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Year : 2021  |  Volume : 12  |  Issue : 1  |  Page : 22

Designing an elderly hospital admission risk prediction model in Iran's hospitals

1 School of Health Management and Information Sciences, Iran University of Medical Sciences, Tehran, Iran
2 Health Management and Economics Research Center, Iran University of Medical Sciences, Tehran, Iran
3 Health Management and Economic Research Center, Health Services Administration, Isfahan University of Medical Sciences, Isfahan, Iran
4 Interprofessional Education and Practice, Center for Innovative Care in Aging Johns Hopkins School of Nursing, Baltimore, United States of America

Correspondence Address:
Farzaneh Doosty
Health Management and Economics Research Center, Iran University of Medical Sciences, Tehran
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/ijpvm.IJPVM_433_18

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Background: The identification of elderly at risk of new functional disabilities in activities of daily living at admission to the hospital may facilitate referral for purposive interventions to prevent decline and institutionalization. This study was aimed at designing a risk prediction model for identifying the elderly at risk of admission in Iran's hospitals. Materials and Methods: This is a cross-sectional descriptive study conducted in 2017. In order to formulate and validate a prediction model, the study was done in two development and validation cohort study. Functional decline was defined as a decline of at least one point on the Katz ADL index at follow-up compared with preadmission status. Results: In development cohort, the mean age was 71 years including 54% of men and 46% women, 22% of men and 17% of women experienced functional decline after 3 months. In the validation cohort, the mean age was 70 years, including 49% of men and 51% women, 19% of men and 15% of women, functional decline after 3 months was observed. Conclusion: On the basis of the findings, aging at risk of hospital admission can be identified by easy designed model with four questions: (1) Is the patient's age more than 85 years? (2) Does the patient's mini mental status <22? (3) Does the patient need help for using general transporting? (4) Has the patient lost weight <5% over the past 6 months and body mass index <18.5? And also geriatrics experts can use the designed model as a predictive tool in order to improve the quality level of healthcare services to elderly as a vulnerable and high risk group. The important point of model is easy to use even for nonspecialists.

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