Professional uncertainty and the problem of supplier-induced demand

Wennberg, John E.; Barnes, Benjamin A.; Zubkoff, Michael

doi:10.1016/0277-9536(82)90234-9

Cited by 513 publications

(218 citation statements)

References 19 publications

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“…Nevertheless, the observed increase supports the important idea that discrete physician-level decisions, in this case, whether to perform a bedside procedure, may be affected by broader system-wide adoptions of new technologies like our bedside procedure service. 12 Other nonclinical factors not observed in our study, such as fee-for-service compensation and variable physician-level diagnostic and therapeutic thresholds, may also affect the rate of bedside procedures.…”

Section: Impact Of a Bedside Procedures Service / Lucas Et Almentioning

confidence: 63%

“…Our findings suggest that although patients' clinical circumstances are likely the most important consideration, nonclinical factors may also affect physicians' decisions. 12 Like other multifaceted decision-making processes of physicians, 15 the complexity of this decision is important to examine because, as our pilot data suggest, a procedure service may not lead to more successful procedure attempts or reductions in the number of major complications. Although the cumulative expertise of our service or the innovative methods of training of other institutions may improve the performance of bedside procedures, 5,13 physicians' decisions about whether to order them will remain paramount, because any improvement in procedural competence will do little to reduce the relative danger of unnecessary procedures 16 or the missed benefit of procedures left undone.…”

Section: Impact Of a Bedside Procedures Service / Lucas Et Almentioning

confidence: 99%

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Impact of a bedside procedure service on general medicine inpatients: A firm‐based trial

Lucas

Asbury

Wang

et al. 2007

Journal of Hospital Medicine

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Section: Impact Of a Bedside Procedures Service / Lucas Et Almentioning

confidence: 63%

Section: Impact Of a Bedside Procedures Service / Lucas Et Almentioning

confidence: 99%

Impact of a bedside procedure service on general medicine inpatients: A firm‐based trial

Lucas

Asbury

Wang

et al. 2007

Journal of Hospital Medicine

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“…Therefore, some of the variation in treatment may, in fact, be appropriate due to patients underlying health status rather than inequalities in care. These limitations notwithstanding, the study design draws upon established small area variation analysis methods described by Wennberg et al 27,28 and remain valid today.…”

Section: Discussionmentioning

confidence: 99%

Variation in prostate cancer treatment associated with population density of the county of residence

Cary

Odisho

Cooperberg

2016

Prostate Cancer Prostatic Dis

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BACKGROUND: We sought to assess variation in the primary treatment of prostate cancer by examining the effect of population density of the county of residence on treatment for clinically localized prostate cancer and quantify variation in primary treatment attributable to the county and state level. METHODS: A total 138 226 men with clinically localized prostate cancer in the Surveillance, Epidemiology and End Result (SEER) database in 2005 through 2008 were analyzed. The main association of interest was between prostate cancer treatment and population density using multilevel hierarchical logit models while accounting for the random effects of counties nested within SEER regions. To quantify the effect of county and SEER region on individual treatment, the percent of total variance in treatment attributable to county of residence and SEER site was estimated with residual intraclass correlation coefficients. RESULTS: Men with localized prostate cancer in metropolitan counties had 23% higher odds of being treated with surgery or radiation compared with men in rural counties, controlling for number of urologists per county as well as clinical and sociodemographic characteristics. Three percent (95% confidence interval (CI): 1.2-6.2%) of the total variation in treatment was attributable to SEER site, while 6% (95% CI: 4.3-9.0%) of variation was attributable to county of residence, adjusting for clinical and sociodemographic characteristics. CONCLUSIONS: Variation in treatment for localized prostate cancer exists for men living in different population-dense counties of the country. These findings highlight the importance of comparative effectiveness research to improve understanding of this variation and lead to a reduction in unwarranted variation.

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“…Some of the variation is due to randomness.43 Finally, some of the discrepancies are probably associated with variations in practice style. 44 Medicare spending per enrollee by state is driven to some degree by total per capita health care expenditures by state. We did not include a variable for this for the simple reason that specific information was not available on per capita expenditures for the fee-for-service sector by state for 1992.…”

Section: Patterns Ofexpenditures Among Statesmentioning

confidence: 99%

State variations in Medicare expenditures.

Kane¹,

Friedman

1997

Am J Public Health

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OBJECTIVES: This study examined variations in Medicare expenditures across states. METHODS: 1992 data on average Medicare expenditures per enrollee, users of services per 1000 enrollees, service use per user, and payment per unit of service were compared across states for various services. Weighted least squares regression analysis was employed to examine total Medicare expenditures per enrollee by state. RESULTS: Variation in Medicare expenditures across states is driven more by average number of service users per 1000 enrollees and average service units per user than by average payment per service unit. Medicare expenditures per enrollee by state are primarily a function of Medicare HMO penetration rate (P = .000), urban area (P = .001), hospital bed supply (P = .005), elderly mortality rate (P = .012), Medicare physician assignment rate (P = .026), percentage of primary care practitioners (P = .042), and interactions between urban elderly and percentage of primary care physicians (P = .005) and Black elderly and nursing home bed supply (P = .012). CONCLUSIONS: Before sweeping Medicare cuts are undertaken or excessive reliance on managed care occurs, attention should be focused on the current disproportionate distribution of expenditures across states.

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Professional uncertainty and the problem of supplier-induced demand

Cited by 513 publications

References 19 publications

Impact of a bedside procedure service on general medicine inpatients: A firm‐based trial

Impact of a bedside procedure service on general medicine inpatients: A firm‐based trial

Variation in prostate cancer treatment associated with population density of the county of residence

State variations in Medicare expenditures.

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