Determinants of patient enablement at primary health care centres in central Ethiopia: a cross-sectional study

• Main Authors: Zewdie Birhanu, Mirkuzie K. Woldie, Tsion Assefa, Sudhakar Morankar
• Format: Article
• Language: English
• Published: AOSIS 2011-04-01
• Series: African Journal of Primary Health Care & Family Medicine
• Subjects: Non-verbal communication; outpatient consultation; patient enablement; predictors; primary health care
• Online Access: https://phcfm.org/index.php/phcfm/article/view/195
• ISSN: 2071-2928; 2071-2936

Background: Patient enablement is associated with behaviours like treatment adherence and self-care and is becoming a well-accepted indicator of quality of care. However, the concept of patient enablement has never been subjected to scientific inquiry in Ethiopia. Objectives: The aim of this study was to determine the degree of patient enablement and its predictors after consultation at primary health care centres in central Ethiopia. Method: Data were collected from 768 outpatients from six primary health care centres in central Ethiopia during a cross-sectional study designed to assess patient satisfaction.Consecutive patients, 15 years or older, were selected for the study from each health centre.Multinomial logistic regression was performed to identify predictors of patient enablement using SPSS (version 16.0). Results: The study showed that 48.4% of patients expressed an intermediate level of enablement, while 25.4% and 26.2% of the patients expressed low and high levels of patient enablement, respectively. Four models were developed to identify predictors of patient enablement. The first model included socio-demographic variables, showing that residence, educational status and occupational status were significantly associated with patient enablement (p < 0.05). This model explained only 20.5% of the variation. The second and third models included institutional aspects, and perceived doctor–patient interaction and information sharing about illness, respectively. They explained 31.1% and 64.9% of the variation. The fourth model included variables that were significantly associated with patient enablement in the first, second and third models and explained 72% of the variation. In this model, perceived empathy and technical competency, non-verbal communication, familiarity with the provider, information sharing about illness and arrangement for follow-up visits were strong predictors of patient enablement (p < 0.05). Conclusion: The present study revealed specific predictors of patient enablement, which health care providers should consider in their practice to enhance patient enablement after consultation.