Abstract:
Introduction: anticoagulants are essential for
preventing and treating thromboembolism;
however, uptake of anticoagulation services
remains low in resource-limited settings, such as
Kenya. Despite the recognized benefits, many
patients struggle with adherence, and contributing
factors remain poorly understood. This study
explored patient and institution-related barriers to
the uptake of anticoagulation services at Moi
Teaching and Referral Hospital (MTRH), Kenya. In
particular, the study focused on knowledge,
adherence, satisfaction, attitudes, service quality,
and access. Methods: a cross-sectional study was
conducted among 282 adult patients (≥18 years)
on anticoagulation therapy for at least three
months. Participants were selected through
consecutive sampling. Data was collected via a
pre-tested, researcher-administered semistructured questionnaire. Quantitative data were
analyzed descriptively, and qualitative responses
were thematically analyzed. Results: while nearly
70% of participants could identify their
anticoagulant, only 42.6% of the respondents
understood how diet, drug interactions, or missed
doses affected treatment. Only 33.5% of the
participants maintained therapeutic International
Normalized Ratio (INR) levels. Non-adherence was
reported in 40% of patients, with frequent missed
doses and irregular clinic visits. Confusion about
follow-up and INR monitoring was common, with
31.7% of patients reporting uncertainty about their
medication regimen and 9.3% not knowing it at all;
clinicians and pharmacists cited inadequate time
(65.4%), lack of structured education programs
(58.2%), and limited patient engagement tools
(42.1%) as key barriers. Conclusion: despite high
patient satisfaction and trust in providers,
significant gaps in knowledge, adherence, and
system support hinder optimal anticoagulation
care. Gender and age-related disparities further
complicate service uptake. Strengthening patient
education, improving INR monitoring awareness,
and integrating structured counseling into care
models are crucial to improving anticoagulation
outcomes in resource-limited settings like MTRH.
