Patient Safety Outcomes under Flexible and Standard Resident Duty-Hour Rules.

BACKGROUND: Concern persists that extended shifts in medical residency programs may adversely affect patient safety. METHODS: We conducted a cluster-randomized noninferiority trial in 63 internal-medicine residency programs during the 2015-2016 academic year. Programs underwent randomization to a group with standard duty hours, as adopted by the Accreditation Council for Graduate Medical Education (ACGME) in July 2011, or to a group with more flexible duty-hour rules that did not specify limits on shift length or mandatory time off between shifts. The primary outcome for each program was the change in unadjusted 30-day mortality from the pretrial year to the trial year, as ascertained from Medicare claims. We hypothesized that the change in 30-day mortality in the flexible programs would not be worse than the change in the standard programs (difference-in-difference analysis) by more than 1 percentage point (noninferiority margin). Secondary outcomes were changes in five other patient safety measures and risk-adjusted outcomes for all measures. RESULTS: The change in 30-day mortality (primary outcome) among the patients in the flexible programs (12.5% in the trial year vs. 12.6% in the pretrial year) was noninferior to that in the standard programs (12.2% in the trial year vs. 12.7% in the pretrial year). The test for noninferiority was significant (P = 0.03), with an estimate of the upper limit of the one-sided 95% confidence interval (0.93%) for a between-group difference in the change in mortality that was less than the prespecified noninferiority margin of 1 percentage point. Differences in changes between the flexible programs and the standard programs in the unadjusted rate of readmission at 7 days, patient safety indicators, and Medicare payments were also below 1 percentage point; the noninferiority criterion was not met for 30-day readmissions or prolonged length of hospital stay. Risk-adjusted measures generally showed similar findings. CONCLUSIONS: Allowing program directors flexibility in adjusting duty-hour schedules for trainees did not adversely affect 30-day mortality or several other measured outcomes of patient safety. (Funded by the National Heart, Lung, and Blood Institute and Accreditation Council for Graduate Medical Education; iCOMPARE ClinicalTrials.gov number, NCT02274818.).

Comparing Outcomes and Costs of Surgical Patients Treated at Major Teaching and Nonteaching Hospitals: A National Matched Analysis.

OBJECTIVE: To compare outcomes and costs between major teaching and nonteaching hospitals on a national scale by closely matching on patient procedures and characteristics. BACKGROUND: Teaching hospitals have been shown to often have better quality than nonteaching hospitals, but cost and value associated with teaching hospitals remains unclear. METHODS: A study of Medicare patients at 340 teaching hospitals (resident-to-bed ratios ≥ 0.25) and matched patient controls from 2444 nonteaching hospitals (resident-to-bed ratios < 0.05).We studied 86,751 pairs admitted for general surgery (GS), 214,302 pairs of patients admitted for orthopedic surgery, and 52,025 pairs of patients admitted for vascular surgery. RESULTS: In GS, mortality was 4.62% in teaching hospitals versus 5.57%, (a difference of -0.95%, <0.0001), and overall paired cost difference = $915 (P < 0.0001). For the GS quintile of pairs with highest risk on admission, mortality differences were larger (15.94% versus 18.18%, difference = -2.24%, P < 0.0001), and paired cost difference = $3773 (P < 0.0001), yielding $1682 per 1% mortality improvement at 30 days. Patterns for vascular surgery outcomes resembled general surgery; however, orthopedics outcomes did not show significant differences in mortality across teaching and nonteaching environments, though costs were higher at teaching hospitals. CONCLUSIONS: Among Medicare patients, as admission risk of mortality increased, the absolute mortality benefit of treatment at teaching hospitals also increased, though accompanied by marginally higher cost. Major teaching hospitals appear to return good value for the extra resources used in general surgery, and to some extent vascular surgery, but this was not apparent in orthopedic surgery.

Comparing Outcomes and Costs of Medical Patients Treated at Major Teaching and Non-teaching Hospitals: A National Matched Analysis.

BACKGROUND: Teaching hospitals typically pioneer investment in new technology and cultivate workforce characteristics generally associated with better quality, but the value of this extra investment is unclear. OBJECTIVE: Compare outcomes and costs between major teaching and non-teaching hospitals by closely matching on patient characteristics. DESIGN: Medicare patients at 339 major teaching hospitals (resident-to-bed (RTB) ratios ≥ 0.25); matched patient controls from 2439 non-teaching hospitals (RTB ratios < 0.05). PARTICIPANTS: Forty-three thousand nine hundred ninety pairs of patients (one from a major teaching hospital and one from a non-teaching hospital) admitted for acute myocardial infarction (AMI), 84,985 pairs admitted for heart failure (HF), and 74,947 pairs admitted for pneumonia (PNA). EXPOSURE: Treatment at major teaching hospitals versus non-teaching hospitals. MAIN MEASURES: Thirty-day all-cause mortality, readmissions, ICU utilization, costs, payments, and value expressed as extra cost for a 1% improvement in survival. KEY RESULTS: Thirty-day mortality was lower in teaching than non-teaching hospitals (10.7% versus 12.0%, difference = - 1.3%, P < 0.0001). The paired cost difference (teaching - non-teaching) was $273 (P < 0.0001), yielding $211 per 1% mortality improvement. For the quintile of pairs with highest risk on admission, mortality differences were larger (24.6% versus 27.6%, difference = - 3.0%, P < 0.0001), and paired cost difference = $1289 (P < 0.0001), yielding $427 per 1% mortality improvement at 30 days. Readmissions and ICU utilization were lower in teaching hospitals (both P < 0.0001), but length of stay was longer (5.5 versus 5.1 days, P < 0.0001). Finally, individual results for AMI, HF, and PNA showed similar findings as in the combined results. CONCLUSIONS AND RELEVANCE: Among Medicare patients admitted for common medical conditions, as admission risk of mortality increased, the absolute mortality benefit of treatment at teaching hospitals also increased, though accompanied by marginally higher cost. Major teaching hospitals appear to return good value for the extra resources used.

Failure-to-Rescue After Acute Myocardial Infarction.

BACKGROUND: Failure-to-rescue (FTR), originally developed to study quality of care in surgery, measures an institution's ability to prevent death after a patient becomes complicated. OBJECTIVES: Develop an FTR metric modified to analyze acute myocardial infarction (AMI) outcomes. RESEARCH DESIGN: Split-sample design: a random 20% of hospitals to develop FTR definitions, a second 20% to validate test characteristics, and an out-of-sample 60% to validate results. SUBJECTS: Older Medicare beneficiaries admitted to short-term acute-care hospitals for AMI between 2009 and 2011. MEASURES: Thirty-day mortality and FTR rates, and in-hospital complication rates. RESULTS: The 60% out-of-sample validation included 234,277 patients across 1142 hospitals that admitted at least 50 patients over 2.5 years. In total, 72.1% of patients were defined as Medically Complicated (complex on admission or subsequently developed a complication or died without a recorded complication) of whom 19.3% died. Spearman r between hospital risk-adjusted 30-day mortality and FTR was 0.89 (P<0.0001); Mortality versus Complication=-0.01 (P=0.6198); FTR versus Complication=-0.10 (P=0.0011). Major teaching hospitals displayed 19% lower odds of FTR versus non-teaching hospitals (odds ratio=0.81, P<0.0001), while hospitals as a group defined by teaching hospital status, comprehensive cardiac technology, and having good nursing mix and staffing, displayed a 33% lower odds of FTR (odds ratio=0.67, P<0.0001) versus hospitals without any of these characteristics. CONCLUSIONS: A modified FTR metric can be created that has many of the advantageous properties of surgical FTR and can aid in studying the quality of care of AMI admissions.

Disparities in Breast Cancer Survival by Socioeconomic Status Despite Medicare and Medicaid Insurance.

Policy Points Patients with low socioeconomic status (SES) experience poorer survival rates after diagnosis of breast cancer, even when enrolled in Medicare and Medicaid. Most of the difference in survival is due to more advanced cancer on presentation and the general poor health of lower SES patients, while only a very small fraction of the SES disparity is due to differences in cancer treatment. Even when comparing only low- versus not-low-SES whites (without confounding by race) the survival disparity between disparate white SES populations is very large and is associated with lower use of preventive care, despite having insurance. CONTEXT: Disparities in breast cancer survival by socioeconomic status (SES) exist despite the "safety net" programs Medicare and Medicaid. What is less clear is the extent to which SES disparities affect various racial and ethnic groups and whether causes differ across populations. METHODS: We conducted a tapered matching study comparing 1,890 low-SES (LSES) non-Hispanic white, 1,824 black, and 723 Hispanic white women to 60,307 not-low-SES (NLSES) non-Hispanic white women, all in Medicare and diagnosed with invasive breast cancer between 1992 and 2010 in 17 US Surveillance, Epidemiology, and End Results (SEER) regions. LSES Medicare patients were Medicaid dual-eligible and resided in neighborhoods with both high poverty and low education. NLSES Medicare patients had none of these factors. MEASUREMENTS: 5-year and median survival. FINDINGS: LSES non-Hispanic white patients were diagnosed with more stage IV disease (6.6% vs 3.6%; p < 0.0001), larger tumors (24.6 mm vs 20.2 mm; p < 0.0001), and more chronic diseases such as diabetes (37.8% vs 19.0%; p < 0.0001) than NLSES non-Hispanic white patients. Disparity in 5-year survival (NLSES - LSES) was 13.7% (p < 0.0001) when matched for age, year, and SEER site (a 42-month difference in median survival). Additionally, matching 55 presentation factors, including stage, reduced the disparity to 4.9% (p = 0.0012), but further matching on treatments yielded little further change in disparity: 4.6% (p = 0.0014). Survival disparities among LSES blacks and Hispanics, also versus NLSES whites, were significantly associated with presentation factors, though black patients also displayed disparities related to initial treatment. Before being diagnosed, all LSES populations used significantly less preventive care services than matched NLSES controls. CONCLUSIONS: In Medicare, SES disparities in breast cancer survival were large (even among non-Hispanic whites) and predominantly related to differences of presentation characteristics at diagnosis rather than differences in treatment. Preventive care was less frequent in LSES patients, which may help explain disparities at presentation.

Examining Causes of Racial Disparities in General Surgical Mortality: Hospital Quality Versus Patient Risk.

BACKGROUND: Racial disparities in general surgical outcomes are known to exist but not well understood. OBJECTIVES: To determine if black-white disparities in general surgery mortality for Medicare patients are attributable to poorer health status among blacks on admission or differences in the quality of care provided by the admitting hospitals. RESEARCH DESIGN: Matched cohort study using Tapered Multivariate Matching. SUBJECTS: All black elderly Medicare general surgical patients (N=18,861) and white-matched controls within the same 6 states or within the same 838 hospitals. MEASURES: Thirty-day mortality (primary); others include in-hospital mortality, failure-to-rescue, complications, length of stay, and readmissions. RESULTS: Matching on age, sex, year, state, and the exact same procedure, blacks had higher 30-day mortality (4.0% vs. 3.5%, P<0.01), in-hospital mortality (3.9% vs. 2.9%, P<0.0001), in-hospital complications (64.3% vs. 56.8% P<0.0001), and failure-to-rescue rates (6.1% vs. 5.1%, P<0.001), longer length of stay (7.2 vs. 5.8 d, P<0.0001), and more 30-day readmissions (15.0% vs. 12.5%, P<0.0001). Adding preoperative risk factors to the above match, there was no significant difference in mortality or failure-to-rescue, and all other outcome differences were small. Blacks matched to whites in the same hospital displayed no significant differences in mortality, failure-to-rescue, or readmissions. CONCLUSIONS: Black and white Medicare patients undergoing the same procedures with closely matched risk factors displayed similar mortality, suggesting that racial disparities in general surgical mortality are not because of differences in hospital quality. To reduce the observed disparities in surgical outcomes, the poorer health of blacks on presentation for surgery must be addressed.

Racial disparities in colon cancer survival: a matched cohort study.

BACKGROUND: Differences in colon cancer survival by race are a recognized problem among Medicare beneficiaries. OBJECTIVE: To determine to what extent the racial disparity in survival is due to disparity in presentation characteristics at diagnosis or disparity in subsequent treatment. DESIGN: Black patients with colon cancer were matched with 3 groups of white patients: a "demographic characteristics" match controlling for age, sex, diagnosis year, and Survey, Epidemiology, and End Results (SEER) site; a "presentation" match controlling for demographic characteristics plus comorbid conditions and tumor characteristics, including stage and grade; and a "treatment" match, including presentation variables plus details of surgery, radiation, and chemotherapy. SETTING: 16 U.S. SEER sites. PATIENTS: 7677 black patients aged 65 years or older diagnosed between 1991 and 2005 in the SEER-Medicare database and 3 sets of 7677 matched white patients, followed until 31 December 2009. MEASUREMENTS: 5-year survival. RESULTS: The absolute difference in 5-year survival between black and white patients was 9.9% (95% CI, 8.3% to 11.4%; P<0.001) in the demographic characteristics match. This disparity remained unchanged between 1991 and 2005. After matching for presentation characteristics, the difference decreased to 4.9% (CI, 3.6% to 6.1%; P<0.001). After additional matching for treatment, this difference decreased to 4.3% (CI, 2.9% to 5.5%; P<0.001). The disparity in survival attributed to treatment differences made up only an absolute 0.6% of the overall 9.9% survival disparity. LIMITATION: An observational study limited to elderly Medicare fee-for-service beneficiaries living in selected geographic areas. CONCLUSION: Racial disparities in colon cancer survival did not decrease among patients diagnosed between 1991 and 2005. This persistent disparity seemed to be more related to presentation characteristics at diagnosis than to subsequent treatment differences. PRIMARY FUNDING SOURCE: Agency for Healthcare Research and Quality and National Science Foundation.

Association of the 2011 ACGME resident duty hour reforms with mortality and readmissions among hospitalized Medicare patients.

IMPORTANCE: Patient outcomes associated with the 2011 Accreditation Council for Graduate Medical Education (ACGME) duty hour reforms have not been evaluated at a national level. OBJECTIVE: To evaluate the association of the 2011 ACGME duty hour reforms with mortality and readmissions. DESIGN, SETTING, AND PARTICIPANTS: Observational study of Medicare patient admissions (6,384,273 admissions from 2,790,356 patients) to short-term, acute care, nonfederal hospitals (n = 3104) with principal medical diagnoses of acute myocardial infarction, stroke, gastrointestinal bleeding, or congestive heart failure or a Diagnosis Related Group classification of general, orthopedic, or vascular surgery. Of the hospitals, 96 (3.1%) were very major teaching, 138 (4.4%) major teaching, 442 (14.2%) minor teaching, 443 (14.3%) very minor teaching, and 1985 (64.0%) nonteaching. EXPOSURE: Resident-to-bed ratio as a continuous measure of hospital teaching intensity. MAIN OUTCOMES AND MEASURES: Change in 30-day all-location mortality and 30-day all-cause readmission, comparing patients in more intensive relative to less intensive teaching hospitals before (July 1, 2009-June 30, 2011) and after (July 1, 2011-June 30, 2012) duty hour reforms, adjusting for patient comorbidities, time trends, and hospital site. RESULTS: In the 2 years before duty hour reforms, there were 4,325,854 admissions with 288,422 deaths and 602,380 readmissions. In the first year after the reforms, accounting for teaching hospital intensity, there were 2,058,419 admissions with 133,547 deaths and 272,938 readmissions. There were no significant postreform differences in mortality accounting for teaching hospital intensity for combined medical conditions (odds ratio [OR], 1.00; 95% CI, 0.96-1.03), combined surgical categories (OR, 0.99; 95% CI, 0.94-1.04), or any of the individual medical conditions or surgical categories. There were no significant postreform differences in readmissions for combined medical conditions (OR, 1.00; 95% CI, 0.97-1.02) or combined surgical categories (OR, 1.00; 95% CI, 0.98-1.03). For the medical condition of stroke, there were higher odds of readmissions in the postreform period (OR, 1.06; 95% CI, 1.001-1.13). However, this finding was not supported by sensitivity analyses and there were no significant postreform differences for readmissions for any other individual medical condition or surgical category. CONCLUSIONS AND RELEVANCE: Among Medicare beneficiaries, there were no significant differences in the change in 30-day mortality rates or 30-day all-cause readmission rates for those hospitalized in more intensive relative to less intensive teaching hospitals in the year after implementation of the 2011 ACGME duty hour reforms compared with those hospitalized in the 2 years before implementation.

Racial disparities in operative procedure time: the influence of obesity.

BACKGROUND: Using Pennsylvania Medicare claims from 1995 to 1996, the authors previously reported that anesthesia procedure length appears longer in blacks than whites. In a new study using a different and larger data set, the authors now examine whether body mass index (BMI), not available in Medicare claims, explains this difference. The authors also examine the relative contributions of surgical and anesthesia times. METHODS: The Obesity and Surgical Outcomes Study of 47 hospitals throughout Illinois, New York, and Texas abstracted chart information including BMI on elder Medicare patients (779 blacks and 14,596 whites) undergoing hip and knee replacement and repair, colectomy, and thoracotomy between 2002 and 2006. The authors matched all black Medicare patients to comparable whites and compared procedure lengths. RESULTS: Mean BMI in the black and white populations was 30.24 and 28.96 kg/m, respectively (P<0.0001). After matching on age, sex, procedure, comorbidities, hospital, and BMI, mean white BMI in the comparison group was 30.1 kg/m (P=0.94). The typical matched pair difference (black-white) in anesthesia (induction to recovery room) procedure time was 7.0 min (P=0.0019), of which 6 min reflected the surgical (cut-to-close) time difference (P=0.0032). Within matched pairs, where the difference in procedure times was greater than 30 min between patients, blacks more commonly had longer procedure times (Odds=1.39; P=0.0008). CONCLUSIONS: Controlling for patient characteristics, BMI, and hospital, elder black Medicare patients experienced slightly but significantly longer procedure length than their closely matched white controls. Procedure length difference was almost completely due to surgery, not anesthesia.

Characteristics associated with differences in survival among black and white women with breast cancer.

IMPORTANCE: Difference in breast cancer survival by race is a recognized problem among Medicare beneficiaries. OBJECTIVE: To determine if racial disparity in breast cancer survival is primarily attributable to differences in presentation characteristics at diagnosis or subsequent treatment. DESIGN, SETTING, AND PATIENTS: Comparison of 7375 black women 65 years and older diagnosed between 1991 to 2005 and 3 sets of 7375 matched white control patients selected from 99,898 white potential controls, using data for 16 US Surveillance, Epidemiology and End Results (SEER) sites in the SEER-Medicare database. All patients received follow-up through December 31, 2009, and the black case patients were matched to 3 white control populations on demographics (age, year of diagnosis, and SEER site), presentation (demographics variables plus patient comorbid conditions and tumor characteristics such as stage, size, grade, and estrogen receptor status), and treatment (presentation variables plus details of surgery, radiation therapy, and chemotherapy). MAIN OUTCOMES AND MEASURES: 5-Year survival. RESULTS: The absolute difference in 5-year survival (blacks, 55.9%; whites, 68.8%) was 12.9% (95% CI, 11.5%-14.5%; P < .001) in the demographics match. This difference remained unchanged between 1991 and 2005. After matching on presentation characteristics, the absolute difference in 5-year survival was 4.4% (95% CI, 2.8%-5.8%; P < .001) and was 3.6% (95% CI, 2.3%-4.9%; P < .001) lower for blacks than for whites matched also on treatment. In the presentation match, fewer blacks received treatment (87.4% vs 91.8%; P < .001), time from diagnosis to treatment was longer (29.2 vs 22.8 days; P < .001), use of anthracyclines and taxols was lower (3.7% vs 5.0%; P < .001), and breast-conserving surgery without other treatment was more frequent (8.2% vs 7.3%; P = .04). Nevertheless, differences in survival associated with treatment differences accounted for only 0.81% of the 12.9% survival difference. CONCLUSIONS AND RELEVANCE: In the SEER-Medicare database, differences in breast cancer survival between black and white women did not substantially change among women diagnosed between 1991 and 2005. These differences in survival appear primarily related to presentation characteristics at diagnosis rather than treatment differences.

Medical and financial risks associated with surgery in the elderly obese.

OBJECTIVE: To study the medical and financial outcomes associated with surgery in elderly obese patients and to ask if obesity itself influences outcomes above and beyond the effects from comorbidities that are known to be associated with obesity. BACKGROUND: Obesity is a surgical risk factor not present in Medicare's risk adjustment or payment algorithms, as BMI is not collected in administrative claims. METHODS: A total of 2045 severely or morbidly obese patients (BMI ≥ 35 kg/m, aged between 65 and 80 years) selected from 15,914 elderly patients in 47 hospitals undergoing hip and knee surgery, colectomy, and thoracotomy were matched to 2 sets of 2045 nonobese patients (BMI = 20-30 kg/m). A "limited match" controlled for age, sex, race, procedure, and hospital. A "complete match" also controlled for 30 additional factors such as diabetes and admission clinical data from chart abstraction. RESULTS: Mean BMI in the obese patients was 40 kg/m compared with 26 kg/m in the nonobese. In the complete match, obese patients displayed increased odds of wound infection: OR (odds ratio) = 1.64 (95% CI: 1.21, 2.21); renal dysfunction: OR = 2.05 (1.39, 3.05); urinary tract infection: OR = 1.55 (1.24, 1.94); hypotension: OR = 1.38 (1.07, 1.80); respiratory events: OR = 1.44 (1.19, 1.75); 30-day readmission: OR = 1.38 (1.08, 1.77); and a 12% longer length of stay (8%, 17%). Provider costs were 10% (7%, 12%) greater in obese than in nonobese patients, whereas Medicare payments increased only 3% (2%, 5%). Findings were similar in the limited match. CONCLUSIONS: Obesity increases the risks and costs of surgery. Better approaches are needed to reduce these risks. Furthermore, to avoid incentives to underserve this population, Medicare should consider incorporating incremental costs of caring for obese patients into payment policy and include obesity in severity adjustment models.

Adjustment for Atherosclerosis Diagnosis Distorts the Effects of Percutaneous Coronary Intervention and the Ranking of Hospital Performance.

BACKGROUND: Coronary atherosclerosis raises the risk of acute myocardial infarction (AMI), and is usually included in AMI risk-adjustment models. Percutaneous coronary intervention (PCI) does not cause atherosclerosis, but may contribute to the notation of atherosclerosis in administrative claims. We investigated how adjustment for atherosclerosis affects rankings of hospitals that perform PCI. METHODS AND RESULTS: This was a retrospective cohort study of 414 715 Medicare beneficiaries hospitalized for AMI between 2009 and 2011. The outcome was 30-day mortality. Regression models determined the association between patient characteristics and mortality. Rankings of the 100 largest PCI and non-PCI hospitals were assessed with and without atherosclerosis adjustment. Patients admitted to PCI hospitals or receiving interventional cardiology more frequently had an atherosclerosis diagnosis. In adjustment models, atherosclerosis was associated, implausibly, with a 42% reduction in odds of mortality (odds ratio=0.58, P<0.0001). Without adjustment for atherosclerosis, the number of expected lives saved by PCI hospitals increased by 62% (P<0.001). Hospital rankings also changed: 72 of the 100 largest PCI hospitals had better ranks without atherosclerosis adjustment, while 77 of the largest non-PCI hospitals had worse ranks (P<0.001). CONCLUSIONS: Atherosclerosis is almost always noted in patients with AMI who undergo interventional cardiology but less often in medically managed patients, so adjustment for its notation likely removes part of the effect of interventional treatment. Therefore, hospitals performing more extensive imaging and more PCIs have higher atherosclerosis diagnosis rates, making their patients appear healthier and artificially reducing the expected mortality rate against which they are benchmarked. Thus, atherosclerosis adjustment is detrimental to hospitals providing more thorough AMI care.

Population-based study of home accessibility features and the activities of daily living: clinical and policy implications.

PURPOSE: To empirically test a biopsychoecological model referred to as Health Environmental Integration (HEI) by showing associations between the perception of unmet need for home accessibility features and the experience of Activities of Daily Living (ADL) difficulties. METHOD: A USA population-based cross-sectional study of the 1994 and 1995 National Health Interview Survey (NHIS) supplements on Disability (NHIS-D). Estimated likelihood of ADL difficulty, comparing those who perceived unmet needs for home accessibility features to those who did not, were obtained through logistic regression after controlling for severity and socioeconomic differences. ADLs included dressing, eating, getting in and out of chairs, or getting to and using the bathroom. RESULTS: There were 12,743 people with physical limitations, 10.3% of whom perceived an unmet need for at least 1 home accessibility feature. After accounting for severity of physical limitations and socioeconomic differences, the odds of an ADL difficulty were 3.7 times larger (95% confidence interval, 2.9 - 4.6) among people who perceived an unmet need for accessibility feature(s). CONCLUSIONS: Findings support concepts of HEI. When attempting to understand the aetiology of ADL difficulty, it is essential to look beyond biomedical and socioeconomic factors to effects of the environment. Rather than single root causes, disability aetiologies occur through linkages among biological, psychological, socioeconomic, and environmental mechanisms.

Variation in chemotherapy utilization in ovarian cancer: the relative contribution of geography.

OBJECTIVE: This study investigates geographic variation in chemotherapy utilization for ovarian cancer in both absolute and relative terms and examines area characteristics associated with this variation. DATA SOURCES: Surveillance, Epidemiology, and End Results (SEER) Medicare data from 1990 to 2001 for Medicare patients over 65 with a diagnosis of ovarian cancer between 1990 and 1999. Chemotherapy within a year of diagnosis was identified by Medicare billing codes. The hospital referral region (HRR) represents the geographic unit of analysis. STUDY DESIGN: A logit model predicting the probability of receiving chemotherapy by each of the 39 HRRs. Control variables included medical characteristics (patient age, stage, year of diagnosis, and comorbidities) and socioeconomic characteristics (race, income, and education). The variation among HRRs was tested by the chi2 statistic, and the relative contribution was measured by the omega statistic. HHR market characteristic are then used to explain HRR-level variation. PRINCIPAL FINDINGS: The average chemotherapy rate was 56.6 percent, with a range by HRR from 33 percent to 67 percent. There were large and significant differences in chemotherapy use between HRRs, reflected by a chi2 for HRR of 146 (df = 38, p < .001). HRR-level variation in chemotherapy use can be partially explained by higher chemotherapy rates in HRRs with a higher percentage of hospitals with oncology services. However, an omega analysis indicates that, by about 15 to one, the variation between patients in use of chemotherapy reflects variations in patient characteristics rather than unexplained variation among HRRs. CONCLUSIONS: While absolute levels of chemotherapy variation between geographic areas are large and statistically significant, this analysis suggests that the role of geography in determining who gets chemotherapy is small relative to individual medical characteristics. Nevertheless, while variation by medical characteristics can be medically justified, the same cannot be said for geographic variation. Our finding that density of oncology hospitals predicts chemotherapy use suggests that provider supply is positively correlated with geographic variation.

Indirect Standardization Matching: Assessing Specific Advantage and Risk Synergy.

OBJECTIVE: To develop a method to allow a hospital to compare its performance using its entire patient population to the outcomes of very similar patients treated elsewhere. DATA SOURCES/SETTING: Medicare claims in orthopedics and common general, gynecologic, and urologic surgery from Illinois, New York, and Texas from 2004 to 2006. STUDY DESIGN: Using two example "focal" hospitals, each hospital's patients were matched to 10 very similar patients selected from 619 other hospitals. DATA COLLECTION/EXTRACTION METHODS: All patients were used at each focal hospital, and we found the 10 closest matched patients from control hospitals with exactly the same principal procedure as each focal patient. PRINCIPAL FINDINGS: We achieved exact matches on all procedures and very close matches for other patient characteristics for both hospitals. There were few to no differences between each hospital's patients and their matched control patients on most patient characteristics, yet large and significant differences were observed for mortality, failure-to-rescue, and cost. CONCLUSION: Indirect standardization matching can produce fair audits of quality and cost, allowing for a comprehensive, transparent, and relevant assessment of all patients at a focal hospital. With this approach, hospitals will be better able to benchmark their performance and determine where quality improvement is most needed.

Template matching for auditing hospital cost and quality.

OBJECTIVE: Develop an improved method for auditing hospital cost and quality. DATA SOURCES/SETTING: Medicare claims in general, gynecologic and urologic surgery, and orthopedics from Illinois, Texas, and New York between 2004 and 2006. STUDY DESIGN: A template of 300 representative patients was constructed and then used to match 300 patients at hospitals that had a minimum of 500 patients over a 3-year study period. DATA COLLECTION/EXTRACTION METHODS: From each of 217 hospitals we chose 300 patients most resembling the template using multivariate matching. PRINCIPAL FINDINGS: The matching algorithm found close matches on procedures and patient characteristics, far more balanced than measured covariates would be in a randomized clinical trial. These matched samples displayed little to no differences across hospitals in common patient characteristics yet found large and statistically significant hospital variation in mortality, complications, failure-to-rescue, readmissions, length of stay, ICU days, cost, and surgical procedure length. Similar patients at different hospitals had substantially different outcomes. CONCLUSION: The template-matched sample can produce fair, directly standardized audits that evaluate hospitals on patients with similar characteristics, thereby making benchmarking more believable. Through examining matched samples of individual patients, administrators can better detect poor performance at their hospitals and better understand why these problems are occurring.

A hospital-specific template for benchmarking its cost and quality.

OBJECTIVE: Develop an improved method for auditing hospital cost and quality tailored to a specific hospital's patient population. DATA SOURCES/SETTING: Medicare claims in general, gynecologic and urologic surgery, and orthopedics from Illinois, New York, and Texas between 2004 and 2006. STUDY DESIGN: A template of 300 representative patients from a single index hospital was constructed and used to match 300 patients at 43 hospitals that had a minimum of 500 patients over a 3-year study period. DATA COLLECTION/EXTRACTION METHODS: From each of 43 hospitals we chose 300 patients most resembling the template using multivariate matching. PRINCIPAL FINDINGS: We found close matches on procedures and patient characteristics, far more balanced than would be expected in a randomized trial. There were little to no differences between the index hospital's template and the 43 hospitals on most patient characteristics yet large and significant differences in mortality, failure-to-rescue, and cost. CONCLUSION: Matching can produce fair, directly standardized audits. From the perspective of the index hospital, "hospital-specific" template matching provides the fairness of direct standardization with the specific institutional relevance of indirect standardization. Using this approach, hospitals will be better able to examine their performance, and better determine why they are achieving the results they observe.

The Hospital Compare mortality model and the volume-outcome relationship.

OBJECTIVE: We ask whether Medicare's Hospital Compare random effects model correctly assesses acute myocardial infarction (AMI) hospital mortality rates when there is a volume-outcome relationship. DATA SOURCES/STUDY SETTING: Medicare claims on 208,157 AMI patients admitted in 3,629 acute care hospitals throughout the United States. STUDY DESIGN: We compared average-adjusted mortality using logistic regression with average adjusted mortality based on the Hospital Compare random effects model. We then fit random effects models with the same patient variables as in Medicare's Hospital Compare mortality model but also included terms for hospital Medicare AMI volume and another model that additionally included other hospital characteristics. PRINCIPAL FINDINGS: Hospital Compare's average adjusted mortality significantly underestimates average observed death rates in small volume hospitals. Placing hospital volume in the Hospital Compare model significantly improved predictions. CONCLUSIONS: The Hospital Compare random effects model underestimates the typically poorer performance of low-volume hospitals. Placing hospital volume in the Hospital Compare model, and possibly other important hospital characteristics, appears indicated when using a random effects model to predict outcomes. Care must be taken to insure the proper method of reporting such models, especially if hospital characteristics are included in the random effects model.

Recovery preference exploration: analysis of patient feedback after imagined scenarios.

OBJECTIVE: To present a new assessment approach, referred to as recovery preference exploration (RPE), for exploring the personal meaning of functional loss and recovery. RPE determines how people would choose to recover from profound disability if they could control that recovery. DESIGN: Twenty-six patients with a variety of medical conditions and one or more limitations in the functions being addressed were recruited from an inner-city ambulatory care clinic. The patients imagined recovery from 15 functional limitations, beginning with severe problems in all functions and ending with complete independence. Individual-specific preferences for recovery in each function were calculated relative to the other 14 and were submitted for principal components analyses. RESULTS: Imagined difficulty in toileting and with depression were most troubling. Principal components analyses identified trade-off choices among domains of physical, psychological, and social functioning. Some people valued physical independence above psychological well-being or social abilities. Others had opposite patterns. Patients' narrative explanations, when triangulated, were consistent with their preferences. CONCLUSION: RPE makes visible the highly personal nature of feelings about ability and disability. Our results may help guide the selection of rehabilitation interventions in ambulatory care.

Does ovarian cancer treatment and survival differ by the specialty providing chemotherapy?

PURPOSE: Chemotherapy for ovarian cancer is usually administered by medical oncologists (MOs) or gynecologic oncologists (GOs). GOs perform a broad spectrum of surgical and medical activities while managing a limited number of diseases; MOs specialize in the administration of chemotherapy but manage a broad array of diseases. We asked whether survival, treatment, and toxicity differed according to the type of specialist providing the chemotherapy after surgery. PATIENTS AND METHODS: Using Surveillance, Epidemiology, and End Results (SEER)--Medicare data for patients 65 years old from 1991 through 2001 from eight SEER sites, we identified 344 patients with ovarian cancer who were treated with chemotherapy by a GO after surgery. Using optimal matching and propensity scores based on 36 characteristics, we matched these patients to 344 similar patients who were operated on and staged by the same type of surgeon but who received chemotherapy from an MO. RESULTS: MOs administered chemotherapy over more weeks than did the GOs (16.5 v 12.1 weeks, respectively; P < .0023), and MO patients had substantially more weeks that included chemotherapy-associated adverse events than GO patients (16.2 v 8.9 weeks, respectively; P < .0001). However, there was no difference in 5-year survival rate between the GO and MO groups (35% v 34%, respectively; P = .45). CONCLUSION: GO- and MO-treated patients who were closely matched on prognostic characteristics experienced very different rates of chemotherapy-associated adverse events and very different chemotherapy treatment styles by specialty type; however, their survival was virtually identical.