Quantitative tools for addressing hospital readmissions

BMC Research Notes

Mary E Luziani³  Diane S Nanno¹  Ronald J Lagoe² 

[1] Crouse Hospital, Syracuse, NY, 13210, USA;Hospital Executive Council, PO Box 35089, Syracuse, NY, 13235, USA;St. Joseph’s Hospital Health Center, Syracuse, NY, 13203, USA

关键词: Hospital readmissions;    Quality assurance;    Hospitalization;   

Others  :  1165275
DOI  :  10.1186/1756-0500-5-620

 received in 2012-06-01, accepted in 2012-10-25,  发布年份 2012

【 摘 要 】

Background

Increased interest in health care cost containment is focusing attention on reduction of hospital readmissions. Major payors have already developed financial penalties for providers that generate excess readmissions. This subject has benefitted from the development of resources such as the Potentially Preventable Readmissions software. This process has encouraged hospitals to renew efforts to improve these outcomes. The aim of this study was to describe quantitative tools such as definitions, risk estimation, and tracking of patients for reducing hospital readmissions.

Findings

This study employed the Potentially Preventable Readmissions software to develop quantitative tools for addressing hospital readmissions. These tools included two definitions of readmissions that support identification and management of patients. They also included analytical approaches for estimation of the risk of readmission for individual patients by age, discharge status of the initial admission, and severity of illness. They also included patient specific spreadsheets for tracking of target populations and for evaluation of the impact of interventions.

Conclusions

The study demonstrated that quantitative tools including the development of definitions of readmissions, estimation of the risk of readmission, and patient specific spreadsheets could contribute to the improvement of patient outcomes in hospitals.

【 授权许可】

   
2012 Lagoe et al.; licensee BioMed Central Ltd.

【 参考文献 】

• [1]Dentzer S: Urgent measures for an old problem. Health Aff 2011, 30(9):1626.
• [2]Iglehart JK: Desperately seeking savings: States shift more Medicaid enrollees to managed care. Health Aff 2011, 30(9):1627-1629.
• [3]Auerbach DL, Kellermann AL: A decade of health care cost growth has wiped out real income gains for an average US family. Health Aff 2011, 30(9):1630-1636.
• [4]Jencks SF, Williams MV, Coleman EA: Rehospitalizations among patients in the Medicare fee for service program. N Engl J Med 2011, 364(16):1582.
• [5]Rau J: Medicare to Penalize 2,211 Hospitals for Excess Readmissions. Kaiser Health News; 2012.
• [6]Their SO, Cogelijns A: Improving health: the reason performance measurement matters. Health Aff 1998, 17(4):26-28.
• [7]Lagoe RJ, Noetscher CM, Murphy ME: Hospital readmissions at the communitywide level: Implications for case management. J Nurs Care Qual 2000, 14(4):1-15.
• [8]Health Care Financing Administration, Medicare Program: Selected performance information on hospitals providing care to Medicare beneficiaries. Fed Regist 1987, 52:30741-30745.
• [9]Hennen J, et al.: Readmission rates, 30 days and 365 days post discharge among the 20 most frequent DRG groups, Medicare inpatients age 65 and older in Connecticut hospitals, fiscal years 1991, 1992, 1993. Conn Med 1995, 59(5):263-270.
• [10]Ashton CM, et al.: The association between quality of inpatient care and early readmission: meta-analysis of the evidence. Medical Care 1997, 35(10):1044-1059.
• [11]3M™ Health Information Systems: Potentially Preventable Readmissions Classification System. 3M Health Information Systems, Wallingford, Conn; 2008.
• [12]Rumball-Smith J, Hider P: The validity of readmission rate as a marker of the quality of hospital care, and a recommendation for its definition. New Zealand Journal of Medicine 2009, 122(1289):63-70.
• [13]Kansagara D, Englander H, Salanitro A, Kagen D, Theobald C, Freeman M, Kripalani S: Risk prediction models for hospital readmission: A systematic review. JAMA 2011, 306(15):1688-1698.
• [14]Gruneir A, Dhalla IA, van Walraven C, Fischer HD, Camacho X, Rochon PA, Anderson GM: Unplanned readmissions after hospital discharge among patients identified as being at high risk for readmission using a validated predictive algorithm. Open Medicine 2011, 5(2):e104-e111.
• [15]Hasan O, Meltzer DO, Shaykevich SA, Bell CM, Kaboli PJ, Auerbach AD, Wetterneck TB, Arora VM, Zhang J, Schnipper JL: Hospital readmission in general medicine patients: A predictive model. J Gen Intern Med 2010, 25(3):211-219.
• [16]Garcia-Perez L, Linertova R, Lorenzo-Riera A, Vazquez-Diaz JR, Duque-Gonzalez , Sarria-Santamera A: Risk factors for hospital readmissions in elderly patients: A systematic review. Q J M 2011, 104(8):639-651.
• [17]Hannan EL, Zhong Y, Lahey SJ, Culliford AT, Gold JP, Smith CR, Higgins RS, Jordan D, Wechsler A: 30 – day readmissions after coronary artery bypass graft surgery in New York State. JACC Cardiovasc Interv 2011, 4(5):569-576.
• [18]van Walraven C, Bennett C, Jennings A, Austin PC, Forster AJ: Proportion of hospital readmissions deemed avoidable: A systematic review. CMAJ 2011, 183(7):E391-E402.
• [19]Allaudeen N, Schnipper JL, Orav EJ, Wachter RM, Vidyarthi AR: Inability of providers to predict unplanned readmissions. J Gen Intern Med 2011, 26(7):771-776.
• [20]van den Bosch WF, Kelder JC, Wagner C: Predicting hospital mortality among frequently readmitted patients. BMC Health Serv Res 2011, 11:57. BioMed Central Full Text
• [21]Glynn N, Bennett K, Silke B: Emergency medical readmission: long-term trends and impact on mortality. Clinics in Medicine 2011, 11(2):114-118.
• [22]Hansen LO, Young RS, Hinami K, Leung A, Williams MV: Interventions to reduce 30-day rehospitalization: a systematic review. Ann Intern Med 2011, 155(8):520-528.
• [23]Cakir B, Gammon G: Evaluating readmission rates: how can we improve? Southern Medicine Journal 2010, 103(11):1079-1083.
• [24]Jha AK, Orav EJ, Epstein AM: Public reporting of discharge planning and rates of readmissions. N Engl J Med 2009, 361(27):2637-2645.
• [25]Lagoe R, Pasinski T, Kronenberg P, Quinn T, Schaengold P: Linking health services at the community level. Canada Healthcare Quarterly 2006, 9(3):60-65.