Nursing home-sensitive conditions: analysis of routine health insurance data and modified Delphi analysis of potentially avoidable hospitalizations

Abstract

Background: Hospitalizations of nursing home residents are associated with various health risks. Previous research indicates that, to some extent, hospitalizations of this vulnerable population may be inappropriate and even avoidable. This study aimed to develop a consensus list of hospital discharge diagnoses considered to be nursing home-sensitive, i.e., avoidable. Methods: The study combined analyses of routine data from six statutory health insurance companies in Germany and a two-stage Delphi panel, enhanced by expert workshop discussions, to identify and corroborate relevant diagnoses. Experts from four different disciplines estimated the proportion of hospitalizations that could potentially have been prevented under optimal conditions. Results: We analyzed frequencies and costs of data for hospital admissions from 242,236 nursing home residents provided by statutory health insurance companies. We identified 117 hospital discharge diagnoses, which had a frequency of at least 0.1%. We recruited experts (primary care physicians, hospital specialists, nursing home professionals and researchers) to estimate the proportion of potentially avoidable hospitalizations for the 117 diagnoses deemed avoidable in two Delphi rounds (n=107 in Delphi Round 1 and n=96 in Delphi Round 2, effective response rate=91%). A total of 35 diagnoses with high and consistent estimates of the proportion of potentially avoidable hospitalizations were identified as nursing home-sensitive. In an expert workshop (n=16), a further 25 diagnoses were discussed that had not reached the criteria, of which another 23 were consented to be nursing home-sensitive conditions. Extrapolating the frequency and mean costs of these 58 diagnoses to the national German context yielded total potentially avoidable care costs of €768,304,547, associated with 219,955 nursing home-sensitive hospital admissions. Conclusion: A total of 58 nursing home-relevant diagnoses (ICD-10-GM three-digit level) were classified as nursing home-sensitive using an adapted Delphi procedure. Interventions should be developed to avoid hospital admission from nursing homes for these diagnoses.

What’s next in hospital digitization? A Delphi-based scenario study

“…The Delphi technique, originally developed in the military domain during the late 1940s, has gained significant prominence in economic and social science research since the early 2000s [63]. Delphi methods are also increasingly being used to address issues in health care [64][65][66][67]. This method facilitates the structured communication and management of expert groups, guided by four fundamental features: (i) anonymity, (ii) iteration, (iii) controlled feedback, and (iv) statistical group response [68].…”

“…In the preparatory phase, we carefully delineated the scope of our study and formulated a well-defined research question. Consequently, we opted for the classical sequential Delphi format, which entailed conducting two consecutive rounds [64]. In the initial round, participants evaluated a set of future-oriented descriptive parameters, attributing expected probabilities (EP) and estimated expressions (E) to each parameter.…”