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Assessing health facility performance in Indonesia using the Pabón‐Lasso model and unit cost analysis of health services
Author(s) -
Hafidz Firdaus,
Ensor Tim,
Tubeuf Sandy
Publication year - 2018
Publication title -
the international journal of health planning and management
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.672
H-Index - 41
eISSN - 1099-1751
pISSN - 0749-6753
DOI - 10.1002/hpm.2497
Subject(s) - benchmarking , unit (ring theory) , activity based costing , health care , health facility , business , per capita , bivariate analysis , lasso (programming language) , population , data envelopment analysis , population health , medicine , operations management , environmental health , statistics , health services , computer science , engineering , mathematics , economics , marketing , mathematics education , world wide web , economic growth
Summary Total health care costs have dramatically increased in Indonesia, and health facilities consume the largest share of health resources. This study aims to provide a better understanding of the characteristics of the best‐performing health facilities. We use 4 national Indonesian datasets for 2011 and analysed 200 hospitals and 95 health centres. We first apply the Pabón‐Lasso model to assess the relative performance of health facilities in terms of bed occupancy rate and the number of admissions per bed; the model gathers together health facilities into 4 sectors representing different levels of productivity. We then use a step‐down costing method to estimate the cost per outpatient visit, inpatient, and bed days in hospitals and health centres. We combined both ratio analysis and applied bivariate and multivariate analyses to identify the predictors of the best‐performing health facility; 37% of hospitals and 33% of health centres were located in the high‐performing sector of the Pabón‐Lasso model. The wide variation in unit costs across health facilities presented a basis for benchmarking and identifying relatively efficient units. Combining the unit cost analysis and Pabón‐Lasso model, we find that health facility performance is affected by both internal (size and capacity, financing, type of patients, ownership, accreditation status, and staff availability) and external factors (economic status, population education level, location, and population density). Our study demonstrates that it is feasible to identify the best‐performing health facilities and provides information about how to improve efficiency using simplistic methods.