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Patterns of Readmissions for Three Common Conditions Among Younger US Adults

  • Devraj Sukul
    Correspondence
    Requests for reprints should be addressed to Devraj Sukul, MD, University of Michigan Samuel and Jean Frankel Cardiovascular Center, 1500 E. Medical Center Drive, SPC 5853, Ann Arbor, MI 48109-5853.
    Affiliations
    Division of Cardiovascular Medicine, Samuel and Jean Frankel Cardiovascular Center, University of Michigan, Ann Arbor
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  • Shashank S. Sinha
    Affiliations
    Division of Cardiovascular Medicine, Samuel and Jean Frankel Cardiovascular Center, University of Michigan, Ann Arbor

    Michigan Integrated Center for Health Analytics and Medical Prediction, Department of Internal Medicine, University of Michigan Medical School, Ann Arbor

    Michigan Center for Integrative Research in Critical Care, University of Michigan, Ann Arbor

    Institute for Healthcare Policy and Innovation, University of Michigan, Ann Arbor
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  • Andrew M. Ryan
    Affiliations
    Institute for Healthcare Policy and Innovation, University of Michigan, Ann Arbor

    Department of Health Management and Policy, University of Michigan School of Public Health, Ann Arbor
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  • Michael W. Sjoding
    Affiliations
    Michigan Integrated Center for Health Analytics and Medical Prediction, Department of Internal Medicine, University of Michigan Medical School, Ann Arbor

    Michigan Center for Integrative Research in Critical Care, University of Michigan, Ann Arbor

    Institute for Healthcare Policy and Innovation, University of Michigan, Ann Arbor

    Division of Pulmonary and Critical Care Medicine, University of Michigan, Ann Arbor
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  • Scott L. Hummel
    Affiliations
    Division of Cardiovascular Medicine, Samuel and Jean Frankel Cardiovascular Center, University of Michigan, Ann Arbor

    Center for Clinical Management Research, Ann Arbor Veterans Affairs Healthcare System, Mich
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  • Brahmajee K. Nallamothu
    Affiliations
    Division of Cardiovascular Medicine, Samuel and Jean Frankel Cardiovascular Center, University of Michigan, Ann Arbor

    Michigan Integrated Center for Health Analytics and Medical Prediction, Department of Internal Medicine, University of Michigan Medical School, Ann Arbor

    Michigan Center for Integrative Research in Critical Care, University of Michigan, Ann Arbor

    Institute for Healthcare Policy and Innovation, University of Michigan, Ann Arbor

    Center for Clinical Management Research, Ann Arbor Veterans Affairs Healthcare System, Mich
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      Abstract

      Background

      Thirty-day readmissions among elderly Medicare patients are an important hospital quality measure. Although plans for using 30-day readmission measures are under consideration for younger patients, little is known about readmission in younger patients or the relationship between readmissions in younger and elderly patients at the same hospital.

      Methods

      By using the 2014 Nationwide Readmissions Database, we examined readmission patterns in younger patients (18-64 years) using hierarchical models to evaluate associations between hospital 30-day, risk-standardized readmission rates in elderly Medicare patients and readmission risk in younger patients with acute myocardial infarction, heart failure, or pneumonia.

      Results

      There were 87,818, 98,315, and 103,251 admissions in younger patients for acute myocardial infarction, heart failure, and pneumonia, respectively, with overall 30-day unplanned readmission rates of 8.5%, 21.4%, and 13.7%, respectively. Readmission risk in younger patients was significantly associated with hospital 30-day risk-standardized readmission rates for elderly Medicare patients for all 3 conditions. A decrease in an average hospital's 30-day, risk-standardized readmission rates from the 75th percentile to the 25th percentile was associated with reduction in younger patients' risk of readmission from 8.8% to 8.0% (difference: 0.7%; 95% confidence interval, 0.5-0.9) for acute myocardial infarction; 21.8% to 20.0% (difference: 1.8%; 95% confidence interval, 1.4-2.2) for heart failure; and 13.9% to 13.1% (difference: 0.8%; 95% confidence interval, 0.5-1.0) for pneumonia.

      Conclusions

      Among younger patients, readmission risk was moderately associated with hospital 30-day, risk-standardized readmission rates in elderly Medicare beneficiaries. Efforts to reduce readmissions among older patients may have important areas of overlap with younger patients, although further research may be necessary to identify specific mechanisms to tailor initiatives to younger patients.

      Keywords

      Clinical Significance
      • The 30-day readmission rate for younger patients was 8.5% for acute myocardial infarction, 21.4% for heart failure, and 13.7% for pneumonia.
      • Readmission risk in younger patients was associated with hospital 30-day, risk-standardized readmission rates among elderly Medicare patients for all 3 conditions.
      • Efforts to reduce readmissions among older patients may overlap with younger patients.
      Hospital readmissions are common,
      • Lindenauer P.K.
      • Bernheim S.M.
      • Grady J.N.
      • et al.
      The performance of US hospitals as reflected in risk-standardized 30-day mortality and readmission rates for Medicare beneficiaries with pneumonia.
      • Bernheim S.M.
      • Grady J.N.
      • Lin Z.
      • et al.
      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.
      • Ross J.S.
      • Chen J.
      • Lin Z.
      • et al.
      Recent national trends in readmission rates after heart failure hospitalization.
      expensive,
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      • Singh V.
      • Satija V.
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      Containing the cost of heart failure management: a focus on reducing readmissions.
      • Barrett M.L.
      • Wier L.M.
      • Jiang H.J.
      • Steiner C.A.
      and associated with adverse outcomes. Approximately 1 in 5 elderly Medicare beneficiaries are readmitted within 30 days at a cost of more than $17 billion annually,
      • Jencks S.F.
      • Williams M.V.
      • Coleman E.A.
      Rehospitalizations among patients in the Medicare fee-for-service program.
      making efforts to reduce readmissions a national priority. The Centers for Medicare & Medicaid Services (CMS) publicly reports hospital 30-day, risk-standardized readmission rates (RSRRs) as a measure of hospital quality.
      • Trimarchi S.
      • Smith D.E.
      • Share D.
      • et al.
      Retroperitoneal hematoma after percutaneous coronary intervention: prevalence, risk factors, management, outcomes, and predictors of mortality: a report from the BMC2 (Blue Cross Blue Shield of Michigan Cardiovascular Consortium) registry.
      The Patient Protection and Affordable Care Act created the Hospital Readmissions Reduction Program (HRRP), which financially penalizes hospitals with higher than expected readmission rates.
      Centers for Medicare & Medicaid Services
      FY 2013 and FY 2014 IPPS final rules: Hospital Readmission Reduction Program supplemental data files.
      • Miller L.W.
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      Patient selection for ventricular assist devices: a moving target.
      Given their associated disease burden and costs,
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      • et al.
      Writing Group Members
      Heart Disease and Stroke Statistics-2016 Update: a report from the American Heart Association.
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      • et al.
      Long-term trends in myocardial infarction incidence and case fatality in the National Heart, Lung, and Blood Institute's Framingham Heart study.
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      • Go A.S.
      Population trends in the incidence and outcomes of acute myocardial infarction.
      • Mosterd A.
      • Hoes A.W.
      Clinical epidemiology of heart failure.
      • Roger V.L.
      Epidemiology of heart failure.
      3 common conditions have been the focus of these programs: acute myocardial infarction, heart failure, and pneumonia. Extensive research has attempted to better understand and prevent readmissions in elderly Medicare beneficiaries for these conditions.
      • Krumholz H.M.
      • Lin Z.
      • Keenan P.S.
      • et al.
      Relationship between hospital readmission and mortality rates for patients hospitalized with acute myocardial infarction, heart failure, or pneumonia.
      • Krumholz H.M.
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      • Schone E.M.
      • et al.
      Patterns of hospital performance in acute myocardial infarction and heart failure 30-day mortality and readmission.
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      Quality of care for elderly patients hospitalized with heart failure.
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      The three-phase terrain of heart failure readmissions.
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      Rehospitalization for heart failure: predict or prevent?.
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      Overcoming the pricing power of hospitals.
      • Krumholz H.M.
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      • Drye E.E.
      • et al.
      An administrative claims measure suitable for profiling hospital performance based on 30-day all-cause readmission rates among patients with acute myocardial infarction.
      • Keenan P.S.
      • Normand S.L.
      • Lin Z.
      • et al.
      An administrative claims measure suitable for profiling hospital performance on the basis of 30-day all-cause readmission rates among patients with heart failure.
      • Lindenauer P.K.
      • Normand S.L.
      • Drye E.E.
      • et al.
      Development, validation, and results of a measure of 30-day readmission following hospitalization for pneumonia.
      Although hospital readmissions have been extensively studied in the elderly Medicare population, readmissions are common among nonelderly adult patients. Younger patients are readmitted approximately 2 million times annually, which is similar in number to elderly Medicare beneficiaries.
      • Barrett M.L.
      • Wier L.M.
      • Jiang H.J.
      • Steiner C.A.
      However, overall patterns of and factors associated with hospital readmission in younger patients thus far have been examined using only single state inpatient data.
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      • Wang Y.
      • Dharmarajan K.
      • Hsieh A.F.
      • Bernheim S.M.
      • Krumholz H.M.
      Readmissions after hospitalization for heart failure, acute myocardial infarction, or pneumonia among young and middle-aged adults: a retrospective observational cohort study.
      • Dreyer R.P.
      • Ranasinghe I.
      • Wang Y.
      • et al.
      Sex differences in the rate, timing, and principal diagnoses of 30-day readmissions in younger patients with acute myocardial infarction.
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      • Olsen M.A.
      • Bommarito K.
      • et al.
      All-payer analysis of heart failure hospitalization 30-day readmission: comorbidities matter.
      Broader knowledge of readmissions among a nationally representative cohort of younger patients with acute myocardial infarction, heart failure, and pneumonia may help tailor specific clinical and policy interventions. This is essential as commercial insurers and Medicaid programs begin to roll out initiatives to reduce readmissions in this population.
      • Bongiovanni D.
      Readmissions penalties: are commercial payors following Medicare's lead?.
      Furthermore, it would be valuable to understand whether younger patients discharged from hospitals with lower readmission rates for elderly Medicare beneficiaries are at lower risk of readmission. If such an association exists, it would suggest that common strategies could be used to reduce readmission rates for both groups.
      We used the 2014 Nationwide Readmissions Database (NRD) to evaluate all-cause unplanned readmissions within 30 days in younger patients aged 18 to 64 years after hospitalization for acute myocardial infarction, heart failure, and pneumonia. Our objectives were to determine the timing and causes of readmission for 3 publicly reported conditions for younger patients in the United States and to assess whether the risk of readmission in younger patients is associated with readmission rates among elderly Medicare beneficiaries.

      Materials and Methods

      Data Source

      We used data from the Nationwide Readmissions Database (NRD) developed by the Agency for Healthcare Research and Quality's Healthcare Cost and Utilization Project. The NRD contains data on all-payer inpatient stays by compiling information from the Agency for Healthcare Research and Quality's Healthcare Cost and Utilization Project State Inpatient Databases.
      • Barrett M.L.
      • Wier L.M.
      • Jiang H.J.
      • Steiner C.A.
      The 2014 NRD was constructed from 22 geographically dispersed states. In the unweighted sample, the 2014 NRD represents 51.2% of the US resident population and 49.3% of all US hospitalizations.
      NRD Overview. Healthcare Cost and Utilization Project (HCUP).

      Study Population

      The unweighted sample was used for all analyses. Our study population included patients who were hospitalized with a primary discharge diagnosis of acute myocardial infarction, heart failure, or pneumonia based on International Classification of Diseases, Ninth Revision, Clinical Modification diagnosis codes (Supplementary Table 1)
      • Dorsey K.B.
      • Grady J.N.
      • Wang C.
      • et al.
      2014 measures updates and specifications report: hospital-level 30-day risk-standardized readmission measures –acute myocardial infarction (version 7.0), heart failure (version 7.0), pneumonia (version 7.0), chronic obstructive pulmonary disease (version 3.0), and stroke (version 3.0).
      occurring between January 1, 2014, and November 30, 2014, for younger adult patients (18-64 years). We also examined hospitalizations among elderly (≥65 years) Medicare beneficiaries at the same hospitals to estimate each hospital's disease-specific 30-day RSRRs for Medicare beneficiaries.

      Index Admission and Readmissions

      Index admissions were defined as the first admission during the study period and all additional admissions occurring more than 30 days after a previous discharge. Admissions for acute myocardial infarction, heart failure, or pneumonia were not considered to be an index admission if patients left against medical advice, were transferred to another acute care hospital, died during the admission, or did not have 30-day follow-up data (eg, admissions in December 2014). Patients transferred in were considered an index admission at the receiving hospital. We also excluded as index admissions those with a missing length of stay, insurance status, and median household income according to ZIP code, and those admitted within 30 days of a prior index admission for the same condition. As per CMS, patients admitted and discharged on the same day with a diagnosis of acute myocardial infarction were not included in the acute myocardial infarction cohort.
      • Dorsey K.B.
      • Grady J.N.
      • Wang C.
      • et al.
      2014 measures updates and specifications report: hospital-level 30-day risk-standardized readmission measures –acute myocardial infarction (version 7.0), heart failure (version 7.0), pneumonia (version 7.0), chronic obstructive pulmonary disease (version 3.0), and stroke (version 3.0).
      Patients could contribute multiple index admissions to the analysis so long as the admissions were not within 30 days of a prior index admission for the same condition. Planned readmissions within 30 days of discharge were identified using the CMS Planned Readmission Algorithm.
      • Dorsey K.B.
      • Grady J.N.
      • Wang C.
      • et al.
      2014 measures updates and specifications report: hospital-level 30-day risk-standardized readmission measures –acute myocardial infarction (version 7.0), heart failure (version 7.0), pneumonia (version 7.0), chronic obstructive pulmonary disease (version 3.0), and stroke (version 3.0).
      If the first readmission after discharge was planned, then no readmission was attributed to that hospitalization and any subsequent unplanned readmission was not counted as a readmission.
      • Dorsey K.B.
      • Grady J.N.
      • Wang C.
      • et al.
      2014 measures updates and specifications report: hospital-level 30-day risk-standardized readmission measures –acute myocardial infarction (version 7.0), heart failure (version 7.0), pneumonia (version 7.0), chronic obstructive pulmonary disease (version 3.0), and stroke (version 3.0).
      We excluded hospitals with fewer than 10 index admissions for elderly Medicare patients or younger patients for each condition to improve the reliability of hospital 30-day RSRRs (Supplementary Figures 1 and 2, available online).

      Diagnoses and Timing of Readmission

      The reasons for readmission were classified using Agency for Healthcare Research and Quality's single-level Clinical Classification Software applied to the principal International Classification of Diseases, Ninth Revision discharge diagnosis.
      HCUP CCS
      Healthcare Cost and Utilization Project (HCUP).
      We identified the percentage of observed 30-day readmissions due to the 5 most common reasons for readmission by single-level Clinical Classification Software categories for the patient cohorts of acute myocardial infarction, heart failure, and pneumonia separately. We reported the percentage of 30-day readmissions occurring on each day (days 1-30) after discharge for each condition.

      Sensitivity Analysis

      Because individual patients may be counted more than once in the primary analysis, we performed a sensitivity analysis including only the first admission for acute myocardial infarction, heart failure, or pneumonia for each patient.

      Statistical Analyses

      By using similar procedures to those used by CMS,
      • Dorsey K.B.
      • Grady J.N.
      • Wang C.
      • et al.
      2014 measures updates and specifications report: hospital-level 30-day risk-standardized readmission measures –acute myocardial infarction (version 7.0), heart failure (version 7.0), pneumonia (version 7.0), chronic obstructive pulmonary disease (version 3.0), and stroke (version 3.0).
      we estimated hospital-specific, 30-day RSRRs for acute myocardial infarction, heart failure, and pneumonia among elderly Medicare patients using hierarchical logistic regression models with a hospital-specific intercept to account for patient clustering. The binary dependent variable was 30-day, all-cause, unplanned readmission. To account for hospital case mix, we adjusted for patient age, gender, and 29 Elixhauser comorbidities.
      • Elixhauser A.
      • Steiner C.
      • Harris D.R.
      • Coffey R.M.
      Comorbidity measures for use with administrative data.
      Separate models were fit for acute myocardial infarction, heart failure, and pneumonia with C-statistics of 0.65, 0.60, and 0.62, respectively. To calculate 30-day RSRRs for each study condition, we used the model to obtain predicted to expected ratios for each hospital. RSRRs were calculated as the product of the predicted to expected ratio and the overall 30-day unplanned readmission rate.
      We then evaluated the association between hospital 30-day RSRRs for elderly patients and risk of readmission among younger patients. We fit a hierarchical logistic regression model among younger patients for each condition with a random hospital-specific intercept. The binary dependent variable was 30-day unplanned readmission, and the primary exposure variable was the 30-day RSRR among Medicare beneficiaries at the hospital where the patient was treated. We adjusted for case mix by including patient age, gender, insurance status, length of stay, 29 Elixhauser comorbidities, care received in the emergency department, median household income by ZIP code, and transfer hospitalization. We also adjusted for available hospital characteristics, including hospital ownership status, teaching status, and bed size.
      Finally, we sought to understand whether a hospital's 30-day RSRR for a specific condition was associated with the risk of readmission in younger patients with a different condition. For example, we examined whether a hospital's 30-day RSRR for heart failure was associated with the risk of readmission for acute myocardial infarction or pneumonia in younger patients. We hypothesized that the risk of readmission in younger patients for a specific condition would not be significantly associated with readmission rates in elderly Medicare patients for nonidentical conditions. However, if a relationship were to exist, it may suggest that hospital strategies targeting the reduction of readmissions for a specific condition may have broader effects across conditions. First, we identified hospitals with estimates of 30-day RSRRs for all 3 conditions. Next, we fit hierarchical regression models as described but included all three 30-day RSRRs as covariates of interest. The dependent variable was 30-day unplanned readmission among younger patients for the acute myocardial infarction, heart failure, and pneumonia cohorts. A P value <.05 was considered statistically significant. All data management and statistical analyses were performed using STATA version 14.2 (StataCorp LP, College Station, Tex).

      Results

      Baseline Patient, Admission, and Hospital Characteristics

      In the 2014 NRD, there were a total of 14.9 million discharges from 2048 hospitals representing 22 geographically dispersed states. There were 87,818, 98,315, and 103,251 index admissions for acute myocardial infarction, heart failure, and pneumonia, respectively, in younger adults (Supplementary Figures 1 and 2, available online). Notably, approximately 25% to 30% of admissions were excluded during construction of the final index admission cohorts for each condition (Supplementary Figure 1, available online). Overall, there were 7504 readmissions for acute myocardial infarction, 21,054 readmissions for heart failure, and 14,165 readmissions for pneumonia. Compared with elderly Medicare beneficiaries, younger patients had lower readmission rates after hospitalization for acute myocardial infarction (8.5% vs 14.9%; P < .001) and pneumonia (13.7% vs 16.1%; P < .001). However, younger patients had higher rates of readmission after heart failure hospitalizations compared with elderly patients (21.4% vs 20.7%; P < .001). Younger patients were more likely to be readmitted if they had a higher number of comorbidities, a longer length of stay, and Medicaid or Medicare (due to disability or end-stage renal disease) (Table 1).
      Table 1Baseline Characteristic of Younger Adult Admissions for Three Conditions Stratified by 30-Day Unplanned Readmission
      Acute Myocardial InfarctionHeart FailurePneumonia
      No ReadmissionReadmissionASDNo ReadmissionReadmissionASDNo ReadmissionReadmissionASD
      N = 80,314N = 7504N = 77,261N = 21,054N = 89,086N = 14,165
      Admission Characteristics
       Age, y, mean (SD)54.1 (7.6)54.8 (7.5)0.0953.5 (8.7)53.5 (9.0)0.00149.9 (11.4)51.6 (10.8)0.15
       Female sex27.9%37.4%0.2038.3%39.4%0.0252.5%50.6%0.04
       No. of Elixhauser comorbidities, mean (SD)2.3 (1.7)3.4 (1.9)0.633.5 (1.8)4.1 (1.8)0.303.1 (1.9)4.0 (2.1)0.45
       No. of Elixhauser comorbidities by categories
      012.1%4.9%0.632.6%1.5%0.276.4%2.7%0.42
      124.9%12.0%9.4%5.7%15.2%7.9%
      225.0%17.9%17.8%13.1%19.9%13.8%
      317.0%20.0%21.6%18.6%19.8%18.3%
      ≥420.6%45.2%48.5%61.1%38.8%57.3%
       Median household income by ZIP code
      $1-$39,99929.6%35.6%0.1540.4%43.3%0.0734.5%36.7%0.06
      $40,000-$50,99927.6%28.1%26.0%26.2%27.9%28.5%
      $51,000-$65,99923.4%20.9%20.0%18.5%21.6%20.6%
      $66,000+19.5%15.4%13.6%12.0%15.9%14.2%
       Length of stay, d, mean (SD)4.2 (5.3)6.5 (7.7)0.355.4 (7.5)6.3 (8.4)0.114.8 (5.4)6.1 (7.2)0.21
       Transfer hospitalization6.8%9.3%0.092.5%2.6%0.011.5%2.2%0.05
       Insurance status
      Medicare (disability/ESRD)14.7%30.4%0.5230.6%38.8%0.3026.8%38.9%0.38
      Medicaid16.9%25.3%29.4%35.1%24.5%30.3%
      Private51.3%30.8%26.0%17.3%35.2%23.0%
      Uninsured/other17.1%13.5%13.9%8.8%13.5%7.8%
      Hospital characteristics
       Hospital control
      Government, nonfederal11.2%12.6%0.0615.0%15.1%0.0314.0%14.2%0.02
      Private nonprofit72.1%69.2%68.8%67.7%68.0%67.2%
      Private, investor-owned16.7%18.3%16.1%17.2%17.9%18.5%
       Hospital teaching status
      Metropolitan nonteaching29.2%29.2%0.0328.3%28.5%0.0134.2%33.9%0.08
      Metropolitan teaching67.2%67.7%66.0%65.8%53.9%56.4%
      Nonmetropolitan hospital3.6%3.1%5.8%5.8%11.9%9.7%
       Hospital bed size
      Small8.9%7.6%0.0612.1%11.1%0.0317.2%14.9%0.07
      Medium26.7%25.4%26.7%26.4%30.6%29.8%
      Large64.5%67.0%61.2%62.5%52.1%55.3%
      ASD = absolute standardized differences; ESRD = end-stage renal disease; SD = standard deviation.

      Timing and Causes of Readmission

      Among younger patients, the median days from discharge to readmission were 9, 13, and 12 days for acute myocardial infarction, heart failure, and pneumonia, respectively. In general, younger and elderly Medicare patients had similar patterns of readmission timing after discharge (Figure 1). Among younger patients, the most common readmission diagnoses were recurrences of each of the respective index admission diagnoses (Table 2). Younger and elderly Medicare patients shared the most common cause of readmission after hospitalizations for heart failure and pneumonia, but not for acute myocardial infarction. The most common cause of readmission after a discharge for acute myocardial infarction among elderly Medicare patients was heart failure, whereas it was acute myocardial infarction in younger patients (Table 2). Heart failure was the only diagnosis that appeared as 1 of the top 5 most common causes of readmission after index hospitalizations for acute myocardial infarction, heart failure, and pneumonia among younger and elderly Medicare patients.
      Figure thumbnail gr1
      Figure 1Percentage of readmissions within 30 days of discharge among younger adult and elderly Medicare patients for 3 conditions. The daily percentage of 30-day readmissions after hospitalizations for acute myocardial infarction (A), heart failure (B), and pneumonia (C) among younger adult and elderly Medicare patients.
      Table 2Common Readmission Diagnoses for Younger Adult and Elderly Medicare Patients
      Elderly Medicare ReadmissionsYounger Adult Readmissions
      Acute Myocardial Infarction
       1) Congestive heart failure; nonhypertensive17.9%1) Acute myocardial infarction14.4%
       2) Acute myocardial infarction12.0%2) Congestive heart failure; nonhypertensive13.0%
       3) Septicemia6.5%3) Nonspecific chest pain8.3%
       4) Cardiac dysrhythmias4.2%4) Complications of surgical procedures or medical care5.1%
       5) Acute and unspecified renal failure3.7%5) Complication of device; implant or graft4.7%
      Heart Failure
       1) Congestive heart failure; nonhypertensive34.0%1) Congestive heart failure; nonhypertensive39.9%
       2) Septicemia6.8%2) Hypertension with complications and secondary hypertension6.8%
       3) Acute and unspecified renal failure5.6%3) Acute and unspecified renal failure4.0%
       4) Hypertension with complications and secondary hypertension4.7%4) Septicemia3.9%
       5) Respiratory failure; insufficient; arrest3.9%5) Respiratory failure; insufficient; arrest3.7%
      Pneumonia
       1) Pneumonia15.3%1) Pneumonia16.4%
       2) Septicemia11.7%2) Septicemia9.5%
       3) Congestive heart failure; nonhypertensive9.2%3) Respiratory failure; insufficient; arrest6.0%
       4) Chronic obstructive pulmonary disease and bronchiectasis6.0%4) Chronic obstructive pulmonary disease and bronchiectasis6.0%
       5) Respiratory failure; insufficient; arrest5.8%5) Congestive heart failure; nonhypertensive5.3%

      Association of Hospital 30-Day, Risk-Standardized Readmission Rates and Readmission Risk in Younger Patients

      The median (interquartile range) hospital 30-day RSRRs among elderly Medicare beneficiaries were 14.8% (14.1%-15.6%), 20.7% (19.5%-22.0%), and 16.0% (15.4%-16.7%) for acute myocardial infarction, heart failure, and pneumonia, respectively. A hospital's 30-day RSRR derived from elderly Medicare patients was significantly associated with the risk of readmission in younger patients for each condition. A 1 percentage point decrease in a hospital's 30-day RSRR for acute myocardial infarction, heart failure, and pneumonia corresponded to an adjusted odds ratio (95% CI) for readmission among younger patients of 0.94 (0.92-0.96; P < .001), 0.96 (0.95-0.96; P < .001), and 0.95 (0.93-0.97; P < .001), respectively. In other words, a decrease in an average hospital's 30-day RSRR from the 75th percentile to the 25th percentile was associated with a reduction in a younger patient's risk of readmission from 8.8% to 8.0% (difference: 0.7%; 95% CI, 0.5-0.9; P < .001) for acute myocardial infarction; 21.8% to 20.0% (difference: 1.8%; 95% CI, 1.4-2.2; P < .001) for heart failure; and 13.9% to 13.1% (difference: 0.8%; 95% CI 0.5-1.0; P < .001) for pneumonia. The average marginal effect of an average hospital's 30-day RSRR on the risk of readmission in younger patients for each condition is demonstrated in Figure 2.
      Figure thumbnail gr2
      Figure 2Predicted risk of readmission for younger adult patients across a spectrum of hospital 30-day RSRRs among elderly Medicare beneficiaries. Average predicted risks of readmission (solid line) and 95% CIs (shaded area) for younger adult patients admitted for acute myocardial infarction (A), heart failure (B), or pneumonia (C) at varying levels of an average hospital's 30-day RSRR derived from elderly Medicare patients hospitalized for each respective condition.
      Thirty-day RSRRs were available for all 3 conditions at 815 hospitals. Among this subgroup, we examined the association of 30-day RSRRs for all 3 conditions on the risk of readmission for hospitalizations of younger patients in the acute myocardial infarction, heart failure, and pneumonia cohorts (Table 3). A hospital's 30-day RSRR for heart failure was significantly associated with the risk of readmission in younger patients across all 3 conditions, whereas 30-day RSRRs for acute myocardial infarction were significantly associated with the risk of readmission for acute myocardial infarction and heart failure but not pneumonia. A hospital's 30-day RSRR for pneumonia was significantly associated with the risk of readmission in younger patients for pneumonia only, not acute myocardial infarction or heart failure (Table 3).
      Table 3Adjusted Odds Ratios of 30-Day, Risk-Standardized Readmission Rates for All Three Conditions on the Probability of Readmission in Younger Patients for Acute Myocardial Infarction, Heart Failure, and Pneumonia
      ExposureAdjusted OR (95% CI)
      AMI Younger Cohort

      N = 86,779

      N/N = 815/840 Available Hospitals
      CHF Younger Cohort

      N = 84,488

      n/N = 815/1241 Available Hospitals
      PNA Younger Cohort

      N = 78,390

      n/N = 815/1550 Available Hospitals
      30-d AMI RSRR for Medicare patients0.96 (0.94-0.98)
      P < .01.
      0.97 (0.95-0.98)
      P < .001.
      0.99 (0.97-1.01)
      30-d HF RSRR for Medicare patients0.97 (0.96-0.98)
      P < .001.
      0.97 (0.96-0.98)
      P < .001.
      0.97 (0.96-0.99)
      P < .001.
      30-d PNA RSRR for Medicare patients0.98 (0.96-1.00)0.99 (0.97-1.01)0.96 (0.94-0.98)
      P < .001.
      Adjusted ORs (95% CI) correspond to a 1 percentage point decrease in a hospital's 30-day RSRR. There were 815 hospitals with estimates of 30-day, risk-standardized readmissions for all 3 conditions. The number of hospitals with estimated RSRRs varied by condition and are shown at the top of each column. The total number of younger patients in each cohort is included at the top of each column.
      AMI = acute myocardial infarction; CI = confidence interval; CHF = congestive heart failure; OR = odds ratio; PNA = pneumonia; RSRR = risk-standardized readmission rate.
      P < .01.
      P < .001.
      In a sensitivity analysis including only the first hospitalization for acute myocardial infarction, heart failure, or pneumonia per patient, we discovered a similar association between a hospital's RSRR in the elderly and the risk of readmission in the nonelderly as was seen in the primary analysis (Supplementary Tables 2 and 3, available online).

      Discussion

      Our study has 2 important findings. First, hospital-level 30-day RSRRs among elderly Medicare beneficiaries were significantly associated with the risk of readmission among younger adults for all 3 conditions. On the basis of our findings, a reduction in an average hospital's RSRR from the 75th percentile to the 25th percentile was associated with an absolute readmission risk reduction ranging from 0.7% to 1.8% in younger patients depending on the condition, suggesting a moderate overall association. Second, we found an unexpected association between the 30-day RSRRs in elderly Medicare beneficiaries and the risk of readmission in younger patients across conditions. A hospital's 30-day RSRR for heart failure was significantly associated with the risk of readmission for all 3 conditions, whereas that for acute myocardial infarction was related to acute myocardial infarction and heart failure but not pneumonia. However, there was no significant relationship between a hospital's RSRR for older adults with pneumonia and the risk of readmission for younger adults with acute myocardial infarction or heart failure. Taken together, these findings suggest efforts to reduce readmissions among older patients may have important areas of overlap with younger patients, although further research is necessary to identify specific mechanisms that explain this relationship.
      Earlier work examining characteristics and readmission patterns among younger adult patients has been limited.
      • Barrett M.L.
      • Wier L.M.
      • Jiang H.J.
      • Steiner C.A.
      • Ranasinghe I.
      • Wang Y.
      • Dharmarajan K.
      • Hsieh A.F.
      • Bernheim S.M.
      • Krumholz H.M.
      Readmissions after hospitalization for heart failure, acute myocardial infarction, or pneumonia among young and middle-aged adults: a retrospective observational cohort study.
      Prior studies have used California inpatient administrative claims data between 2007 and 2009 to evaluate readmissions among patients aged 18 to 64 years.
      • Ranasinghe I.
      • Wang Y.
      • Dharmarajan K.
      • Hsieh A.F.
      • Bernheim S.M.
      • Krumholz H.M.
      Readmissions after hospitalization for heart failure, acute myocardial infarction, or pneumonia among young and middle-aged adults: a retrospective observational cohort study.
      • Dreyer R.P.
      • Ranasinghe I.
      • Wang Y.
      • et al.
      Sex differences in the rate, timing, and principal diagnoses of 30-day readmissions in younger patients with acute myocardial infarction.
      • Davis J.D.
      • Olsen M.A.
      • Bommarito K.
      • et al.
      All-payer analysis of heart failure hospitalization 30-day readmission: comorbidities matter.
      In one study, the overall readmission rates after index hospitalization for acute myocardial infarction, heart failure, and pneumonia were 11.2%, 23.4%, and 14.4%, respectively, in their cohort of younger adult patients.
      • Ranasinghe I.
      • Wang Y.
      • Dharmarajan K.
      • Hsieh A.F.
      • Bernheim S.M.
      • Krumholz H.M.
      Readmissions after hospitalization for heart failure, acute myocardial infarction, or pneumonia among young and middle-aged adults: a retrospective observational cohort study.
      Each of these was greater than the overall readmission rates of 8.5%, 21.4%, and 13.7% readmission rates for acute myocardial infarction, heart failure, and pneumonia, respectively, reported in our study. This lower rate of readmissions might be explained by the inclusion of a larger, more nationally representative cohort of patients in our study along with continued declines in readmission rates for acute myocardial infarction and heart failure.
      • Fingar K.
      • Washington R.
      Trends in hospital readmissions for four high-volume conditions, 2009-2013. HCUP Statistical Brief #196.
      The modestly higher rate of readmission after heart failure hospitalizations among younger patients compared with elderly patients deserves brief mention (21.4% vs 20.7%). Although this finding has been demonstrated for heart failure,
      • Ranasinghe I.
      • Wang Y.
      • Dharmarajan K.
      • Hsieh A.F.
      • Bernheim S.M.
      • Krumholz H.M.
      Readmissions after hospitalization for heart failure, acute myocardial infarction, or pneumonia among young and middle-aged adults: a retrospective observational cohort study.
      the mechanism explaining this phenomenon remains unclear. We speculate on 2 potential mechanisms. First, perhaps differences in the common causes of heart failure between younger and older patients partially account for this phenomenon. For instance, heart failure with reduced ejection fraction is a more common cause of heart failure among younger patients and may be associated with a worse prognosis in this age group.
      • Mosterd A.
      • Hoes A.W.
      Clinical epidemiology of heart failure.
      Second, socioeconomic factors, including lack of health insurance, may pose challenges to appropriate outpatient follow-up and management for younger patients.
      Our study is the first to examine the association between readmissions for elderly and younger patients after the HRRP was introduced. We extend prior literature by introducing the novel finding that 30-day RSRRs for elderly Medicare beneficiaries have a significant association with the risk of readmission for younger patients for acute myocardial infarction, heart failure, and pneumonia. This finding has several important implications. First, because other insurers beyond Medicare are concerned with reducing readmissions, understanding the mechanisms by which hospitals with low 30-day RSRRs achieve reduced readmissions across the spectrum of age is an important step in designing and implementing readmission reduction programs more broadly. One possible mechanism may include similar patterns and timing of readmission.
      • Ranasinghe I.
      • Wang Y.
      • Dharmarajan K.
      • Hsieh A.F.
      • Bernheim S.M.
      • Krumholz H.M.
      Readmissions after hospitalization for heart failure, acute myocardial infarction, or pneumonia among young and middle-aged adults: a retrospective observational cohort study.
      • Dharmarajan K.
      • Hsieh A.F.
      • Lin Z.
      • et al.
      Diagnoses and timing of 30-day readmissions after hospitalization for heart failure, acute myocardial infarction, or pneumonia.
      Second, there may be substantial costs associated with reducing a hospital's RSRR in elderly patients.
      • Chaudhry S.I.
      • Phillips C.O.
      • Stewart S.S.
      • et al.
      Telemonitoring for patients with chronic heart failure: a systematic review.
      On the basis of our findings, a reduction in a hospital's RSRR by 1 percentage point is associated with an approximately 5% reduction in the relative probability of readmission and a smaller reduction in the absolute risk among younger patients across all 3 conditions. Thus, an increased understanding of the factors associated with readmissions in nonelderly patients may inform the development of more cost-effective strategies to reduce readmissions in this population.
      We also demonstrate that hospital 30-day RSRRs may be associated with risk of readmission across conditions. For instance, we found that a hospital's 30-day RSRR for heart failure was significantly associated with readmission in the younger population across all 3 conditions, suggesting that this measure may be a good indicator of overall quality of care. Indeed, heart failure was the only diagnosis in the top 5 causes of readmission for all 3 conditions in both younger and elderly Medicare patients. Therefore, hospitals that effectively manage heart failure among elderly Medicare beneficiaries may do so by proactively preventing readmissions for heart failure across ages and conditions using diverse approaches with broad applicability.
      There are some data to support this speculation. A prior study reported several hospital strategies that were associated with reduced hospital RSRRs for heart failure.
      • Bradley E.H.
      • Curry L.
      • Horwitz L.I.
      • et al.
      Hospital strategies associated with 30-day readmission rates for patients with heart failure.
      These included hospital partnerships with community physicians and local hospitals aimed at reducing readmissions; discharge summaries sent directly to the patient's primary care physician; arrangement of follow-up appointments before discharge; and staff assigned to follow-up specific test results.
      • Bradley E.H.
      • Curry L.
      • Horwitz L.I.
      • et al.
      Hospital strategies associated with 30-day readmission rates for patients with heart failure.
      These broad strategies may, in part, reduce readmissions across ages and conditions, thus explaining the observed association between a hospital's RSRR for heart failure and the risk of readmission among younger patients with acute myocardial infarction or pneumonia. Nevertheless, given the relatively small sample size of this subgroup, these findings should be considered hypothesis-generating and warrant further evaluation.
      Our findings have several important implications. There is growing momentum for initiatives aimed at mitigating healthcare costs by reducing readmissions. The HRRP has imposed substantial financial penalties, resulting in approximately $1 billion in penalties since the program's inception in October 2012.
      • Miller L.W.
      • Guglin M.
      Patient selection for ventricular assist devices: a moving target.
      Although not without controversy, many studies have demonstrated multiple beneficial effects of this policy.
      • Desai N.R.
      • Ross J.S.
      • Kwon J.Y.
      • et al.
      Association between hospital penalty status under the hospital readmission reduction program and readmission rates for target and nontarget conditions.
      • Carey K.
      • Lin M.Y.
      Readmissions to New York hospitals fell for three target conditions from 2008 to 2012, consistent with Medicare goals.
      • Zuckerman R.B.
      • Sheingold S.H.
      • Orav E.J.
      • Ruhter J.
      • Epstein A.M.
      Readmissions, observation, and the hospital readmissions reduction program.
      Inspired by the initial success of the HRRP, Medicaid and private insurers also are designing programs to reduce readmissions for their nonelderly enrollees.
      • Bongiovanni D.
      Readmissions penalties: are commercial payors following Medicare's lead?.
      For example, Illinois has implemented a Medicaid Readmission Penalty Program based on the SMART Act.
      Potentially Preventable Readmissions Policy. PPR Overview: Department of Healthcare and Family Services 2014.
      It remains to be determined whether best practices and quality-improvement efforts targeting older adults, such as Project Better Outcomes for Older Adults through Safe Transitions (BOOST)
      • Hansen L.O.
      • Greenwald J.L.
      • Budnitz T.
      • et al.
      Project BOOST: effectiveness of a multihospital effort to reduce rehospitalization.
      and Project Re-Engineered Discharge (RED),
      • Naylor M.D.
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      • Schwartz J.S.
      Transitional care of older adults hospitalized with heart failure: a randomized, controlled trial.
      • Naylor M.D.
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      • et al.
      Comprehensive discharge planning and home follow-up of hospitalized elders: a randomized clinical trial.
      • Jack B.W.
      • Chetty V.K.
      • Anthony D.
      • et al.
      A reengineered hospital discharge program to decrease rehospitalization: a randomized trial.
      will be similarly effective in younger adult patients.

      Study Limitations

      Our study should be interpreted in the context of the following study design issues. First, because of data limitations in the NRD, we were unable to account for complete measures of clinical and socioeconomic risk in our models.
      • Joynt K.E.
      • Jha A.K.
      A path forward on Medicare readmissions.
      • Joynt K.E.
      • Jha A.K.
      Thirty-day readmissions–truth and consequences.
      National Quality Forum
      Risk Adjustment for Socioeconomic Status or other Sociodemographic Factors. 2014.
      Thus, residual confounding due to both elderly and younger patients being sicker at some hospitals remains an important concern as with most observational studies. Second, we were unable to use the specific case-mix adjustment method used by CMS for estimation of 30-day RSRRs for HRRP and Hospital Compare.
      • Dorsey K.B.
      • Grady J.N.
      • Wang C.
      • et al.
      2014 measures updates and specifications report: hospital-level 30-day risk-standardized readmission measures –acute myocardial infarction (version 7.0), heart failure (version 7.0), pneumonia (version 7.0), chronic obstructive pulmonary disease (version 3.0), and stroke (version 3.0).
      This method of risk-adjustment requires 12 months of claims data before admission, which was not available in this dataset. However, as in prior work, we used Elixhauser comorbidities for case-mix adjustment
      • Joynt K.E.
      • Orav E.J.
      • Jha A.K.
      Thirty-day readmission rates for Medicare beneficiaries by race and site of care.
      ; the discrimination of our models compared similarly to models used by CMS.
      • Krumholz H.M.
      • Lin Z.
      • Drye E.E.
      • et al.
      An administrative claims measure suitable for profiling hospital performance based on 30-day all-cause readmission rates among patients with acute myocardial infarction.
      • Keenan P.S.
      • Normand S.L.
      • Lin Z.
      • et al.
      An administrative claims measure suitable for profiling hospital performance on the basis of 30-day all-cause readmission rates among patients with heart failure.
      • Lindenauer P.K.
      • Normand S.L.
      • Drye E.E.
      • et al.
      Development, validation, and results of a measure of 30-day readmission following hospitalization for pneumonia.
      Third, we did not have data available on vital status among patients who were not readmitted. Therefore, we were unable to account for the competing risk of death after discharge. However, most operational initiatives for programs targeted toward readmission consider mortality and readmission as separate outcomes. Fourth, there are important limitations of the NRD that deserve specific mention. The NRD includes only hospitalizations from community hospitals as defined by the American Hospital Association; therefore, admissions to federal hospitals such as the Veterans Affairs health systems are not included. Readmissions to hospitals in different states from the index hospitalization are not captured because the NRD is a compilation of various State Inpatient Databases. Also, readmissions when the discharge date occurred in 2015 were not captured. These limitations of the dataset may have led to a modest underestimation of the actual number of readmissions that occurred. Finally, we also recognize the limitations regarding our 30-day RSRR calculations due to the availability of 11 months of data in the NRD compared with the 3 years of historical data used in the CMS measures. This leads to the potential of measurement error in our 30-day RSRR calculations. Although there is no method to compare the hospital-specific RSRRs we estimated with Hospital Compare because of the de-identified nature of the NRD, our national observed readmission rates were largely comparable. Specifically, our 30-day observed readmission rates for elderly Medicare beneficiaries for acute myocardial infarction, congestive heart failure, and pneumonia were 14.9%, 20.7%, and 16.1%, respectively, whereas currently on Hospital Compare they are 16.8%, 21.9%, and 17.1%, respectively. Overall, our calculated rates were modestly lower than the reported readmission rates on Hospital Compare that we suspect are due to the inclusion of generally healthier Medicare Advantage patients.

      Conclusions

      Approximately 1 in 12 patients with acute myocardial infarction, 1 in 5 patients with heart failure, and 1 in 7 patients with pneumonia aged less than 65 years are readmitted within 30 days of discharge. Their risk of readmission is moderately associated with a hospital's rate of 30-day readmissions among elderly Medicare beneficiaries. Further research is needed to elucidate the mechanisms responsible for 30-day readmissions among younger patients and whether it is most effective to improve existing readmission reduction programs or design novel strategies targeted to younger adults.

      Supplementary Data

      Supplementary Table 1International Classification of Diseases, Ninth Revision, Clinical Modification Inclusion Criteria for Acute Myocardial Infarction, Heart Failure, and Pneumonia Index Admissions
      ICD-9-CM CodesDescription
      AMI
       410.00AMI (anterolateral wall) episode of care unspecified
       410.01AMI (anterolateral wall) initial episode of care
       410.10AMI (other anterior wall) episode of care unspecified
       410.11AMI (other anterior wall) initial episode of care
       410.20AMI (inferolateral wall) episode of care unspecified
       410.21AMI (inferolateral wall) initial episode of care
       410.30AMI (inferoposterior wall) episode of care unspecified
       410.31AMI (inferoposterior wall) initial episode of care
       410.40AMI (other inferior wall) episode of care unspecified
       410.41AMI (other inferior wall) initial episode of care
       410.50AMI (other lateral wall) episode of care unspecified
       410.51AMI (other lateral wall) initial episode of care
       410.60AMI (true posterior wall) episode of care unspecified
       410.61AMI (true posterior wall) initial episode of care
       410.70AMI (subendocardial) episode of care unspecified
       410.71AMI (subendocardial) initial episode of care
       410.80AMI (other specified site) episode of care unspecified
       410.81AMI (other specified site) initial episode of care
       410.90AMI (unspecified site) episode of care unspecified
       410.91AMI (unspecified site) initial episode of care
      CHF
       402.01Malignant hypertensive heart disease with CHF
       402.11Benign hypertensive heart disease with CHF
       402.91Hypertensive heart disease with CHF
       404.01Malignant hypertensive heart and renal disease with CHF
       404.03Malignant hypertensive heart and renal disease with CHF and renal failure
       404.11Benign hypertensive heart disease and renal disease with CHF
       404.13Benign hypertensive heart disease and renal disease with CHF and renal failure
       404.91Unspecified hypertensive heart and renal disease with CHF
       404.93Hypertension and nonspecified heart and renal disease with CHF and renal failure
       428.0Congestive heart failure, unspecified
       428.1Left heart failure
       428.2Systolic heart failure, unspecified
       428.21Systolic heart failure, acute
       428.22Systolic heart failure, chronic
       428.23Systolic heart failure, acute or chronic
       428.3Diastolic heart failure, unspecified
       428.31Diastolic heart failure, acute
       428.32Diastolic heart failure, chronic
       428.33Diastolic heart failure, acute or chronic
       428.4Combined systolic and diastolic heart failure, unspecified
       428.41Combined systolic and diastolic heart failure, acute
       428.42Combined systolic and diastolic heart failure, chronic
       428.43Combined systolic and diastolic heart failure, acute or chronic
       428.9Heart failure, unspecified
      Pneumonia
       480.0Pneumonia due to adenovirus
       480.1Pneumonia due to respiratory syncytial virus
       480.2Pneumonia due to parainfluenza virus
       480.3Pneumonia due to SARS-associated coronavirus
       480.8Viral pneumonia: pneumonia due to other virus not elsewhere classified
       480.9Viral pneumonia unspecified
       481.0Pneumococcal pneumonia (streptococcus pneumoniae pneumonia)
       482.0Pneumonia due to Klebsiella pneumoniae
       482.1Pneumonia due to Pseudomonas
       482.2Pneumonia due to Haemophilus influenzae
       482.3Pneumonia due to streptococcus unspecified
       482.31Pneumonia due to streptococcus group A
       482.32Pneumonia due to streptococcus group B
       482.39Pneumonia due to other streptococcus
       482.4Pneumonia due to staphylococcus unspecified
       482.41Pneumonia due to Staphylococcus aureus
       482.42Methicillin resistant pneumonia due to Staphylococcus aureus
       482.49Other staphylococcus pneumonia
       482.81Pneumonia due to anaerobes
       482.82Pneumonia due to Escherichia coli
       482.83Pneumonia due to other gram-negative bacteria
       482.84Pneumonia due to Legionnaires' disease
       482.89Pneumonia due to other specified bacteria
       482.9Bacterial pneumonia unspecified
       483.0Pneumonia due to Mycoplasma pneumoniae
       483.1Pneumonia due to chlamydia
       483.8Pneumonia due to other specified organism
       485.0Bronchopneumonia organism unspecified
       486.0Pneumonia organism unspecified
       487.0Influenza with pneumonia
       488.11Influenza due to identified novel H1N1 influenza virus with pneumonia
      ICD-9-CM codes obtained from the 2014 Measures Updates and Specifications Report Hospital-Level 30-Day Risk-Standardized Readmission Measures.
      • Dorsey K.B.
      • Grady J.N.
      • Wang C.
      • et al.
      2014 measures updates and specifications report: hospital-level 30-day risk-standardized readmission measures –acute myocardial infarction (version 7.0), heart failure (version 7.0), pneumonia (version 7.0), chronic obstructive pulmonary disease (version 3.0), and stroke (version 3.0).
      AMI = acute myocardial infarction; CHF = congestive heart failure; ICD-9-CM = International Classification of Diseases, Ninth Revision, Clinical Modification; SARS = severe acute respiratory syndrome.
      Figure thumbnail fx1
      Supplementary Figure 1Flow diagram of study sample. *Detailed exclusions are shown in . AMI = acute myocardial infarction; HF = heart failure; PNA = pneumonia.
      Figure thumbnail fx2ab
      Supplementary Figure 2Flow diagram of admission- and hospital-level exclusions for acute myocardial infarction, heart failure, and pneumonia. A, Acute myocardial infarction. B, Heart failure. C, Pneumonia.
      Figure thumbnail fx2c
      Supplementary Figure 2Flow diagram of admission- and hospital-level exclusions for acute myocardial infarction, heart failure, and pneumonia. A, Acute myocardial infarction. B, Heart failure. C, Pneumonia.
      Supplementary Table 2Description of Sensitivity Analysis Cohort
      AMIHeart FailurePneumonia
      Elderly Medicare index admissions90,990173,832148,570
      Readmissions (%)12,856 (14.1)33,160 (19.1)22,639 (15.2)
      Nonelderly index admissions84,48974,78197,035
      Readmissions (%)6663 (7.9)13,430 (18.0)12,347 (12.7)
      AMI = acute myocardial infarction.
      Supplementary Table 3Adjusted Odds Ratios for Readmission Among Younger Patients for a 1 Percentage Point Decrease in a Hospital's 30-Day, Risk-Standardized Readmission Rates for Each Condition in the Primary and Sensitivity Analyses
      Adjusted OR95% CIP Value
      Acute myocardial infarction
       Primary analysis0.940.92-0.96<.001
       Sensitivity analysis0.930.91-0.95<.001
      Heart failure
       Primary analysis0.960.95-0.96<.001
       Sensitivity analysis0.940.93-0.96<.001
      Pneumonia
       Primary analysis0.950.93-0.97<.001
       Sensitivity analysis0.940.92-0.96<.001
      CI = confidence interval; OR = odds ratio.

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