[Factors Related to the Unplanned 90-Day Readmission Rate Among Elderly at a Geriatric Medicine Center].

BACKGROUND: Unplanned readmissions increase healthcare utilization rates and healthcare costs. The Taiwan Healthcare Indicator Series regards the rate of hospital readmission as an important indicator of inpatient-care quality. The elderly face a higher risk of unplanned readmission due to elderly-specific health and disease characteristics such as deteriorating body functions and the relatively high incidence of complications after the treatment of acute diseases. PURPOSE: To explore the factors that relate to the unplanned readmission of elderly within 90 days of discharge at a geriatric medical center. METHODS: We retrospectively reviewed the medical records of inpatients aged ≥65 years who had been admitted between January 2013 and December 2014. Related factors that affected the rate of unplanned readmission within 90 days of discharge were screened and analyzed using the chi-squared test and logistic regression analysis. RESULTS: The 90-day unplanned readmission rate was 20.3%. Factors that were found to relate to unplanned readmissions were: emergency room admission (88.7%), lack of regular outpatient follow-up (60.4%), cerebrovascular incidents (43.4%), osteoporosis (32.1%), gastrointestinal diseases (45.3%), and a hemoglobin level < 10.0 mg/dL (35.8%). CONCLUSIONS / IMPLICATIONS FOR PRACTICE: The results of the present study may help the healthcare team better understand the factors that affect unplanned readmission in the elderly. We suggest that these teams provide timely health education for elderly, integrative healthcare for chronic diseases, and appropriate nutritional supplements in order to reduce unplanned readmissions.

Developing a predictive model for hospital-associated disability among older patients hospitalized for an acute illness: the HAD-FREE Score.

PURPOSE: To develop a predictive model to identify hospitalized older patients at risk of functional decline. METHODS: This retrospective cohort study recruited participants aged 65 years and over admitted to internal medicine wards of a tertiary medical center in Taiwan during May to October 2017 for developing predictive model (n = 1698) and those admitted during November to December 2017 for validation study (n = 530) of the model. Demographic data, geriatric assessments and hospital conditions (admission route and length of hospital stay) were collected for analysis. RESULTS: Overall, of the 1698 participants (mean age 75.8 ± 7.9 years, 60.9% male) enrolled in the development study, 20.1% had functional decline. Results of multivariate logistic regression showed that older age, hearing impairment, history of falls within one year, risk of malnutrition, physical restraint, admission via emergency department and hospital stay ≥ 5 days were independent predictive factors for decline. A scoring system, HAD-FREE Score, constructed from the above predictive factors ranged from 0 to 18 points and ≥ 6 points was chosen as the cut-off point. The area under the receiver operating characteristic analysis was 0.748 (95% confidence interval: 0.720-0.776), the sensitivity was 65.3% and the specificity was 71.3%. Validation of the HAD-FREE Score showed moderate discriminative ability in the validation study. CONCLUSION: A HAD-FREE Score developed from seven independent factors could predict functional decline with moderate discriminative ability and good validation. This scoring system can be the basis of an automatic dynamic tracking within the electronic medical record to identify those older patients at risk of functional decline during hospitalization.