Readmission Rates for Chronic Obstructive Pulmonary Disease Under the Hospital Readmissions Reduction Program: an Interrupted Time Series Analysis

Abstract

Background

Hospital readmission rates decreased for myocardial infarction (AMI), heart failure (CHF), and pneumonia with implementation of the first phase of the Hospital Readmissions Reduction Program (HRRP). It is not established whether readmissions fell for chronic obstructive pulmonary disease (COPD), an HRRP condition added in 2014.

Objective

We sought to determine whether HRRP penalties influenced COPD readmissions among Medicare, Medicaid, or privately insured patients.

Design

We analyzed a retrospective cohort, evaluating readmissions across implementation periods for HRRP penalties (“pre-HRRP” January 2010–April 2011, “implementation” May 2011–September 2012, “partial penalty” October 2012–September 2014, and “full penalty” October 2014–December 2016).

Patients

We assessed discharged patients ≥ 40 years old with COPD versus those with HRRP Phase 1 conditions (AMI, CHF, and pneumonia) or non-HRRP residual diagnoses in the Nationwide Readmissions Database.

Interventions

HRRP was announced and implemented during this period, forming a natural experiment.

Measurements

We calculated differences-in-differences (DID) for 30-day COPD versus HRRP Phase 1 and non-HRRP readmissions.

Key Results

COPD discharges for 1.2 million Medicare enrollees were compared with 22 million non-HRRP and 3.4 million HRRP Phase 1 discharges. COPD readmissions decreased from 19 to 17% over the study. This reduction was significantly greater than non-HRRP conditions (DID − 0.41%), but not HRRP Phase 1 (DID + 0.02%). A parallel trend was observed in the privately insured, with significant reduction compared with non-HRRP (DID − 0.83%), but not HRRP Phase 1 conditions (DID − 0.45%). Non-significant reductions occurred in Medicaid (DID − 0.52% vs. non-HRRP and − 0.21% vs. Phase 1 conditions).

Conclusions

In Medicare, HRRP implementation was associated with reductions in COPD readmissions compared with non-HRRP controls but not versus other HRRP conditions. Parallel findings were observed in commercial insurance, but not in Medicaid. Condition-specific penalties may not reduce readmissions further than existing HRRP trends.

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Contributors and Data Availability

Data was made available through the Agency for Healthcare Research and Quality’s Healthcare Utilization Project. A full list of partner organizations providing data for the Nationwide Readmissions Database can be found at https://www.hcup-us.ahrq.gov/db/hcupdatapartners.jsp.

References

  1. 1.

    Jencks SF, Williams MV, Coleman EA. Rehospitalizations among patients in the Medicare fee-for-service program. N Engl J Med. 2009;360(14):1418-28. https://doi.org/10.1056/NEJMsa0803563

    CAS  Article  Google Scholar 

  2. 2.

    Patient Protection and Affordable Care Act, Pub. L. No. 111-148, Stat. 124 Stat. 119 (March 23, 2010).

  3. 3.

    Medicare Program; Proposed Changes to the Hospital Inpatient Prospective Payment Systems for Acute Care Hospitals and the Long-Term Care Hospital Prospective Payment System and Fiscal Year 2012 Rates, 76 (2011).

  4. 4.

    Medicare Program; Hospital Inpatient Prospective Payment Systems for Acute Care Hospitals and the Long-Term Care Hospital Prospective Payment System and FY 2012 Rates; Hospitals’ FTE Resident Caps for Graduate Medical Education Payment, 76 (2011).

  5. 5.

    Medicare Program; Hospital Inpatient Prospective Payment Systems for Acute Care Hospitals and the Long-Term Care Hospital Prospective Payment System and Proposed Fiscal Year 2014 Rates; Quality Reporting Requirements for Specific Providers; Hospital Conditions of Participation, 78 (2013).

  6. 6.

    Medicare Program; Hospital Inpatient Prospective Payment Systems for Acute Care Hospitals and the Long-Term Care Hospital Prospective Payment System and Fiscal Year 2014 Rates; Quality Reporting Requirements for Specific Providers; Hospital Conditions of Participation; Payment Policies Related to Patient Status, 78 (2013).

  7. 7.

    Healthcare Cost and Utilization Project. Introduction to the HCUP Nationwide Readmissions Database (NRD) 2010-2016. Agency for Healthcare Research and Quality, Rockville, MD. 2018. https://www.hcup-us.ahrq.gov/db/nation/nrd/Introduction_NRD_2010-2016.jsp. Accessed October 15 2018.

  8. 8.

    Wasfy JH, Zigler CM, Choirat C, Wang Y, Dominici F, Yeh RW. Readmission Rates After Passage of the Hospital Readmissions Reduction Program: A Pre-Post Analysis. Ann Intern Med. 2017;166(5):324-31. https://doi.org/10.7326/m16-0185

    Article  PubMed  Google Scholar 

  9. 9.

    Ryan AM, Krinsky S, Adler-Milstein J, Damberg CL, Maurer KA, Hollingsworth JM. Association Between Hospitals’ Engagement in Value-Based Reforms and Readmission Reduction in the Hospital Readmission Reduction Program. JAMA Intern Med. 2017;177(6):862-8. https://doi.org/10.1001/jamainternmed.2017.0518

    Article  PubMed  PubMed Central  Google Scholar 

  10. 10.

    Desai NR, Ross JS, Kwon JY, Herrin J, Dharmarajan K, Bernheim SM, et al. Association Between Hospital Penalty Status Under the Hospital Readmission Reduction Program and Readmission Rates for Target and Nontarget Conditions. JAMA. 2016;316(24):2647-56. https://doi.org/10.1001/jama.2016.18533

    Article  PubMed  PubMed Central  Google Scholar 

  11. 11.

    Demiralp B, He F, Koenig L. Further Evidence on the System-Wide Effects of the Hospital Readmissions Reduction Program. Health Serv Res. 2018;53(3):1478-97. https://doi.org/10.1111/1475-6773.12701

    Article  PubMed  Google Scholar 

  12. 12.

    Fingar K, Washington R. Trends in Hospital Readmissions for Four High-Volume Conditions, 2009-2013: Statistical Brief #196. Rockville (MD): Agency for Healthcare Research and Quality (US); 2015.

  13. 13.

    Myers LC, Faridi MK, Hasegawa K, Hanania NA, Camargo CA, Jr. The Hospital Readmissions Reduction Program and Readmissions for Chronic Obstructive Pulmonary Disease, 2006-2015. Ann Am Thorac Soc. 2019; https://doi.org/10.1513/AnnalsATS.201909-672OC

  14. 14.

    Zuckerman RB, Joynt Maddox KE, Sheingold SH, Chen LM, Epstein AM. Effect of a Hospital-wide Measure on the Readmissions Reduction Program. N Engl J Med. 2017;377(16):1551-8. https://doi.org/10.1056/NEJMsa1701791

    Article  PubMed  Google Scholar 

  15. 15.

    Carey K, Lin MY. Readmissions To New York Hospitals Fell For Three Target Conditions From 2008 To 2012, Consistent With Medicare Goals. Health Aff (Millwood). 2015;34(6):978-85. https://doi.org/10.1377/hlthaff.2014.1408

    Article  Google Scholar 

  16. 16.

    Ferro EG, Secemsky EA, Wadhera RK, Choi E, Strom JB, Wasfy JH, et al. Patient Readmission Rates For All Insurance Types After Implementation Of The Hospital Readmissions Reduction Program. Health Aff (Millwood). 2019;38(4):585-93. https://doi.org/10.1377/hlthaff.2018.05412

    Article  Google Scholar 

  17. 17.

    HCUP. Nationwide Readmissions Database (NRD) [database on the Internet]. Agency for Healthcare Research and Quality. 2010-2016. Available from: https://www.hcup-us.ahrq.gov/nrdoverview.jsp.

  18. 18.

    Yale New Haven Health Services Corporation/Center for Outcomes Research & Evaluation. 2016 Condition-Specific Measures Updates and Specifications Report Hospital-Level 30-Day Risk-Standardized Readmission Measures. Baltimore, MD: Centers for Medicare & Medicaid Services; 2016.

  19. 19.

    Yale New Haven Health Services Corporation/Center for Outcomes Research & Evaluation. 2017 Condition-Specific Measures Updates and Specifications Report Hospital-Level 30-Day Risk-Standardized Readmission Measures. Baltimore, MD: Centers for Medicare & Medicaid Services; 2017.

  20. 20.

    Stagg V. ELIXHAUSER: Stata module to calculate Elixhauser index of comorbidity. Boston College Department of Economics: Statistical Software Components; 2015.

  21. 21.

    Moore BJ, White S, Washington R, Coenen N, Elixhauser A. Identifying Increased Risk of Readmission and In-hospital Mortality Using Hospital Administrative Data: The AHRQ Elixhauser Comorbidity Index. Med Care. 2017;55(7):698-705. https://doi.org/10.1097/MLR.0000000000000735

    Article  PubMed  Google Scholar 

  22. 22.

    Buhr RG, Jackson NJ, Kominski GF, Dubinett SM, Ong MK, Mangione CM. Comorbidity and thirty-day hospital readmission odds in chronic obstructive pulmonary disease: a comparison of the Charlson and Elixhauser comorbidity indices. BMC Health Serv Res. 2019;19(1):701. https://doi.org/10.1186/s12913-019-4549-4

    Article  PubMed  PubMed Central  Google Scholar 

  23. 23.

    Joynt KE, Figueroa JE, Oray J, Jha AK. Opinions on the Hospital Readmission Reduction Program: Results of a National Survey of Hospital Leaders. Am J Manag Care. 2016;22(8):e287-94.

    PubMed  PubMed Central  Google Scholar 

  24. 24.

    Regenstein M, Andres E. Reducing hospital readmissions among medicaid patients: a review of the literature. Qual Manag Health Care. 2014;23(1):20-42. https://doi.org/10.1097/qmh.0000000000000016

    Article  PubMed  Google Scholar 

  25. 25.

    Trudnak T, Kelley D, Zerzan J, Griffith K, Jiang HJ, Fairbrother GL. Medicaid Admissions And Readmissions: Understanding The Prevalence, Payment, And Most Common Diagnoses. Health Aff (Millwood). 2014;33(8):1337-44. https://doi.org/10.1377/hlthaff.2013.0632

    Article  Google Scholar 

  26. 26.

    Gai Y, Pachamanova D. Impact of the Medicare hospital readmissions reduction program on vulnerable populations. BMC Health Serv Res. 2019;19(1):837. https://doi.org/10.1186/s12913-019-4645-5

    Article  PubMed  PubMed Central  Google Scholar 

  27. 27.

    Krishnan JA, Gussin HA, Prieto-Centurion V, Sullivan JL, Zaidi F, Thomashow BM. Integrating COPD into Patient-Centered Hospital Readmissions Reduction Programs. Copd. 2015;2(1):70-80. https://doi.org/10.15326/jcopdf.2.1.2014.0148

    Article  PubMed  Google Scholar 

  28. 28.

    Press VG, Au DH, Bourbeau J, Dransfield MT, Gershon AS, Krishnan JA, et al. Reducing Chronic Obstructive Pulmonary Disease Hospital Readmissions. An Official American Thoracic Society Workshop Report. Ann Am Thorac Soc. 2019;16(2):161-70. https://doi.org/10.1513/AnnalsATS.201811-755WS

    Article  PubMed  PubMed Central  Google Scholar 

  29. 29.

    Shah T, Press VG, Huisingh-Scheetz M, White SR. COPD Readmissions: Addressing COPD in the Era of Value-based Health Care. Chest. 2016;150(4):916-26. https://doi.org/10.1016/j.chest.2016.05.002

    Article  PubMed  PubMed Central  Google Scholar 

  30. 30.

    Fan VS, Gaziano JM, Lew R, Bourbeau J, Adams SG, Leatherman S, et al. A comprehensive care management program to prevent chronic obstructive pulmonary disease hospitalizations: a randomized, controlled trial. Ann Intern Med. 2012;156(10):673-83. https://doi.org/10.7326/0003-4819-156-10-201205150-00003

    Article  PubMed  Google Scholar 

  31. 31.

    Auerbach AD, Kripalani S, Vasilevskis EE, Sehgal N, Lindenauer PK, Metlay JP, et al. Preventability and Causes of Readmissions in a National Cohort of General Medicine Patients. JAMA Intern Med. 2016;176(4):484-93. https://doi.org/10.1001/jamainternmed.2015.7863

    Article  PubMed  PubMed Central  Google Scholar 

  32. 32.

    Donzé J, Aujesky D, Williams D, Schnipper JL. Potentially Avoidable 30-Day Hospital Readmissions in Medical Patients: Derivation and Validation of a Prediction Model. JAMA Intern Med. 2013;173(8):632-8. https://doi.org/10.1001/jamainternmed.2013.3023

    Article  PubMed  Google Scholar 

  33. 33.

    Hakim MA, Garden FL, Jennings MD, Dobler CC. Performance of the LACE index to predict 30-day hospital readmissions in patients with chronic obstructive pulmonary disease. Clin Epidemiol. 2018;10:51-9. https://doi.org/10.2147/clep.S149574

    Article  PubMed  Google Scholar 

  34. 34.

    Wang H, Robinson RD, Johnson C, Zenarosa NR, Jayswal RD, Keithley J, et al. Using the LACE index to predict hospital readmissions in congestive heart failure patients. BMC Cardiovasc Disord. 2014;14:97. https://doi.org/10.1186/1471-2261-14-97

    Article  PubMed  PubMed Central  Google Scholar 

  35. 35.

    Buhr RG, Jackson NJ, Kominski GF, Dubinett SM, Mangione CM, Ong MK. Factors associated with differential readmission diagnoses following acute exacerbations of chronic obstructive pulmonary disease. J Hosp Med. 2020;15. https://doi.org/10.12788/jhm.3367

  36. 36.

    Press VG, Miller BJ. The Hospital Readmissions Reduction Program and COPD: More Answers, More Questions. J Hosp Med. 2020; https://doi.org/10.12788/jhm.3362

  37. 37.

    Wadhera RK, Joynt Maddox KE, Wasfy JH, Haneuse S, Shen C, Yeh RW. Association of the Hospital Readmissions Reduction Program With Mortality Among Medicare Beneficiaries Hospitalized for Heart Failure, Acute Myocardial Infarction, and Pneumonia. JAMA. 2018;320(24):2542-52. https://doi.org/10.1001/jama.2018.19232

    Article  PubMed  PubMed Central  Google Scholar 

  38. 38.

    Dharmarajan K, Wang Y, Lin Z, et al. Association of changing hospital readmission rates with mortality rates after hospital discharge. JAMA. 2017;318(3):270-8. https://doi.org/10.1001/jama.2017.8444

    Article  PubMed  PubMed Central  Google Scholar 

  39. 39.

    Samarghandi A, Qayyum R. Effect of Hospital Readmission Reduction Program on Hospital Readmissions and Mortality Rates. J Hosp Med. 2019;14:E25-e30. https://doi.org/10.12788/jhm.3302

    Article  PubMed  Google Scholar 

  40. 40.

    Carey K, Lin MY. Hospital Readmissions Reduction Program: Safety-Net Hospitals Show Improvement, Modifications To Penalty Formula Still Needed. Health Aff (Millwood). 2016;35(10):1918-23. https://doi.org/10.1377/hlthaff.2016.0537

    Article  Google Scholar 

  41. 41.

    Gu Q, Koenig L, Faerberg J, Steinberg CR, Vaz C, Wheatley MP. The Medicare Hospital Readmissions Reduction Program: potential unintended consequences for hospitals serving vulnerable populations. Health Serv Res. 2014;49(3):818-37. https://doi.org/10.1111/1475-6773.12150

    Article  PubMed  PubMed Central  Google Scholar 

  42. 42.

    Salerno AM, Horwitz LI, Kwon JY, Herrin J, Grady JN, Lin Z, et al. 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. BMJ Open. 2017;7(7):e016149. https://doi.org/10.1136/bmjopen-2017-016149

    Article  PubMed  PubMed Central  Google Scholar 

  43. 43.

    Sheingold SH, Zuckerman R, Shartzer A. Understanding Medicare Hospital Readmission Rates And Differing Penalties Between Safety-Net And Other Hospitals. Health Aff (Millwood). 2016;35(1):124-31. https://doi.org/10.1377/hlthaff.2015.0534

    Article  Google Scholar 

  44. 44.

    Sjoding MW, Cooke CR. Readmission Penalties for Chronic Obstructive Pulmonary Disease Will Further Stress Hospitals Caring for Vulnerable Patient Populations. Am J Respir Crit Care Med. 2014;190(9):1072-4. https://doi.org/10.1164/rccm.201407-1345LE

    Article  PubMed  PubMed Central  Google Scholar 

  45. 45.

    Feemster LC, Au DH. Penalizing hospitals for chronic obstructive pulmonary disease readmissions. Am J Respir Crit Care Med. 2014;189(6):634-9. https://doi.org/10.1164/rccm.201308-1541PP

    Article  PubMed  PubMed Central  Google Scholar 

  46. 46.

    Rinne ST, Castaneda J, Lindenauer PK, Cleary PD, Paz HL, Gomez JL. Chronic Obstructive Pulmonary Disease Readmissions and Other Measures of Hospital Quality. Am J Resp Crit Care Med. 2017;196(1):47-55. https://doi.org/10.1164/rccm.201609-1944OC

    Article  PubMed  Google Scholar 

  47. 47.

    McCarthy B, Casey D, Devane D, Murphy K, Murphy E, Lacasse Y. Pulmonary rehabilitation for chronic obstructive pulmonary disease. Cochrane Database Syst Rev. 2015;(2):Cd003793. https://doi.org/10.1002/14651858.CD003793.pub3

  48. 48.

    Puhan MA, Gimeno-Santos E, Cates CJ, Troosters T. Pulmonary rehabilitation following exacerbations of chronic obstructive pulmonary disease. Cochrane Database Syst Rev. 2016;12:Cd005305. https://doi.org/10.1002/14651858.CD005305.pub4

    Article  PubMed  Google Scholar 

  49. 49.

    Williams MT, Effing TW, Paquet C, Gibbs CA, Lewthwaite H, Li LSK, et al. Counseling for health behavior change in people with COPD: systematic review. Int J Chron Obstruct Pulmon Dis. 2017;12:2165-78. https://doi.org/10.2147/copd.S111135

    Article  PubMed  PubMed Central  Google Scholar 

  50. 50.

    van Eerd EA, van der Meer RM, van Schayck OC, Kotz D. Smoking cessation for people with chronic obstructive pulmonary disease. Cochrane Database Syst Rev. 2016;(8):Cd010744. https://doi.org/10.1002/14651858.CD010744.pub2

  51. 51.

    Bekkat-Berkani R, Wilkinson T, Buchy P, Dos Santos G, Stefanidis D, Devaster JM, et al. Seasonal influenza vaccination in patients with COPD: a systematic literature review. BMC Pulm Med. 2017;17(1):79. https://doi.org/10.1186/s12890-017-0420-8

    Article  PubMed  PubMed Central  Google Scholar 

  52. 52.

    Walters JA, Tang JN, Poole P, Wood-Baker R. Pneumococcal vaccines for preventing pneumonia in chronic obstructive pulmonary disease. Cochrane Database Syst Rev. 2017;1:Cd001390. https://doi.org/10.1002/14651858.CD001390.pub4

    Article  PubMed  Google Scholar 

  53. 53.

    Global Initiative for Chronic Obstructive Lung Disease. Global Strategy for the Prevention, Diagnosis, and Management of COPD. Fontana, WI. 2019. https://goldcopd.org/wp-content/uploads/2018/11/GOLD-2019-v1.7-FINAL-14Nov2018-WMS.pdf.

  54. 54.

    Joshi S, Nuckols T, Escarce J, Huckfeldt P, Popescu I, Sood N. Regression to the Mean in the Medicare Hospital Readmissions Reduction Program. JAMA Intern Med. 2019;179(9):1167-73. https://doi.org/10.1001/jamainternmed.2019.1004

    Article  Google Scholar 

  55. 55.

    Kaiser Family Foundation. Status of State Action on the Medicaid Expansion Decision. 2019. https://www.kff.org/health-reform/state-indicator/state-activity-around-expanding-medicaid-under-the-affordable-care-act. Accessed November 6 2019.

  56. 56.

    Bennett KJ, Probst JC. Thirty-Day Readmission Rates Among Dual-Eligible Beneficiaries. J Rural Health. 2016;32(2):188-95. https://doi.org/10.1111/jrh.12140

    Article  PubMed  Google Scholar 

  57. 57.

    Joynt Maddox KE, Reidhead M, Qi AC, Nerenz DR. Association of Stratification by Dual Enrollment Status With Financial Penalties in the Hospital Readmissions Reduction Program. JAMA Intern Med. 2019;179(6):769-76. https://doi.org/10.1001/jamainternmed.2019.0117

    Article  PubMed  PubMed Central  Google Scholar 

  58. 58.

    Zuckerman RB, Sheingold SH, Orav EJ, Ruhter J, Epstein AM. Readmissions, Observation, and the Hospital Readmissions Reduction Program. N Engl J Med. 2016;374(16):1543-51. https://doi.org/10.1056/NEJMsa1513024

    CAS  Article  PubMed  Google Scholar 

  59. 59.

    Wadhera RK, Joynt Maddox KE, Kazi DS, Shen C, Yeh RW. Hospital revisits within 30 days after discharge for medical conditions targeted by the Hospital Readmissions Reduction Program in the United States: national retrospective analysis. BMJ. 2019;366:l4563. https://doi.org/10.1136/bmj.l4563

    Article  PubMed  PubMed Central  Google Scholar 

  60. 60.

    Chhabra KR, Ibrahim AM, Thumma JR, Ryan AM, Dimick JB. Impact Of Medicare Readmissions Penalties On Targeted Surgical Conditions. Health Aff (Millwood). 2019;38(7):1207-15. https://doi.org/10.1377/hlthaff.2019.00096

    Article  Google Scholar 

  61. 61.

    Albritton J, Belnap TW, Savitz LA. The Effect Of The Hospital Readmissions Reduction Program On Readmission And Observation Stay Rates For Heart Failure. Health Aff (Millwood). 2018;37(10):1632-9. https://doi.org/10.1377/hlthaff.2018.0064

    Article  Google Scholar 

  62. 62.

    Ody C, Msall L, Dafny LS, Grabowski DC, Cutler DM. Decreases In Readmissions Credited To Medicare’s Program To Reduce Hospital Readmissions Have Been Overstated. Health Aff (Millwood). 2019;38(1):36-43. https://doi.org/10.1377/hlthaff.2018.05178

    Article  Google Scholar 

  63. 63.

    Thompson MP, Kaplan CM, Cao Y, Bazzoli GJ, Waters TM. Reliability of 30-Day Readmission Measures Used in the Hospital Readmission Reduction Program. Health Serv Res. 2016;51(6):2095-114. https://doi.org/10.1111/1475-6773.12587

    Article  PubMed  PubMed Central  Google Scholar 

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Funding

This research was supported in part by the University of California at Los Angeles (UCLA) Clinical and Translational Science Institute, National Institutes of Health/National Center for Advancing Translational Science (NCATS) Grant Number UL1TR001881, and the UCLA Joyce and Saul Brandman Fund for Pulmonary Research. The investigators maintained full independence in conducting the research and the funders had no role in the design of the study or interpretation of the results.

Dr. Buhr was supported by NIH/NCATS UCLA CTSI Grant Number TL1TR001883-01, as well as the UCLA Specialty Training for Advanced Research (STAR) program. Dr. Buhr also received a loan repayment award from NIH National Heart, Lung, and Blood Institute (NHLBI) Grant Number L30HL134025. Dr. Mangione received support from the UCLA Resource Centers for Minority Aging Research Center for Health Improvement of Minority Elderly under National Institutes of Health NIH/NIA under Grant P30AG021684 and from the NIH/NCATS UCLA CTSI under Grant UL1TR001881. Dr. Mangione holds the Barbara A. Levey and Gerald S. Levey Endowed Chair in Medicine, which partially supported her work.

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Contributions

Drs. Buhr and Jackson had full access to all of the data in the study and take responsibility for the integrity of the data and accuracy of the analysis.

Drs. Buhr, Dubinett, Kominski, Ong, and Mangione contributed to the conception and design of the study.

All authors contributed to the drafting of the manuscript. All of the authors listed above approved this version of the manuscript to be published.

Corresponding author

Correspondence to Russell G. Buhr MD, PhD.

Ethics declarations

This study was exempted from review based on its use of deidentified, publicly available data by the UCLA Institutional Review Board (IRB No. 18-001208).

Conflict of Interest

Dr. Buhr received personal consulting fees from GlaxoSmithKline and Mylan/Theravance Biopharma, not related to this work.

Dr. Jackson reports nothing to disclose.

Dr. Kominski reports nothing to disclose.

Dr. Dubinett is a member of the scientific advisory boards of Johnson & Johnson Lung Cancer Initiative, T-cure Bioscience, Cynvenio Biosystems, and EarlyDx, Inc., not related to this work.

Dr. Ong reports nothing to disclose.

Dr. Mangione is a member of the United States Preventive Services Task Force (USPSTF). This article does not necessarily represent the views and policies of the USPSTF.

Drs. Buhr, Ong, and Dubinett are employed part-time by the Veterans Health Administration.

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Buhr, R.G., Jackson, N.J., Kominski, G.F. et al. Readmission Rates for Chronic Obstructive Pulmonary Disease Under the Hospital Readmissions Reduction Program: an Interrupted Time Series Analysis. J GEN INTERN MED (2020). https://doi.org/10.1007/s11606-020-05958-0

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KEY WORDS

  • COPD
  • comorbidity
  • readmission
  • multilevel modeling