Allocation and development of the general practitioner workforce in China from 2012 to 2015: a literature review

Abstract

BackgroundGeneral practitioners have an important role in primary health care, and the number of general practitioners can to some extent represent the quality of primary health care. This study aimed to quantify changes in the general practitioner workforce in China after recent health-care reforms, and assess the equity of general practitioner allocation in terms of geography and population. MethodsWe adopted the method of literature review to obtain relevant historical data from official statistical bulletins and publications. We analysed the equity of general practitioners' allocation in China, from the aspects of geography (east, central, and western regions) and resident population. FindingsFrom 2012 to 2015, the total population of China increased by 1·52%. The number of general practitioners increased from 109 794 to 188 649, with an average annual growth of 19·77%. Meanwhile, the number of general practitioners per 10 000 population increased from 0·81 to 1·37. General practitioners accounted for 4·20% of doctors in 2012, increasing to 6·21% in 2015. The population density in east, central, and western China in 2015 was 526·23, 254·95, and 54·44 per km2, respectively, while the numbers of general practitioners per 10 000 population in each area were 1·83, 1·05, and 1·06. The density of general practitioners per 10 000 km2 was 614·08 in east China, 131·41 in central China, and 30·77 in western China in 2012, increasing to 961·94, 268·51, and 57·03, respectively, in 2015. InterpretationInadequate numbers and inequitable distribution of general practitioners represents one of the most obvious problems in primary health-care resourcing in China. Eastern China has been relatively successful in developing and increasing its general practitioner workforce since 2012. By contrast, the number of general practitioners per 10 000 population in central China has run at a lower level. FundingNational Nature Science Foundation of China (#71503170; for data interpretation), Shanghai Municipal Commission of Health and Family Planning (#201440036; for data collection), Pudong New Area Health and Family Planning Commission (#PW2016A-4; for data analysis).