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Erschienen in: Human Resources for Health 1/2021

Open Access 01.12.2021 | Research

Projections of psychiatrists’ distribution for patients in Japan: a utilization-based approach

verfasst von: Norio Sugawara, Norio Yasui-Furukori, Kazutaka Shimoda

Erschienen in: Human Resources for Health | Ausgabe 1/2021

Abstract

Background

Depopulation accompanied by population aging is a major public health concern in Japan. Although adequate allocation of mental healthcare resources is needed, there have been few studies on the impact of population change on the supply–demand balance for mental illness in Japan. The aim of this study is to predict psychiatrists' distribution for patients with mental illness via a utilization-based approach.

Methods

We set patients with schizophrenia, mood disorders, vascular dementia or Alzheimer’s disease as study subjects and conducted analyses for 2015, 2025, 2035, and 2045 across all prefectures. Moreover, we evaluated the regional maldistribution of demand and supply by calculating the number of psychiatrists per patient, Gini coefficients (GC), and Herfindahl–Hirschman Index (HHI).

Results

The mean number of psychiatrists per patient for patients with schizophrenia, mood disorders, vascular dementia, and Alzheimer’s disease in 2025, 2035, and 2045 was significantly lower than in 2015. For all of the abovementioned diseases, both the GC and HHI will increase until 2045.

Conclusion

If psychiatrists are allocated at the current population-to-psychiatrist ratio, the shortage of psychiatrists will continue to worsen in the future. To overcome this inequity, policy makers should make plans to shift responsibilities from psychiatrists to other mental health workers and to ensure the adequate geographical allocation of healthcare resources.
Hinweise

Publisher's Note

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Introduction

The increasing number of patients with mood disorders and Alzheimer's disease has increased the demand for psychiatrists in Japan [1]. In 2013, the Ministry of Health, Labour, and Welfare (MHLW) designated mental illness as the fifth priority disease for the national medical service, and all prefectures in Japan were required to start regional medical care planning for mental illness [2]. Optimizing the balance between supply and demand for the mental healthcare system is a public health issue, and psychiatrists are an essential human resource for the system.
Healthcare systems in Japan are facing the problems of depopulation accompanied by population aging. Based on 2015 national census data, the National Institute of Population and Social Security Research (IPSS) predicted that the Japanese population will decrease from 127 to 106 million by 2045 [3]. In the same analysis, the IPSS also indicated that the elderly population (aged 65 years and over) will increase by 15.7%, while the young population (aged 0 to 14 years) will decrease by 28.6%. Because the age of onset differs by disease, changes in population structure could lead to different utilization patterns of healthcare services for each mental illness. Although adequate allocation of mental healthcare resources is needed, there have been few studies concerning the impact of population change on the supply–demand balance with respect to mental illness in Japan.
In this study, we employed a utilization-based approach in which current or target rates of healthcare system utilization are multiplied by future population estimates to estimate the demand of mental illness. This approach has been widely used in Organisation for Economic Co-operation and Development (OECD) member countries [4, 5]. There have been other approaches to estimate the demand for healthcare workforces. A service-based approach or a task-based approach could be used for the same purpose [6]. The former approach is based on the estimation of the shifting needs of an organization that are required to operate effectively. The estimation requires data on the burden of disease, epidemiological changes, hospital bed-to-staff ratios, and the expected budget for staff salaries. On the other hand, the estimation of need in a task-based approach is founded on the tasks a typical professional can undertake in a given time period. Both approaches could be useful for healthcare workforce planning at relatively local level, but effectively accomplish this planning at the national level requires an enormous amount of data.
The aim of this study is to predict psychiatrists' distribution for patients with mental illness and to predict the future healthcare supply–demand balance. The projections of the availability of human resources in the mental healthcare system could support policy decision-making. To the best of our knowledge, this study is the first report on the projection of psychiatrists’ distribution for patients with mental illness in Japan.

Methods

Analytical parameters

Data on the number of psychiatrists per prefecture were obtained from the 2016 Survey of Physicians, Dentists, and Pharmacists (SPDP) on the MHLW website [7]. In addition, we obtained data on population projections until 2045 from the IPSS [3]. These projections took the count from the 2015 Population Census as the base population [8]. The utilization rate per 100,000 population per prefecture was obtained from the 2017 Patient Survey on the MHLW website [1]. Based on the Statistics Act, Article 2, the MHLW conducted the Patient Survey to obtain basic data needed for the development of health policies by identifying age, sex, diagnosis according to the International Classification of Diseases, tenth revision (ICD-10), and condition at time of survey for each patient. The survey covers inpatient and outpatient treatment in medical facilities, including 6395 hospitals and 5526 clinics. The survey report provides estimates of the utilization rates broken down by sex, 5-year age groups and ICD-10 diagnoses. We set patients with schizophrenia, mood disorders, vascular dementia, and Alzheimer’s disease as the study subjects, as those are the leading mental disorders associated with relatively higher loss of disability-adjusted life-years (DALYs) in Japan [9]. The requirement for written informed consent was waived by the Ethics Committee since the study involved record review only.
To project the number of future psychiatrists, we assumed that the psychiatrist-to-population ratio in Japan would be constant from 2015 to 2045. Although the current distribution of psychiatrists in Japan is not adequate, we assumed that attractiveness of urban areas to psychiatrists would not change [10]. We calculated the number of psychiatrists per population based on the 2016 SPDP and the 2015 Population Census for each prefecture. Following the abovementioned assumption, the estimation of the number of psychiatrists in 2015, 2025, 2035 and 2045 was based on the psychiatrist-to-population ratio and population projections in Japan.
In a utilization-based approach, future demand is calculated by multiplying the future population by the utilization rate for each disease. First, we obtained the utilization rate for each disease, by age and sex, as variables from the 2017 Patient Survey. Population by age and sex in the future was based on population projections from 2015 to 2045. We then multiplied these variables for estimates of the future number of patients as the criterion for demand in each prefecture. For each disease, we calculated the number of psychiatrists per patient in Japan.
We employed the Gini coefficient (GC) as an indicator of the distribution of psychiatrists to aid in the evaluation of inequity in human resources by prefecture. In this study, Lorenz curves are drawn by plotting the cumulative proportion of psychiatrists on the vertical axis and the cumulative proportion of the estimated number of patients on the horizontal axis in ascending order by psychiatrists per patient across all prefectures. After that, we calculated the GCs based on the Lorenz curves. The GC is traditionally used to analyze the distribution of income and wealth and has a theoretical range from 0 (perfect evenness) to 1 (maximum possible unevenness). It provides a standardized value to reflect the relative unevenness of a distribution. In this study, higher values of the GC indicated higher levels of human resource (psychiatrists) inequality experienced by patients with mental illnesses among prefectures.
The Herfindahl–Hirschman Index (HHI), which has been widely used to evaluate mergers and acquisitions, was adopted as an indicator of patient concentration. In this study, the HHI for each disease is calculated as the sum of squared patient shares (percentages) across all prefectures. It approaches zero when a market is occupied by a large number of competitors of relatively equal size and reaches its maximum of 10,000 points when there is a market monopoly. The HHI was interpreted as the concentration of patients with mental illness to estimate future demand transfer. In this study, higher values of the HHI indicated higher concentrations of patients with mental illnesses among prefectures.
In Tables 1 and 2, we ordered the prefectures according to the identification codes (JIS X 0401) from the Japanese Industrial Standards Committee.
Table 1
Forecasted psychiatrists and patients, 2015 to 2045
 
Psychiatrists
Schizophrenia
Mood disorders
Alzheimer's disease
Vascular dementia and others
 
2015
2025
2035
2045
2015
2025
2035
2045
2015
2025
2035
2045
2015
2025
2035
2045
2015
2025
2035
2045
Hokkaido
733
683
619
545
9569
9071
8297
7303
5194
4998
4537
3993
4227
5647
6804
6744
1725
2313
2753
2819
Aomori
153
135
116
96
2371
2160
1877
1562
1275
1164
1013
838
1089
1357
1547
1530
441
556
628
632
Iwate
125
113
100
86
2283
2118
1896
1641
1233
1144
1021
881
1146
1349
1485
1461
463
555
607
611
Miyagi
266
254
233
206
3955
3894
3656
3275
2177
2143
1993
1763
1645
2157
2624
2717
673
894
1067
1133
Akita
142
123
103
84
1912
1685
1419
1154
1020
904
769
618
1043
1213
1316
1262
418
498
533
521
Yamagata
146
132
117
100
1989
1827
1626
1401
1076
991
887
761
1079
1220
1341
1330
435
508
547
551
Fukushima
209
189
167
144
3388
3167
2831
2430
1821
1702
1525
1307
1614
1947
2260
2309
656
810
922
964
Ibaraki
241
227
208
185
5047
4871
4518
4035
2722
2667
2446
2184
1999
2664
3277
3297
831
1103
1333
1381
Tochigi
176
167
154
139
3398
3288
3077
2788
1839
1799
1675
1507
1343
1706
2083
2104
554
709
846
885
Gunma
232
219
202
183
3400
3280
3076
2782
1841
1804
1667
1511
1463
1883
2261
2247
603
779
922
946
Saitama
617
612
587
554
12,333
12,430
12,168
11,475
6747
6932
6612
6277
3984
6185
7754
7881
1682
2524
3166
3322
Chiba
624
614
584
548
10,672
10,612
10,279
9629
5821
5911
5594
5269
3703
5551
6851
6840
1553
2266
2798
2885
Tokyo
2057
2107
2108
2071
22,127
23,146
23,785
23,404
12,688
13,237
13,173
13,040
7822
10,612
12,467
13,286
3218
4348
5158
5597
Kanagawa
989
983
948
901
15,189
15,468
15,260
14,374
8470
8677
8321
7957
5236
7848
9665
10,052
2183
3212
3981
4238
Niigata
217
201
181
160
4051
3793
3455
3057
2196
2077
1883
1660
2045
2443
2773
2721
830
1013
1129
1141
Toyama
133
124
114
102
1880
1772
1639
1474
1015
978
891
800
913
1133
1307
1227
373
467
530
517
Ishikawa
163
156
146
134
1965
1898
1793
1646
1072
1057
984
905
875
1109
1329
1296
359
456
540
544
Fukui
92
86
79
72
1351
1279
1190
1071
734
705
654
589
660
786
907
896
268
326
369
375
Yamanashi
92
84
75
66
1443
1364
1235
1069
788
743
668
586
688
842
981
990
281
349
400
412
Nagano
228
213
195
175
3630
3458
3218
2883
1977
1899
1739
1570
1896
2283
2599
2568
775
946
1066
1079
Gifu
173
162
148
133
3474
3302
3062
2740
1894
1825
1663
1494
1514
1947
2260
2202
624
798
921
924
Shizuoka
342
324
300
272
6400
6142
5737
5183
3475
3385
3122
2837
2722
3635
4320
4304
1121
1495
1766
1810
Aichi
760
757
734
701
12,215
12,407
12,321
11,787
6807
6992
6754
6490
4257
6141
7486
7685
1772
2511
3068
3240
Mie
219
206
190
173
3111
2985
2790
2524
1701
1649
1514
1379
1367
1729
1994
1978
562
709
813
826
Shiga
128
126
122
114
2295
2314
2266
2139
1271
1296
1245
1178
892
1191
1474
1525
370
493
603
642
Kyoto
353
339
316
289
4399
4267
4053
3712
2441
2415
2240
2063
1852
2544
3039
2952
761
1036
1235
1238
Osaka
1052
1015
948
873
14,928
14,577
13,952
12,859
8275
8245
7650
7122
5454
7970
9382
9156
2262
3228
3834
3855
Hyogo
590
566
528
483
9460
9242
8788
8033
5192
5144
4794
4421
3832
5283
6377
6394
1577
2160
2597
2677
Nara
161
149
134
118
2365
2218
2010
1755
1286
1236
1103
973
993
1361
1633
1572
413
557
663
657
Wakayama
102
93
83
73
1705
1561
1401
1228
927
861
766
674
837
986
1085
1026
341
405
440
426
Tottori
96
90
83
75
995
933
859
778
540
516
475
426
529
613
697
691
213
255
284
289
Shimane
117
108
99
89
1227
1128
1030
927
661
620
567
506
718
807
881
836
290
335
358
350
Okayama
296
284
268
250
3244
3125
2976
2778
1784
1757
1654
1537
1556
1935
2234
2167
635
794
911
910
Hiroshima
370
359
339
316
4812
4667
4446
4137
2644
2619
2461
2287
2136
2768
3264
3177
878
1139
1331
1338
Yamaguchi
202
186
168
149
2494
2279
2059
1838
1345
1263
1132
1004
1282
1554
1740
1603
522
637
704
674
Tokushima
131
119
106
93
1345
1236
1108
969
727
677
604
525
683
790
889
851
278
328
361
356
Kagawa
142
134
124
113
1704
1610
1503
1369
921
890
823
745
834
1001
1155
1108
341
416
470
466
Ehime
141
130
117
103
2446
2273
2061
1824
1323
1246
1126
992
1230
1479
1691
1631
499
608
684
683
Kochi
123
110
97
84
1305
1173
1039
899
707
647
567
489
731
830
912
847
294
339
369
354
Fukuoka
856
846
812
764
8545
8511
8247
7777
4728
4777
4588
4300
3541
4713
5772
5858
1450
1936
2339
2451
Saga
161
152
141
128
1412
1342
1244
1132
768
742
693
624
692
818
945
958
280
339
382
396
Nagasaki
219
200
179
156
2420
2233
1990
1733
1308
1216
1092
952
1213
1440
1640
1620
492
594
664
675
Kumamoto
335
317
296
271
3047
2893
2677
2436
1667
1600
1491
1353
1569
1861
2126
2136
635
772
865
889
Oita
181
169
155
139
2036
1907
1738
1564
1107
1050
963
860
1041
1266
1456
1406
423
522
591
590
Miyazaki
191
177
161
143
1918
1786
1605
1425
1038
977
890
784
961
1170
1355
1346
391
483
551
558
Kagoshima
265
243
219
194
2859
2659
2386
2101
1554
1441
1312
1151
1522
1730
1949
1987
615
722
793
826
Okinawa
268
274
274
267
2199
2339
2379
2315
1239
1295
1310
1277
793
1065
1350
1561
328
448
557
653
Mean
332
320**
302**
279**
4602
4504**
4298**
3966**
2533
2509*
2354**
2180**
1898
2523**
2994**
3007**
781
1036**
1222**
1262**
The Wilcoxon Signed-Ranks Test with the Bonferroni correction was employed for comparisons between 2015 and other time points
*p < 0.05, **p < 0.001
Table 2
Forecasted psychiatrist per patients, 2015–2045
 
Schizophrenia
   
Mood disorders
   
Alzheimer's disease
   
Vascular dementia and others
   
 
2015
2025
2035
2045
2015
2025
2035
2045
2015
2025
2035
2045
2015
2025
2035
2045
Hokkaido
0.077
0.075
0.075
0.075
0.141
0.137
0.136
0.136
0.173
0.121
0.091
0.081
0.425
0.295
0.225
0.193
Aomori
0.065
0.063
0.062
0.061
0.120
0.116
0.115
0.115
0.140
0.099
0.075
0.063
0.347
0.243
0.185
0.152
Iwate
0.055
0.053
0.053
0.052
0.101
0.099
0.098
0.098
0.109
0.084
0.067
0.059
0.270
0.204
0.165
0.141
Miyagi
0.067
0.065
0.064
0.063
0.122
0.119
0.117
0.117
0.162
0.118
0.089
0.076
0.395
0.284
0.218
0.182
Akita
0.074
0.073
0.073
0.073
0.139
0.136
0.134
0.136
0.136
0.101
0.078
0.067
0.340
0.247
0.193
0.161
Yamagata
0.073
0.072
0.072
0.071
0.136
0.133
0.132
0.131
0.135
0.108
0.087
0.075
0.336
0.260
0.214
0.181
Fukushima
0.062
0.060
0.059
0.059
0.115
0.111
0.110
0.110
0.129
0.097
0.074
0.062
0.319
0.233
0.181
0.149
Ibaraki
0.048
0.047
0.046
0.046
0.089
0.085
0.085
0.085
0.121
0.085
0.063
0.056
0.290
0.206
0.156
0.134
Tochigi
0.052
0.051
0.050
0.050
0.096
0.093
0.092
0.092
0.131
0.098
0.074
0.066
0.318
0.236
0.182
0.157
Gunma
0.068
0.067
0.066
0.066
0.126
0.121
0.121
0.121
0.159
0.116
0.089
0.081
0.385
0.281
0.219
0.193
Saitama
0.050
0.049
0.048
0.048
0.091
0.088
0.089
0.088
0.155
0.099
0.076
0.070
0.367
0.242
0.185
0.167
Chiba
0.058
0.058
0.057
0.057
0.107
0.104
0.104
0.104
0.169
0.111
0.085
0.080
0.402
0.271
0.209
0.190
Tokyo
0.093
0.091
0.089
0.088
0.162
0.159
0.160
0.159
0.263
0.199
0.169
0.156
0.639
0.485
0.409
0.370
Kanagawa
0.065
0.064
0.062
0.063
0.117
0.113
0.114
0.113
0.189
0.125
0.098
0.090
0.453
0.306
0.238
0.213
Niigata
0.054
0.053
0.052
0.052
0.099
0.097
0.096
0.096
0.106
0.082
0.065
0.059
0.261
0.198
0.160
0.140
Toyama
0.071
0.070
0.070
0.069
0.131
0.127
0.128
0.128
0.146
0.109
0.087
0.083
0.357
0.266
0.215
0.197
Ishikawa
0.083
0.082
0.081
0.081
0.152
0.148
0.148
0.148
0.186
0.141
0.110
0.103
0.454
0.342
0.270
0.246
Fukui
0.068
0.067
0.066
0.067
0.125
0.122
0.121
0.122
0.139
0.109
0.087
0.080
0.343
0.264
0.214
0.192
Yamanashi
0.064
0.062
0.061
0.062
0.117
0.113
0.112
0.113
0.134
0.100
0.076
0.067
0.327
0.241
0.188
0.160
Nagano
0.063
0.062
0.061
0.061
0.115
0.112
0.112
0.111
0.120
0.093
0.075
0.068
0.294
0.225
0.183
0.162
Gifu
0.050
0.049
0.048
0.049
0.091
0.089
0.089
0.089
0.114
0.083
0.065
0.060
0.277
0.203
0.161
0.144
Shizuoka
0.053
0.053
0.052
0.052
0.098
0.096
0.096
0.096
0.126
0.089
0.069
0.063
0.305
0.217
0.170
0.150
Aichi
0.062
0.061
0.060
0.059
0.112
0.108
0.109
0.108
0.179
0.123
0.098
0.091
0.429
0.301
0.239
0.216
Mie
0.070
0.069
0.068
0.069
0.129
0.125
0.125
0.125
0.160
0.119
0.095
0.087
0.390
0.291
0.234
0.209
Shiga
0.056
0.054
0.054
0.053
0.101
0.097
0.098
0.097
0.143
0.106
0.083
0.075
0.346
0.256
0.202
0.178
Kyoto
0.080
0.079
0.078
0.078
0.145
0.140
0.141
0.140
0.191
0.133
0.104
0.098
0.464
0.327
0.256
0.233
Osaka
0.070
0.070
0.068
0.068
0.127
0.123
0.124
0.123
0.193
0.127
0.101
0.095
0.465
0.314
0.247
0.226
Hyogo
0.062
0.061
0.060
0.060
0.114
0.110
0.110
0.109
0.154
0.107
0.083
0.076
0.374
0.262
0.203
0.180
Nara
0.068
0.067
0.067
0.067
0.125
0.121
0.121
0.121
0.162
0.109
0.082
0.075
0.390
0.268
0.202
0.180
Wakayama
0.060
0.060
0.059
0.059
0.110
0.108
0.108
0.108
0.122
0.094
0.076
0.071
0.299
0.230
0.189
0.171
Tottori
0.096
0.096
0.097
0.096
0.178
0.174
0.175
0.176
0.181
0.147
0.119
0.109
0.451
0.353
0.292
0.260
Shimane
0.095
0.096
0.096
0.096
0.177
0.174
0.175
0.176
0.163
0.134
0.112
0.106
0.403
0.322
0.277
0.254
Okayama
0.091
0.091
0.090
0.090
0.166
0.162
0.162
0.163
0.190
0.147
0.120
0.115
0.466
0.358
0.294
0.275
Hiroshima
0.077
0.077
0.076
0.076
0.140
0.137
0.138
0.138
0.173
0.130
0.104
0.099
0.421
0.315
0.255
0.236
Yamaguchi
0.081
0.082
0.082
0.081
0.150
0.147
0.148
0.148
0.158
0.120
0.097
0.093
0.387
0.292
0.239
0.221
Tokushima
0.097
0.096
0.096
0.096
0.180
0.176
0.175
0.177
0.192
0.151
0.119
0.109
0.471
0.363
0.294
0.261
Kagawa
0.083
0.083
0.083
0.083
0.154
0.151
0.151
0.152
0.170
0.134
0.107
0.102
0.416
0.322
0.264
0.242
Ehime
0.058
0.057
0.057
0.056
0.107
0.104
0.104
0.104
0.115
0.088
0.069
0.063
0.283
0.214
0.171
0.151
Kochi
0.094
0.094
0.093
0.093
0.174
0.170
0.171
0.172
0.168
0.133
0.106
0.099
0.418
0.324
0.263
0.237
Fukuoka
0.100
0.099
0.098
0.098
0.181
0.177
0.177
0.178
0.242
0.180
0.141
0.130
0.590
0.437
0.347
0.312
Saga
0.114
0.113
0.113
0.113
0.210
0.205
0.203
0.205
0.233
0.186
0.149
0.134
0.575
0.448
0.369
0.323
Nagasaki
0.090
0.090
0.090
0.090
0.167
0.164
0.164
0.164
0.181
0.139
0.109
0.096
0.445
0.337
0.270
0.231
Kumamoto
0.110
0.110
0.111
0.111
0.201
0.198
0.199
0.200
0.214
0.170
0.139
0.127
0.528
0.411
0.342
0.305
Oita
0.089
0.089
0.089
0.089
0.164
0.161
0.161
0.162
0.174
0.133
0.106
0.099
0.428
0.324
0.262
0.236
Miyazaki
0.100
0.099
0.100
0.100
0.184
0.181
0.181
0.182
0.199
0.151
0.119
0.106
0.488
0.366
0.292
0.256
Kagoshima
0.093
0.091
0.092
0.092
0.171
0.169
0.167
0.169
0.174
0.140
0.112
0.098
0.431
0.337
0.276
0.235
Okinawa
0.122
0.117
0.115
0.115
0.216
0.212
0.209
0.209
0.338
0.257
0.203
0.171
0.817
0.612
0.492
0.409
Mean
0.075
0.074**
0.074**
0.073**
0.138
0.134**
0.134**
0.134**
0.166
0.124**
0.098**
0.089**
0.406
0.301**
0.241**
0.213**
The Wilcoxon Signed-Ranks Test with the Bonferroni correction was employed for comparisons between 2015 and other time points
**p < 0.001

Statistical analysis

Because the Shapiro–Wilk test did not confirm the normality of the data distribution, the Wilcoxon Signed-Ranks Test with the Bonferroni correction was employed for comparisons between 2015 and other time points. A value of p < 0.05 was considered significant. The data analysis was performed using R for Windows, Version 3.6.3 (The R Foundation for Statistical Computing, Vienna, Austria) [11].

Results

Table 1 displays forecasts of the number of psychiatrists and patients with mental illness in each prefecture. The mean numbers of psychiatrists and patients with schizophrenia and mood disorders in 2025, 2035, and 2045 are significantly lower than those in 2015. In each prefecture, excluding Tokyo, the number of psychiatrists is forecasted to decrease. Similarly, the number of patients with schizophrenia or mood disorders in each prefecture, excluding Tokyo and Okinawa, will decrease by 2045. On the other hand, the mean numbers of patients with vascular dementia and Alzheimer’s disease at the abovementioned three time points will be significantly higher than those in 2015. In all prefectures, the number of patients with vascular dementia or Alzheimer's disease is projected to increase by 2045. Figure 1 shows the relationship between population growth rate and patient growth rate from 2015 to 2045 in each prefecture. We also summarized the number of psychiatrists per patient (Table 2). The mean number of psychiatrists per patient for patients with schizophrenia, mood disorders, vascular dementia, and Alzheimer’s disease at the abovementioned three time points is projected to be significantly lower than in 2015.
The GC and HHI for each mental illness are shown in Figs. 2 and 3, respectively. The results show that both the GC and HHI for the four mental illnesses will increase.

Discussion

In this study, we predicted psychiatrists’ distribution for patients with mental illness in Japan. On the supply side, the mean numbers of psychiatrists in 2025, 2035, and 2045 are significantly lower than those in 2015. On the demand side, in line with depopulation, the mean numbers of patients with schizophrenia and mood disorders are significantly lower than those in 2015. However, regarding vascular dementia and Alzheimer’s disease, the mean numbers of patients with these diseases at the abovementioned three time points are significantly higher than those in 2015. For all of the abovementioned diseases, the HHI will consistently increase from 2015 to 2045. Regarding the supply–demand balance, the mean number of psychiatrists per patient for patients with schizophrenia, mood disorders, vascular dementia, and Alzheimer’s disease at the abovementioned three time points is significantly lower than in 2015. For all of the abovementioned diseases, the GC will consistently increase from 2015 to 2045.
In Japan, the shortage of physicians, including psychiatrists, has recently become a serious public health issue [12, 13]. Several studies have indicated that the cause of this shortage is related not only to the absolute number of physicians but also to their maldistribution [14, 15]. Regarding the mental healthcare system in Japan, the absolute number of psychiatrists increased from 1996 to 2012, while the GC based on the number of physicians per population did not change during the same period [16]. Because the population decline has continued to accelerate since the population peaked at 128 million in 2008 [17], we could not predict the future demand–supply balance and equality based on this short observation period. Furthermore, different patterns of healthcare services utilization for each mental illness were not considered in the analysis, and changes in the population structure might not be consistent with the utilization patterns of patients. A study from the US [18], in which the population is predicted to increase in the future, indicated that a shortage of psychiatrists per population will occur despite the increasing number of psychiatrists. Apart from mental illness, Ishikawa and colleagues forecasted the distribution of physicians for patients with acute myocardial infarction, cerebral stroke, and all medical care in Hokkaido [5]. Their results indicated that the GCs for the abovementioned three conditions will decrease from 2015 to 2035, while the HHIs will increase in Hokkaido.
Our results indicate that the change in disease structure with the increase in patients with dementia and decrease in those with schizophrenia and mood disorders will continue until 2045. Unlike the overall trend, the predicted number of patients with schizophrenia or mood disorders had not decreased in Okinawa and Tokyo by 2045. The high birth rate of Okinawa, and the migration of young people to Tokyo, might explain these predictions. The mean number of psychiatrists per patient with mental illness, especially dementia, is predicted to decrease in the same period. The maldistribution of psychiatrists will worsen in the future. To overcome this inequity, policy makers should make plans for not only the adequate geographical allocation of healthcare resources, but also the shifting of responsibilities from psychiatrists to other mental health workers. The use of information and communication technologies (ICTs) for the delivery of health services to rural communities and improved productivity of psychiatrists with more effective interventions would also ameriolate the inequity.
Several limitations of this study should be acknowledged. First, our study focuses on the number of psychiatrists as the supply side of the mental healthcare system. However, human resources in the healthcare system consist of not only psychiatrists but also nurses and other health care professionals. Furthermore, the accessibility, number and performance of medical facilities are also important factors for the supply side of the system. Analysis of supply and demand in view of these various factors is important for carrying out a more detailed analysis that will be useful for supporting policy formulation. Increasing data collection on relevant values will minimize the limitations in this area. Second, we estimated the number of psychiatrists using population projections until 2045 and psychiatrists' distribution in 2015. Our results indicate that the shortage of psychiatrists will continue to worsen if psychiatrists are allocated at the current population-to-psychiatrist ratio. However, the age distribution, retirement patterns, and future supply of psychiatrists could affect the future number of psychiatrists. Further updating research is needed to predict the number of psychiatrists for forecasting the supply–demand balance accurately. Third, our results are limited by the fact that the utilization-based approach is based on several assumptions, as with other modeling methods. The utilization-based approach could result in an over-estimation of the demand, particularly in service areas open to supply-induced demand (for instance private psychiatry services) or areas where best practices are poorly implemented. The assumption of this approach is that patients’ behavior will not change during the forecast period. Several factors, such as innovations in preventive medicine, screening and treatment, changes in medical care preferences, and changes in the capacity of the population to pay for services, could affect the behaviors of patients with mental illness. Although this analysis is based on a fixed value for the utilization rate, future research with newer rates would enable us to provide more accurate results.
In conclusion, this study forecasts the psychiatrists' distribution for patients with mental illness to analyze the healthcare supply–demand balance based on a utilization-based approach. While the number of patients with schizophrenia or mood disorders in each prefecture, excluding Tokyo and Okinawa, will decrease by 2045, the number with Alzheimer's disease or vascular dementia in all prefectures is projected to increase. For the four mental illness estimated considered, the difference between prefectures in the minimum and maximum number of psychiatrists per patient were approximately 2-folds or more in 2015. As long as psychiatrists are allocated at the current population-to-psychiatrist ratio, the shortage of psychiatrists will continue to worsen in the future. To overcome this inequity, it is necessary to discuss incentives for medical services in rural area, or mandatory requirement of practice in rural areas for psychiatrists who become board-certified psychiatrist. Although this analysis is based on a fixed value for the utilization rate, future research with frequent model updating would yield more accurate results.

Acknowledgements

We would like to thank all the participants and coworkers who contributed to the SPDP, Population Projections, Population Census, and Patient Survey.

Declarations

No ethical approval is required for the manuscript under the standard of the ethical review board in our university.
Not applicable.

Competing interests

The authors declare that they have no competing interests.
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Metadaten
Titel
Projections of psychiatrists’ distribution for patients in Japan: a utilization-based approach
verfasst von
Norio Sugawara
Norio Yasui-Furukori
Kazutaka Shimoda
Publikationsdatum
01.12.2021
Verlag
BioMed Central
Erschienen in
Human Resources for Health / Ausgabe 1/2021
Elektronische ISSN: 1478-4491
DOI
https://doi.org/10.1186/s12960-021-00594-z

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