Public Health Action International Union Against Tuberculosis and Lung Disease Health solutions for the poor VOL 10 NO 1 PUBLISHED 21 MARCH 2020 PHA 2020; 10(1): 47–52 © 2020 The Union AFFILIATIONS 1 Centre for Infectious Diseases Research in Zambia (CIDRZ), Lusaka, Zambia 2 Operational Centre Brussels, Medical Department, Médecins Sans Frontières - Operational Research Unit (LuxOR), MSF Luxembourg 3 The Lighthouse Clinic, Lilongwe, Malawi 4 International Union Against Tuberculosis and Lung Disease, Paris, France 5 London School of Hygiene & Tropical Medicine, London, UK 6 Institute for Global Health & Infectious Diseases, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA CORRESPONDENCE Theodora Savory, Strategic Information, CIDRZ, Plot 3460 Alick Nkhata Road, Lusaka 10101, Zambia. e-mail: Theodora.Savory@ cidrz.org KEY WORDS anthropometry; EMR; data quality; HIV; SORT IT Effects of real-time electronic data entry on HIV programme data quality in Lusaka, Zambia K. Moomba, 1 A. Williams, 2 T. Savory, 1 M. Lumpa, 1 P. Chilembo, 1 H. Tweya, 3 A. D. Harries, 4,5 M. Herce 1,6 G lobal antiretroviral therapy (ART) scale-up in re- sponse to the human immunodeficiency virus (HIV) pandemic has enabled 67% of people living with HIV (PLHIV) in Eastern and Southern Africa to now access treatment. 1 In Zambia, approximately 960 000 PLHIV are currently accessing ART out of an estimated 1 200 000 PLHIV nationally. 2 The Centre for Infectious Disease Research in Zambia (CIDRZ) is a key partner in Zambia’s national ART scale-up, and sup- ports HIV-related service delivery in two provinces, in- cluding Lusaka, the capital city (estimated population: 2.6 million). 3 The Zambian public health system consists of three levels of care—first level (health posts, health centres and district hospitals), second level (provincial and general hospitals) and tertiary level (central and teach- ing hospitals). ART services are offered free of charge at all levels and in all public health facilities. As na- tional ART scale-up has accelerated since 2002, 4 and the number of patients on treatment has grown, chal- lenges have emerged with the management of ART programme data. Initially, paper-based registers and treatment cards were used to monitor PLHIV on ART, but as the number of patients and the variety of ser- vice delivery outlets grew, it became increasingly diffi- cult to maintain completeness and accuracy of data with these monitoring tools. 5 Reliable medical records data are critical for good clinical practice, programme management, and decision making. 6 Electronic medical records (EMRs), first developed in the early 1970s, 7 facilitate the collection of com- plete, accurate, and timely data. EMR systems have the potential to improve the quality of patient care, reduce the workload for healthcare workers, strengthen the monitoring and evaluation of health programmes and provide information for deci- sion-making. 8–11 However, realizing this potential de- pends on the completeness and quality of data en- tered into the EMR, with the possibility that health facilities can misreport performance on key pro- gramme indicators. 12 The EMR system used throughout Zambia is the SmartCare system, a Windows-based platform devel- oped by the Zambian Ministry of Health (MoH) in col- laboration with the Centers for Disease Control and Prevention (CDC). The SmartCare EMR was first intro- duced in 2004 to capture individual-level HIV patient data and programme indicators, but was later ex- panded to include other health facility services (e.g., outpatient care, laboratory testing, etc.). The system has become an integral part of the Zambian ART pro- gramme, serving as a clinical information manage- ment system to promote care continuity, and is vital to national and PEPFAR (President’s Emergency Fund for AIDS Relief) monitoring and evaluation. The SmartCare system has evolved over time. A pa- per-based patient file was part of the initial implemen- tation of SmartCare, with data clerks entering all in- formation from the paper-based file into the EMR at the end of the clinic day: this was called Electron- ic-Last. In 2015, the Zambian MoH introduced a direct entry system for SmartCare, with healthcare workers entering the data in real-time over a local area net- work: this was called Electronic-First. CIDRZ has been an implementing partner for SmartCare roll-out since the system’s inception. Following this shift from retro- spective to real-time data entry, vital questions have arisen about the impact of this new methodology Received 6 November 2019 Accepted 9 January 2020 http://dx.doi.org/10.5588/pha.19.0068 Setting: Human immunodeficiency virus (HIV) clinics in five hospitals and five health centres in Lusaka, Zambia, which transitioned from daily entry of paper-based data records to an electronic medical record (EMR) system by dedicated data staff (Electronic-Last) to direct real-time data entry into the EMR by frontline health workers (Electronic-First). Objective: To compare completeness and accuracy of key HIV-related variables before and after transition of data entry from Electronic-Last to Electronic-First. Design: Comparative cross-sectional study using existing secondary data. Results: Registration data (e.g., date of birth) was 100% complete and pharmacy data (e.g., antiretroviral therapy regimen) was 90% complete under both approaches. Completeness of anthropometric and vital sign data was 75% across all facilities under Electronic-Last, and this worsened after Electronic-First. Completeness of TB screening and World Health Organization clinical staging data was also 75%, but improved with Electronic-First. Data entry errors for registration and clinical consulta- tions decreased under Electronic-First, but errors in- creased for all anthropometric and vital sign variables. Patterns were similar in hospitals and health centres. Conclusion: With the notable exception of clinical con- sultation data, data completeness and accuracy did not improve after transitioning from Electronic-Last to Elec- tronic-First. For anthropometric and vital sign variables, completeness and accuracy decreased. Quality improve- ment interventions are needed to improve Electronic-First implementation.