Biomedical subjects

Arlene S Ash

Publications and source records attributed to Arlene S Ash.

At least 19 recordsLinked to original sources

PubMed2005

Developing a quality measure for clinical inertia in diabetes care.

OBJECTIVE: To develop a valid quality measure that captures clinical inertia, the failure to initiate or intensify therapy in response to medical need, in diabetes care and to link this process measure with outcomes of glycemic control. DATA SOURCES: Existing databases from 13 Department of Veterans Affairs hospitals between 1997 and 1999. STUDY DESIGN: Laboratory results, medications, and diagnoses were collected on 23,291 patients with diabetes. We modeled the decision to increase antiglycemic medications at individual visits. We then aggregated all visits for individual patients and calculated a treatment intensity score by comparing the observed number of increases to that expected based on our model. The association between treatment intensity and two measures of glycemic control, change in HbA1c during the observation period, and whether the outcome glycosylated hemoglobin (HbA1c) was greater than 8 percent, was then examined. PRINCIPAL FINDINGS: Increases in antiglycemic medications occurred at only 9.8 percent of visits despite 39 percent of patients having an initial HbA1c level greater than 8 percent. A clinically credible model predicting increase in therapy was developed with the principal predictor being a recent HbA1c greater than 8 percent. There were considerable differences in the intensity of therapy received by patients. Those patients receiving more intensive therapy had greater improvements in control (p < .001). CONCLUSIONS: Clinical inertia can be measured in diabetes care and this process measure is linked to patient outcomes of glycemic control. This measure may be useful in efforts to improve clinicians management of patients with diabetes.

Aged↗

PubMed2005

Do variations in disease prevalence limit the usefulness of population-based hospitalization rates for studying variations in hospital admissions?

BACKGROUND: Studies of geographic variation in hospitalizations commonly examine age- and gender-adjusted population-based hospitalization rates (ie, the numbers of persons hospitalized relative to what is expected given the age/gender distributions in the area population). OBJECTIVE: To determine whether areas identified as extreme using population-based hospitalization rates remain extreme when ranked by disease-based hospitalization rates (the numbers of persons hospitalized relative to what is expected given the amount of disease in the area). DESIGN: The authors examined 1997 Medicare data on both inpatient admissions and outpatient visits of patients 65 years and older in each of 71 small areas in Massachusetts for 15 medical conditions. For each area, the number of people having each condition was calculated as the sum of those hospitalized plus those treated as outpatients only. The authors used hierarchical Bayesian modeling to estimate area-specific population-based hospitalization rates, disease-based hospitalization rates (DHRs), and disease prevalence. MAIN OUTCOME MEASURE: The extent to which the same areas were identified as extreme based on population-based hospitalization rates versus DHRs. RESULTS: Area-specific population-based hospitalization rates, DHRs, and disease prevalence varied substantially. Areas identified as extreme using population-based hospitalization rates often were not extreme when ranked by DHRs. For 11 of the 15 conditions, 5 or more of the 14 areas ranked in top and bottom deciles by population-based hospitalization rates were more likely than not (ie, with probability > or = 0.50) to be at least 2 deciles less extreme when ranked by DHRs. CONCLUSION: Differences in disease prevalence can limit the usefulness of population-based hospitalization rates for studying variations in hospital admissions.

Aged↗

PubMed2005

Predicting pharmacy costs and other medical costs using diagnoses and drug claims.

BACKGROUND: Predicting health care costs for individuals and populations is essential for managing care. However, the comparative power of diagnostic and drug data for predicting future costs has not been closely examined. OBJECTIVE: We sought to compare the predictive performance of claims-based models using diagnoses, drugs claims, and combined data to predict health care costs. SUBJECTS: More than 1 million commercially insured, nonelderly individuals in a national (MEDSTAT MarketScan) research database comprised our sample. MEASURES: We used 1997 and 1998 drug and diagnostic profiles to predict costs in 1998 and 1999, respectively. To assess model performance, we compared R2 values and predictive ratios (predicted costs/actual costs) for important subgroups. RESULTS: Models using both drug and diagnostic data best predicted subsequent-year total health care costs (highest R2 = 0.168 versus 0.116 and 0.146 for models based on drug or diagnostic data alone, respectively), with highly accurate predictive ratios (0.95-1.05) for subgroups of patients with major medical conditions. Models predicting pharmacy costs had substantially higher R2 values than models predicting other medical costs (highest R2 0.493 versus 0.124). Drug-based models predicted future pharmacy costs better than diagnosis-based models (highest R2 = 0.482 versus 0.243), whereas diagnosis-based models predicted total costs (highest R2 = 0.146 versus 0.116) and nonpharmacy costs (highest R2 = 0.116 versus 0.071) more effectively than drug-based models. Newer models had markedly higher R values than older ones, largely because of richer data rather than model refinements. CONCLUSIONS: Combined drug and diagnostic data predicts total health care costs better than either type of data alone. Pharmacy spending is particularly predictable from drug data, whereas diagnoses are more useful than drugs for predicting other medical costs and total costs. Using even slightly more recent data can substantially boost model performance measures; thus, model comparisons should be conducted on the same dataset.

Actuarial Analysis↗

PubMed2004

Compensation and advancement of women in academic medicine: is there equity?

BACKGROUND: Women have been entering academic medicine in numbers at least equal to their male colleagues for several decades. Most studies have found that women do not advance in academic rank as fast as men and that their salaries are not as great. These studies, however, have typically not had the data to examine equity, that is, do women receive similar rewards for similar achievement? OBJECTIVE: To examine equity in promotion and salary for female versus male medical school faculty nationally. DESIGN: Mailed survey questionnaire. SETTING: 24 randomly selected medical schools in the contiguous United States. PARTICIPANTS: 1814 full-time U.S. medical school faculty in 1995-1996, stratified by sex, specialty, and graduation cohort. MEASUREMENTS: Promotion and compensation of academic medical faculty. RESULTS: Among the 1814 faculty respondents (response rate, 60%), female faculty were less likely to be full professors than were men with similar professional roles and achievement. For example, 66% of men but only 47% of women (P < 0.01) with 15 to 19 years of seniority were full professors. Large deficits in rank for senior faculty women were confirmed in logistic models that accounted for a wide range of other professional characteristics and achievements, including total career publications, years of seniority, hours worked per week, department type, minority status, medical versus nonmedical final degree, and school. Similar multivariable modeling also confirmed gender inequity in compensation. Although base salaries of nonphysician faculty are gender comparable, female physician faculty have a noticeable deficit (-11,691 dollars; P = 0.01). Furthermore, both physician and nonphysician women with greater seniority have larger salary deficits (-485 dollars per year of seniority; P = 0.01). LIMITATIONS: This is a cross-sectional study of a longitudinal phenomenon. No data are available for faculty who are no longer working full-time in academic medicine, and all data are self-reported. CONCLUSIONS: Female medical school faculty neither advance as rapidly nor are compensated as well as professionally similar male colleagues. Deficits for female physicians are greater than those for nonphysician female faculty, and for both physicians and nonphysicians, women's deficits are greater for faculty with more seniority.

Career Mobility↗

PubMed2004

Effect of patient gender on late-life depression management.

PURPOSE: To determine whether patient gender influences physicians' management of late-life major depression in older and younger elderly patients. METHODS: In 1996-2001, physician subjects viewed a professionally produced videotape vignette portraying an elderly patient meeting diagnostic criteria for major depression, then answered interviewer-administered questions about differential diagnosis and treatment. Patient gender and other characteristics were systematically varied in different versions of the videotape, but clinical content was held constant. This was a stratified random sample of 243 internists and family physicians with Veterans Health Administration (VA) or non-VA ambulatory care practices in the Northeastern United States. Outcomes were whether physicians followed a guideline-recommended management approach: treating with antidepressants or mental health referral or both and seeing the patient for follow-up within 2 weeks. RESULTS: Only 19% of physicians recommended treating depression (12% recommended antidepressants and 7% mental health referral), and 43% recommended follow-up within 2 weeks. Patient gender did not influence management recommendations in either younger old (67 year old) or older old (79 year old) patients (p > 0.12 for all comparisons). CONCLUSIONS: Gender disparities previously documented in the management of major conditions are not seen for the management of depression, a potentially stigmatized condition that does not require resource-intense interventions.

Adult↗

PubMed2004

Monitoring depression care: in search of an accurate quality indicator.

BACKGROUND: Linking process and outcomes is critical to accurately estimating healthcare quality and quantifying its benefits. OBJECTIVES: The objective of this study was to explore the relationship of guideline-based depression process measures with subsequent overall and psychiatric hospitalizations. RESEARCH DESIGN: This is a retrospective cohort study during which we used administrative and centralized pharmacy records for sample identification, derivation of guideline-based process measures (antidepressant dosage and duration adequacy), and subsequent hospitalization ascertainment. Depression care was measured from June 1, 1999, through August 31, 1999. We used multivariable regression to evaluate the link between depression care and subsequent overall and psychiatric hospitalization, adjusting for patient age, race, sex, socioeconomic status, comorbid illness, and hospitalization in the prior 12 months. SUBJECTS: We studied a total of 12,678 patients from 14 Northeastern VHA hospitals. RESULTS: We identified adequate antidepressant dosage in 90% and adequate duration in 45%. Those with adequate duration of antidepressants were less likely to be hospitalized in the subsequent 12 months than those with inadequate duration (odds ratio [OR],.90; 95% confidence interval [CI], .81-1.00). Those with adequate duration of antidepressants were less likely to have a psychiatric hospitalization in the subsequent 12 months than those with inadequate duration (OR, .82; 95% CI, .69-.96). We did not demonstrate a significant link between dosage adequacy and subsequent overall or psychiatric hospitalization. CONCLUSIONS: Guideline-based depression process measures derived from centralized data sources offer an important method of depression care surveillance. Their accuracy in capturing depression care quality is supported by their link to healthcare utilization. Further work is needed to assess the effect of implementing these quality indicators on depression care.

Adult↗

PubMed2004

Faculty self-reported experience with racial and ethnic discrimination in academic medicine.

BACKGROUND: Despite the need to recruit and retain minority faculty in academic medicine, little is known about the experiences of minority faculty, in particular their self-reported experience of racial and ethnic discrimination at their institutions. OBJECTIVE: To determine the frequency of self-reported experience of racial/ethnic discrimination among faculty of U.S. medical schools, as well as associations with outcomes, such as career satisfaction, academic rank, and number of peer-reviewed publications. DESIGN: A 177-item self-administered mailed survey of U.S. medical school faculty. SETTING: Twenty-four randomly selected medical schools in the contiguous United States. PARTICIPANTS: A random sample of 1,979 full-time faculty, stratified by medical school, specialty, graduation cohort, and gender. MEASUREMENTS: Frequency of self-reported experiences of racial/ethnic bias and discrimination. RESULTS: The response rate was 60%. Of 1,833 faculty eligible, 82% were non-Hispanic white, 10% underrepresented minority (URM), and 8% non-underrepresented minority (NURM). URM and NURM faculty were substantially more likely than majority faculty to perceive racial/ethnic bias in their academic environment (odds ratio [OR], 5.4; P <.01 and OR, 2.6; P <.01, respectively). Nearly half (48%) of URM and 26% of NURM reported experiencing racial/ethnic discrimination by a superior or colleague. Faculty with such reported experiences had lower career satisfaction scores than other faculty (P <.01). However, they received comparable salaries, published comparable numbers of papers, and were similarly likely to have attained senior rank (full or associate professor). CONCLUSIONS: Many minority faculty report experiencing racial/ethnic bias in academic medicine and have lower career satisfaction than other faculty. Despite this, minority faculty who reported experiencing racial/ethnic discrimination achieved academic productivity similar to that of other faculty.

Adult↗

PubMed2004

Can we use automated data to assess quality of hypertension care?

OBJECTIVE: To determine whether extractable blood pressure (BP) information available in a computerized patient record system (CPRS) could be used to assess quality of hypertension care independently of clinicians' notes. STUDY DESIGN: Retrospective cohort study of a random sample of hypertensive patients from 10 Department of Veterans Affairs (VA) sites across the country. METHODS: We abstracted BPs from electronic clinicians' notes for all medical visits of 981 hypertensive patients in 1999. We compared these with BP measurements available in a separate vitals signs file in the CPRS. We also evaluated whether assessments of performance varied by source by using patients' last documented BP reading. RESULTS: When the vital signs file and notes were combined, a BP measurement was taken for 71% of 6097 medical visits; 60% had a BP measurement only in the vital signs file. Combining sources, 43% of patients had a BP reading of less than 140/90 mm Hg; by site this varied (34%-51%). Vital signs file data alone yielded similar findings; site rankings by rates of BP control changed minimally. CONCLUSIONS: Current performance review programs collect clinical data from both clinicians' notes and automated sources as available. However, we found that notes contribute little information with respect to BP values beyond automated data alone. The VA's vital signs file is a prototypical automated data system that could make assessment of hypertension care more efficient in many settings.

Aged↗

PubMed2004

Risk adjustment of Medicare capitation payments using the CMS-HCC model.

This article describes the CMS hierarchical condition categories (HCC) model implemented in 2004 to adjust Medicare capitation payments to private health care plans for the health expenditure risk of their enrollees. We explain the model's principles, elements, organization, calibration, and performance. Modifications to reduce plan data reporting burden and adaptations for disabled, institutionalized, newly enrolled, and secondary payer subpopulations are discussed.

Adolescent↗

PubMed2004

The relationship of system-level quality improvement with quality of depression care.

OBJECTIVE: To explore the relationship of systemwide continuous quality improvement (CQI) with depression care quality in the Veterans Health Administration (VHA). STUDY DESIGN: Observational study using data from 2 VHA studies. PATIENTS AND METHODS: The Depression Care Quality Study (DCQS) was a retrospective cohort study of depression care quality in the northeastern United States involving 12 678 patients cared for at 14 VHA facilities; it used guideline-based process measures (ie, dosage and duration adequacy). The VHA CQI survey was a cross-sectional survey of systemwide CQI among a representative sample of VHA hospitals; it assessed CQI and organizational culture (OC) at 116 VHA hospitals nationwide and provided data on the 14 study facilities. We used analysis of variance to identify differences in the adequacy of depression care among these facilities. Pearson's correlation was used to identify the relationship of CQI and OC with facility-level depression care adequacy. RESULTS: Mean depression care adequacy differed among the 14 DCQS facilities (P < .0001). Overall dosage adequacy was 90% (range: 87%-92%). Overall duration adequacy was 45% (range: 39%-64%). There was no correlation between CQI and either dosage adequacy (r= .004, P= .98) or duration adequacy (r= -.17, P= .55). Similarly, there was no correlation between OC and either dosage adequacy (r= -.35, P= .22) or duration adequacy (r= -.12, P= .68). CONCLUSION: Although CQI may help bridge the healthcare quality gap, it may not be associated with higher disease-specific quality of care.

Adult↗

PubMed2003

Comparing the importance of disease rate versus practice style variations in explaining differences in small area hospitalization rates for two respiratory conditions.

Many studies have reported large variations in age- and sex-adjusted rates of hospitalizations across small geographic areas. These variations have often been attributed to differences in medical practice style which are not reflected in differences in health care outcomes. There is, however, another potentially important source of variation that has not been examined much in the literature: geographic differences in the age-sex adjusted size of the pool of patients who present with the disease and are candidates for hospitalization. Previous studies of small area variations in hospitalization rates have only used data on hospitalizations. Thus, it has not been possible to distinguish the extent to which differences in hospitalization rates are due to (i). differences in the chance that patients diagnosed with a disease are admitted to a hospital, which we refer to as the 'practice style effect,' versus (ii). geographic differences in the total amount of diagnosed disease, which we refer to as the 'disease effect.' Elementary methods for estimating the relative strength of the two effects directly from the data can be misleading, since equal amounts of variability in each effect result in unequal impacts on hospitalization rates. In this paper we describe a model-based approach for estimating the relative importance of the practice style effect and the disease effect in explaining variations in hospitalization rates. The key to our approach is the use of data on both inpatient and outpatient visits. We use 1997 Medicare data for two respiratory medical conditions across 71 small areas in Massachusetts: chronic bronchitis and emphysema, and bacterial pneumonia. Based on a Poisson model for the process generating hospitalizations and outpatient visits, we use a Bayesian framework and Gibbs sampling to compute and compare the correlation between the number of people hospitalized and each of these two sources of variation. Our results show that for the two conditions, disease rate variation explains at least as much of the variation in hospitalization rates as does practice style variation.

Aged↗

PubMed2003

Chemotherapy use among Medicare beneficiaries at the end of life.

BACKGROUND: Although many observers believe that cancer chemotherapy is overused at the end of life, there are no published data on this. OBJECTIVE: To determine the frequency and duration of chemotherapy use in the last 6 months of life stratified by type of cancer, age, and sex. DESIGN: Retrospective cohort analysis. SETTING: Administrative databases from Massachusetts and California. PATIENTS: All Medicare patients who died of cancer in Massachusetts and 5% of Medicare cancer decedents in California in 1996. MEASUREMENTS: Use of intravenous chemotherapy agents, chemotherapy administration, or medical evaluation for chemotherapy from Medicare billing data for each patient in 30-day periods from the date of death backward. RESULTS: In Massachusetts, 33% of cancer decedents older than 65 years of age received chemotherapy in the last 6 months of life, 23% in the last 3 months, and 9% in the last month. In California, the percentages were 26%, 20%, and 9%, respectively. Chemotherapy use greatly declined with age. Chemotherapy use was similar for patients with breast, colon, and ovarian cancer and those with cancer generally considered unresponsive to chemotherapy, such as pancreatic, hepatocellular, or renal-cell cancer or melanoma. Patients with types of cancer that are unresponsive to chemotherapy had shorter duration of chemotherapy use. CONCLUSION: Among patients who died of cancer, chemotherapy was used frequently in the last 3 months of life. The cancer's responsiveness to chemotherapy does not seem to influence whether dying patients receive chemotherapy at the end of life.

Age Factors↗

PubMed2003

Measuring the quality of depression care in a large integrated health system.

BACKGROUND: Guideline-based depression process measures provide a powerful way to monitor depression care and target areas needing improvement. OBJECTIVES: To assess the adequacy of depression care in the Veterans Health Administration (VHA) using guideline-based process measures derived from administrative and centralized pharmacy records, and to identify patient and provider characteristics associated with adequate depression care. RESEARCH DESIGN: This is a cohort study of patients from 14 VHA hospitals in the Northeastern United States which relied on existing databases. Subject eligibility criteria: at least one depression diagnosis during 1999, neither schizophrenia nor bipolar disease, and at least one antidepressant prescribed in the VHA during the period of depression care profiling (June 1, 1999 through August 31, 1999). Depression care was evaluated with process measures defined from the 1997 VHA depression guidelines: antidepressant dosage and duration adequacy. We used multivariable regression to identify patient and provider characteristics predicting adequate care. SUBJECTS: There were 12,678 patients eligible for depression care profiling. RESULTS: Adequate dosage was identified in 90%; 45% of patients had adequate duration of antidepressants. Significant patient and provider characteristics predicting inadequate depression care were younger age (<65), black race, and treatment exclusively in primary care. CONCLUSIONS: Under-treatment of depression exists in the VHA, despite considerable mental health access and generous pharmacy benefits. Certain patient populations may be at higher risk for inadequate depression care. More work is needed to align current practice with best-practice guidelines and to identify optimal ways of using available data sources to monitor depression care quality.

Adult↗

PubMed2003

Quality improvement implementation in the nursing home.

OBJECTIVE: To examine quality improvement (QI) implementation in nursing homes, its association with organizational culture, and its effects on pressure ulcer care. DATA SOURCES/STUDY SETTING: Primary data were collected from staff at 35 nursing homes maintained by the Department of Veterans Affairs (VA) on measures related to QI implementation and organizational culture. These data were combined with information obtained from abstractions of medical records and analyses of an existing database. STUDY DESIGN: A cross-sectional analysis of the association among the different measures was performed. DATA COLLECTION/EXTRACTION METHODS: Completed surveys containing information on QI implementation, organizational culture, employee satisfaction, and perceived adoption of guidelines were obtained from 1,065 nursing home staff. Adherence to best practices related to pressure ulcer prevention was abstracted from medical records. Risk-adjusted rates of pressure ulcer development were calculated from an administrative database. PRINCIPAL FINDINGS: Nursing homes differed significantly (p<.001) in their extent of QI implementation with scores on this 1 to 5 scale ranging from 2.98 to 4.08. Quality improvement implementation was greater in those nursing homes with an organizational culture that emphasizes innovation and teamwork. Employees of nursing homes with a greater degree of QI implementation were more satisfied with their jobs (a 1-point increase in QI score was associated with a 0.83 increase on the 5-point satisfaction scale, p<.001) and were more likely to report adoption of pressure ulcer clinical guidelines (a 1-point increase in QI score was associated with a 28 percent increase in number of staff reporting adoption, p<.001). No significant association was found, though, between QI implementation and either adherence to guideline recommendations as abstracted from records or the rate of pressure ulcer development. CONCLUSIONS: Quality improvement implementation is most likely to be successful in those VA nursing homes with an underlying culture that promotes innovation. While QI implementation may result in staff who are more satisfied with their jobs and who believe they are providing better care, associations with improved care are uncertain.

Aged↗

PubMed2003

Using claims data to examine mortality trends following hospitalization for heart attack in Medicare.

OBJECTIVE: To see if changes in the demographics and illness burden of Medicare patients hospitalized for acute myocardial infarction (AMI) from 1995 through 1999 can explain an observed rise (from 32 percent to 34 percent) in one-year mortality over that period. DATA SOURCES: Utilization data from the Centers for Medicare and Medicaid Services (CMS) fee-for-service claims (MedPAR, Outpatient, and Carrier Standard Analytic Files); patient demographics and date of death from CMS Denominator and Vital Status files. For over 1.5 million AMI discharges in 1995-1999 we retain diagnoses from one year prior, and during, the case-defining admission. STUDY DESIGN: We fit logistic regression models to predict one-year mortality for the 1995 cases and apply them to 1996-1999 files. The CORE model uses age, sex, and original reason for Medicare entitlement to predict mortality. Three other models use the CORE variables plus morbidity indicators from well-known morbidity classification methods (Charlson, DCG, and AHRQ's CCS). Regressions were used as is--without pruning to eliminate clinical or statistical anomalies. Each model references the same diagnoses--those recorded during the pre- and index admission periods. We compare each model's ability to predict mortality and use each to calculate risk-adjusted mortality in 1996-1999. PRINCIPAL FINDINGS: The comprehensive morbidity classifications (DCG and CCS) led to more accurate predictions than the Charlson, which dominated the CORE model (validated C-statistics: 0.81, 0.82, 0.74, and 0.66, respectively). Using the CORE model for risk adjustment reduced, but did not eliminate, the mortality increase. In contrast, adjustment using any of the morbidity models produced essentially flat graphs. CONCLUSIONS: Prediction models based on claims-derived demographics and morbidity profiles can be extremely accurate. While one-year post-AMI mortality in Medicare may not be worsening, outcomes appear not to have continued to improve as they had in the prior decade. Rich morbidity information is available in claims data, especially when longitudinally tracked across multiple settings of care, and is important in setting performance targets and evaluating trends.

Adolescent↗

PubMed2003

Hypertension management in patients with diabetes: the need for more aggressive therapy.

OBJECTIVE: Clinical trials have demonstrated the importance of tight blood pressure control among patients with diabetes. However, little is known regarding the management of hypertension in patients with coexisting diabetes. To examine this issue, we addressed 1) whether hypertensive patients with coexisting diabetes are achieving lower levels of blood pressure than patients without diabetes, 2) whether there are differences in the intensity of antihypertensive medication therapy provided to patients with and without diabetes, and 3) whether diabetes management affects decisions to increase antihypertensive medication therapy. RESEARCH DESIGN AND METHODS: We abstracted medical records to collect detailed information on 2 years of care provided for 800 male veterans with hypertension. We compared patients with and without diabetes on intensity of therapy and blood pressure control. Intensity of therapy was described using a previously validated measure that captures the likelihood of an increase in antihypertensive medications. We also determined whether increases in antihypertensive medications were less likely at those visits in which the diabetes medications were being adjusted. RESULTS: Of the 274 hypertensive patients with diabetes, 73% had a blood pressure > or =140/90 mmHg, compared with 66% in the 526 patients without diabetes (P = 0.04). Diabetic patients also received significantly (P = 0.05) less intensive antihypertensive medication therapy than patients without diabetes. Less intensive therapy in diabetic patients could not be explained by clinicians being distracted by the treatment for diabetes. CONCLUSIONS: There is an urgent need to improve hypertension care and blood pressure control in patients with diabetes. Additional information is required to understand why clinicians are not more aggressive in managing blood pressure when patients also have diabetes.

Aged↗

PubMed2002

Disease burden profiles: an emerging tool for managing managed care.

As health plans assume financial risk for providing health care services, effectively managing the health of a population remains one of the toughest challenges. This article shows how risk assessment methods can be used to measure disease burden in the full population and to discriminate levels of future health care needs within specific disease cohorts. We also examine and compare the predictive power of claims-based models within a diabetic cohort.

Chronic Disease↗

PubMed2002

Profiling nursing homes using Bayesian hierarchical modeling.

OBJECTIVES: New methods developed to improve the statistical basis of provider profiling may be particularly applicable to nursing homes. We examine the use of Bayesian hierarchical modeling in profiling nursing homes on their rate of pressure ulcer development. DESIGN: Observational study using Minimum Data Set data from 1997 and 1998. SETTING: A for-profit nursing home chain. PARTICIPANTS: Residents of 108 nursing homes who were without a pressure ulcer on an index assessment. MEASUREMENTS: Nursing homes were compared on their performance on risk-adjusted rates of pressure ulcer development calculated using standard statistical techniques and Bayesian hierarchical modeling. RESULTS: Bayesian estimates of nursing home performance differed considerably from rates calculated using standard statistical techniques. The range of risk-adjusted rates among nursing homes was 0% to 14.3% using standard methods and 1.0% to 4.8% using Bayesian analysis. Fifteen nursing homes were designated as outliers based on their z scores, and two were outliers using Bayesian modeling. Only one nursing home had greater than a 50% probability of having a true rate of ulcer development exceeding 4%. CONCLUSIONS: Bayesian hierarchical modeling can be successfully applied to the problem of profiling nursing homes. Results obtained from Bayesian modeling are different from those obtained using standard statistical techniques. The continued evaluation and application of this new methodology in nursing homes may ensure that consumers and providers have the most accurate information regarding performance.

Bayes Theorem↗