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. 2012 Nov 21;3(4):419-36.
doi: 10.4338/ACI-2012-05-RA-0016. Print 2012.

Exploring the value of clinical data standards to predict hospitalization of home care patients

K A Monsen, H L Swanberg, S C Oancea, B L Westra

Exploring the value of clinical data standards to predict hospitalization of home care patients

K A Monsen et al. Appl Clin Inform. .

Abstract

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.

Keywords: Home care; OASIS; Omaha system; electronic health record; hospitalization; risk assessment.

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Figures

Fig. 1
Fig. 1
Comparison of Receiver Operating Characteristic (ROC) Curves for Hospitalization Risk Score (HRS) and Charlson Index of Comorbidity (CIC)
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References

    1. National Association for Home Care and Hospice Basic statistics about home care. 2010. Internet http://www.nahc.org/facts/10hc_stats.pdf
    1. Medicare Payment Advisory Committee Medicare and the health care delivery system. Washington D.C.: June, 2011.
    1. Murkofsky RL, Alston K. The past, present, and future of skilled home health agency care. Clin Geriatr Med 2009; 25(1): 1,17, v - PubMed
    1. 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(7): 398–405 - PubMed
    1. 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(2): 118–127 - PubMed