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GEOGRAPHIC ACCESS TO PHYSICIAN SERVICES Joseph P. Newhouse Division of Health Policy Research and Education, Harvard Medical School, Boston, Massachusetts 02115

Prior to the last decade, it was widely accepted that physicians were geo­ graphically maldistributed; indeed, a major federal initiative, the National Health Service Corps, was based on that premise (24). The maldistribution most commonly referred to was between urban and rural areas, although there was some reference to maldistribution within urban areas as well. The usual evidence cited to show the existence of maldistribution was unequal physician/population ratios between urban and rural areas, examples of which are in Table 1 . (Although the data that I and others cite in fact distinguish metropolitan and nonmetropolitan communities, I use the less exact, but more familiar terms, urban and rural.) In addition, especially in the late 1960s and early 1970s, there were examples of towns that werc losing physicians; that is, physicians were retiring and not being replaced. The conventional view of maldistribution was not undergirded by a well­ articulated theory of how physicians chose to locate their practices; numbers analogous to those in Table 1 were believed to speak for themselves. To the degree a theory of physician location existed, it seemed to be of the following sort: Physicians prefer to locate in cities. Because of virtually unlimited demand for their services, or their ability to create demand, physicians can afford to locate in cities and thus can continue to indulge their preferences. (See Ref. 19, Appendix A, for examples of quotations along these lines.) Moreover, it was probably the case that during the 1960s, maldistribution, as conventionally defined, was worsening; that is, the inequalities in physician/population ratios were growing. This, however, is difficult to 207

0163-]525/9010510-0207$02.00

208

NEWHOUSE Table 1

Physician/population ratios in met­

ropolitan and non-metropolitan areas (office­ based physicians per 100,000 persons) Year

Metropolitan

Non-metropolitan

1970 1980

112 135 152

51 74 92

1985

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Source: Calculated from data in American Medic­

al Association, Physician Characteristics and Dis­ tribution in the US, 1987 ed. Table A-6, and Statis­ tical Abstract, 1988, Table 30. Data for 1986 show a fall in physicians in non-metropolitan areas from

1985;

however, it appears that the definition of a

metropolitan area has not been held constant. For

the 1987 edition of Physician Characteris­ 1986 figure is based on 3 I 7 metropolitan areas, whereas the 1986 edition of Physician Characteristics says the 1985 figure, which is the same figure for 1985 as in the 1987 edition , is based on 300 metropolitan areas. It appears, then, that some physicians who were non­ metropolitan in 1985 have been reclassified as met­ ropolitan in 1986 because the county in which they example,

tics

states that the

were located has been reclassified as metropolitan.

demonstrate definitively_ The data in Table 1 on the growth rates of physi­ cians in various locations do not go back before 1970 because the American Medical Association changed its classification scheme for physicians in the

late 1960s, a change that makes deriving a consistent time series difficult. Growth rates for physicians in nonmetropolitan areas in the late 1960s were probably stagnant, but probably were growing in metrop olitan areas. If so, it is not difficult to understand the appeal of the claim that physicians were maldistributed and that any increase in the number of physicians that were being trained would do little to alleviate the problem.

About a decade ago I and my colleagues began to apply standard economic location theory to physician practice patterns ( 17, 18, 26, 27). Somewhat to our surprise, given the unanimity of prior literature that standard theory did not apply, we found that the testable propositions derived from location theory fit the data. As is to be expected with any challenge to widely held prevailing views, our work has been controversial. In this article, I begin by sketching our theory of physician location and

consider its testable hypotheses. I then discuss the empirical evidence supporting this theory and the policy implications. I then consider subsequent criticism, and I conclude by briefly discussing the logical next steps for research in this field.

GEOGRAPHIC ACCESS TO PHYSICIANS

209

AN ECONOMIC THEORY OF PHYSICIAN LOCATION Standard location theory was developed to predict choices of profit­ maximizing firms in locating production. With relatively minor mod­ ifications, this theory can also be applied to location choices of physicians. The standard theory assumes that firms locate so as to maximize their profits. Calculation of profit at alternative locations typically involves both demand and cost at those locations; for purposes of simplicity, we can be

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principally concerned with demand. Consider a physician who is deciding on a location for his/ber practice. Suppose initially that all locations are equally preferable except for demand factors; i.e. such factors as climate, cultural opportunities, congestion, pollu­ tion, and the cost of producing physician services all balance out. Suppose further that demand per person is on average the same in each location. Instead of locating so as to maximize profits, we assume that under these conditions physicians will locate so as to maximize the demand they face. This choice may be made because it will permit physicians to charge the highest prices (i.e. maximize profit) or do the most interesting work (i.e. see the most interesting cases). Figure 1 provides a simple example and will also serve to motivate tests of several hypotheses. Suppose there are three towns on a highway. The towns are equally attractive to a physician except for their size; one has a population of 5000; one of 30,000; and one of 10,000. No one lives between the towns. The location of physicians, with four different total numbers of physicians, 1, 4,

9, and 18, shown on the right, are pictured. Why the numbers are as they

- 1 ----------1----------1------

1

- 1 ---------- 1 ---------- 1 ------

4

0

1

1

0

3

0

- 1 ---------- 1 ----------1-----2

-

1

6

----------

4

10,000 Figure 1

1

9

1

----------

12 30,000

1

------

18

2 5,000

Location of physicians with one, four, nine, and 18 total physicians.

210 are

NEWHOUSE

I discuss below. I also assume that demand for physician services falls as

travel time increases; there is considerable empirical support for this assump­ tion

(21). To simplify the numerical example, I make the extreme assumption

that people will not travel outside their town at all to seek care; this extreme assumption, however, is not necessary to derive the hypotheses. Suppose none of the three towns currently has a physician, and a new physician is seeking to choose among them. The theory predicts that the physician will locate in the town of

30,000 because the demand for services is

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greatest there. Notice that if demand does not fall with travel time, the physician could locate in any of the three towns and would face the same demand because individuals would travel from all three towns to where the physician was located. If a second physician enters the market represented by these three towns, he or she will also locate in the town of

30,000, because locating there will

maximize the demand faced by the second physician. So, too, will a third physician. The fourth physician entering the market, however, will locate in the town

10,000; that will lead to more demand for that physician's services than would becoming the fourth physician in the town of 30,000 (line 2 of the

of

Figure). This is where 1 use the extreme assumption that people will not

30,000, 30,000 people four ways, whereas all four physicians have a market of 10,000 people if the physician enters the town of 10,000. Suppose, however, that people in an unserved town will travel for

travel. If they do not travel and the physician locates in the town of the physician splits a market of

care, but people in a served town obtain care locally. In this more realistic case, where the fourth physician locates depends upon the factor by which

30,000, 7500 patients from the town of 30,000 plus a one quarter share of the 15,000 patients (3750 patients) from the other two

travel diminishes demand. If the fourth physician enters the town of he or she has (by assumption)

towns diminished by however much travel deters demand. If travel diminishes

30,000, the 30,000; otherwise the physician

demand by less than one third relative to demand in the town of fourth physician would prefer the town of

10,000. If the fourth physician chooses the town of 30,000, the fifth would enter the town of 10,000.

will locate in the town of

Not until there are nine physicians in the market, however, can the town of

5000 be assured of having a physician. (The eighth physician will be in­ different in choosing between being the first physician in the town of 5000 or being the second in the town of 10,000, and the ninth physician will choose whichever of those two options the eighth physician did not choose). Thereaf­ ter, as still more physicians enter the market, each town will gain physicians proportionately. Several testable hypotheses can be derived from this theory:

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GEOGRAPHIC ACCESS TO PHYSICIANS

211

1. For any given number of physicians, as city size increases, the likeli­ hood that a city has one or more physicians increases. In the pure theoretical case just described, for any given total number of physicians there is a critical town size. Above that critical size all towns will have a physician, and below it none will. For example, with two physicians the critical town size in the example is between 10,000 and 30,000; with six total physicians it is between 5000 and 10,000. In reality, of course, the assumptions of the pure model are not satisfied. Towns are not equally attractive. Demand per person differs somewhat. The size of surrounding populations differs. All these factors act as random error in location decisions; as a result, some towns below the critical town size will have a physician and some above it will not. Nonetheless, there should be a systematic relationship between the likelihood that a town has a physician and its size. (See Ref. 17 for a formal model that incorporates random error.) 2. Suppose we group towns with a population size in a given interval together; for example, in Figure 1 suppose we group the towns of 5000 and 10,000 population together. Suppose the total number of physicians grows. Then the theory predicts that town-size groups that began the period with at least one physician in each town will gain physicians at the same rate, and town-size groups near the critical town size will gain them at a faster rate. For example, as the number of physicians in the example goes from four to nine (lines 2 and 3 of the Figure), the number in the town of 30,000 doubles (from 3 to 6), but the number in the towns of 5000 and 10,000 triples (from 1 to 3). This is a direct consequence of some towns' gaining physicians for the first time. Of course, small towns that are well below the critical town size may not gain physicians at all. For example, as the number of physicians grows from two to three, nothing happens in the towns of 5000 and 10,000, and if there were a fourth town of 500, it would not gain a physician as the numbers grow from four to nine. Thus, growth rates will be highest in town size groups just below the critical town size. 3. To this point we have not taken cognizance of specialties. If specialties did not compete with each other, there would be no need to bring specialty into the analysis. In that case it would follow from the first hypothesis that the critical town size would be less for larger specialties and that physicians in such specialties would therefore be more diffused. (That is, a large specialty would be like the bottom line, with 18 physicians, and a small specialty would be like the top line, with one.) In reality, however, there is a certain amount of competition among specialties; this is perhaps most apparent between a general (or family) practitioner, on the one hand, and a general internist (or general pediatrician), on the other, but almost all specialists perform some service or procedure that

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212

NEWHOUSE

other specialists also perform. Competition among specialties alters the sim­ ple prediction that larger specialties will be more diffused. To illustrate the issue, suppose a general practitioner and a general internist are located in the same city. Consider first a patient who is interested in obtaining a service that both physicians perform. Some consumers may not know or care about the difference in training between the two physicians or may find other factors more important in choosing which of the two to use, but other consumers may care and prefer the internist. If this is the case, some patients who are equidistant between the internist and the general practitioner will prefer the internist. Thus, the internist in the city will have a larger market area than the general practitioner. (This will also be true if, as seems likely, a referring physician is more likely to refer to the internist.) It follows that to the general practitioner, the city is more like a small town without an internist, and that therefore general practitioners are more likely to be located in smaller towns; internists and other more special­ ized physicians are more likely to be located in larger cities. Another mechanism will lead to the same result. The last few paragraphs have discussed services or procedures that both the less specialized and the more specialized physician perform, but now consider services that only the more specialized physician performs. In maximizing the demand faced for those services, the mechanism for location will be like that described for a non-competing specialist. The first specialist (e.g. internist) will tend to locate in the largest city (the town of 30,000 in the example). Once the specialist is located in the large city, however, he or she will provide not only the non-competing services but also the competing services. A general prac­ titioner or less specialized physician will then find it more attractive to locate in a smaller city; in effect, part of the market for general practitioner services has already been taken in the larger cities. In other words, specialists are disproportionately in cities because it is worth more to the more specialized physician (the one with the unique service) to be located there. The model described above has been extended by Baumgardner (la) to consider greater and lesser scope of practice within practices of physicians who label themselves similarly (e.g. general practitioners). EMPIRICAL EVIDENCE All these hypotheses are strongly supported by the data. Table 2 shows the location of various specialists in 1970 and 1979, a period of large growth in the number of physicians. Note that in any given year the proportion of towns with a given type of physician rises with population (hypothesis 1); one can reject the hypothesis that there is no relationship between a town's population and the likelihood that it has a given type of specialist (p « 0.01). Similar

GEOGRAPHIC ACCESS TO PHYSICIANS Table 2

213

Percentage of communities with nonfederal physician specialty services in 1970 and 1979" Number of

FIE physi-

Percentage of communities, by size of populationC

ciansb in 23 Specialty and year Group

sample states

2,5-5

5-10

10 -20

20-30

30-50

50-200

200+

I

General and family

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practice 1970

11,514

89

96

99

100

100

100

100

1979

11,869

86

96

99

100

100

100

100

1970

5242

17

40

69

96

100

100

100

1979

9467

23

52

84

97

100

100

100

Group 2 Internal medicined

General surgery 1970

5214

42

79

97

100

100

100

100

1979

6071

44

77

96

100

100

100

100

1970

2928

13

32

74

96

100

100

100

1979

3978

15

35

77

97

100

100

100

Obstetrics/ gynecology

Pediatrics" 1970

2263

6

17

57

92

100

100

100

1979

3429

12

25

68

92

100

100

lOa

1970

1990

3

12

28

46

91

lOa

100

1979

3203

9

17

40

59

96

lOa

100

1970

1823

5

22

60

88

100

lOa

lOa

1979

3042

9

30

73

97

100

lOa

lOa

Psychiatry

Radiology

Group 3 Anesthesiology 1970

1527

11

19

34

65

90

97

100

1979

2303

11

19

40

83

lOa

lOa

100

Orthopedic surgery 1970

1380

2

6

29

67

91

100

lOa

1979

2409

7

17

47

88

100

100

100

1970

1539

2147

4 4

15

54

87

lOa

lOa

lOa

1979

14

62

89

100

100

100

4

8

36

71

50

95

100

100

15

85

95

100

100

Ophthalmology

Pathology 1970

1979

1073

1840

214

NEWHOUSE

Table 2

(continued) Number of

FfE physiciansb in Specialty and year

Pe rcent age of communities, by size of population"

23

sample states

2.5-5

5-10

7

29

62

98

100

100

10

47

89

100

100

100

10-20

20-30

30-50

50-200

200-t

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Urology 1970

950

1979

1340

2

1970

902

2

9

38

85

95

100

100

1979

1127

2

6

29

79

98

98

100

Otolaryngology

Dermatology 1970

528

3

10

31

79

100

100

1979

795

3

15

59

96

98

100

4

6

25

48

73

100

4

13

24

70

98

100

Group 4 Neurology 1970

395

1979

724

0

1970

349

0

2

8

28

78

IOU

1979

523

0

2

18

56

88

100

1970

210

0

1

2

16

51

97

1979

430

8

20

46

83

100

Neurosurgery

Plastic surgery

Any physician 41, 325 58,911

1970 1979

92

97

99

100

100

100

100

90

97

100

100

100

100

100

Number of towns in

1970

615

352

182

52

58

37

33

each population

1979

644

.379

206

66

57

40

34

range "Data are from the h

23 states (FIE)

Full-time equivalent

December

31 .

listed in

(18).

Population of towns is specific to the relevant year.

physic ians in hos pital and office-based practice. excluding resident physicians, as 0

For physic ians with more than one specialty, fractions of FIEs are allocated according to the rules describe,

in the text .

'In thousands. d Includes cardiology. gastroenterology, and pulmonary diseases. e

Includes pediatric cardiology and other pediatric subspecialties; does not include pediatric allergy.

results have also been found in Quebec (4). It is also apparent that towns gained physicians as the number of physicians grew; that is, the critical town s ize decreased in virtually every specialty (hypothesis 1). Although there is an association between the number of physicians in a given specialty and the critical town size (i.e. how diffused the specialty is), the association is not perfect. For example, although there are more internists

GEOGRAPHIC ACCESS TO PHYSICIANS

215

than general surgeons, surgeons tend to be in smaller towns (the critical town size is smaller for surgeons). This may be partly

an

artifact, because some of

the internists are medical subspecialists, and the true number of general internists is less. Nonetheless, there are probably more general internists than general surgeons, so the question of why surgeons are more diffused is still pertinent. We interpret the greater diffusion of the surgeons as reflecting the substitution between the general practitioner and the internist discussed above; there appears to be a greater overlap between the general practitioner

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and the internist than between the general practitioner and the surgeon. As predicted by the third hypothesis, general and family practitioners are concentrated in smaller towns (Table 3), most likely for reasons discussed above. The second hypothesis predicts that growth rates will be greater in town sizes at and just below the critical town size. This hypothesis is also supported by the data (Table 4); for a formal test of the hypothesis see Ref. 17. The formal test rejects the null hypothesis that town-size groups just below the critical town size have the same growth rates as larger town-size groups at the

1 % level. One somewhat aberrant specialty with respect to these predictions appears to be otolaryngology; not only are growth rates lower in the smaller town size groups (Table 4), but fewer communities of 5000 to 30,000 actually had such a specialist in residence in 1979 than in 1970, despite growth in the specialty

Table 3

Location of office-based physicians , 1979

Country type and size

General and family

Medical plus sur-

practitioners per

gical specialists per

100,000 population

100,000 population

Nonmetropolitan counties Less than 10,000 inhabitants

28.6

7.6

Less than 25,000 inhabitants

29.0

14.8

Less than 50,000 inhabitants

26. 1

34.4

50,000 or more inhabitants

22.1

50.0

19.4

64.8

66.3

Potential metropolitan counties Counties in standard metropolitan statistical areas

50,000 to 499,999 inhabitants

20.4

500,000 to 999,999 inhabitants

17.9

73.4

1,000,000 to 4,999,999 in-

19.0

80.4

21.00

86. 3

habitants

5,000,000 or more inhabitants

Source: American Medical Association. Physician Characteristics and Distribution in the US, 1980.

216

NEWHOUSE

Table 4

Ratio of specialists per person in 1979 t o specialists per person in 1970' Specialist-to-person ratios, 1979/1970, by size of townb

Specialty

2.5-5

5-10

Internal medicine

1.79

General surgery

1.08

Obstetricslgynecology Pediatrics

10-20

20-30

30-50

50-200

200+

1.56

1.64

1.54

1.62

1.68

1.65

1.00

1.04

1.08

1.06

1.02

1.08

1.50

1.27

1.23

1.42

1.25

1.21

1.22

2.66

1.62

1.36

1.43

1.38

1.35

1.35

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Psychiatry

1.29

1.30

1.56

1.42

1.34

1.50

Radiology

2.19c

1.50

1.34

1.38

1.44

1.39

1.56

Anesthesiology

1.01

1.01

1.40

1.46

1.44

1.28

1.42

3.46c

1.92

1.95

1.70

1.51

1.47

Orthopedic surgery Ophthalmology

1.18

1.39

1.29

1.39

1.17

1.26

Pathology

2.06c

1.52

1.45

1.49

1.31

1.57

Urology

1.43c

1.70

1.63

1.36

1.18

1.20

Otolaryngology

0.97c

0.91

1.06

1.30

1.23

1.14

Dermatology

1.44

1.79

1.56

1.31

1.33

Neurology

2.19c

1.69

3.01

1.80

1.72

2.71c

2.57

1.44

1 . 28

2.47

2.19

1.69

Neurosurgery Plastic surgery General and family practice

0.92

0.95

0.99

1.03

1.08

1.05

1.00

General practice

0.54

0.55

0.56

0.61

0.62

0.64

0.58

'Data from the

23

states listed in (18). Values for town-size intervals in which fewer

than 5% of the towns

had a given type of physician in 1970 have been deleted. If these values are regressed on the percentage of communities in a twon-size interval that had a specialist of that type in 1970, one can reject the null hypothesis

of no association at the b

1%

level. In other words, the rate of growth is faster in smaller towns.

In thousands. COnly 5 to 10% of the towns in this population range had a specialist in

1970.

(Table 2). The difference between otolaryngology and the other specialties is most likely accounted for by the same phenomenon that accounts for general practitioners' being disproportionately located in small towns (Table 3); more than 20 years ago it was common to combine ophthalmology and otolaryngol­ ogy (eye, ear, nose, and throat), but such a combination has become rare in recent years. (We counted a town as having both an ophthalmologist and an otolaryngologist if the physician indicated both specialties.) For the same reasons that general practitioners are more common in small towns than internists, those physicians who combined ophthalmology and otolaryngology would be disproportionately in small towns relative to pure ophthalmologists or pure otolaryngologists. As the physicians who combined eye, ear; nose, and throat practices retired and died, they were not replaced by a new cohort of eye, ear, nose, and throat physicians. Rather, the critical town sizes fell for the growing numbers of pure ophthalmologists and otolaryngologists, but, in the case of otolaryngologists, not to the level where the old eye, ear, nose, and throat doctors had been. In our data, this appears as a decrease in the number of small towns with such a physician.

GEOGRAPHIC ACCESS TO PHYSICIANS

217

Notice also that our data do not account for allied health personnel that compete with physicians; for example, optometrists compete with ophthal­ mologists, and psychologists compete with psychiatrists. Our theory would predict that allied health personnel would be located (relative to the counter­ part physician specialty) disproportionately in smaller towns. I have sketched above a model by which if consumers prefer internists to general practitioners (or internists are more likely to obtain referrals), in­ ternists will be located disproportionately in larger cities. The same reasoning

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applies to any type of physician that consumers may prefer. Thus, if consum­ ers prefer board-certified physicians, they will locate disproportionately in larger cities. The data strongly support this hypothesis (Table

5). Similarly, if

consumers prefer United States medical school graduates to foreign medical school graduates, United States medical school graduates will locate dis­ proportionately in larger cities.

IMPLICATIONS FOR POLICY As noted at the outset, the National Health Service Corps was established on the presumption that the market for physician services failed. Two pieces of evidence that were used to establish this proposition were the unequal physician/population ratios of the sort described in Table

1 and anecdotes

about towns losing physicians. Our theory not only predicts that physician/population ratios will be un­ equal between metropolitan and non-metropolitan areas (this follows directly from hypothesis

1), it also predicts that interventions of the type that induce a

physician to go to a manpower shortage area will be ineffective because a new physician in a town will simply displace other physicians. There are two exceptions: 1. If the intervention induces a physician to go to a town that otherwise would

not have attracted any physicians. This is a so-called "comer solution" case.

2. If the intervention alters demand for care. For example, if the National Health Service Corps is used to staff a neighborhood health center that provides free or subsidized health care, demand will increase and physi­ cians will not necessarily be displaced. Consider further the "comer solution" case; i.e. the intervention induces a physician to practice in a manpower shortage area that otherwise would not have attracted a physician. Our theory suggests that this may well be econom­ ically inefficient. Intuitively, the physician is less busy in the new location than she would have been in a larger city. Of course, one may still argue for

218

NEWHOUSE

Table 5

Percentage of specialists who were board-certified in towns of different sizes in

1970 and 1979a Percentage of specialists, by size of townb Specialty

2.5--5

5--1 0

10 20

20-30

30-50

50-200

15 43

34 46

35 52

39

44 59

54 66

47

58

18 32

30 49

43 53

52 63

61 57

60 71

60

5 34

21 38

40 56

54 71

56 70

62 60

63 68

33 43

51 57

51 57

65 74

70 71

71 74

67 67

10 33

24 27

19 30

37 42

35 40

38 49

41 47

57 71

56 72

75 80

81 90

87 88

89 92

84 88

14 29

18 39

27 36

26 45

50 53

54 59

54 58

72

62

56 72

63 77

77 83

79 88

82 85

67

38 69

49 71

53 74

73 81

73 84

72 83

86

83 78

79 87

81 85

89 89

85 90

82 87

29 58

45 73

66 80

55 75

75 82

69 82

200+

Group 2 Internal medicinec

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1970 1979

60

General surgery

1970 1979

66

Obstetrics/gynecology

1970 1979 Pediatricsd

1970 1979 Psychiatry

1970 1979 Radiology

1970 1979 Group 3 Anesthesiology

1970 1979 Orthopedic surgery

1970 1979 Ophthalmology

1970 1979 Pathology

1970 1979 Urology

1970 1979

219

GEOGRAPHIC ACCESS TO PHYSICIANS

Table 5

(continued)

Otolaryngology

27 72

1970 1979

32 65

39 69

64 82

64 77

72 84

79

72

59 74

65 82

79

43 50

60 62

46 60

50 72

49 64

75 78

37

61 58

66 68

Dermatology

1970 1979

67

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Group 4 Neurology

1970 1979

37

Neurosurgery

1970 1979 Plastic surgery

1970 1979 a

Nonfederal physicians in patient care excluding residents from 23 states listed in (18). Physicians are

expressed as fulHime equivalents. bIn thousands. C

Includes cardiology. gastroenterology, and pulmonary diseases.

d Includes pediatric cardiology. �

Fewer than

19.5

physicians in this specialty were present in this town-size interval

in

this year.

the intervention on grounds of equity; perhaps the paucity of physicians in rural areas imposes a considerable burden on rural residents to travel for care. Or, if they choose not to travel, their health might be harmed. (Placing a physician in a shortage area could be economically efficient if others in non-shortage areas were willing to pay to do so; that is, if there were externalities. Hemenway (7) argues for judging physician distribution for its effects on health and not on the grounds of economic efficiency, but if externalities are present it is not necessary to abandon economic efficiency as a criterion.) However, the argument based on equity does not appear to fit the facts. It has been shown that travel time for the overwhelming majority of rural residents is not an important issue (27); very few rural residents have to travel far in absolute terms to see most types of specialists (Table 6). (Here rural is defined as the population that lives in towns of 25,000

or

less or does not live

in towns; the majority of this group does not live in towns.) The second piece of evidence in the early 1970s supporting the notion that standard theory did not apply were anecdotes about the number of small towns who were losing physicians. (For some evidence that this process may be continuing into the 1980s, see Ref. 8.) Our theory, however, predicts a more

220

NEWHOUSE Table 6

Cumulative percentage of US rural population within various distances

of physician specialists

Straight line distance in milesb N" in Specialty

area

5

10

15

20

25

30

50

1 00

Group 1

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General and family practice 1 970

1 1 ,314

58

86

95

98

99

99

1 00

1 00

1 979

1 1 ,729

58

85

95

98

99

99

1 00

100

1970

5 19 1

25

43

59

72

82

89

97

1 00

1979

9495

33

54

70

81

89

93

99

1 00

Group 2 Internal medicine

General surgery 1 970

5 1 35

37

62

78

89

94

97

99

100

1 979

6006

40

66

83

92

96

97

1 00

1 00

Obstetrics/gynecology 1 970

3001

24

42

58

72

82

88

97

1 00

1 979

4053

28

48

65

77

86

91

98

1 00

1970

1911

11

23

34

4S

56

64

86

98

1 979

3 1 68

18

33

47

60

70

78

94

1 00

Psychiatry

Pediatrics 1970

2292

18

34

49

62

73

81

94

1 00

1 979

35 1 5

25

43

59

71

80

86

96

1 00

Radiology 1 970

1 8 26

18

34

48

60

71

79

94

1 00

1 979

3662

25

44

60

73

84

89

98

1 00

Group 3

Anesthesiology 1970

1555

13

25

37

49

59

68

88

99

1979

2364

17

32

45

57

69

77

92

1 00

Orthopedic surgery 1 970

1 347

8

19

30

42

53

63

87

98

1979

2381

18

34

48

61

73

80

95

1 00

Ophthalmology 1 970

1 509

15

29

42

55

69

77

93

1 00

1979

21 1 3

20

36

50

63

75

82

96

1 00

1 970

1049

11

23

34

47

59

68

90

99

1 979

1797

18

33

47

61

73

81

96

1 00

Pathology

221

GEOGRAPHIC ACCESS TO PHYSICIANS Table 6 (continued) Urology 99

1970

941

9

20

31

43

55

64

88

1979

1327

15

29

42

55

68

76

94 100

Otolaryngology 1970

880

13

25

37

50

64

13

92 100

1979

1139

13

27

38

51

63

71

90

99

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Dennatology 1970

534

5

13

22

33

45

54

80

97

1979

792

8

19

30

41

52

62

87

98

Group 4 Neurology 1970

370

4

II

17

25

33

41

67

93

1979

749

8

17

27

37

48

57

82

98

Neurosurgery 1970

352

3

8

14

21

29

37

62

93

1979

519

4

12

19

27

37

45

74

95

1970

214

1

5

10

14

21

26

49

86

1979

437

5

13

21

30

40

48

73

96

Plastic surgery

Any physician

•

1970

60

87

96

98

99

99 100 100

1979

61

87

96

98

99

100 100 100

N

denotes the number of full-time-equivalent

(FfE)

physicians in hospital- and office-

based practice (excluding resident physicians) in the area of study as of December

31.

For

physicians with more than one specialty. fractions of FfEs were allocated according to the rules described in the text. The area of the study comprised the described in (27). b Actual driving distances are 20 to 25% greater.

16 slates and surrounding areas

rapid rate of growth of physicians in small towns than in large cities, and if that prediction is correct, as Table 5 suggests it is, there should have been few instances of this. Thus, the anecdotes not only appear to conflict with our theory but also with our data. In fact, there may be no conflict. The explanation is that the theory and data apply to a given specialty. In the 1960s it is likely that a process akin to that described above for the eye, ear, nose, and throat doctor was occurring on a much larger scale with respect to the general practitioner. Relatively few medical students were entering general practice in the 1960s. Thus, the cohort of older general practitioners was not being replaced (Table 7). The critical town size for internists, pediatricians, and other specialties was falling, but it had not fallen far enough that physicians in these specialties were locating in all the towns that were losing their only general practitioner. Thus, just as some small communities were losing otolaryngologists, an even larger num-

222

NEWHOUSE Table 7

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Year

Number of general and family practitioners

General practitioners

Family practitioners

Sum

1965

7 1,366

7 1,366

1970

57,948

57,948

1975

42,374

12,183

54,557

1980

32,519

27,530

60,049

1985

27,030

40,021

67,051

Source: American Medical Association, Physician Characteristics US, 1987 edition.

and Distribution in the

ber were probably losing general practitioners. Such a loss was, of course, a considerable problem for the communities affected, a problem that the National Health Service Corps was to address. Another response to the problem, a response subsidized by federal monies, was the establishment of family practice training programs. For the same reasons

that

we

would

expect

general

practitioners

to

locate

dis­

proportionately in small towns, we would also expect family practitioners to locate disproportionately in small towns (relative to more narrowly special­ ized physicians such as internists and pediatricians). Thus, over the longer term such training programs promised to address the problems of communi­ ties that had lost their only general practitioner. Family practitioners, however, may not locate in the same fashion as general practitioners. Because family practitioners are better trained than general practitioners, they may be better able to compete against internists and pediatricians in the large city; hence, they may not be in as many small towns as were general practitioners. The evidence on where the newly trained family practitioners are locating is not yet in, partly because it is difficult to distin­ guish in the data general practitioners who had settled somewhere and then became certified in family practice but did not change their location. Our theory also sheds light on a different type of response to the perception of the availability of too few physicians in rural areas, namely training more medical students who are reared in rural areas (23). This response is based on research in which individual physicians are used as the unit of observation. A typical study will use logistic regression, in which the dependent variable indicates whether a physician is practicing in a rural area and the explanatory variables are the characteristics of the individual physician. The physician's place of rearing is often the most important explanatory variable (3, 20). It does not necessarily follow, however, that increasing the number of physicians reared in rural areas will change the distribution of physicians. Take the example shown in Figure 1, and suppose that physicians prefer to practice in the towns in which they were reared. Suppose further that six physicians were reared in the town of 30,000, two in the town of 10,000, and

GEOGRAPHIC ACCESS TO PHYSICIANS

223

one in the town of 5000. It is apparent that the preferences of all can be accommodated within the numbers of physicians per town that our theory predicts. Stated another way, predictions of the aggregate number of physi­ cians in each town from our theory would be correct, but one would also find a perfect correlation between place of rearing and location. Now suppose that the physician who was reared in the town of 5000 in fact did not care where she practiced. As long as the facts are as described above, nothing observable would change; that is, the six physicians who were reared

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in the town of 30,000 would still be found practicing there and so on. Now let the distribution of medical students be deliberately skewed, such that there are two physicians taken from the town of 5000 and only five from the town of 30,000. According to our theory, the numbers of physicians per town will not change; if the second physician who was reared in the town of 5000 cares about living there, the first physician, who by assumption does not care, will practice in the town of 30,000. In the jargon of economics, the change is inframarginal. Of course, a suffiCiently discriminatory admissions policy (favoring those reared in small towns) will change the equilibrium distribution of physicians to favor small towns; however, it will not change it by as much as one would project on the basis of logistic regression coefficients. The reason is that as more physicians begin to practice in smaller towns, income per physician in small towns will start to fall, and this will induce some physicians who otherwise would have chosen to practice in small towns not to locate there. To summarize, altering the distribution of medical students to favor those reared in small towns may not change the number of physicians located in small towns at all and will almost certainly not change it by as much as one would predict on the basis of examining where individual physicians with varying characteristics have chosen to locate. For similar reasons, an admissions policy that favors residents of a state may generate little or no increase in the supply of physicians in a state, assuming, as appears to be the case, that there is a national market for physicians. Also, for similar reasons, the effect of a decrease in foreign medical graduates cannot be projected by simply looking at where such personnel are now located. It is often claimed that inner city and rural areas will be disproportionately affected by limitations on the entry of such persons into the country. Although this is likely to be the initial impact, according to the theory we have outlined, a disproportionate decrease in the physician supply in such areas would cause other physicians to move into such areas, and in the long run they should be proportionately affected. In other words, it should not be assumed that United States graduates will not go to such areas simply because they are not there now.

224

NEWHOUSE

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OTHER VIEWS The theory described above has been controversial ( l b, 5, 9, 23). This controversy has resulted in part because of a theoretical misunderstanding and in part because of misinterpretation of empirical data. The theoretical misunderstanding is at bottom semantic and involves label­ ing this the "trickle-down" theory ( l b, 16, 23). It is not clear what those who use the term "trickle-down" mean by it but, as is clear. from Figure 1, a more accurate descriptive term would be "spreading-out." The term "trickle down" implies that large cities "fill up," and then additional physicians no longer go to large cities but instead start to go to small towns. As is clear from Figure 1 and Table 4, this is not correct either as a description of the theory or as a representation of reality. The major empirical misunderstandings have been to continue to analyze data that aggregate across specialties and/or to continue to cite inequalities in physician/population ratios as evidence that physicians are maldistributed, with the implication that one could and should intervene to change this (5, 9). I have discussed above the difficulties caused by aggregating across special­ ties. In particular, because general practitioners comprised a large percentage of small town physician supply (Table 3) and because they were not growing in line with other specialties (indeed, they were falling in numbers!) (Table 7), the aggregate number of physicians in small towns was not growing as fast as in large towns in the 1960s. Now that the decrease in general practitioners is coming to an end and the training of family practitioners is increasing, this factor will be less important in aggregated statistics. Nonetheless, it appears to make little sense to count two internists the same as an internist and a pediatrician, as does aggregating across specialties. I have also pointed out that in an economically efficient allocation of physicians, there would always be some inequality because towns below the critical town size will tend not to have physicians. Note that some critics, arguing that there would have to be a large increase in total numbers before some physicians would "trickle down" to rural areas, claim that, as a strategy for attracting physicians to rural areas, expansion of aggregate numbers is "inefficient" (e.g. Ref. Ib). This use of "inefficient" is not in the economic sense. More fundamentally, should one try to attract more physicians to rural areas? One argument supporting this view is based on the observed inequali­ ties in physician/population ratios (Table 1) and presumes that they imply an access problem. The observed inequalities, however, are misleadingly large if they are used to make inferences about the relative access of rural residents to physicians. The usual interpretation is of the reciprocal population per physi-

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GEOGRAPHIC ACCESS TO PHYSICIANS

225

cian-that patient loads of physicians in rural areas are higher and therefore access is poorer (2). Such an interpretation is unwarranted. First, as Reinhardt (25) was the first to emphasize, access to physician services is not necessarily proportional to the number of physicians; in particular, physicians may substitute allied health personnel for their own professional time. Second, the interpretation assumes that residents of rural areas seek care from physicians in rural areas. But in fact 16% of patient visits occur outside the patient's county of residence (10). For residents of rural areas, the closest physician may be in a metropolitan area, or in any event, residents of non-metropolitan areas tend to use physicians in metropolitan areas to a greater degree than metropolitan residents use non-metropolitan physicians. For example, about 46% of visits by non-metropolitan residents are made to metropolitan physicians, whereas only 12% of visits by metropolitan residents are made to non-metropolitan physicians (11). Using the fact that 70% of the population is metropolitan, one can show that patient loads per physician are much less unequal than population/physician ratios make them appear. One other misinterpretation of the unequal physician/population ratios is that high patient loads may deter physicians from locating in rural areas. For example, Cooper et al (3) speak of this as being the most "foreboding" element of rural practice. Their argument overlooks the options for the physician to (a) add allied health personnel or (b) not accept new patients. Contrary to this view, our theory suggests that higher patient loads are an attraction to physicians. A fact that is inconsistent with the presumption that large patient loads are a deterrent to rural location, but that is consistent with our theory, is that physician hours in non-metropolitan areas are on average only slightly greater than physician hours in metropolitan areas of less than one million (19). Travel to physicians in other counties, or border crossing, is another reason that data on the number of physicians in small rural counties is misleading (9). The issue is not how many counties do not have a physician but how far individuals living in such counties must travel to seek care. As the data in Table 6 demonstrate, travel times for such individuals may not be greater than the time many individuals in major metropolitan areas spend traveling for care. If the common interpretation of the inequalities in geographic access to physicians were correct, one ought to observe lower patient visit rates and longer queues in rural areas. Patient visit rates are somewhat lower, but the differential is not so large that it could not be plausibly explained by lower demand from some combination of differential insurance coverage and differ­ ential income. Waiting times for an appointment are not markedly longer in

226

NEWHOUSE

rural areas (12), a finding that is not consistent with a view that access for rural residents is poor because physicians in rural areas are swamped. Another common empirical misunderstaIlding is to attribute the "shortage" of physicians in rural areas to the low incomes of physicians in such areas. Such computations almost invariably fail to adjust physician incomes for the cost of living. Although it is difficult to make such an adjustment, one attempt to do so estimated that physicians in metropolitan areas of a million people or

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more earned less in real tenns than other physicians ( 19) because the higher nominal incomes of physicians in such areas did not compensate for the higher cost of living there. The estimated differences in real income, howev­ er, were small. (The theory would predict that in equilibrium, the income differences would solely reflect the marginal physician' s preferences for size of city.)

FUTURE RESEARCH The above discussion has not explicitly considered differentials in physician! popUlation ratios across states, although that has historically been a concern. The issue in the present context is the degree to which the existing differen­ tials between states with relatively low ratios, such as Mississippi and South Dakota, and states with relatively high ratios, such as Maryland and Massa­ chusetts, can be explained by the theory described above. The latter states have 2.5 to 3 times more physicians per person than the fonner. In explaining these differences, one would have to consider the degree to which medical schools and teaching hospitals bring in patients from outside the state (and consider the issue of border crossing more generally), as well as to net out of physician supply in the state the component that was attributable to training (both those being trained and time devoted to teaching). One would, of course, net out physicians not engaged in patient care, and net out of both the numerator and the denominator special populations with their own physicians, e . g . physicians in the military. Further, one would have to adjust for demand differences among the states (e.g. differential health insurance coverage, age, etc). According to the theory, remaining interstate differentials would pre­ sumptively be attributable to non-pecuniary differences (i.e. some states being more attractive to live in than others) . The issue from a theoretical point of view is whether the size of the remaining differences can plausibly be attributed to this; the issue from a policy point of view is whether the remaining differences ought to be modified because of possible damage to health, although there is little evidence that over the observed range of variation there is any link between the number of physicians in a state and the health of its residents (but for some evidence see Ref. 6).

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GEOGRAPHIC ACCESS TO PHYSICIANS

227

Finally, nothing has been said above about the distribution of physicians within metropolitan areas, in particular whether (a) those decisions regarding location can be explained by the theory described above and (b) intervention is appropriate to increase the number of physicians located in poverty areas. The appropriateness of the theory depends upon the importance of travel costs. Recall the example of the three cities on a highway; if demand did not fall with travel time, the first physician could locate in any city and face the same demand. If a physician can locate anywhere within the city and face the same demand, the theory will not predict location. If, however, travel time does matter and if demand is lower for the poor (perhaps because of less insurance and lower income), the theory would predict fewer physicians in poor areas. (In that case, to a physician making a location decision, a poor part of a metropolitan area is like a smaller town.) Thus, that fewer physicians locate in poverty areas is consistent with the theory. Intervention in this case would be more appropriate, the more that the paucity of physicians in the poor areas deters demand that society would like to encourage. Low demand, however, may be more a function of price or cultural factors than of location. If so, simply attracting more physicians to the poor area will not be a very effective instrument in raising demand. Interventions aimed at demand, such as greater insurance coverage, free or subsidized care at health centers, or community organization and education, need to be considered. LOCATION OF PHYSICIANS IN THE 1 990s What then can be said about the location of physicians in the 1990s? Based on the theory described above, the key factors influencing location are the total numbers of physicians and their distribution across specialties. The greater the growth in total numbers, the greater will be the diffusion of physicians. Moreover, the greater the growth in the number of primary care physicians, who are disproportionately located in small towns, the greater will be the growth of the physician stock in smaller towns. The American Medical Association's (AMA) projections for total numbers of physicians indicate growth, but at a substantially slower rate than in the immediate past. Between 1 970 and 1986 the number of active physicians grew at an average rate of 3.2% per year; between 1986 and 2000 the AMA projects a growth rate of 1 .6% per year (Ref. 1 5 , Tables 2 . 1 and 4.2). Thus, abstracting from any shifts of the population from small towns toward larger towns and abstracting from any shifts in specialty, the theory sketched above would predict continued diffusion, albeit not at such a rapid rate as was observed in the 1 970s and early 1980s.

228

NEWHOUSE

The future distribution of physicians by specialty is more difficult to predict than the total number. Implied in the theory of geographic location described above is also a theory of specialty distribution; if one relabels towns with varying total demand as specialties with varying total demand, and if one assumes that at least some physicians will trade off income against the non-pecuniary aspects of a specialty , one can show that in equilibrium, other issues being equal, specialties wiII grow in proportion to demand for their

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services . Because of technological change, however, demand for specialty services is probably much less stable over time than demand at a given location (think of nephrology before and after renal dialysis, or cardiac surgery before and after the development of bypass grafting). Morever, non-pecuniary aspects of a specialty may also be less stable than non-pecuniary aspects of a location (will the greater age and severity of illness among hospitalized patients make internal medicine less attractive relative to other specialties?). Because of these instabilities , the distribution of physicians by specialty may well show larger departures from an equilibrium at any one point in time than the distribution of physicians by geographic location. Marder et al (15) also project the distribution of specialists by the year 2000 ; their projections show that percentage growth will differ by specialty,

but all specialties will grow in absolute terms . The number of general and family practitioners is projected to rise by 9% from 1986 to 2000 , and the number of general internists and general pediatricians is projected to rise by

29 and 35%, respectively. These projections , however, assume that the pattern of specialty choice observed between 1978 and 1986 for the cohort of male and female physicians who entered residency in 1978 will simply repeat itself. The theory outlined above supports such an assumption only under con­ ditions that are not likely to be satisfied: (a) that the choices made by the 1978 cohort represent equilibrium choices; (b) that relative demand growth by specialty in the 1986-2000 period will be similar to that in the 197&-1986 period; and (c) that non-pecuniary characteristics remain relatively the same. Even if these assumptions are not satisfied, however, it is hard to know whether there is any systematic bias in the resulting projections. The effect of one factor seems clear, however; if relative fees of cognitively oriented specialties are raised relative to those of procedure-oriented specialties, as recommended by the Physician Payment Review Commission (22), it seems likely that such specialties will grow more rapidly than the above projections . This should augment the number o f physicians i n small towns. Thus, in view of the projected continued growth in the number of physi­ cians and the likelihood that each specialty will continue to grow, it seems likely that there will be continued diffusion of physicians into smaller towns.

GEOGRAPHIC ACCESS TO PHYSICIANS

229

Whether this is good or bad, however, is open to debate. Those who believe that rural areas are now shortchanged will no doubt welcome such a develop­ ment, but there is good evidence that concentration or regionalization of procedures leads to better outcomes (13, 14). A more concrete way to state the issue is to ask whether a neurosurgeon practicing in a town of 30,000 really has enough business to maintain his or her skills. Some might argue that although procedure-oriented specialists should be

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concentrated in larger cities (or perhaps that physicians in procedure-oriented specialties have diffused far enough) , the same arguments do not apply to primary care physicians (or that such physicians have not diffused far enough) . Such persons might consider at what size town a nurse practitioner or a physician assistant might be preferred to

a

primary care physician for the

delivery of services. Unfortunately, the answer to that question remains conjectural; it, too, must remain a topic for future research.

Literature Cited la. Baumgardner, J . R. 1 988. Physicians' services and the division of labor across local markets. J. Polito £Con. 96:94882 lb. Budetti, P. B. 1984. The trickle-down theory-Is that any way to make policy? Am. J. Public Health 74:1303-4 2. Budetti, P. B . , Kletke, P. R . , Connelly, J. P. 1 982. Current distribution and trends in the location pattern of pediatri­ cians, family practitioners, and general practitioners between 1976 and 1979. Pediatrics 70:780-89 3. Cooper, 1 . K . , Heald, K . , Samuels, M. 1 972. The decision for rural practice. J. Med. Ed. 47:939--44 4. Dionne, G . , Langlois, A . , Lemire, N. 1987. More on the geographical dis­ tribution of physicians. J. Health Econ. 6:365-74 5. Fruen, M. A . , Cantwell, J. R. 1982. Geographic distribution of physicians: Past trends and future influences. Jn­ quiry 1 9:44-50 6. Hadley, J. 1982. More Medical Care, Better Health? Washington, DC: Urban lnst. Press 7. Hemenway, D. 1982. The optimal loca­ tion of doctors. N. Engl. J. Med. 306:397-401 8 , Hicks, L. L. 1984. Social policy im­ plications of physician shonage areas in Missouri. Am. J. Public Health 74: 1 3 16-21 9. Kindig, D . A., Movassaghi, H. 1989. Physician supply in small rural counties. Health Affairs 8:(2)63--76

10. Kleinman, J. C. 1 983. Evaluating the definition of physician shonage areas. Health Servo Res. 1 8:280-83 1 1. Kleinman, J. C . , Makuc, D. 1 982. Travel for ambulatory medical care. Med. Care, Vol. 20 1 2. Kleinman, J. C . , Wilson, R. 1977. Are 'Medically underserved areas' medically underserved? Health Servo Res. 1 2 : 1 4762 1 3. Luft, H. S., Bunker, J., Enthoven, A. 1979. Should operations be regional­ ized? An empirical study of the relation between surgical volume and mortality. N. Engl. J. Med. 30 1 : 1364-69 1 4 . Luft, H . S . , Hunt, S. S . , Maerki, S. G. 1987. The volume-outcome relationship: Practice-makes-perfect or selective­ referral patterns. In Health Servo Res. 22: 157-82 1 5 . Marder, W. D . , Kletke, P. R . , Silber­ ger, A. B . , Wiltke, R. J. 1 988. Physi­

cian Supply and Utilization by Specialty: Trends and Projections. Chicago: Am.

Med. Assoc.

16. Moscovice. I. 1 983. Policy approaches

for improving the distribution of physi­ cians. Health Servo Res. 18(2) :270-74 17. Newhouse, J. P., Williams, A. P., Ben­ nett, B . W . , Schwartz, W. B . 1982. Does the geographical distribution of physicians reflect market failure? Bell J. Econ. 1 3:493--506 18. Newhouse, J. P., Williams, A. P., Ben­ nett, B. W . , Schwartz, W. B. 1 982. Where have all the doctors gone? J. Am. Med. Assoc. 247:2392-96

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19 . Newhouse, J. P . , Williams, A. P. , Bennett, B. W . , Schwartz, W. B. 1 982 . The geographic distribution of

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