Food Insecurity and Delayed or Forgone Medical Care During the COVID-19 Pandemic.

Objectives. To describe food insecurity in the United States in December 2020 and examine associations with underuse of medical care during the COVID-19 pandemic. Methods. We fielded a nationally representative Web-based survey in December 2020 (n = 8318). Multivariable logistic regression models and predicted probabilities were used to evaluate factors associated with food insecurity and compare the likelihood of delaying or forgoing medical care because of cost concerns by food security status. Results. In December 2020, 18.8% of US adults surveyed reported experiencing food insecurity. Elevated odds of food insecurity were observed among non-Hispanic Black, Hispanic, and low-income respondents. Experiencing food insecurity was significantly associated with a greater likelihood of forgoing any type of medical care as a result of cost concerns. Conclusions. Food insecurity during the COVID-19 pandemic disproportionately affected non-White and low-income individuals. Experiencing food insecurity was a significant risk factor for delaying or forgoing medical care, an association that could have cumulative short- and long-term health effects. Public Health Implications. Comprehensive policies that target the most at-risk groups are needed to address the high rates of food insecurity in the United States and mitigate its adverse health effects. (Am J Public Health. 2022;112(5):776-785. https://doi.org/10.2105/AJPH.2022.306724).

Burden of mental distress in the United States is associated with delayed medical visits and missed prescription refills during the COVID-19 pandemic.

The COVID-19 pandemic has contributed to poor health due to a decrease in healthcare utilization and those with mental health problems may be impacted. For this analysis, data came from a cross-sectional, nationally representative December 2020 survey. Logistic regression analyses examined associations between (1) mental distress and delayed medical visits, (2) mental distress and missed prescription refills, controlling for sociodemographics, pre-existing chronic conditions, and access to health insurance. We found that, compared to those that exhibited normal levels of mental distress, those with mild (aOR = 2.83, 95% CI = 2.47-3.24), moderate (aOR = 3.43, 95% CI = 2.95-3.99), and severe (aOR = 4.96, 95% CI = 4.21-5.84) mental distress showed greater odds of delaying medical visits. Similarly, compared to those that exhibited normal levels of mental distress, those with mild (aOR =3.93, 95% CI = 3.04-5.09), moderate (aOR =6.52, 95% CI = 5.07-8.43), and severe (aOR =8.69, 95% CI = 6.71-11.32) mental distress showed greater odds of missing prescription refills. Our study shows that individuals who showed signs of mental distress had increased odds of delayed medical visits and missed prescription refills, compared to those that showed normal levels of mental distress.

Changes in prenatal care and vaccine willingness among pregnant women during the COVID-19 pandemic.

INTRODUCTION: Concerns about SARS-CoV-2 infection risk in health care settings have resulted in changes in prenatal care and birth plans, such as shifts to in-person visits and increased Cesarean delivery. These changes may affect quality of care and limit opportunities for clinicians to counsel pregnant individuals, who are at higher risk of severe COVID-19 disease and adverse pregnancy outcomes, about prevention and vaccination. METHODS: We conducted a cross-sectional online survey of United States adults on changes in prenatal care, COVID-19 vaccine willingness, and reasons for unwillingness to receive a vaccine. We summarized changes in access to care and examined differences in vaccine willingness between pregnant and propensity-score matched non-pregnant controls using chi-squared tests and multivariable conditional logistic regression. RESULTS: Between December 15-23, 2020, 8481 participants completed the survey, of which 233 were pregnant. Three-quarters of pregnant women (n = 186) experienced a change in prenatal care, including format of care (n = 84, 35%) and reduced visits (n = 69, 24%). Two-thirds experienced a change in birth plans, from a hospital birth to home birth (n = 45, 18%) or vaginal birth to a Cesarean delivery (n = 42, 17%). Although 40% of pregnant women (n = 78) were unwilling to receive COVID-19 vaccination, they had higher, though non-significant, odds of reporting willingness to receive vaccination compared to similar non-pregnant women (aOR 1.38, 95% CI: 0.95, 2.00). CONCLUSION: To support pregnant women through the perinatal care continuum, maternity care teams should develop protocols to foster social support, patient-centered education around infection prevention that focuses on improved risk perception, expected changes in care due to COVID-19, and vaccine effectiveness and safety.

A Novel Score for mHealth Apps to Predict and Prevent Mortality: Further Validation and Adaptation to the US Population Using the US National Health and Nutrition Examination Survey Data Set.

BACKGROUND: The C-Score, which is an individual health score, is based on a predictive model validated in the UK and US populations. It was designed to serve as an individualized point-in-time health assessment tool that could be integrated into clinical counseling or consumer-facing digital health tools to encourage lifestyle modifications that reduce the risk of premature death. OBJECTIVE: Our study aimed to conduct an external validation of the C-Score in the US population and expand the original score to improve its predictive capabilities in the US population. The C-Score is intended for mobile health apps on wearable devices. METHODS: We conducted a literature review to identify relevant variables that were missing in the original C-Score. Subsequently, we used data from the 2005 to 2014 US National Health and Nutrition Examination Survey (NHANES; N=21,015) to test the capacity of the model to predict all-cause mortality. We used NHANES III data from 1988 to 1994 (N=1440) to conduct an external validation of the test. Only participants with complete data were included in this study. Discrimination and calibration tests were conducted to assess the operational characteristics of the adapted C-Score from receiver operating curves and a design-based goodness-of-fit test. RESULTS: Higher C-Scores were associated with reduced odds of all-cause mortality (odds ratio 0.96, P<.001). We found a good fit of the C-Score for all-cause mortality with an area under the curve (AUC) of 0.72. Among participants aged between 40 and 69 years, C-Score models had a good fit for all-cause mortality and an AUC >0.72. A sensitivity analysis using NHANES III data (1988-1994) was performed, yielding similar results. The inclusion of sociodemographic and clinical variables in the basic C-Score increased the AUCs from 0.72 (95% CI 0.71-0.73) to 0.87 (95% CI 0.85-0.88). CONCLUSIONS: Our study shows that this digital biomarker, the C-Score, has good capabilities to predict all-cause mortality in the general US population. An expanded health score can predict 87% of the mortality in the US population. This model can be used as an instrument to assess individual mortality risk and as a counseling tool to motivate behavior changes and lifestyle modifications.

Burden of mental distress in the US associated with trust in media for COVID-19 information.

During the COVID-19 pandemic, news and social media outlets have played a major role in dissemination of information. This analysis aimed to study the association between trust in social and traditional media and experiences of mental distress among a representative sample of US adults. Data for this study came from National Pandemic Pulse, a cross-sectional, nationally representative survey that sampled participants on the Dynata platform. Participants included 6435 adults surveyed between 15-23 December 2020. Ordinal logistic regression analyses examined the associations of trust in (i) social media, (ii) print media, (iii) broadcast TV and (iv) cable TV, for COVID-19-related information with self-reported mental distress (4-item Patient Health Questionnaire), controlling for sociodemographics and census region. Compared with those who distrusted social media, those who trusted social media had 2.09 times (95% CI = 1.84-2.37) greater adjusted odds of being in a more severe category of mental distress. In contrast, compared with those who distrusted print media, those who trusted print media had 0.80 times (95% CI = 0.69-0.93) lower adjusted odds of being in a more severe category of mental distress. No significant associations were found between mental distress and trust in broadcast or cable TV for accessing news about COVID-19. Trust in different news outlets may be associated with mental distress during public health emergencies like the COVID-19 pandemic. Future studies should explore mechanisms behind these associations, including adherence to best practices for crisis reporting among different media sources and exposure of individuals to misinformation.

During the COVID-19 pandemic, both, traditional channels like print, TV and cable news, as well as social media, have been major sources to obtain news about the pandemic. In this manuscript, we study the association between trust in social and traditional media and symptoms of mental distress among a nationally representative sample of 6435 US adults surveyed in December 2020. Our findings show that those who reported trusting traditional print media were less likely to report more severe mental distress. Conversely, those who reported trusting social media were more likely to report more severe levels of mental distress. This highlights the urgent need for understanding the diffusion patterns of misinformation and rumors that circulate on social media, and consumers' reactions to them. It is important that during a public health emergency, we follow best practices for crisis communication to reduce panic, address uncertainty, promote protective behaviors and mental health.

Rapid Real-time Tracking of Nonpharmaceutical Interventions and Their Association With Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Positivity: The Coronavirus Disease 2019 (COVID-19) Pandemic Pulse Study.

BACKGROUND: Current mitigation strategies for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) rely on the population-wide adoption of nonpharmaceutical interventions (NPIs). Monitoring the adoption of NPIs and their associations with SARS-CoV-2 infection history can provide key information for public health. METHODS: We sampled 1030 individuals in Maryland from 17-28 June 2020 to capture sociodemographically and geographically resolved information about NPI adoption and access to SARS-CoV-2 testing, and examine associations with self-reported SARS-CoV-2 positivity. RESULTS: Overall, 92% reported traveling for essential services and 66% visited friends/family. Use of public transport was reported by 18%. In total, 68% reported strict social distancing indoors and 53% reported strict masking indoors; indoor social distancing was significantly associated with age, and race/ethnicity and income were associated with masking. Overall, 55 participants (5.3%) self-reported ever testing positive for SARS-CoV-2, with strong dose-response relationships between several forms of movement frequency and SARS-CoV-2 positivity. In a multivariable analysis, a history of SARS-CoV-2 infection was negatively associated with strict social distancing (adjusted odds ratio [aOR] for outdoor social distancing, 0.10; 95% confidence interval, .03-.33). Only public transport use (aOR for >7 times vs never, 4.3) and visiting a place of worship (aOR for ≥3 times vs never, 16.0) remained significantly associated with SARS-CoV-2 infection after adjusting for strict social distancing and demographics. CONCLUSIONS: These results support public health messaging that strict social distancing during most activities can reduce SARS-CoV-2 transmission. Additional considerations are needed for indoor activities with large numbers of persons (places of worship and public transportation), where even NPIs may not be possible or sufficient.

Decision-support tools via mobile devices to improve quality of care in primary healthcare settings.

BACKGROUND: The ubiquity of mobile devices has made it possible for clinical decision-support systems (CDSS) to become available to healthcare providers on handheld devices at the point-of-care, including in low- and middle-income countries. The use of CDSS by providers can potentially improve adherence to treatment protocols and patient outcomes. However, the evidence on the effect of the use of CDSS on mobile devices needs to be synthesized. This review was carried out to support a World Health Organization (WHO) guideline that aimed to inform investments on the use of decision-support tools on digital devices to strengthen primary healthcare. OBJECTIVES: To assess the effects of digital clinical decision-support systems (CDSS) accessible via mobile devices by primary healthcare providers in the context of primary care settings. SEARCH METHODS: We searched CENTRAL, MEDLINE, Embase, Global Index Medicus, POPLINE, and two trial registries from 1 January 2000 to 9 October 2020. 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. SELECTION CRITERIA: Study design: we included randomized trials, including full-text studies, conference abstracts, and unpublished data irrespective of publication status or language of publication.  Types of participants: we included studies of all cadres of healthcare providers, including lay health workers and other individuals (administrative, managerial, and supervisory staff) involved in the delivery of primary healthcare services using clinical decision-support tools; and studies of clients or patients receiving care from primary healthcare providers using digital decision-support tools. Types of interventions: we included studies comparing digital CDSS accessible via mobile devices with non-digital CDSS or no intervention, in the context of primary care. CDSS could include clinical protocols, checklists, and other job-aids which supported risk prioritization of patients. Mobile devices included mobile phones of any type (but not analogue landline telephones), as well as tablets, personal digital assistants, and smartphones. We excluded studies where digital CDSS were used on laptops or integrated with electronic medical records or other types of longitudinal tracking of clients. DATA COLLECTION AND ANALYSIS: A machine learning classifier that gave each record a probability score of being a randomized trial screened all search results. Two review authors screened titles and abstracts of studies with more than 10% probability of being a randomized trial, and one review author screened those with less than 10% probability of being a randomized trial. We followed standard methodological procedures expected by Cochrane and the Effective Practice and Organisation of Care group. We used the GRADE approach to assess the certainty of the evidence for the most important outcomes. MAIN RESULTS: Eight randomized trials across varying healthcare contexts in the USA,. India, China, Guatemala, Ghana, and Kenya, met our inclusion criteria. A range of healthcare providers (facility and community-based, formally trained, and lay workers) used digital CDSS. Care was provided for the management of specific conditions such as cardiovascular disease, gastrointestinal risk assessment, and maternal and child health. The certainty of evidence ranged from very low to moderate, and we often downgraded evidence for risk of bias and imprecision. We are uncertain of the effect of this intervention on providers' adherence to recommended practice due to the very low certainty evidence (2 studies, 185 participants). The effect of the intervention on patients' and clients' health behaviours such as smoking and treatment adherence is mixed, with substantial variation across outcomes for similar types of behaviour (2 studies, 2262 participants). The intervention probably makes little or no difference to smoking rates among people at risk of cardiovascular disease but probably increases other types of desired behaviour among patients, such as adherence to treatment. The effect of the intervention on patients'/clients' health status and well-being  is also mixed (5 studies, 69,767 participants). It probably makes little or no difference to some types of health outcomes, but we are uncertain about other health outcomes, including maternal and neonatal deaths, due to very low-certainty evidence. The intervention may slightly improve patient or client acceptability and satisfaction (1 study, 187 participants). We found no studies that reported the time between the presentation of an illness and appropriate management, provider acceptability or satisfaction, resource use, or unintended consequences. AUTHORS' CONCLUSIONS: We are uncertain about the effectiveness of mobile phone-based decision-support tools on several outcomes, including adherence to recommended practice. None of the studies had a quality of care framework and focused only on specific health areas.   We need well-designed research that takes a systems lens to assess these issues.

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.

The impact of India's accredited social health activist (ASHA) program on the utilization of maternity services: a nationally representative longitudinal modelling study.

BACKGROUND: In 2006, the Government of India launched the accredited social health activist (ASHA) program, with the goal to connect marginalized communities to the health care system. We assessed the effect of the ASHA program on the utilization of maternity services. METHODS: We used data from Indian Human Development Surveys done in 2004-2005 and in 2011-2012 to assess demographic and socioeconomic factors associated with the receipt of ASHA services, and used difference-in-difference analysis with cluster-level fixed effects to assess the effect of the program on the utilization of at least one antenatal care (ANC) visit, four or more ANC visits, skilled birth attendance (SBA), and giving birth at a health facility. RESULTS: Substantial variations in the receipt of ASHA services were reported with 66% of women in northeastern states, 30% in high-focus states, and 16% of women in other states. In areas where active ASHA activity was reported, the poorest women, and women belonging to scheduled castes and other backward castes, had the highest odds of receiving ASHA services. Exposure to ASHA services was associated with a 17% (95% CI 11.8-22.1) increase in ANC-1, 5% increase in four or more ANC visits (95% CI - 1.6-11.1), 26% increase in SBA (95% CI 20-31.1), and 28% increase (95% CI 22.4-32.8) in facility births. CONCLUSIONS: Our results suggest that the ASHA program is successfully connecting marginalized communities to maternity health services. Given the potential of the ASHA in impacting service utilization, we emphasize the need to strengthen strategies to recruit, train, incentivize, and retain ASHAs.

Setting the global research agenda for community health systems: literature and consultative review.

BACKGROUND: Globally, there is renewed interest in and momentum for strengthening community health systems, as also emphasized by the recent Astana Declaration. Recent reviews have identified factors critical to successful community health worker (CHW) programs but pointed to significant evidence gaps. This review aims to propose a global research agenda to strengthen CHW programs. METHODS AND RESULTS: We conducted a search for extant systematic reviews on any intermediate factors affecting the effectiveness of CHW programs in February 2018. A total of 30 articles published after year 2000 were included. Data on research gaps were abstracted and summarized under headings based on predominant themes identified in the literature. Following this data gathering phase, two technical advisory groups comprised of experts in the field of community health-including policymakers, implementors, researchers, advocates and donors-were convened to discuss, validate, and prioritize the research gaps identified. Research gap areas that were identified in the literature and validated through expert consultation include selection and training of CHWs, community embeddedness, institutionalization of CHW programs (referrals, supervision, and supply chain), CHW needs including incentives and remuneration, governance and sustainability of CHW programs, performance and quality of care, and cost-effectiveness of CHW programs. Priority research questions included queries on effective policy, financing, governance, supervision and monitoring systems for CHWs and community health systems, implementation questions around the role of digital technologies, CHW preferences, and drivers of CHW motivation and retention over time. CONCLUSIONS: As international interest and investment in CHW programs and community health systems continue to grow, it becomes critical not only to analyze the evidence that exists, but also to clearly define research questions and collect additional evidence to ensure that CHW programs are effective, efficient, equity promoting, and evidence based. Generally, the literature places a strong emphasis on the need for higher quality, more robust research.

A conceptual framework for measuring community health workforce performance within primary health care systems.

BACKGROUND: With the 40th anniversary of the Declaration of Alma-Ata, a global effort is underway to re-focus on strengthening primary health care systems, with emphasis on leveraging community health workers (CHWs) towards the goal of achieving universal health coverage for all. Institutionalizing effective, sustainable community health systems is currently limited by a lack of standard metrics for measuring CHW performance and the systems they work within. Developed through iterative consultations, supported by the Bill & Melinda Gates Foundation and in partnership with USAID and UNICEF, this paper details a framework, list of indicators, and measurement considerations for monitoring CHW performance in low- and middle-income countries. METHODS: A review of peer-reviewed articles, reports, and global data collection tools was conducted to identify key measurement domains in monitoring CHW performance. Three consultations were successively convened with global stakeholders, community health implementers, advocates, measurement experts, and Ministry of Health representatives using a modified Delphi approach to build consensus on priority indicators. During this process, a structured, web-based survey was administered to identify the importance and value of specific measurement domains, sub-domains, and indicators determined through the literature reviews and initial stakeholder consultations. Indicators with more than 75% support from participants were further refined with expert qualitative input. RESULTS: Twenty-one sub-domains for measurement were identified including measurement of incentives for CHWs, supervision and performance appraisal, data use, data reporting, service delivery, quality of services, CHW absenteeism and attrition, community use of services, experience of services, referral/counter-referral, credibility/trust, and programmatic costs. Forty-six indicators were agreed upon to measure the sub-domains. In the absence of complete population enumeration and digitized health information systems, the quality of metrics to monitor CHW programs is limited. CONCLUSIONS: Better data collection approaches at the community level are needed to strengthen management of CHW programs and community health systems. The proposed list of metrics balances exhaustive and pragmatic measurement of CHW performance within primary healthcare systems. Adoption of the proposed framework and associated indicators by CHW program implementors may improve programmatic effectiveness, strengthen their accountability to national community health systems, drive programmatic quality improvement, and plausibly improve the impact of these programs.

Evidence on feasibility and effective use of mHealth strategies by frontline health workers in developing countries: systematic review.

OBJECTIVES: Given the large-scale adoption and deployment of mobile phones by health services and frontline health workers (FHW), we aimed to review and synthesise the evidence on the feasibility and effectiveness of mobile-based services for healthcare delivery. METHODS: Five databases - MEDLINE, EMBASE, Global Health, Google Scholar and Scopus - were systematically searched for relevant peer-reviewed articles published between 2000 and 2013. Data were extracted and synthesised across three themes as follows: feasibility of use of mobile tools by FHWs, training required for adoption of mobile tools and effectiveness of such interventions. RESULTS: Forty-two studies were included in this review. With adequate training, FHWs were able to use mobile phones to enhance various aspects of their work activities. Training of FHWs to use mobile phones for healthcare delivery ranged from a few hours to about 1 week. Five key thematic areas for the use of mobile phones by FHWs were identified as follows: data collection and reporting, training and decision support, emergency referrals, work planning through alerts and reminders, and improved supervision of and communication between healthcare workers. Findings suggest that mobile based data collection improves promptness of data collection, reduces error rates and improves data completeness. Two methodologically robust studies suggest that regular access to health information via SMS or mobile-based decision-support systems may improve the adherence of the FHWs to treatment algorithms. The evidence on the effectiveness of the other approaches was largely descriptive and inconclusive. CONCLUSIONS: Use of mHealth strategies by FHWs might offer some promising approaches to improving healthcare delivery; however, the evidence on the effectiveness of such strategies on healthcare outcomes is insufficient.

Adolescent/Youth Reproductive Mobile Access and Delivery Initiative for Love and Life Outcomes (ARMADILLO) Study: formative protocol for mHealth platform development and piloting.

BACKGROUND: There is a high unmet need for sexual and reproductive health (SRH) information and services among youth (ages 15-24) worldwide (MacQuarrie KLD. Unmet Need for Family Planning among Young Women: Levels and Trends 2014). With the proliferation of mobile technology, and its popularity with this age group, mobile phones offer a novel and accessible platform for a discreet, on-demand service providing SRH information. The Adolescent/Youth Reproductive Mobile Access and Delivery Initiative for Love and Life Outcomes (ARMADILLO) formative study will inform the development of an intervention, which will use the popular channel of SMS (text messages) to deliver SRH information on-demand to youth. METHODS/DESIGN: Following the development of potential SMS message content in partnership with SRH technical experts and youth, formative research activities will take place over two phases. Phase 1 will use focus group discussions (FGDs) with youth and parents/caregivers to develop and test the appropriateness and acceptability of the SMS messages. Phase 2 will consist of 'peer piloting', where youth participants will complete an SRH outcome-focused pretest, be introduced to the system and then have three weeks to interact with the system and share it with friends. Participants will then return to complete the SRH post-test and participate in an in-depth interview about their own and their peers' opinions and experiences using ARMADILLO. DISCUSSION: The ARMADILLO formative stage will culminate in the finalization of country-specific ARMADILLO messaging. Reach and impact of ARMADILLO will be measured at later stages. We anticipate that the complete ARMADILLO platform will be scalable, with the potential for national-level adoption.

Strategies for Sustained Empowerment of Community Health Workers: A Qualitative Analysis of the Comprehensive Rural Health Project in Jamkhed, India.

To understand the core aspects of an empowerment-based Community Health Worker (CHW) training program, we studied the model of the Comprehensive Rural Health Project (CRHP) in Jamkhed, India-an organization known for facilitating empowerment of women as Village Health Workers (VHWs) and agents of community change. We define empowerment as a means by which individuals gain health and development-related skills and knowledge to facilitate positive change within their lives and communities. Using VHW training observations and semi-structured interviews with health workers and senior trainers, 6 themes were developed and applied in 4 focus group sessions with 18 multigenerational VHWs trained by the CRHP. Transcripts were qualitatively analyzed under 6 themes-selection, baseline training, continuing education and support, community participation, community empowerment, and commitment and longevity. Empowerment of VHWs was found to be an intentional process involving the creation of safe and supportive environments conducive to long-term participatory and experiential learning with professionals who facilitate and mentor. The impact of the baseline training is maintained through ongoing program-VHW interactions and knowledge reinforcement in both the field and training center. Importantly, these interactions reinforce VHWs' credibility and confidence in communities served. Community participation was found to be of key importance starting at the selection phase. The methods used for selection, training and ongoing support are critical to developing a cadre of competent, effective and motivated VHWs as well as fostering long-lasting self-development and leadership skills. Downstream effectiveness of community empowerment on health outcomes is demonstrated through indicators such as access to safe deliveries, declining child malnutrition rates, high vaccination rates as well as reductions in stigmatization of illness and caste discrimination.

How Can Community Data Be Leveraged to Advance Primary Health Care? A Scoping Review of Community-Based Health Information Systems.

BACKGROUND: Community-based health information systems (CBISs) can provide critical insights into how community health systems function, and digitized CBISs may improve the quality of community-level data and facilitate integration and use of CBISs within the broader health system. This scoping review aims to understand how CBISs have been implemented, integrated, and used to support community health outcomes in low- and middle-income countries (LMICs). METHODS: Both peer-reviewed and gray literature were included; relevant articles were identified using key terms and controlled vocabulary related to community/primary health care, health information systems, digital health, and LMICs. A total of 11,611 total records were identified from 5 databases and the gray literature. After deduplication, 6,985 peer-reviewed/gray literature were screened, and 95 articles/reports were included, reporting on 105 CBIS implementations across 38 countries. RESULTS: Findings show that 55% of CBISs included some level of digitization, with just 28% being fully digitized (for data collection and reporting). Data flow from the community level into the health system varied, with digitized CBISs more likely to reach national-level integration. National-level integration was primarily seen among vertical CBISs. Data quality challenges were present in both paper-based and digitized CBISs, exacerbated by fragmentation of the community health landscape with often parallel reporting systems. CBIS data use was constrained to mostly vertical and digitized (partially or fully) CBISs at national/subnational levels. CONCLUSION: Digitization can play a pivotal role in strengthening CBIS use, but findings demonstrate that CBISs are only as effective as the community health systems they are embedded within. Community-level data are often not being integrated into national/subnational health information systems, undermining the ability to understand what the community health needs are. Furthermore, stronger investments within community health systems need to be in place broadly to reduce fragmentation and provide stronger infrastructural and systemic support to the community health workforce.

Impact of a recognition package as an incentive to strengthen the motivation, performance, and retention of village health teams in Uganda: a study protocol for a cluster randomized controlled trial.

INTRODUCTION: Uganda's community health worker (CHW), or village health team (VHT), program faces significant challenges with poor retention and insufficient financial and program investment. Adequate compensation comprising financial and non-financial components is critical to retaining any workforce, including CHWs. This study evaluates the impact of a recognition-based non-financial incentives package on the motivation, performance, and retention of VHTs, as well as on the utilization of health services by the community. The incentive package and intervention were developed in collaboration with the district-level leadership and award VHTs who have met predetermined performance thresholds with a certificate and a government-branded jacket in a public ceremony. METHODS: A two-armed cluster randomized controlled trial (RCT), conducted at the parish level in Uganda's Masindi District, will evaluate the effects of the 12-month intervention. The cluster-RCT will use a mixed-methods approach, which includes a baseline/endline VHT survey to assess the impact of the intervention on key outcomes, with an expected sample of 240 VHTs per study arm; our primary outcome is the total number of household visits per VHT and our multiple secondary outcomes include other performance indicators, motivation, and retention; VHT performance and retention data will be validated using monthly phone surveys tracking key performance indicators and through abstraction of VHT-submitted health facility reports; and focus group discussions will be conducted with VHTs and community members to understand how the intervention was received. Data collection activities will be administered in local languages. To assess the impact of the intervention, the study will conduct a regression analysis using Generalized Estimating Equations adjusting for cluster effect. Further, a difference-in-differences analysis will be conducted. DISCUSSION: This study utilized a cluster-RCT design to assess the impact of a recognition-based incentives intervention on the motivation, performance, and retention of VHTs in Uganda's Masindi District. Utilizing a mixed-methods approach, the study will provide insights on the effectiveness and limitations of the intervention, VHT perspectives on perceived value, and critical insights on how non-financial incentives might support the strengthening of the community health workforce. TRIAL REGISTRATION: ClinicalTrials.gov NCT05176106. Retrospectively registered on 4 January 2022.

Use of a digital job-aid in improving antenatal clinical protocols and quality of care in rural primary-level health facilities in Burkina Faso: a quasi-experimental evaluation.

OBJECTIVE: We assessed the impact of a digital clinical decision support (CDS) tool in improving health providers adherence to recommended antenatal protocols and service quality in rural primary-level health facilities in Burkina Faso. DESIGN: A quasi-experimental evaluation based on a cross-sectional post-intervention assessment comparing the intervention district to a comparison group. SETTING AND PARTICIPANTS: The study included 331 direct observations and exit interviews of pregnant women seeking antenatal care (ANC) across 48 rural primary-level health facilities in Burkina Faso in 2021. INTERVENTION: Digital CDS tool to improve health providers adherence to recommended antenatal protocols. OUTCOME MEASURES: We analysed the quality of care on both the supply and demand sides. Quality-of-care service scores were based on actual care provided and expected care according to standards. Pregnant women's knowledge of counselling and satisfaction score after receiving care were also calculated. Other outcomes included time of clinical encounter. RESULTS: The overall quality of health service provision was comparable across intervention and comparison health facilities (52% vs 51%) despite there being a significantly higher proportion of lower skilled providers in the intervention arm (42.5% vs 17.8%). On average, ANC visits were longer in the intervention area (median 24 min, IQR 18) versus comparison area (median 12 min, IQR: 8). The intervention arm had a significantly higher score difference in women's knowledge of received counselling (16.4 points, 95% CI 10.37 to 22.49), and women's satisfaction (16.18 points, 95% CI: 9.95 to 22.40). CONCLUSION: Digital CDS tools provide a valuable opportunity to achieve substantial improvements of the quality of ANC and broadly maternal and newborn health in settings with high burden mortality and less trained health cadres when adequately implemented.

Health-focused conversational agents in person-centered care: a review of apps.

Health-focused apps with chatbots ("healthbots") have a critical role in addressing gaps in quality healthcare. There is limited evidence on how such healthbots are developed and applied in practice. Our review of healthbots aims to classify types of healthbots, contexts of use, and their natural language processing capabilities. Eligible apps were those that were health-related, had an embedded text-based conversational agent, available in English, and were available for free download through the Google Play or Apple iOS store. Apps were identified using 42Matters software, a mobile app search engine. Apps were assessed using an evaluation framework addressing chatbot characteristics and natural language processing features. The review suggests uptake across 33 low- and high-income countries. Most healthbots are patient-facing, available on a mobile interface and provide a range of functions including health education and counselling support, assessment of symptoms, and assistance with tasks such as scheduling. Most of the 78 apps reviewed focus on primary care and mental health, only 6 (7.59%) had a theoretical underpinning, and 10 (12.35%) complied with health information privacy regulations. Our assessment indicated that only a few apps use machine learning and natural language processing approaches, despite such marketing claims. Most apps allowed for a finite-state input, where the dialogue is led by the system and follows a predetermined algorithm. Healthbots are potentially transformative in centering care around the user; however, they are in a nascent state of development and require further research on development, automation and adoption for a population-level health impact.

Understanding Factors That Support Community Health Worker Motivation, Job Satisfaction, and Performance in Three Ugandan Districts: Opportunities for Strengthening Uganda's Community Health Worker Program.

BACKGROUND: Uganda's community health worker (CHW) program experiences several challenges related to the appropriate motivation, job satisfaction, and performance of the CHW workforce. This study aims to identify barriers in the effective implementation of financial and non-financial incentives to support CHWs and to strengthen Uganda's CHW program. METHODS: The study was implemented in Uganda's Lira, Wakiso, and Mayuge districts in May 2019. Ten focus group discussions (FGDs) were held with 91 CHWs, 17 in-depth interviews (IDIs) were held with CHW supervisors, and 7 IDIs were held with policy-level stakeholders. Participants included stakeholders from both the Ugandan government and non-governmental organizations (NGOs). Utilizing a thematic approach, themes around motivation, job satisfaction, incentive preferences, and CHW relationships with the community, healthcare facilities, and government were analyzed. RESULTS: CHWs identified a range of factors that contributed to their motivation or demotivation. Non-monetary factors included recognition from the health system and community, access to transportation, methods for identification as a healthcare worker, provision of working tools, and training opportunities. Monetary factors included access to monthly stipends, transportation-related refunds, and timely payment systems to reduce refund delays to CHWs. Additionally, CHWs indicated wanting to be considered for recruitment into the now-halted rollout of a salaried CHW cadre, given the provision of payment. CONCLUSION: It is imperative to consider how to best support the current CHW program prior to the introduction of new cadres, as it can serve to exacerbate tensions between cadres and further undermine provision of community health. Providing a harmonized, balanced, and uniform combination of both monetary incentives with non-monetary incentives is vital for effective CHW programs.

Implementation Outcomes Assessment of a Digital Clinical Support Tool for Intrapartum Care in Rural Kenya: Observational Analysis.

BACKGROUND: iDeliver, a digital clinical support system for maternal and neonatal care, was developed to support quality of care improvements in Kenya. OBJECTIVE: Taking an implementation research approach, we evaluated the adoption and fidelity of iDeliver over time and assessed the feasibility of its use to provide routine Ministry of Health (MOH) reports. METHODS: We analyzed routinely collected data from iDeliver, which was implemented at the Transmara West Sub-County Hospital from December 2018 to September 2020. To evaluate its adoption, we assessed the proportion of actual facility deliveries that was recorded in iDeliver over time. We evaluated the fidelity of iDeliver use by studying the completeness of data entry by care providers during each stage of the labor and delivery workflow and whether the use reflected iDeliver's envisioned function. We also examined the data completeness of the maternal and neonatal indicators prioritized by the Kenya MOH. RESULTS: A total of 1164 deliveries were registered in iDeliver, capturing 45.31% (1164/2569) of the facility's deliveries over 22 months. This uptake of registration improved significantly over time by 6.7% (SE 2.1) on average in each quarter-year (P=.005), from 9.6% (15/157) in the fourth quarter of 2018 to 64% (235/367) in the third quarter of 2020. Across iDeliver's workflow, the overall completion rate of all variables improved significantly by 2.9% (SE 0.4) on average in each quarter-year (P<.001), from 22.25% (257/1155) in the fourth quarter of 2018 to 49.21% (8905/18,095) in the third quarter of 2020. Data completion was highest for the discharge-labor summary stage (16,796/23,280, 72.15%) and lowest for the labor signs stage (848/5820, 14.57%). The completion rate of the key MOH indicators also improved significantly by 4.6% (SE 0.5) on average in each quarter-year (P<.001), from 27.1% (69/255) in the fourth quarter of 2018 to 83.75% (3346/3995) in the third quarter of 2020. CONCLUSIONS: iDeliver's adoption and data completeness improved significantly over time. The assessment of iDeliver' use fidelity suggested that some features were more easily used because providers had time to enter data; however, there was low use during active childbirth, which is when providers are necessarily engaged with the woman and newborn. These insights on the adoption and fidelity of iDeliver use prompted the team to adapt the application to reflect the users' culture of use and further improve the implementation of iDeliver.