Predictors of transfer from rehabilitation to acute care in burn injuries

Journal of Trauma and Acute Care Surgery

Volumn 73, Issue 6, 2012, Pages 1596-1601

  Schneider, Jeffrey C ^a   Gerrard, Paul ^a   Goldstein, Richard ^a   Divita, Margaret A ^d   Niewczyk, Paulette ^d   Ryan, Colleen M ^b,c   Tan, Wei Han ^a   Kowalske, Karen ^e   Zafonte, Ross ^a  

^a and Red Sox Foundation and Massachusetts General Hospital Home Base Program   (United States)

^b MASSACHUSETTS GENERAL HOSPITAL   (United States)

^c SHRINERS HOSPITALS FOR CHILDREN   (United States)

^d DAEMEN COLLEGE   (United States)

^e UNIVERSITY OF TEXAS AT DALLAS   (United States)

Author keywords

Burn injury; complications; outcomes; rehabilitation; risk factors

Indexed keywords

ACUTE TRANSFER RISK SCORING SYSTEM; ADULT; AGE; AGED; ARTICLE; BURN; CLINICAL CLASSIFICATION; CROSS-SECTIONAL STUDY; EMERGENCY CARE; FEMALE; FUNCTIONAL ASSESSMENT; HOSPITAL ADMISSION; HUMAN; MAJOR CLINICAL STUDY; MALE; PATIENT TRANSPORT; PREDICTOR VARIABLE; PRIORITY JOURNAL; REHABILITATION CARE; RETROSPECTIVE STUDY; SCORING SYSTEM; VALIDITY;

BURNS; CROSS-SECTIONAL STUDIES; FEMALE; HUMANS; INTENSIVE CARE; LOGISTIC MODELS; MALE; MIDDLE AGED; PATIENT READMISSION; PATIENT TRANSFER; RETROSPECTIVE STUDIES; RISK FACTORS;

EID: 84871201630     PISSN: 21630755     EISSN: 21630763     Source Type: Journal    
DOI: 10.1097/TA.0b013e318270d73d     Document Type: Article

References (31)

1. Gomez M, Cartotto R, Knighton J, et al. Improved survival following thermal injury in adult patients treated at a regional burn center. J Burn Care Res. 2008;29:130-137.
2. Sliwa JA, Heinemann A, Semik P. Inpatient rehabilitation following burn injury: patient demographics and functional outcomes. Arch Phys Med Rehabil. 2005;86:1920-1923.
3. MedPAC. Promoting Greater Efficiency in Medicine. Report to the Congress:Medicare Payment Advisory Commission; Washington, DC. 2007.
4. Jencks SF,Williams MV, Coleman EA. Rehospitalizations among patients in the Medicare fee-for-service program. N Engl J Med. 2009;360: 1418-1428.
5. RothEJ,LovellL,HarveyRL, et al. Incidence of and risk factors for medical complications during stroke rehabilitation. Stroke. 2001;32:523-529.
6. Stineman MG, Ross R, Maislin G, et al. Risks of acute hospital transfer and mortality during stroke rehabilitation. Arch Phys Med Rehabil. 2003;84:712-718.
7. Wright RE, Rao N, Smith RM, et al. Risk factors for death and emergency transfer in acute and subacute inpatient rehabilitation. Arch Phys Med Rehabil. 1996;77:1049-1055.
8. Deshpande AA, Millis SR, Zafonte RD, et al. Risk factors for acute care transfer among traumatic brain injury patients. Arch Phys Med Rehabil. 1997;78:350-352.
9. Guo Y, Persyn L, Palmer JL, et al. Incidence of and risk factors for transferring cancer patients from rehabilitation to acute care units. Am J Phys Med Rehabil. 2008;87:647-653.
10. Alam E, Wilson RD, Vargo MM. Inpatient cancer rehabilitation: a retrospective comparison of transfer back to acute care between patients with neoplasm and other rehabilitation patients. Arch Phys Med Rehabil. 2008;89:1284-1289.
11. Schneider J, Tan W-H, Goldstein R, et al. Evaluation of zero onset days in burn rehabilitation. Am J Phys Med Rehabil. 2010;89:S36.
12. Tan WH, Goldstein R, Gerrard P, et al. Outcomes and predictors in burn rehabilitation. J Burn Care Res. 2012;33:110-117.
13. Elixhauser A, Steiner C, Harris DR, et al. Comorbidity measures for use with administrative data. Med Care. 1998;36:8-27.
14. Healthcare Cost and Utilization Project. Comorbidity Software. Version 3.5: Available at: http://www.hcup-us.ahrq.gov/toolssoftware/comorbidity/ comorbidity.jsp. Accessed June 14, 2012
15. Sterne JA, White IR, Carlin JB, et al. Multiple imputation for missing data in epidemiological and clinical research: potential and pitfalls. BMJ. 2009;338:b2393.
16. Grunkemeier GL, Wu Y. Bootstrap resampling methods: something for nothing? Ann Thorac Surg. 2004;77:1142-1144.
17. Sullivan LM, Massaro JM, D'Agostino RB Sr. Presentation of multivariate data for clinical use: the Framingham Study risk score functions. Stat Med. 2004;23:1631-1660.
18. Steyerberg EW, Harrell FE Jr, Borsboom GJ, et al. Internal validation of predictive models: efficiency of some procedures for logistic regression analysis. J Clin Epidemiol. 2001;54:774-781.
19. America's Healthy Future Act of 2009
20. Stillman G, Granger C, Niewczyk P. Projecting function of stroke patients in rehabilitation using the AlphaFIM instrument in acute care. PM R. 2009;1:234-239.
21. Kansagra D, Englander H, Salanitro A, et al. Risk prediction models for hospital readmission: a systematic review. JAMA. 2011;306:1688-1698.
22. Lichtman JH, Leifheit-Limson EC, Jones SB, et al. Predictors of hospital readmission after stroke: a systematic review. Stroke. 2010;41: 2525-2533.
23. Ryan CM, Schoenfeld DA, Thorpe WP, et al. Objective estimates of the probability of death from burn injuries. N Engl J Med. 1998;338: 362-366.
24. Thombs BD, Singh VA, Halonen J, et al. The effects of preexisting medical comorbidities on mortality and length of hospital stay in acute burn injury: evidence from a national sample of 31,338 adult patients. Ann Surg. 2007;245:629-634.
25. Allaudeen N, Vidyarthi A, Maselli J, et al. Redefining readmission risk factors for general medicine patients. J Hosp Med. 2011;6:54-60.
26. Hernandez AF, Greiner MA, Fonarow GC, et al. Relationship between early physician follow-up and 30-day readmission among Medicare beneficiaries hospitalized for heart failure. JAMA. 2010;303:1716-1722.
27. Ahmed OI, Rak DJ. Hospital readmission among participants in a transitional case management program. Am J Manag Care. 2010;16: 778-783.
28. MedPAC. Medicare Payment Policy. Report to the Congress: Medicare Payment Advisory Commission; 2011.
29. Friedman B, Basu J. The rate and cost of hospital readmissions for preventable conditions. Med Care Res Rev. 2004;61:225-240.
30. Amarasingham R, Moore BJ, Tabak YP, et al. An automated model to identify heart failure patients at risk for 30-day readmission or death using electronic medical record data. Med Care. 2010;48:981-988.
31. Choo B, Umraw N, Gomez M, et al. The utility of the functional independence measure (FIM) in discharge planning for burn patients. Burns. 2006;32:20-23.