Jacqueline N. Grady

National Patterns of Risk-Standardized Mortality and Readmission for Acute Myocardial Infarction and Heart Failure: Update on Publicly Reported Outcomes Measures Based on the 2010 Release

Background—Patient outcomes provide a critical perspective on quality of care. The Centers for Medicare and Medicaid Services (CMS) is publicly reporting hospital 30-day risk-standardized mortality rates (RSMRs) and risk-standardized readmission rates (RSRRs) for patients hospitalized with acute myocardial infarction (AMI) and heart failure (HF). We provide a national perspective on hospital performance for the 2010 release of these measures. Methods and Results—The hospital RSMRs and RSRRs are calculated from Medicare claims data for fee-for-service Medicare beneficiaries, 65 years or older, hospitalized with AMI or HF between July 1, 2006, and June 30, 2009. The rates are calculated using hierarchical logistic modeling to account for patient clustering, and are risk-adjusted for age, sex, and patient comorbidities. The median RSMR for AMI was 16.0% and for HF was 10.8%. Both measures had a wide range of hospital performance with an absolute 5.2% difference between hospitals in the 5th versus 95th percentile for AMI and 5.0% for HF. The median RSRR for AMI was 19.9% and for HF was 24.5% (3.9% range for 5th to 95th percentile for AMI, 6.7% for HF). Distinct regional patterns were evident for both measures and both conditions. Conclusions—High RSRRs persist for AMI and HF and clinically meaningful variation exists for RSMRs and RSRRs for both conditions. Our results suggest continued opportunities for improvement in patient outcomes for HF and AMI.

Burden of Illness Score for Elderly Persons: Risk adjustment incorporating the cumulative impact of diseases, physiologic abnormalities, and functional impairments

Background/Objectives. To develop and validate a new risk adjustment index–the Burden of Illness Score for Elderly Persons (BISEP)–which integrates multiple domains, including diseases, physiologic abnormalities, and functional impairments. Research Design Subjects. The index was developed in a prospective cohort of 525 patients aged ≥70 years from the medicine service of a university hospital. The index was validated in a cohort of 1246 patients aged ≥65 years from 27 hospitals. The outcome was 1-year mortality. Results. Five risk factors were selected from diagnosis, laboratory, and functional status axes: high-risk diagnoses, albumin ≤3.5 mg/dL, creatinine >1.5 mg/dL, dementia, and walking impairment. The BISEP score (range 0–7) created four groups of increasing risk: group I (score 0–1), group II (2), group III (3), and group IV (≥4). In the development cohort, where overall mortality was 154/525 (29%), 1-year mortality rates increased significantly across each risk group, from 8% to 24%, 51%, and 74%, in groups I to IV respectively (&khgr;2 trend, P = 0.001)—an overall 17-fold increased risk by hazard ratio. The c-statistic for the final model was 0.83. Corresponding rates in the validation cohort, where overall mortality was 488/1246 (39%), were 5%, 17%, 33%, and 61% in groups I to IV, respectively (&khgr;2 trend, P = 0.001)—an overall 18-fold increased risk by hazard ratio. The c-statistic for the final model was 0.77. In each cohort, sequential addition of variables from different sources (eg, administrative, laboratory, and chart) substantially improved model fit and predictive accuracy. BISEP had significantly superior mortality prediction compared with five widely used measures. Conclusions. BISEP provides a useful new risk adjustment system for hospitalized older persons. Although index performance using different data sources has been evaluated, the full BISEP model, incorporating disease, laboratory, and functional impairment information, demonstrates the best performance.

The performance of US hospitals as reflected in risk-standardized 30-day mortality and readmission rates for medicare beneficiaries with pneumonia†‡

BACKGROUND Pneumonia is a leading cause of hospitalization and death in the elderly, and remains the subject of both local and national quality improvement efforts. OBJECTIVE To describe patterns of hospital and regional performance in the outcomes of elderly patients with pneumonia. DESIGN Cross-sectional study using hospital and outpatient Medicare claims between 2006 and 2009. SETTING A total of 4,813 nonfederal acute care hospitals in the United States and its organized territories. PATIENTS Hospitalized fee-for-service Medicare beneficiaries age 65 years and older who received a principal diagnosis of pneumonia. INTERVENTION None. MEASUREMENTS Hospital and regional level risk-standardized 30-day mortality and readmission rates. RESULTS Of the 1,118,583 patients included in the mortality analysis 129,444 (11.6%) died within 30 days of hospital admission. The median (Q1, Q3) hospital 30-day risk-standardized mortality rate for patients with pneumonia was 11.1% (10.0%, 12.3%), and despite controlling for differences in case mix, ranged from 6.7% to 20.9%. Among the 1,161,817 patients included in the readmission analysis 212,638 (18.3%) were readmitted within 30 days of hospital discharge. The median (Q1, Q3) 30-day risk-standardized readmission rate was 18.2% (17.2%, 19.2%) and ranged from 13.6% to 26.7%. Risk-standardized mortality rates varied across hospital referral regions from a high of 14.9% to a low of 8.7%. Risk-standardized readmission rates varied across hospital referral regions from a high of 22.2% to a low of 15%. CONCLUSIONS Risk-standardized 30-day mortality and, to a lesser extent, readmission rates for patients with pneumonia vary substantially across hospitals and regions and may present opportunities for quality improvement, especially at low performing institutions and areas.

The Effect of a Multifaceted Physician Office‐Based Intervention on Older Women's Mammography Use

BACKGROUND: In response to identified low mammography use among older women in three geographic areas in Connecticut, a physician office‐based mammography intervention was initiated under the Health Care Financing Administrations Health Care Quality Improvement Program.

National Patterns of Risk-Standardized Mortality and Readmission After Hospitalization for Acute Myocardial Infarction, Heart Failure, and Pneumonia: Update on Publicly Reported Outcomes Measures Based on the 2013 Release

ABSTRACTBACKGROUNDThe Centers for Medicare & Medicaid Services publicly reports risk-standardized mortality rates (RSMRs) within 30-days of admission and, in 2013, risk-standardized unplanned readmission rates (RSRRs) within 30-days of discharge for patients hospitalized with acute myocardial infarction (AMI), heart failure (HF), and pneumonia. Current publicly reported data do not focus on variation in national results or annual changes.OBJECTIVEDescribe U.S. hospital performance on AMI, HF, and pneumonia mortality and updated readmission measures to provide perspective on national performance variation.DESIGNTo identify recent changes and variation in national hospital-level mortality and readmission for AMI, HF, and pneumonia, we performed cross-sectional panel analyses of national hospital performance on publicly reported measures.PARTICIPANTSFee-for-service Medicare and Veterans Health Administration beneficiaries, 65 years or older, hospitalized with principal discharge diagnoses of AMI, HF, or pneumonia between July 2009 and June 2012. RSMRs/RSRRs were calculated using hierarchical logistic models risk-adjusted for age, sex, comorbidities, and patients’ clustering among hospitals.ResultsMedian (range) RSMRs for AMI, HF, and pneumonia were 15.1% (9.4–21.0%), 11.3% (6.4–17.9%), and 11.4% (6.5–24.5%), respectively. Median (range) RSRRs for AMI, HF, and pneumonia were 18.2% (14.4–24.3%), 22.9% (17.1–30.7%), and 17.5% (13.6–24.0%), respectively. Median RSMRs declined for AMI (15.5% in 2009–2010, 15.4% in 2010–2011, 14.7% in 2011–2012) and remained similar for HF (11.5% in 2009–2010, 11.9% in 2010–2011, 11.7% in 2011–2012) and pneumonia (11.8% in 2009–2010, 11.9% in 2010–2011, 11.6% in 2011–2012). Median hospital-level RSRRs declined: AMI (18.5% in 2009–2010, 18.5% in 2010–2011, 17.7% in 2011–2012), HF (23.3% in 2009–2010, 23.1% in 2010–2011, 22.5% in 2011–2012), and pneumonia (17.7% in 2009–2010, 17.6% in 2010–2011, 17.3% in 2011–2012).ConclusionsWe report the first national unplanned readmission results demonstrating declining rates for all three conditions between 2009–2012. Simultaneously, AMI mortality continued to decline, pneumonia mortality was stable, and HF mortality experienced a small increase.

Development and Validation of an Algorithm to Identify Planned Readmissions From Claims Data.

BACKGROUND It is desirable not to include planned readmissions in readmission measures because they represent deliberate, scheduled care. OBJECTIVES To develop an algorithm to identify planned readmissions, describe its performance characteristics, and identify improvements. DESIGN Consensus-driven algorithm development and chart review validation study at 7 acute-care hospitals in 2 health systems. PATIENTS For development, all discharges qualifying for the publicly reported hospital-wide readmission measure. For validation, all qualifying same-hospital readmissions that were characterized by the algorithm as planned, and a random sampling of same-hospital readmissions that were characterized as unplanned. MEASUREMENTS We calculated weighted sensitivity and specificity, and positive and negative predictive values of the algorithm (version 2.1), compared to gold standard chart review. RESULTS In consultation with 27 experts, we developed an algorithm that characterizes 7.8% of readmissions as planned. For validation we reviewed 634 readmissions. The weighted sensitivity of the algorithm was 45.1% overall, 50.9% in large teaching centers and 40.2% in smaller community hospitals. The weighted specificity was 95.9%, positive predictive value was 51.6%, and negative predictive value was 94.7%. We identified 4 minor changes to improve algorithm performance. The revised algorithm had a weighted sensitivity 49.8% (57.1% at large hospitals), weighted specificity 96.5%, positive predictive value 58.7%, and negative predictive value 94.5%. Positive predictive value was poor for the 2 most common potentially planned procedures: diagnostic cardiac catheterization (25%) and procedures involving cardiac devices (33%). CONCLUSIONS An administrative claims-based algorithm to identify planned readmissions is feasible and can facilitate public reporting of primarily unplanned readmissions.

Screening Mammography: Is It Suitably Targeted to Older Women Who are Most Likely to Benefit?

OBJECTIVES To determine whether screening mammography is suitably targeted to older women who are most likely to benefit. DESIGN Prospective cohort study. SETTING New Haven County, Connecticut. PARTICIPANTS Eight hundred forty-four community-dwelling older women were interviewed as part of the 1990 New Haven Established Populations for the Epidemiologic Study of the Elderly (EPESE) program. MEASUREMENTS Mammography use was ascertained from Medicare Part B claims data. A four-level prognostic mortality index was developed using items previously shown to be predictive of mortality. Mammography use and all-cause mortality were evaluated by prognostic stage over a 5-year period, January 1, 1991, to December 31, 1995. RESULTS Five-year mortality increased steadily with each prognostic stage (12% to 68%, P = .001), whereas the 5-year mammography use rate declined (48% to 7%, P = .001). Over half the women (53%) in the most favorable prognostic group did not receive a mammogram, whereas 13% in the two worst prognostic groups received at least one mammogram. CONCLUSION Screening mammography may be underutilized among older women who are the most likely to benefit and overutilized among those who are unlikely to benefit.

Hospital Characteristics Associated With Risk-standardized Readmission Rates

Background: Safety-net and teaching hospitals are somewhat more likely to be penalized for excess readmissions, but the association of other hospital characteristics with readmission rates is uncertain and may have relevance for hospital-centered interventions. Objective: To examine the independent association of 8 hospital characteristics with hospital-wide 30-day risk-standardized readmission rate (RSRR). Design: This is a retrospective cross-sectional multivariable analysis. Subjects: US hospitals. Measures: Centers for Medicare and Medicaid Services specification of hospital-wide RSRR from July 1, 2013 through June 30, 2014 with race and Medicaid dual-eligibility added. Results: We included 6,789,839 admissions to 4474 hospitals of Medicare fee-for-service beneficiaries aged over 64 years. In multivariable analyses, there was regional variation: hospitals in the mid-Atlantic region had the highest RSRRs [0.98 percentage points higher than hospitals in the Mountain region; 95% confidence interval (CI), 0.84–1.12]. For-profit hospitals had an average RSRR 0.38 percentage points (95% CI, 0.24–0.53) higher than public hospitals. Both urban and rural hospitals had higher RSRRs than those in medium metropolitan areas. Hospitals without advanced cardiac surgery capability had an average RSRR 0.27 percentage points (95% CI, 0.18–0.36) higher than those with. The ratio of registered nurses per hospital bed was not associated with RSRR. Variability in RSRRs among hospitals of similar type was much larger than aggregate differences between types of hospitals. Conclusions: Overall, larger, urban, academic facilities had modestly higher RSRRs than smaller, suburban, community hospitals, although there was a wide range of performance. The strong regional effect suggests that local practice patterns are an important influence. Disproportionately high readmission rates at for-profit hospitals may highlight the role of financial incentives favoring utilization.

Trends in readmission rates for safety net hospitals and non-safety net hospitals in the era of the US Hospital Readmission Reduction Program: a retrospective time series analysis using Medicare administrative claims data from 2008 to 2015

Objective To compare trends in readmission rates among safety net and non-safety net hospitals under the US Hospital Readmission Reduction Program (HRRP). Design A retrospective time series analysis using Medicare administrative claims data from January 2008 to June 2015. Setting We examined 3254 US hospitals eligible for penalties under the HRRP, categorised as safety net or non-safety net hospitals based on the hospital’s proportion of patients with low socioeconomic status. Participants Admissions for Medicare fee-for-service patients, age ≥65 years, discharged alive, who had a valid five-digit zip code and did not have a principal discharge diagnosis of cancer or psychiatric illness were included, for a total of 52 516 213 index admissions. Primary and secondary outcome measures Mean hospital-level, all-condition, 30-day risk-adjusted standardised unplanned readmission rate, measured quarterly, along with quarterly rate of change, and an interrupted time series examining: April–June 2010, after HRRP was passed, and October–December 2012, after HRRP penalties were implemented. Results 58.0% (SD 15.3) of safety net hospitals and 17.1% (SD 10.4) of non-safety net hospitals’ patients were in the lowest quartile of socioeconomic status. The mean safety net hospital standardised readmission rate declined from 17.0% (SD 3.7) to 13.6% (SD 3.6), whereas the mean non-safety net hospital declined from 15.4% (SD 3.0) to 12.7% (SD 2.5). The absolute difference in rates between safety net and non-safety net hospitals declined from 1.6% (95% CI 1.3 to 1.9) to 0.9% (0.7 to 1.2). The quarterly decline in standardised readmission rates was 0.03 percentage points (95% CI 0.03 to 0.02, p<0.001) greater among safety net hospitals over the entire study period, and no differential change among safety net and non-safety net hospitals was found after either HRRP was passed or penalties enacted. Conclusions Since HRRP was passed and penalties implemented, readmission rates for safety net hospitals have decreased more rapidly than those for non-safety net hospitals.

Variation in the Diagnosis of Aspiration Pneumonia and Association with Hospital Pneumonia Outcomes

Rationale: National efforts to compare hospital outcomes for patients with pneumonia may be biased by hospital differences in diagnosis and coding of aspiration pneumonia, a condition that has traditionally been excluded from pneumonia outcome measures. Objectives: To evaluate the rationale and impact of including patients with aspiration pneumonia in hospital mortality and readmission measures. Methods: Using Medicare fee‐for‐service claims for patients 65 years and older from July 2012 to June 2015, we characterized the proportion of hospitals’ patients with pneumonia diagnosed with aspiration pneumonia, calculated hospital‐specific risk‐standardized rates of 30‐day mortality and readmission for patients with pneumonia, analyzed the association between aspiration pneumonia coding frequency and these rates, and recalculated these rates including patients with aspiration pneumonia. Results: A total of 1,101,892 patients from 4,263 hospitals were included in the mortality measure analysis, including 192,814 with aspiration pneumonia. The median proportion of hospitals’ patients with pneumonia diagnosed with aspiration pneumonia was 13.6% (10th‐90th percentile, 4.2‐26%). Hospitals with a higher proportion of patients with aspiration pneumonia had lower risk‐standardized mortality rates in the traditional pneumonia measure (12.0% in the lowest coding and 11.0% in the highest coding quintiles) and were far more likely to be categorized as performing better than the national mortality rate; expanding the measure to include patients with aspiration pneumonia attenuated the association between aspiration pneumonia coding rate and hospital mortality. These findings were less pronounced for hospital readmission rates. Conclusions: Expanding the pneumonia cohorts to include patients with a principal diagnosis of aspiration pneumonia can overcome bias related to variation in hospital coding.