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For-Profit Enterprise in Health Care. 1986. National Academy Press, Washington, D.C. Medical Staff Size, Hospital Pn~rileges, and Compensation Arrangements: A Companson of System Hospitals Michael A. Momsey, Jeffrey A. Alexander, and Stephen M. Shortell INTRODUCTION Since 1975, multihospital systems have grown at a 3 to 4 percent annual rate (Ermann and Gabel, 1984~. ~M any observers see fi~ndamen- tal changes in the practice of medicine as a result of this trend (Starr, 1982), particularly in regard to the investor-ownecl (IO) systems (Relman, 19801. Among the concerns are (1) potential conflict of interest between the profit motive and patient needs, (2) the ability of investor-owned system hospitals to deliver care in terms of the number and types of physicians that affiliate with such hospitals, (3) the degree to which IO system hospitals review pnvi- leges, and (4) the nature of the financial re- lationships between physicians and IO system hospitals. The first issue is beyond the range of this paper. The remaining three are addressed in descriptive fashion by comparing IO system hospitals with freestanding hospitals and hos- pitals in other types of systems. The analysis uses available data from the American Hospital Association (AHA). The following section de- scubes the three data sets used. This is fol- lowed by findings pertaining to Me number and types of physicians, privilege criteria and review, and compensation arrangements. A concluding section discusses the implications Dr. Morrisey is in the Department of Health Care Organization and Policy and Dr. Alexander is in the Department of Health Services Administration, both at the University of Alabama at Birmingham. When this paper was written they were with the Hospital Research and Educational Trust, Chicago, Illinois. Dr. Shortell is with the J. L. Kellogg Graduate School of Management and Center for Health Services and Pol- icy Research at Northwestern University, Evanston, Illinois. of the findings and makes suggestions for fur- ther study. DATA AND METHODS Most of the medical staff data are drawn from the 1982 AHA Survey of Medical Staff Organization. This survey was mailed to 3,027 nonfederal, short-term, acute care hospitals in the 48 contiguous states and the District of Columbia. Because the survey was designed to test the effects of regulation, the sample hospitals were chosen by a 25 percent random design augmented with additional hospitals in 22 states. These states were primarily those with mandatory or voluntary rate-setting pro- grams. The survey had an overall response rate of 69.9 percent. Due to the sampling design, the sample is not wholly representative of na- tional data. The respondents are larger, more likely to be from the Northeast, Middle At- lantic, and West North Central regions, more likely to have a teaching program, and less likely to be IO hospitals (Shortell et al., 1985~. Data on the size, specialty composition, and physicians on the hospital payroll as well as all control variables were taken from the 1982 AHA Annual Survey of Hospitals. This uni- verse survey had an overall response rate of 89.9 percent. The data on hospital system participation are drawn from the 1982 AHA Validation Sur- vey of Multihospital Systems. That survey col- lected information on the hospitals participating in the system, the date they joined, and the type of participation (i.e., owned, leased, sponsored, or contract-managed). To our knowledge, this is the most complete file of multihospital system hospitals in existence. For purposes of this analysis, when two or more hospitals are owned, leased, or spon- sored by another entity, they are categorized 422
STAFF SIZE, PRIVILEGES, AND COMPENSATION as being part of a system. System hospitals are then subdivided by ownership: religious, sec- ular nonprofit, public (i.e., owned by a state or local government), and IO. Contract-man- aged hospitals are given a unique category as are freestanding hospitals. Federal hospitals have been excluded. This yields six mutually exclusive and exhaustive categories. Two analyses are conducted for each vari- able of interest. First, simple comparisons across the six cells are presented. Statistical tests are performed comparing IO system hospitals with hospitals in each of the other cells. When the variables are continuous, l-tests of means are calculated; when the data are dichotomous, chi-squared tests are used. Second, regression techniques are used to test for the same differences controlling for system, hospital, region, and urban location variables. Specifically, the equation controls for · System size (the number of hospitals in the system); · Staffed beds (the average number of beds set up and staffed over the course of the year); · Teaching status (number of interns and residents on the hospital payroll); · Northeast region (Connecticut, Maine, Massachusetts, New Hampshire, New Jersey, New York, Pennsylvania, Rhode Island, Ver- mont); · South region (Alabama, Arkansas, Dis- trictofColumbia, Delaware, Florida, Georgia, Kentucky, Louisiana, Maryland, Mississippi, 423 North Carolina, Oklahoma, South Carolina, Tennessee, Texas, Virginia, West Virginia); · North Central region (Illinois, Indiana, Iowa, Kansas, Michigan, Montana, Missouri, Nebraska, North Dakota, Ohio, South Dakota, Wisconsin); and ~ Standard metropolitan statistical area (SMSA) size (under 100,000, 100,000-250,000, 250,000-500,000, 500,000-1 million, 1 million- 25 million, over 25 million). For exploratory purposes these equations are estimated twice, once to allow comparisons of all system types to freestanding hospitals and once again to allow direct comparisons with IO system hospitals. Equations empha- sizing continuous dependent variables are es- timated using ordinary least squares regression techniques; dichotomous dependent variables are analyzed using logit regression. Means and standard deviations of all vari- ables are found in Appendix Tables A-1, A-2, A-3, and Am. Because different sample sizes are available for different variables, four sets of summary statistics are reported. NUMBER AND TYPES OF PHYSIC~S Table 1 presents data on the number of ap- plications for medical staff membership re- ceived in 1981. The average IO system hospital received 16 applications. This is comparable to freestanding and voluntary system hospi- tals. However, publicly owned system hospi- tals received twice that number of applications; TABLE 1 Compulsion of Investor-O~ed System Hospitals with Other Ties of Hospitals: How Many Physicians Applied for Active Stab Pnvileges During Calendar Year 1981? Investor Owned Religious Nonprofit Public Contract Systems Freestanding Systems Systems Systems Managed Mean Mean Mean Mean Mean Mean N(S.D.) N (S.D.) N(S.D.) N(S.D.) N (S.D.) N(S.D.) . - 11716. 11 1,283 13.48 22319.22 5927.25 6 33.50** 1237.48*** (18.02) (20.71) (24.64) (51.62) (26.82) (10.90) ***I significant at p c .01 when compared to hospitals in investor-owned systems. **T significant at p s .05 when compared to hospitals in investor-owned systems.
424 contract-managed hospitals only received 7.5 applications, on average. These differences are related to differences in hospital size, location, and teaching status. When these factors are taken into account (Ap- pendix Table A-5), it is only the secular non- profit system hospitals that differ significantly from IO system hospitals. They receive on av- erage 5.2 more applications annually than do IOs. Table 2 shows that IO system hospitals ac- cept a higher percentage of applicants (89. 76 percent) than does any other hospital group. Appendix Table A-6 demonstrates that, con- trolling for other factors, this difference is even more pronounced. Nonprofit secular system hospitals approve 12 percent fewer applica- tions, religious systems 8.9 percent fewer, and freestanding and contract-managed hospitals approve over 11 percent fewer applications than do IO system hospitals. While IO system hospitals received and ac- cepted more medical staffapplications in 1981, these hospitals, nonetheless, had smaller med- ical staffs than did other system hospitals (Ta- ble 3A). However, the average of 91 physicians in IO system hospitals is comparable to free- standing hospitals and almost twice as large as contract-managed hospitals. This result is largely attributable to differences in hospital size across system control. Table 3B reports the number of physicians per 100 beds. When measured on this basis, IO system hospitals have over 61 physicians per 100 beds. This is larger than contract-managed, freestanding, and most system hospitals. Only voluntary sec FOR-PROFIT ENTERPRISE IN HEALTH CARE ular system hospitals have more active and associate medical staff members per 100 hos- pital beds. As Appendix Table A-7 reports, however, while the relationship across hospital types continues to hold when other factors are introduced, it is only the public system, free- standing, and contract-managed hospitals that exhibit statistically significant differences from IO system hospitals. The specialty composition of the staff was also examined, focusing on family practice, pe- diatrics, general internal medicine, other medical specialties, and general surgery. The simple comparisons are reported in Table 4. In general the IO system hospitals have as many or more physicians per 100 beds as hos- pitals in other categories. The principal ex- cephon is in pediatrics where voluntary secular system hospitals have more physicians. These findings hold when other factors are entered into the equations (Appendix Tables A-8, A- 9, A-10, A-11, and A-121. Interestingly, the larger IO medical stabs appear to anse, in part, Dom larger numbers of internists and other medical specialists. Table 5 reports the dependence of hospitals on the top five admitters to the hospital. All differences are statistically significant. Con- tract-managed hospitals derived over 63 per- cent of their a~nissions from five physicians or physician groups; public system hospitals only 12 percent. IO system hospitals fall in the lower end of We range with approximately 40 percent of their admissions provided through the top five admitters. When hospital size and other factors are controlled (Appendix Table TABLE 2 Comparison of Investor-Owned System Hospitals with Other Types of Hospitals: What Percentage of the Physicians Who Applied for Active StaR Privileges During Calendar Year 1981 Were Accepted? Investor Owned Systems Freestanding Religious Nonprofit Systems Systems Public Contract Systems Managed Mean Mean Mean Mean Mean Mean N(S.D.) ~(S.D.) N(S.D.) N(S.D.) N (S D) N (S.D.) 11789.76 19283 81.39*** 22386.75 5981.45 6 72.93 123 76.~*** (23.39) (34.99) (29. 1 ~(35.57) (39.62) (39.85) ***T significant at p s .01 when compared to hospitals in investor-owned systems.
STAFF SIZE, PRIVILEGES, AND COMPENSATION 425 TABLE 3A Comparison of Investor-Owned System Hospitals with Other Types of Hospitals: How Many Practitioners (Total) Were on the Active or Associate Medical Staff as of September 30, 1982? Investor Owned Religious Nonprofit Public Cont~act SystemsFreestanding Systems Systems Systems Managed MeanMean Mean Mean Mean Mean N (S.D. ) N (S.D.) N (S.D.) N (S.D.) N (S.~.) N (S.D.) 395 91.03 3,453 90.32 538 144.07*** 232 (93.89) (140.32) (120.21) 169.47*** 31 (300.17) 286.65** 355 (449.59) 46.73*** (78.41) ***T significant at p s .01 when compared with hospitals in investor-owned systems. **T significant at p ' .05 when compared with hospitals in investor-owned systems. A-13), IO system hospitals have a lower con- centration of admissions than do voluntary sec- ular system hospitals and contract-mana~ed facilities. Finally, Table 6 reports the percentage of the top five admitting physicians who are board certified. With the exception of contract-man- aged hospitals, which had a smaller percentage of board-certified heavy admitters, there was no statistically significant difference between hospitals in IO chains and other types of hos- pitals. This finding is born out by the multi- variate analysis in Appendix Table A-14. PRIVILEGES CRITERLt AND REVIEW Although IO sytem hospitals accept more applications (see Table 2), there is no statis- tically significant difference in the proportion of these hospitals Hat require at least some specialties to be board certified (Table 7~. This result holds when other factors are included in the regression as well (Appendix Table A- 15~. Recently reported AHA data indicate that proprietary hospitals (not just IO system hos- pitals) have a somewhat higher number of board- certified staff members than do nonprofit hos- pitals (28.8 per 100 beds versus 24.6 per 100 beds) (Amencan Medical Association, 19841. This finding is consistent with earlier AHA data. When earlier data are controlled for over factors, however, the difference loses statis- bcal significance (Morrisey, 1984~. Table 8 re- ports the proportion of active and associate medical staff members who were board cer- hfied in 1982. Sixty-one percent ofthe medical stab members of hospitals in IO chains were board certified. This percentage is not statis- dcally different from hospitals in most other ownership control categories. Hospitals in re- ligious systems had ahi~er proportion of board TABLE 3B Comparison of Investor-Owned System lIospitals with Other Types of Hospitals: How Many Practitioners (Total) Were on the Active or Associate Medical Staff per 100 Staffed Beds as of September 30. 1982? Investor Owned Systems Freestanding Religious Systems Nonprofit Public Contract Systems Systems Managed Mean Mean Mean Mean Mean Mean N(S.D.) N (S.D.) N (S. D ) N(S.D.) N (S. D.) N (S.D.) 39561.39 3~453 43.67*** 538 52.24*** 23266.03 31 61.61 355 36.97*** (55.57) (44.07) (36.79) (73.14) (51.98) (39.49) ***T significant at p ' .01 when compared to hospitals in investor-owned systems.
426 - V2 - o ._ ._ C) ¢ :^ Cat. Ct Go of 3 o^ L. .. Cal Cal ~ - ._ Cal o ~ I 1 JO o ~ ,~ ^ C; U) US U) C.) Ct ._ Hi, o ~ ~ o V7 ~ ~ . Can ~ ;,, `_ ~ 3 ~ O _ ¢ . :> ~ o ~ C) ' ~ ¢ Cal - o o C) ~ ~ o ~3 C5 _, ~ o ~ C) ~ _ C) - ~ Cal C it, sol _ * * * * * * c~ ~ ~ CD 0 ~ ~ O OC ~ O- 1~= =- -~= ^ Q _ CD CC CO C~ CD C~ C~ C~ C~ C~ C~ C~ ~ C~ C~ * o o _ i= C~ _ C~ _ ~ oo (D ~ ~ O O - ~ 00 CO C~ ~, C~ ~ 0 C~ ~ ~ U: C~ _ _ ~_ C~ * ~L 7v ^ ~ CO *= ~ CD ^ 0 ct ~ 0 ao a~ ~ u C) ~ o 0 ~ o ~ C~ C~ _ _ z -^ C) ~ _ _ C ~ C~ 0 CD 0 _ _ _ oo oo C ~ ~o C ~ * * * * oo oo ~ ~ oo ~ _ ~ _ C~ ~ ~ CC ~ ~ C~ .. . . . . . . . . ~ % ~ ~, ~ CO ~ ~ U' - V' o ~ ._ _ ,= ~ ~ Z _ _ ~ _ ~ * * * * * * * * _^ C~ C~ _ CD CO _ C*~ _ * C~ Ct Q ~ c~ ~ co o o ~ c~ oo s: ~ . ~ oo C~ ~ ~ ~' CO ~ CO ._ _ C~ ~U) ~ ~ U, U) ~Z~ ~ ~ . ^ ~ ~ C~ C~ ~ ~ ~ co Ct ~ ~ 0 ~ ~ ~ ~ ~ _ o=~ ~' o-~_~= ~ O ~CD - C: ._ C) V, . . ~ V) ~ £ C) ~ V: ~ :` ~ V] ~ ~:5 ~ Q) ~ _ 3 3 o o o o ~, . C~: V) ._._ _ ._._ _ _ ~ et ~ _ ._ ._ S U, C~ o o ~ _ `_ ~ ~ _ _ ._ 3 3 5~ C¢ e~ S £ ~ o o C) C) ~ _ _ 3 3 _ U) o o . . Vl ~ _ C) .~, e~ _ =_~5 ~ ~ ~ C: ~O C: Ct Ct s" C, C ._ ._ C~ E~ * * * ~: C~ C=: ._ .= U) C~ * *
STAFF SIZE, PRIVILEGES, AND COMPENSATION TABLE 5 Comparison of Investor-Owned System Hospitals with Other Types of Hospitals: What Percentage of Total Admissions During Calendar Year 1981 Were Admitted by the Five Highest Admitting Physicians? Investor Owned Religious Systems Freestanding Systems 427 Mean Mean Mean N (S.D.) N (S.D.) N (S.D.) N Nonprofit Public Contract Systems Systems Managed Mean (S.D.) N Mean (S.D.) N Mean (S.D.) 117 40.54 1,283 46.57** 223 32.65** 59 50.38* 6 12.38*** 123 63.56*** (27.47) (33.54) (28.61) (35.54) (2.22) (31.81) ***I significant at p ' .01 when compared with hospitals in investor-owned systems. **T significant at p c .05 when compared with hospitals in investor-owned systems. *T significant at p c .10 when compared with hospitals in investor-owned systems. TABLE 6 Comparison of Investor-Owned System Hospitals with Other Types of Hospitals: What Percentage of Top Five Admitting Physicians Are Board Certified? Investor Owned Religious Nonprofit Public Contract Systems Freestanding Systems Systems Systems Managed Mean Mean Mean Mean Mean Mean N(S.D.) N(S.D.) N(S.D.) N(S.D.) N (S.D.) N (S.D.) 11762.79 1,23660.98 22165.29 5760.61 6 65.00 121 52.66** (35.34) (36.40) (33.44) (37.30) (28.11) (36.97) **T significant at p c .05 when compared with hospitals in investor-owned systems. ce~ied medical staff members, but this dif- ference loses statistical significance in the mul- tivanate analysis (Appendix Table A-161. Further, IO system hospitals have longer probationary periods for new medical staff members than do either freestanding or con- tract-managed hospitals (Table 91. System hos pitals, across Me board, are similar in this respect. These differences disappear, how- ever, when other factors are considered (Table A-17). The differences appear to be largely attributable to hospital and community size. While no data are available from AHA sur- veys pertaining to utilization review and qual TABLE 7 Comparison of Investor-Owned System Hospitals with Other Types of Hospitals: Is Board Certification Required for Any (or Ad) Specialties on Your Hospital's Active Stat Investor Owned Systems Religious Freestanding Systems Nonprofit Public Contract Systems Systems Managed N % N % N % N %N % N % l Yes 35 29.91 396 30.87 54 24.22 20 33.902 33.33 29 23.58 No 82 70.09 887 69.13 169 75.78 39 66.104 66.67 94 76.42 Total 117 100.00 1,283 100.00 223 100.00 59 100.00 6 100.00 123 100.00
428 FOR-PROFIT ENTERPRISE IN HEALTH CARE TABLE 8 Comparison of Investor-Owned System Hospitals with Other Types of Hospitals: What Proportion of Active and Associate Medical Staff in the Hospital Are Board Certified? Investor Owned Systems Freestanding Mean N (S.D.) 348 0.61 (0.22) N 3,062 Mean (S.D.) 0.61 (0.35) Religious Nonprofit Systems Systems N Mean (S.D.) N 500 0.65*** (0.26) 204 Mean (S.D.) N 0.65 (0.41) Public Systems 30 0.58 (0.24) ***T significant at p s .01 when compared with hospitals in investor-owned systems. ity assurance activities of different types of hospitals, some descriptive data are available from a recent AMA survey (1984~. They report that a somewhat higher percentage of pro- prietary (not just IO system) hospitals formally review clinical decisions than do nonproprie- taryhospitals (83 percent versus 79.8 percent). A somewhat lower percentage of proprietary hospitals set guidelines to reduce length of stay (65.9 percent versus 71.8 percent); review length of stay after discharge (84.9 percent ver- sus 90.1 percent); attempt to reduce the num- ber of treatment procedures that physicians prescribe (26.7 percent versus 32.2 percent); and review the range of services that the hos- pital provides (6.7 percent versus 9.5 percent). COMPENSATION ARRANGEMENTS Table 10, based on AHA annual survey data, compares the number of full-time and part Contract Managed Mean N (S.D.) 304 0.58 (0.25) time physicians and dentists employed by the hospital in a clinical capacity. On average, public system hospitals employ over 80 physicians. Freestanding hospitals employ approximately seven physicians. All private voluntary system hospitals employ similar numbers. However, IO system hospitals employ less than one phy- sician, on average. With the exception of the public system hospitals, none of these differ- ences remain when one controls for hospital size, teaching commitment, and location (Ap- pendix Table A-181. That is, except for public system hospitals, hospitals are quite similar in their employment of physicians. Hospital-based physicians have historically had the greatest direct financial affiliation win hospitals. These affiliations involve employ- ment, form of compensation, and billing ar- ran~ements. Tables 11 and 12 report the available data from the AHA Survey on Med- ical Staff Organization on the form of compen TABLE 9 Comparison of Investor-Owned System Hospitals with Other Types of Hospitals: What Is the Usual Number of Months for Provisional Appointment Before a Physician Is Awarded Full Privileges? Investor Owned Religious Nonprofit Public Contract Systems Freestanding Systems Systems Systems Managed - Mean Mean Mean Mean Mean Mean N (S.D.) N (S.D.) ~(S.D.) N (S.D.) N (S.D.) N (S.D.) . . 7 9.62 1,283 8.80* 223 10.41 so 9.44 6 11.00 123 7.85*** (I 54! ts.29) (4.98) <5.15) `2.45) t4.2s' ***T significant at p 5 .01 when compared with hospitals in investor-owned systems. *T significant at p 5 .10 when compared with hospitals in investor-owned systems.
STAFF SIZE, PRIVILEGES, AND COMPENSATION TABLE 10 Comparison of Investor-Owned System Hospitals with Other Types of Hospitals: How Many Full-Time and Part-Time Physicians and Dentists Were on the Hospital Payroll as of September 30, 1982? 429 Inv es to r Owned Religious Nonprofit Public Contract Systems Freestanding Systems Systems Systems Managed Mean Mean Mean Mean Mean Mean N (S.D.) N (S.D.) N (S.D.) N (S.D.) N (S.D.) N (S.D.) 395 0.28 3~453 6.91*** 538 5.87*** 232 7.77*** 31 80.48*** 355 1.03** (1.58) (30.67) (14.91) (22.94) (150.90) (5.25) ***I significant at p s .01 when compared with hospitals in investor~wned systems. **I significant at p s .05 when compared with hospitals in investor-owned systems. sation for anesthesiologists and radiologists. The results are similar 57 percent of public sys- tem hospitals compensate their physicians on a salary basis, and the remainder use an out- put-based arrangement such as a percentage of revenue, or the hospital or patient pays on a fee-for-service basis. Approximately 12 per- cent of freestanding and contract-managed hospitals use salary compensation. Secular nonprofit system hospitals are somewhat more likely and religious systems somewhat less likely to use salary arrangement than are freestand- ing hospitals. In marked contrast, IO system hospitals almost never use a salary form of compensation. These relationships are gen- erally supported in the multivariate compari- sons (Appendix Tables A-l9 and A-20. The form of compensation for pathologists is summarized in Table 13. Much larger pro- portions of hospitals of all types compensate these physicians with salary arrangements. It is still the case, however, that a smaller pro- portion of IO system hospitals use the salary form. The statistically significant differences with IO system hospitals are maintained only for religious and public system hospitals once over factors are considered (Appendix Table A-211. Finally, Tables 14, 15, and 16 report the degree to which the hospital bills for physician services as one moves from anesthesiology to radiology to pathology. As with other mea- sures of financial involvement with physicians, IO system hospitals are least likely to bill pa- tients for physician services. In this regard Hey are most like religious system hospitals and least like freestanding hospitals anal public sys- tem hospitals. These differences persist when other factors are controlled (Appendix Tables A-22, A-23, and A-24. . . . TABLE 11 Comparison of Investor-Owned System Hospitals with Other Types of Hospitals: What Is the Primary Form of Compensation for Anesthesiologists?a Investor Owned Religious Nonprofit Public Contract Systems Freestanding Systems Systems Systems Managed N % N % N % N % N To N % Yes 78 98.73 785 88.40*** 143 94.70 33 82.50*** 3 42.86*** 61 88.41** No 1 1.27 103 11.60*** 8 5.30 7 17.50*** 4 57.14*** 8 11.59** Total 79 100.00 888 100.00 151 100.00 40 100.00 7 100.00 69 100.00 ayes = percent of revenue or fee-for-service; no = straight salary; "other" types not included. ***Chi-square significant at p ' .01 when compared with hospitals in investor-owned systems. **Chi-square significant at p c .05 when compared with hospitals in investor-owned systems.
430 FOR-PROFIT ENTERPRISE IN HEALTH CARE: TABLE 12 Comparison of Investor-Owned System Hospitals with Other Types of Hospitals: What Is the Primary Form of Compensation for Radiologists?a Investor Owned Religious Nonprofit Public Contract Systems Freestanding Systems Systems Systems Managed N % N %N % N % N % N Yes 77 97.47 782 88.06**146 96.69 34 85.00** 3 42.86*** 66 No 2 2.53 106 11.94**5 3.31 6 15.00** 4 57.14*** 3 Total 79 100.00 888 100.00151 100.00 40 100.00 7 100.00 69 151 100.00 40 100.00 ayes = percent of revenue or fee-for-service; no = straight salary; "other" types not included. ***Ch~-square significant at p s .01 when compared with hospitals in investor-owIled systems. **Ch~-square significant at p c .05 when compared with hospitals in investor-owned systems. DISCUSSION After controlling for system size, hospital size, teaching activity, region of the country, and SMSA size, IO system hospitals tend to differ from other times of ha~r~ital~ in the fill lowing ways: , ~_ ~ ~ ., 1. They accept a somewhat higher per- centage of medical staffapplications than other types of hospitals. 2. They take essentially the same time to review physician performance before award- ing field privileges as do other hospitals. 3. They have a larger number of physicians per bed. 4. They have a larger number of internists and other medical specialists than other hos- pitals, but fewer pediatricians than secular nonprofit hospitals. 5. They experience less concentration of ad % 95.65 4.35 100.00 missions than secular nonprofit hospital sys- tems and contract-managed hospitals, but are similar to other hospitals. 6. They are less likely to have salaried ar- rangements with anesthesiologists, patholo- gists, or radiologists. 7. They are more likely to have hospital- based specialists directly bill for services. On all other dimensions investigated, IOs are essentially similar to other types of hos- pitals, whether system owned or freestanding. Because the study is descriptive and ex- ploratory, no firm conclusions can be drawn. ~ reference to the original three issues (i.e., number and types of physicians, privilege cri- teria and review process, and compensation arrangements), the data do suggest the follow- ing observations and raise several questions for fixture investigation. TABLE 13 Comparison of Investor-Owned System Hospitals with Other Types of Hospitals: What Is the Primary Forrn of Compensation for Pathologists?a Investor Owned Systems N % Freestanding N % Religious Nonprofit Systems Systems N % Yes 67 84.81 56863.96*** 9965.56*** 27 No 12 15.19 32036.04*** 5234.44*** 13 Total 79 100.00 888100.00 151100.00 40 N % 67.50* 32.50* 100.00 Public Systems N % N 2 28.57*** 58 5 71.43*** 11 7 100.00 69 Contract- Managed 84.06 15.94 100.00 ayes = percent of revenue or fee-for-service; no = straight salary; "other" types not included. ***Chi-square significant at p ' .01 when compared with hospitals in investor-owned systems. *Chi-square significant at p ' .10 when compared with hospitals in investor-owned systems.
c STAFF SIZE, PRIVILEGES, AND COMPENSATION TABLE 14 Comparison of Investor-Owned System Hospitals with Other Types of Hospitals: Do Your Anesthesiologists Bill Patients Directly? Investor Owned Religious Nonprofit Public Contract Systems Freestanding Systems Systems Systems Managed N % N % N % N % N % N % Yes 89 85.58 805 69.52*** 170 No 15 14.42 353 30.48*** 32 Total 104 100.00 1,158 100.00 202 84.16 3768.52** 15.84 1731.48** 100.00 54100.00 550.00** 550.00** 10100.00 ***Chi-square significant at p c .01 when compared with hospitals in investor-owned systems. **Chi-square significant at p c .05 when compared with hospitals in investor-owned systems. Medical Staff Size and Composition The fact that IO system hospitals have a somewhat greater number of physicians per 100 bells and accept a higher percentage of applications to their staff suggests that they have at least as "adequate" a supply of medical staff resources as do other hospitals. If any- thing, IOs are expanding their medical staffs at a faster rate since the volume of applications to their staffs is comparable to other types of hospitals. It is not known whether the larger number of medical specialists per 100 beds is a matter of deliberate policy on the part of IO systems or more a reflection of the mix of phy- sicians available in the communities in which IO system hospitals have located. Among the questions for discussion and fu- ture exploration are the following: · Do the larger staffs give IO system hos- pitals greater or lesser flexibility to expand or contract their service mix relative to other hos- pitals? 437 54 45 99 · Does the greater percentage of applica- tions accepted suggest that IO system hospi- tals are "out-competing" other hospitals for the increasing supply of physicians? What are the implications for the type, volume, and quality of services that are offered to the community? · Does the clinical behavior of physicians differ between those primarily affiliated with IO system hospitals versus those primarily af- filiated with other types of hospitals? Diag- nosis-specific, physician-specific data are needed to address these issues. Privilege Criteria and Review This study indicates that at least as many IO system hospitals require board certification as a requirement of medical staff membership as do other hospitals. Combined with the other data indicating that IO system hospitals have a percentage of physicians who are board cer- tified similar to that of nonproprietary hospi- tals, this suggests that IOs exhibit as much TABLE IS Comparison of Investor-Owned System Hospitals with Other Types of Hospitals: Do Your Radiologists Bill Patients Directly? Investor Owned Religious Nonprofit Public Contract Systems Freestanding Systems Systems Systems Managed N % N % N % ~To N % ^N % To Yes 87 83.65 63054.40*** 155 No 17 16.35 52845.60*** 47 Total 104 100.00 1,158100.00 202 33 21 100.00 54 61. 11*** 5 38.89*** 5 100.00 10 50.00** 58 50.00** 41 100.00 99 58.59*** 41.41*** 100.00 ***Chi-square significant at p s .01 when compared with hospitals in investor-owned systems. **Chi-square significant at p s .05 when compared with hospitals in investor-owned systems.
432 FOR-PROFIT ENTERPRISE IN HEALTH CARE TABLE 16 Comparison of Investor-Owned System Hospitals with Other Types of Hospitals: Do Your Pathologists Bill Patients Directly? Investor Owned Systems Freestanding N % N % Religious Nonprofit Public Systems Systems Systems N % N % N % Cont~act- Managed N % Yes 56 53.85 20017.27*** 5125.25*** 1527.78*** 110.00** 2828.28*** No 48 46.15 95882.73*** 15174.75*** 3972.22*** 990.00** 7171.72*** Total 104 100.00 1,158100.00 202100.00 54100.00 10100.00 99100.00 ***Chi-square significant at p ' .01 when compared with hospitals in investor-owned systems. **Chi-square significant at p c .o5 when compared with hospitals in investormwned systems. concern for attracting competent physicians as do other hospitals. This is further supported by the fact that IO system hospitals generally have as long a probationary period before granting full privileges as do other hospitals. Among the questions for discussion and fu- ture examination are the following: · Beyond meeting the basic structure and process accreditation standards of the loins Commission on Accreditation of Hospitals, it would be useful to know what additional qual- ity assurance mechanisms are used by differ- ent types of hospitals. · Given competitive and cost-containment pressures, it would be useful to know the de- gree to which cost-effective physician perfor- mance will be used as a criterion for granting and renewing clinical privileges, and the ex- tent to which this may differ across types of hospital ownership. · Carefully designed outcome studies that control for differences in case mix and other relevant variables are also needed to identify the degree to which there may be differences in the quality of care provided by different types of hospitals. Compensation Arrangements The fact that IO hospitals are less likely to have salaried relationships with their hospital- based specialists and more likely to have their physicians bill directly for their services sug- gests looser financial relationships between IO hospitals and these specialists. This may result from a philosophy of promoting physician au tonomy and, under cost-based reimburse- ment, may also have been viewed as financially advantageous. Among the questions for discussion and fu- ture exploration are the following ~ The looser financial relationships may be the result of the regulatory environments in which IO system hospitals have located to date. It would be useful to know whether the new SIedicare prospective payment system has changed these relationships. · Does the new payment system, the in- creased number of physicians, and the appar- ent emergence of price competition suggest that new compensation arrangements are being developed between hospitals and physicians? If so, are arrangements likely to diEer by hos- pital ownership. What implications do they have for the cost, volume, and quality of the service provided? The relationships between hospitals and physicians are complex and rapidly changing as a result of changes in the environment. This exploratory study has documented some ofthe differences in relationships, but, in the end, has posed many more questions for fixture work. ACKNOWLEDGMENTS This paper was funded, in part, by contract 0557~176 from the Institute of Medicine, Na- honal Academy of Sciences, to the Hospital Research and Educational Trust. The opinions and conclusions expressed herein are solely those of the authors. The authors thank Robert
STAFF SIZE, PRIVILEGES, AND COMPENSATION Anderson and Bonnie Lewis for excellent re- search assistance and advice. REFERENCES American Medical Association (1984) SMS Report 3~4). Ermann, D., and I. Gabel (1984) Multihospital sys- tems: Issues and empirical findings. Health Affairs 341):50-64. Morrisey, M. A. (1984) The composition of hospital 433 medical stabs. Health Care Management Review 9~3~:11- 20. Relman, A. S. (1980) The new medical-industrial complex. The New EnglandJourn~il of Medicine 303:963 970. Shortell, S. M., M. A. Morrisey, and D. A. Conrad (1985) Economic regulation and hospital behavior: The ellects on medical stab organization and hospital-phy- sician relationships. Health Services Research 20~5):597- 628. Starr, P. (1982) The Social Transformation of Amer- ican Medicine. New York: Basic Books.
APPENDIX Sample Characteristics and Multivar~ate Results TABLE A-1 Descriptive Statistics for Hospitals in the Analysis of Practitioner and Medical Stag Size and Composition (N = 5,004) Variables Standard Mean Deviation Sum Independent Variables Freestanding hospital0.690.463,453 System characteristics System control Religious nonprofit0.110.31538 Secular nonprofit0.050.21232 Investor-owned0.080.27395 Public0.010.0831 Contract-managed0.070.26355 System size24.0977.20120,553 Hospital characteristics Number of beds181.80177.40909,724 Regional location Northeast0.150.36766 South0.360.481,800 North Central0.310.461,531 West0.170.38872 SMSA sizea Non-SMSA0.470.502,348 Under 100,0000.010.1055 100,000-250,0000.090.28429 250,000-500,0000.090.28431 500,000-1 million0.090.28426 1 million-2.5 million0.130.33638 Over 2.5 million0.140.34677 House staff10.5345.5452,709 Dependent Variables Full-time and part-time active M.D.s and D.D.s on payroll Number6.3529.5831,779 Number per 100 staffed beds2.227.9911,123 Total active and associate medical staff Number97.95150.18490,131 Number per 100 staged beds46.6646.41233,504 By specialty group (N = 4,935)b General and family practice8.978.1144,258 Pediatrics2.937.3114,482 General internal medicine5.518.6327,182 Other medical specialty4.207.8520,713 General surgery4.074.8220,074 Proportion of active and associate medical staff that is board certified0.610.332,724 aSize of standard metropolitan statistical area (SMSA). bOf the 5,004 community hospitals, 69 were missing one or more responses on number of medical staff by specialty. 434
STAFF SIZE, PRIVILEGES, AND COMPENSATION TABLE A-2 Descriptive Statistics for Hospitals in the Analysis of Privilege Awarding and of Concentration of Admissions (N= 1,811) Variables Standard Mean Deviation Sum Independent Variables Freestanding hospital0.710.451,283 System characteristics System control Religious nonprofit0.120.33223 Secular nonprofit0.030.1859 Investor-owned0.060.25117 Public0.000.066 Contract-managed0.070.25123 System size21.1572.3638,295 Hospital characteristics Number of beds192.87171.98349,295 Regional location Northeast0.230.42422 South0.260.44470 Norm Central0.320.47573 West0.190.39346 SMSA sizea Non-SMSA0.440.50791 Under 10O,0000.020.1228 100,000-250,0000.090.29166 250,000 500,0000.090.28160 500,000 1 million0.080.28150 1 million-2.5 million0.150.35264 Over 2.5 million0.140.35252 House staff9.7942.3517,728 Dependent; Variables Number who applied for active stay privileges14.4722.5426,198 Percent who were accepted82.2334.17148,913 Usual number of months of provisional appointment9.015.1616,324 Board certification is required0.300.46536 Percent of admissions by top five admitting physicians45.6333.2282,641 Percent of top five admitting physicians who are board certified61.0736.07107,363 aSize of standard metropolitan statistical area (SMSA). 435
436 FOR-PROFIT ENTERPRISE IN HEALTH CARE TABLE A-3 Descriptive Statistics for Hospitals in the Analysis of Physicians' Primary Form of Compensation (N = 1,234) Variables independent Variables . Standard Mean Deviation Sum Freestanding hospital0.720.45888 System characteristics System control Religious nonprofit0 120.33151 Secular nonprofit0.030.1840 Investor-owned0.060.2479 Public0.010.087 Contract-managed0.060.2369 System size20.7672.0325,612 Hospital characteristics Number of beds218.62190.62269,779 Regional location Northeast0.260.44316 South0.260.44320 North Central0.290.46364 West0.190.39234 SMSA sizes Non-SMSA0.360.48940 Under 100,0000.020.1322 100,000-250,0000.100.30127 250,000-500,0000.100.30123 500,000 1 million0.090.29114 1 million-2.5 million0.170.37204 Over 2.5 million0.170.37204 House staff14.5053.8317,892 Dependent Variables Anesthesiologists are paid a percent of revenues or a fee for service0.890.311,103 Pathologists are paid a percent of revenues or a fee for service0.670.47821 Radiologists are paid a percent of revenues or a fee for service0.900.301,108 aSize of standard metropolitan statistical area (SMSA).
STAFF SIZE, PRIVILEGES, AND COMPENSATION TABLE AL Descriptive Statistics for Hospitals in the Analysis of Physicians' Direct Patient Billing Decisions (N = 1,627) Variables Standard Mean Deviation Sum Freestanding hospital System characteristics System control Religious nonprofit Secular nonprofit Investor-owned Public Contract-managed System size Hospital characteristics Number of beds Regional location Northeast South North Central West Independent Variables 0.71 0.12 0.03 0.06 0.01 0.06 20.21 0.45 1,lS8 0.33 0.18 0.24 0.08 0.24 70.53 212.37183.63 0.25 0.26 0.30 0.19 202 0.43 0.44 0.46 0.39 408 427 480 312 SMSA sizea Non-SMSA 0.37 0.48605 Under 100,000 0.02 0.1328 100,000-250,000 0.09 0.29154 250,000-500,000 0.10 0.30160 500,000-1 million 0.09 0.291S4 1 million-2.5 million 0.17 0.37273 Over 2.5 million 0.16 0.36253 House staff 13.55 53.3622,053 Dependent Variables Anesthesiologists bill patients directly 0.71 0.45 1,160 Pathologists bill patients directly 0.22 0.41 351 Radiologists bill patients directly 0.59 0.49 968 aSize of standard metropolitan statistical area (SMSA). 437
438 FOR-PROFIT ENTERPRISE IN HEALTH CARE TABLE A-S How M=y Physicians Apphed for Active Stem Proteges at Your Hospital During Calendar Year 1981? System Control Coefficients Relative to Freestanding Hospitals Investor-Owned Systems VariablesCoefficient Standard ErrorCoefficient Standard Error Freestanding hospitals - 3.43 2.16 System characteristics System control Religious nonprofit2.52 1.33*- 0.90 2.40 Secular nonprofit8.61 2.40***5.19 3.09* Investor-owned3.43 2.16 Public '-5.77 7.40-9.20 7.64 Contract-managed0.92 1.96-2.50 2.36 System size-0.01 0.01- 0.01 0.01 Hospital characteristics Number ' of beds4.37 0.34***4.37 0.34*** Regional location Northeast-5.13 1.38***- 5.13 1.38*** South-2.79 1.31**-2.79 1.31** North Central-5.00 1.25***- 5.00 1.25*** SMSA sizea Under 100,0001.66 3.461.66 3.46 100,000-250,0001.57 1.581.57 1.58 250,000-500,0005.54 1.60***5.54 1.60*** 500,000 1 'million4.97 1.72***4.97 1.72*** 1 million-2.5 million12.12 1.39***12.12 1.39*** Over 2.5 million15.38 1.47***15.38 1.47*** House stab9.58 1.19***9.58 1.19*** Constant2.96 1.16**6.38 2.28*** Model statistics R2 0.38 0.38 N 1,811 1,811 aSize of standard metropolitan statistical area (SMSA). ***T is significant at p ' .01. **T is significant at p s .05. *T is significant at p s .10.
STAFF SIZE, PRIVILEGES, AND COMPENSATION TABLE A-6 What Percentage of the Physicians Who Applied for Active Staff Privileges During Calendar Year 1981 Were Accepted? _ 439 System Control Coefficients Relative to Freestanding Hospitals Coefficient Standard Error Coefficient Standard Error Variables Investor-Owned Systems Freestanding hospitals - 11.84 4.05*** System characteristics System control Religious nonprofit2.94 2.49- 8.90 4.49** Secular nonprofit-0.19 4.50- 12.03 5.78** Investor-owned11.84 4.05*** Public- 10.38 13.86-22.22 14.31 Contract-managed0.26 3.67- 11.58 4.43*** System size-0.02 0.01- 0.02 0.01 Hospital characteristics Number of beds3.59 0.63***3.59 0.63*** Regional location Northeast0.93 2.580.93 2.58 South- 5.03 2.45**- 5.03 2.45** North Central-7.63 2.34***- 7.63 2.34*** SMSA sizea Under 100,00012.46 6.48*12.46 6.48* 100,000-250,0009.63 2.95***9.63 2.95*** 250,000-500,0005.46 3.01*5.46 3.01* 500,00~1 million1.23 3.231.23 3.23 1 million-2.5 million3.97 2.603.97 2.60 Over 2.5 million-3.37 2.76- 3.37 2.76 House staE-5.08 2.23**-5.08 2.23** Constant76.78 2.17***88.62 4.28*** Model statistics R2 0.06 0.06 N 1,811 1,811 aSize of standard metropolitan statistical area (SMSA). ***T is significant at p c .01. **T is significant at p _ .05. *T is significant at p _ .10.
Freestanding Hospitals 440 FOR-PROFIT ENTERPRISE IN HEALTH CARE TABLE A-7 How Many Practitioners (Total) Were on the Active or Associate Medical Staff per 100 Staffed Beds as of September 30, 1982? System Control Coefficients Relative to Investor-Owned Systems Variables Coefficient Standard Error Coefficient Standard Error _ Freestanding hospitals -8.54 2.72*** System characteristics System control Religious nonprofit5.79 1.91***- 2.75 3.14 Secular nonprofit12.62 2.74***4.08 3.65 Investor-owned8.54 2.72*** Public-8.22 7.30- 16.76 7.70*** Contract-managed- 1.67 2.5710.21 3.01*** System size0.00 0.010.00 0.01 Hospital characteristics Number of beds-3.62 0.45***-3.62 0.45*** Regional location Northeast-10.96 2.04***- 10.96 2.04*** South- 18.58 1.68***- 18.58 1.68*** Norm Central-22.77 1.71***-22.77 1.71*** SMSA sizer Under 100,00033.10 5.49***33.10 5.49*** 100~000 250,00023.16 2.17***23.16 2.17*** 250,000 500,00029.15 2.17***29.15 2.17*** 500,000-1 million36.02 2.23***36.02 2.23*** 1 million-2.5 million47.80 1.94***47.80 1.94*** Over 2.5 million49.13 1.96***49.13 1.96*** House staff14.55 1.57***14.55 1.57*** Constant44.59 1.58***53.13 2.96*** Model statistics R2 0.26 0.26 N 5,004 5,004 a Size of standard metropolitan statistical area (SMSA). ***T is significant at p c .01.
STAFF SIZE, PRIVILEGES, AND COMPENSATION TABLE A-8 How Many General and Family Practice Medical Specialists Were on the Medical Stag per 100 Staff Becis as of September 30, 1982? System Control Coefficients Relative to 441 Freestanding Hospitals Investor-Owned Systems VariablesCoefficient Standard ErrorCoefficient Standard Error Freestanding hospitals -1.03 0.51 System characteristics System control Religious nonprofit0.48 0.36- 0.55 0.59 Secular nonprofit0.67 0.52- 0.35 0.69 Investor-owned1.03 0.51** Public1.09 1.360.05 1.44 Contract-managed0.46 0.49-0.57 0.57 System size0.00 0.000.00 0.00 Hospital characteristics Number of beds- 1.69 0.08***- 1.69 0.08 Regional location Northeast-4.71 0.39***-4.71 0.39 South-4.24 0.32***-4.24 0.32 North Central-3.05 0.33***-3.05 0 33 SMSA sizea Under 100,000 100,000-250,000 250,000 500,000 500,000-1 million 1 million-2.5 million Over 2.5 million House staff Constant Model statistics R2 N 0.96 2.06 2.82 2.51 2.88 2.83 0.38 13.68 0.16 4,935 1.06 0.41*** 0.41*** 0.42*** 0.36*** 0.37*** 0.29 0.31*** 0.96 2.06 2.82 2.51 2.88 2.83 0.38 14.71 1.06 0.41*** 0.41*** 0.42*** 0.36*** 0.37*** 0.29 0.56*** 0.16 4,935 a Size of standard metropolitan statistical area (SMSA). ***T is significant at p s .01. **T is significant at p s .05.
442 FOR-PROFIT ENTERPRISE IN HEALTH CARE TABLE A-9 How Many Pediatric Meclical Specialists Were on the Medical Staff per 100 Staffed Beds as of September 30, 1982? _ . System Control Coefficients Relative to- Freestanding Hospitals Investor-Owned Systems VariablesCoefficient Standard ErrorCoefficient Standard Error Freestanding hospitals 0.63 0.47 System characteristics System control Religious nonprofit-0.18 0.330.45 0.55 Secular nonprofit1.11 0.48**1.74 0.64*** Investor-owIled-0.63 0.47 Public-2.91 1.27**-2.27 1.34* Contract-managed- 0.08 0.460.55 0.53 System size0.00 0.000.00 0.00 Hospital characteristics Number of beds- 0.18 0.08**- 0.18 0.08** Regional location Northeast-0.68 0.36*- 0.68 0.36* South- 1.00 0.30***- 1.00 0.30*** North Central-1.87 0.31***- 1.87 0.31*** SMSA sizea Under 100,0002.39 0.99**2.39 0.99** 100, 00~250, 0001.55 0.38***1.55 0.38*** 250, 00~500, 0002.21 0.38***2.21 0.38*** 500,000 1 million3.54 0.39***3.54 0.39*** 1 million-2.5 million4.38 0.34***4.38 0.34*** Over 2.5 million3.85 0.34***3.85 0.34*** House stab2.53 0.27***2.53 0.27*** Constant2.37 0.28***1.74 0.52*** Model statistics R2 0.11 0.11 N 4,935 4,935 aSize of standard metropolitan statistical area (SMSA). ***T is significant at p 5 .01. **T is significant at p 5 .05. *T is significant at p 5 .10.
STAFF SIZE, PFUVILEGES, AND COMPENSATION 443 TAM;: A-lO How Many Genera] Internal Medical Specialists Were on Me Medical Staff per 100 Staffed Beds as of September 30, 1982? System Control Coefficients Relative to- - Freestanding Hospitals Vanables Investor-Owned Systems Coefficient Standard Error Coefficient Standard Error Freestanding hospitals - 2.04 0.53*** System characteristics System control Religious nonprofit0.96 0.37***- 1.07 0.61* Secular nonprofit1.09 0.54**- 0.95 0.71 Investor-owned2.04 0.53*** Public- 1.12 1.42- 3.16 1.50** Contract-managed0.08 0.51- 1.96 0.59*** System size0.00 0.000.00 0.00 Hospital characteristics Number of beds0.13 0.090.13 0.09 Regional location Northeast0.02 0.400.02 0.40 South-2.81 0.33***-2.81 0.33*** North Central-3.46 0.34***- 3.46 0.34*** SMSA sizea Under 100,0004.43 1.11***4.43 1.11*** 100,000-250,0002.85 0.42***2.85 0.42*** 250,000-500,0002.98 0.42***2.98 0.42*** 500,000-1 million4.10 0.43***4.10 0.43*** 1 million-2.5 million5.25 0.38***5.25 0.38*** Over 2.5 million6.68 0.38***6.68 0.38*** House stab2.20 0.30***2.20 0.30*** Constant4.31 0.32***6.34 0.58*** Model statistics R2 0.20 0.20 N 4,935 4,935 aSize of standard metropolitan statistical area (SMSA). ***T significant at p ' .01. **T significant at p ' .05. *T significant at p c .10.
444 FOR-PROFIT ENTERPRISE IN HEALTH CARE TABLE A-ll How Many Other Medical Specialists Were on the Medical Staff per 100 Staffed Beds as of September 30, 1982? System Control Coefficients Relative to Freestanding Hospitals Investor-Owned Systems V enablesCoefEicient Standard ErrorCoefficient Standard Error Freestanding hospitals -2.46 0.48*** System characteristics System control Religious nonprofit1.07 0.34***-1.39 0.56** Secular nonprofit1.23 0.49**- 1.23 0.65* Investor-owned2.46 0.48*** Public-0.55 1.29-3.01 1.36** Contract-managed0.24 0.47-2.22 0.54*** System size0.00 0.000.00 0.00 Hospital characteristics Number of beds- 0.14 0.08*- 0.14 0.08* Regional location Northeast- 1.63 0.37***- 1.63 0.37*** South- 1.80 0.31***- 1.80 0.31*** North Central-2.72 0.31***- 2.72 0.31*** SMSA sizea Under 100,0004.40 1.01***4.40 1.01*** 100,000-250,0002.52 0.39***2.52 0.39*** 250,000-500,00~03.35 0.39***3.35 0.39*** 500,000-1 million4.31 0.39***4.31 0.39*** 1 million-2.5 million6.17 0.35***6.17 0.35*** Over 2.5 million7.31 0.35***7.31 0.35*** House stag1.84 0.28***1.84 0.28*** Constant2.92 0.29***5.38 0.53*** Model statistics R2 0.20 0.20 N 4,935 4,935 aSize of standard statistical metropolitan area (SMSA). ***T is significant at p c .01. **T is significant at p c .oS. *T is significant at p c .10.
STAFF SIZE, PRIVILEGES, AND COMPENSATION 445 TABLE A-12 How Many General Surgery Specialists Were on the Medical Staff per 100 Staffed Beds as of September 30, 1982? - System Control Coefficients Relative to Freestanding Hospitals Variables Investor-Owned Systems Coefficient Standard Error Coefficient Standard Error Freestanding hospitals System characteristics System control Religious nonprofit Secular nonprofit Investor-owned Public Contract-managed System size Hospital characteristics Number of beds Regional location Northeast South North Central SMSA sizea 0.91 0.54 0.83 -0.09 -0.07 0.00 -0.39 -0.51 -1.33 -1.64 -0.83 0.22*** 0.31* 0.31*** 0.82 0.30 0.00 0.05*** 0.23** 0.19*** 0.20*** 0.07 -0.30 -0.93 -0.90 0.00 -0.39 -0.51 -1.33 -1.64 0.31*** 0.36 0.42 0.87 0-34*** 0.00 0.05*** 0.23** 0.19*** 0.20*** Under 100,000 1.60 0.64** 1.60 0.64** 100,000-250,000 1.62 0.25*** 1.62 0.25*** 250,0t)0-500,000 2.10 0.25*** 2.10 . 0.25*** 500,0(~0-1 million 2.78 0.25*** 2.78 0.25*** 1 million-2.5 million 3.49 0.22*** 3.49 0.22*** Over 2.5 million 3.59 0.22*** 3.59 0.22*** House staff 1.02 0.18**$ 1.02 0.18*** Constant 4.03 0.18*** 4.87 0.34*** Model statistics R2 0.13 0.13 N 4,935 4,935 aSize of standard statistical metropolitan area (SMSA). ***T is significant at p 5 .01. **T is significant at p s .o5. *T is significant at p s .10.
446 FOR-PROFIT ENTERPRISE IN HEALTH CARE TABLE A-13 What Percentage of Total Admissions During Calendar Year 1981 Were Admitted by the Five Highest Admitting Physicians? System Control Coefficients Relative to Freestanding Hospitals Investor-Owned Systems VariablesCoefficient Standard ErrorCoefficient Standard Error - Freestanding hospitals 3.44 2.68 System characteristics System control Religious nonprofit-5.54 1.64*$*- 2.10 2.96 Secular nonprofit8.70 2.97***12.13 3.82*** Investor-owned-3.44 2.68 Public- 17.09 9.15*- 13.65 9.45 Contract-managed7.96 2.43***11.40 2.92*** System size-0.02 0.01**- 0.02 0.01** Hospital characteristics Number of beds-10.72 0.41***-10.72 0.41*** Regional location Northeast-2.58 1.70- 2.58 1.70 South8.00 1.62***8.00 1.62*** Norm Central10.51 1.55***10.51 1.55*** SMSA sizea Under 100,000- 25.11 4.28***- 25.11 4.28*** 100,000-250,000- 18.25 1.95***- 18.25 1.95*** 250,000-500,000- 18.14 1.98***- 18.14 1.98*** 500,000-1 million-17.72 2.13***17.72 2.13*** 1 million-2.5 million-22.43 1.72***- 22.43 1.72*** Over 2.5 million-21.57 1.82***- 21.57 1.82*** House staff13.44 1.48***13.44 1.48*** Constant72.20 1.43***68.76 2.82*** Model statistics R2 0.57 0.57 N 1,811 1,811 aSize of standard statistical metropolitan area (SM~SA). ***T is significant at p ' .01. **T is significant at p s .05. *T is signficant at p s .10.
STAFF SIZE, PRIVILEGES, AND COMPENSATION TABLE A-14 Percentage of Top Five Admitting Physicians Who Are Board Certified 447 System Control Coefficients Relative to Freestanding Hospitals Variables Investor-Owned Systems Coefficient Standard Error Coefficient Standard Error Freestanding hospitals -2.61 4.27 System characteristics System control Religious nonprofit0.70 2.63- 1.91 4.73 Secular nonprofit-3.86 4.82- 6.47 6.14 Investor-owned2.61 4.27 Public-4.43 14.59-7.05 15.07 Contract-managed- 5.68 3.91- 8.30 4.67 System size0.01 0.020.01 0.02 Hospital characteristics Number of beds4.94 0.67***4.94 0.67 Regional location Northeast-2.75 2.76- 2.75 2.76 South- 7.87 2.60***- 7.87 2.60 North Central- 6.30 2.49**- 6.30 2.49 SMSA sizea Under 100,00011.14 6.8211.14 6.82 100,000-250,0004.36 3.154.36 3.15 250,000-500,000-2.25 3.20-2.25 3.20 500,000-1 million- 1.53 3.43- 1.53 3.43 1 million-2.5 million0.72 2.780.72 2.78 Over 2.5 million0.02 2.950.02 2.95 House staE-0.03 2.41- 0.03 2.41 Constant56.06 2.30***S8.67 4.51 Model statistics R2 0.067 0.067 N 1,758 1,758 aSize of standard statistical metropolitan area (SMSA). ***T is significant at p s .01. **T is significant at p s .05. *T is significant at p s .10.
448 FOR-PROFIT ENTERPRISE IN HEALTH CARE TABLE A-15 Is Board Certification Required for Any (or All) Specialties on Your Hospital Active Staff? System Control Coefficients Relative to Freestanding Hospitals Variables Investor-Owned Systems Coellicient Standard Error Coefficient Standard Error Freestanding hospitals -0.08 0.28 System characteristics System control Religious nonprofit-0.33 0.18*- 0.41 0.31 Secular nonprofit0.20 0.300.12 0.39 Investorowned0.08 0.28 Public-0.50 0.90-0.58 0.93 Contract-managed-0.06 0.26-0.13 0.31 System size-0.00 0.00- 0.00 0.00 Hospital characteristics Number of beds0.10 0.04**0.10 0.04 Regional locations Northeast0.78 0.18***0.78 0.18 South0.67 0.18***0.67 0.18 North Central0.45 0.17***0.45 0.17 SMSA sizea Under 100,0000.53 0.400.53 0.40 100,000-250,0000.09 0.200.09 0.20 250,00.0-500,0000.18 0.200.18 0.20 500,000-1 million0.20 0.210.20 0.21 1 million-2.5 million0.37 0.17**0.37 0.17 Over 2.5 million0.64 0.18***0.64 0.18 House staB0.21 0.150.21 0.15 Constant-1.78 0.16***-1.70 0.30 Model statistics Pseudo R 0.17 0.17 N 1,811 1,811 aSize of standard statistical metropolitan area (SMSA). ***T is significant at p s .01. **T is significant at p 5 .05. *T is significant at p s .10. . .
STAFF SIZE, PRIVILEGES, AND COMPENSATION 449 TABLE A-16 Proportion of Active and Associate Medical Staff Who Are Board Certified l System Control Coefficients Relative to Freestanding Hospitals Vanables Investor-Owned Systems Coefficient Standard ErrorCoefficient Standard Error Freestanding hospital 0.02 0.02 System characteristics System control Religious nonprofit0.02 0.020.04 0.03 Secular nonprofit0.02 0.020.04 0.03 Investor-owned-0.02 0.02 Public-0.11 0.06*-0.09 0.06 Contract-managed-0.02 0.02o.oo 0.03 System size0.00 0.000.00 0.00 Hospital characteristics Number of beds0.02 o.oo***0.02 o.oo*** Regional location Northeast- 0.03 0.02**- 0.03 0.02** South- 0.05 0.01***0.05 0.01*** North Central-0.08 0.01***-0.08 0.01*** SMSA sizea Under 100,0000.06 0.050.06 0.05 100,000-250,0000.04 0.02**0.04 0.02** 250,000-500,0000.05 0.02***0.05 0.02*** 500,000-1 million0.07 0.02***0.07 0.02*** 1 million-2.5 million0.07 0.02***0.07 0.02*** Over 2.s million0.06 0.02***0.06 0.02*** House staff0.01 0.010.01 0.01 Constant0.59 0.01***0.s7 0.03*** Model statistics 0-043 4,448 0.043 4,448 aSize of standard statistical metropolitan area (SMSA). ***T is significant at p ' .01. **T is significant at p ~ .05. *T is significant at p _ .10.
450 FOR-PROFIT ENTERPRISE IN HEALTH CARE TABLE A-17 What Is the Usual Number of Months for Provisional Appointment Before a Physician Is Awarded Full Privileges? System Control Coefficients Relative to- Freestanding Hospitals Investor-Owned Systems Vanables Coefficient Standard Error Coefficient Standard Error Freestanding hospitals System characteristics System control Religious nonprofit Secular nonprofit Investor-owned Public Contract-managed System size Hospital characteristics Number of beds Regional location Northeast South North Central - 1.11 0.50 0.55 1.39 -0.43 0.00 0.56 0.48 0.010 -0.18 0.37 0.67 0.60 2.05 0.54 0.00 0.09 0.38 0.36 0.35 0.55 0.60 0.56 0.05 0.84 0.98 0.00 0.56 0.48 0.00 .18 0.67 0.86 2.12 0.66 0.00 0.09 0.38 0.36 0.35 SMSA sizea Under 100,0000.89 0.960.89 0.96 100,000 250,0001.59 0.44***1.59 0.44*** 250,000 500,0001.33 0.45***1.33 0.45*** 500,000-1 million1.83 0.48***1.83 0.48*** 1 million-2.5 million1.92 0.39***1.92 0.39*** Over2.5 million1.56 0.41***1.56 0.41*** House stab- 1.25 0.33***- 1.25 0.33*** Constant6.88 0.32***7.42 0.63*** Model statistics R2 0.10 0.10 N 1,811 1,811 aSize of standard statistical metropolitan area (SMSA). ***T is significant at p s .01.
STAFF SIZE, PRIVILEGES, AND COMPENSATION 451 TABLE A-18 How Many Full-Time and Part-Time Physicians and Dentists Were on the Hospital Payroll as of September 30, 1982? System Control Coefficients Relative to- Freestanding Hospitals Investor-Owned Systems Variables Coefficient Standard Error Coefficient Standard Error Freestanding hospitals 1.53 1.67 System characteristics System control Religious nonprofit-1.72 1.17- 0.19 1.93 Secular nonprofit-2.18 1.68- 0.64 2.24 Investor-owned-1.53 1.67 Public46.91 4.47***48.44 4.72 Contract-managed-0.48 1.571.05 1.85 System size0.00 0.010.00 0.01 Hospital characteristics Number of beds2.41 0.28***2.41 0.28 Regional location Northeast10.14 1.25***10.14 1.25 South-1.28 1.03-1.28 1.03 North Central0.50 1.050.50 1.05 SMSA sized Under 100,000-4.79 3.36-4.79 3.36 100,000-250,000-2.67 1.33**-2.67 1.33 250,000-500,000-2.23 1.33*-2.23 1.33 500,000-1 million-4.97 1.36***- 4.97 1.36 1 million-2.5 million0.92 1.19o.9a 1.19 Over 2.5 million6.78 1.20***6.78 1.20 House stay24.19 0.96***24.19 0.96 Constant-1.90 0.97*- 3.43 1.81 Model statistics R2 0.32 0.32 N S,004 5,004 aSize of standard statistical metropolitan area (SMSA). ***T is significant at p s .01. **T is significant at p s .05. *T is significant at p s .10.
452 FOR-PROFIT ENTERPRISE IN HEALTH CARE TABLE A-l9 The Primary Form of Compensation for Anesthesiologists Is a Percent of Revenue or Fee for Service System Control Coefficients Relative to Freestanding Hospitals Investor-Owned Systems VariablesCoefficient Standard ErrorCoefficient Standard Error Freestanding hospitals -1.49 1.07 System characteristics System control Religious nonprofit0.53 0.39- 0.95 1.12 Secular nonprofit-0.65 0.46- 2.14 1.14* Investor-owned1.49 1.07 Public- 2.52 0.96$**- 4.01 1.41*** Contract-managed- 0.52 0.50- 2.00 1.09* System size0.00 0.000.00 0.00 Hospital characteristics Number of beds0.09 0.080.09 0.08 Regional location Northeast-1.20 0.32***-1.20 0.32*** South- 0.12 0.36- 0.12 0.36 North Central-0.14 0.34-0.14 0.34 SMSA sizea Under 100,0000.50 0.810.50 0.81 100,000-250,0000.46 0.420.46 0.42 250,000-500,0000.12 0.350.12 0.35 500,000-1 million1.11 0.47**1.11 0.47** 1 million-2.5 million0.39 0.340.39 0 34 Over 2.5 million0.18 0.320.18 0.32 House stag- 0.93 0.20***- 0.93 0.20*** Constant2.36 0.34***3.85 1.08*** Model statistics Pseudo R 0.28 0.28 N 1,234 1,234 aSize of standard metropolitan statistical area (SMSA). ***Chi-square significant at p ' .01. **Chi-square significant at p ' .05. *Chi-square significant at p ' .10.
STAFF SIZE, PRIVILEGES, AND COMPENSATION TABLE A-20 The Primary Form of Compensation for Radiologists Is a Percent of Revenue or Fee for Service - System Control Coefficients Relative to 453 Freestanding Hospitals Investor-Owned Systems Variables Coefficient Standard ErrorCoefficient Standard Error Freestanding hospitals - 0.62 0.87 System characteristics System control Religious nonprofit1.23 0.49**0.60 0.98 Secular nonprofit-0.24 0.51-0.87 0.97 Investor-owned0.62 0.88 Public-2.23 1.09**-2.85 1.36 Contract-managed0.28 0.74- 0.35 0.96 System size0.00 0.000.00 0.00 Hospital characteristics Number of beds-0.03 0.07-0.03 0.07 Regional location Northeast-1.44 0.34***-1.44 0.34 South0.14 0.410.14 0.41 North Central0.01 0.390.01 0.39 SMSA sizea Under 100,000- 0.05 0.83- 0.05 0.83 100,000-250,0000.08 0.470.08 0.47 250, 0~500, 000-0.60 0 37-0.60 0.37 500,000-1 million0.81 0.520.81 0.52 1 million-2.5 million-0.12 0.37- 0.12 0.37 Over 2.5 million-0.95 0.32***- 0.95 0.32 House staff-0.70 0.20***-0.70 0.20 Constant3.14 0.36***3.76 0.89 Model statistics Pseudo R 0.41 0.41 N 1,234 1,234 aSize of standard metropolitan statistical area (SMSA). ***Chi-square significant at p 5 .01. **Chi-square significant at p 5 .05.
454 FOR-PROFIT ENTERPRISE IN HEALTH Cow TABLE A-21 The Primary Form of Compensation for Pathologists Is a Percent of Revenue or Fee for Service System Control CoefBicients Relative to Freestanding Hospitals Vanables Investor-Owned Systems Coefficient Standard ErrorCoefficient Standard Error Freestanding hospitals - 0.69 0.48 System characteristics System control Religious nonprofit-0.29 0.~-0.98 0.50 Secular nonprofit-0.11 0.40- 0.80 0.60 Investor-owned0.69 0.48 Public- 1.57 1.00-2.26 1.09 Contract-managed1.37 0.50***0.68 0.51 System size-0.00 0.00**- 0.00 0.00 Hospital characteristics Number of beds-0.09 0.05-0.09 0.05 Regional location Northeast- 2.58 0.23***- 2.58 0.23 South0.10 0.240.10 0.24 North Central-0.28 0.23- 0.28 0.23 SMSA sizea Under 100,000- 0.03 0~55-0.03 0~55 100,000-250,0000.21 0.280.21 0.28 250,000-500,000- 0.33 0.27- 0.33 0.27 500,000-1 million0.03 0.290.03 0.29 1 million-2.5 million- 0.24 0.24- 0.24 0.24 Over 2.5 million-0.28 0.24- 0.28 0.24 House stem-0.51 0.21***- 0.57 0.21 Constant1.91 0.22***2.59 0.50 Model statistics Pseudo R 0.48 0.48 N 1,234 1,234 aSize of standard metropolitan statistical area (SMSA). ***Chi-square significant at p s .01. **Chi-square significant at p s .05. *Chi-square significant at p c .10.
STAFF SIZE, PRIVILEGES, AND COMPENSATION TABLE A-22 Do Your Anesthesiologists BiD Patients Directly? System Conko1 Coefficients Relative to 455 Freestanding Hospitals Variables Investor-Owned Systems Coefficient Standard Error Coefficient Standard Error . Freestanding hospitals -0.78 0.35** System characteristics System control Religious nonprofit. 0.94 0.22**- 0.33 0.40 Secular nonprofit-0.29 0.34- 1.07 0.47** Investor-owned0.78 0.35** Public- 2.49 0.80***- 3.26 0.86*** Contract-managed- 0.40 0.28- 1.17 0.37*** System size0.00 0.000.00 0.00 Hospital characteristics Number of beds0.54 0.07***0.54 0.07*** Regional location Northeast-0.49 0.20**- 0.49 0.20** South- 0.43 0.19**- 0.43 0.19** Norm Central-0.37 0.18**- 0.37 0.18** SMSA sizea Under 100,0001.36 0.64**1.36 0.64** 100,000-250,0000.63 0.23***0.63 0.23*** 25O,000-500,0000.95 0.23***0.95 0.23*** 500,000-1 million1.01 0.26***1.01 0.26*** 1 million-2.5 million1.09 0.21***1.09 0.21*** Over 2.5 million0.95 0.~***0.95 0.22*** House staff- 0.78 0.17***- 0.78 0.17*** Constant-0.19 0.16- 0.58 0.36 Model statistics Pseudo R 0.38 0.38 N 1,627 1,627 aSize of standard metropolitan statistical area (SMSA). ***Chi-square significant at p 5 .01. **Chi-square significant at p ' .05. *Chi-square significant at p c .10.
Freestanding Hospitals Vanables 456 FOR-PROFIT ENTERPRISE IN HEALTH CARE TABLE A-23 Do Your Radiologists BiD Patients Directly? System Control Coefficients Relative to- Investor-Owned Systems Coefficient Standard ErrorCoefficient Standard Error Freestanding hospitals -1.26 0.33*** System characteristics System control Religious nonprofit0.75 0.19*$*- 0.51 0.37 Secular nonprofit0.31 0.31-0.95 0.43** Investor-owned1.26 0.33*** Public-0.77 0.73-2.02 0.80** Contract-managed0.16 0.27-1.10 0.36*** System size0.00 0.000.00 0.00 Hospital characteristics Number of beds0.29 0.05***0.29 0.05*** Regional location Northeast0.01 0.170.01 0.17 South0.86 0. 17***0.86 0. 17*** North Central0.44 0.16***0.44 0.16*** SMSA sizea Under 100,0000.92 0.52*0.92 0.52* 100,000 250,0000.60 0.22***0.60 0.22*** 250,000-500,0000.27 0.200.27 0.20 500,000-1 million0.52 0.22**0.52 0.22** 1 million-2.5 million0.46 0.18***0.46 0.18*** Over 2.5 million-0.35 0.18*- 0.35 0.18* House staff- 0.33 0.00**- 0.33 0.00** Constant-0.85 0.15***0.41 0.34 Model statistics Pseudo P 0.29 0.29 N 1,627 1,627 aSize of standard metropolitan statistical area (SMSA). ***Chi-square significant at p c .01. **Chi-square significant at p ' .05. *Chi-square significant at p c .10.
STAFF SIZE, PRIVILEGES, AND COMPENSATION TABLE A-24 Do Your Pathologists Bill Patients Directly? 457 System Control Coefficients Relative to Freestanding Hospitals Investor-Owned Systems VariablesCoefficient Standard ErrorCoefficient Standard Error Freestanding hospitals - 1.43 0.29*** System characteristics System control Religious nonprofit0.35 0.19*- 1.08 0.32*** Secular nonprofit0.44 0.33- 0.99 0.42** Investor-owned1.43 0.29*** Public- 2.10 1.21*- 3.52 1.24*** Contract-managed0.87 0.28***- 0.56 0.32* System size-0.00 0.00*- 0.00 0.00* Hospital characteristics Number of beds-0.00 0.05-0.00 005 Regional location Northeast- 1.51 0.28***-l.S1 0.28*** South0.95 0.18***0.95 0.18*** North Central-0.03 0.19- 0.03 0.19 SMSA sizes Under 100,0001.09 0.45**1.09 0.45** 100,000 250,0000.78 0.23***0.78 0.23*** 250,000 500,0000.09 0.250.09 0.25 500,000-1 million0.12 0.270.12 0.27 1 million-2.5 million0.42 0.21**0.42 0.21** Over 2.5 million0.43 0.23*0.43 0.23* House staff0.42 0.14***0.42 0.14*** Constant- 1.88 0.18***- 0.46 0.30 Model statistics Pseudo R 0.34 0.34 N 1,627 1,627 aSize of standard metropolitan statistical area (SMSA). ***Chi-square significant at p c .01. **Chi-square significant at p ' .05. *Chi-square significant at p 5 .10.