Implementation of a home-based program for early detection of clinical deterioration in cystic fibrosis.

Abstract

A statistical decision-making system, based on daily self measurements obtained at home, has been developed that will predict the clinical status of a patient with cystic fibrosis (CF). The data for the study were collected from patients randomly selected from those served by the University of Minnesota CF Center. Participants recorded four daily measurements (weight, vital capacity, breathing rate, and resting pulse) and one weekly measurement (height) and returned completed diaries to the coordinating center each week. The goal of the rule was to determine whether each patient's clinical status was deteriorating, remaining stable, or improving at the time of the most recent set of weekly measurements. This early detection and intervention criterion (EDIC) is being used in the clinical setting to aid in the management of patients with cystic fibrosis. The computer hardware and software, particularly the relational database, have provided an efficient basis for the continued use of EDIC.