Impact of point-of-care ultrasound use on patient referral decisions in rural Kenya: a mixed methods study.

Background: Point-of-care ultrasound (POCUS) is recognized as a key imaging modality to bridge the diagnostic imaging gap in Low- and Middle-Income Countries (LMICs). POCUS use has been shown to impact patient management decisions including referral for specialist care. This study explored the impact of POCUS use on referral decisions among trained healthcare providers working in primary rural and peri-urban health facilities in Kenya. Methods: A concurrent mixed methods approach was used, including a locally developed survey (N = 38) and semi-structured interviews of POCUS trained healthcare providers (N = 12). Data from the survey was descriptively analyzed and interviews were evaluated through the framework matrix method. Results: Survey results of in-facility access to Xray, Ultrasonography, CT scan and MRI were 49%, 33%, 3% and 0% respectively. Only 54% of the facilities where trainees worked had the capacity to perform cesarean sections, and 38% could perform general surgery. Through a combined inductive and deductive evaluation of interview data, we found that the emerging themes could be organized through the framework of the six domains of healthcare quality as described by the Institute of Medicine: Providers reported that POCUS use allowed them to make referral decisions which were timely, safe, effective, efficient, equitable and patient-centered. Challenges included machine breakdown, poor image quality, practice isolation, lack of institutional support and insufficient feedback on the condition of patients after referral. Conclusion: This study highlighted that in the setting of limited imaging and surgical capacity, POCUS use by trained providers in Kenyan primary health facilities has the potential to improve the patient referral process and to promote key dimensions of healthcare quality. Therefore, there is a need to expand POCUS training programs and to develop context specific POCUS referral algorithms. [ABSTRACT FROM AUTHOR]