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
Sarah J Crane, Ericka E Tung, Gregory J Hanson, Stephen Cha, Rajeev Chaudhry, Paul Y Takahashi, Sarah J Crane, Ericka E Tung, Gregory J Hanson, Stephen Cha, Rajeev Chaudhry, Paul Y Takahashi
Abstract
Background: The prevention of recurrent hospitalizations in the frail elderly requires the implementation of high-intensity interventions such as case management. In order to be practically and financially sustainable, these programs require a method of identifying those patients most at risk for hospitalization, and therefore most likely to benefit from an intervention. The goal of this study is to demonstrate the use of an electronic medical record to create an administrative index which is able to risk-stratify this heterogeneous population.
Methods: We conducted a retrospective cohort study at a single tertiary care facility in Rochester, Minnesota. Patients included all 12,650 community-dwelling adults age 60 and older assigned to a primary care internal medicine provider on January 1, 2005. Patient risk factors over the previous two years, including demographic characteristics, comorbid diseases, and hospitalizations, were evaluated for significance in a logistic regression model. The primary outcome was the total number of emergency room visits and hospitalizations in the subsequent two years. Risk factors were assigned a score based on their regression coefficient estimate and a total risk score created. This score was evaluated for sensitivity and specificity.
Results: The final model had an AUC of 0.678 for the primary outcome. Patients in the highest 10% of the risk group had a relative risk of 9.5 for either hospitalization or emergency room visits, and a relative risk of 13.3 for hospitalization in the subsequent two year period.
Conclusions: It is possible to create a screening tool which identifies an elderly population at high risk for hospital and emergency room admission using clinical and administrative data readily available within an electronic medical record.
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References
- US Census Bureau.
- Coleman E, Parry C, Chalmers S, Min S. The Care Transitions Interventions: Results of a randomized controlled trial. Archives of Internal Medicine. 2006;166:1822–1828. doi: 10.1001/archinte.166.17.1822.
- Caplan G, Williams A, Daly B, Abraham K. A randomized controlled trial of comprehensive geriatric assessment and multidisciplinary intervention after discharge of the elderly from the emergency department - the DEED II study. Journal of the American Geriatrics Society. 2004;52:1417–1423. doi: 10.1111/j.1532-5415.2004.52401.x.
- CMMS. CMMS RFP for Care Management for High-Cost Beneficiaries (CMS-5015-N) 2004.
- Counsell S, Callahan C, Clark D, Tu W, Buttar A, Stump T, Ricketts G. Geriatric care management for low-income seniors: a randomized controlled trial. Journal of the American Medical Association. 2007;298:2623–2633. doi: 10.1001/jama.298.22.2623.
- Shelton P, Sagar M, Schraeder C. Identifying elderly persons at risk for hospitalization or emergency department visit. American Journal of Managed Care. 2000;40:925–933.
- Miller E, Weissert W. Predicting elderly people's risk for nursing home placement, hospitalization, functional impairment and mortality: a synthesis. Med Care Res Rev. 2000;57:259–297. doi: 10.1177/107755870005700301.
- McGeechan K, Macaskill P, Irwig L, Liew G, Wong T. Assessing New Biomarkers and Predictive Models for Use in Clinical Practice. Archives of Internal Medicine. 2008;168:2304–2310. doi: 10.1001/archinte.168.21.2304.
- Boult C, Dowd B, McCaffrey D, Boult L, Hernandez R, Krulewitch H. Screening elders at risk for hospital admission. Journal of the American Geriatrics Society. 1993;41:811–817.
- Pacala J, Boult C, Boult L. Predictive validity of a questionnaire that identifies older persons at risk for hospital admission. Journal of the American Geriatrics Society. 1995;42:374–377.
- Coleman E. et al.Predicting hospitalization and functional decline in health plan enrollees: are administrative data as accurate as self report? JAGS. 1998;46:419–425.
- Wagner J, Bachmann L, Boult C, Harari D, von Renteln-Kruse W. et al.Predicting the risk of hospital admission in older persons-validation of a brief self-administered questionairre in three European countries. J Am Geriatr Soc. 2006;54:1271–1276. doi: 10.1111/j.1532-5415.2006.00829.x.
- Pacala J, Boult C, Reed R, Aliberti E. Predictive validity of the Pra Instrument among older recipients of managed care. J Am Geriatr Soc. 1997;45:614–617.
- Mazzaglia G. et al.Screening of older community dwelling people at risk for death and hospitalization. J Am Geriatr Soc. 2007;55:1955–1960. doi: 10.1111/j.1532-5415.2007.01446.x.
- Hertzog A, WL R. Age and response rates to interview sample surveys. J Gerontol. 1988;43S:200–205.
- Root J, Stablesford S. Easy to read consumer communications: a missing link in Medicaid managed care. J Health Polit Policy Law. 1999;24:1–26.
- Vojta C, Vojta D, TenHave T, Amaya M, Lavizzo-Mourey R, Asch D. Risk screening in a Medicare/Medicaid population. J Gen Internal Med. 2001;16:525–530. doi: 10.1046/j.1525-1497.2001.016008525.x.
- Quan H, Parsons G, Ghali W. Validity of information on comorbidity derived from ICD-9-CCM administrative data. Med Care. 2002;40:675–685. doi: 10.1097/00005650-200208000-00007.
- Fried L, Guralnik N. Disability in older adults: evidence regarding significance, etiology, and risk. J Am Geriatr Soc. 1997;45:92–100.
- Fried L, Kronmal R, Newman A. et al.Risk factors for 5 year mortality in older adults: the Cardiovascular Health Study. JAMA. 1998;279:585–592. doi: 10.1001/jama.279.8.585.
- Bogardus S, Towle V, Williams C, Desai M, Inouye S. What does the medical record reveal about functional status. J Gen Internal Med. 2001;16:728–836. doi: 10.1111/j.1525-1497.2001.00625.x.
Source: PubMed