An automated method for analyzing adherence to therapeutic guidelines: application in diabetes.
BACKGROUND
Physicians' adherence to guidelines can be used for measuring prescribing appropriateness. We present a simple approach allowing the automation of this process.


METHODS
The drug therapy is described in terms of treatment type, pharmacotherapeutic classes, international non proprietary names (INN) and doses. A rule-based engine implementing the guideline generates recommendations for each patient record. These are automatically compared with prescriptions of the same patient in three levels of detail.


METHODS
Ambulatory patients admitted for the follow-up of their type 2 diabetes between June 2003 and September 2004 in a university hospital in France.


RESULTS
For 574 patient records included in the study, physicians agreed with the guideline recommendations over the choice of type of treatment in 473 cases (82%). When agreement over pharmacotherapeutic class of drugs was also taken into account, the adherence ratio decreased to 448 cases (78%). Finally, when the dosage of each drug was taken into account, the adherence ratio dropped to 396 cases (69%). Adherence ratios were also dependent on the type of treatment at admission: low for patients on oral tritherapy, and on diet and exercise. The results also highlighted inertia of physicians for beginning drug therapy and the underuse of biguanides.


CONCLUSIONS
The proposed method provides an automatable way of measuring the appropriateness of treatment choice, which can be used for chronic diseases.
Toussi
Massoud
M
Lim&Bio Laboratoire d'Informatique Médicale et de Bioinformatique, University of Paris Nord. massoudtoussi@gmail.com
Ebrahiminia
Vahid
V
Le Toumelin
Philippe
P
Cohen
Régis
R
Venot
Alain
A
D003131:Combined Modality Therapy; D020000:Decision Support Systems, Clinical; D003924:Diabetes Mellitus, Type 2 / Q000188:drug therapy*; D004305:Dose-Response Relationship, Drug; D004359:Drug Therapy, Combination; D005602:France; D019983:Guideline Adherence / Q000706:statistics & numerical data*; D006801:Humans; D007004:Hypoglycemic Agents / Q000008:administration & dosage*; D016347:Medical Records Systems, Computerized / Q000706:statistics & numerical data*
D007004:Hypoglycemic Agents