Improving documentation of clinical care within a clinical information network: an essential initial step in efforts to understand and improve care in Kenyan hospitals

• Published in: BMJ global health Vol. 1; no. 1; p. e000028
• Main Authors: Tuti, Timothy, Bitok, Michael, Malla, Lucas, Paton, Chris, Muinga, Naomi, Gathara, David, Gachau, Susan, Mbevi, George, Nyachiro, Wycliffe, Ogero, Morris, Julius, Thomas, Irimu, Grace, English, Mike
• Format: Journal Article
• Language: English
• Published: England BMJ Publishing Group LTD 2016; BMJ Publishing Group
• Subjects: Analysis; Collaboration; Data collection; Disease; Documentation; Global health; Hospitals; Information systems; Knowledge discovery; Low income areas; Low income groups; Medical records; Patients; Pediatrics; Kenya
• ISSN: 2059-7908; 2059-7908
• DOI: 10.1136/bmjgh-2016-000028

In many low income countries health information systems are poorly equipped to provide detailed information on hospital care and outcomes. Information is thus rarely used to support practice improvement. We describe efforts to tackle this challenge and to foster learning concerning collection and use of information. This could improve hospital services in Kenya. We are developing a Clinical Information Network, a collaboration spanning 14 hospitals, policy makers and researchers with the goal of improving information available on the quality of inpatient paediatric care across common childhood illnesses in Kenya. Standardised data from hospitals' paediatric wards are collected using non-commercial and open source tools. We have implemented procedures for promoting data quality which are performed prior to a process of semi-automated analysis and routine report generation for hospitals in the network. In the first phase of the Clinical Information Network, we collected data on over 65 000 admission episodes. Despite clinicians' initial unfamiliarity with routine performance reporting, we found that, as an initial focus, both engaging with each hospital and providing them information helped improve the quality of data and therefore reports. The process has involved mutual learning and building of trust in the data and should provide the basis for collaborative efforts to improve care, to understand patient outcome, and to evaluate interventions through shared learning. We have found that hospitals are willing to support the development of a clinically focused but geographically dispersed Clinical Information Network in a low-income setting. Such networks show considerable promise as platforms for collaborative efforts to improve care, to provide better information for decision making, and to enable locally relevant research.