Clinicians can use data to improve daily clinical practice.
This paper offers eight principles for using data to support improvement in busy clinical settings : 1) seek usefulness, not perfection, in the measurement ; 2) use a balanced set of process, outcome, and cost measures ; 3) keep measurement simple (think big, but start small) ; 4) use qualitative and quantitative data ; 5) write down the operational definitions of measures ; 6) measure small, representative samples ; 7) build measurement into daily work ; and 8) develop a measurement team.
The following approaches to using data for improvement are recommended.
First, begin with curiosity about outcomes or a need to improve results.
Second, try to avoid knee-jerk, obstructive criticism of proposed measurements.
Instead, propose solutions that are practical, goal-oriented, and good enough to start with.
Third, gather baseline data on a small sample and check the findings.
Fourth, try to change and improve the delivery process while gathering data.
Fifth, plot results over time and analyze them by using a control chart or other graphical method.
Sixth, refine your understanding of variation in processes and outcomes by dividing patients into clinically homogeneous subgroups (stratification) and analyzing the results separately for each subgroup.
Finally, make further changes while measuring key outcomes over time. (...)
Mots-clés Pascal : Médecine générale, Analyse donnée, Mesure, Méthodologie, Application médicale, Critère sélection, Homme, Education santé, Enseignement
Mots-clés Pascal anglais : Internal medicine, Data analysis, Measurement, Methodology, Medical application, Selection criterion, Human, Health education, Teaching
Notice produite par :
Inist-CNRS - Institut de l'Information Scientifique et Technique
Cote : 98-0177344
Code Inist : 002B30A09. Création : 11/09/1998.