chaipi understanding the changing role of infection preventionists the columbia/apic study

CHAIPIUnderstanding The Changing Role of

Infection PreventionistsThe Columbia/APIC Study

May 7th, 2009

Patricia Stone, PhD, FAANAssociate Professor of Nursing, Columbia University

Primary Investigator, CHAIPI Study

Sarah Jordan, Study Coordinator

The CHAIPI Study

This study is designed to inform our understanding of institutional, procedural, and technological innovations that can assist health professionals in reducing and eliminating the morbidity, mortality, and high costs associated with hospital-associated infections.

The ultimate goal is to generate knowledge that will inform evidence-based decision making for health policy makers, hospital administrators, epidemiologists, and infection preventionists.

Problem

Infection Preventionists (IPs) are key to reducing HAI

The role of the Infection Preventionist is changing

– Monitor infection rates

– Monitor provider behaviors

– Intervene

– Implement

– Lead

Increased use of technology to perform role

The PNICE Study

The survey and research methodology used in the CHAIPI study are based on the Prevention of Nosocomial Infections & Cost Effectiveness (P-NICE) study

P-NICE is a three-year, two-phase study to describe infection control department staffing and interventions implemented in ICUs across the U.S. The study is conducted by Columbia University

School of Nursing and headed by Dr. Pat Stone.

PHASE I • Survey of eligible NHSN hospitals• 250 hospitals participated (450 ICUs)• 66% response rate• Completed April 2008

PHASE II• Collection of data from subsample of NHSN hospitals• Medicare and HAI data for 2007• Patient Census• RN Staffing Data

The PNICE Study

Overview of the CHAIPI IP Study

Purpose of Research

Understand the changing role of IPs

Evaluate the impact of CHAIPI on

– IP roles

– Department resources

– Infection prevention and control processes

– HAI rates

Methods

Comparison of data from two time points:– Infection control department characteristics– IP roles– Processes– HAI rates Compare CHAIPI and non-CHAIPI hospitals

Web-based surveys of infection control department staff – First survey took place from Oct 21, 2008 to Jan1, 2009– Second survey will take place in the Spring of 2010

Site visits at six hospitals to be conducted this summer

Sample:

All California acute care hospitals. Psychiatric, drug/alcohol rehab, nursing

homes, and children’s hospitals were ineligible.

Participation:– 207 hospitals participated out of 350 eligible hospitals contacted; a 59%

recruitment rate

– 45 of 51 CHAIPI hospitals contributed to the survey; a 88% recruitment rate

Infection Control Department Staffing and Resources

IP Study HospitalsHospital Demographics

N (%)Beds

Mean (SD)

Outpatient clinics Long term care Rehab

155 (75)71 (34)56 (27)

--66 (76)31 (27)

Outpatient clinics N = 155 surgery dialysisGI* radiation/oncologyphysical therapyIV therapyOutpatient other

127 (61)42 (20)86 (42)72 (35)

107 (52)63 (30)70 (34)

• Hospitals with outpatient clinics average 3.65 clinics/hospital +/-1.8.

• 176 (85%) of IP departments provide services to at least one outpatient clinic, rehab, or long term care unit.

* CHAIPI hospitals were significantly more likely to provide services to a outpatient GI clinics, 72 % vs. 51 %

Infection control departments providing services to other facilities or outpatient clinics

Utilization of Electronic Surveillance Systems

CHAIPIN = 40

Non-CHAIPIN = 163 p-value

Electronic Surveillance SystemAICEMedminedTheradocSafety Surveillor CustomOther

13 (32.5)4 (31)9 (69)1 (8)1 (8)1 (8)1 (8)

31 (20)10 (32)

00

3 (10)7 (23)

14 (45)

.10

Staff members who use the systemHospital Epidemiologist Infection PreventionistsOther

3 (23)12 (92)7 (54)

3 (10)29 (94)12 (39)

.24

.88

.36

Years since system implemented Mean (SD) 4.0 (2.0) 4.9 (3.6) .006

Utilize which of the following features:

Use built-in templates to create reports and data summaries

12 (92) 22 (73) .16

Automatic alerts 11 (85) 14 (47) .02

Integration of infection data with CDC definitions and/or reporting requirements

4 (31) 15 (50) .24

Data mining (integrated with clinical, lab, and pharmacy data)

5 (38) 11 (37) .91

Share reports with key committees and hospital administration

0 1 (3) .78

Comparison of the qualifications and experience of Infection Prevention and Control Department Staff: Infection Control Department Director

Comparison of the qualifications and experience of Infection Prevention and Control Department Staff: Infection Preventionists

Comparison of the qualifications and experience of Infection Prevention and Control Department Staff:Hospital Epidemiologists

N Mean (SD)

CHAIPI Study 2008 - CA hospitals 123 0.55 (0.53) 1 IP / 180 beds

PNICE Study 2008 - U.S. NHSN hospitals 246 0.69 (0.54) 1 IP / 144 beds

Richards et al 1999 - U.S. NNIS hospitals 227 0.87 1 IP / 115 beds

The difference between IP study and PNICE hospital staffing is significant at p < .05 after adjusting for hospital size.

Proportion of total time that Infection Preventionists spend on specific tasks

Proportion of total time that Infection Preventionists spend in specific locations

Mandatory Reporting

*Scale: 1 - much less, 5 - much more

Impact of mandatory reporting on the Infection Control department: Comparison of California and P-NICE study hospitals

IP Study hospitals

PNICE hospitals

N = 192 N = 152

Mandatory reporting has affected departmentN (%)

177 (92)N (%)

104 (71)(35 Missing / DK)

How has mandatory reporting affected the following: Mean (median)*

Influence of the department on hospital decision making 3.52 (4) 3.5 (3)

Resources to department to assist infection control 3.14 (3) 3.13 (3)

Time for routine infection control activities besides mandatory reporting

2.14 (2) 2.27 (2)

Other (e.g. more work, not enough time, not enough help) 3.9 (4) 3.4 (4)

Hospital- wide HAI Rates and Infection Prevention and

Control Policies

Hospital –wide mean monthly infection rates, data from July – Sept 2008

All IP Study HospitalsN Mean (SD) Median

CHAIPI N Mean (SD)

Non-CHAIPIN Mean (SD) p-value

BSI / 1000 patient days

98 0.57 (1.53) 0.13 20 0.67 (1.38) 78 .54 (1.57) .74

MRSA- BSI / 1000 patient days

109 0.17 (0.88) 0 20 0.10 (0.20) 89 0.18 (0.97) .44

Hand hygiene practices and leadership involvement

• 97% of hospitals report monitoring hand hygiene, the majority by observation.

• 60% report that hand hygiene is practiced correctly more than 75% of the time

N = 185 N (%)

Hand Hygiene Practices: Antiseptic agent in rooms or high workload areas 177 (96) Educational and reminder posters 17 (92) Education materials given to patients/visitors 123 (67) Provide real-time feedback to employees 113 (62) Education seminars/videos for staff 108 (59) Reward/administrative sanctions 41 (22) Other 24 (13)

Leadership involvement: Including hand hygiene in strategic goals 90 (49) Model hand hygiene during leadership rounds 61 (33) Leading morning huddles 9 (5) Other 21 (11)

Policies on Infectious Agents

Hospital Wide MRSA Policies: N = 168

Written PolicyN (%)

Implemented Correctly

N (%)

Implement contact precautions for patients with positive cultures for MRSA

161 (96) 89 (55)

Cohort patients colonized with MRSA in the same room 130 (77) 34 (26)

Implement presumptive isolation/contact precautions pending a MRSA screen

70 (42) 23 (33)

Policies on Surveillance CulturesN = 164 N (%)

Collect a surveillance culture upon hospital admission 57 (35)

If yes, for which patients?All admissions (excluding L&D)Readmissions within 30 days Transfers from nursing homesICU patientsDialysis patientsOther

10 (18)10 (18)24 (42)38 (67)17 (30)28 (49)

Surgical Site Infection Prevention Policies

Implemented correctly is defined as 95% of the time or better. Implementation percentages are a proportion of hospital swith a written policy. Hospitals without policies did not report implementation rates.

ICU HAI Rates and Infection Prevention and Control

Policies

Infection rates in ICUS: Comparison of the Rates of Device Associated Infections by ICU Type to national NHSN data

IP Study Sample NHSN1

N Mean (SD) Median N Mean MedianCentral Line Associated Blood Stream Infection (CLBSI)

Medical ICU 15 2.1 (2.2) 1.9 144 2.4 1.9

Medical/ Surgical

87 2.3 (3.5) 0.9104 (teach) 2 1.5

343 (other) 1.5 0.6

Ventilator Associated Pneumonia (VAP)Medical ICU 11 1.8 (2.6) 0 93 2.5 1.9

Medical/ Surgical

89 2.6 (4.4) 079 (teach) 3.3 2.3

187 (other) 2.3 1.5

Catheter Associated Urinary Tract Infection (CAUTI)

Medical ICU 6 2.4 (3.7) 0 68 4.1 3.7

Medical/ Surgical

36 3.2 (3.4) 2.059 (teach) 3.3 2.9

130 (other) 3.1 2.6

1 Edwards JR, Peterson KD, Andrus MA, Dudeck MA, Pollock DA, Horan TC. National Healthcare Safety Network (NHSN) Report, data summary for 2006 through 2007, issued November 2008 , Am J Infect Control 2008;36 609-626

Central Line Associated Blood Stream Infection Prevention Policies


Ventilator Associated Pneumonia Prevention Policies


Catheter Associated Urinary Tract Infection Prevention Policies


Next Steps

Qualitative Site Visits

• Visiting six CHAIPI hospitals, two from each cohort

• Late June – August 2009

• Research team will conduct one hours interviews with infection control department personnel, the administrator who oversees the department, and one ICU manager

• The goal of site visits is to gain a more in-depth understanding of the changes and challenges affecting infection control professionals and their daily activities

• Currently recruiting hospitals

TimelinePapers from Survey 1 are in development

– Description of staffing and IP time use – Use of surveillance procedures and contact precautions and their impact on MRSA rates– Overview of utilization of ESS

Dissemination 2010– Scientific abstracts and publications– APIC 2010 session– Prevention strategist article– Webinar– Press releases– Key legislative committees

Goal is to change practice based on

best evidence!

http://cumc.columbia.edu/studies/pnice/chaipi

chaipi understanding the changing role of infection preventionists the columbia/apic study

Documents

eligible hospitals

infection control departments

impact of chaipi

chaipi ip studypage

chaipi studysarah jordan

twophase study

outpatient clinics n

outpatient clinics average