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Australian Health Review Australian Health Review Society
Journal of the Australian Healthcare & Hospitals Association
RESEARCH ARTICLE

Readmissions following hospitalisations for cardiovascular disease: a scoping review of the Australian literature

Clementine Labrosciano https://orcid.org/0000-0001-5995-4616 A B C , Tracy Air A B , Rosanna Tavella B C D , John F. Beltrame B C D and Isuru Ranasinghe A C D E
+ Author Affiliations
- Author Affiliations

A Health Performance and Policy Research Unit, Basil Hetzel Institute for Translational Research, 37A Woodville Road, Woodville South, SA 5011, Australia. Email: clementine.labrosiano@adelaide.edu.au; tracy.air@adelaide.edu.au

B Translational Vascular Function Research Collaborative, Basil Hetzel Institute for Translational Research, 37A Woodville Road, Woodville South, SA 5011, Australia. Email: rosanna.tavella@adelaide.edu.au; john.beltrame@adelaide.edu.au

C Discipline of Medicine, University of Adelaide, 28 Woodville Road, Woodville South, SA 5011, Australia.

D Central Adelaide Local Health Network, SA Health, The Queen Elizabeth Hospital, 28 Woodville Road, Woodville South, SA 5011, Australia.

E Corresponding author. Email: isuru.ranasinghe@adelaide.edu.au

Australian Health Review 44(1) 93-103 https://doi.org/10.1071/AH18028
Submitted: 5 February 2018  Accepted: 23 October 2018   Published: 20 February 2019

Abstract

Objective International studies suggest high rates of readmissions after cardiovascular hospitalisations, but the burden in Australia is uncertain. We summarised the characteristics, frequency, risk factors of readmissions and interventions to reduce readmissions following cardiovascular hospitalisation in Australia.

Methods A scoping review of the published literature from 2000–2016 was performed using Medline, EMBASE and Cumulative Index to Nursing and Allied Health Literature (CINAHL) databases and relevant grey literature.

Results We identified 35 studies (25 observational, 10 reporting outcomes of interventions). Observational studies were typically single-centre (11/25) and reported readmissions following hospitalisations for heart failure (HF; 10/25), acute coronary syndrome (7/25) and stroke (6/25), with other conditions infrequently reported. The definition of a readmission was heterogeneous and was assessed using diverse methods. Readmission rate, most commonly reported at 1 month (14/25), varied from 6.3% to 27%, with readmission rates of 10.1–27% for HF, 6.5–11% for stroke and 12.7–17% for acute myocardial infarction, with a high degree of heterogeneity among studies. Of the 10 studies of interventions to reduce readmissions, most (n = 8) evaluated HF management programs and three reported a significant reduction in readmissions. We identified a lack of national studies of readmissions and those assessing the cost and resource impact of readmissions on the healthcare system as well as a paucity of successful interventions to lower readmissions.

Conclusions High rates of readmissions are reported for cardiovascular conditions, although substantial methodological heterogeneity exists among studies. Nationally standardised definitions are required to accurately measure readmissions and further studies are needed to address knowledge gaps and test interventions to lower readmissions in Australia.

What is known about the topic? International studies suggest readmissions are common following cardiovascular hospitalisations and are costly to the health system, yet little is known about the burden of readmission in the Australian setting or the effectiveness of intervention to reduce readmissions.

What does this paper add? We found relatively high rates of readmissions following common cardiovascular conditions although studies differed in their methodology making it difficult to accurately gauge the readmission rate. We also found several knowledge gaps including lack of national studies, studies assessing the impact on the health system and few interventions proven to reduce readmissions in the Australian setting.

What are the implications for practitioners? Practitioners should be cautious when interpreting studies of readmissions due the heterogeneity in definitions and methods used in Australian literature. Further studies are needed to test interventions to reduce readmissions in the Australians setting.


References

[1]  Australian Institute of Health and Welfare (AIHW). Cardiovascular disease: Australian facts 2011. Cardiovascular disease series. Canberra: AIHW; 2011. Available at: https://www.aihw.gov.au/getmedia/9621f6a8-f076-4e3e-a9c7-dece59ff0d74/12116.pdf.aspx?inline=true [verified 8 December 2018].

[2]  Australian Institute of Health and Welfare (AIHW). Australia’s health 2016. Australia’s health series. Canberra: AIHW; 2016. Available at: https://www.aihw.gov.au/getmedia/9844cefb-7745-4dd8-9ee2-f4d1c3d6a727/19787-AH16.pdf.aspx?inline=true [verified 8 December 2018].

[3]  Keenan PS, Normand SL, Lin Z, Drye EE, Bhat KR, Ross JS, Schuur JD, Stauffer BD, Bernheim SM, Epstein AJ, Wang Y, Herrin J, Chen J, Federer JJ, Mattera JA, Wang Y, Krumholz HM. An administrative claims measure suitable for profiling hospital performance on the basis of 30-day all-cause readmission rates among patients with heart failure. Circ Cardiovasc Qual Outcomes 2008; 1 29–37.
An administrative claims measure suitable for profiling hospital performance on the basis of 30-day all-cause readmission rates among patients with heart failure.Crossref | GoogleScholarGoogle Scholar | 20031785PubMed |

[4]  Gheorghiade M, Zannad F, Sopko G, Klein L, Pina IL, Konstam MA, Massie BM, Roland E, Targum S, Collins SP, Filippatos G, Tavazzi L. Acute heart failure syndromes: current state and framework for future research. Circulation 2005; 112 3958–68.
Acute heart failure syndromes: current state and framework for future research.Crossref | GoogleScholarGoogle Scholar | 16365214PubMed |

[5]  Lichtman JH, Leifheit-Limson EC, Jones SB, Wang Y, Goldstein LB. Preventable readmissions within 30 days of ischemic stroke among Medicare beneficiaries. Stroke 2013; 44 3429–35.
Preventable readmissions within 30 days of ischemic stroke among Medicare beneficiaries.Crossref | GoogleScholarGoogle Scholar | 24172581PubMed |

[6]  Bravata DM, Ho SY, Meehan TP, Brass LM, Concato J. Readmission and death after hospitalization for acute ischemic stroke: 5-year follow-up in the Medicare population. Stroke 2007; 38 1899–904.
Readmission and death after hospitalization for acute ischemic stroke: 5-year follow-up in the Medicare population.Crossref | GoogleScholarGoogle Scholar | 17510453PubMed |

[7]  Hannan EL, Zhong Y, Krumholz H, Walford G, Holmes DR, Stamato NJ, Jacobs AK, Venditti FJ, Sharma S, King SB. 30-Day readmission for patients undergoing percutaneous coronary interventions in New York state. JACC Cardiovasc Interv 2011; 4 1335–42.
30-Day readmission for patients undergoing percutaneous coronary interventions in New York state.Crossref | GoogleScholarGoogle Scholar | 22192374PubMed |

[8]  Secemsky EA, Schermerhorn M, Carroll BJ, Kennedy KF, Shen C, Valsdottir LR, Landon B, Yeh RW. Readmissions after revascularization procedures for peripheral arterial disease: a nationwide cohort study. Ann Intern Med 2018; 168 93–9.
Readmissions after revascularization procedures for peripheral arterial disease: a nationwide cohort study.Crossref | GoogleScholarGoogle Scholar | 29204656PubMed |

[9]  van Walraven C, Jennings A, Forster AJ. A meta-analysis of hospital 30-day avoidable readmission rates. J Eval Clin Pract 2012; 18 1211–18.
A meta-analysis of hospital 30-day avoidable readmission rates.Crossref | GoogleScholarGoogle Scholar | 22070191PubMed |

[10]  Giamouzis G, Kalogeropoulos A, Georgiopoulou V, Laskar S, Smith AL, Dunbar S, Triposkiadis F, Butler J. Hospitalization epidemic in patients with heart failure: risk factors, risk prediction, knowledge gaps, and future directions. J Card Fail 2011; 17 54–75.
Hospitalization epidemic in patients with heart failure: risk factors, risk prediction, knowledge gaps, and future directions.Crossref | GoogleScholarGoogle Scholar | 21187265PubMed |

[11]  Higgins JPT, Thompson SG, Deeks JJ, Altman DG. Measuring inconsistency in meta-analyses. BMJ 2003; 327 557–60.
Measuring inconsistency in meta-analyses.Crossref | GoogleScholarGoogle Scholar |

[12]  Moher D, Liberati A, Tetzlaff J, Altman DG. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. Ann Intern Med 2009; 151 264–9.
Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement.Crossref | GoogleScholarGoogle Scholar | 19622511PubMed |

[13]  Paul B, Soon KH, Dunne J, De Pasquale CG. Diagnostic and prognostic significance of plasma N-terminal-pro-brain natriuretic peptide in decompensated heart failure with preserved ejection fraction. Heart Lung Circ 2008; 17 497–501.
Diagnostic and prognostic significance of plasma N-terminal-pro-brain natriuretic peptide in decompensated heart failure with preserved ejection fraction.Crossref | GoogleScholarGoogle Scholar | 18722158PubMed |

[14]  Pathik B, De Pasquale CG, McGavigan AD, Sinhal A, Vaile J, Tideman PA, Jones D, Bridgman C, Selvanayagam JB, Heddle W, Chew DP. Subspecialisation in cardiology care and outcome: should clinical services be redesigned, again? Intern Med J 2016; 46 158–66.
Subspecialisation in cardiology care and outcome: should clinical services be redesigned, again?Crossref | GoogleScholarGoogle Scholar | 26387874PubMed |

[15]  Kilkenny MF, Dewey HM, Sundararajan V, Andrew NE, Lannin N, Anderson CS, Donnan GA, Cadilhac DA. Readmissions after stroke: linked data from the Australian Stroke Clinical Registry and hospital databases. Med J Aust 2015; 203 102–6.
Readmissions after stroke: linked data from the Australian Stroke Clinical Registry and hospital databases.Crossref | GoogleScholarGoogle Scholar | 26175251PubMed |

[16]  Yu S, Arima H, Bertmar C, Hirakawa Y, Priglinger M, Evans K, Krause M. Depression but not anxiety predicts recurrent cerebrovascular events. Acta Neurol Scand 2016; 134 29–34.
Depression but not anxiety predicts recurrent cerebrovascular events.Crossref | GoogleScholarGoogle Scholar | 26411629PubMed |

[17]  Nguyen TN, Cumming RG, Hilmer SN. The impact of frailty on mortality, length of stay and re-hospitalisation in older patients with atrial fibrillation. Heart Lung Circ 2016; 25 551–7.
The impact of frailty on mortality, length of stay and re-hospitalisation in older patients with atrial fibrillation.Crossref | GoogleScholarGoogle Scholar | 26809464PubMed |

[18]  Rana S, Tran T, Luo W, Phung D, Kennedy RL, Venkatesh S. Predicting unplanned readmission after myocardial infarction from routinely collected administrative hospital data. Aust Health Rev 2014; 38 377–82.
Predicting unplanned readmission after myocardial infarction from routinely collected administrative hospital data.Crossref | GoogleScholarGoogle Scholar | 25001433PubMed |

[19]  Parker GB, Hilton TM, Walsh WF, Owen CA, Heruc GA, Olley A, Brotchie H, Hadzi-Pavlovic D. Timing is everything: the onset of depression and acute coronary syndrome outcome. Biol Psychiatry 2008; 64 660–6.
Timing is everything: the onset of depression and acute coronary syndrome outcome.Crossref | GoogleScholarGoogle Scholar | 18602090PubMed |

[20]  Dwyer JP, Redfern J, Freedman SB. Low utilisation of cardiovascular risk reducing therapy in patients with acute coronary syndromes and non-obstructive coronary artery disease. Int J Cardiol 2008; 129 394–8.
Low utilisation of cardiovascular risk reducing therapy in patients with acute coronary syndromes and non-obstructive coronary artery disease.Crossref | GoogleScholarGoogle Scholar | 18295912PubMed |

[21]  Murphy BM, Elliott PC, Le Grande MR, Higgins RO, Ernest CS, Goble AJ, Tatoulis J, Worcester MU. Living alone predicts 30-day hospital readmission after coronary artery bypass graft surgery. Eur J Cardiovasc Prev Rehabil 2008; 15 210–5.
Living alone predicts 30-day hospital readmission after coronary artery bypass graft surgery.Crossref | GoogleScholarGoogle Scholar | 18391650PubMed |

[22]  Tully PJ, Baker RA, Turnbull D, Winefield H. The role of depression and anxiety symptoms in hospital readmissions after cardiac surgery. J Behav Med 2008; 31 281–90.
The role of depression and anxiety symptoms in hospital readmissions after cardiac surgery.Crossref | GoogleScholarGoogle Scholar | 18398676PubMed |

[23]  Saito M, Negishi K, Eskandari M, Huynh Q, Hawson J, Moore A, Koneru S, Foster S, Marwick TH. Association of left ventricular strain with 30-day mortality and readmission in patients with heart failure. J Am Soc Echocardiogr 2015; 28 652–66.
Association of left ventricular strain with 30-day mortality and readmission in patients with heart failure.Crossref | GoogleScholarGoogle Scholar | 25783858PubMed |

[24]  Islam T, O’Connell B, Lakhan P. Hospital readmission among older adults with congestive heart failure. Aust Health Rev 2013; 37 362–8.
| 23701906PubMed |

[25]  Betihavas V, Frost SA, Newton PJ, Macdonald P, Stewart S, Carrington MJ, Chan YK, Davidson PM. An absolute risk prediction model to determine unplanned cardiovascular readmissions for adults with chronic heart failure. Heart Lung Circ 2015; 24 1068–73.
An absolute risk prediction model to determine unplanned cardiovascular readmissions for adults with chronic heart failure.Crossref | GoogleScholarGoogle Scholar | 26048319PubMed |

[26]  Lefkovits J, Brennan A, Dinh D, Brien R, Driscoll A, Reid C; on behalf of the Victorian Cardiac Outcomes Registry (VCOR). The Victorian Cardiac Outcomes Registry annual report 2015. Melbourne: Monash University, DEPM; 2016. Available at: https://vcor.org.au/sites/default/files/VCOR_files/2015_vcor_annual_report.pdf [verified 8 December 2018].

[27]  Kilkenny MF, Longworth M, Pollack M, Levi C, Cadilhac DA. Factors associated with 28-day hospital readmission after stroke in Australia. Stroke 2013; 44 2260–8.
Factors associated with 28-day hospital readmission after stroke in Australia.Crossref | GoogleScholarGoogle Scholar | 23800558PubMed |

[28]  Bureau of Health Information (BHI). Return to acute care following hospitalisation: spotlight on readmissions. Sydney: BHI; 2015.

[29]  Cadilhac DA, Kim J, Lannin NA, Levi CR, Dewey HM, Hill K, Faux S, Andrew NE, Kilkenny MF, Grimley R, Thrift AG, Grabsch B, Middleton S, Anderson CS, Donnan GA, Australian Stroke Clinical Registry Consortium Better outcomes for hospitalized patients with TIA when in stroke units: an observational study. Neurology 2016; 86 2042–8.
Better outcomes for hospitalized patients with TIA when in stroke units: an observational study.Crossref | GoogleScholarGoogle Scholar | 27164692PubMed |

[30]  Huynh QL, Saito M, Blizzard CL, Eskandari M, Johnson B, Adabi G, Hawson J, Negishi K, Marwick TH. Roles of nonclinical and clinical data in prediction of 30-day rehospitalization or death among heart failure patients. J Card Fail 2015; 21 374–81.
Roles of nonclinical and clinical data in prediction of 30-day rehospitalization or death among heart failure patients.Crossref | GoogleScholarGoogle Scholar | 25724302PubMed |

[31]  Robertson J, McElduff P, Pearson SA, Henry DA, Inder KJ, Attia JR. The health services burden of heart failure: an analysis using linked population health data-sets [published erratum appears in BMC Health Serv Res 2013; 13: 179]. BMC Health Serv Res 2012; 12 103
The health services burden of heart failure: an analysis using linked population health data-sets [published erratum appears in BMC Health Serv Res 2013; 13: 179].Crossref | GoogleScholarGoogle Scholar | 22533631PubMed |

[32]  He VY, Condon JR, You J, Zhao Y, Burrow JN. Adverse outcome after incident stroke hospitalization for Indigenous and non-Indigenous Australians in the Northern Territory. Int J Stroke 2015; 10 89–95.
Adverse outcome after incident stroke hospitalization for Indigenous and non-Indigenous Australians in the Northern Territory.Crossref | GoogleScholarGoogle Scholar | 26352280PubMed |

[33]  Worrall-Carter L, McEvedy S, Wilson A, Rahman MA. Gender differences in presentation, coronary intervention, and outcomes of 28,985 acute coronary syndrome patients in Victoria, Australia. Womens Health Issues 2016; 26 14–20.
Gender differences in presentation, coronary intervention, and outcomes of 28,985 acute coronary syndrome patients in Victoria, Australia.Crossref | GoogleScholarGoogle Scholar | 26701204PubMed |

[34]  Slamowicz R, Erbas B, Sundararajan V, Dharmage S. Predictors of readmission after elective coronary artery bypass graft surgery. Aust Health Rev 2008; 32 677–83.
Predictors of readmission after elective coronary artery bypass graft surgery.Crossref | GoogleScholarGoogle Scholar | 18980563PubMed |

[35]  Kociol RD, Lopes RD, Clare R, Thomas L, Mehta RH, Kaul P, Pieper KS, Hochman JS, Weaver WD, Armstrong PW, Granger CB, Patel MR. International variation in and factors associated with hospital readmission after myocardial infarction. JAMA 2012; 307 66–74.
International variation in and factors associated with hospital readmission after myocardial infarction.Crossref | GoogleScholarGoogle Scholar | 22215167PubMed |

[36]  Oldland E, Driscoll A, Currey J. High complexity chronic heart failure management programmes: programme characteristics and 12 month patient outcomes. Collegian 2014; 21 319–26.
High complexity chronic heart failure management programmes: programme characteristics and 12 month patient outcomes.Crossref | GoogleScholarGoogle Scholar | 25632729PubMed |

[37]  Atkins ER, Geelhoed EA, Knuiman M, Briffa TG. One third of hospital costs for atherothrombotic disease are attributable to readmissions: a linked data analysis. BMC Health Serv Res 2014; 14 338
One third of hospital costs for atherothrombotic disease are attributable to readmissions: a linked data analysis.Crossref | GoogleScholarGoogle Scholar | 25102911PubMed |

[38]  New South Wales Auditor-General. Performance audit, managing length of stay and unplanned readmissions in NSW public hospitals. Sydney: Audit Office of New South Wales; 2015. Available at: https://www.audit.nsw.gov.au/ArticleDocuments/358/01_Managing_Length_ of_Stay_Hospital_Readmission_Full_Report.pdf.aspx?Embed=Y [verified 8 December 2018].

[39]  Betihavas V, Davidson PM, Newton PJ, Frost SA, Macdonald PS, Stewart S. What are the factors in risk prediction models for rehospitalisation for adults with chronic heart failure? Aust Crit Care 2012; 25 31–40.
What are the factors in risk prediction models for rehospitalisation for adults with chronic heart failure?Crossref | GoogleScholarGoogle Scholar | 21889893PubMed |

[40]  Stewart S, Ball J, Horowitz JD, Marwick TH, Mahadevan G, Wong C, Abhayaratna WP, Chan YK, Esterman A, Thompson DR, Scuffham PA, Carrington MJ. Standard versus atrial fibrillation-specific management strategy (SAFETY) to reduce recurrent admission and prolong survival: pragmatic, multicentre, randomised controlled trial. Lancet 2015; 385 775–84.
Standard versus atrial fibrillation-specific management strategy (SAFETY) to reduce recurrent admission and prolong survival: pragmatic, multicentre, randomised controlled trial.Crossref | GoogleScholarGoogle Scholar | 25467562PubMed |

[41]  Davidson PM, Cockburn J, Newton PJ, Webster JK, Betihavas V, Howes L, Owensby DO. Can a heart failure-specific cardiac rehabilitation program decrease hospitalizations and improve outcomes in high-risk patients? Eur J Cardiovasc Prev Rehabil 2010; 17 393–402.
Can a heart failure-specific cardiac rehabilitation program decrease hospitalizations and improve outcomes in high-risk patients?Crossref | GoogleScholarGoogle Scholar | 20498608PubMed |

[42]  Driscoll A, Tonkin A, Stewart A, Worrall-Carter L, Thompson DR, Riegel B, Hare DL, Davidson PM, Mulvany C, Stewart S. Complexity of management and health outcomes in a prospective cohort study of 573 heart failure patients in Australia: does more equal less? J Clin Nurs 2013; 22 1629–38.
Complexity of management and health outcomes in a prospective cohort study of 573 heart failure patients in Australia: does more equal less?Crossref | GoogleScholarGoogle Scholar | 23387324PubMed |

[43]  Stewart S, Carrington MJ, Marwick TH, Davidson PM, Macdonald P, Horowitz JD, Krum H, Newton PJ, Reid C, Chan YK, Scuffham PA. Impact of home versus clinic-based management of chronic heart failure: the WHICH? (Which Heart Failure Intervention Is Most Cost-Effective & Consumer Friendly in Reducing Hospital Care) multicenter, randomized trial. J Am Coll Cardiol 2012; 60 1239–48.
Impact of home versus clinic-based management of chronic heart failure: the WHICH? (Which Heart Failure Intervention Is Most Cost-Effective & Consumer Friendly in Reducing Hospital Care) multicenter, randomized trial.Crossref | GoogleScholarGoogle Scholar | 23017533PubMed |

[44]  Roughead EE, Barratt JD, Ramsay E, Pratt N, Ryan P, Peck R, Killer G, Gilbert AL. The effectiveness of collaborative medicine reviews in delaying time to next hospitalization for patients with heart failure in the practice setting: results of a cohort study. Circ Heart Fail 2009; 2 424–8.
The effectiveness of collaborative medicine reviews in delaying time to next hospitalization for patients with heart failure in the practice setting: results of a cohort study.Crossref | GoogleScholarGoogle Scholar | 19808372PubMed |

[45]  Barker A, Barlis P, Berlowitz D, Page K, Jackson B, Lim WK. Pharmacist directed home medication reviews in patients with chronic heart failure: a randomised clinical trial. Int J Cardiol 2012; 159 139–43.
Pharmacist directed home medication reviews in patients with chronic heart failure: a randomised clinical trial.Crossref | GoogleScholarGoogle Scholar | 21392837PubMed |

[46]  Scott IA, Darwin IC, Harvey KH, Duke AB, Buckmaster ND, Atherton J, Harden H, Ward M. Multisite, quality-improvement collaboration to optimise cardiac care in Queensland public hospitals. Med J Aust 2004; 180 392–7.
| 15089729PubMed |

[47]  Mudge A, Denaro C, Scott I, Bennett C, Hickey A, Jones MA. The paradox of readmission: effect of a quality improvement program in hospitalized patients with heart failure. J Hosp Med 2010; 5 148–53.
The paradox of readmission: effect of a quality improvement program in hospitalized patients with heart failure.Crossref | GoogleScholarGoogle Scholar | 20235283PubMed |

[48]  Martin L, Murphy M, Scanlon A, Clark D, Farouque O. The impact on long term health outcomes for STEMI patients during a period of process change to reduce door to balloon time. Eur J Cardiovasc Nurs 2016; 15 e37–44.
The impact on long term health outcomes for STEMI patients during a period of process change to reduce door to balloon time.Crossref | GoogleScholarGoogle Scholar | 25784283PubMed |

[49]  Stewart S, Carrington MJ, Horowitz JD, Marwick TH, Newton PJ, Davidson PM, Macdonald P, Thompson DR, Chan YK, Krum H, Reid C, Scuffham PA. Prolonged impact of home versus clinic-based management of chronic heart failure: extended follow-up of a pragmatic, multicentre randomized trial cohort. Int J Cardiol 2014; 174 600–10.
Prolonged impact of home versus clinic-based management of chronic heart failure: extended follow-up of a pragmatic, multicentre randomized trial cohort.Crossref | GoogleScholarGoogle Scholar | 24825029PubMed |

[50]  Korda RJ, Du W, Day C, Page K, Macdonald PS, Banks E. Variation in readmission and mortality following hospitalisation with a diagnosis of heart failure: prospective cohort study using linked data. BMC Health Serv Res 2017; 17 220
Variation in readmission and mortality following hospitalisation with a diagnosis of heart failure: prospective cohort study using linked data.Crossref | GoogleScholarGoogle Scholar | 28320381PubMed |

[51]  Sutherland K, Marashi-Pour S, Chen HT, Morgan A, Levesque JF. Recast the debate about preventable readmissions. BMJ Qual Saf 2016; 25 386–7.
Recast the debate about preventable readmissions.Crossref | GoogleScholarGoogle Scholar | 26733726PubMed |

[52]  Southern DA, Ngo J, Martin BJ, Galbraith PD, Knudtson ML, Ghali WA, James MT, Wilton SB. Characterizing types of readmission after acute coronary syndrome hospitalization: implications for quality reporting. J Am Heart Assoc 2014; 3 e001046
Characterizing types of readmission after acute coronary syndrome hospitalization: implications for quality reporting.Crossref | GoogleScholarGoogle Scholar | 25237046PubMed |

[53]  Feltner C, Jones CD, Cene CW, Zheng ZJ, Sueta CA, Coker-Schwimmer EJ, Arvanitis M, Lohr KN, Middleton JC, Jonas DE. Transitional care interventions to prevent readmissions for persons with heart failure: a systematic review and meta-analysis. Ann Intern Med 2014; 160 774–84.
Transitional care interventions to prevent readmissions for persons with heart failure: a systematic review and meta-analysis.Crossref | GoogleScholarGoogle Scholar | 24862840PubMed |

[54]  Coleman EA, Berenson RA. Lost in transition: challenges and opportunities for improving the quality of transitional care. Ann Intern Med 2004; 141 533–6.
Lost in transition: challenges and opportunities for improving the quality of transitional care.Crossref | GoogleScholarGoogle Scholar | 15466770PubMed |

[55]  Jack BW, Chetty VK, Anthony D, Greenwald JL, Sanchez GM, Johnson AE, Forsythe SR, O’Donnell JK, Paasche-Orlow MK, Manasseh C, Martin S, Culpepper L. A reengineered hospital discharge program to decrease rehospitalization: a randomized trial. Ann Intern Med 2009; 150 178–87.
A reengineered hospital discharge program to decrease rehospitalization: a randomized trial.Crossref | GoogleScholarGoogle Scholar | 19189907PubMed |

[56]  Krumholz HM, Wang Y, Mattera JA, Wang Y, Han LF, Ingber MJ, Roman S, Normand S-LT. An administrative claims model suitable for profiling hospital performance based on 30-day mortality rates among patients with heart failure. Circulation 2006; 113 1693–701.
An administrative claims model suitable for profiling hospital performance based on 30-day mortality rates among patients with heart failure.Crossref | GoogleScholarGoogle Scholar | 16549636PubMed |

[57]  Krumholz HM, Keenan PS, Brush JE, Bufalino VJ, Chernew ME, Epstein AJ, Heidenreich PA, Ho V, Masoudi FA, Matchar DB, Normand SL, Rumsfeld JS, Schuur JD, Smith SC, Spertus JA, Walsh MN. Standards for measures used for public reporting of efficiency in health care: a scientific statement from the American Heart Association Interdisciplinary Council on Quality of Care and Outcomes research and the American College of Cardiology Foundation. J Am Coll Cardiol 2008; 52 1518–26.
Standards for measures used for public reporting of efficiency in health care: a scientific statement from the American Heart Association Interdisciplinary Council on Quality of Care and Outcomes research and the American College of Cardiology Foundation.Crossref | GoogleScholarGoogle Scholar | 19017522PubMed |

[58]  Dehmer GJ, Drozda JP, Brindis RG, Masoudi FA, Rumsfeld JS, Slattery LE, Oetgen WJ. Public reporting of clinical quality data: an update for cardiovascular specialists. J Am Coll Cardiol 2014; 63 1239–45.
Public reporting of clinical quality data: an update for cardiovascular specialists.Crossref | GoogleScholarGoogle Scholar | 24509280PubMed |

[59]  Centre for Medicare and Medicaid Services 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. Final rules. Fed Regist 2013; 78 50495–1040.
| 23977713PubMed |

[60]  Gerhardt G, Yemane A, Hickman P, Oelschlaeger A, Rollins E, Brennan N. Medicare readmission rates showed meaningful decline in 2012. Medicare Medicaid Res Rev 2013; 3 E1–E12.
Medicare readmission rates showed meaningful decline in 2012.Crossref | GoogleScholarGoogle Scholar |