Estimating the Unit Costs of Healthcare Service Delivery in India: Addressing Information Gaps for Price Setting and Health Technology Assessment.
Journal
Applied health economics and health policy
ISSN: 1179-1896
Titre abrégé: Appl Health Econ Health Policy
Pays: New Zealand
ID NLM: 101150314
Informations de publication
Date de publication:
10 2020
10 2020
Historique:
pubmed:
15
3
2020
medline:
19
8
2021
entrez:
15
3
2020
Statut:
ppublish
Résumé
India's flagship National Health insurance programme (AB-PMJAY) requires accurate cost information for evidence-based decision-making, strategic purchasing of health services and setting reimbursement rates. To address the challenge of limited health service cost data, this study used econometric methods to identify determinants of cost and estimate unit costs for each Indian state. Using data from 81 facilities in six states, models were developed for inpatient and outpatient services at primary and secondary level public health facilities. A best-fit unit cost function was identified using guided stepwise regression and combined with data on health service infrastructure and utilisation to predict state-level unit costs. Health service utilisation had the greatest influence on unit cost, while number of beds, facility level and the state were also good predictors. For district hospitals, predicted cost per inpatient admission ranged from 1028 (313-3429) Indian Rupees (INR) to 4499 (1451-14,159) INR and cost per outpatient visit ranged from 91 (44-196) INR to 657 (339-1337) INR, across the states. For community healthcare centres and primary healthcare centres, cost per admission ranged from 412 (148-1151) INR to 3677 (1359-10,055) INR and cost per outpatient visit ranged from 96 (50-187) INR to 429 (217-844) INR. This is the first time cost estimates for inpatient admissions and outpatient visits for all states have been estimated using standardised data. The model demonstrates the usefulness of such an approach in the Indian context to help inform health technology assessment, budgeting and forecasting, as well as differential pricing, and could be applied to similar country contexts where cost data are limited.
Sections du résumé
BACKGROUND
India's flagship National Health insurance programme (AB-PMJAY) requires accurate cost information for evidence-based decision-making, strategic purchasing of health services and setting reimbursement rates. To address the challenge of limited health service cost data, this study used econometric methods to identify determinants of cost and estimate unit costs for each Indian state.
METHODS
Using data from 81 facilities in six states, models were developed for inpatient and outpatient services at primary and secondary level public health facilities. A best-fit unit cost function was identified using guided stepwise regression and combined with data on health service infrastructure and utilisation to predict state-level unit costs.
RESULTS
Health service utilisation had the greatest influence on unit cost, while number of beds, facility level and the state were also good predictors. For district hospitals, predicted cost per inpatient admission ranged from 1028 (313-3429) Indian Rupees (INR) to 4499 (1451-14,159) INR and cost per outpatient visit ranged from 91 (44-196) INR to 657 (339-1337) INR, across the states. For community healthcare centres and primary healthcare centres, cost per admission ranged from 412 (148-1151) INR to 3677 (1359-10,055) INR and cost per outpatient visit ranged from 96 (50-187) INR to 429 (217-844) INR.
CONCLUSION
This is the first time cost estimates for inpatient admissions and outpatient visits for all states have been estimated using standardised data. The model demonstrates the usefulness of such an approach in the Indian context to help inform health technology assessment, budgeting and forecasting, as well as differential pricing, and could be applied to similar country contexts where cost data are limited.
Identifiants
pubmed: 32170666
doi: 10.1007/s40258-020-00566-9
pii: 10.1007/s40258-020-00566-9
pmc: PMC7519005
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
699-711Références
Lancet. 2011 Feb 5;377(9764):505-15
pubmed: 21227492
Sex Transm Infect. 2016 Mar;92(2):130-4
pubmed: 26438349
Value Health. 2019 Oct;22(10):1146-1153
pubmed: 31563257
Indian J Med Res. 2017 Sep;146(3):354-361
pubmed: 29355142
Appl Health Econ Health Policy. 2015 Dec;13(6):595-613
pubmed: 26449485
Bull World Health Organ. 2005 Oct;83(10):747-55
pubmed: 16283051
Appl Health Econ Health Policy. 2017 Oct;15(5):681-692
pubmed: 28409489
Cost Eff Resour Alloc. 2018 Mar 19;16:11
pubmed: 29559855
Pharmacoecon Open. 2020 Jun;4(2):249-261
pubmed: 31468323
Pharmacoecon Open. 2018 Jun;2(2):179-190
pubmed: 29623618
F1000Res. 2018 Feb 28;7:245
pubmed: 29770210
PLoS One. 2014 Mar 13;9(3):e91781
pubmed: 24626285
Glob Health Action. 2018;11(1):1527556
pubmed: 30326795
Adv Health Econ Health Serv Res. 1983;4:257-303
pubmed: 10299466
Clin Kidney J. 2018 Oct;11(5):726-733
pubmed: 30288270
Cost Eff Resour Alloc. 2017 Oct 26;15:21
pubmed: 29089861
J Health Econ. 1986 Jun;5(2):107-27
pubmed: 10287222
Cost Eff Resour Alloc. 2007 Nov 05;5:13
pubmed: 17983475
PLoS One. 2013 Jul 23;8(7):e69728
pubmed: 23936088
Soc Sci Med. 2002 Sep;55(6):895-906
pubmed: 12220092
Vaccine. 2018 Jun 18;36(26):3836-3841
pubmed: 29776749
PLoS One. 2018 Jan 11;13(1):e0191132
pubmed: 29324861
Cost Eff Resour Alloc. 2008 Nov 13;6:22
pubmed: 19014524
PLoS One. 2016 Aug 18;11(8):e0160986
pubmed: 27536781
Health Econ. 1995 Nov-Dec;4(6):467-78
pubmed: 8653186
Health Econ. 2004 Nov;13(11):1117-24
pubmed: 15386683
Pharmacoecon Open. 2019 Sep;3(3):391-402
pubmed: 30783991
Health Policy Plan. 2005 Jan;20(1):1-13
pubmed: 15689425
Indian J Community Med. 2019 Apr-Jun;44(2):147-151
pubmed: 31333294
Cost Eff Resour Alloc. 2018 Mar 9;16:10
pubmed: 29541000
Cost Eff Resour Alloc. 2003 Feb 26;1(1):3
pubmed: 12773218