Showcasing Innovation in Workforce Productivity

Pathfinder Project –Gathering Health and Wellbeing Data Workshop

Presentation by

Greater Manchester West Mental Health NHS Foundation Trust

Ruth Barker, Head of Human ResourcesFiona Johnson, Workforce Planning Manager

Introduction

• Overview of the Project• Why we are here today• Our aims as participants in the project• Timescales past and future

Initial Data Collection

Assessment questions Possible information sourceObjective 1: To determine key areas where levels of sickness absence due to mental ill health are relatively highAgree sickness absence codes to be included with mental health sickness absence definition.

 S23 Mental DisordersS25 PsychologicalS27 Stress/AnxietyS28 Substance/Alcohol Misuse

All absence data to cover 09/10, 10/11 and 11 to date (nearest quarter)

ESR

Community and Inpatient split for above time periods, n.b. may need to sum to 6 month intervals or longer if numbers are small

ESR

Banding split for above quarters for mental health sickness absence

ESR

Separate quarters as above for business teams/streams ESR   

Initial Data Collection (cont.)Objective 2: Determine the take up of in-house services aimed at staff who are suffering mental ill health and the pattern of their take up by staff who have mental ill healthAgree OH services included e.g. counseling (indicate which type), PTSD interventions, and psychology and psychiatry interventions and mental health EAP interventions where available. Include numbers within time periods as above, any breakdown possible by business stream/band/inpatient/community/ geographical area (where a potential issue due to access issues) Separate, if possible, management and self-referral. Ideally extract the length of absence against intervention type, if there is more than one. Aware this may be skewed, as may be hierarchy of interventions. (Can compare to average length of absence-useful for business case)Would also be useful to know length of absence for management and self –referral, if services can be accessed by both routes. 

 OH service delivery data. (If more than one supplier may need o agree proforma for them to complete, as data is unlikely to represented in a similar format between suppliers)Counseling service data (may be separate to above if on a separate contract)EAP data where applicable  

Objective 3: Determine the impact on mental health sickness absence from violent incidences whilst at work from patientsOver three days absence for violent incidence- 09/10, 10/11 and 11 to date (by quarter if possible)

RIDDOR reports

Degree of violenceIndicate business streamSeverity rating (and match against an average absence, or average per incidence and we can sum from raw data.)

Incidence severity ratings.  Identify men length of absences following each category of violent incidence, over the last year.

Initial Data Collection (cont.)Objective 4: Determine the organisational changes and influence that may have had an impact on mental wellbeingProject manager to write a brief ‘story’ of the trust over the last 5 years, with assistance from project steering group members

Written report

Objective 5: Determine level of policy information available to staff and managersProject steering groups to identify trust policies that potentially have an impact on mental wellbeing

List of policies highlighted with those considered to have a direct impact and with another colour those considered to have an indirect impact

Objective 5: Determine level of training aimed at improving mental wellbeing within the trustProject Steering Group to identify mandatory and optional training available to staff and managers, that have an impact on mental wellbeing.

List of training available highlighted with those considered to have a direct impact and with another colour those considered to have an indirect impact

Objective 6: Determine the self reported mental wellbeing of staffAre staff reporting a decrease in mental wellbeing over time of vice versa? Are staff survey results reflected in other data?  

Staff survey results- utilize the most up to date and 2 years previous to that date. Supply copies of reports highlightingStaff engagement scoresPhysical violence from staff, patients and public in the last 12 monthsSuffering from work related stressWhether staff feel satisfied with the quality of work and patient care they are able to deliverHaving an appraisal in the last 12 monthsHaving E&D training in the last 12 months

Most Information was to Hand• Occupational Health &

Counselling• RIDDOR• Relevant Policies (10)• Staff Survey Results• Training Provision• Organisation Charts

• Strategic Workforce Plan

• GMW Drivers for Change

• Staff in Post data• Grade Mix data

(Christmas Trees)

Some Info had to be prepared

• The Trust Story• Staffing and absence data.

Initial Data Collection

Assessment questions Possible information sourceObjective 1: To determine key areas where levels of sickness absence due to mental ill health are relatively highAgree sickness absence codes to be included with mental health sickness absence definition.

 S23 Mental DisordersS25 PsychologicalS27 Stress/AnxietyS28 Substance/Alcohol Misuse

All absence data to cover 09/10, 10/11 and 11 to date (nearest quarter)

ESR

Community and Inpatient split for above time periods, n.b. may need to sum to 6 month intervals or longer if numbers are small

ESR

Banding split for above quarters for mental health sickness absence

ESR

Separate quarters as above for business teams/streams ESR   

Electronic Staff Record• Reference Period• Absence data required in respect of each quarter in:• 2009/2010, 2010/2011, and 2011 (to quarter ending Dec 2011).• Types of Absence• Current ESR reasons• S10 – Anxiety/Stress/Depression/Other Psychiatric Illness• S32 – Substance Abuse• Previous ESR Reasons• Mental Disorders• Psychological• Stress/Anxiety• Substance/Alcohol Misuse• Data Required• In respect of each type of absence and in total:• Number of people who have had an occurrence of absence, instances of absence, FTE days lost, calendar days lost,

percentage time lost• Presentation of Data• Data to be presented to allow analysis by Directorate, by in-patient and by community, by gender, by pay-band (sub

divided by review/non-review body XR/XN).

Example of data submittedGreater Manchester West MH NHS FTTrust Total

Staff in Post Headcount

Staff in Post FTE

MWB Episodes

MWB Calendar Days Lost

MWB FTE Days Lost

All Sick Episodes

All Sick Calendar Days Lost

All Sick FTE Days Lost

Q1 09/10 Q2 09/10 Q3 09/10 Q4 09/10 Q1 10/11 Q2 10/11 Q3 10/11 Q4 10/11 Q1 11/12 Q2 11/12 Q3 11/12 Q4 11/12 Q1 12/13

Local Development of dataGMW Pathfinder Project - Mental Well Being. All data from ESR

Trust Total

Staff in Post Headcount

Staff in Post FTE

MWB Episodes

MWB Calendar Days Lost

MWB FTE Days Lost

All Sick Episodes

All Sick Calendar Days Lost

All Sick FTE Days Lost

MWB FTE days lost per FTE

employee

Average FTE duration of a MWB sickness episode

Q1 09/10 Q2 09/10 Q3 09/10 Q4 09/10 Q1 10/11 Q2 10/11 Q3 10/11 Q4 10/11 Q1 11/12 Q2 11/12 Q3 11/12 Q4 11/12 Q1 12/13

Standardised Graphs

Summarised Comparative DataMWB Episodes of absence per year FTE days lost due to MWB absences per year

2009/10 2010/11 2011/12 2009/10 2010/11 2011/12Directorate A Directorate A Directorate B Directorate B Directorate C Directorate C Directorate D Directorate D Directorate E Directorate E Directorate F Directorate F TOTAL TOTAL

Average duration of MWB episode of absence Average % hours lost to MWB out of all hours available

2009/10 2010/11 2011/12 2009/10 2010/11 2011/12Directorate A Directorate A Directorate B Directorate B Directorate C Directorate C Directorate D Directorate D Directorate E Directorate E Directorate F Directorate F TOTAL TOTAL

Benefits of data gathering

• 3 years worth of data – spot the trends• Data quality – Not Known/Undisclosed• Benchmarking

Next Steps

• Analysis of increase in occurrences of absence• Obtain consistent data from ESR, Occ Health and

RIDDOR• Which data is of most use to Directorates and

preparation of data pack for each.• How do we identify where to target interventions• How do we identify most effective interventions

Things we would do differently

• Align all data sources as far as possible (Occ Health, RIDDOR)

• Trust story – would have done by Directorate, with more detail (objective explanation of data)

Conclusions

• Be absolutely clear on what you are gathering – define your data requirements precisely.

• Outline your Organisation’s history in detail.• Check the data you receive from OH, EAPs etc• Data requirements of project differed from

those of line managers.• Remember data is the means to an end.

Any Questions?