TZA_2012_PPPIEPR_v01_M
Pay for Performance Programme Impact Evaluation in Pwani Region 2012
A Controlled Before and After Study
Name | Country code |
---|---|
Tanzania | TZA |
Pay For Performance (P4P) - Tanzania
The Ministry of Health and Social Welfare (MOHSW) in Tanzania with support from the Clinton Health Access Initiative (CHAI) launched a P4P programme in one region of Tanzania, Pwani, with funding from the Norwegian Ministry of Foreign Affairs in January 2011.
P4P was conceived as a tool to accelerate the attainment of Millennium Development Goals (MDGs) 4 and 5. The P4P initiative is implemented in all seven districts within the Pwani region. All facilities, including hospitals, health centres and dispensaries within these districts are eligible to participate in the scheme, irrespective of ownership, on the condition that they provide reproductive and child health (RCH) services.
The objectives of the evaluation are:
To address these objectives, there are three components to the evaluation: an IMPACT evaluation, a PROCESS evaluation, and an ECONOMIC evaluation. The specific objectives and methods of each component of the study are reviewed in turn.
Background: The use of supply-side incentives to increase health service utilisation and enhance service quality is gaining momentum in many low- and middle-income countries. However, there is a paucity of evidence on the impact of such schemes, their cost-effectiveness, and the process of implementation and potential unintended consequences in these settings. A pay for performance (P4P) programme was introduced in Pwani region of Tanzania in 2011.
Methods/design: An evaluation of the programme will be carried out to inform a potential national rollout. A controlled before and after study will examine the effect of the P4P programme on quality, coverage, and cost of targeted maternal and newborn healthcare services and selected non-targeted services at facilities in Tanzania. Data will be collected from a survey of 75 facilities, 750 patients exiting consultations, over 75 health workers, and 1,500 households of women who delivered in the previous year, in all seven intervention districts. Data will be collected from the same number of respondents in four control districts. A process evaluation will examine: whether the P4P programme was implemented as planned; stakeholder response to the programme and its acceptability; and implementation bottlenecks and facilitating factors. Three rounds of process data collection will be conducted including a review of available P4P documents, individual interviews and focus group discussions with key informants working at facility and district level in five of the intervention districts, and at the regional and national levels. An economic evaluation will measure the cost-effectiveness of P4P relative to current practice from a societal perspective.
Discussion: This evaluation will contribute robust evidence on the impact and cost-effectiveness of P4P in a low income setting, as well as generate a better understanding of the feasibility of integrating complex intervention packages like P4P within health systems in resource poor settings.
Sample survey data [ssd]
v1.0
2014
Pay for performance
Impact evaluation
Pwani region, Tanzania (7 districts).
District
Pwani region (Tanzania) population, individuals,households, health facilities.
Payment for performance (P4P) programmes can be applied on the demand or the supply side.
Name | Affiliation |
---|---|
Josephine Borghi | Ifakara Health Institute, London School of Hygiene and Tropical Medicine |
Masuma Mamdani | Ifakara Health Institute |
Salim Abdulla | Ifakara Health Institute |
Iddy Mayumana | Ifakara Health Institute |
Irene Mashasi | Ifakara Health Institute |
Peter Binyaruka | Ifakara Health Institute |
Edith Patouillard | Ifakara Health Institute, London School of Hygiene and Tropical Medicine |
Ikunda Njau | Ifakara Health Institute |
Ottar Maestad | Norway Chr. Michelsen Institute |
Name |
---|
Ifakara Health Institute |
Name | Role |
---|---|
Norwegian Ministry of Foreign Affairs | Financial support |
Ministry of Health and Social Welfare | Contractor |
Clinton Health Access Initiative | Implementor |
Name | Affiliation | Role |
---|---|---|
Hassan Mshinda | Support | |
Paul Smithson | Ifakra Healht Institute | Reviewer |
Joanna Schellenberg | London School of Hygiene and Tropical Medicine | Reviewer |
Kara Hanson | Reviewer | |
Henry Mollel | Reviewer | |
Seema Vyas | Reviewer |
The health facility is the primary sampling unit. Facilities were sampled from those that were eligible to participate in the P4P scheme (they offered reproductive and child health services and had submitted a one year backlog of HMIS data, enabling performance targets to be measured). All eligible hospitals (n = 6) and health centres (n = 16) from the intervention districts were included in the sample along with all eligible non-public dispensaries (n = 11). An equivalent number of facilities in control areas were sampled by level of care. Public dispensaries were sampled at random with probability proportional to the number of public dispensaries in a given district (n = 42). In control areas, hospitals and health centres were sampled to match as closely as possible with selected intervention facilities in terms of annual outpatient care visits and staffing levels. A total of 75 health facilities were sampled from intervention districts, and 75 were sampled from control districts (Figure 2). In Pwani region, 46% of all facilities in the region were included in the sample.
The aim of the sampling procedure for the selection of health facilities was to seek district representation, while for the health worker survey it was to obtain the views, attitudes, and perceptions of at least one health worker per facility. No sample size calculation was therefore carried out. In dispensaries, one health worker will be interviewed. If more than one health worker is on duty, preference will be given to someone other than the incharge to avoid overburdening them with questions (as they will be interviewed for the facility survey). In health centres and hospitals, two health workers will be interviewed. The health workers will be selected at random from those who are on duty at the facility on the day the interviewers are present.
For the exit and household surveys, the sample size calculation was based on the formula by Hayes and Bennett, 1999, adjusted for the cluster design of the study at the facility level [23]. We estimated the size needed to detect a 17% reduction in waiting time from 114 minutes (SD 66) [24] to 95 minutes, with a k value of 0.25, 80% power and a significance level at of 5% (two tailed test). We did not increase the sample size to account for non-response because response rates of 100% were observed in previous studies in Tanzania [25,26]. The estimated sample size was 10 exit interviews per facility, equivalent to a total of 750 interviews in intervention and control areas respectively. A balance in the number of interviews between antenatal, postnatal clients and non-targeted services will be sought.
Exit interview patients will be approached by interviewers upon entry to the health facility and asked a series of screening questions to check their eligibility. Eligible patients will then be asked for their informed consent to participate in the study. This process will be repeated until the required number of eligible consenting respondents has been attained. Participants will then be monitored by the interviewers from their time of arrival at the facility until their time of departure, and the waiting and consultation times will be measured using a stopwatch. The cadre of the provider seen by the woman/child will also be recorded by the interviewer. The survey tool will be administered to patients upon completion of their consultation in a quiet location within the facility, at distance from providers and other patients.
For the household survey, we estimated that the required sample size to detect an 11 percentage point increase in institutional deliveries (from 50 to 61%), with k value of 0.25, 90% power, and a significance level at of 5% (two tailed test), and a 90% response rate, was 20 households per cluster, equivalent to 1,500 women per study arm. The following process was followed to identify eligible households. First, villages were sampled from the facility catchment area; for all dispensaries, the village where the facility is located will be selected by the research team; for health centres and hospitals, two villages will be selected at random from all villages lying within the ward where the facility is located. Second, all hamlets (comprising approximately 100 households) within this village/these villages, and located within the catchment area of the facility will be dentified; a random sample of four of these hamlets will then be selected. In the case of dispensaries, all four hamlets will reside within the selected village. In the case of health centres and hospitals, two hamlets will be sampled from each village. Third, five households will be sampled from each of the selected hamlets, amounting to a total of 20 households within each facility's catchment area; households will be selected at random from the selected hamlets using a modified Expanded Programme of immunisation (EPI) type sampling scheme that ensures an equal chance of any household being selected.
At the centre of the hamlet the supervisor throws a pen to determine the direction, and counts 10 houses in the direction indicated by the pen. A number is picked at random by writing down ten numbers and picking one at random. The house with the corresponding number is the starting point for data collection. The supervisor introduces the study to the household head, or a representative of the household and asks him/her if there are any eligible women living in the household: a woman aged 16 to 49 who had a baby between Oct 2010 and Oct 2011. If there is an eligible woman, they leave a copy of the consent form with them and ask if it would be convenient to return for interview the next day, at an agreed time. The pen is then thrown again and the next household in the direction of the pen is selected for interview. The supervisor continues going household to household in this way until five eligible households consenting to being interviewed are identified. If there is a junction in the path, the supervisor throws a pen again to determine the direction.
Household survey: baseline 2882 women (96% out of 3000), endline 2911 women (97% out of 3000)
Facility survey: b. 148, e (99% out of 150). 150 (100% out of 150)
Exit survey: b. 1462 (98% 1500), e. 1500 (100% 1500)
Health workers survey : b. 101, e. 94.
The health facility survey aims to measure the effects of P4P on service availability and provision at the sampled facilities. It is comprised of three sections. In the first section, questions focus on basic service provision within the facility (staffing levels, opening hours, facility management, as well as facility infrastructure). The second section of the survey compiles equipment and drug availability data. The third section captures HMIS data on service utilisation, facility expenditures and revenues for the 12-month period before P4P was implemented (January to December 2010 (at baseline) and the period from January 2011 to December 2012 (at endline). The health facility survey will be administered to the facility in-charge or in his/her absence to a knowledgeable health worker or administrator.
The health worker survey tool aims to measure the effects of P4P on health workers’ working conditions and attitudes towards work at the selected facilities.
The exit interview survey primarily intends to measure the effect of the P4P initiative on a range of subjective and objective indicators of quality of care for targeted and selected non-targeted services. The survey will also examine the effect of P4P on the cost of these services. Respondents eligible for interview include women of reproductive age (aged between 16 to 49 years) attending antenatal or postnatal care, or women with children under-one year of age coming for a preventive check up or an immunisation for the baby. These patients will respond to questions linked to the services targeted by P4P. Patients attending care for non-targeted services will also be interviewed. Non-targeted service users will include: women of reproductive age who are not pregnant, or children under five years of age accompanied by a woman of reproductive age, reporting with fever and no cough (as a proxy for malaria), or fever and cough (as a proxy for acute respiratory infection – ARI), or diarrhoea. These conditions were chosen as they were the three most significant conditions reported at outpatient departments in Tanzania in 2009.
A survey of women who had delivered within the previous 12 months will also be carried out. The women’s survey addresses the effects of P4P on service use during pregnancy, place of delivery, birth weight and postpartum care and care for the newborn as well as related costs and service satisfaction. Household socioeconomic status is also measured in this survey.
Start | End | Cycle |
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2012-01 | 2012-03 | Baseline |
2013-02 | 2013-04 | Endline |
Start date | End date |
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2012-01 | 2012-12 |
Name | Affiliation |
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Clerk | Ifakara Health Institute |
Ifakara Health Insitute
To provide quality assurance within the impact evaluation, survey data will be checked by supervisors at the end of each day of data collection. Household, exit, and health worker interview data will be collected using hand held devices (Samsung Galaxy tablets 7.0 and Huawei IDEOS phones) with skip and quality check functions to minimize data entry error. Facility data will be captured on paper and double entered. Data will be backed up on CD each day in a Microsoft Access Database, and converted to Stata for analysis. Hard copies of questionnaires will be stored in a lockable room. Electronic output will be anonymised. Interviews and focus groups conducted as part of the process and economic evaluation will be conducted in Kiswahili and recorded using sound digital recorders. Audio sound files will be transcribed and translated into English by the bilingual researchers who conducted the interviews. All translated data obtained from interviews and focus group discussions will be entered into QSR Nvivo 9 for data management, for the process evaluation, and into Microsoft Excel for the economic evaluation.
Impact data will be checked first for consistency and after export to Stata, data cleaning will be undertaken. Binary variables (Yes = 1, No = 0) will be created for all categorical variables. All binary and continuous variables will be summarized by calculating means and standard deviations. A comparison of all variables between intervention and control arms will be made at baseline. Tests of differences in means between intervention and control groups will be conducted using the Adjusted Wald F-test. Principal component analysis (PCA) will be used for creating socioeconomic status (SES) indices for household and exit interview data analysis using data collected on household size and characteristics, access to utilities, durable asset ownership, food security, household expenditures, head of household marital status, highest level of education attained, and main occupation. Data that use a Likert scale (e.g., dissatisfied = 1, neither satisfied nor dissatisfied = 2, satisfied = 3) will be analyzed by calculating individual mean scores for each variable.
Ifakara Health Institute
Ifakara Health Institute
http://data.ihi.or.tz/index.php/catalog/7
Cost: None
Name | Affiliation |
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Masuma Mamdani | Ifakara Health Institute |
Name | Affiliation | |
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Data Unit | Ifakara Health Institute | dc@ihi.or.tz |
Licensed datasets
Josephine Borghi, Iddy Mayumana, Irene Mashasi, Peter Binyaruka, Edith Patouillard, Ikunda Njau, Ottar Maestad, Salim Abdulla and Masuma Mamdani "Evaluation of a pay for performance programme in Pwani region in Tanzania: A controlled before and after study", Ifakara Health Institute, Dar es Salaam
Not available
The user of the data acknowledges that the original collector of the data, the authorized distributor of the data, and the relevant funding agency bear no responsibility for use of the data or for interpretations or inferences based upon such uses.
Ifakara Health Institute
Name | Affiliation | URL | |
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Masuma Mamdani | Ifakara Health Institute | mmamdani@ihi.or.tz | |
Info IHI | Ifakara Health Institute | info@ihi.or.tz | www.ihi.or.tz |
DDI_TZA_2012_PPPIEPR_v01_M
Name | Affiliation | Role |
---|---|---|
Juan Manuel Blanco | Ifakara Health Institute | Documentation of the DDI |
2014-05-24
Version 02 (January 2015). Edited version based on Version 01 DDI (DDI_IHI_IMPACT_P4PPilot_IMPACT_201405_v03) that was done by Ifakara Health Institute.