User-centered design and usability testing of RxMAGIC: a prescription management and general inventory control system for free clinic dispensaries

The relationship between electronic health records user interface features and data quality of patient clinical information: an integrative review

OBJECTIVES

Electronic health records (EHRs) user interfaces (UI) designed for data entry can potentially impact the quality of patient information captured in the EHRs. This review identified and synthesized the literature evidence about the relationship of UI features in EHRs on data quality (DQ).

MATERIALS AND METHODS

We performed an integrative review of research studies by conducting a structured search in 5 databases completed on October 10, 2022. We applied Whittemore & Knafl's methodology to identify literature, extract, and synthesize information, iteratively. We adapted Kmet et al appraisal tool for the quality assessment of the evidence. The research protocol was registered with PROSPERO (CRD42020203998).

RESULTS

Eleven studies met the inclusion criteria. The relationship between 1 or more UI features and 1 or more DQ indicators was examined. UI features were classified into 4 categories: 3 types of data capture aids, and other methods of DQ assessment at the UI. The Weiskopf et al measures were used to assess DQ: completeness (n = 10), correctness (n = 10), and currency (n = 3). UI features such as mandatory fields, templates, and contextual autocomplete improved completeness or correctness or both. Measures of currency were scarce.

DISCUSSION

The paucity of studies on UI features and DQ underscored the limited knowledge in this important area. The UI features examined had both positive and negative effects on DQ. Standardization of data entry and further development of automated algorithmic aids, including adaptive UIs, have great promise for improving DQ. Further research is essential to ensure data captured in our electronic systems are high quality and valid for use in clinical decision-making and other secondary analyses.

Tracking health commodity inventory and notifying stock levels via mobile devices: a mixed methods systematic review

BACKGROUND

Health systems need timely and reliable access to essential medicines and health commodities, but problems with access are common in many settings. Mobile technologies offer potential low-cost solutions to the challenge of drug distribution and commodity availability in primary healthcare settings. However, the evidence on the use of mobile devices to address commodity shortages is sparse, and offers no clear way forward.

OBJECTIVES

Primary objective To assess the effects of strategies for notifying stock levels and digital tracking of healthcare-related commodities and inventory via mobile devices across the primary healthcare system Secondary objectives To describe what mobile device strategies are currently being used to improve reporting and digital tracking of health commodities To identify factors influencing the implementation of mobile device interventions targeted at reducing stockouts of health commodities SEARCH METHODS: We searched CENTRAL, MEDLINE Ovid, Embase Ovid, Global Index Medicus WHO, POPLINE K4Health, and two trials registries in August 2019. We also searched Epistemonikos for related systematic reviews and potentially eligible primary studies. We conducted a grey literature search using mHealthevidence.org, and issued a call for papers through popular digital health communities of practice. Finally, we conducted citation searches of included studies. We searched for studies published after 2000, in any language.

SELECTION CRITERIA

For the primary objective, we included individual and cluster-randomised trials, controlled before-after studies, and interrupted time series studies. For the secondary objectives, we included any study design, which could be quantitative, qualitative, or descriptive, that aimed to describe current strategies for commodity tracking or stock notification via mobile devices; or aimed to explore factors that influenced the implementation of these strategies, including studies of acceptability or feasibility. We included studies of all cadres of healthcare providers, including lay health workers, and others involved in the distribution of health commodities (administrative staff, managerial and supervisory staff, dispensary staff); and all other individuals involved in stock notification, who may be based in a facility or a community setting, and involved with the delivery of primary healthcare services. We included interventions aimed at improving the availability of health commodities using mobile devices in primary healthcare settings. For the primary objective, we included studies that compared health commodity tracking or stock notification via mobile devices with standard practice. For the secondary objectives, we included studies of health commodity tracking and stock notification via mobile device, if we could extract data relevant to our secondary objectives.

DATA COLLECTION AND ANALYSIS

For the primary objective, two authors independently screened all records, extracted data from the included studies, and assessed the risk of bias. For the analyses of the primary objectives, we reported means and proportions where appropriate. We used the GRADE approach to assess the certainty of the evidence, and prepared a 'Summary of findings' table. For the secondary objective, two authors independently screened all records, extracted data from the included studies, and applied a thematic synthesis approach to synthesise the data. We assessed methodological limitation using the Ways of Evaluating Important and Relevant Data (WEIRD) tool. We used the GRADE-CERQual approach to assess our confidence in the evidence, and prepared a 'Summary of qualitative findings' table.

MAIN RESULTS

Primary objective For the primary objective, we included one controlled before-after study conducted in Malawi. We are uncertain of the effect of cStock plus enhanced management, or cStock plus effective product transport on the availability of commodities, quality and timeliness of stock management, and satisfaction and acceptability, because we assessed the evidence as very low-certainty. The study did not report on resource use or unintended consequences. Secondary objective For the secondary objectives, we included 16 studies, using a range of study designs, which described a total of eleven interventions. All studies were conducted in African (Tanzania, Kenya, Malawi, Ghana, Ethiopia, Cameroon, Zambia, Liberia, Uganda, South Africa, and Rwanda) and Asian (Pakistan and India) countries. Most of the interventions aimed to make data about stock levels and potential stockouts visible to managers, who could then take corrective action to address them. We identified several factors that may influence the implementation of stock notification and tracking via mobile device. These include challenges tied to infrastructural issues, such as poor access to electricity or internet, and broader health systems issues, such as drug shortages at the national level which cannot be mitigated by interventions at the primary healthcare level (low confidence). Several factors were identified as important, including strong partnerships with local authorities, telecommunication companies, technical system providers, and non-governmental organizations (very low confidence); availability of stock-level data at all levels of the health system (low confidence); the role of supportive supervision and responsive management (moderate confidence); familiarity and training of health workers in the use of the digital devices (moderate confidence); availability of technical programming expertise for the initial development and ongoing maintenance of the digital systems (low confidence); incentives, such as phone credit for personal use, to support regular use of the system (low confidence); easy-to-use systems built with user participation (moderate confidence); use of basic or personal mobile phones to support easier adoption (low confidence); consideration for software features, such as two-way communication (low confidence); and data availability in an easy-to-use format, such as an interactive dashboard (moderate confidence).

AUTHORS' CONCLUSIONS

We need more, well-designed, controlled studies comparing stock notification and commodity management via mobile devices with paper-based commodity management systems. Further studies are needed to understand the factors that may influence the implementation of such interventions, and how implementation considerations differ by variations in the intervention.