Development of a Clinical Prediction Rule for Adverse Events in Multimorbid Patients in Emergency and Hospitalisation

Int J Environ Res Public Health. 2022 Jul 14;19(14):8581. doi: 10.3390/ijerph19148581.

Abstract

(1) Background: There is currently a global consensus that the quality of comprehensive care for acutely hospitalised elderly people should include addressing functionality and mobility, cognitive status, prevention of pressure ulcers, urinary incontinence, falls and delirium, as well as pain control and medication-related problems. The aim of this study is to develop and validate a clinical prediction rule for multimorbid patients admitted to an acute care hospital unit for any of the five adverse events included in our vulnerability pentad: falls, pressure ulcers, urinary incontinence, pain and delirium. (2) Methods: Longitudinal analytical clinimetric study, with two cohorts. The study population will consist of multimorbid patients hospitalised for acute care, referred from the Emergency Room. A clinical prediction rule will be proposed, incorporating predictive factors of these five adverse outcomes described. This study has received funding, awarded in November 2020 (PI-0107-2020), and was approved in October 2019 by the Research Ethics Committee ″Costa del Sol″. (3) Conclusions: Preventing adverse events in hospitalised patients is particularly important for those with multimorbidity. By applying a clinical prediction rule to detect specific risks, an estimate can be obtained of their probability of occurrence.

Keywords: adverse events; clinical prediction rule; clinical safety; multimorbidity; nursing; validation study.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Aged
  • Clinical Decision Rules
  • Delirium* / diagnosis
  • Hospitalization
  • Humans
  • Multimorbidity
  • Pain
  • Pressure Ulcer* / epidemiology
  • Urinary Incontinence*

Grants and funding

This research was funded by Public Healthcare System (Andalusian Regional Ministry of Health and Families). Grant number: PI-0107-2020.