The Complexity of Determining Whether a Nursing Home Transfer Is Avoidable at Time of Transfer

Abstract

Objectives To describe the relationship between nursing facility resident risk conditions and signs and symptoms at time of acute transfer and diagnosis of conditions associated with potentially avoidable acute transfers (pneumonia, urinary tract infection, congestive heart failure (CHF), chronic obstructive pulmonary disease (COPD) or asthma, dehydration, pressure sores). Design As part of a demonstration project to reduce potentially avoidable hospital transfers, Optimizing Patient Transfers, Impacting Medical Quality, Improving Symptoms: Transforming Institutional Care (OPTIMISTIC) project clinical staff collected data on residents who transferred to the emergency department (ED) or hospital. Cross‐tabulations were used to identify associations between risk conditions or symptoms and hospital diagnoses or death. Mixed‐effects logistic regression models were used to describe the significance of risk conditions, signs, or symptoms as predictors of potentially avoidable hospital diagnoses or death. Setting Indiana nursing facilities (N=19). Participants Long‐stay nursing facility residents (N=1,174), who experienced 1,931 acute transfers from November 2014 to July 2016. Measurements Participant symptoms, transfers, risk factors, and hospital diagnoses. Results We found that 44% of acute transfers were associated with 1 of 6 potentially avoidable diagnoses. Symptoms before transfer did not discriminate well among hospital diagnoses. Symptoms mapped into multiple diagnoses and most hospital diagnoses had multiple associated symptoms. For example, more than two‐thirds of acute transfers of residents with a history of CHF and COPD were for reasons other than exacerbations of those two conditions. Conclusion Although it is widely recognized that many transfers of nursing facility residents are potentially avoidable, determining “avoidability” at time of transfer is complex. Symptoms and risk conditions were only weakly predictive of hospital diagnoses.