Replication Data for: Health System Changes Under Pay-for-Performance: The Effects of Rwanda's National Program on Facility Inputs (doi:10.7910/DVN/MGBCRU)

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Document Description

Citation

Title:

Replication Data for: Health System Changes Under Pay-for-Performance: The Effects of Rwanda's National Program on Facility Inputs

Identification Number:

doi:10.7910/DVN/MGBCRU

Distributor:

Harvard Dataverse

Date of Distribution:

2016-07-08

Version:

1

Bibliographic Citation:

Ngo, Diana; Sherry, Tisamarie; Bauhoff, Sebastian, 2016, "Replication Data for: Health System Changes Under Pay-for-Performance: The Effects of Rwanda's National Program on Facility Inputs", https://doi.org/10.7910/DVN/MGBCRU, Harvard Dataverse, V1

Study Description

Citation

Title:

Replication Data for: Health System Changes Under Pay-for-Performance: The Effects of Rwanda's National Program on Facility Inputs

Identification Number:

doi:10.7910/DVN/MGBCRU

Authoring Entity:

Ngo, Diana (Occidental College)

Sherry, Tisamarie (Brigham and Women’s Hospital)

Bauhoff, Sebastian (CGD)

Distributor:

Harvard Dataverse

Access Authority:

Bauhoff, Sebastian

Depositor:

Bauhoff, Sebastian

Date of Deposit:

2016-07-08

Holdings Information:

https://doi.org/10.7910/DVN/MGBCRU

Study Scope

Keywords:

Social Sciences, Health Policy, Pay for Performance

Abstract:

Pay-for-performance (P4P) programs have been introduced in numerous developing countries with the goal of increasing the provision and quality of health services through financial incentives. Despite the popularity of P4P, there is limited evidence on how providers achieve performance gains and how P4P affects health system quality by changing structural inputs. We explore these two questions in the context of Rwanda's 2006 national P4P program by examining the program's impact on structural quality measures drawn from international and national guidelines. Given the program's previously documented success at increasing institutional delivery rates, we focus on a set of delivery-specific and more general structural inputs. Using the program's quasi-randomized rollout, we apply multivariate regression analysis to short-run facility data from the 2007 Service Provision Assessment. We find positive program effects on the presence of maternity-related staff, the presence of covered waiting areas, and a management indicator and a negative program effect on delivery statistics monitoring. We find no effects on a set of other delivery-specific physical resources, delivery-specific human resources, delivery-specific operations, general physical resources, and general human resources. Using mediation analysis, we find that the positive input differences explain a small and insignificant fraction of P4P's impact on institutional delivery rates. The results suggest that P4P increases provider availability and facility operations but is only weakly linked with short-run structural health system improvements overall.

Notes:

The data used in this analysis (2007 Rwanda Service Provision Assessment SPA) must be requested through the MeasureDHS website: http://dhsprogram.com/what-we-do/survey/survey-display-290.cfm

Methodology and Processing

Sources Statement

Data Sources:

2007 Rwanda Service Provision Assessment, available upon request from Measure DHS

Origins of Sources:

http://dhsprogram.com/what-we-do/survey/survey-display-290.cfm

Data Access

Notes:

<a href="http://creativecommons.org/publicdomain/zero/1.0">CC0 1.0</a>

Other Study Description Materials

Related Publications

Citation

Title:

Ngo, Diana; Sherry, Tisamarie & Bauhoff, Sebastian “What's in the Black Box of Pay-for-Performance Programs? Health Facility Inputs and Institutional Deliveries in the Rwandan National Program,” forthcoming at Health Policy and Planning, doi: 10.1093/heapol/czw091

Bibliographic Citation:

Ngo, Diana; Sherry, Tisamarie & Bauhoff, Sebastian “What's in the Black Box of Pay-for-Performance Programs? Health Facility Inputs and Institutional Deliveries in the Rwandan National Program,” forthcoming at Health Policy and Planning, doi: 10.1093/heapol/czw091

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