Analysis of user interactions with a digital health wallet for enabling care continuity in the context of an ongoing pandemic.

BACKGROUND: The onset of COVID-19 and related policy responses made it difficult to study interactive health informatics solutions in clinical study settings. Instrumented log and event data from interactive systems capture temporal details that can be used to generate insights about care continuity during ongoing pandemics. OBJECTIVE: To investigate user interactions with a digital health wallet (DHW) system for addressing care continuity challenges in chronic disease management in the context of an ongoing pandemic. MATERIALS AND METHODS: We analyzed user interaction log data generated by clinicians, nurses, and patients from the deployment of a DHW in a feasibility study conducted during the COVID-19 pandemic in Kenya. We used the Hamming distance from Information Theory to quantify deviations of usage patterns extracted from the events data from predetermined workflow sequences supported by the platform. RESULTS: Nurses interacted with all the user interface elements relevant to triage. Clinicians interacted with only 43% of elements relevant to consultation, while patients interacted with 67% of the relevant user interface elements. Nurses and clinicians deviated from the predetermined workflow sequences by 42% and 36%, respectively. Most deviations pertained to users going back to previous steps in their usage workflow. CONCLUSIONS: User interaction log analysis is a valuable alternative method for generating and quantifying user experiences in the context of ongoing pandemics. However, researchers should mitigate the potential disruptions of the actual use of the studied technologies as well as use multiple approaches to investigate user experiences of health technology during pandemics.

Continuity of community-based healthcare provision during COVID-19: a multicountry interrupted time series analysis.

BACKGROUND: Pandemics often precipitate declines in essential health service utilisation, which can ultimately kill more people than the disease outbreak itself. There is some evidence, however, that the presence of adequately supported community health workers (CHWs), that is, financially remunerated, trained, supplied and supervised in line with WHO guidelines, may blunt the impact of health system shocks. Yet, adequate support for CHWs is often missing or uneven across countries. This study assesses whether adequately supported CHWs can maintain the continuity of essential community-based health service provision during the COVID-19 pandemic. METHODS: Interrupted time series analysis. Monthly routine data from 27 districts across four countries in sub-Saharan Africa were extracted from CHW and facility reports for the period January 2018-June 2021. Descriptive analysis, null hypothesis testing, and segmented regression analysis were used to assess the presence and magnitude of a possible disruption in care utilisation after the earliest reported cases of COVID-19. RESULTS: CHWs across all sites were supported in line with the WHO Guideline and received COVID-19 adapted protocols, training and personal protective equipment within 45 days after the first case in each country. We found no disruptions to the coverage of proactive household visits or integrated community case management (iCCM) assessments provided by these prepared and protected CHWs, as well as no disruptions to the speed with which iCCM was received, pregnancies were registered or postnatal care received. CONCLUSION: CHWs who were equipped and prepared for the pandemic were able to maintain speed and coverage of community-delivered care during the pandemic period. Given that the majority of CHWs globally remain unpaid and largely unsupported, this paper suggests that the opportunity cost of not professionalising CHWs may be larger than previously estimated, particularly in light of the inevitability of future pandemics.

Lessons from an eight-country community health data harmonization collaborative.

BACKGROUND: Community health workers (CHWs) are individuals who are trained and equipped to provide essential health services to their neighbors and have increased access to healthcare in communities worldwide for more than a century. However, the World Health Organization (WHO) Guideline on Health Policy and System Support to Optimize Community Health Worker Programmes reveals important gaps in the evidentiary certainty about which health system design practices lead to quality care. Routine data collection across countries represents an important, yet often untapped, opportunity for exploratory data analysis and comparative implementation science. However, epidemiological indicators must be harmonized and data pooled to better leverage and learn from routine data collection. METHODS: This article describes a data harmonization and pooling Collaborative led by the organizations of the Community Health Impact Coalition, a network of health practitioners delivering community-based healthcare in dozens of countries across four WHO regions. OBJECTIVES: The goals of the Collaborative project are to; (i) enable new opportunities for cross-site learning; (ii) use positive and negative outlier analysis to identify, test, and (if helpful) propagate design practices that lead to quality care; and (iii) create a multi-country 'brain trust' to reinforce data and health information systems across sites. RESULTS: This article outlines the rationale and methods used to establish a data harmonization and pooling Collaborative, early findings, lessons learned, and directions for future research.