 4: Be observant of the route you take to get to the village. You will need to describe

how to get to the village in the cover sheet.

Step 5: Once you have arrived, look for the LC1 (this might involve calling him). While look-

ing for him be observant of village characteristics. You will need to draw a map of the village

in the map sheet.

Step 6: Talk to the LC1 explaining who you are and the purpose of your visit. Tell him that

you want 3 VHTs to participate to the listing exercise. Ask for the LC1 to select the most ac-

tive VHTs. 1 of the VHTs needs to be a woman. If there is no woman VHT, ask him to mobi-

lise the Secretary for Women’s Affairs. You need to help the LC1 in the mobilisation. Be co-

operative, in case he needs to call the VHTs, offer to use your phone. Make sure that the

LC1 asks the VHTs to come with their households’ lists.

Step 7: While you wait for the informants to arrive, start filling in the following fields in the

cover sheet: enumerator ID, directions to the village and date.

DO NOT start the exercise until all informants have arrived.

Step 8: Once all informants have arrived, thank them for coming, explain who you are and

the purpose of the exercise. Ask for their roles, names and phone contacts and record them

on the cover sheet.

Step 9: Record the start time on the cover sheet, then announce that you are going to start.

The first step of the exercise is to draw a detailed map of the village. Divide the map into

parts according to the village areas and assign numbers to each of them (1-6). A list of the

abbreviations that you can use on a map key follows. DO NOT use any abbreviations be-

sides those listed in the key. Write out the full name of every other landmark.

Map Key:

o P/S – primary school

o H/C – health centre

o P. Water – piped water

o RD - road

o VHT – Village Health Team

o LC1 – Local Chairperson 1

Step 10: Start the listing exercise. Pick area number 1 from the village map and ask the in-

formants to list for you all the households who live in that area. Ask for all information nec-

essary to fill the household row in the listing sheet before proceeding to the next household.

When informants finish listing all households located in area 1, leave them some time to

think of whether they have forgotten anybody. Ask them to take a look at their own lists to

see if any household escaped their memory. Only when you are sure all households are cap-

tured, pass to area 2 and repeat the process. Be aware that the LC1 village list may be out-

dated. It is important not to rely only on this list for information. Use the map as the main

tool for conducting the exercise and helping the LC1 and VHTs think through the most cur-

rent list of households.

MAKE SURE the village map is always visible to all informants throughout the process.

MAKE SURE you point the areas on the village map so that all informants are clear of the

area that you are about to cover.

Step 11: Once the listing is complete, tell them that you would like one of them to show you

around the village as you would like to see some of the households. Only visit the house-

holds where: (1) whose youngest child is 4 years old, or those for which the informants (2)

didn’t know whether the household had children or (3) didn’t know whether the children

were under the age of 5.

Step 12: Thank the other informants for their participation and pay them 4,000 each. Make

sure you fill in the receipts sheet and have them sign.

IF your guide remembers more households while walking through the village, MAKE SURE

to record them.


Step 13: Once you have reached a certain household, introduce yourself and ask the mother

or guardian for the age of their youngest child. Ask the mother and guardian to also show

you their youngest child. Ask the mother or guardian to also see the child’s birth card (birth

certificate) or immunisation card (basically any document that shows the age of the child

will work). Record the age of the child in the last column of the listing sheet.

IF you cannot see the birth card, ask the mother or guardian what the age of their youngest

child is. Ask them how many years and months the child is old. Record it on the last column

of the listing sheet.

IF the mother or guardian is not able to tell you the precise age of the child, then ask them

if the child has had his 5th birthday already or not. If they say that the child already had

his/her 5th birthday, then write ―>5‖ in the last column of the listing sheet. If they say

he/she has not, then write ―<5‖.

IF the mother or guardian does not know whether the child already had his/her 5th birthday,

then observe the child and use your own judgment to decide whether the child is above or

below 5. Write ―666‖ if you think the child is above 5 or ―444‖ if you think the child is below

5. Write ―888‖ if you could not see the child.

Step 14: Once you have visited all the households, thank your guide and appreciate her/him

for her/his help with 6,000. Make sure the receipt is signed.

Step 15: Make sure all your sheets are in the folder.

Step 16: You are ready to head back to the office. On your way back to the office pass by

the village where you will be heading to the next day and announce your visit to the LC1.

Make sure the LC1 understands that himself and VHTs will need to come to the meeting

with his households’ lists.

Step 17: Return to the office and hand in the folder to your Field Manager.

DATA COLLECTION INSTRUCTIONS

The village folder contains:

1. A cover sheet

2. A sheet for drawing the village map

3. 20 listing sheets

4. A receipts sheet

The following are the instructions on how to fill each of these sheets.

GENERAL VERY IMPORTANT RULES ON HOW TO COMPILE THESE DATA:

Write your answers INSIDE of the boxes. All the listing sheets will be

scanned and the information will be read electronically. Anything that you

write outside of the boxes will not be read by the computer.

Write CLEARLY. You can write in upper or lower case. Choose the way that

your handwriting looks clearest.


1. Cover sheet

This contains the following pre-filled information: district, district ID, sub-county, sub-

county ID, parish, parish ID, village and village ID.

The following table contains the instructions on how to fill in the fields of the cover sheet

that are not pre-filled:

FIELD INSTRUCTIONS

ENUMERATOR ID Write your enumerator ID number. Ask your Field Manager for

it.

ROLE Write whether the informant is a VHT, LC1 or Secretary for

Women’s Affairs.

FIRST NAME (CHRISTIAN

NAME)

Write the person’s Christian name.

SURNAME Write the person’s surname.

ANY OTHER NAME Write any other name the person is known by, if any. This

could be a pet name.

PHONE NUMBER 1 Write the phone number the person can be reached at.

PHONE NUMBER 2 Write the other phone number the person can be reached at.

DIRECTIONS TO THE VIL-

LAGE

Describe how to get to this village from the closest town or the

closest trading centre. Please bear in mind that the directions

that you are giving will be used by enumerators during the

baseline exercise. While describing, imagine to be giving direc-

tions to somebody who is not familiar with this area and needs

to visit this village for the first time.

COMMENTS Write a comment on how the listing exercise went.

DATE (DD/MM/YYYY) Write the day (2 digits) and the month (2 digits)

Example: The 2nd of June will be written as 02/06/2014

START TIME Write the hour (2 digits) and the minutes (2 digits) in which

you begin the exercise.

Examples: 09:15, 11:45, 01:55

END TIME Write the hour (2 digits) and the minutes (2 digits) in which

you end the exercise. This will be time in which you are ready

to leave the village, after having visited the households.

Examples: 07:45, 05:00, 06:30

2. Blank page for the village map

The first step of the listing exercise is to draw a village map with the help of the informants.

MAKE SURE you draw a compass on a corner of the page so that the sense in which your

map is to be read is understandable.

The map needs to be very precise and easily readable.

Particularly, you need to indicate on it: landmarks (such as schools, churches, boreholes,

trading centres, health centres, etc…), main roads, geographical features (such as rivers,

swamps, etc…), important houses (LC1 Chairperson’s house, etc…), rich families’ houses,

etc...

After populating the map with the features just listed, you will need to divide it up in at least

4 areas, maximum 6 areas. Assign a number to each area. You will use the map to lead the

informants through the listing exercise.


3. Listing sheet

The following table contains all the fields of the listing sheet and instructions on the correct

way to fill them.

FIELD INSTRUCTIONS

DISTRICT Write the district ID that you find on the cover sheet.

SUB-COUNTY Write the sub-county ID that you find on the cover sheet.

PARISH Write the parish ID that you find on the cover sheet.

VILLAGE Write the village ID that you find on the cover sheet.

FIELD MANAGER ID Write the Field Manager ID. Ask your Field Manager for it.

ENUMERATOR ID Write your enumerator ID. Ask your Field Manager for it.

DATE (DD/MM/YYYY) Write the day (2 digits) and the month (2 digits)

Example: The 2nd of June will be written as 02/06/2014

TIME (HH:MM) Write the hour (2 digits) and the minutes (2 digits) in which

you begin writing on the sheet.

Examples: 09:15, 11:45, 01:55

(1) Cross if wrong entry Cross the box in case you wish to delete the information that

you have written in the corresponding row. If there is a mis-

take, scribble or strike in ANY column, write an ―X‖ in the box

in the leftmost column. It is okay to write as many ―X‖ marks

as necessary.

Example: If you misspell any of the names you have written,

DO NOT scribble on them, but simply cross the box at the be-

ginning of the row.

(2) First name (Christian

name) of the senior male

999=No male

777=Do not know

Write the Christian name of the senior male in the household.

This will typically be the household head. In case the household

head has passed away or abandoned the household, then you

will need to write the name of the most senior male in the

household.

(3) Surname of the senior

male

999=No male

777=Do not know

Write the surname of the senior male in the household. In case

he is best known by a pet name, write the surname on the up-

per part of the cell and the pet name in the lower part of the

cell.

(4) First name (Christian

name) of the senior fe-

male

999=No female

777=Do not know

Write the Christian name of the senior female in the household.

This will typically be the household head’s spouse. In case the

spouse has passed away or abandoned the household, then

you will need to write the name of the most senior female in

the household.

5) Surname of the senior

female

999=No female

777=Do not know

Write the surname of the senior female in the household. In

case she is best known by a pet name, write the surname on

the upper part of the cell and the pet name in the lower part of

the cell.

Household location Write the number (1-6) corresponding to the area in which the

household lives. You find this number in your village map.

(7)

Children <5?

1=YES

0=NO

777=DN

Ask: ―Does the household have children under the age of 5?‖ If the answer is ―yes‖ Write 1

If the answer is ―no‖ Write 0

If the information is not known Write 777

You must write one of these numbers (1, 0 or 777) in this col-

umn. Do not leave it blank.

(8)

Age youngest child

If the answer to (7) is ―yes‖ Ask: ―What is the age of the

youngest child?‖ Record the answer. This can be 0, 1, 2, 3 or 4.


Do not write other numbers!

Example: If they tell you the child is 1 years and a half old,

write ―2‖, do not write 1.5.

Other example: If the child is less than one month old, write 0.

We only want to know the age of the youngest child. You do

not need to record the ages of the other children under five

years. If the answer to (7) is ―don’t know‖ Probe whether the in-

formants don’t know whether the household has children, or

whether they don’t know if the children are under the age of 5.

In case they say the household have children, but they are not

sure of their ages, ask them to tell you their best guess of the

age of the youngest child. Write the number corresponding to

the age. If they insist that they don’t know, write ―777‖ (don’t

know).

In case they say they don’t know whether the household has

children, then write ―777‖ (don’t know). If the answer to (7) is ―no‖ LEAVE BLANK and proceed to

question (9)

(9)

Pregnant?

1=YES

0=NO

777=DN

Ask: ―Is anybody in the household pregnant?‖ If the answer is ―yes‖ Write 1

If the answer is ―no‖ Write 0

If the information is not known Write 777

You must write one of these numbers in this column. Do not

leave it blank.

(10)

Actual age of youngest

child:

ONLY answer this question in case the answer to (8) is 4 or

777, meaning if the age of the youngest child is 4 or the VHT

did not know the age of the youngest child or whether the

household had children. Example: If the child is 4 years and 11 months old Write

4.11

If the child is 5 years and a month old Write 5.1

If you need to use your own judgment for establishing the

child’s age, write ―444‖ if you think the child is below 5, ―666‖

if you think the child is above 5, or ―888‖ if you were not able

to see the child.


Appendix 3: Survey Tools Appendix 3.A: Long household survey


Appendix 3.B: Anthropometric survey


Appendix 3.C: Health centre survey


Appendix 4: Field team roles and structure

Appendix 4.A: Field team job descriptions

Research Coordinator/ Research Associate (RC/RA): The Research Coordina-

tor/Research Associate was responsible for overseeing all study activities including survey

design, programming and budgeting related to the study including the field preparations,

management of survey teams, data quality, finances and partner relations.

Field Manager (FM): The Field Manager was responsible for the coordination of all field-

work including the direct supervision of field staff, managing field expenses, meeting data

collection targets, coordinating field logistics and inventory.

Accountability Officer (AO): The Accountability Officer was responsible to track the com-

pletion status of all surveys, document replacements, track missing surveys and works in

basic data cleaning and supporting the Field Manager where necessary.

Team Leader (TL): Each Team Leader is responsible for a team of 19 data collection staff

(displayed in Figure 1) meeting their survey number targets, transportation management,

survey material distribution and conducting occasional spot checks.

Auditor: The Auditors were responsible for conducting survey quality checks through sur-

prise ―spot checks‖ where enumerator technique is assessed as well as survey ―back

checks‖ where a household was re-surveyed to check for accuracy.

Enumerator: An enumerator was responsible for carrying out interviews and completing

the questionnaires while adhering to the data collection protocols. This study had three dif-

ferent types of enumerators including:

Household Enumerator: Collected 4.5 one and a half hour-long household surveys

per day.

Health Centre Enumerator: Collected 1 two to three hour-long survey each day

Anthropometric Enumerator: Collected height, weight and Middle-Upper Arm Circum-

ference (MUAC) measurements for every child under five within households after the

household enumerators had visited and successfully collected a survey, however this

survey was sometimes collected first in order to meet targets

Mobiliser: A mobiliser was responsible to schedule all household and health centre survey

appointments the day prior to the survey taking place to ensure that the correct respondent

is available. The mobilisers were also responsible for collecting the Health Centre Mobilisa-

tion survey gathering ―surprise‖ information about the clinic and staff presence.

Trackers: A tracker was responsible to collect household surveys that were not completed

on the first day of the survey. One tracking visit was made to each household and if the

respondent was not available, they were replaced.


Appendix 4.B: Team Organisational Structure

Chart A: North Region Team

Research Coordinator: Paola Elice

Senior Field Manager:

Douglas Kaziro

Accountability Officer: Azizi Bunyinza

Team Leader 1: Benard Okello

12 Household Enumerators

3 Anthro Enumerators

1 Health Centre Enumerator

2 Mobilisers

1 Tracker

Team Leader 2: Bruce Orech




2 Mobilisers

1 Tracker

Team Leader 3: Martin Atyera




2 Mobilisers

1 Tracker

Auditor 1: Rubangakene

Simon

Auditor 2: Nyeko Xavier

Francis


Chart B: West Region Team

Research Associate: Laura Schmucker

Field Manager: Joshua Bwirra

Accountability Officer: Alex Mwesigwa

Team Leader 1: Mathew Kato




2 Mobilisers

1 Tracker

Team Leader 2: Amon Natukwatsa




2 Mobilisers

1 Tracker

Team Leader 3: Joseph Karuma




2 Mobilisers

1 Tracker

Auditor 1: Innocent Mwesigye

Auditor 2: Kyomugisha Anne


Chart C: East Region Team - Tororo




Team Leader 1: Caroline Nyaburu




2 Mobilisers

1 Tracker

Team Leader 2: Dominic Okecho




2 Mobilisers

1 Tracker

Team Leader 3: Epalati William




2 Mobilisers

1 Tracker

Auditor 1: Wendo Jean

Auditor 2: Aguga Sharon


Chart D: East Region Team – Manafwa




Team Leader 1: Ajilong Juliet




2 Mobilisers

1 Tracker

Team Leader 2: Wamai John

Poul




2 Mobilisers

1 Tracker

Auditor 1: Namulanda John

Auditor 2: Namunane Jacqueline


Chart E: East Region Team - Katakwi/Bukedea



Senior Field Manager: Douglas Kaziro Field Manager: Joshua Bwirra

Accountability Officer: Alex Mwesigwa & Azizi

Bunyinza

Team Leader 1: Ajilong Juliet




2 Mobilisers

1 Tracker

Team Leader 2: Emulu Edmund




2 Mobilisers

1 Tracker

Auditor 1: Emma Odeke

Auditor 2: Maurice Okoed

Chart F: Innovations for Poverty Action Uganda National Office Staff Structure

Country Director: Daniele Ressler

Research Manager :

Kyle Holloway

Survey Coordinator:

Vianney Mbonigaga


Research Associate: Laura

Schmucker


Accountability Officer, Team Leaders,

Auditors, Mobilisers, Enumerators

Senior Field Manager:

Douglas Kaziro

Accountability Officer, Team Leaders,

Auditors, Mobilisers, Enumerators

Research Programmemer:

Lenny Gichia

Senior Data Manager: Ezra Rwakazooba

Finance & Accounting

Manager: Samuel Kalule

Finance Assistant: Robert

Maiku

Deputy Country Director: Dickson

Malunda

Human Resource / Operations Manager:

Florence Anena

Administrative Assistant: Joan

Atwine

Receptionist: Barbara

Wanyana

Office Assistant

(2 positions)

Security Guard (1 position)

Appendix 5: Baseline Data Collection and Implementation Gantt Chart

Version 14-Jun-15

m m !

!

#District Partner

# HCs with

intervention1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4

1 Agago GOAL 24 D m m m m !

2 Apac HEPS 18 D m m m m

3 Bukedea FOC-REV 4 D m m m m m m

4 Bundibigyo KRC 12 c D m m m m

5 Gulu HEPS 29 D m m m m

6 Kabarole KRC 26 D m m m m m m ! ! m m ! !

7 Katakwi FOC-REV 12 D m m m m ! ! ! m m

8 Kibaale KRC 23 D m m m m

9 Kitgum MUCOBADI 11 c c D m m m m

10 Lamwo MUCOBADI 13 c c D m m m m

11 Lira HEPS 11 D m m m m ! ! ! m m ! !

12 Manafwa FOC-REV 8 D m m m m m m ! !

13 Mubende KRC 34 D m m m m

14 Nakaseke HEPS 11 D m m m m

15 Pader MUCOBADI 16 D m m m m m m !

16 Tororo FOC-REV 31 D m m m m ! !

283

m

m

Mirroring the 4 weeks without field activities in Mid Dec - Mid January, we expect no follow-ups from Mid June - Mid July

ACT Health Consortium - Consolidated Gaant Chart of Major Benchmarks Baseline to Midline

Further information & Assumptions

F/U in holiday period

time for mobilisation time for mobilisation

COLOUR &

SYMBOLS

KEYS

1st cycle not complete before 12 month survey

Must start follow-up before phase 1 done

Oct-15 Nov-15 Dec-15Apr-15 May-15 Jun-15 Jul-15

DFID review

Aug-15 Sep-15

D: CRC data received Basel ine Midline6-month f/u

Feb-15 Mar-15Aug-14 Sep-14 Oct-14 Nov-14

Hol idaysPhase 1 community activi ty

Dec-14 Jan-15

Follow-up dialogues/interfaces happen 6 months so the follow-up activities will span almost as much time as initial activities, just that there are fewer activities

Follow-up also requires mobilisation

There are a number of factors that prevent us from being able to precisely determine the exact end date of the first round of activities - we shall have to update this on a quarterly basis

Phase 1 community activities (see tab P2, P3, P4 detailed steps)

Follow-up

Time to follow-up is marked from the last dialogue/interface

As each HC completes phase 1 community activities, we will plot the specific follow-up meeting in detailed implementation plans

When baseline data is confirmed complete, we alert field teams that they can do the district introduction of the programme. At the same time, GOAL processes CRCs

Mobilisation activities. Once started, we want the process to be continuous. So, we need to build in mobilisation time in beginning of 2015 also.

P2 (separate dialogues) takes approximately 5 weeks from mobilisation to community dialogue

P3 (interface only) takes approximately 3 weeks from mobilisation to interface

P4 (full programme) takes approximately 6 weks from mobilisation to interface

Appendix 6: Intervention Resources Appendix 6.A: CRC Template

Appendix 6.B: Full treatment procedure manual

Appendix 7: Midline Gantt Chart

GOAL ACT Health Study, Uganda

IPA Midline Work Plan (as of May 5, 2015)

Midline funding period June 1, 2015 - May 31, 2016

Note: District midline survey data collection timeline is subject to change - this will be discussed and agreed with GOAL based on implementation timeframes and to optimise RCT

Midline timeframe

2015 2016

Activities Responsible position Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr May

- Baseline report refinements/additions and dissemination RA/RC x

- Local Insitutional Review Board (IRB) Application RA/RC x x

- IPA Institutional Review Board (IRB ) Application RA/RC x x

- Operationalise survey budget and train project staff on project finances

RA/RC

x

- Procurement (Test/Purchase of SECA scales, height boards, PDA, MUAC tapes)

RA/RC x

- Conduct planning to ensure field security (hotels, boda/matatu driver contracts, locations)

RA/RC

x

- Design survey questionnaires (Community, Health Centre, An-thropometric)

RA/RC x

- Programme survey questionnaires (Community, Health Centre, Anthropometric)

RA/RC/IPA Research Pro-grammer

x

- Prepare survey manuals and data collection protocols RA/RC

x

- Prepare respondents tracking system RA/RC

x x

- Prepare Data Quality Control Plan (high frequency checks, weekly enumerators' checks, back-checks, spot-checks)

RA/RC

x x

- Recruitment - East team (Katakwi, Bukedea, Manafwa) RA/RC/IPA Field Managers

x

- Training & Finalise hiring - East team: Bukedea, Katakwi, Manafwa

RA/RC/IPA Field Managers

x

- Survey implementation - East team: Bukedea, Katakwi, Manafwa


x x

Data collection in Bukedea

x

Data collection in Katakwi

x x

Data collection in Manafwa

x

- Recruitment - Tororo team (Tororo) RA/RC/IPA Field Managers

x

- Training & Finalise hiring - Tororo team RA/RC/IPA Field Managers

x


- Survey implementation - Tororo RA/RC/IPA Field Managers

x

Data collection in Tororo

x

- Recruitment - West&Central team (Kabarole, Bundibugyo, Kibaale, Nakaseke, Mubende)


x

- Training & Finalise hiring - West&Central team RA/RC/IPA Field Managers

x

- Survey implementation - West&Central RA/RC/IPA Field Managers

x x x

Data collection in Kabarole

x

Data collection in Bundibugyo

x

Data collection in Kibaale

x

Data collection in Mubende

x x

Data collection in Nakaseke

x

- Recruitment - North team (Lira, Pader, Apac, Kitgum, Lamwo, Agago, Gulu)


x

- Training - North team RA/RC/IPA Field Managers

x

- Survey implementation - North RA/RC/IPA Field Managers

x x x x

Data collection in Lira

x

Data collection in Pader

x x

Data collection in Gulu

x x

Data collection in Lamwo

x

Data collection in Kitgum

x

Data collection in Agago

x x

Data collection in Apac

x

- Budget reconciliation (Budgeted vs. Actual) RA/IPA Finance & Accounting Manager

x

- Produce district level reports RA/IPA US HQ-based RA

x x - Data Cleaning RA/IPA US HQ-based RA

x x x x

- Data Analysis: Phase I - Primary treatment outcomes (includ-ing a comparison between treatment groups)

RA/IPA US HQ-based RA

x x

- Midline report writing RA/IPA US HQ-based RA

x x

- Data Analysis: Phase II - Theory/Mechanisms behind detected effects

RA/IPA US HQ-based RA

- Midline report dissemination RA

- Field validation workshop RA/Principle Investigator Team/GOAL implementators

- Data Analysis: Phase III - Comparison to P2P RA/IPA US HQ-based RA


Appendix 8: Additional Balance Checks

Figure 8.A compares balance between the treatment groups receiving the information and mobilisation intervention, versus those that

did not.

Figure 5.a: Balance with regard to T1 (information & mobilisation)

Mean T1=1 Mean T1=0 Difference in

means

P-value N T1=1 N T1=0

Health

centre

survey

Separate maternity ward 1.46 1.47 -0.01 0.85 186 192

SE 0.04 0.04

Public Health Care funds re-

ceived

5,610.28 5,703.5 -93.22 0.98 158 163

SE 2,048.71 2,662.9

Health Centres with piped wa-

ter source

0.14 0.13 0.01 0.74 186 192

SE 0.03 0.02

Average number of stockouts in

past 3 months

0.39 0.43 -0.04 0.44 186 192

SE 0.04 0.04

House

-hold

survey

Deaths of children under 5

years old

0.02 0.02 0 0.98 7,791 7,860

SE 0 0

Equipment used during exami-

nation

-3.28 -5.15 1.87 0.06 5,913 6,096

SE 0.69 0.73


Figure 8.B compares balance between the treatment groups receiving interface meetings versus those that did not.

Figure 5.b: Balance with regard to T2 (interface meetings)

Mean T2=1 Mean T2=0 Difference in

means

P-value N T2=1 N T2=0

Health

centre

survey

Separate maternity ward 1.47 1.46 0.01 0.84 190 188

SE 0.04 0.04


ceived

8,282.48 2,878.33 5,404.15 0.11 156 165

SE 3,232.44 261.11


ter source

0.13 0.14 -0.01 0.91 190 188

SE 0.02 0.02

Average number of stockouts

in past 3 months

0.43 0.39 0.04 0.41 190 188

SE 0.04 0.04

House

-hold

survey


years old

0.02 0.02 0 0.24 7,844 7,807

SE 0 0


nation

-4.67 -3.73 -0.94 0.35 5,980 6,029

SE 0.66 0.76


Figure 8.C compares balance between the full treatment group (the information and mobilisation + interface) and the pure control.

Figure 5.c: Balance with regard to T1 (full programme) and T4 (pure

control)

Mean pure

control (A1)

Mean full pro-

gramme (A4)

Difference in

means A1-A4 P-value N (A1) N (A4)

Health

centre

survey

Separate maternity ward 1.44 1.44 0 0.99 95 93

SE (0.05) (0.05)


ceived 8226.48 2929.46 -5297.02 0.2 84 77

SE (3955.9) (435.27)


ter source 0.15 0.14 -0.01 0.88 95 93

SE (0.04) (0.04)

Average number of stockouts

in past 3 months 0.42 0.42 0 0.98 95 93

SE (0.05) (0.05)

House

-hold

survey


years old 0.02 0.02 0 0.42 3917 3901

SE (0) (0)


nation -4.13 -5.08 -0.95 0.5 3044 2928

SE (0.9) (1.1)

Note: (1) SE refers to Standard Error (2) Units of PHC funding are in 1,000 UGX (3)…

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