Validation of a Predictive Model to Identify Patients at High Risk for Hospital Readmission

Journal for Healthcare Quality

Volumn 38, Issue 1, 2016, Pages 34-41

  Spiva, Leeanna ^a   Hand, Marti ^b   Vanbrackle, Lewis ^a   McVay, Frank ^b  

^a KENNESAW STATE UNIVERSITY   (United States)

^b WellStar Douglas Hospital   (United States)

Author keywords

avoidable; preventable; rates; readmission; rehospitalization

Indexed keywords

COMMUNITY HOSPITAL; CONTROLLED CLINICAL TRIAL; ELECTRONIC MEDICAL RECORD; HOSPITAL READMISSION; HUMAN; HUMAN TISSUE; LOGISTIC REGRESSION ANALYSIS; MAJOR CLINICAL STUDY; PREDICTOR VARIABLE; PROBABILITY; RANDOMIZED CONTROLLED TRIAL; RETROSPECTIVE STUDY; RISK FACTOR; STATISTICAL MODEL; VALIDATION PROCESS; ADULT; AGED; ALGORITHM; FEMALE; FORECASTING; MALE; MIDDLE AGED; PROCEDURES; RISK ASSESSMENT; STATISTICS AND NUMERICAL DATA; TRENDS; UNITED STATES; VALIDATION STUDY;

ADULT; AGED; ALGORITHMS; FEMALE; FORECASTING; HOSPITALS, COMMUNITY; HUMANS; LOGISTIC MODELS; MALE; MIDDLE AGED; PATIENT READMISSION; RETROSPECTIVE STUDIES; RISK ASSESSMENT; RISK FACTORS; SOUTHEASTERN UNITED STATES;

EID: 84978204174     PISSN: 10622551     EISSN: 19451474     Source Type: Journal    
DOI: 10.1111/jhq.12070     Document Type: Article

References (25)

1. Billings, A., Dixon, J., Mijanovich, T., Wennberg, D. Case finding for patients at risk of readmission to hospital: Development of algorithm to identify high risk patients. British Medical Journal 2006;333:327. Retrieved August 30, 2012, from http://www.bmj.com/content/333/7563/327.
2. Bottle, A., Aylin, P., Majeed, A. Identifying patients at high risk of emergency hospital admissions: A logistic regression analysis. Journal of the Royal Society of Medicine 2006;99: 406-414.
3. Cheung, A.M., Tansey, C.M., Tomlinson, G., Diaz?Granados, N., Matte, A., Barr, A., et al. Two?year outcomes, health care use, and costs of survivors of acute respiratory distress syndrome. American Journal Respiratory Critical Care Medicine 2006;174:538-544.
4. Cornish, P.L., Knowles, S.R., Marchesano, R., Tam, V., Shadowitz, S., Juurlink, D.N., et al. Unintended medication discrepancies at the time of hospital admission. Archives of Internal Medicine 2005;165:424-429.
5. Cotter, P.E.,Bhalla,V.K.,Wallis, S.J.,& Biram, R.W. Predicting readmissions: Poor performance of the LACE index in an older UK population. Age and Ageing 2012;41:784-789.
6. Department of Health and Human Services. Application of incentives to reduce avoidable readmissions to hospitals. Federal Registry 2008;73:28-239.
7. Giamouzis, G., Kalogeropoulous, A., Georgiopoulou, V., Laskar, S., Smith, A., Dunbar, S., et al. Hospitalization epidemic in patients with heart failure: Risk factors, risk prediction, knowledge gaps and future directions. Journal of Cardiac Failure 2011;17:54-75.
8. Goldfield, N.I., McCullough, E.C., Hughes, J.S., Tang, A.M., Eastman, B., Rawlins, L.K., et al. Identifying potentially preventable readmissions. Health Care Finance Review 2008;30:75-91.
9. Goodman, D.C., Fisher, E.S., Chang, C.H. After hospitalization: A Dartmouth atlas report on post?acute care for Medicare beneficiaries. Dartmouth Atlas Report. Retrieved November 1, 2011 from http://www. dartmouthatlas.org/downloads/reports/Post-discharge-events-092811.pdf.
10. Gruneir, A., Dhalla, I.A., van Walraven, C., Fisher, H.D., Camacho, X., Rochon, P.A., Anderson, G.M. Unplanned readmissions after hospital discharge among patients identified as being at high risk for readmission using a validated predictive algorithm. Open Medicine 2011;5:e104-e111.
11. Hasan, O., Meltzer, D.O., Shaykevich, S.A., Bell, C.M., Kaboli, P.J., Auerbach, A.D., et al. Hospital readmission in general medicine patients: A prediction model. Journal General Internal Medicine 2010;25:211-219.
12. Jencks, S.F., Williams, M.V., Coleman, E.A. Rehospitalizations among patients in the Medicare fee?for?service program. New England Journal of Medicine 2009;360:1418-1428.
13. Johnson, T., Bardhan, J., Odwazny, R., Harting, B., Skarupski, K., McNutt, R. Hospital care may not affect the risk of readmission. Quality in Management Health Care 2012;21:68-73.
14. Kalisch, B.J., Dabney, B.W., Lee, S. Safety of mobilizing hospitalized adults: Review of the literature. Journal Nursing Care Quality 2013; 28:162-168.
15. Kalisch, B.J., Tschannen, D., Lee, H., Friese, C. Hospital variation in missed nursing care. American Journal Medical Quality 2011;26:291-299.
16. Kalisch, B.J., Williams, R. Development and psychometric testing of a tool to measure missed nursing care. Journal of Nursing Administration 2009;39:211-219.
17. Kansagara, D., Englander, H., Salanitro, A., Kage, D., Theobald, C., Freeman, M., et al. Risk predictionmodels for hospital readmission a systematic review. Journal of the American Medical Association 2011;306:1688-1698.
18. Medicare Payment Advisory Commission. Report to Congress: enhancing Medicare's technical assistance to and oversight of providers. 2011. Retrieved November 1, 2011 from http://www.medpac.gov/documents/Jun11-EntireReport.pdf.
19. Mudge, A.M., Kasper, K., Clair, A., Redfern, H., Bell, J.J., Barras, M.A., et al. Recurrent readmissions inmedical patients: A prospective study. Journal Hospital Medicine 2011;6:61-67.
20. National Quality Forum (NQF). Endorsement summary: All cause readmissions. 2012. Retrieved August 29, 2012, fromhttp://www. qualityforum.org/News-And-Resources/Endorsement-Summaries/AllCause Read missions-Endorsement-Summary.aspx.
21. Office of Management and Budget. Transforming and modernizing America's healthcare system. 2009. Retrieved November 1, 2011 from http://www.whitehouse. gov/omb/fy2010-issue-healthcare.
22. van Walraven, C., Bell, C. Risk of death or readmission among people discharged on Friday. Canadian Medical Association Journal 2002;166:1672-1673.
23. vanWalraven, C.,Dhalla, I.A., Bell, C.,Etchells, E., Stiell, I.G., Zarnke, K., et al. Derivation and validation of an index to predict early death or unplanned readmission after discharge from hospital to the community. Canadian Medical Association Journal 2010;182:551-557.
24. Vest, J.R.,Gamm,L.D.,Oxford,B.A.,Gonzalez, M.I.,Slawson, K.M. Determinants of preventable readmissions in theUnited States:Asystematic review. Implementation Science 2011;5:88. Retrieved August 30, 2012, fromhttp://www. implementationscience.com/content/5/1/88.
25. Yam, C.H., Wong, E.L., Chan, F.W., Wong, F.Y., Leung, M.C., Yeoh, E.K. Measuring and preventing potentially avoidable hospital readmissions: A review of the literature. Hong Kong Medical Journal 2010;16:383-389.