1. Showcasing Innovation in Workforce Productivity Pathfinder Project –Gathering Health and Wellbeing Data Workshop

2. Presentation by Greater Manchester West Mental Health NHS Foundation Trust Ruth Barker, Head of Human Resources Fiona Johnson, Workforce Planning Manager

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

4. Initial Data Collection Assessment questionsPossible information source Objective 1: To determine key areas where levels of sickness absence due to mental ill health are relatively high Agree sickness absence codes to be included with mental health sickness absence definition. S23 Mental Disorders S25 Psychological S27 Stress/Anxiety S28 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/streamsESR

5. 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 health Agree 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 patients Over three days absence for violent incidence- 09/10, 10/11 and 11 to date (by quarter if possible) RIDDOR reports Degree of violence Indicate business stream Severity 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.

6. Initial Data Collection (cont.) Objective 4: Determine the organisational changes and influence that may have had an impact on mental wellbeing Project 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 managers Project 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 trust Project 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 staff Are 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 highlighting  Staff engagement scores  Physical violence from staff, patients and public in the last 12 months  Suffering from work related stress  Whether staff feel satisfied with the quality of work and patient care they are able to deliver  Having an appraisal in the last 12 months  Having E&D training in the last 12 months

7. 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)

8. Some Info had to be prepared The Trust Story Staffing and absence data.

9. Initial Data Collection Assessment questionsPossible information source Objective 1: To determine key areas where levels of sickness absence due to mental ill health are relatively high Agree sickness absence codes to be included with mental health sickness absence definition. S23 Mental Disorders S25 Psychological S27 Stress/Anxiety S28 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/streamsESR

10. 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).

12. Example of data submitted Greater Manchester West MH NHS FT 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 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

13. Local Development of data GMW 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

14. Standardised Graphs

15. Summarised Comparative Data MWB Episodes of absence per yearFTE days lost due to MWB absences per year 2009/102010/112011/12 2009/102010/112011/12 Directorate A Directorate B Directorate C Directorate D Directorate E Directorate F TOTAL Average duration of MWB episode of absenceAverage % hours lost to MWB out of all hours available 2009/102010/112011/12 2009/102010/112011/12 Directorate A Directorate B Directorate C Directorate D Directorate E Directorate F TOTAL

16. Benefits of data gathering 3 years worth of data – spot the trends Data quality – Not Known/Undisclosed Benchmarking

17. 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

18. 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)

19. 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.

20. Any Questions?