Guinness, L

Jacobs, R

Obure, CD

Vassall, A

LSHTM Research Online

Obure, CD; Jacobs, R; Guinness, L; Vassall, A Technical efficiencyof integrated HIV and sexual reproductive health services in low andmiddle income settings: An application of data envelopment anal-ysis. In: 9th World Congress on Health Economics: CelebratingHealth Economics, IHEA, July 7-10, 2013, Sydney, Australia. (Un-published)Downloaded from: http://researchonline.lshtm.ac.uk/1343415/DOI:Usage GuidelinesPlease refer to usage guidelines at http://researchonline.lshtm.ac.uk/policies.html or alterna-tively contact researchonline@lshtm.ac.uk.Available under license: http://creativecommons.org/licenses/by-nc-nd/2.5/  Technical efficiency of integrated HIV and sexual reproductive health services in low and middle income settings: An application of data envelopment analysis  Carol Dayo Obure, Rowena Jacobs, Lorna Guinness, Anna Vassall and the Integra Research Team International Health Economics Association July 9, 2013 Sydney, Australia Introduction  Well articulated rationale for integrating HIV and SRH services in low income high prevalence settings   However little remains known about the efficiency gains associated with integrating these services   Purpose of the study are:  to compare the relative technical efficiency of a sample of health facilities providing integrated HIV and SRH services in Kenya and Swaziland; and    to determine whether the level of integration of HIV and SRH services affects technical efficiency.   Data and methods Period  2008/2009 and 2010/2011 from 40 facilities in Kenya and Swaziland Data 1. Client visits for 6 HIV and SRH services, 2. Clinical and non clinical staff FTEs 3. Capital stock (building, equipment and staff training) 4. Measure of integration (Composite integration score): number of services in facility; number of services in MCH unit; range of services per clinical staff; and range of services in one consultation room. From Routine monitoring data at health facility level Analysis Two stage DEA 1. Output oriented DEA model : 3 inputs – 2 categories of labour and unit size (proxy for capital stock) and 6 outputs : numbers of HIV and SRH visits. 2. Tobit regression of bias corrected DEA scores against environmental variables: facility size (categorised by bed capacity); facility ownership (public/private); level of integration; catchment population; and proportion of HIV client visits.  Relative technical efficiency – pooled data  Observations Mean (SD) Kruskal-Wallis test (P-value) Year TE and year   1 (2008/2009) 40 0.71 (0.28)  0.3432 2  (2010/2011) 40 0.76 (0.31) Country TE and country  Kenya 60 0.68 (0.30)  0.0020 Swaziland 20 0.91(0.18) Facility size TE and facility size  Large (150 -350 beds) 14 0.84 (0.23)   0.0070 Medium (10- 90 beds) 18 0.55 (0.31) Small (< 10 beds) 48 0.78 (0.29) Ownership TE and ownership  Private  16 0.82 (0.28)  0.1206 Public 64 0.71 (0.30) Location TE and location  Urban 34 0.86 (0.22)  0.0047 Rural 46 0.64 (0.31) No of efficient units on frontier Year 1 (2008/2009) 15/40   Year 2 (2010/2011) 22/40    Determinants of efficiency Explanatory variables Coefficient t-statistic Constant 0.916 2.86    Year 2010/11 0.096 1.18 Swaziland 0.345* 1.90 Catchment population -0.024 -0.42 Proportion of HIV visits 0.383 0.92 Integration index -0.134 -1.31 Public -0.032 -0.13 Rural -0.409* -1.81 Medium facility (10-90 beds) -0.147 -0.61 Small facility (< 10 beds) 0.173 0.79    Number of observations 80 *Statistical significance at the 10% level  Conclusion  Considerable variation in TE but on average high level of TE across study sites   Associations found between TE and country, facility size and location  No clear evidence to support conventional assumption that more integrated health facilities operate more efficiently  Challenges of real world economic evaluation – other contextual factors possibly affecting efficiency of HIV/SRH service delivery Next steps  Quality dimensions to be incorporated in subsequent analysis of TE  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 

Technical efficiency of integrated HIV and sexual reproductive health services in low and middle income settings: An application of data envelopment analysis

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Technical efficiency of integrated HIV and sexual reproductive health services in low and middle income settings: An application of data envelopment analysis

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