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

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. 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. 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. Study design: we included randomized trials, including full-text studies, conference abstracts, and unpublished data irrespective of publication status or language of publication.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. 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. 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. 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.

Agarwal S ，Glenton C ，Tamrat T ，Henschke N ，Maayan N ，Fønhus MS ，Mehl GL ，Lewin S ... -  《Cochrane Database of Systematic Reviews》

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

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. 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. 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. 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. 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). 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.

Agarwal S ，Glenton C ，Henschke N ，Tamrat T ，Bergman H ，Fønhus MS ，Mehl GL ，Lewin S ... -  《Cochrane Database of Systematic Reviews》

Birth and death notification via mobile devices: a mixed methods systematic review.

Ministries of health, donors, and other decision-makers are exploring how they can use mobile technologies to acquire accurate and timely statistics on births and deaths. These stakeholders have called for evidence-based guidance on this topic. This review was carried out to support World Health Organization (WHO) recommendations on digital interventions for health system strengthening. Primary objective: To assess the effects of birth notification and death notification via a mobile device, compared to standard practice. Secondary objectives: To describe the range of strategies used to implement birth and death notification via mobile devices and identify factors influencing the implementation of birth and death notification via mobile devices. We searched CENTRAL, MEDLINE, Embase, the Global Health Library, and POPLINE (August 2, 2019). We searched two trial registries (August 2, 2019). We also searched Epistemonikos for related systematic reviews and potentially eligible primary studies (August 27, 2019). We conducted a grey literature search using mHealthevidence.org (August 15, 2017) and issued a call for papers through popular digital health communities of practice. Finally, we conducted citation searches of included studies in Web of Science and Google Scholar (May 15, 2020). We searched for studies published after 2000 in any language.  SELECTION CRITERIA: For the primary objective, we included individual and cluster-randomised trials; cross-over and stepped-wedge study designs; controlled before-after studies, provided they have at least two intervention sites and two control sites; and interrupted time series studies. For the secondary objectives, we included any study design, either quantitative, qualitative, or descriptive, that aimed to describe current strategies for birth and death notification via mobile devices; or to explore factors that influence the implementation of these strategies, including studies of acceptability or feasibility. For the primary objective, we included studies that compared birth and death notification via mobile devices with standard practice. For the secondary objectives, we included studies of birth and death notification via mobile device as long as we could extract data relevant to our secondary objectives. We included studies of all cadres of healthcare providers, including lay health workers; administrative, managerial, and supervisory staff; focal individuals at the village or community level; children whose births were being notified and their parents/caregivers; and individuals whose deaths were being notified and their relatives/caregivers. For the primary objective, two authors independently screened all records, extracted data from the included studies and assessed risk of bias. For the analyses of the primary objective, we reported means and proportions, where appropriate. We used the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach to assess the certainty of the evidence and we prepared a 'Summary of Findings' table. For the secondary objectives, two authors screened all records, one author extracted data from the included studies and assessed methodological limitations using the WEIRD tool and a second author checked the data and assessments. We carried out a framework analysis using the Supporting the Use of Research Evidence (SURE) framework to identify themes in the data. We used the GRADE-CERQual (Confidence in the Evidence from Reviews of Qualitative research) approach to assess our confidence in the evidence and we prepared a 'Summary of Qualitative Findings' table. For the primary objective, we included one study, which used a controlled before-after study design. The study was conducted in Lao People's Democratic Republic and assessed the effect of using mobile devices for birth notification on outcomes related to coverage and timeliness of Hepatitis B vaccination. However, we are uncertain of the effect of this approach on these outcomes because the certainty of this evidence was assessed as very low. The included study did not assess resource use or unintended consequences. For the primary objective, we did not identify any studies using mobile devices for death notification. For the secondary objective, we included 21 studies. All studies were conducted in low- or middle-income settings. They focussed on identification of births and deaths in rural, remote, or marginalised populations who are typically under-represented in civil registration processes or traditionally seen as having poor access to health services. The review identified several factors that could influence the implementation of birth-death notification via mobile device. These factors were tied to the health system, the person responsible for notifying, the community and families; and include: - Geographic barriers that could prevent people's access to birth-death notification and post-notification services - Access to health workers and other notifiers with enough training, supervision, support, and incentives - Monitoring systems that ensure the quality and timeliness of the birth and death data - Legal frameworks that allow births and deaths to be notified by mobile device and by different types of notifiers - Community awareness of the need to register births and deaths - Socio-cultural norms around birth and death - Government commitment - Cost to the system, to health workers and to families - Access to electricity and network connectivity, and compatibility with existing systems - Systems that protect data confidentiality We have low to moderate confidence in these findings. This was mainly because of concerns about methodological limitations and data adequacy. We need more, well-designed studies of the effect of birth and death notification via mobile devices and on factors that may influence its implementation.

Vasudevan L ，Glenton C ，Henschke N ，Maayan N ，Eyers J ，Fønhus MS ，Tamrat T ，Mehl GL ，Lewin S ... -  《Cochrane Database of Systematic Reviews》

Mobile technologies to support healthcare provider to healthcare provider communication and management of care.

The widespread use of mobile technologies can potentially expand the use of telemedicine approaches to facilitate communication between healthcare providers, this might increase access to specialist advice and improve patient health outcomes. To assess the effects of mobile technologies versus usual care for supporting communication and consultations between healthcare providers on healthcare providers' performance, acceptability and satisfaction, healthcare use, patient health outcomes, acceptability and satisfaction, costs, and technical difficulties. We searched CENTRAL, MEDLINE, Embase and three other databases from 1 January 2000 to 22 July 2019. We searched clinical trials registries, checked references of relevant systematic reviews and included studies, and contacted topic experts. Randomised trials comparing mobile technologies to support healthcare provider to healthcare provider communication and consultations compared with usual care. We followed standard methodological procedures expected by Cochrane and EPOC. We used the GRADE approach to assess the certainty of the evidence. We included 19 trials (5766 participants when reported), most were conducted in high-income countries. The most frequently used mobile technology was a mobile phone, often accompanied by training if it was used to transfer digital images. Trials recruited participants with different conditions, and interventions varied in delivery, components, and frequency of contact. We judged most trials to have high risk of performance bias, and approximately half had a high risk of detection, attrition, and reporting biases. Two studies reported data on technical problems, reporting few difficulties. Mobile technologies used by primary care providers to consult with hospital specialists We assessed the certainty of evidence for this group of trials as moderate to low. Mobile technologies: - probably make little or no difference to primary care providers following guidelines for people with chronic kidney disease (CKD; 1 trial, 47 general practices, 3004 participants); - probably reduce the time between presentation and management of individuals with skin conditions, people with symptoms requiring an ultrasound, or being referred for an appointment with a specialist after attending primary care (4 trials, 656 participants); - may reduce referrals and clinic visits among people with some skin conditions, and increase the likelihood of receiving retinopathy screening among people with diabetes, or an ultrasound in those referred with symptoms (9 trials, 4810 participants when reported); - probably make little or no difference to patient-reported quality of life and health-related quality of life (2 trials, 622 participants) or to clinician-assessed clinical recovery (2 trials, 769 participants) among individuals with skin conditions; - may make little or no difference to healthcare provider (2 trials, 378 participants) or participant acceptability and satisfaction (4 trials, 972 participants) when primary care providers consult with dermatologists; - may make little or no difference for total or expected costs per participant for adults with some skin conditions or CKD (6 trials, 5423 participants). Mobile technologies used by emergency physicians to consult with hospital specialists about people attending the emergency department We assessed the certainty of evidence for this group of trials as moderate. Mobile technologies: - probably slightly reduce the consultation time between emergency physicians and hospital specialists (median difference -12 minutes, 95% CI -19 to -7; 1 trial, 345 participants); - probably reduce participants' length of stay in the emergency department by a few minutes (median difference -30 minutes, 95% CI -37 to -25; 1 trial, 345 participants). We did not identify trials that reported on providers' adherence, participants' health status and well-being, healthcare provider and participant acceptability and satisfaction, or costs. Mobile technologies used by community health workers or home-care workers to consult with clinic staff We assessed the certainty of evidence for this group of trials as moderate to low. Mobile technologies: - probably make little or no difference in the number of outpatient clinic and community nurse consultations for participants with diabetes or older individuals treated with home enteral nutrition (2 trials, 370 participants) or hospitalisation of older individuals treated with home enteral nutrition (1 trial, 188 participants); - may lead to little or no difference in mortality among people living with HIV (RR 0.82, 95% CI 0.55 to 1.22) or diabetes (RR 0.94, 95% CI 0.28 to 3.12) (2 trials, 1152 participants); - may make little or no difference to participants' disease activity or health-related quality of life in participants with rheumatoid arthritis (1 trial, 85 participants); - probably make little or no difference for participant acceptability and satisfaction for participants with diabetes and participants with rheumatoid arthritis (2 trials, 178 participants). We did not identify any trials that reported on providers' adherence, time between presentation and management, healthcare provider acceptability and satisfaction, or costs. Our confidence in the effect estimates is limited. Interventions including a mobile technology component to support healthcare provider to healthcare provider communication and management of care may reduce the time between presentation and management of the health condition when primary care providers or emergency physicians use them to consult with specialists, and may increase the likelihood of receiving a clinical examination among participants with diabetes and those who required an ultrasound. They may decrease the number of people attending primary care who are referred to secondary or tertiary care in some conditions, such as some skin conditions and CKD. There was little evidence of effects on participants' health status and well-being, satisfaction, or costs.

Gonçalves-Bradley DC ，J Maria AR ，Ricci-Cabello I ，Villanueva G ，Fønhus MS ，Glenton C ，Lewin S ，Henschke N ，Buckley BS ，Mehl GL ，Tamrat T ，Shepperd S ... -  《Cochrane Database of Systematic Reviews》

Targeted client communication via mobile devices for improving maternal, neonatal, and child health.

The global burden of poor maternal, neonatal, and child health (MNCH) accounts for more than a quarter of healthy years of life lost worldwide. Targeted client communication (TCC) via mobile devices (MD) (TCCMD) may be a useful strategy to improve MNCH. To assess the effects of TCC via MD on health behaviour, service use, health, and well-being for MNCH. In July/August 2017, we searched five databases including The Cochrane Central Register of Controlled Trials, MEDLINE and Embase. We also searched two trial registries. A search update was carried out in July 2019 and potentially relevant studies are awaiting classification. We included randomised controlled trials that assessed TCC via MD to improve MNCH behaviour, service use, health, and well-being. Eligible comparators were usual care/no intervention, non-digital TCC, and digital non-targeted client communication. We used standard methodological procedures recommended by Cochrane, although data extraction and risk of bias assessments were carried out by one person only and cross-checked by a second. We included 27 trials (17,463 participants). Trial populations were: pregnant and postpartum women (11 trials conducted in low-, middle- or high-income countries (LMHIC); pregnant and postpartum women living with HIV (three trials carried out in one lower middle-income country); and parents of children under the age of five years (13 trials conducted in LMHIC). Most interventions (18) were delivered via text messages alone, one was delivered through voice calls only, and the rest were delivered through combinations of different communication channels, such as multimedia messages and voice calls. Pregnant and postpartum women TCCMD versus standard care For behaviours, TCCMD may increase exclusive breastfeeding in settings where rates of exclusive breastfeeding are less common (risk ratio (RR) 1.30, 95% confidence intervals (CI) 1.06 to 1.59; low-certainty evidence), but have little or no effect in settings where almost all women breastfeed (low-certainty evidence). For use of health services, TCCMD may increase antenatal appointment attendance (odds ratio (OR) 1.54, 95% CI 0.80 to 2.96; low-certainty evidence); however, the CI encompasses both benefit and harm. The intervention may increase skilled attendants at birth in settings where a lack of skilled attendants at birth is common (though this differed by urban/rural residence), but may make no difference in settings where almost all women already have a skilled attendant at birth (OR 1.00, 95% CI 0.34 to 2.94; low-certainty evidence). There were uncertain effects on maternal and neonatal mortality and morbidity because the certainty of the evidence was assessed as very low. TCCMD versus non-digital TCC (e.g. pamphlets) TCCMD may have little or no effect on exclusive breastfeeding (RR 0.92, 95% CI 0.79 to 1.07; low-certainty evidence). TCCMD may reduce 'any maternal health problem' (RR 0.19, 95% CI 0.04 to 0.79) and 'any newborn health problem' (RR 0.52, 95% CI 0.25 to 1.06) reported up to 10 days postpartum (low-certainty evidence), though the CI for the latter includes benefit and harm. The effect on health service use is unknown due to a lack of studies. TCCMD versus digital non-targeted communication No studies reported behavioural, health, or well-being outcomes for this comparison. For use of health services, there are uncertain effects for the presence of a skilled attendant at birth due to very low-certainty evidence, and the intervention may make little or no difference to attendance for antenatal influenza vaccination (RR 1.05, 95% CI 0.71 to 1.58), though the CI encompasses both benefit and harm (low-certainty evidence). Pregnant and postpartum women living with HIV TCCMD versus standard care For behaviours, TCCMD may make little or no difference to maternal and infant adherence to antiretroviral (ARV) therapy (low-certainty evidence). For health service use, TCC mobile telephone reminders may increase use of antenatal care slightly (mean difference (MD) 1.5, 95% CI -0.36 to 3.36; low-certainty evidence). The effect on the proportion of births occurring in a health facility is uncertain due to very low-certainty evidence. For health and well-being outcomes, there was an uncertain intervention effect on neonatal death or stillbirth, and infant HIV due to very low-certainty evidence. No studies reported on maternal mortality or morbidity. TCCMD versus non-digital TCC The effect is unknown due to lack of studies reporting this comparison. TCCMD versus digital non-targeted communication TCCMD may increase infant ARV/prevention of mother-to-child transmission treatment adherence (RR 1.26, 95% CI 1.07 to 1.48; low-certainty evidence). The effect on other outcomes is unknown due to lack of studies. Parents of children aged less than five years No studies reported on correct treatment, nutritional, or health outcomes. TCCMD versus standard care Based on 10 trials, TCCMD may modestly increase health service use (vaccinations and HIV care) (RR 1.21, 95% CI 1.08 to 1.34; low-certainty evidence); however, the effect estimates varied widely between studies. TCCMD versus non-digital TCC TCCMD may increase attendance for vaccinations (RR 1.13, 95% CI 1.00 to 1.28; low-certainty evidence), and may make little or no difference to oral hygiene practices (low-certainty evidence). TCCMD versus digital non-targeted communication TCCMD may reduce attendance for vaccinations, but the CI encompasses both benefit and harm (RR 0.63, 95% CI 0.33 to 1.20; low-certainty evidence). No trials in any population reported data on unintended consequences. The effect of TCCMD for most outcomes is uncertain. There may be improvements for some outcomes using targeted communication but these findings were of low certainty. High-quality, adequately powered trials and cost-effectiveness analyses are required to reliably ascertain the effects and relative benefits of TCCMD. Future studies should measure potential unintended consequences, such as partner violence or breaches of confidentiality.

Palmer MJ ，Henschke N ，Bergman H ，Villanueva G ，Maayan N ，Tamrat T ，Mehl GL ，Glenton C ，Lewin S ，Fønhus MS ，Free C ... -  《Cochrane Database of Systematic Reviews》