Krumholz, Harlan; MD, SM; Lin, Zhenqiu; Keenan, Patricia; PhD, MHS; Chen, Jersey; MD, MPH; Ross, Joseph; MD, MHS; Drye, Elizabeth; MD, SM; Bernheim, Susannah; MD, MHS; Wang, Yun; Bradley, Elizabeth; Han, Lein; Normand, Sharon-Lise JAMA. 309(6): , February 13, DOI: /jama RELATIONSHIP BETWEEN HOSPITAL READMISSION AND MORTALITY RATES FOR PATIENTS HOSPITALIZED WITH ACUTE MYOCARDIAL INFARCTION, HEART FAILURE, OR PNEUMONIA

WHY THIS PAPER? PhD: Care transitions for older adults post hospital admission RCT in a residential TC setting Health literacy and SDM intervention (enhanced patient and carer involvement in decisions about care transitions)  Based on Coleman’s work – reducing risks assoc. with care transitions (adverse drug events, readmission, poor information transfer) through ‘coaching’ patient and carer and a patient held medical record  Delivered via family meetings with a geriatrician and specialist aged care nurse  Utilised QPL, audio-recording and telephone call post discharge  Experience was of high return to hospital rate and mortality within 12 months of entry to study. General Practice: DVA Coordinated Veteran’s Care Program  Targets older veterans with one or more of: HF, Pneumonia, Coronary Artery Disease, Diabetes and COPD who have complex care needs  Intervention is care coordinator as well as assessment and care planning  Care coordinator role encompasses CDSMS, coaching, information transfer between health professionals,

BACKGROUND Measuring outcomes of care is important  CMS began publicly reporting hospital 30-day, all-cause, risk-standardised mortality rates (RSMRs) for AMI and HF in 2007; pneumonia in 2008  In June 2009, public reporting expanded to include hospital 30-day, all-cause, risk- standardised readmission rates (RSRRs)  Mortality and readmission rates proposed for use in federal programs to modify hospital payments based on performance We need to understand the relationship between mortality and readmission rates  If the measures have a strong positive association, there may be redundancy  Need to investigate concerns about an inverse relationship between the measures (concern that interventions that reduce mortality may also increase readmission by resulting in a higher risk group being discharged from hospital)

THE CONTEXT  In the US, nearly one in five Medicare patients is readmitted to a hospital within 30 days of discharge at a cost of $17.5 billion  Safety-net hospitals treat large numbers of poor patients with limited access to primary and follow-up care  Hospital Readmissions Reduction Program (HRRP) commenced 1 Oct 2012  ~ 2/3rds of US hospitals will receive penalties of up to 1% of reimbursement for Medicare fee-for-service patients in 2013 fiscal year 1 ; increasing to 3% by 2015  Hospitals that care for medically complex or socioeconomically vulnerable patients (large teaching hospitals and safety-net hospitals) will be disadvantaged 2.  1 Joynt KE, Jha AK. A Path Forward on Medicare Readmissions. NEJM Mar 6.  2 Joynt KE, Jha AK. Characteristics of hospitals receiving penalties under the Hospital Readmissions Reduction Program. JAMA Jan 23;309(4):342-3.

PREVIOUS STUDIES At the patient level  In a study of VA hospitals from 2002 to 2006, Heidenreich et al. (2010) reported a decline in 30-day mortality following an admission for HF and an increase in 30-day readmission for HF. Odds ratios for outcomes were adjusted for patient demographics, diagnoses within the past year, laboratory data, and for clustering of patients within hospitals. At the hospital level  Using data from the CMS Hospital Compare public reporting database, Gorodeski et al. (2010) identified a potential concern in the relationship between RSMR and RSRR for patients with HF.

STUDY AIMS 1.To investigate the association between hospital-level 30-day RSMRs and RSRRs for Medicare beneficiaries admitted with AMI, HF or pneumonia. 2.To further determine the relationship between RSMRs and RSRRs for subgroups of hospitals to evaluate if the relationships varied systematically. Subgroups based on safety net status, urban-rural location, teaching status as well as ownership status

DESIGN, SETTING AND PARTICIPANTS Medicare fee-for-service beneficiaries (65+) discharged with AMI, HF or pneumonia between July 1, 2005, and June 30, hospitals for AMI 4767 hospitals for HF 4811 hospitals for pneumonia Stratified sample by hospital region, safety-net status and urban or rural status

STATISTICAL ANALYSIS  Hierarchical logistic regression models to estimate RSMRs and RSRRs for each hospital; adjusted for age, sex, clinical covariates (numerous) and clustering of patients within the same hospital  Calculated means and distributions of hospital RSMRs and RSRRs  Quantified the linear and nonlinear relationship between RSMR and RSRR using Pearson correlation (weighted by RSMR and RSRR volume) and generalized additive models  Stratified correlations by hospital characteristics  For each condition (AMI, HF and pneumonia), classified all hospitals according to their placement within quartiles for both RSMR and RSRR and determined the proportion of hospitals with better and worse performance on both measures.

2 Figure. Scatterplot of Hospital-Level RSMRs and RSRRs for AMI, HF and Pneumonia Blue lines are the cubic spline smooth regression lines with RSRR as the dependent variable and RSMR as the independent variable. Tinted areas around the cubic spline regression lines indicate 95% confidence bands. Acute myocardial infarction Heart failure Pneumonia Mortality Readmission 11%

AUTHORS’ COMMENTS  Failed to find evidence that a hospital's performance on the measure for 30-day RSMR is strongly associated with performance on 30-day RSRR.  For AMI and pneumonia, there was no discernible relationship, and for HF, the relationship was only modest and not throughout the entire range of performance.  At all levels of performance on the mortality measures, both high and low performers on the readmission measures were found.  From a policy perspective, the independence of the measures is important. A strong inverse relationship might have implied that institutions would need to choose which measure to address (mortality or readmisison).

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