Exploring the Value of Clinical Data Standards to Predict Hospitalization of Home Care Patients

Summary

Background: There is a critical need to reduce hospitalizations for Medicare patients and electronic health record (EHR) home care data provide new opportunities to evaluate risk of hospitalization for patients.

Objectives: The objectives of this study were to 1) develop a measure to predict risk of hospitalization among home care patients, the Hospitalization Risk Score (HRS), and 2) compare it with an existing severity of illness measure, the Charlson Index of Comorbidity (CIC).

Methods: A convenience sample of clinical data from 14 home care agencies’ EHRs, representing 1,643 home care patient episodes was used for the study. The development of the HRS was based on review of the literature, and expert panel evaluation to construct the HRS. Descriptive statistics and generalized linear models were used for comparative analysis; areas under curve (AUC) values were compared for receiver operating curves (ROC), and cut points predicting hospitalization were evaluated.

Results: The HRS for this sample ranged from 0 to 5.6, with a median of 1.25. The CIC for this sample ranged from 0 to 9 and with a median of 0. Nearly three fourths of the sample was hospitalized at an HRS of 2, and a CIC of 1. AUC values for ROC were 0.63 for HRS and 0.59 for the CIC. The ROC curves were significantly different (t = -7.59, p <0.003).

Conclusions: This preliminary study demonstrates the potential value of the HRS using Omaha System EHR data. There was a statistically significant difference for predicting hospitalization of home care patients with the HRS versus the CIC; however the AUC values for both were low. Continued research is needed to further refine the HRS, determine whether it is more sensitive for particular subgroups of patients, and combine it with additional risk factors in understanding rehospitalization.

Citation: Monsen KA, Swanberg HL, Oancea SC, Westra BL. Exploring the value of clinical data standards to predict hospitalization of home care patients. Appl Clin Inf 2012; 3: 419–436

http://dx.doi.org/10.4338/ACI-2012-05-RA-0016

Keywords

Home care - hospitalization - electronic health record - Omaha system - OASIS - risk assessment

• References

• 1 National Association for Home Care and Hospice.. Basic statistics about home care. 2010. Internet. http://www.nahc.org/facts/10hc_stats.pdf
• 2 Medicare Payment Advisory Committee.. Medicare and the health care delivery system. Washington, D. C.: June, 2011.
• 3 Murkofsky RL, Alston K. The past, present, and future of skilled home health agency care. Clin Geriatr Med 2009; 25 (Suppl. 01) 1 17, v.
• 4 Esslinger E, Kevech M, Anderson D, Knowles B. Home health quality improvement national campaign: The journey and potential impact on clinical practice. Home Healthc Nurse 2008; 26 (Suppl. 07) 398-405.
• 5 Bowles KH, Cater JR. Screening for risk of rehospitalization from home care: Use of the outcomes assessment information set and the probability of readmission instrument. Res Nurs Health 2003; 26 (Suppl. 02) 118-127.
• 6 Swanberg H. Concepts related to hospitalization of home care patients: A literature review. 2011 Unpublished master’s thesis, University of Minnesota.
• 7 Lyon D, Lancaster GA, Taylor S, Dowrick C, Chellaswamy H. Predicting the likelihood of emergency admission to hospital of older people: Development and validation of the emergency admission risk likelihood index (EARLI). Fam Pract 2007; 24 (Suppl. 02) 158-167.
• 8 Enguidanos S, Hoang T, Hillary KA, Haynes RL. Predictors of hospitalization among home health managed care patients. Home Health Care Management & Practice 2010; December 01.
• 9 Fortinsky RH, Madigan EA, Sheehan TJ, Tullai-McGuinness S, Fenster JR. Risk factors for hospitalization among Medicare home care patients. West J Nurs Res 2006; 28 (Suppl. 08) 902-917.
• 10 Crossen-Sills J, Toomey I, Doherty M. Strategies to reduce unplanned hospitalizations of home healthcare patients: A step by step approach. Home Healthc Nurse 2006; 24 (Suppl. 06) 368-376.
• 11 Rosati RJ, Huang L. Development and testing of an analytic model to identify home healthcare patients at risk for a hospitalization within the first 60 days of care. Home Health Care Serv Q 2007; 26 (Suppl. 04) 21-36.
• 12 Crane SJ, Tung EE, Hanson GJ, Cha S, Chaudhry R, Takahashi PY. Use of an electronic administrative database to identify older community dwelling adults at high-risk for hospitalization or emergency department visits: The elders risk assessment index. BMC Health Serv Res 2010; 10: 338.
• 13 Mazzaglia G, Roti L, Corsini G, Colombini A, Maciocco G, Marchionni N. et al. Screening of older community-dwelling people at risk for death and hospitalization: The assistenza socio-sanitaria in Italia project. J Am Geriatr Soc 2007; 55 (12) 1955-1960.
• 14 Chan M, Nicklason F, Vial JH. Adverse drug events as a cause of hospital admission in the elderly. Intern Med J 2001; 31 (Suppl. 04) 199-205.
• 15 Flaherty JH, Perry HM, 3rd Lynchard GS, Morley JE. Polypharmacy and hospitalization among older home care patients. J Gerontol A Biol Sci Med Sci 2000; 55 (10) M554-M559.
• 16 Kuzuya M, Hirakawa Y, Suzuki Y, Iwata M, Enoki H, Hasegawa J. et al. Association between unmet needs for medication support and all-cause hospitalization in community-dwelling disabled elderly people. J Am Geriatr Soc 2008; 56 (Suppl. 05) 881-886.
• 17 Shelton P, Sager MA, Schraeder C. The community assessment risk screen (CARS): Identifying elderly persons at risk for hospitalization or emergency department visit. Am J Manag Care 2000; 6 (Suppl. 08) 925-933.
• 18 Mudge AM, Kasper K, Clair A, Redfern H, Bell JJ, Barras MA. et al. Recurrent readmissions in medical patients: A prospective study. Journal of Hospital Medicine 2011; 6 (Suppl. 02) 61-67.
• 19 Sokol MC, McGuigan KA, Verbrugge RR, Epstein RS. Impact of medication adherence on hospitalization risk and healthcare cost. Med Care 2005; 43 (Suppl. 06) 521-530.
• 20 Desai MM, Bogardus Jr ST, Williams CS, Vitagliano G, Inouye SK. Development and validation of a risk-adjustment index for older patients: The high-risk diagnoses for the elderly scale. J Am Geriatr Soc 2002; 50 (Suppl. 03) 474-481.
• 21 Marcantonio ER, McKean S, Goldfinger M, Kleefield S, Yurkofsky M, Brennan TA. Factors associated with unplanned hospital readmission among patients 65 years of age and older in a Medicare managed care plan. Am J Med 1999; 107 (Suppl. 01) 13-17.
• 22 Huang BY, Cornoni-Huntley J, Hays JC, Huntley RR, Galanos AN, Blazer DG. Impact of depressive symptoms on hospitalization risk in community-dwelling older persons. J Am Geriatr Soc 2000; 48 (10) 1279-1284.
• 23 Sayers SL, Hanrahan N, Kutney A, Clarke SP, Reis BF, Riegel B. Psychiatric comorbidity and greater hospitalization risk, longer length of stay, and higher hospitalization costs in older adults with heart failure. J Am Geriatr Soc 2007; 55 (10) 1585-1591.
• 24 Braunstein JB, Anderson GF, Gerstenblith G, Weller W, Niefeld M, Herbert R. et al. Noncardiac comorbidity increases preventable hospitalizations and mortality among Medicare beneficiaries with chronic heart failure. J Am Coll Cardiol 2003; 42 (Suppl. 07) 1226-1233.
• 25 Jencks SF, Williams MV, Coleman EA. Rehospitalizations among patients in the Medicare fee-for-service program. N Engl J Med 2009; 360 (14) 1418-1428.
• 26 Anderson MA, Hanson KS, DeVilder NW, Helms LB. Hospital readmissions during home care: A pilot study. J Community Health Nurs 1996; 13 (Suppl. 01) 1-12.
• 27 Culler SD, Parchman ML, Przybylski M. Factors related to potentially preventable hospitalizations among the elderly. Med Care 1998; 36 (Suppl. 06) 804-817.
• 28 Landi F, Onder G, Russo A, Tabaccanti S, Rollo R, Federici S. et al. A new model of integrated home care for the elderly: Impact on hospital use. J Clin Epidemiol 2001; 54 (Suppl. 09) 968-970.
• 29 Kennedy BS, Kasl SV, Vaccarino V. Repeated hospitalizations and self-rated health among the elderly: A multivariate failure time analysis. Am J Epidemiol 2001; 153 (Suppl. 03) 232-241.
• 30 Allaudeen N, Vidyarthi A, Maselli J, Auerbach A. Redefining readmission risk factors for general medicine patients. J Hosp Med 2011; 6 (Suppl. 02) 54-60.
• 31 van Walraven C, Dhalla IA, Bell C, Etchells E, Stiell IG, Zarnke K. et al. Derivation and validation of an index to predict early death or unplanned readmission after discharge from hospital to the community. CMAJ 2010; 182 (Suppl. 06) 551-557.
• 32 Sheeran T, Byers AL, Bruce ML. Depression and increased short-term hospitalization risk among geriatric patients receiving home health care services. Psychiatr Serv 2010; 61 (Suppl. 01) 78-80.
• 33 Inouye SK, Zhang Y, Jones RN, Shi P, Cupples LA, Calderon HN. et al. Risk factors for hospitalization among community-dwelling primary care older patients: Development and validation of a predictive model. Med Care 2008; 46 (Suppl. 07) 726-731.
• 34 Miller EA, Weissert WG. Predicting elderly people’s risk for nursing home placement, hospitalization, functional impairment, and mortality: A synthesis. Med Care Res Rev 2000; 57 (Suppl. 03) 259-297.
• 35 Caffrey C, Sengupta M, Moss A, Harris-Kojetin L, Valverde R. Home health care and discharged hospice care patients: United states, 2000 –2007. National Health Statistics Report. 2011 Aprin 27, 2011; 38: 1-28.
• 36 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 (Suppl. 05) 373-383.
• 37 Hasan O, Meltzer DO, Shaykevich SA, Bell CM, Kaboli PM. et al. Hospital readmission in general patients: A prediction model. J Gen Intern Med 2009; 25 (Suppl. 03) 211-219.
• 38 Southern DA, Quan H, Ghali WA. Comparison of the Elixhauser and Charlson/Deyo methods of comorbidity measurement in administrative data. Med Care 2004; 42 (Suppl. 04) 355-360.
• 39 Deyo RA, Cherkin DC, Ciol MA. Adapting a clinical comorbidity index for use with ICD-9-CM administrative databases. J Clin Epidemiol 1992; 45 (Suppl. 06) 613-619.
• 40 Needham DM, Scales DC, Laupacis A, Pronovost PJ. A systematic review of the Charlson comorbidity index using Canadian administrative databases: A perspective on risk adjustment in critical care research. J Crit Care 2005; 20 (Suppl. 01) 12-19.
• 41 Stukenborg GJ, Wagner DP, Connors Jr AF. Comparison of the performance of two comorbidity measures, with and without information from prior hospitalizations. Med Care 2001; 39 (Suppl. 07) 727-739.
• 42 University of Manitoba Community Health Sciences, Manitoba Centre for Health Policy.. Concept: Charlson Index, SAS Code. Internet. http://mchp-appserv.cpe.umanitoba.ca/viewConcept.php?conceptID=1098
• 43 Westra BL, Savik K, Oancea C, Choromanski L, Holmes JH, Bliss D. Predicting improvement in urinary and bowel incontinence for home health patients using electronic health record data. J Wound Ostomy Continence Nurs 2011; 38 (Suppl. 01) 77-87.
• 44 Dierich MT, Mueller C, Westra BL. Medication regimens in older home care patients. J Gerontol Nurs 2011; 37 (12) 45-55.
• 45 Centers for Medicare and Medicaid Services, Home Health Quality Initiative.. OASIS Data Set. 2012. Internet. https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/HomeHealthQualityInits/HHQIOASISDataSet.html
• 46 Martin KS. The Omaha System: A key to practice, documentation, and information management. (Reprinted 2nd ed.). Omaha, NE: Health Connections Press; 2005
• 47 The Omaha System: Solving the Clinical Data-Information Puzzle. 2012. Internet. http://www.omahasys tem.org
• 48 Monsen KA, Foster DJ, Gomez T, Poulsen JK, Mast J, Westra BL, Fishman E. Evidence-based standardized care plans for use internationally to improve home care practice and population health. Applied Clinical Informatics 2011; 2: 373-384. doi:10.4338/ACI-2011–03-RA-0023
• 49 Monsen KA, Westra BL, Paitich N, Ekstrom D, Mehle SC, Kaeding M, Abdo S, Natarajan G, Ruddarraju U. Developing a shared personal health record for elders and providers: Technology and content. J Gerontol Nurs 2012; 38 (Suppl. 07) 21-25.
• 50 Ash JS, McCormack JL, Sittig DF, Wright A, McMullen C, Bates DW. Standard practices for computerized clinical decision support in community hospitals: A national survey. J Am Med Inform Assn 2012 June 15.
• 51 Monsen KA, Radosevich DM, Kerr MJ, Fulkerson JA. Public health nurses tailor interventions for families at risk. Public Health Nurs 2011; 28 (Suppl. 02) 119-128.
• 52 Greiner M, Pfeiffer D, Smith RD. Principles and practical application of the receiver-operating characteristic analysis for diagnostic tests. Prev Vet Med 2000; 45 1–2 23-41.
• 53 Westra BL, Dey S, Fang G, Steinbach M, Kumar V, Savik K. et al. Interpretable predictive models for knowledge discovery from homecare electronic health records. Journal of Healthcare Engineering 2011; 2 (Suppl. 01) 55-74.
• 54 Monsen KA, Westra BL, Oancea SC, Yu F, Kerr MJ. Linking home care interventions and hospitalization outcomes for frail and non-frail elderly patients. Res Nurs Health 2011; 34 (Suppl. 02) 160-168.