1. Examining the links between staff flexibility, workload, and service delivery in the context of SRH and HIV service integration S. Sweeney, C.D. Obure, F. Terris-Prestholt, C. Michaels, C. Watts, the Integra Research Team, A. Vassall

2. Background: Integration of HIV and SRH services may yield improvements in efficiency Economies of scope Economies of scale Despite a clear rationale for integration, there is scarce evidence on the costs and potential efficiency gains of integrated service provision

3. Methods (1) Baseline: 2008-09 Endline: 2010-11 Kenya: 24 public facilities, 6 private facilities Swaziland: 8 public facilities, 2 private facilities Core MCH services: family planning (FP), post-natal care (PNC), antenatal care (ANC) Non-core services: STI management (STI), voluntary HIV testing and counselling (VCT), provider-initiated HIV testing and counselling (PITC), cervical cancer screening (CaCx), and HIV treatment and care

4. Methods (2): Data Sources Key informant interviews with staff, time sheets and direct observations of services Staff time was allocated as a percentage of clinical staff full-time equivalency (FTE) according to service mix and time use Workload was estimated as the number of outpatient visits per clinical staff FTE per day Process and output data collected from routine monitoring registers Service was considered ‘present’ if > 10 visits recorded per year, and if staff FTE was > 0

5. Methods (3): Data Analysis Objectives: Observe the improvements in resource integration from baseline to endline Identify the relationship between non-core service availability and human resource integration Evaluate the effect of improvements in integration on staff workload Data analysed in Stata and Excel Due to small sample sizes and potential confounding factors, this analysis is descriptive

6. Resource Integration Indicators Human Resource Integration Physical Resource Integration Service Availability in the MCH Unit Service Availability in the Facility Example: HIV Testing and Counselling <--- More integratedLess integrated ---> HCT conducted for all MCH clients within MCH unit, by MCH nurses MCH clients referred to a separate HCT unit, staffed by HCT counsellor or lab technician HCT referred out to a separate facility

7. RESULTS

8. Changes in Resource Use Indicators from Baseline to Endline

9. Changes in Resource Use Indicators from Baseline to Endline (2)

10. Improvements in Resource Integration from Baseline to Endline

11. INCREASE IN SCOPE

12. Increase in Scope: Which services are added / dropped?

13. Increase in Scope: Patterns in Human Resource Integration

14. CHANGES IN WORKLOAD

15. Variation in staff workload

16. HR Integration and staff workload

17. Changes in Staff Workload and HR Integration

18. Implications for policy Integration was not scaled up uniformly; readiness assessment should precede integration policy PITC, cervical cancer screening and STI services can potentially be more easily incorporated into MCH unit Integration may be a way to improve workload in underworked facilities However, policy makers should also be careful about overworking staff in the context of supplier-induced demand

19. Acknowledgements Ministry of Health, Swaziland Ministries of Health, Kenya Family Health Options Kenya (FHOK) Family Life Association of Swaziland (FLAS) Learn more at: www.integrainitiative.org Support for this study was provided by the Bill & Melinda Gates Foundation. The views expressed herein are those of the author(s) and do not necessarily reflect the official policy or position of the Bill & Melinda Gates Foundation For a copy of this presentation please visit same.lshtm.ac.uk

21. Changes in integration indicators over time: very little change on aggregate level Service Availability in MCH/FP Unit (out of 5) Service Availability in Facility (out of 8) Human Resources Integration (out of 5) Physical Resources Integration (out of 5) 2008-2 009 2010- 2011 Differen ce 2008- 2009 2010- 2011 Differen ce 2008- 2009 2010- 2011 Differen ce 2008- 2009 2010- 2011 Differen ce Country Kenya (n = 30)2.232.300.076.106.560.431.881.920.041.29 0.00 Swaziland (n = 10)2.202.300.106.707.000.301.361.00-0.361.151.18-0.03 Facility Type Hospital (n = 2)3.00 0.008.00 0.002.771.79-0.990.980.59-0.39 District Hospital (n= 5)2.202.400.207.80 0.001.942.330.391.370.89-0.48 Sub District Hospital (n = 6)2.001.83-0.176.33 0.002.001.75-0.261.161.03-0.13 Health Centre (n = 17)1.411.520.125.356.180.82*1.151.210.080.710.960.25* Public Health Unit (n = 2)2.503.000.505.506.501.000.770.35-0.56*0.880.80-0.08 SRH Clinic (n = 8)3.87 0.006.87 0.002.722.54-0.172.572.610.03 Model FP (n = 12)2.422.500.086.586.860.252.312.410.091.271.230.04 PNC (n = 20)1.451.550.105.806.490.651.030.92-0.110.720.750.03 SRH (n = 8)3.87 0.006.87 0.002.722.54-0.172.572.610.03 Location Rural (n = 23)1.561.610.045.616.240.61*1.371.35-0.010.830.970.15 Urban (n = 17)3.123.230.127.127.240.122.262.13-0.131.831.65-0.18 Ownership Type Private (n = 8)3.87 0.006.87 0.002.722.54-0.172.752.61-0.03 Public (n = 32)1.811.920.096.096.630.501.511.47-0.350.92 0.00

22. Increase in Scope: Impact on Utilization

23. Variation in Facility Outputs

24. Average Change in Staff Workload 2008-20092010-2011 p value (t-test) F ratio (p value) (ANOVA) Country 0.86 (0.36) Kenya (n = 30) 17.4215.170.32 Swaziland (n = 10) 13.8115.360.68 HR Integration 2.04 (0.16) Least change (n = 29) 17.7214.880.19 Most change (n = 11) 13.3416.090.50 Facility Type 4.71 (0.00) Hospital (n = 2) 10.7124.870.52 District Hospital (n= 5) 15.8615.650.95 Sub District Hospital (n = 6) 10.1116.240.13 Health Centre (n = 17) 19.4010.540.00 Public Health Unit (n = 2) 17.6021.780.68 SRH Clinic (n = 8) 16.7920.040.46 Model 0.87 (0.43) FP (n = 12) 16.2514.670.67 PNC (n = 20) 16.5713.610.27 SRH (n = 8) 16.7920.040.46 Location 6.51 (0.01) Rural (n = 23) 16.9712.030.04 Urban (n = 17) 15.9019.520.21

25. Variation in staff workload