Electronic Medical Record Systems, Data Quality and Loss to Follow-Up: Survey of Antiretroviral Therapy Programmes in Resource-Limited settings/Systemes D'enregistrement Electronique Des Donnees Medicales, Qualite Des Donnees et Nombre De Perdus De Vue : Enquete Sur Les Programmes De Traitement Antiretroviral Dans Les Pays a Ressources limitees/Sistemas De Historias Clinicas Electronicas, Calidad De Los Datos Y Perdidas De Seguimiento

Introduction Access to antiretroviral therapy (ART) has improved in lower-income countries over the past 4 years as a result of an exceptional commitment by the international community and donor agencies. WHO estimates that about 3 million people were receiving ART in low- and middle-income countries at the end of 2007, a figure representing a 7.5-fold increase over the previous 4 years. (1) The number of patients starting ART has increased exponentially since 2003 and must continue to do so if the goal of universal access to ART is to be achieved. (2) In the absence of curative treatments, lifelong follow-up of patients on ART is required to monitor adherence, treatment response and adverse effects. A growing amount of increasingly complex information needs to be reviewed at each visit, and new data must be added to the record. An important aspect is retention in care: a recent analysis of treatment programmes showed that losses to follow-up have become more common with the scale-up of ART. (3) Programmes find it increasingly difficult to follow the growing population of patients and to trace those who do not return to the clinic. Electronic Medical Record (EMR) systems can improve health care by increasing adherence to therapeutic guidelines and protocols, informing clinical decisions and decreasing medication errors. (4,5) EMR systems allow early identification of patients who miss appointments, thereby facilitating their timely tracing, and provide a platform for operational research. (6) Little is known about the role of EMR systems in the context of the scale-up of ART in resource-limited settings. A recent review identified the need for studies on the best ways of using information systems to support the expansion of HIV care in such settings. (7) The objective of this study was to describe the electronic medical databases used in ART programmes in lower-income countries and to assess the measures such programmes employ to maintain and improve data quality and reduce the loss of patients to follow-up. Methods Workshop and subsequent survey In June 2006, representatives of 21 ART programmes from 15 countries (Benin, Brazil, Burundi, Cote d'Ivoire, the Gambia, India, Kenya, Malawi, Mall, Nigeria, South Africa, Thailand, Uganda, Zambia and Zimbabwe) attended a workshop on the use of EMR systems in ART programmes in resource-limited settings. Ten of the 21 programmes participated in the Antiretroviral Treatment in Lower Income Countries (ART-LINC) collaboration, a network of treatment sites of the International Epidemiological Databases to Evaluate AIDS (IeDEA, http://www. iedea-hiv.org). (8-10) The workshop was jointly organized by IeDEA and the Knowledge Communities and Strategies (KCS) unit at WHO and hosted by the Centers for Disease Control and Prevention (CDC, United States Department of Health and Human Services) offices in Entebbe, Uganda. Based on the workshop, an online questionnaire covering the EMR systems in place, human and electronic resources, reporting systems, data storage, quality control measures and the tracing of patients lost to follow-up was written in English, translated into French and revised after pilot testing in Bern and Bordeaux. The questionnaire is available from biblio@ispm.unibe.ch. ART treatment programmes that participated in the Entebbe workshop were invited to complete the questionnaire. All sites (n = 21) agreed to participate in the survey. WHO's web-based Data Collector system (11) was used. The questionnaire was uploaded 20 December 2006, and all sites had responded by 12 February 2007. Data quality in ART-LINC Questions from the Entebbe survey were used to create indicators of data quality. First, for each programme, a computation was made of the number of hours dedicated to data entry per week divided by the number of ART patients enrolled. This was done separately for data entry clerks and medical staff. …