estimating the relationship between financial and non-financial incentives on health worker...
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Estimating the relationship between financial and non-financial incentives on health worker motivation: a national study in Malawi Allison Goldberg, Associate November 3, 2012. Presentation Outline. Background Study Methodology Results Policy Implications What’s Next? . Background. - PowerPoint PPT PresentationTRANSCRIPT
Estimating the relationship between financial and non-financial incentives on health worker motivation: a national study in Malawi
Allison Goldberg, AssociateNovember 3, 2012
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Presentation Outline Background Study Methodology Results Policy Implications What’s Next?
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Background Malawi has some of the worst health worker to population ratios in
the world. In 2003, it was estimated that ~ 4000 doctors, nurses, and midwives were serving a population of ~ 12 million.*
In 2004, the MOH of Malawi launched the 6-year Emergency Human Resources Programme (EHRP) to increase the number of health workers primarily through 52 percent salary top-ups.**
An evaluation of the EHRP showed the programme to be effective. Across 11 priority cadres, the total number of health workers increased by 53 percent – from 5,453 in 2004 to 8,369 in 2009.*
A strategy to retain and maximize Malawi’s newly scaled-up workforce was not developed.
* Manafa O, McAuliffe E, Maseko F. et al. 2009. Retention of health workers in Malawi: perspectives of health workers and district management. Human Resources for Health 7: 65
** DFID. July 2, 2010. Evaluation of Malawi’s Emergency Human Resources Programme (EHRP): EHRP Final Report. Produced by Management Sciences for Health (MSH) and Management Solutions Consulting (MSC) Limited.
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Background (cont’d) Why Study Motivation?
Researchers and policy-makers recognize that a motivated health workforce is critical to job retention and service delivery performance*
Financial and non-financial incentives have been shown to improve health worker motivation at the aggregate level in SSA.* This relationship is less clear in Malawi.
State Capacity
International Donors
Financial & Non-Financial
IncentivesMotivation
RetentionService Delivery
Performance
HealthOutcomes
•Manafa O, McAuliffe E, Maseko F. et al. 2009. Retention of health workers in Malawi: perspectives of health workers and district management. Human Resources for Health 7: 65 World Health Organization (WHO). 2006. The World Health Report – Working Together For Health. Geneva: World Health Organization.Franco LM, Bennett S, and Kanfer R. 2002. Health sector reform and public sector health worker motivation: a conceptual framework. Social Science & Medicine 54: 1255-66.Wibulpolprasert S and Pengpaibon P. 2003. Integrated strategies to tackle the inequitable distribution of doctors in Thailand: four decades of experience. Human Resources for Health 1: 12.Willis-Shattuck M, Bidwell P, Thomas S et al. 2008. Motivation and retention of health workers in developing countries: a systematic review. BMC Health Services Research 8: 247.
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Study Methodology Study Design
Survey conducted by the USAID-funded from October to December 2010
Data was collected from 163 health facilities across Malawi’s 27 districts
Health facilities from the public, private for-profit, and faith-based sectors (CHAM) were sampled using an equal-probability, systematic sampling design
Up to 4 health workers were interviewed per facility, allowing for a maximum of 640 health workers to be selected
602 health workers across every health cadre were included
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Study Methodology (cont’d)
Financial Incentives
Non-Financial Incentives
Motivation
Potential Control Variables
• A composite score devised using the validated Intrinsic Motivation Inventory (IMI).*
• The 7 items on the IMI subscale were averaged for each respondent.
• The 7 items were measured on a 1 to 5 scale, ranging from strongly disagree to strongly agree.
• Gender • Age • Religiosity• Years in Health Care• Years in Current Position• Health Sector
• Adequacy of Compensation• Fairness of Pay• Other Benefits (e.g. Paid Vacation)
• Perceived Value• Autonomy• Job security• Composite Score of Performance
Management & Support Factors• Independent Measures of
Performance Management & Support * Deci EL and Ryan RM. 1985. Intrinsic Motivation and Self-Determination in Human Behavior. New York: Plenum Press.Deci EL and Ryan RM. 2008. Facilitating optimal motivation and psychological well-being across life's domains. Canadian Psychology 49: 14–23.
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Study Methodology (cont’d) Analysis Strategy
Descriptive statistics about health worker composition and characteristics
A stepwise estimation procedure, using the backward elimination technique at the .2 significance level, was used for model selection
Multivariate regressions were used to assess the association between the financial and non-financial incentives on health worker motivation in Malawi
All analysis were conducted using STATA statistical software. Sample weights were used to account for variation in the number of health workers, across
health sectors and geographic clusters, in the sample.
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Results Descriptive Results
Most health workers are male (61 percent) and in their 30s (42 percent).
Almost all health workers identify as being religious (98 percent), which is expected given the centrality of religion to life in Malawi.*
58 percent of health workers have worked in healthcare for 1 to 5 years, which means that a majority became health professionals during the EHRP period.
72 percent of health workers have been in their current position for 1 – 5 years.
Health workers from the public (70 percent) and faith-based (22 percent) sectors make up a majority of the sample, which is expected given that these sectors provide ~ 97 percent of health services in Malawi.**
* Yeatman SE and Trinitapoli. 2008. Beyond denomination: The relationship between religion and family planning in rural Malawi. Demographic Research 19(55): 1851-82.** Ministry of Health (MOH), Republic of Malawi. 2004. Human Resources in the Health Sector: Towards a Solution. Blantyre. 2004.
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Results (cont’d)Model 1: Financial and non-financial incentives on health worker motivation
Variables b coefficient 95% CI
Age .0425* [.01, .07]
Years in Healthcare -.0372* [-.07, -.00]
Financial Incentives
Compensation -.0497* [-.07, -.21]
Additional Benefits -.0143 [-.04, .09]
Fairness in Pay -.0102 [-.04, .02]
Non-Financial Incentives
Perceived Value .0311* [.00, .06]
Job Security .0255 [-.00, .05]
Autonomy .0432* [.01, .07]
Performance Management & Support Index .1722* [.09, .25]
Constant 3.55
Number of Health Workers 591
Notes: Only those control variables found to be significant at the .2 significance level using the stepwise estimation procedure were included in the model. “*” denotes significance at the .05 level.
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Model 2: Financial and non-financial incentive, including performance management & support indicators, on health worker motivation
Variables b coefficient 95% CI Variables b coefficient 95% CI
Age .0285 [-.00, .06]
Years in Healthcare -.0273 [-.06, .00]
Financial Incentives
Compensation -.0395* [-.06, -.01]
Non-Financial Incentives
Perceived Value .0458* [.01, .07]
Autonomy .0468* [.02, .08]
Performance Management & Support Indicators
Clear communication of job expectations .0167 [-.02, .05] Steady workload .0800* [.04, .11]
Adequate equipment and supplies -.0065 [-.03, .02] Manageable workload .0422* [.02, .07]
Adequate safety measures to protect against HIV
-.0032 [-.02, .02] Job-qualification/skill match .0234 [-.01, .05]
Supervisor support in challenge .0573* [.01, .10] Evaluation fairness .0001 [-.03, .03]
Supervisor performance feedback -.0037 [-.03, .23] Promotion and career advancement opportunities
.0495* [.01, .07]
Client feedback .0149 [-.02, .05] Professional development opportunities
-.0040 [-.03, .02]
Access to informational resources .1088* [.06, .16] Strong performance is rewarded .0056 [-.02, .03]
Constant 2.86
Number of Health Workers 582
Notes: Only those control variables found to be significant at the .2 significance level using the stepwise estimation procedure were included in the model. Only those financial and non-financial incentives that were significantly associated with health worker motivation in Model 1 were entered into Model 2. “*” denotes significance at the .05 level.
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Key Messages Despite the multiple financial and non-financial factors
that have been previously identified as contributing to the motivation of health workers in sub-Saharan Africa, it is a strong performance management and support system as well as flexibility and autonomy in the workplace that contribute to the most to health worker motivation in Malawi.
Interestingly, perceptions of compensation adequacy has a negative association with health worker motivation. This is an important consideration for future research that will be conducted in the next month to inform Malawi’s HRH strategy.
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Policy Implications Non-Financial Incentives
1. Less expensive and sustainable approach• Costs are incurred (e.g. training, supervision from higher-level staff,
and follow-ups), but the long-term benefits (e.g. improvements in the organizational infrastructure of local health systems) may outweigh the costs.
2. Complement to HRH programs that the Malawian government and donors already support
• Re-emphasize how financial incentives are structured under PBI programs (e.g. cash towards education) to improve performance and management support indicators
• Increase the opportunity for health professionals to earn intrinsic rewards, like autonomy and perceived value, which are critical to making improvements in QOC indicators** Leonard KL and Masatu MC. Nov 2010. Professionalism and the Know-Do Gap: Exploring Intrinsic Motivation among
Health Workers in Tanzania. Health Economics, 19(12): 1461-1477.
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What’s Next? Investigation of the relationship between compensation and health
worker motivation using objective measures Salary data (original base salary and new salary after the top-off was
collected1. Does compensation health worker motivation across the entire sample ?2. Do health workers who received the salary top off (N=511) have different levels
of motivation than health workers who did not receive this fiscal benefit (N=39)? Formal comparisons between health workers on their levels of
motivation Location (rural versus urban) *Health workers who entered the health workforce before versus after the
EHRP Health cadre (N=82 unique positions) Health sector (CHAM versus Public)
Consultation with the MOH’s HRH Technical Working Group in Malawi about the design of their next 5-year HRH strategy The MOH expects to complete the strategic plan with technical and financial
support from Abt Associates Inc. in the next few months
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Acknowledgements MOH officials and the health professionals who took time
away from their work to participate in this study
USAID/Malawi and colleagues at Abt Associates Inc. and Management International for their involvement and support
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Questions?
Allison Goldberg
Thank You