Effect and significance of incorporating access in estimating the number of required physicians: focus on differences in population density in the target area.
Accessibility
Capacity
Fairness
Medical resource allocation
Number of doctors
Primary care
Journal
International journal of health geographics
ISSN: 1476-072X
Titre abrégé: Int J Health Geogr
Pays: England
ID NLM: 101152198
Informations de publication
Date de publication:
17 05 2021
17 05 2021
Historique:
received:
20
12
2020
accepted:
28
04
2021
entrez:
18
5
2021
pubmed:
19
5
2021
medline:
28
5
2021
Statut:
epublish
Résumé
Geographical imbalances in the health workforce, particularly the shortage of health care workers in rural areas, is an issue of social and political concern in most countries. Estimating the number of required doctors is essential for evidence-based health policy planning. In this study, we propose two methods for estimating the number of required doctors using a simple method. One is counting by unit and the other is incorporating access to medical institutions. The purpose of this study is to verify the need to incorporate access to medical institutions when estimating the number of required physicians in a region by comparing both estimation methods from the viewpoint of regional population density. We calculated the ratio of outpatients who can access medical institutions and the number of required physicians using the travel time by car and the number of patients who can be treated per doctor per day (estimation method for the number of physicians based on the access simulation, hereinafter referred to as EAS). We compared the results of this estimation with those of a conventional method, such as the number of doctors per population (estimation method for the number of physicians based on the number of patients, hereinafter referred to as ENP) to show how important it is to incorporate the element of accessibility in such a simulation analysis. Based on the results, we discussed the applicability of the proposed method. ENP estimated that 38,685 outpatient primary care (PC) physicians were required and EAS estimated that 46,378 were required. There was a difference of about 8000. A comparison of the EAS-estimated number of physicians and the ENP-estimated number of physicians showed that the ENP-estimated number was small, particularly in areas with low population density. The results showed that it is effective to use the proposed EAS method for the estimation of PC physicians, particularly in areas with low population density. We showed that the method of allocating the number of physicians in proportion to the number of patients in a certain unit requires paying attention to the setting of the unit.
Sections du résumé
BACKGROUND
Geographical imbalances in the health workforce, particularly the shortage of health care workers in rural areas, is an issue of social and political concern in most countries. Estimating the number of required doctors is essential for evidence-based health policy planning. In this study, we propose two methods for estimating the number of required doctors using a simple method. One is counting by unit and the other is incorporating access to medical institutions. The purpose of this study is to verify the need to incorporate access to medical institutions when estimating the number of required physicians in a region by comparing both estimation methods from the viewpoint of regional population density.
METHODS
We calculated the ratio of outpatients who can access medical institutions and the number of required physicians using the travel time by car and the number of patients who can be treated per doctor per day (estimation method for the number of physicians based on the access simulation, hereinafter referred to as EAS). We compared the results of this estimation with those of a conventional method, such as the number of doctors per population (estimation method for the number of physicians based on the number of patients, hereinafter referred to as ENP) to show how important it is to incorporate the element of accessibility in such a simulation analysis. Based on the results, we discussed the applicability of the proposed method.
RESULTS
ENP estimated that 38,685 outpatient primary care (PC) physicians were required and EAS estimated that 46,378 were required. There was a difference of about 8000. A comparison of the EAS-estimated number of physicians and the ENP-estimated number of physicians showed that the ENP-estimated number was small, particularly in areas with low population density.
CONCLUSIONS
The results showed that it is effective to use the proposed EAS method for the estimation of PC physicians, particularly in areas with low population density. We showed that the method of allocating the number of physicians in proportion to the number of patients in a certain unit requires paying attention to the setting of the unit.
Identifiants
pubmed: 34001102
doi: 10.1186/s12942-021-00274-0
pii: 10.1186/s12942-021-00274-0
pmc: PMC8130267
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
21Références
Int J Health Geogr. 2004 Feb 26;3(1):3
pubmed: 14987337
BMC Health Serv Res. 2012 Aug 01;12:230
pubmed: 22852816
Int J Health Geogr. 2006 May 15;5:19
pubmed: 16700904
Int J Equity Health. 2011 Sep 22;10:39
pubmed: 21939511
J Rural Health. 2005 Winter;21(1):3-11
pubmed: 15667004
N Engl J Med. 2017 Apr 6;376(14):1301-1303
pubmed: 28301297
Cancer Epidemiol Biomarkers Prev. 2018 Nov;27(11):1265-1274
pubmed: 28751476
Lancet. 1992 Dec 5;340(8832):1391-3
pubmed: 1360099
Soc Sci Med. 2012 Dec;75(11):1954-63
pubmed: 22920275
Int J Equity Health. 2015 May 12;14:43
pubmed: 25962781
Electron Physician. 2016 Sep 20;8(9):2911-2917
pubmed: 27790343
JAMA. 1995 Nov 15;274(19):1558-60
pubmed: 7474226
Int J Equity Health. 2015 Jan 08;14:1
pubmed: 25566790
MMWR Surveill Summ. 2017 Jan 13;66(2):1-7
pubmed: 28081057