JBJS | Geographic Variations in the Rates of Operative Procedures Involving the Shoulder, Including Total Shoulder Replacement, Humeral Head Replacement, and Rotator Cuff Repair*

The Journal of Bone & Joint Surgery, Volume 81, Issue 6

Articles | June 01, 1999

Geographic Variations in the Rates of Operative Procedures Involving the Shoulder, Including Total Shoulder Replacement, Humeral Head Replacement, and Rotator Cuff Repair*

MICHAEL G. VITALE, M.D., M.P.H.†; JESSICA J. KRANT, M.D.‡; ANNETINE C. GELIJNS, PH.D.‡; DANIEL F. HEITJAN, PH.D.‡; RAYMOND R. ARONS, DR.P.H.‡; LOUIS U. BIGLIANI, M.D.†; EVAN L. FLATOW, M.D.§, NEW YORK, N.Y.

View Disclosures and Other Information

Investigation performed at New York Orthopaedic Hospital and International Center for Health Outcomes and Innovation Research, Columbia-Presbyterian Medical Center, New York City

The Journal of Bone & Joint Surgery. 1999; 81:763-72

5 Recommendations (Recommend) | 3 Comments | Saved by 3 Users Save Case

Article

Tables

References

text A A A

Abstract

Background: Although geographic variations in the rates of orthopaedic procedures have been well documented, considerable controversy remains regarding the factors that drive these variations, particularly the role of the availability of orthopaedic surgeons. Moreover, little attention has been specifically focused on variations in the rates of commonly performed shoulder procedures.Methods: The current study documents state-to-state variations in the rates of total shoulder replacement, humeral head replacement, and rotator cuff repair and examines factors that might account for these variations. The regional incidences of these three procedures were analyzed with use of the Health Care Financing Administration Medicare database (MEDPAR, 1992). The rates were age-adjusted, and variations were measured with use of high:low ratios, variation coefficients, and systematic components of variation. Potential causes of variation were analyzed with use of Spearman and partial correlations as well as with Poisson regression.Results: Rates for the three procedures that were studied varied from one state to another by as much as tenfold. Humeral head replacement had the lowest rate of variation according to all three measures. All three procedures were performed less often in states that were more densely populated. With the numbers available for study, no consistent, significant relationship was found between the density of orthopaedists and shoulder surgeons and the rates of any procedure.Conclusions: The striking variations that were noted for these commonly performed procedures showed that there is a clear need for well designed clinical research to further define the factors that account for the variations and to examine the effectiveness and appropriate indications for the procedures.

Figures in this Article

Introduction

Introduction | Materials and Methods | Results | Discussion | References

Epidemiological studies have documented widespread and persistent variations in the utilization of both orthopaedic and nonorthopaedic procedures, such as those for the treatment of acute myocardial infarction^8,21 as well as hysterectomy, prostatectomy, and coronary artery bypass grafting^{2,9,12,13,22,27}. With regard to orthopaedics, geographic variations have been found for several types of operative intervention, including procedures on the lumbar spine^1,15,18 and the cervical spine⁴, total hip and total knee arthroplasty^19,28, and arthroscopy. However, virtually no variation has been found for other procedures, such as those for the treatment of fractures about the hip^{3,5-7,10,11,25}.

It is commonly believed that professional uncertainty is an important factor in these variations. This uncertainty is largely the result of incomplete scientific evidence concerning the so-called appropriateness of alternative treatments for some clinical conditions. For example, there is considerable controversy about the benefits and risks of operative compared with nonoperative treatment of herniated lumbar discs, and widespread variations have been documented^15,18. In contrast, for fractures about the hip, internal fixation is widely accepted as providing the best outcome, and low rates of variation have been noted^10,11.

In addition to professional uncertainty, other factors, including differences in the availability and practice style of physicians and differences in the characteristics of patients, may determine the rates of utilization of particular procedures. Keller et al. suggested that variations in the incidences of several major orthopaedic procedures may be explained at least partially by differences in the number of orthopaedic surgeons among regions¹¹. However, Peterson et al., in a 1992 study of variations in the utilization of hip and knee replacements in the Medicare population, were unable to confirm an association between the orthopaedic workforce and the volumes of such procedures¹⁹. Those authors found a strong inverse correlation between the rates of these procedures and the population density in each state (r = 0.5 for total hip replacement and r = 0.46 for total knee replacement). Thus, the factors that may account for widespread variation in the utilization of medical care remain to be further elucidated.

As far as we know, no studies have examined whether there are regional variations in the rates of operative procedures on the shoulder. Furthermore, the relationship between factors related to the delivery of care (such as variations in the physician and orthopaedic-surgeon workforces) and factors related to the consumption of health care (such as the characteristics and preferences of the patients) has not been addressed with regard to operative procedures involving the shoulder. Despite ongoing innovations in the operative treatment of shoulder pain, uncertainty persists about when to use nonoperative treatment and when to intervene operatively. Moreover, patients who have shoulder problems differ with regard to their attitudes toward risk and their preferences for outcomes and, therefore, with regard to their decisions about appropriate treatment. These observations suggest that there may well be major variations in the rates of operative procedures involving the shoulder.

The current study had two objectives. First, we sought to determine whether there are significant variations in the utilization of common shoulder procedures, including total shoulder replacement, humeral head replacement, and rotator cuff repair. Second, if such variations were found, we wanted to analyze certain factors that may contribute to them; we were especially interested in possible relationships between the rates of shoulder procedures and the distributions of orthopaedic surgeons, of orthopaedic surgeons with special expertise in operative treatment of the shoulder, and of primary-care physicians.

*No benefits in any form have been received or will be received from a commercial party related directly or indirectly to the subject of this article. No funds were received in support of this study.

†Department of Orthopaedic Surgery, Columbia-Presbyterian Medical Center, 622 West 168th Street, PH 11, New York, N.Y. 10032.

‡International Center for Health Outcomes and Innovation Research, Columbia-Presbyterian Medical Center, 180 Fort Washington Avenue, HP 7, New York, N.Y. 10032.

§Department of Orthopaedic Surgery, Mount Sinai Medical Center, 5 East 98th Street, Box 1188, New York, N.Y. 10029. Please address requests for reprints to Dr. Flatow.

*No benefits in any form have been received or will be received from a commercial party related directly or indirectly to the subject of this article. No funds were received in support of this study.

†Department of Orthopaedic Surgery, Columbia-Presbyterian Medical Center, 622 West 168th Street, PH 11, New York, N.Y. 10032.

‡International Center for Health Outcomes and Innovation Research, Columbia-Presbyterian Medical Center, 180 Fort Washington Avenue, HP 7, New York, N.Y. 10032.

§Department of Orthopaedic Surgery, Mount Sinai Medical Center, 5 East 98th Street, Box 1188, New York, N.Y. 10029. Please address requests for reprints to Dr. Flatow.

View Larger

TABLE I AGE-STANDARDIZED RATES FOR TOTAL SHOULDER REPLACEMENT, HUMERAL HEAD REPLACEMENT, AND ROTATOR CUFF REPAIR IN THE UNITED SATES FOR MEDICARE PATIENTS MORE THAN SIXTY-FIVE YEARS OLD, ACCORDING TO THE MEDPAR DATABASE*

*The rates are given per 100,000 Medicare beneficiaries.

State	Total Shoulder Replacement		Humeral Head Replacement		Rotator Cuff Repair
Rate	No. of Procedures	Rate	No. of Procedures	Rate	No. of Procedures
Alabama	12.35	77	7.85	45	25.16	152
Alaska	15.87	4	13.92	4	21.13	8
Arizona	13.14	75	13.10	72	30.36	177
Arkansas	11.35	42	11.01	40	26.09	103
California	8.76	300	10.52	357	29.09	1028
Colorado	19.21	72	11.75	44	51.72	223
Connecticut	3.25	17	9.57	45	28.49	139
Delaware	7.84	7	5.53	6	33.27	31
District of Columbia	2.47	2	4.36	3	24.15	20
Florida	10.91	281	10.51	263	23.02	593
Georgia	10.44	77	9.40	75	26.28	216
Hawaii	2.81	5	4.83	7	19.63	30
Idaho	25.60	35	12.00	17	64.92	93
Illinois	8.04	124	8.97	134	22.66	352
Indiana	10.99	86	7.53	60	24.61	204
Iowa	14.22	64	12.86	60	51.09	228
Kansas	17.62	68	10.65	40	44.16	160
Kentucky	6.91	44	4.60	27	21.97	115
Louisiana	9.82	52	10.45	56	21.06	117
Maine	12.21	26	10.40	20	33.70	65
Maryland	7.64	45	6.97	39	31.95	185
Massachusetts	5.36	49	10.12	89	26.79	241
Michigan	10.52	134	10.35	130	26.73	344
Minnesota	12.63	78	11.13	73	40.95	234
Mississippi	11.24	40	9.40	36	9.41	36
Missouri	9.75	78	10.19	80	30.14	243
Montana	16.88	21	15.98	20	55.31	66
Nebraska	14.97	35	14.63	37	54.28	127
Nevada	10.39	18	7.12	13	31.07	57
New Hampshire	11.04	17	8.76	13	32.96	52
New Jersey	4.92	59	7.41	80	20.01	219
New Mexico	9.38	21	12.42	24	21.46	46
New York	5.97	156	8.39	208	13.81	351
North Carolina	9.46	98	8.47	79	24.29	245
North Dakota	17.57	16	17.48	18	85.52	86
Ohio	11.12	178	10.64	162	23.94	392
Oklahoma	11.72	51	7.47	31	20.26	90
Oregon	17.43	78	10.22	44	43.45	200
Pennsylvania	7.84	166	11.01	226	25.78	518
Rhode Island	12.84	19	7.35	13	27.90	44
South Carolina	8.49	41	9.16	42	19.48	104
South Dakota	8.84	10	13.89	15	59.65	64
Tennessee	8.20	62	9.21	67	17.09	130
Texas	10.49	202	9.23	180	23.52	472
Utah	19.57	32	12.27	21	63.49	110
Vermont	12.66	9	15.51	12	33.66	28
Virginia	15.04	114	8.48	66	35.84	282
Washington	16.99	114	15.98	104	64.10	414
West Virginia	6.96	23	12.48	36	11.95	39
Wisconsin	8.59	62	11.37	83	50.11	343
Wyoming	23.33	13	3.90	4	40.93	25

Add to My JBJS

*The rates are given per 100,000 Medicare beneficiaries.

State	Total Shoulder Replacement		Humeral Head Replacement		Rotator Cuff Repair
Rate	No. of Procedures	Rate	No. of Procedures	Rate	No. of Procedures
Alabama	12.35	77	7.85	45	25.16	152
Alaska	15.87	4	13.92	4	21.13	8
Arizona	13.14	75	13.10	72	30.36	177
Arkansas	11.35	42	11.01	40	26.09	103
California	8.76	300	10.52	357	29.09	1028
Colorado	19.21	72	11.75	44	51.72	223
Connecticut	3.25	17	9.57	45	28.49	139
Delaware	7.84	7	5.53	6	33.27	31
District of Columbia	2.47	2	4.36	3	24.15	20
Florida	10.91	281	10.51	263	23.02	593
Georgia	10.44	77	9.40	75	26.28	216
Hawaii	2.81	5	4.83	7	19.63	30
Idaho	25.60	35	12.00	17	64.92	93
Illinois	8.04	124	8.97	134	22.66	352
Indiana	10.99	86	7.53	60	24.61	204
Iowa	14.22	64	12.86	60	51.09	228
Kansas	17.62	68	10.65	40	44.16	160
Kentucky	6.91	44	4.60	27	21.97	115
Louisiana	9.82	52	10.45	56	21.06	117
Maine	12.21	26	10.40	20	33.70	65
Maryland	7.64	45	6.97	39	31.95	185
Massachusetts	5.36	49	10.12	89	26.79	241
Michigan	10.52	134	10.35	130	26.73	344
Minnesota	12.63	78	11.13	73	40.95	234
Mississippi	11.24	40	9.40	36	9.41	36
Missouri	9.75	78	10.19	80	30.14	243
Montana	16.88	21	15.98	20	55.31	66
Nebraska	14.97	35	14.63	37	54.28	127
Nevada	10.39	18	7.12	13	31.07	57
New Hampshire	11.04	17	8.76	13	32.96	52
New Jersey	4.92	59	7.41	80	20.01	219
New Mexico	9.38	21	12.42	24	21.46	46
New York	5.97	156	8.39	208	13.81	351
North Carolina	9.46	98	8.47	79	24.29	245
North Dakota	17.57	16	17.48	18	85.52	86
Ohio	11.12	178	10.64	162	23.94	392
Oklahoma	11.72	51	7.47	31	20.26	90
Oregon	17.43	78	10.22	44	43.45	200
Pennsylvania	7.84	166	11.01	226	25.78	518
Rhode Island	12.84	19	7.35	13	27.90	44
South Carolina	8.49	41	9.16	42	19.48	104
South Dakota	8.84	10	13.89	15	59.65	64
Tennessee	8.20	62	9.21	67	17.09	130
Texas	10.49	202	9.23	180	23.52	472
Utah	19.57	32	12.27	21	63.49	110
Vermont	12.66	9	15.51	12	33.66	28
Virginia	15.04	114	8.48	66	35.84	282
Washington	16.99	114	15.98	104	64.10	414
West Virginia	6.96	23	12.48	36	11.95	39
Wisconsin	8.59	62	11.37	83	50.11	343
Wyoming	23.33	13	3.90	4	40.93	25

View Larger

TABLE II MEASURES OF VARIATIONS FOR THE RATES OF TOTAL SHOULDER REPLACEMENT, HUMERAL HEAD REPLACEMENT, AND ROTATOR CUFF REPAIR

Procedure	Coefficient of Variation	High:Low Ratio	Systematic Component of Variation (Age-Adjusted)
Rotator cuff repair	0.477	9.09	0.342
Total shoulder replacement	0.427	10.36	0.203
Humeral head replacement	0.301	4.48	0.045

Add to My JBJS

TABLE II MEASURES OF VARIATIONS FOR THE RATES OF TOTAL SHOULDER REPLACEMENT, HUMERAL HEAD REPLACEMENT, AND ROTATOR CUFF REPAIR

Procedure	Coefficient of Variation	High:Low Ratio	Systematic Component of Variation (Age-Adjusted)
Rotator cuff repair	0.477	9.09	0.342
Total shoulder replacement	0.427	10.36	0.203
Humeral head replacement	0.301	4.48	0.045

View Larger

TABLE III POPULATION AND WORKFORCE DENSITIES ACCORDING TO STATE

*Derived from Statistical Abstract of the United States, 1993: The National Data Book²⁴.†Derived from Physician Characteristics and Distribution in the United States, 1993 Edition (1992 Data)²⁰.

State	Population Density* (no. of people per sq. mile)	State Workforce-Availability Densities (no. of physicians per 1000 Medicare beneficiaries)
All Physicians	Primary-Care Physicians	Orthopaedic Surgeons	Shoulder Specialists
Alabama	81.5	12.25	3.50	0.33	0.028
Alaska	1.0	28.46	11.00	1.64	0.107
Arizona	33.7	16.27	3.75	0.41	0.047
Arkansas	46.1	10.45	3.21	0.31	0.025
California	197.9	23.95	5.57	0.55	0.049
Colorado	33.5	21.33	5.60	0.68	0.089
Connecticut	677.2	23.37	5.24	0.49	0.041
Delaware	352.5	16.66	9.11	0.46	0.032
District of Columbia	9649.5	53.44	4.86	0.65	0.064
Florida	249.8	13.81	2.92	0.32	0.029
Georgia	116.6	16.67	4.22	0.48	0.047
Hawaii	180.5	22.27	5.60	0.41	0.058
Idaho	12.9	11.19	3.59	0.51	0.022
Illinois	209.2	18.03	5.08	0.35	0.039
Indiana	157.8	12.83	3.74	0.33	0.037
Iowa	50.3	10.47	3.01	0.29	0.030
Kansas	30.8	13.56	3.99	0.29	0.027
Kentucky	94.5	12.93	3.53	0.31	0.025
Louisiana	98.4	16.44	3.69	0.40	0.027
Maine	40.0	14.02	3.80	0.41	0.063
Maryland	502.1	31.65	7.13	0.58	0.048
Massachusetts	765.3	25.33	5.74	0.45	0.050
Michigan	166.1	15.38	3.85	0.26	0.032
Minnesota	56.3	18.58	5.75	0.43	0.051
Mississippi	55.7	10.17	2.88	0.25	0.021
Missouri	75.4	14.24	3.33	0.34	0.022
Montana	5.7	12.57	3.57	0.54	0.041
Nebraska	20.9	13.16	4.09	0.34	0.049
Nevada	12.1	13.31	3.57	0.43	0.050
New Hampshire	123.8	18.10	4.28	0.55	0.034
New Jersey	1049.9	19.45	4.73	0.39	0.042
New Mexico	13.0	17.40	4.63	0.45	0.036
New York	383.7	25.23	6.00	0.36	0.040
North Carolina	140.5	15.52	3.84	0.41	0.037
North Dakota	9.2	12.48	4.44	0.30	0.020
Ohio	269.0	15.41	3.80	0.05	0.031
Oklahoma	46.8	11.29	3.13	0.30	0.032
Oregon	31.0	15.98	4.24	0.48	0.050
Pennsylvania	267.9	16.26	3.96	0.32	0.038
Rhode Island	961.8	17.84	4.43	0.45	0.049
South Carolina	119.7	14.29	3.96	0.38	0.038
South Dakota	9.4	10.48	4.06	0.36	0.062
Tennessee	121.9	15.50	3.97	0.41	0.026
Texas	67.4	17.57	4.25	0.45	0.043
Utah	221.0	21.51	4.94	0.67	0.094
Vermont	61.6	21.88	5.63	0.53	0.064
Virginia	161.0	19.24	4.96	0.52	0.035
Washington	77.1	19.30	5.32	0.58	0.043
West Virginia	75.2	11.06	3.22	0.21	0.022
Wisconsin	92.2	14.54	4.09	0.41	0.037
Wyoming	4.8	13.35	4.82	0.62	0.618

Add to My JBJS

TABLE III POPULATION AND WORKFORCE DENSITIES ACCORDING TO STATE

State	Population Density* (no. of people per sq. mile)	State Workforce-Availability Densities (no. of physicians per 1000 Medicare beneficiaries)
All Physicians	Primary-Care Physicians	Orthopaedic Surgeons	Shoulder Specialists
Alabama	81.5	12.25	3.50	0.33	0.028
Alaska	1.0	28.46	11.00	1.64	0.107
Arizona	33.7	16.27	3.75	0.41	0.047
Arkansas	46.1	10.45	3.21	0.31	0.025
California	197.9	23.95	5.57	0.55	0.049
Colorado	33.5	21.33	5.60	0.68	0.089
Connecticut	677.2	23.37	5.24	0.49	0.041
Delaware	352.5	16.66	9.11	0.46	0.032
District of Columbia	9649.5	53.44	4.86	0.65	0.064
Florida	249.8	13.81	2.92	0.32	0.029
Georgia	116.6	16.67	4.22	0.48	0.047
Hawaii	180.5	22.27	5.60	0.41	0.058
Idaho	12.9	11.19	3.59	0.51	0.022
Illinois	209.2	18.03	5.08	0.35	0.039
Indiana	157.8	12.83	3.74	0.33	0.037
Iowa	50.3	10.47	3.01	0.29	0.030
Kansas	30.8	13.56	3.99	0.29	0.027
Kentucky	94.5	12.93	3.53	0.31	0.025
Louisiana	98.4	16.44	3.69	0.40	0.027
Maine	40.0	14.02	3.80	0.41	0.063
Maryland	502.1	31.65	7.13	0.58	0.048
Massachusetts	765.3	25.33	5.74	0.45	0.050
Michigan	166.1	15.38	3.85	0.26	0.032
Minnesota	56.3	18.58	5.75	0.43	0.051
Mississippi	55.7	10.17	2.88	0.25	0.021
Missouri	75.4	14.24	3.33	0.34	0.022
Montana	5.7	12.57	3.57	0.54	0.041
Nebraska	20.9	13.16	4.09	0.34	0.049
Nevada	12.1	13.31	3.57	0.43	0.050
New Hampshire	123.8	18.10	4.28	0.55	0.034
New Jersey	1049.9	19.45	4.73	0.39	0.042
New Mexico	13.0	17.40	4.63	0.45	0.036
New York	383.7	25.23	6.00	0.36	0.040
North Carolina	140.5	15.52	3.84	0.41	0.037
North Dakota	9.2	12.48	4.44	0.30	0.020
Ohio	269.0	15.41	3.80	0.05	0.031
Oklahoma	46.8	11.29	3.13	0.30	0.032
Oregon	31.0	15.98	4.24	0.48	0.050
Pennsylvania	267.9	16.26	3.96	0.32	0.038
Rhode Island	961.8	17.84	4.43	0.45	0.049
South Carolina	119.7	14.29	3.96	0.38	0.038
South Dakota	9.4	10.48	4.06	0.36	0.062
Tennessee	121.9	15.50	3.97	0.41	0.026
Texas	67.4	17.57	4.25	0.45	0.043
Utah	221.0	21.51	4.94	0.67	0.094
Vermont	61.6	21.88	5.63	0.53	0.064
Virginia	161.0	19.24	4.96	0.52	0.035
Washington	77.1	19.30	5.32	0.58	0.043
West Virginia	75.2	11.06	3.22	0.21	0.022
Wisconsin	92.2	14.54	4.09	0.41	0.037
Wyoming	4.8	13.35	4.82	0.62	0.618

View Larger

TABLE IV CORRELATION COEFFICIENTS AND SIGNIFICANCE VALUES FOR TOTAL SHOULDER REPLACEMENT, HUMERAL HEAD REPLACEMENT, AND ROTATOR CUFF REPAIR*

*Population density correlations are Spearman rank values. Physician correlation values represent partial correlations, controlling for population density. †Indicates significance at p = 0.05.

Variable	Total Shoulder Replacement		Humeral Head Replacement		Rotator Cuff Repair
Coefficient	P Value	Coefficient	P Value	Coefficient	P Value
Population density	-0.63	<0.001†	-0.38	0.006†	-0.50	<0.001†
Physician density	-0.16	0.28	0.001	0.99	-0.10	0.49
Primary-care-physician density	-0.03	0.82	-0.02	0.91	0.005	0.97
Orthopaedic-surgeon density	0.31	0.03†	0.15	0.29	0.11	0.42
Shoulder-specialist density	0.28	0.05†	0.11	0.43	0.19	0.19

Add to My JBJS

TABLE IV CORRELATION COEFFICIENTS AND SIGNIFICANCE VALUES FOR TOTAL SHOULDER REPLACEMENT, HUMERAL HEAD REPLACEMENT, AND ROTATOR CUFF REPAIR*

*Population density correlations are Spearman rank values. Physician correlation values represent partial correlations, controlling for population density. †Indicates significance at p = 0.05.

Variable	Total Shoulder Replacement		Humeral Head Replacement		Rotator Cuff Repair
Coefficient	P Value	Coefficient	P Value	Coefficient	P Value
Population density	-0.63	<0.001†	-0.38	0.006†	-0.50	<0.001†
Physician density	-0.16	0.28	0.001	0.99	-0.10	0.49
Primary-care-physician density	-0.03	0.82	-0.02	0.91	0.005	0.97
Orthopaedic-surgeon density	0.31	0.03†	0.15	0.29	0.11	0.42
Shoulder-specialist density	0.28	0.05†	0.11	0.43	0.19	0.19

View Larger

TABLE V RELATIVE RISKS AND CONFIDENCE INTERVALS FOR TOTAL SHOULDER REPLACEMENT, HUMERAL HEAD REPLACEMENT, AND ROTATOR CUFF REPAIR, ACCORDING TO POISSON REGRESSION ESTIMATES*

*The values are given as Poisson regression estimates derived with use of generalized estimating equation models. The age-group is referenced to a sixty-five to sixty-nine-year-old group standard. The gender is referenced to female. †Indicates significance at p = 0.05 with respect to humeral head replacement. The Poisson regression model suggests that, after adjusting for age, gender, and population density, there is little if any correlation between physician density and rates of procedures.

Variable	Total Shoulder Replacement		Humeral Head Replacement		Rotator Cuff Repair
Relative Risk	95 Percent Confidence Interval	Relative Risk	95 Percent Confidence Interval	Relative Risk	95 Percent Confidence Interval
Gender (male:female)	1.70	0.58—4.95	2.40†	1.39—4.14	5.07†	1.81—14.25
Population density	0.81†	0.74—0.89	0.93†	0.87—0.98	0.94	0.84—1.04
Physician density	0.87	0.50—1.52	1.17	0.78—1.76	0.48	0.22—1.02
Primary-care-physician density	0.96	0.55—1.67	0.90	0.61—1.33	1.97†	1.03—3.77
Orthopaedic-surgeon density	0.89	0.76—1.04	0.91†	0.87—0.95	1.06	0.84—1.34
Shoulder-specialist density	1.13	0.79—1.61	1.06	0.87—1.29	1.29	0.80—2.07
Age-group
70—74 yrs.	1.33†	1.16—1.52	1.44†	1.30—1.60	1.03	0.94—1.14
75—79 yrs.	1.67†	1.30—2.14	1.90†	1.60—2.25	1.02	0.80—1.30
80—84 yrs.	1.45	0.90—2.33	2.46†	1.87—3.24	0.71	0.45—1.11
=85 yrs.	0.97	0.40—2.38	2.54†	1.64—3.94	0.35†	0.15—0.84

Add to My JBJS

TABLE V RELATIVE RISKS AND CONFIDENCE INTERVALS FOR TOTAL SHOULDER REPLACEMENT, HUMERAL HEAD REPLACEMENT, AND ROTATOR CUFF REPAIR, ACCORDING TO POISSON REGRESSION ESTIMATES*

Variable	Total Shoulder Replacement		Humeral Head Replacement		Rotator Cuff Repair
Relative Risk	95 Percent Confidence Interval	Relative Risk	95 Percent Confidence Interval	Relative Risk	95 Percent Confidence Interval
Gender (male:female)	1.70	0.58—4.95	2.40†	1.39—4.14	5.07†	1.81—14.25
Population density	0.81†	0.74—0.89	0.93†	0.87—0.98	0.94	0.84—1.04
Physician density	0.87	0.50—1.52	1.17	0.78—1.76	0.48	0.22—1.02
Primary-care-physician density	0.96	0.55—1.67	0.90	0.61—1.33	1.97†	1.03—3.77
Orthopaedic-surgeon density	0.89	0.76—1.04	0.91†	0.87—0.95	1.06	0.84—1.34
Shoulder-specialist density	1.13	0.79—1.61	1.06	0.87—1.29	1.29	0.80—2.07
Age-group
70—74 yrs.	1.33†	1.16—1.52	1.44†	1.30—1.60	1.03	0.94—1.14
75—79 yrs.	1.67†	1.30—2.14	1.90†	1.60—2.25	1.02	0.80—1.30
80—84 yrs.	1.45	0.90—2.33	2.46†	1.87—3.24	0.71	0.45—1.11
=85 yrs.	0.97	0.40—2.38	2.54†	1.64—3.94	0.35†	0.15—0.84

Materials and Methods

Introduction | Materials and Methods | Results | Discussion | References

Sources of Data

Currently, no administrative database provides data on all patients in the United States after specific medical interventions or on all patients who have a particular medical diagnosis. However, the Medicare Provider Analysis and Review (MEDPAR) file of the Health Care Financing Administration provides a full sample of the entire Medicare population. The 1992 database, which includes approximately eleven million records, was used in the present study to analyze data regarding the incidences of total shoulder replacement, humeral head replacement, and rotator cuff repair; our goals were to document variations in the incidences of these procedures and to better understand the factors that drive the variations. The database was searched for records that matched procedure codes 81.81 (total shoulder replacement), 81.80 (humeral head replacement), and 83.63 (rotator cuff repair). Most Medicare beneficiaries are more than sixty-five years old, and we specifically restricted our analysis to these patients.

Calculation of Rates

All rates concerning Medicare patients are expressed as the rate of the procedure per 100,000 Medicare beneficiaries. For each of the fifty-one states (the District of Columbia was considered a state for the purpose of the current study, but Puerto Rico was not included), we standardized the raw MEDPAR data to account for differences in the age distributions of the Medicare population, with use of demographic information obtained from the 1994 Medicare Provider Analysis and Review (the only year for which appropriate data were available). The gender distribution for the rates of procedures was available only as the overall percentage of men and women who had each procedure in each state. Thus, we were unable to directly standardize the data for gender as well as age. Unless otherwise mentioned, all MEDPAR-based rates in the current report are age-standardized.

The relationship between the age-standardized rates for each procedure in each state and various patient-related and physician-related factors then were examined.

Variables

We investigated the factor of population density because a previous report¹⁹ had documented its relationship to the rates of procedures. We defined population density as the total number of all residents of each state per square mile. The 1992 data on state population densities were obtained from Statistical Abstract of the United States, 1993: The National Data Book²⁴. Other variables that were examined included the total number of physicians as well as the number of orthopaedic surgeons and primary-care physicians in each state (determined with use of 1992 data from Physician Characteristics and Distribution in the United States, 1993 edition²⁰) and the number of shoulder specialists per 100 Medicare beneficiaries. The choice to use density rates based on the Medicare population rather than on state populations was made because this was the population for which data on the rates of procedures were available.

No truly valid measure of practice specialization relating to the shoulder is available for each state. Special training in the operative treatment of the shoulder may be included in various fellowships, including traditional shoulder fellowships, sports-medicine fellowships, and certain upper-extremity fellowships. Furthermore, many orthopaedic surgeons maintain an interest in operative treatment of the shoulder, and may subspecialize in it, without having had formal fellowship training. Such interest may be reflected in subscription to the Journal of Shoulder and Elbow Surgery; the rates of subscription to this publication (which were obtained courtesy of the Journal of Shoulder and Elbow Surgery) correlated highly with the distribution of members of the American Shoulder and Elbow Surgeons (obtained courtesy of that association) (r = 0.94). Thus, we used the rates of subscription to the Journal of Shoulder and Elbow Surgery as a proxy for specialization in the treatment of the shoulder. Primary-care physicians were defined as all physicians in family practice, general practice, and internal medicine combined. Because of our nation's increased focus on primary care and gatekeeping, we investigated whether the density of primary-care providers was correlated with the rates of procedures.

Correlations

Age-standardized rates of procedures for each state were correlated with population density, physician density, density of orthopaedic surgeons, density of subscribers to the Journal of Shoulder and Elbow Surgery (as a proxy for specialization in the treatment of the shoulder), and density of primary-care physicians. The Spearman rank-correlation test was used to assess the significance of the correlation of rates of procedures with population density. Because population density showed strong negative correlations with the rates of all three procedures (r = - 0.63 and p < 0.001 for total shoulder replacement, r = - 0.38 and p = 0.006 for humeral head replacement, and r = -0.50 and p < 0.001 for rotator cuff repair), we repeated our analysis with use of Pearson partial correlations, controlling for the effect of this factor. Removal of the effects of age and population density to the extent possible allowed us to assess more accurately the true effect of workforce-availability factors.

Poisson Regression

To estimate the effect of all predictors simultaneously, we fit Poisson regression models with use of the generalized estimating equation method¹⁴. We used the state as the unit, the vector of unstandardized rates of procedures in five age-groups for each state as the response variable, and an exchangeable working correlation matrix. We used the log population in the age-group as an offset, and we fit models predicting rates of procedures on the basis of the log of the gender ratio (male:female), the log population density in the state, the log physician density, the log orthopaedic-surgeon density, the log shoulder-specialist density, the log primary-care-physician density, and indicator variables for age-group.

Quantification of Variation

Range of variation: In order to assess the range of variation among the fifty-one states for each operative procedure, the highest and lowest rates were combined in a ratio to highlight the extreme range of variation.

Coefficient of variation: The coefficient of variation is a method of standardizing variation across procedures. These coefficients were calculated on the basis of the standard deviation divided by the mean for each of the three procedures.

Systematic component of variation: The systematic component of variation has been used in the literature on variations in rates to calculate the amount of variation that is not random^16,17,23,26. The systematic component of variation is equal to the estimate of total variance minus the random component of variation; that is, the value represents the amount of nonrandom variation that remains unexplained. A large systematic component of variation implies that many theoretically measurable factors have not yet been taken into account. The pioneers of this concept were McPherson and Wennberg^16,17, and we used their method to perform our analysis. We calculated the systematic component of variation for each procedure, using directly age-standardized rates to quantify the amount of unexplained variation not related to age.

Results

Introduction | Materials and Methods | Results | Discussion | References

Variations in the Rates of Procedures

Variations among the fifty-one states were noted for all three operative procedures for 1992. The age-standardized rates ranged from 3.90 (Wyoming) to 17.48 (North Dakota) per 100,000 Medicare beneficiaries for humeral head replacement, from 9.41 (Mississippi) to 85.52 (North Dakota) for rotator cuff repair, and from 2.47 (District of Columbia) to 25.60 (Idaho) for total shoulder replacement (Table I). The age-standardized rates of procedures and the raw number of cases for each procedure were calculated. Wide variation in the age-standardized rates was found for all three procedures.

Rotator cuff repair had the largest coefficient of variation (0.477), and total shoulder replacement had the largest high:low ratio with regard to rates of procedures (10.36), whereas humeral head replacement had both the lowest coefficient (0.301) and the lowest high:low ratio (4.48) (Table II). Thus, the rate of humeral head replacement was less variable than the rates of the other procedures, according to all analyses.

We observed the same trend with regard to the relative amount of systematic variation for each procedure. When systematic components of variation were calculated according to age-adjusted rates, rotator cuff repair had the largest component of nonrandom (that is, area-related) variation (0.342) and humeral head replacement had the smallest (0.045) (Table II). A smaller systematic component of variation implies that age accounts for more of the variation in rates, whereas a larger one suggests that there is variation exceeding that which is expected on the basis of age alone.

The physician workforce varied widely among states as well, not only in terms of absolute numbers but also when population density was taken into account. Of the fifty-one states included in our analysis, the District of Columbia had the highest population density (9649.5 people per square mile), followed by New Jersey (1049.9), and Alaska had the lowest rate (1.0) (Table III). In terms of overall physician density, the District of Columbia had the highest rate (53.44 per 1000 Medicare beneficiaries), followed by Maryland (31.65), and Mississippi had the lowest rate (10.17). With regard to the density of orthopaedic surgeons, Alaska had the highest rate (1.64 per 1000 Medicare beneficiaries), followed by Colorado (0.68), and Ohio had the lowest rate (0.05). In terms of the density of shoulder specialists, Wyoming had the highest rate (0.618 per 1000 Medicare beneficiaries), followed by Alaska (0.107), and North Dakota had the lowest rate (0.020). With regard to the density of primary-care physicians, Alaska had the highest rate (11.00 per 1000 Medicare beneficiaries), followed by Delaware (9.11), and Mississippi had the lowest rate (2.88).

Population Density

The Spearman correlations show that the variations in the rates of all three procedures are significant and are inversely related to population density (r = -0.63 and p < 0.001 for total shoulder replacement, r = -0.38 and p = 0.006 for humeral head replacement, and r = -0.50 and p < 0.001 for rotator cuff repair) (Table IV). Because of this consistent relationship, we performed partial correlations to control for differences in population density among states.

Workforce

No significant relationship was found, with the numbers available, between the total supply of physicians and the rate of any of the three procedures after controlling for population density (p = 0.28 for total shoulder replacement, p = 0.99 for humeral head replacement, and p = 0.49 for rotator cuff repair) (Table IV). This was also the case when only primary-care physicians were considered (p = 0.82 for total shoulder replacement, p = 0.91 for humeral head replacement, and p = 0.97 for rotator cuff repair). Partial correlation revealed a significant positive relationship between the density of orthopaedic surgeons and the rate of total shoulder replacement (r = 0.31 and p = 0.03), but no relationship was detected, with the numbers available, between this factor and humeral head replacement (r = 0.15 and p = 0.29) or rotator cuff repair (r = 0.11 and p = 0.42). Total shoulder replacement was also the only procedure for which a significant positive relationship with the density of shoulder specialists was detected (r = 0.28 and p = 0.05 compared with r = 0.11 and p = 0.43 for humeral head replacement and r = 0.19 and p = 0.19 for rotator cuff repair) (Table IV).

Regression estimates for the three procedures were derived with use of the generalized estimating equation method¹⁴ (Table V). The estimated relative risk is the exponential of the regression coefficient. The interpretation of this coefficient is that, for a one-unit increase in the predictor, with all other predictors held constant, the rate of procedures increases by a factor of relative risk. With regard to age-groups, relative risk represents the factor by which the rate of the procedure increases in a given age-group relative to the reference age-group of sixty-five to sixty-nine years. A relative risk of less than one suggests that higher values of the factor are associated with lower rates of procedures, whereas a relative risk of more than one suggests that higher values are associated with higher rates of procedures. Lower and upper limits of a 95 percent confidence interval also were calculated for relative risk. A confidence interval that does not include the number one indicates that the factor is significant at the 5 percent level. The age-groups with a higher proportion of men tended to have higher rates of procedures; these differences were significant with regard to humeral head replacement and rotator cuff repair (Table V). More sparsely populated states had higher rates of all three procedures. In addition, all of the older age-groups had significantly more humeral head replacements than did the reference group that was sixty-five to sixty-nine years old (p = 0.05). Rotator cuff repairs were positively associated with the density of primary-care physicians, and the oldest age-group had significantly fewer procedures than did the youngest age-group (p = 0.05). Other than population density, none of the factors were predictive of the rate of total shoulder replacement except age; the group that was seventy to seventy-four years old and the group that was seventy-five to seventy-nine years old had higher rates of procedures than did the group that was sixty-five to sixty-nine years old. The Poisson analysis did not confirm a significant association between the densities of primary-care physicians, orthopaedic surgeons, and shoulder specialists and the rates of procedures (Table V).

These results are based on correlation between the rates of procedures and the density of physicians, with both factors expressed as the number per Medicare beneficiary. For comparison, we examined the same correlations with use of the density of physicians (primary-care physicians, orthopaedic surgeons, and shoulder specialists) expressed as the number of physicians per resident in each state. Perhaps the availability of physicians to the Medicare population is determined more by the number of physicians per state resident than by the number per Medicare beneficiary. When physician density was expressed in this way, partial correlation revealed a significant correlation between the densities of orthopaedic surgeons and shoulder specialists and the rate of rotator cuff repair only (r = 0.39 and r = 0.29, respectively). However, the results of the Poisson multivariate analysis were essentially unchanged regardless of which way the analysis was done; population density showed a strong negative correlation with the rates of procedures, and there was no real correlation between physician density at any level of specialization and the rates of procedures.

Discussion

Introduction | Materials and Methods | Results | Discussion | References

Three general conclusions are supported by this study. First, there was significant variation in the rates of each of the three procedures, with humeral head replacement having the least variation. Second, population density showed a strong, significant negative relationship with the rates of all three procedures. Third, the physician workforce had a limited role in driving the rates of any of the procedures.

Humeral head replacement is used to treat fractures of the proximal part of the humerus that are not amenable to primary fixation and to treat arthritis of the glenohumeral joint, and there is a roughly even distribution between these two major indications. Many authors have reported little variability in the rates of trauma-related procedures, such as those for fractures about the hip¹⁰, perhaps because there is less professional uncertainty regarding the proper management of these patients. Of the three procedures that were considered in the current study, humeral head replacement was by far the one most driven by acute trauma, which provides a possible explanation for the lower rates of variation associated with this procedure. Nevertheless, we suspect that there are differences in practice patterns among orthopaedic surgeons in different states with regard to the indications for humeral head replacement, even after trauma. It would be interesting to study whether low rates of humeral head replacement were offset by higher rates of open reduction and internal fixation of these fractures, but our database did not allow this analysis.

Both correlation and multiple-regression analysis revealed a strong and consistent negative relationship between population density and the rates of all three procedures. This finding is similar to that reported by Peterson et al. in their study of total hip and total knee arthroplasty¹⁹. Database review cannot directly explain this finding, but there are several possible explanations. Population density may serve as a proxy for differences in other patient characteristics, such as lifestyle and occupation, that are not reflected by the available data. Residents of states with a low population density (for example, North Dakota, Idaho, Wyoming, and Montana) may have a higher prevalence of arthritis, overuse syndromes, and trauma as a result of the more strenuous, labor-intensive lifestyle in these rural areas, which have a large agricultural workforce. Alternatively, people who work in such occupations may have less tolerance for functional disability and incapacity because of the demands of their work and therefore may seek operative treatment more readily. In any event, the interesting and robust inverse relationship between rates of procedures and population density merits additional study.

We were surprised to find relatively weak relationships between the availability of physicians with various levels of specialization and the rates of the procedures after controlling for age and population density. Pearson correlations between the densities of orthopaedic surgeons and shoulder specialists and the rate of total shoulder replacement were only moderate. The positive correlation between total shoulder replacement and the density of shoulder surgeons that is suggested by the Pearson correlation makes intuitive sense. Total shoulder replacement is a technically challenging procedure that has undergone considerable incremental innovations over the last few years. This procedure has only recently begun to be performed outside of large medical centers, and it still is likely to be predominantly the domain of specialized shoulder surgeons. Therefore, we expected that the availability of shoulder surgeons might drive the rate of total shoulder replacement. However, the Poisson multivariate analysis, which simultaneously adjusted for gender, age, population density, and workforce specialization, did not confirm these findings. Generally, we believe that the Poisson analysis more closely reflects reality in that it adjusts for a wider range of possibly confounding variables. Furthermore, the Pearson analysis does not weight observations according to sample size as the Poisson regression does; thus, it is more subject to the effect of large outliers. Our interpretation of the Poisson regression analysis is that there is no real relationship between the availability of physicians at any level of specialization and total shoulder replacement, after adjusting for a wider range of factors, such as population density, age, gender, and all of the physician densities. Instead, we found a weak negative relationship (relative risk = 0.91) between the density of orthopaedic surgeons and the rate of humeral head replacement as well as a stronger positive relationship (relative risk = 1.97) between the density of primary-care physicians and the rate of rotator cuff repair (Table V). Because these relationships are not detected with use of the Pearson model, are small in magnitude and barely reach the level of significance with use of the Poisson model, and are somewhat counterintuitive, their true importance, if any, is unclear. Our data suggest that there is little or no correlation between the density of either general orthopaedic surgeons or shoulder specialists and the rates of these procedures.

Our results highlight some important points about variations among rates of procedures and their relationship to population and workforce variables. However, limitations of this study leave room for future investigations in these areas. First, use of only MEDPAR data limited our study to an older, Medicare population. Total shoulder replacement and humeral head replacement usually are performed in these age-groups, but rotator cuff tears often occur in a younger population. In addition, lifestyles and practice styles may vary in such a way that, in some states, patients may seek and receive treatment earlier (that is, before the age of sixty-five years old), whereas in other states, a systematic delay before treatment is sought may cause more patients to be counted as part of the Medicare population. These limitations can be addressed in future studies that include data on a wider range of age-groups.

A second limitation of the current study is that shoulder specialists were accounted for with use of a proxy measure (subscription to the Journal of Shoulder and Elbow Surgery). Although this measure correlated strongly with the locations of members of the American Shoulder and Elbow Surgeons, not all physicians who consider themselves specialists in this area may have been included with use of this measure. Small differences in the density of shoulder specialists may have a major effect on our findings. A more direct measure of actual and self-described specialists in each state should be developed for use in future studies.

Moreover, because of the available data, we used the state as the basic unit of analysis. Patients may cross state borders to obtain care, which introduces some error into the analysis. Our analysis did not account for this factor. This problem can be largely avoided by use of a hospital service area as the unit of analysis, as was done by Wennberg et al.²⁷ and other investigators¹¹, in numerous population-based studies.

Finally, although we examined several important variables, many are left for future investigators to explore. The effects of payer mix, race, socioeconomic status (including occupational and lifestyle preferences), and surgical training are only some of the other factors that may contribute to variations in the rates of these operative procedures.

In summary, we documented significant geographic variations in the rates of common shoulder procedures. In contrast to previous investigators, we failed to find a significant relationship between the availability of surgeons and the rates of these procedures; however, we found a strong negative relationship between the density of a given state population and the rates of operative procedures performed in that state.

Variations in the utilization of health care have been well described for numerous areas of clinical intervention. These variations clearly have a profound effect on health-care costs and, more importantly, on the outcomes for patients, who often take some risk to achieve some apparent benefit. Patients who have an orthopaedic procedure take risks related to anesthesia and to the operation itself in order to obtain an improvement in functional status and quality of life. Technological innovations in orthopaedics have provided new opportunities for improving the quality of life of our aging population, but there is evidence that intervention may not be appropriately distributed. If the rates of shoulder procedures vary by as much as tenfold, as the current study suggests that they do, it is likely that we are either providing too little or too much intervention, or perhaps both.

Although research based on a large database can reveal variations in the utilization of operative procedures, it cannot help to determine which rate is appropriate. The answer obviously depends on the prevalence of disease, patient preference, and the indications for operative intervention. Our findings suggest important areas that warrant additional research. First, we need to understand whether variations in the rates of shoulder procedures are indeed occupationally driven and whether these variations are the result of differences in the prevalence of disease or in patient preference, or both. Second, our finding of a particularly high variation in the rates of total shoulder replacement and rotator cuff repair suggests that additional high-quality clinical research is needed to determine the appropriate indications for operative intervention as well as the benefits, risks, and costs of different types of operative intervention. There is clearly a need for more clinical research to determine the effectiveness and appropriateness of these commonly performed procedures. Database review is a powerful tool that can help to determine how such research should be focused.

References

Introduction | Materials and Methods | Results | Discussion | References

Cherkin, D. C.; Deyo, R. A.; Loeser, J. D.; Bush, T.; and Waddell, G.: An international comparison of back surgery rates. Spine,19: 1201-1206, 1994.191201 1994 [PubMed]

Detsky, A. S.: Regional variation in medical care. New England J. Med.,333: 589-590, 1995.333589 1995

Diehr, P.; Cain, K. C.; Kreuter, W.; and Rosenkranz, S.: Can small-area analysis detect variation in surgery rates? The power of small-area variation analysis. Med. Care,30: 484-502, 1992.30484 1992 [PubMed]

Einstadter, D.; Kent, D. L.; Fihn, S. D.; and Deyo, R. A.: Variation in the rate of cervical spine surgery in Washington State. Med. Care,31: 711-718, 1993.31711 1993 [PubMed]

Fisher, E. S.; Welch, H. G.; and Wennberg, J. E.: Prioritizing Oregon's hospital resources. An example based on variations in discretionary medical utilization. J. Am. Med. Assn.,267: 1925-1931, 1992.2671925 1992

Fisher, E. S.; Wennberg, J. E.; Stukel, T. A.; and Sharp, S. M.: Hospital readmission rates for cohorts of Medicare beneficiaries in Boston and New Haven. New England J. Med.,331: 989-995, 1994.331989 1994

Gittelsohn, A., and Powe, N. R.: Small area variations in health care delivery in Maryland. Health Services Res.,30: 295-317, 1995.30295 1995

Guadagnoli, E.; Hauptman, P. J.; Ayanian, J. Z.; Pashos, C. L.; McNeil, B. J.; and Cleary, P. D.: Variation in the use of cardiac procedures after acute myocardial infarction. New England J. Med.,333: 573-578, 1995.333573 1995

Hannan, E. L.; Siu, A. L.; Kumar, D.; Kilburn, H., Jr.; and Chassin, M. R.: The decline in coronary artery bypass graft surgery mortality in New York State. The role of surgeon volume. J. Am. Med. Assn.,273: 209-213, 1990.273209 1990

Hinton, R. Y.; Lennox, D. W.; Ebert, F. R.; Jacobsen, S. J.; and Smith, G. S.: Relative rates of fracture of the hip in the United States. Geographic, sex, and age variations. J. Bone and Joint Surg.,77-A: 695-702, May 1995.77-A695 1995

Keller, R. B.; Soule, D. N.; Wennberg, J. E.; and Hanley, D. F.: Dealing with geographic variations in the use of hospitals. The experience of the Maine Medical Assessment Foundation Orthopaedic Study Group. J. Bone and Joint Surg.,72-A: 1286-1293, Oct. 1990.72-A1286 1990

Keskimäki, I.; Aro, S.; and Teperi, J.: Regional variation in surgical procedure rates in Finland. Scandinavian J. Soc. Med.,22: 132-138, 1994.22132 1994

Kimmel, S. E.; Berlin, J. A.; and Laskey, W. K.: The relationship between coronary angioplasty procedure volume and major complications. J. Am. Med. Assn.,274: 1137-1142, 1995.2741137 1995

Liang, K., and Zeger, S. L.: Longitudinal data analysis using generalized linear models. Biometrika,73: 13-22, 1986.7313 1986

Loeser, J. D.; Van Konkelenberg, R.; Volinn, E.; and Cousins, M. J.: Small area analysis of lumbar spine surgery in South Australia. Australian and New Zealand J. Surg.,63: 14-19, 1993.6314 1993

McPherson, K.; Strong, P. M.; Epstein, A.; and Jones, L.: Regional variations in the use of common surgical procedures: within and between England and Wales, Canada, and the United States of America. Soc. Sci. and Med.,15A: 273-288, 1981.15A273 1981

McPherson, K.; Wennberg, J. E.; Hovind, O. B.; and Clifford, P.: Small-area variations in the use of common surgical procedures: an international comparison of New England, England, and Norway. New England J. Med.,307: 1310-1314, 1982.3071310 1982

Nilasena, D. S.; Vaughn, R. J.; Mori, M.; and Lyon, J. L.: Surgical trends in the treatment of diseases of the lumbar spine in Utah's Medicare population, 1984 to 1990. Med. Care,33: 585-597, 1995.33585 1995 [PubMed]

Peterson, M. G. E.; Hollenberg, J. P.; Szatrowski, T. P.; Johanson, N. A.; Mancuso, C. A.; and Charlson, M. E.: Geographic variations in the rates of elective total hip and knee arthroplasties among Medicare beneficiaries in the United States. J. Bone and Joint Surg.,74-A: 1530-1539, Dec. 1992.74-A1530 1992

Physician Characteristics and Distribution in the United States, 1993 Edition, pp. 8-42. Department of Physician Data Services, Division of Survey and Data Resources, American Medical Association, 1992.

Pilote, L.; Calif, R. M.; Sapp, S.; Miller, D. P.; Mark, D. B.; Weaver, W. D.; Gore, J. M.; Armstrong, P. W.; Ohman, E. M.; and Topol, E. J.: Regional variation across the United States in the management of acute myocardial infarction. New England J. Med.,333: 565-572, 1995.333565 1995

Roos, L. L., and Roos, N. P.: Using large data bases for research on surgery. In Socioeconomics of Surgery, pp. 259-275. Edited by I. M. Rutkow. St. Louis, C. V. Mosby, 1989.

Roos, N. P.; Wennberg, J. E.; and McPherson, K.: Using diagnosis-related groups for studying variations in hospital admissions. Health Care Financ. Rev.,9: 53-62, 1988.953 1988 [PubMed]

Statistical Abstract of the United States, 1993: The National Data Book. United States Department of Commerce, Economics and Statistics Administration, Bureau of the Census. Washington, D.C., United States Government Printing Office, 1994.

Stroup, N. E.; Freni-Titulaer, L. W. J.; and Schwartz, J. J.: Unexpected geographic variation in rates of hospitalization for patients who have fracture of the hip. Medicare enrollees in the United States. J. Bone and Joint Surg.,72-A: 1294-1298, Oct. 1990.72-A1294 1990

Wennberg, J. E.; McPherson, K.; and Caper, P.: Will payment based on diagnosis-related groups control hospital costs?. New England J. Med.,311: 295-300, 1984.311295 1984

Wennberg, J. E.; Freeman, J. L.; Shelton, R. M.; and Bubolz, T. A.: Hospital use and mortality among Medicare beneficiaries in Boston and New Haven. New England J. Med.,321: 1168-1173, 1989.3211168 1989

Williams, M. H.; Newton, J. N.; Frankel, S. J.; Braddon, F.; Barclay, E.; and Gray, J. A.: Prevalence of total hip replacement: how much demand has been met?. J. Epidemiol. and Commun. Health,48: 188-191, 1994.48188 1994

Topics

View Larger

*The rates are given per 100,000 Medicare beneficiaries.

State	Total Shoulder Replacement		Humeral Head Replacement		Rotator Cuff Repair
Rate	No. of Procedures	Rate	No. of Procedures	Rate	No. of Procedures
Alabama	12.35	77	7.85	45	25.16	152
Alaska	15.87	4	13.92	4	21.13	8
Arizona	13.14	75	13.10	72	30.36	177
Arkansas	11.35	42	11.01	40	26.09	103
California	8.76	300	10.52	357	29.09	1028
Colorado	19.21	72	11.75	44	51.72	223
Connecticut	3.25	17	9.57	45	28.49	139
Delaware	7.84	7	5.53	6	33.27	31
District of Columbia	2.47	2	4.36	3	24.15	20
Florida	10.91	281	10.51	263	23.02	593
Georgia	10.44	77	9.40	75	26.28	216
Hawaii	2.81	5	4.83	7	19.63	30
Idaho	25.60	35	12.00	17	64.92	93
Illinois	8.04	124	8.97	134	22.66	352
Indiana	10.99	86	7.53	60	24.61	204
Iowa	14.22	64	12.86	60	51.09	228
Kansas	17.62	68	10.65	40	44.16	160
Kentucky	6.91	44	4.60	27	21.97	115
Louisiana	9.82	52	10.45	56	21.06	117
Maine	12.21	26	10.40	20	33.70	65
Maryland	7.64	45	6.97	39	31.95	185
Massachusetts	5.36	49	10.12	89	26.79	241
Michigan	10.52	134	10.35	130	26.73	344
Minnesota	12.63	78	11.13	73	40.95	234
Mississippi	11.24	40	9.40	36	9.41	36
Missouri	9.75	78	10.19	80	30.14	243
Montana	16.88	21	15.98	20	55.31	66
Nebraska	14.97	35	14.63	37	54.28	127
Nevada	10.39	18	7.12	13	31.07	57
New Hampshire	11.04	17	8.76	13	32.96	52
New Jersey	4.92	59	7.41	80	20.01	219
New Mexico	9.38	21	12.42	24	21.46	46
New York	5.97	156	8.39	208	13.81	351
North Carolina	9.46	98	8.47	79	24.29	245
North Dakota	17.57	16	17.48	18	85.52	86
Ohio	11.12	178	10.64	162	23.94	392
Oklahoma	11.72	51	7.47	31	20.26	90
Oregon	17.43	78	10.22	44	43.45	200
Pennsylvania	7.84	166	11.01	226	25.78	518
Rhode Island	12.84	19	7.35	13	27.90	44
South Carolina	8.49	41	9.16	42	19.48	104
South Dakota	8.84	10	13.89	15	59.65	64
Tennessee	8.20	62	9.21	67	17.09	130
Texas	10.49	202	9.23	180	23.52	472
Utah	19.57	32	12.27	21	63.49	110
Vermont	12.66	9	15.51	12	33.66	28
Virginia	15.04	114	8.48	66	35.84	282
Washington	16.99	114	15.98	104	64.10	414
West Virginia	6.96	23	12.48	36	11.95	39
Wisconsin	8.59	62	11.37	83	50.11	343
Wyoming	23.33	13	3.90	4	40.93	25

Add to My JBJS

*The rates are given per 100,000 Medicare beneficiaries.

State	Total Shoulder Replacement		Humeral Head Replacement		Rotator Cuff Repair
Rate	No. of Procedures	Rate	No. of Procedures	Rate	No. of Procedures
Alabama	12.35	77	7.85	45	25.16	152
Alaska	15.87	4	13.92	4	21.13	8
Arizona	13.14	75	13.10	72	30.36	177
Arkansas	11.35	42	11.01	40	26.09	103
California	8.76	300	10.52	357	29.09	1028
Colorado	19.21	72	11.75	44	51.72	223
Connecticut	3.25	17	9.57	45	28.49	139
Delaware	7.84	7	5.53	6	33.27	31
District of Columbia	2.47	2	4.36	3	24.15	20
Florida	10.91	281	10.51	263	23.02	593
Georgia	10.44	77	9.40	75	26.28	216
Hawaii	2.81	5	4.83	7	19.63	30
Idaho	25.60	35	12.00	17	64.92	93
Illinois	8.04	124	8.97	134	22.66	352
Indiana	10.99	86	7.53	60	24.61	204
Iowa	14.22	64	12.86	60	51.09	228
Kansas	17.62	68	10.65	40	44.16	160
Kentucky	6.91	44	4.60	27	21.97	115
Louisiana	9.82	52	10.45	56	21.06	117
Maine	12.21	26	10.40	20	33.70	65
Maryland	7.64	45	6.97	39	31.95	185
Massachusetts	5.36	49	10.12	89	26.79	241
Michigan	10.52	134	10.35	130	26.73	344
Minnesota	12.63	78	11.13	73	40.95	234
Mississippi	11.24	40	9.40	36	9.41	36
Missouri	9.75	78	10.19	80	30.14	243
Montana	16.88	21	15.98	20	55.31	66
Nebraska	14.97	35	14.63	37	54.28	127
Nevada	10.39	18	7.12	13	31.07	57
New Hampshire	11.04	17	8.76	13	32.96	52
New Jersey	4.92	59	7.41	80	20.01	219
New Mexico	9.38	21	12.42	24	21.46	46
New York	5.97	156	8.39	208	13.81	351
North Carolina	9.46	98	8.47	79	24.29	245
North Dakota	17.57	16	17.48	18	85.52	86
Ohio	11.12	178	10.64	162	23.94	392
Oklahoma	11.72	51	7.47	31	20.26	90
Oregon	17.43	78	10.22	44	43.45	200
Pennsylvania	7.84	166	11.01	226	25.78	518
Rhode Island	12.84	19	7.35	13	27.90	44
South Carolina	8.49	41	9.16	42	19.48	104
South Dakota	8.84	10	13.89	15	59.65	64
Tennessee	8.20	62	9.21	67	17.09	130
Texas	10.49	202	9.23	180	23.52	472
Utah	19.57	32	12.27	21	63.49	110
Vermont	12.66	9	15.51	12	33.66	28
Virginia	15.04	114	8.48	66	35.84	282
Washington	16.99	114	15.98	104	64.10	414
West Virginia	6.96	23	12.48	36	11.95	39
Wisconsin	8.59	62	11.37	83	50.11	343
Wyoming	23.33	13	3.90	4	40.93	25

View Larger

TABLE II MEASURES OF VARIATIONS FOR THE RATES OF TOTAL SHOULDER REPLACEMENT, HUMERAL HEAD REPLACEMENT, AND ROTATOR CUFF REPAIR

Procedure	Coefficient of Variation	High:Low Ratio	Systematic Component of Variation (Age-Adjusted)
Rotator cuff repair	0.477	9.09	0.342
Total shoulder replacement	0.427	10.36	0.203
Humeral head replacement	0.301	4.48	0.045

Add to My JBJS

TABLE II MEASURES OF VARIATIONS FOR THE RATES OF TOTAL SHOULDER REPLACEMENT, HUMERAL HEAD REPLACEMENT, AND ROTATOR CUFF REPAIR

Procedure	Coefficient of Variation	High:Low Ratio	Systematic Component of Variation (Age-Adjusted)
Rotator cuff repair	0.477	9.09	0.342
Total shoulder replacement	0.427	10.36	0.203
Humeral head replacement	0.301	4.48	0.045

View Larger

TABLE III POPULATION AND WORKFORCE DENSITIES ACCORDING TO STATE

State	Population Density* (no. of people per sq. mile)	State Workforce-Availability Densities (no. of physicians per 1000 Medicare beneficiaries)
All Physicians	Primary-Care Physicians	Orthopaedic Surgeons	Shoulder Specialists
Alabama	81.5	12.25	3.50	0.33	0.028
Alaska	1.0	28.46	11.00	1.64	0.107
Arizona	33.7	16.27	3.75	0.41	0.047
Arkansas	46.1	10.45	3.21	0.31	0.025
California	197.9	23.95	5.57	0.55	0.049
Colorado	33.5	21.33	5.60	0.68	0.089
Connecticut	677.2	23.37	5.24	0.49	0.041
Delaware	352.5	16.66	9.11	0.46	0.032
District of Columbia	9649.5	53.44	4.86	0.65	0.064
Florida	249.8	13.81	2.92	0.32	0.029
Georgia	116.6	16.67	4.22	0.48	0.047
Hawaii	180.5	22.27	5.60	0.41	0.058
Idaho	12.9	11.19	3.59	0.51	0.022
Illinois	209.2	18.03	5.08	0.35	0.039
Indiana	157.8	12.83	3.74	0.33	0.037
Iowa	50.3	10.47	3.01	0.29	0.030
Kansas	30.8	13.56	3.99	0.29	0.027
Kentucky	94.5	12.93	3.53	0.31	0.025
Louisiana	98.4	16.44	3.69	0.40	0.027
Maine	40.0	14.02	3.80	0.41	0.063
Maryland	502.1	31.65	7.13	0.58	0.048
Massachusetts	765.3	25.33	5.74	0.45	0.050
Michigan	166.1	15.38	3.85	0.26	0.032
Minnesota	56.3	18.58	5.75	0.43	0.051
Mississippi	55.7	10.17	2.88	0.25	0.021
Missouri	75.4	14.24	3.33	0.34	0.022
Montana	5.7	12.57	3.57	0.54	0.041
Nebraska	20.9	13.16	4.09	0.34	0.049
Nevada	12.1	13.31	3.57	0.43	0.050
New Hampshire	123.8	18.10	4.28	0.55	0.034
New Jersey	1049.9	19.45	4.73	0.39	0.042
New Mexico	13.0	17.40	4.63	0.45	0.036
New York	383.7	25.23	6.00	0.36	0.040
North Carolina	140.5	15.52	3.84	0.41	0.037
North Dakota	9.2	12.48	4.44	0.30	0.020
Ohio	269.0	15.41	3.80	0.05	0.031
Oklahoma	46.8	11.29	3.13	0.30	0.032
Oregon	31.0	15.98	4.24	0.48	0.050
Pennsylvania	267.9	16.26	3.96	0.32	0.038
Rhode Island	961.8	17.84	4.43	0.45	0.049
South Carolina	119.7	14.29	3.96	0.38	0.038
South Dakota	9.4	10.48	4.06	0.36	0.062
Tennessee	121.9	15.50	3.97	0.41	0.026
Texas	67.4	17.57	4.25	0.45	0.043
Utah	221.0	21.51	4.94	0.67	0.094
Vermont	61.6	21.88	5.63	0.53	0.064
Virginia	161.0	19.24	4.96	0.52	0.035
Washington	77.1	19.30	5.32	0.58	0.043
West Virginia	75.2	11.06	3.22	0.21	0.022
Wisconsin	92.2	14.54	4.09	0.41	0.037
Wyoming	4.8	13.35	4.82	0.62	0.618

Add to My JBJS

TABLE III POPULATION AND WORKFORCE DENSITIES ACCORDING TO STATE

State	Population Density* (no. of people per sq. mile)	State Workforce-Availability Densities (no. of physicians per 1000 Medicare beneficiaries)
All Physicians	Primary-Care Physicians	Orthopaedic Surgeons	Shoulder Specialists
Alabama	81.5	12.25	3.50	0.33	0.028
Alaska	1.0	28.46	11.00	1.64	0.107
Arizona	33.7	16.27	3.75	0.41	0.047
Arkansas	46.1	10.45	3.21	0.31	0.025
California	197.9	23.95	5.57	0.55	0.049
Colorado	33.5	21.33	5.60	0.68	0.089
Connecticut	677.2	23.37	5.24	0.49	0.041
Delaware	352.5	16.66	9.11	0.46	0.032
District of Columbia	9649.5	53.44	4.86	0.65	0.064
Florida	249.8	13.81	2.92	0.32	0.029
Georgia	116.6	16.67	4.22	0.48	0.047
Hawaii	180.5	22.27	5.60	0.41	0.058
Idaho	12.9	11.19	3.59	0.51	0.022
Illinois	209.2	18.03	5.08	0.35	0.039
Indiana	157.8	12.83	3.74	0.33	0.037
Iowa	50.3	10.47	3.01	0.29	0.030
Kansas	30.8	13.56	3.99	0.29	0.027
Kentucky	94.5	12.93	3.53	0.31	0.025
Louisiana	98.4	16.44	3.69	0.40	0.027
Maine	40.0	14.02	3.80	0.41	0.063
Maryland	502.1	31.65	7.13	0.58	0.048
Massachusetts	765.3	25.33	5.74	0.45	0.050
Michigan	166.1	15.38	3.85	0.26	0.032
Minnesota	56.3	18.58	5.75	0.43	0.051
Mississippi	55.7	10.17	2.88	0.25	0.021
Missouri	75.4	14.24	3.33	0.34	0.022
Montana	5.7	12.57	3.57	0.54	0.041
Nebraska	20.9	13.16	4.09	0.34	0.049
Nevada	12.1	13.31	3.57	0.43	0.050
New Hampshire	123.8	18.10	4.28	0.55	0.034
New Jersey	1049.9	19.45	4.73	0.39	0.042
New Mexico	13.0	17.40	4.63	0.45	0.036
New York	383.7	25.23	6.00	0.36	0.040
North Carolina	140.5	15.52	3.84	0.41	0.037
North Dakota	9.2	12.48	4.44	0.30	0.020
Ohio	269.0	15.41	3.80	0.05	0.031
Oklahoma	46.8	11.29	3.13	0.30	0.032
Oregon	31.0	15.98	4.24	0.48	0.050
Pennsylvania	267.9	16.26	3.96	0.32	0.038
Rhode Island	961.8	17.84	4.43	0.45	0.049
South Carolina	119.7	14.29	3.96	0.38	0.038
South Dakota	9.4	10.48	4.06	0.36	0.062
Tennessee	121.9	15.50	3.97	0.41	0.026
Texas	67.4	17.57	4.25	0.45	0.043
Utah	221.0	21.51	4.94	0.67	0.094
Vermont	61.6	21.88	5.63	0.53	0.064
Virginia	161.0	19.24	4.96	0.52	0.035
Washington	77.1	19.30	5.32	0.58	0.043
West Virginia	75.2	11.06	3.22	0.21	0.022
Wisconsin	92.2	14.54	4.09	0.41	0.037
Wyoming	4.8	13.35	4.82	0.62	0.618

View Larger

TABLE IV CORRELATION COEFFICIENTS AND SIGNIFICANCE VALUES FOR TOTAL SHOULDER REPLACEMENT, HUMERAL HEAD REPLACEMENT, AND ROTATOR CUFF REPAIR*

*Population density correlations are Spearman rank values. Physician correlation values represent partial correlations, controlling for population density. †Indicates significance at p = 0.05.

Variable	Total Shoulder Replacement		Humeral Head Replacement		Rotator Cuff Repair
Coefficient	P Value	Coefficient	P Value	Coefficient	P Value
Population density	-0.63	<0.001†	-0.38	0.006†	-0.50	<0.001†
Physician density	-0.16	0.28	0.001	0.99	-0.10	0.49
Primary-care-physician density	-0.03	0.82	-0.02	0.91	0.005	0.97
Orthopaedic-surgeon density	0.31	0.03†	0.15	0.29	0.11	0.42
Shoulder-specialist density	0.28	0.05†	0.11	0.43	0.19	0.19

Add to My JBJS

TABLE IV CORRELATION COEFFICIENTS AND SIGNIFICANCE VALUES FOR TOTAL SHOULDER REPLACEMENT, HUMERAL HEAD REPLACEMENT, AND ROTATOR CUFF REPAIR*

*Population density correlations are Spearman rank values. Physician correlation values represent partial correlations, controlling for population density. †Indicates significance at p = 0.05.

Variable	Total Shoulder Replacement		Humeral Head Replacement		Rotator Cuff Repair
Coefficient	P Value	Coefficient	P Value	Coefficient	P Value
Population density	-0.63	<0.001†	-0.38	0.006†	-0.50	<0.001†
Physician density	-0.16	0.28	0.001	0.99	-0.10	0.49
Primary-care-physician density	-0.03	0.82	-0.02	0.91	0.005	0.97
Orthopaedic-surgeon density	0.31	0.03†	0.15	0.29	0.11	0.42
Shoulder-specialist density	0.28	0.05†	0.11	0.43	0.19	0.19

View Larger

TABLE V RELATIVE RISKS AND CONFIDENCE INTERVALS FOR TOTAL SHOULDER REPLACEMENT, HUMERAL HEAD REPLACEMENT, AND ROTATOR CUFF REPAIR, ACCORDING TO POISSON REGRESSION ESTIMATES*

Variable	Total Shoulder Replacement		Humeral Head Replacement		Rotator Cuff Repair
Relative Risk	95 Percent Confidence Interval	Relative Risk	95 Percent Confidence Interval	Relative Risk	95 Percent Confidence Interval
Gender (male:female)	1.70	0.58—4.95	2.40†	1.39—4.14	5.07†	1.81—14.25
Population density	0.81†	0.74—0.89	0.93†	0.87—0.98	0.94	0.84—1.04
Physician density	0.87	0.50—1.52	1.17	0.78—1.76	0.48	0.22—1.02
Primary-care-physician density	0.96	0.55—1.67	0.90	0.61—1.33	1.97†	1.03—3.77
Orthopaedic-surgeon density	0.89	0.76—1.04	0.91†	0.87—0.95	1.06	0.84—1.34
Shoulder-specialist density	1.13	0.79—1.61	1.06	0.87—1.29	1.29	0.80—2.07
Age-group
70—74 yrs.	1.33†	1.16—1.52	1.44†	1.30—1.60	1.03	0.94—1.14
75—79 yrs.	1.67†	1.30—2.14	1.90†	1.60—2.25	1.02	0.80—1.30
80—84 yrs.	1.45	0.90—2.33	2.46†	1.87—3.24	0.71	0.45—1.11
=85 yrs.	0.97	0.40—2.38	2.54†	1.64—3.94	0.35†	0.15—0.84

Add to My JBJS

TABLE V RELATIVE RISKS AND CONFIDENCE INTERVALS FOR TOTAL SHOULDER REPLACEMENT, HUMERAL HEAD REPLACEMENT, AND ROTATOR CUFF REPAIR, ACCORDING TO POISSON REGRESSION ESTIMATES*

Variable	Total Shoulder Replacement		Humeral Head Replacement		Rotator Cuff Repair
Relative Risk	95 Percent Confidence Interval	Relative Risk	95 Percent Confidence Interval	Relative Risk	95 Percent Confidence Interval
Gender (male:female)	1.70	0.58—4.95	2.40†	1.39—4.14	5.07†	1.81—14.25
Population density	0.81†	0.74—0.89	0.93†	0.87—0.98	0.94	0.84—1.04
Physician density	0.87	0.50—1.52	1.17	0.78—1.76	0.48	0.22—1.02
Primary-care-physician density	0.96	0.55—1.67	0.90	0.61—1.33	1.97†	1.03—3.77
Orthopaedic-surgeon density	0.89	0.76—1.04	0.91†	0.87—0.95	1.06	0.84—1.34
Shoulder-specialist density	1.13	0.79—1.61	1.06	0.87—1.29	1.29	0.80—2.07
Age-group
70—74 yrs.	1.33†	1.16—1.52	1.44†	1.30—1.60	1.03	0.94—1.14
75—79 yrs.	1.67†	1.30—2.14	1.90†	1.60—2.25	1.02	0.80—1.30
80—84 yrs.	1.45	0.90—2.33	2.46†	1.87—3.24	0.71	0.45—1.11
=85 yrs.	0.97	0.40—2.38	2.54†	1.64—3.94	0.35†	0.15—0.84