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Although Americans pay much more for a day in the hospital than Canadians, we know little about whether inpatient physician practice patterns might explain some of this difference. The authors compared the utilization of all diagnostic imaging (plain radiographs, computed tomography (CT) and magnetic resonance imaging (MRI) scanning, ultrasound, nuclear medicine and vascular studies) and selected laboratory tests (hematology, basic biochemistry, and advanced biochemistry) for all patients discharged with selected medical and surgical diagnoses in 1990 and 1991 from four university hospitals and four community hospitals in Canada (n = 6,491) and the United States (n = 7,980). Overall, US medical patients received 22% more diagnostic tests than their Canadian counterparts (544.2 relative value units [RVUs] vs. 446.5 RVUs in Canada, P < 0.001), which was mainly the result of higher radiology use. Although mean radiology use was 40% higher in the United States (370.0 vs. 264.5 RVUs in Canada, P < 0.05), there was little difference in the use of laboratory tests between countries (174.2 vs. 182.4 RVUs in Canada, P = 0.3). Within radiology, only CT and MRI use differed significantly between countries (US patients received 119% more tests than Canadians). These findings were consistent after adjustments for age, gender, diagnosis-related group, and university status. Differences in test use between countries were mainly the result of more testing among the US elderly than counterparts in Canada. Among surgical patients, there was little difference between countries for radiology (76.3 vs. 67.3 RVUs in Canada, P < 0.05) and laboratory (83.6 vs. 91.4 RVUs in Canada, P < 0.05). Comparable inpatients admitted to US hospitals received more diagnostic tests than their Canadian counterparts even in hospitals with similar availability of technology. Differences between countries were larger for high-cost tests than for lower-cost tests. Much of the difference in test use is explained by more intensive use for the elderly in the United States.

Prospective payment has created incentives for hospitals to identify physicians who are responsible for high or excessive rates of resource use. However, at teaching hospitals it is unclear whether individual attending or resident physicians account for a substantial portion of the observed variations in hospital resource use. To explore this issue, case-mix adjusted hospital length of stay and ancillary resource use at a university teaching hospital for 7,667 consecutive discharges on general medicine wards and 7,566 discharges on medical subspecialty wards were evaluated. After controlling for case mix and patient characteristics (patients' age, sex, marital status, insurance status, and ward service), only 2% of the length of stay variance (log transformed) was attributable to the attending physician on general medicine wards (P = 0.06) and 1% on subspecialty medicine wards (P < 0.01). For total ancillary resource use, about 2% of the variance was attributable to general medicine and subspecialty ward attendings. Similar associations were found for resident physicians, although the overlap of attending and resident physicians' month-long rotations prevented critical appraisal of their independent contributions to resource use. Furthermore, labeling attending physicians as high or low hospital resource utilizers based on data from one month of attending duty (mean admissions = 33 +/- 7) would be scarcely better than randomly classifying them (kappas ranged from -0.05 for length of stay on subspecialty services to 0.18 for pharmacy use on general medicine services). In conclusion, in this university teaching hospital, attendings and residents account or a small, although statistically significant, amount of the variation in hospital resource use. It would be impractical for the hospital to reliably profile the resource use intensity of individual physicians.

In this study we used information from discharge abstracts to develop three different risk-adjusted measures of hospital performance: a Risk-Adjusted Mortality Index, a Risk-Adjusted Readmissions Index, and a Risk-Adjusted Complications Index. The adjustments have face validity, and appear to account for much of the variation across hospitals in the rates of these adverse events. The indexes are stable over time, and are not biased with respect to hospital size, ownership, or teaching status. All three indexes appear to have construct validity when tested against the changes in hospital care that occurred when PPS was introduced.

The study purpose was to increase mammography screening among older women by identifying female Medicare beneficiaries without a recent mammogram and assesses the cost-effectiveness of a personalized targeted mailing encouraging them to have a mammogram.A randomized paired controlled trial included 1229 pairs of women matched on zip code, race, and urban or rural county. Postintervention mammography claims were measured from November 1997 through December 1998. The subjects were female Medicare beneficiaries ageor = 70, living in Michigan foror = 5 years, having no significant comorbidity likely to affect screening, and no mammogram foror = 5 years. Intervention subjects received a personally addressed letter from the Medical Director of Michigan Medicare with materials emphasizing the individual's lack of use of the Medicare mammography screening benefit, reasons for screening, and how to be screened.Women who received the mailing were 60% more likely to have a subsequent mammogram (OR 1.6, P0.005), with diagnostic mammograms increasing more than screening mammograms (2.8% vs. 0.8%). The absolute increase was greatest for women age 70 to 79, 10.6% in the intervention group versus 6.5% for controls, odds ratio 1.7 (P0.02). A statewide Medicare intervention in Michigan would cost of 108,000 US dollars to 238,000 US dollars, producing 3500 to 4300 additional mammograms at 31 US dollars to 55 US dollars per additional mammogram.The intervention increased mammography among long-term noncompliant older women, particularly increasing diagnostic mammograms. This approach can be directly implemented in other states and nationally. It may also be useful for other preventive services.

Background. There is accumulating evidence that screening programs can alter the natural history of colorectal cancer, a significant cause of mortality and morbidity in the US. Understanding how the technology to diagnose colonic diseases is utilized in the population provides insight into both the access and processes of care. Method. Using Medicare Part B billing files from the state of Michigan from 1986 to 1989 we identified all procedures used to diagnose colorectal disease. We utilized the Medicare Beneficiary File and the Area Resource File to identify beneficiary-specific and community-sociodemographic characteristics. The beneficiary and sociodemographic characteristics were, then, used in multiple regression analyses to identify their association with procedure utilization. Results. Sigmoidoscopic use declined dramatically with the increasing age cohorts of Medicare beneficiaries. Urban areas and communities with higher education levels had more sigmoidoscopic use. Among procedures used to examine the entire colon, isolated barium enema was used more frequently in African Americans, the elderly, and females. The combination of barium enema and sigmoidoscopy was used more frequently among females and the newest technology, colonoscopy, was used most frequently among White males. Conclusion. The existence of race, gender, and socioeconomic disparities in the use of colorectal technologies in a group of patients with near-universal insurance coverage demonstrates the necessity of understanding the reason(s) for these observed differences to improve access to appropriate technologies to all segments in our society.

The Integrated Inpatient Management Model was a 2.5-year controlled prospective trial of using a clinical information system to direct and monitor physician and hospital practice on general medicine services of an 880-bed university hospital. For the over 2,000 admissions on both a control service and the intervention service, the mean length of stay (LOS) decreased when compared with historic norms (0.68 and 0.95 days respectively; P < 0.01 for both). This difference in mean LOS represents a savings of 580 hospital days for the intervention over the control service; (95% confidence interval, 300 to 1420 days). There also was a trend for the intervention service to have fewer LOS outliers than expected (P = 0.14). Ancillary service use decreased by 17% on both control and intervention services (a trend that disappeared after the study was terminated), while other internal medicine services experienced a 29% increase in this measure of resource use. The intervention service experienced fewer preventable deaths (P = 0.04), but there were no differences in global quality of care measures, readmission and mortality rates, and patient satisfaction. This use of a clinical information system is a prototype for the systems that will be needed for all forms of managed care.

In this study, 675 general medicine admissions at a university teaching hospital were reviewed to evaluate six potential generic quality screens: 1) in-hospital death; 2) 28-day early readmission; 3) low patient satisfaction; 4) worsening severity of illness (as determined by an increase in Laboratory Acute Physiology and Chronic Health Evaluation APACHE-L); and 5) deviations from expected hospital length of stay; and 6) expected ancillary resource use. The quality of care for a stratified random sample of admissions were evaluated using structured implicit review (inter-rate reliability, Kappa = 0.5). Patients who died in-hospital were substantially more likely than those who were discharged alive to be rated as having had substandard care (30% vs. 10%; P < 0.001). In contrast, cases who had subsequent early readmissions did not have poorer quality ratings. Similarly, lower patient satisfaction was not associated with poorer ratings of technical process of care. Cases with lower-than-expected ancillary resource use (case-mix adjusted for diagnosis-related group) were more likely to be rated as having received substandard care than those with higher-than-expected resource use (16% vs. 6%; P < 0.05), and there was a similar trend for cases with shorter than expected length of stays. Associations between worsening severity of illness, as determined by APACHE-L scores, and quality were confounded because such patients were more likely to have died in-hospital.(ABSTRACT TRUNCATED AT 250 WORDS)

Health care policy makers, concerned with the rising cost of health care, have focused on the observed variation in the use of hospitals as a potential area in which to lower health care costs, i.e., if hospital utilization can be decreased, health care costs may also decline. However, it is crucial that the reasons for the observed variation in the current practice be understood or attempts to reduce costs may lead to policies that harm groups of patients and the providers and institutions currently delivering care. Using hospital discharge data from 59 hospital market communities in the lower peninsula of Michigan in 1984-86, the authors examined possible associations between socioeconomic characteristics and the observed small area variation in hospital discharge rates. First, a series of Poisson regressions was used for each of five covariates and 112 modified diagnosis-related groups (DRGs). Then, multiple regressions were examined, utilizing the five socioeconomic characteristics, after excluding statistically influential communities. The results indicate that community characteristics, including education, poverty, and unemployment, have a statistically significant association with the observed small area hospital discharge rate for many DRGs. Moreover, the direction of the effect is consistent across multiple disease categories. In multiple regressions, the five selected socioeconomic variables explained 48% of the variance for medical admissions and 19% for surgical admissions. For most DRGs, high educational levels were associated with lower hospitalization rates. The authors also identified statistically influential communities whose hospital utilization profile was different from that of most communities in Michigan.

A principal concern regarding Medicare's diagnosis-related group (DRG)-based prospective payment system is whether hospitals caring for more severely ill patients may be undercompensated for the services they provide. Research on possible inequities in hospital payment has been hampered by the absence of an objective, easily obtained, and valid measure of patients' severity of illness. Because laboratory data are objective and computerized in most of our nation's hospitals, a system utilizing such data, if shown to discriminate between patients of differing expected resource use, could prove most helpful in examining possible inequities in prospective payment system hospital payment. At a major teaching hospital, data were used from length of stay inlier patients in the 10 most frequent medical DRGs in the U.S. to develop and evaluate a severity of illness system called APACHE-L. APACHE-L uses the laboratory component of the original APACHE score. Whereas DRGs explained 20% of the variation in length of stay for the top ten DRGs, APACHE-L explained up to an additional 14% of the variation. For ancillary resource use, DRGs explained 10% of the variance, and APACHE-L explained up to an additional 15%. Diagnosis-related group-specific analyses demonstrated that the amount of resource use variance explained by APACHE-L varied widely depending on the DRG (from R2 = .00 for DRG 410, chemotherapy; to R2 = .38 for DRG 320, kidney and urinary tract infections, age greater than 17 years with complications or comorbidities). The APACHE-L score, which is objective and readily available in our nation's hospitals, shows considerable promise as a severity of illness adjuster for a subset of DRGs.

This paper describes the development of risk-adjusted mortality indices (RAMI) using 1985 MEDPAR data from 657 hospitals. The RAMI methodology is adopted from the Commission on Professional and Hospital Activities, however, both inhospital and post-discharge deaths are counted within time windows that vary by clinical condition. Five different RAMI measures (expected deaths/observed deaths) are developed, compared, and aggregated into various hospital characteristic strata. These measures vary by which discharge is held responsible for deaths within a time window, and whether or not inhospital deaths that occur beyond the time window are included. The RAMIs using varying time windows are compared with the RAMIs based upon inhospital deaths only. The inhospital RAMI was higher for the nonteaching hospitals (.95) as compared with the major and minor teaching institutions (.91 and .89). The RAMIs using the varying time windows, on the other hand, tend to be higher for the teaching institutions (e.g., 1.07 for major teaching hospitals; 0.99 for nonteaching hospitals).

A large portion of the resources of the Professional Standards Review Organization Program have been directed toward the review of inpatients to determine their need for continued hospitalization. The primary goal of this review process is the containment of hospital costs through the elimination of unnecessary patient hospitalization. A cost benefit analysis of this review process shows that the potential financial savings accrued are unlikely to offset the costs associated with the review procedure.

The diagnosis-related group (DRG)-based Medicare prospective payment system pays hospitals a fixed amount for the care of similar patients. The DRG definitions serve as the modifier of payment for Medicare patients. The dependence on these patient definitions raises many questions, among them the reason(s) for observed resource variability within a DRG. Various severity-of-illness measures have been shown to account for some of the resource variability noted within the DRGs. Most severity-of-illness studies to date, however, have not attempted to assess the effect of other known sources of resource variation, such as differing physician practice patterns. The authors examined the ability of severity of illness, as defined by disease staging, and physician practice variation to explain residual intra-DRG variability in length of stay. They demonstrate that physician practice variation accounts for more variance reduction than does severity of illness.

The Commission on Professional and Hospital Activities (CPHA) developed the Risk-Adjusted Mortality Index (RAMI), a method for comparing hospital death rates using existing abstract or billing data. The method is comprehensive insofar as it includes all payers and all types of cases except neonates. RAMI was designed to differentiate among admissions on the basis of the patient characteristics that increase or reduce the risk of dying in the hospital. Using a large national data base, risk factors were determined empirically within each of 310 clusters based on diagnosis-related groups (DRGs). The model was very effective at predicting risk-adjusted outcomes, with a correlation of 0.98 between actual and predicted deaths in a sample of 300 hospitals. RAMI appears to be a powerful tool for using existing data to monitor changes over time in hospital death rates.

The Diagnosis-Related Group (DRG)-based Medicare Prospective Payment System has raised a number of concerns. One major concern has centered on both the definition of outlier patients and how hospitals are to be paid for their care. The epidemiology of outlier patients, however, has received relatively little attention. Using a retrospective database, we constructed a case control study in which the cases were DRG outliers and the control patients were DRG-matched inlier patients. We then examined both the prior hospitalization experience of outlier patients and inlier controls, and the prior outlier experience of the attending physicians of outlier patients and inlier control patients. We demonstrated that DRG-based outlier patients were more likely to have had prior admissions to the hospital as compared with DRG-matched inlier control patients. Moreover, DRG-matched outlier cases were more likely to have had prior outlier admissions as compared to controls--an effect that was more pronounced when only the subset of patients who actually had a prior admission was evaluated. Finally, physicians of the DRG outlier patients were more likely to have had previous outlier patients than physicians of the DRG-matched inlier control patients. In summary, we were able to demonstrate that DRG-based outlier patients have a different prior admission and outlier experience than DRG-matched inlier control patients. However, because we showed the same relationship when we evaluated the outlier experience of physicians of outlier patients as compared to physicians of DRG-matched inlier controls, we were unable to determine if the effect was patient- or physician-based.(ABSTRACT TRUNCATED AT 250 WORDS)

Although numerous studies have been made of the determinants of small-area variation in hospital discharge rates, there is still disagreement about the role of socioeconomic factors. The lack of consensus stems, in part, from the difficulty in comparing results across studies that use different units and methods of analysis. Many of the studies using well-defined hospital service areas did not have the data needed to conduct a controlled analysis of the determinants of hospital utilization. Most of the studies that have performed controlled analyses have relied on larger geopolitical areas, which are not believed to capture self-contained health care systems. The study described here used a consistent set of data, three methods of analysis, and two units of analysis to test the importance of socioeconomic characteristics in explaining the variation in medical and surgical discharge rates in Michigan. Socioeconomic factors are found to be statistically significant determinants of the variation in both medical and surgical discharge rates, whether the method of analysis is simple correlations or multiple regressions, and whether the unit of analysis is the county or a well-designed hospital service area. These results suggest that previous small-area variation studies may have incorrectly concluded that socioeconomic characteristics do not explain differences in utilization rates.

Analysis of age-adjusted hospital admission profiles among small geographic areas has shown marked variation in hospital admissions for both surgical and medical cases in areas ranging from Maine to Manitoba. Much of the work has been led by John Wennberg and has focused on rural areas. This study examines the degree of variation in hospital admissions in small areas in the state of Michigan to determine whether those diseases that demonstrated high variation in Maine also demonstrated the same degree of variation in Michigan. The data on the degree of variation in 111 modified diagnosis-related groups (M-DRGs) from the state of Maine were supplied by Dr. Wennberg. Using the same M-DRGs, we defined age-adjusted, population-based hospital admission rates for the lower peninsula of Michigan for 1980 among 60 previously defined hospital marked communities. The observed hospital discharge counts in each of the M-DRGs were compared to the expected counts in each of the 60 communities, where the expected count was based on an indirect age adjustment. Both the Maine and Michigan small area data were expressed by the M-DRG's systematic standard deviation in which random variation has been accounted for via a Poisson probability model. It was found that the systematic standard deviations of the M-DRGs in Maine and the M-DRGs in Michigan strongly correlated with a Spearman correlation coefficient of 0.71 (P less than 0.001).(ABSTRACT TRUNCATED AT 250 WORDS)