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Investigating health workers remuneration in Sierra Leone:
preliminary results and reflections on methods
Maria Paola Bertone, LSHTMMaria Paola Bertone, LSHTMMylene Lagarde, LSHTM
3rd Conference of the African Health Economics and Policy AssociationNairobi, 11-13 March 2014
www.lshtm.ac.uk
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Introduction
Health
Service Delivery
Information
Medical Products
Determinants of HWs motivation:
- Financial incentives- Internal Health
WorkersInformation
Leadership & Governance Financing
- Internal determinants
- Work context- Cultural context
(Franco et al, 2003)
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Financial remuneration(s)• Reforms to revise formal “incentive package” for HWs• But: how much do we really know about HWs remunerations?
– Informal sources – Informal sources – Salary supplementations, “one-off” payments and per diems– Private practice and activities outside of the health sector
• And what about the consequences of these remunerations?
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Overview of the literature
Global Initiatives and “vertical Remuneration of HWs
Per diems
Global Initiatives and “vertical programs”
HWs financial coping strategies
Remuneration of HWs
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Aims and objectives• Overall objectives of my research:
1. (i) HWs remuneration structure, (ii) determinants of remuneration2. How remunerations may influence the type of activities that HWs
performperform3. HWs views on multiple remunerations: multiple upward
accountabilities and financial coping strategies/livelihood strategies4. “Political economy” of HWs remuneration at local level
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Context
FHCI(announcement)
Abolition of some salary supplem.FHCI (launch)
Sources: Bertone et al (under review) and KIIs at central and district level
1991 2002
Conflict Early reconstruction period
Health System Strenghening process
20102009 2011 2012 2013
Salary increase
PBFRemote Allowance
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Methods
Challenges
• Sensitivity of some questions
� Combination of quantitative methods :
Collecting data on HWs remuneration
• Sensitivity of some questions � HWs provide “normative” answers or no response• (Perceived) incentives to mis-/under-report some income components• Variation over time
1. Cross-sectional survey2. Indirect questioning
(Randomized Response Technique)
3. Longitudinal self-administered logbook
+ qualitative in-depth interviews
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Timeline of field activities
1 2 4 5 6 7 8
--------- October 2013 -------------------- November 2013 -------------------- September 2013 -----------
3
Daily logbook
Survey &indirect questionnaire
Logbook collection Logbook collection
Visit 1 Visit 2 Visit 3
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Survey• Cross-sectional (Sept. 2013) with reference to previous month• Administered by 10 trained enumerators
� Most commonly used technique� Inexpensive and rapid� Inexpensive and rapid� Problems when self-
administered� Recall bias and no
response for sensitive questions
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Indirect questioning� To improve accuracy of answers to sensitive questions� No information on individual respondents� Practical issues:
• Adapted die � calculator provided• Same die for 3 questions (most sensitive)• Same die for 3 questions (most sensitive)• Distribution unknown, but likely not normal (many 0s)
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Logbook• Self-administered• Over 8 weeks• Enumerators filled in a
weekly summary and probed, especially for probed, especially for incomes not earned daily
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Over 8 weeks
Visit 1
Direct survey:- salary- Remote Allowance- PBF bonus- revenues from UF- salary top-up- per diems/DSA
Longitudinal logbook:- all remunerations earned
Probing and weekly summary:
- salary- Remote Allowance- PBF bonus- revenues from UF
Visit 2 & 3
- per diems/DSA- IGA (outside health)
Indirect questioning:- “gifts” from patients- sale of drugs or other items w/in facility- private practice
- revenues from UF- payment from extra work (night shifts, etc)- per diems/DSA- salary top-up- “gifts” from patients- sale of drugs or other items w/in facility- private practice- IGA (outside health)
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Sampling 1. Choice of 3 districts based on (i) number, type and remoteness of
facilities, (ii) presence of NGOs 2. Facilities: only health centers
– Randomly selected– About 200 facilities
3. HWs interviewed selected among those present:– Only CHOs, CHA+nurses,
MCH Aides– in-charge or highest in rank – 1 or 2 HWs per facility� 297 HWs in sampling frame
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ResultsDistrict Type of facility Gender Age
BoKene-ma
Moya-mba CHC CHP
MCH Post male female Total
CHO 18 6 6 29 0 1 22 8 41.430
11%CHO 18 6 6 29 0 1 22 8 41.4 11%CHA+Nurse 23 33 20 39 32 5 32 44 40.8
7629%
MCH Aide 55 51 54 26 46 88 0 160 40.9
16060%
Total96
36%90
34%80
30%94
35%78
29%94
35%54
20%21280% 41.0
266100%
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Results from survey
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Salary and other incomes: 82% No salary-other incomes: 14%Salary only: 3% No incomes: 1%
Average salary
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Results – indirect questions• “Gifts”/payments from patients: -9,626 Le.• Sale of drugs and other items: -3,911 Le.• Private practice: -22,067 Le.
�Possible explanations for negative results:– Design issues– “Reticence” of HWs (Lensvelt-Mulders et al 2003, Coutts et al 2011, Akwataghibe et al 2012 - HWs in Nigeria)
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Results – logbook / per diems• Per diems per week
Workshop on nutrition (Moyamba)
HPV vaccine (Bo)
Polio campaign
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Results – logbook / “gifts”• “Gifts” per week
Add what had happened
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Results – logbook / total• Total remuneration per week
Add what had happened
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Comparison – survey vs. logbook
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Discussion – methodsInitial hypotheses Results Possible explanations
Recall bias in survey�underestimation of all income components
Generally, higher results in survey than logbook
• Lack on completeness in logbooks•Theoretical income vs. what is actually received• HWs consider longer time span than a month• “Perceptions” around own income• “Perceptions” around own income
Indirect questioning: better estimation for sensitive incomes
Negative results(under-reporting)
“Reticence” of HWs even with indirect questions + design issues� logbooks may provide better estimates
Variation over time: related to ongoing activities in the district
High variation for some incomes
Seems to be explained by district and activities ongoing in each of them
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Discussion – methods (2)Method Advantages DisadvantagesCross-sectionalsurvey
• Relatively inexpensive and rapid� can increase sample size and power
• Recall bias (in which direction?)• Does not capture variation over time• Bias for sensitive questions
Indirect • In theory, more reliable estimates • Less efficient (need larger sample)Indirect questioning
• In theory, more reliable estimates on sensitive questions• Relatively rapid to administer• Local acceptability and understanding
• Less efficient (need larger sample)• Complex to administer / train enumerators• Issues w/ non-normal distribution• “Reticence”
Longitudinal logbook
• Attrition lower than expected (20 HWs-7.52% at week 7)• Data on sensitive incomes (“gifts”)• More precise estimation for non-regular incomes
• Reliability and completeness• Possible underestimation of some incomes• Better done at different times of the year• Extra work for HWs• Time consuming
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Discussion – HWs remunerations
• HWs remuneration is ‘complex’:– Multiple sources of income related to different activities– Variation over time related to (i) ongoing activities; (ii) NGO/donor presence;
(iii) irregularity of some payments.
• The consequences of the remuneration at individual level on • The consequences of the remuneration at individual level on performance and motivation should be explored
• From a policy perspective, it is essential to better understand the entire set of remunerations before embarking in reforms of the incentive package
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Next steps• Determinants of remuneration: do individual characteristics of HWs
explain remuneration levels?• Activities performed: how remunerations impact on the type of
activities performed daily by HWsactivities performed daily by HWs• Further data collection: qualitative interviews to have a better
understanding of (i) financial coping strategies/livelihood strategies of HWs, (ii) consequences of multiple remunerations
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AcknowledgementsThe Health Workers who took their time to respond to the survey
and fill in the logbooks for 2 months.‘My’ team in the field: Abdulrahman, Alimu, Christiana, Fatmata,
Edrissa, James, John, Michael, Precious, Sajallieu & Mr Bah. Those who shared their research with me and helped with mine:
Christophe Lemiere, Jean-Benoit Falisse, Laura Anselmi, Giulia Greco, Arianna Cowling.Christophe Lemiere, Jean-Benoit Falisse, Laura Anselmi, Giulia Greco, Arianna Cowling.The NGO Solthis who provided logistics support for my fieldwork
I am grateful to the Fondation AEDES for funding my PhD and to the ReBUILD Consortium which funds field work.
www.fondation-aedes.org
FONDATION