我国全科医生发展现状及需求预测

胡冰稚; 张涛; 陈小玲; 陈小东; 史树银

doi:10.16766/j.cnki.issn.1674-4152.003903

我国全科医生发展现状及需求预测

doi: 10.16766/j.cnki.issn.1674-4152.003903

1.
新疆医科大学第一附属医院人力资源部，新疆乌鲁木齐 830011
2.
新疆医科大学第五附属医院，新疆乌鲁木齐 830000

基金项目:

新疆维吾尔自治区自然科学基金面上项目 2023D01C156

详细信息

通讯作者:
通信作者: 史树银，E-mail: 1305630347@qq.com

中图分类号: R192.3 R499
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- 文章访问数: 5
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- 被引次数: 0
出版历程
- 收稿日期: 2025-01-02
- 网络出版日期: 2025-05-14

Development status and future demand projections of general practitioners in China

1.
Human Resources Department, the First Affiliated Hospital of Xinjiang Medical

摘要

摘要: 目的分析2012—2021年我国全科医生发展变化情况，预测2022—2026年全科医生数量。方法运用Excel 2010建立数据库，分别采用灰色GM(1，1)模型和指数平滑模型对我国全科医生数量进行预测分析。结果观测期内，我国全科医师数量、注册为全科医学专业人数、每万人口全科医师数量均呈现增长趋势。全科医师数量由2012年的109 794人增加至2021年的434 868人，年均增长率为18.77%，注册为全科医学专业的人数由2012年的37 173人增加至2021年的314 297人，年均增长率为30.58%，每万人口全科医师数由2012年的0.81人增加至2021年的3.08人，年均增长率为18.17%。建立的全科医生灰色GM(1，1)模型拟合等级为1级，平均相对误差为3.341%；建立最佳的全科医生指数平滑模型为Brown线性趋势模型，平均相对误差为3.338%。结论指数平滑模型对2012—2021年我国全科医生预测精度优于灰色GM(1，1)模型，未来我国全科医师总量缺口问题将可能继续存在，需继续加大全科医师总量配置，优化全科医师培养和激励机制。
- 全科医生 /
- 发现现状 /
- 需求 /
- 预测
Abstract: Objective To analyze the development trends of general practitioners (GPs) in China from 2012 to 2021 and predict the number of general practitioners from 2022 to 2026. Methods A database was established using Excel 2010. The gray GM (1, 1) model and the exponential smoothing model were used to predict and analyze the number of general practitioners in China, respectively. Results During the observation period, the total number of general practitioners, the number of registered general practitioners, and the number of general practitioners per 10 000 population all showed an increasing traend. The total number of general practitioners increased from 109 794 in 2012 to 434 868 in 2021, with an average annual growth rate of 18.77%. The number of registered general practitioners under the general practice specialty increased from 37 173 in 2012 to 314 297 in 2021, with an average annual growth rate of 30.58%. The number of general practitioners per 10 000 population increased from 0.81 in 2012 to 3.08 in 2021, with an average annual growth rate of 18.17%. The grey GM (1, 1) model for GPs has a grade 1 fit, with an average relative error of 3.341%. The best exponential smoothing model for general practitioners was the Brown linear trend model, with an average relative error of 3.338%. Conclusion The accuracy of the exponential smoothing model for predicting general practitioners in China from 2012 to 2021 is better than that of the grey GM (1, 1) model. However, the problem of the total shortage of general practitioners in China is expected to persist in the future. It is necessary to further increase the allocation of the total number of general practitioners and optimize the cultivation and incentive mechanism of general practitioners.
- General practitioner /
- Current status discovery /
- Demand /
- Prediction

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表 1 2012—2021年我国全科医师数及其机构分布情况

Table 1. The number of general practitioners and their institutional distribution in China from 2012 to 2021

年份	全科医生(人)	医院[人(%)]	社区卫生服务中心(站)[人(%)]	乡镇卫生院[人(%)]	其他机构[人(%)]
2012	109 794	21 074(19.19)	47 863(43.59)	38 557(35.12)	2 300(2.09)
2013	145 511	25 758(17.70)	60 181(41.36)	56 825(39.05)	2 747(1.89)
2014	172 597	30 428(17.63)	68 914(39.93)	70 296(40.73)	2 959(1.71)
2015	188 649	31 382(16.64)	73 288(38.85)	80 975(42.92)	3 004(1.59)
2016	209 083	34 654(16.57)	78 337(37.47)	92 791(44.38)	3 301(1.58)
2017	252 717	49 400(19.55)	83 933(33.21)	110 900(43.88)	8 484(3.36)
2018	308 740	51 071(16.54)	95 603(30.97)	134 538(43.58)	27 528(8.92)
2019	365 082	60 499(16.57)	103 841(28.44)	161 658(44.28)	39 084(10.71)
2020	408 820	72 090(17.63)	110 190(26.95)	179 411(43.89)	47 129(11.53)
2021	434 868	54 115(12.44)	107 871(24.81)	176 432(40.57)	96 450(22.18)

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表 2 2012—2021年我国全科医生专业配置情况

Table 2. Specialty allocation of general practitioners in China from 2012 to 2021

年份	全科医生(人)	注册为全科医学专业[人(%)]	取得全科医生培训合格证[人(%)]	每万人口全科医师数
2012	109 794	37 173(33.86)	72 621(66.14)	0.81
2013	145 511	47 402(32.58)	98 109(67.42)	1.07
2014	172 597	64 156(37.17)	108 441(62.83)	1.27
2015	188 649	68 364(36.24)	120 285(63.76)	1.37
2016	209 083	77 631(37.13)	131 452(62.87)	1.51
2017	252 717	96 235(38.08)	156 482(61.92)	1.82
2018	308 740	156 800(50.79)	151 940(49.21)	2.22
2019	365 082	210 622(57.69)	154 460(42.31)	2.61
2020	408 820	255 867(62.59)	152 953(37.41)	2.90
2021	434 868	314 297(72.27)	-	3.08
注：“-”为无数据。由于统计口径变化，2021年，全科医生数指注册为全科医学专业和注册为乡村全科执业(助理)医师的人数之和。

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表 3 灰色GM(1, 1)模型方程及其参数

Table 3. Grey GM (1, 1) model equation and its parameters

项目	参数值	拟合方程	C值	P值	模型的拟合等级
全科医生(人)	a=-0.141 6 u=121 120	X(k+1)=964 997.658 6e^{(0.141 63k)}-855 203.658 6	0.07	1.0	1级
注册为全科医学专业的人数(人)	a=-0.253 7 u=26 780	X(k+1)=142 708.229 2e^{(0.253 75k)}-105 535.229 2	0.08	1.0	1级
人口(万人)	a=-0.004 2 u=136 340	X(k+1)=32 357 724.860 9e^{(0.004 231 2k)}-32 221 802.860 9	0.11	1.0	1级

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表 4 指数平滑模型参数及模型的拟合信息

Table 4. Parameters of exponential smoothing model and fitting information of the model

项目	模型	模型参数					模型拟合信息
项目	模型	α	γ	β	t值	P值	R²	RMSE	MAPE	BIC
全科医生(人)	简单模型	1.000			3.066	0.013	0.885	38 722.456	12.606	21.359
	Holt线性趋势	1.000	1.000		0.449	0.056	0.988	13 132.133	3.338	19.426
					0.791	0.241
	Brown线性趋势	1.000			10.605	＜0.001	0.988	12 378.956	3.338	19.078
	阻尼趋势	1.000	1.000	0.900	1.421	0.198	0.988	13 968.948	3.960	19.780
					0.662	0.529
					4.862	0.002
注册为全科医学专业的人数(人)	简单模型	1.000			2.586	0.029	0.848	37 802.442	18.557	21.311
	Holt线性趋势	1.000	0.998		2.799	0.023	0.972	17 198.153	8.221	19.966
	Brown线性趋势	0.988			5.885	＜0.001	0.972	16 211.281	8.229	19.617
	阻尼趋势	1.000	0.997	1.000	2.045	0.080	0.972	18 385.281	8.218	20.329
					0.834	0.432
					3.876	0.006
人口(万人)	简单模型	1.000			3.237	0.010	0.885	660.457	0.384	13.216
	Holt线性趋势	0.900	1.000		2.039	0.076	0.991	190.315	0.103	10.958
					1.024	0.336
	Brown线性趋势	0.998			12.976	＜0.001	0.991	181.878	0.103	10.637
	阻尼趋势	0.892	0.999	0.933	1.714	0.130	0.993	190.710	0.101	11.192
					0.821	0.439
					12.893	＜0.001

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表 5 灰色GM(1, 1)模型和指数平滑模型的预测结果比较

Table 5. Comparison of prediction results between the grey GM (1, 1) model and the exponential smoothing model

年份	灰色GM(1, 1)模型			每万人口全科医生数预测值(人)	全科医师注册率预测值(%)	指数平滑模型			每万人口全科医生数预测值(人)	全科医师注册率预测值(%)
年份	人口(万人)	全科医生(人)	注册为全科医学专业(人)	每万人口全科医生数预测值(人)	全科医师注册率预测值(%)	人口(万人)	全科医生(人)	注册为全科医学专业(人)	每万人口全科医生数预测值(人)	全科医师注册率预测值(%)
2012	135 922	109 794	37 173	0.81	33.86	135 925	109 796	37 430	0.81	34.09
2013	137 201	146 821	41 221	1.07	28.08	136 724	145 508	47 305	1.06	32.51
2014	137 783	169 159	53 128	1.23	31.41	137 530	181 228	57 629	1.32	31.80
2015	138 367	194 896	68 474	1.41	35.13	138 566	199 683	80 750	1.44	40.44
2016	138 954	224 549	88 253	1.62	39.30	139 007	204 702	72 876	1.47	35.60
2017	139 543	258 713	113 744	1.85	43.97	140 137	229 517	86 780	1.64	37.81
2018	140 135	298 076	146 599	2.13	49.18	140 790	296 350	114 608	2.10	38.67
2019	140 729	343 427	188 944	2.44	55.02	141 072	364 762	216 333	2.59	59.31
2020	141 325	395 678	243 521	2.80	61.55	141 475	421 424	264 590	2.98	62.78
2021	141 925	455 879	313 862	3.21	68.85	141 417	452 559	301 325	3.20	66.58
2022	142 526	525 240	404 521	3.69	77.02	141 309	460 917	372 408	3.26	80.80
2023	143 131	605 153	521 366	4.23	86.15	141 357	486 966	430 521	3.44	88.41
2024	143 738	697 225	671 963	4.85	96.38	141 406	513 015	488 634	3.63	95.25
2025	144 347	803 305	786 059	5.57	97.85	141 454	539 064	526 747	3.81	97.71
2026	144 959	925 525	976 219	6.38	105.47	141 503	565 113	554 859	3.99	98.18

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