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

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)

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?

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

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

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

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

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

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

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)

Logbook• Self-administered• Over 8 weeks• Enumerators filled in a

weekly summary and probed, especially for probed, especially for incomes not earned daily

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)

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

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%

Results from survey

Salary and other incomes: 82% No salary-other incomes: 14%Salary only: 3% No incomes: 1%

Average salary

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)

Results – logbook / per diems• Per diems per week

Workshop on nutrition (Moyamba)

HPV vaccine (Bo)

Polio campaign

Results – logbook / “gifts”• “Gifts” per week

Add what had happened

Results – logbook / total• Total remuneration per week

Add what had happened

Comparison – survey vs. logbook

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

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

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

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

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