Modelling factors associated with therapeutic inertia in hypertensive patients: Analysis using repeated data from a hospital registry in West Africa

Author:

Barro Mahamadou1ORCID,Yaméogo Aristide Relwendé234,Mba Robert Darlin5,Kaboré Rémi6,Mandi Germain3,Dahourou Désiré Lucien1,Zabsonré Patrice3,Méda Nicolas4,Goungounga Juste789

Affiliation:

1. Institut de Recherche en Sciences de la Santé, Département de Biomédical/Santé Publique, Ouagadougou, Burkina Faso

2. IDEES Le Havre, UMR CNRS 6266, Université du Havre, Normandie Université, Le Havre, France

3. Service de cardiologie, Centre Hospitalier Universitaire Yalgado Ouédraogo, Ouagadougou, Burkina Faso

4. UFR-SDS, Département de la Santé Publique; Université Joseph KI-ZERBO, Ouagadougou, Burkina Faso

5. Aix Marseille Univ, INSERM, IRD, SESSTIM Sciences Économiques & Sociales de la Santé & Traitement de l’Information Médicale, Marseille, France

6. , Bordeaux School of public health/Université de Bordeaux, Bordeaux, France

7. Digestive Cancer Registry of Burgundy, Dijon University Hospital, Dijon, France; Unit 1231 Epidemiology and Clinical Research in Digestive Cancers, National Institute of Health and Medical Research, University of Burgundy-Franche Comte, Dijon, France

8. Univ Rennes, EHESP, CNRS, Inserm, Arènes-UMR 6051, RSMS-U 1309, F-35000, Rennes, France

9. Écoles Des Hautes Études en Santé Publique, Département METIS, 15 Avenue du Professeur Léon Bernard, CS 74312, 35043, Rennes Cedex, France.

Abstract

The proportion of poorly controlled hypertensives still remains high in the general African population. This is largely due to therapeutic inertia (TI), defined as the failure to intensify or modify treatment in a patient with poorly controlled blood pressure (BP). The objective of this study was to identify the determinants of TI. We conducted a retrospective cohort study from March 2012 to February 2014 of hypertensive patients followed during 4 medical visits. The TI score was the number of visits with TI divided by the number of visits where a therapeutic change was indicated. A random-effects logistic model was used to identify the determinants of TI. A total of 200 subjects were included, with a mean age of 57.98 years and 67% men. The TI score was measured at 85.57% (confidence interval [CI] 95% = [82.41–88.92]). Measured individual heterogeneity was significantly significant (0.78). Three factors were associated with treatment inertia, namely the number of antihypertensive drugs (odd ratios [OR] = 1.27; CI = [1.02–1.58]), the time between consultations (OR = 0.94; CI = [0.91–0.97]), and treatment noncompliance (OR = 15.18; CI = [3.13–73.70]). The random-effects model performed better in predicting high-risk patients with TI than the classical logistic model (P value < .001). Our study showed a high TI score in patients followed in cardiology in Burkina Faso. Reduction of the TI score through targeted interventions is necessary to better control hypertension in our cohort patients.

Publisher

Ovid Technologies (Wolters Kluwer Health)

Subject

General Medicine

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