Examining the association between comorbidity indexes and functional status in hospitalized medicare fee-for-service beneficiaries

Physical Therapy

Volumn 96, Issue 2, 2016, Pages 232-240

  Kumar, Amit ^a   Graham, James E ^a   Resnik, Linda ^b,c   Karmarkar, Amol M ^a   Deutsch, Anne ^d,e   Tan, Alai ^a   Snih, Soham Al ^a   Ottenbacher, Kenneth J ^a  

^a UNIVERSITY OF TEXAS MEDICAL BRANCH   (United States)

^b BROWN UNIVERSITY   (United States)

^c PROVIDENCE VETERANS AFFAIRS MEDICAL CENTER   (United States)

^d RTI INTERNATIONAL   (United States)

^e REHABILITATION INSTITUTE OF CHICAGO   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

AGED; COMORBIDITY; DISABILITY; ECONOMICS; FEMALE; FRACTURES, BONE; HEALTH SERVICES RESEARCH; HOSPITAL PATIENT; HUMAN; LEG INJURIES; MALE; MEDICAL FEE; MEDICARE; REHABILITATION CENTER; REPLACEMENT ARTHROPLASTY; RETROSPECTIVE STUDY; STATISTICS AND NUMERICAL DATA; STROKE REHABILITATION; UNITED STATES; VERY ELDERLY;

AGED; AGED, 80 AND OVER; ARTHROPLASTY, REPLACEMENT; COMORBIDITY; DISABILITY EVALUATION; FEE-FOR-SERVICE PLANS; FEMALE; FRACTURES, BONE; HEALTH SERVICES RESEARCH; HUMANS; INPATIENTS; LEG INJURIES; MALE; MEDICARE; REHABILITATION CENTERS; RETROSPECTIVE STUDIES; STROKE REHABILITATION; UNITED STATES;

EID: 84956948363     PISSN: 00319023     EISSN: 15386724     Source Type: Journal    
DOI: 10.2522/ptj.20150039     Document Type: Article

References (36)

1. Graf C. Functional decline in hospitalized older adults. Am J Nurs. 2006;106:58-67.
2. Hoenig HM, Rubenstein LZ. Hospitalassociated deconditioning and dysfunction. J Am Geriatr Soc. 1991;39:220-222.
3. Brown CJ, Friedkin RJ, Inouye SK. Prevalence and outcomes of low mobility in hospitalized older patients. J Am Geriatr Soc. 2004;52:1263-1270.
4. Fields SD, MacKenzie CR, Charlson ME, Sax FL. Cognitive impairment: can it predict the course of hospitalized patients? J Am Geriatr Soc. 1986;34:579-585.
5. Inouye SK, Peduzzi PN, Robison JT, et al. Importance of functional measures in predicting mortality among older hospitalized patients. JAMA. 1998;279:1187-1193.
6. Narain P, Rubenstein LZ, Wieland GD, et al. Predictors of immediate and 6-month outcomes in hospitalized elderly patients: the importance of functional status. J Am Geriatr Soc. 1988;36:775-783.
7. Sabartes O, Miralles R, Ferrer M, et al. Factors predicting return home of hospitalized aged patients. An Med Interna. 1999; 16:407-414.
8. Kansagara D, Englander H, Salanitro A, et al. Risk prediction models for hospital readmission: a systematic review. JAMA. 2011;306:1688-1698.
9. Ottenbacher KJ, Graham JE, Ottenbacher AJ, et al. Hospital readmission in persons with stroke following postacute inpatient rehabilitation. J Gerontol A Biol Sci Med Sci. 2012;67:875-881.
10. Kim DH, Schneeweiss S. Measuring frailty using claims data for pharmacoepidemiologic studies of mortality in older adults: evidence and recommendations. Pharmacoepidemiol Drug Saf. 2014;23:89- 1901.
11. Centers for Medicare & Medicaid Services. Readmissions Reduction Program 2012 Available a t : http://www. cms.gov/Medicare/Medicare-Fee-for- Service-Payment/AcuteInpatientPPS/ Readmissions-Reduction-Program.html. Accessed April 2015.
12. Centers for Medicare & Medicaid Services. Bundled Payments for Care Improvement (BPCI) Initiative 2013. Available at: http:// innovation.cms.gov/initiatives/bundledpayments/. Accessed December 2014.
13. Faurot KR, Jonsson Funk M, Pate V, et al. Using claims data to predict dependency in activities of daily living as a proxy for frailty. Pharmacoepidemiol Drug Saf. 2015;24:59-66.
14. Schneeweiss S, Setoguchi S, Brookhart MA, et al. Assessing residual confounding of the association between antipsychotic medications and risk of death using survey data. CNS Drugs. 2009;23:171-180.
15. Schneeweiss S, Wang PS. Association between SSRI use and hip fractures and the effect of residual confounding bias in claims database studies. J Clin Psychopharmacol. 2004;24:632-638.
16. Groll DL, To T, Bombardier C, Wright JG. The development of a comorbidity index with physical function as the outcome. J Clin Epidemiol. 2005;58:595-602.
17. Charlson ME, Pompei P, Ales KL, MacKenzie CR. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis. 1987;40:373-383.
18. Elixhauser A, Steiner C, Harris DR, Coffey RM. Comorbidity measures for use with administrative data. Med Care. 1998;36: 8-27.
19. Bravo G, Dubois MF, Hebert R, et al. A prospective evaluation of the Charlson Comorbidity Index for use in long-term care patients. J Am Geriatr Soc. 2002;50: 740-745.
20. Centers for Medicare & Medicaid Services. Medicare Program; Inpatient Rehabilitation Facility Prospective Payment System for federal fiscal year 2011: final rule. Fed Regist. 2011;75:42835-42884.
21. Pope GC, Kautter J, Ellis RP, et al. Risk adjustment of Medicare capitation payments using the CMS-HCC model. Health Care Financ Rev. 2004;25:119-141.
22. Ware JE Jr, Sherbourne CD. The MOS 36-item short-form health survey (SF-36), I: conceptual framework and item selection. Med Care. 1992;30:473-283.
23. Groll DL, Heyland DK, Caeser M, Wright JG. Assessment of long-term physical function in acute respiratory distress syndrome (ARDS) patients: comparison of the Charlson Comorbidity Index and the Functional Comorbidity Index. Am J Phys Med Rehabil. 2006;85:574-581.
24. Haines K, Berney S, Warrillow S, Denehy L. Predicting physical function and health related quality of life following intensive care. Int J Phys Med Rehabil. 2014;2:1- 6.
25. Fan E, Gifford JM, Chandolu S, et al. The Functional Comorbidity Index had high inter-rater reliability in patients with acute lung injury. BMC Anesthesiol. 2012;12:21.
26. The Medicare Payment Advisory Commission (MedPAC). Report to the Congress: Medicare and the health care delivery system. Inpatient Rehabilitation Facility Services. July 2013. Available at: http://www. medpac.gov/documents/reports/mar13_ entirereport.pdf?sfvrsn_0. Accessed June 2015.
27. Inpatient Rehabilitation Facility Patient Assessment Instrument (IRF-PAI) Training Manual. Buffalo, NY: Uniform Data System for Medical Rehabilitation; 2001.
28. Ottenbacher KJ, Hsu Y, Granger CV, Fiedler RC. The reliability of the Functional Independence Measure: a quantitative review. Arch Phys Med Rehabil. 1996; 77:1226-1232.
29. Deyo RA, Cherkin DC, Ciol MA. Adapting a clinical comorbidity index for use with ICD-9-CM administrative databases. J Clin Epidemiol. 1992;45:613-619.
30. Resnik L, Gozalo P, Hart DL. Weighted index explained more variance in physical function than an additively scored functional comorbidity scale. J Clin Epidemiol. 2011;64:320-330.
31. Centers for Medicare & Medicaid Services. Risk Adjustment: Evaluation of the CMSHCC Risk Adjustment Model 2015. Available at: https://www.cms.gov/Medicare/ Health-Plans/MedicareAdvtgSpecRate Stats/downloads/Evaluation_Risk_Adj_ Model_2011.pdf. Accessed August 2015.
32. Kleinbaum D, Kupper L, Nizam A, et al. Applied Regression Analysis and Other Multivariable Methods. 5th ed. Boston, MA: Cengage Learning; 2013.
33. Noyes K, Liu H, Temkin-Greener H. Medicare capitation model, functional status, and multiple comorbidities: model accuracy. Am J Manag Care. 2008;14:679-690.
34. Centre for Clinical Practice at NICE (UK). Rehabilitation After Critical Illness 2009. Available at: http://www.ncbi.nlm.nih. gov/books/NBK11658/. Accessed July 2015.
35. Institute of Medicine. Performance Measurement: Accelerating Improvement (Pathways to Quality Health Care Series). Washington, DC: The National Academics Press; 2006. Available at: https://www.iom.edu/Reports/ 2005/Performance-Measurement-Acceler ating-Improvement.aspx. Accessed October 2014.
36. US Congress. The Improving Medicare Post-Acute Care Transformation Act of 2014, HR 4994 (113th) 2014. Available at: https://www.govtrack.us/congress/ bills/113/hr4994. Accessed March 2015.