Electronic clinical decision algorithms for the integrated primary care management of febrile children in low-resource settings: review of existing tools

Point-of-care diagnostics for infection and antimicrobial resistance in sub-Saharan Africa: A narrative review

OBJECTIVES

Sub-Saharan African (SSA) countries are severely impacted by antimicrobial resistance (AMR). Due to gaps in access to diagnostics in SSA, the true extent of AMR remains unknown. This diagnostic gap affects patient management and leads to significant antimicrobial overuse. This review explores how point-of-care (POC) testing for pathogen identification and AMR may be used to close the diagnostic gap in SSA countries.

METHODS

A narrative review exploring current clinical practice and novel developments in the field of POC testing for infectious diseases and AMR.

RESULTS

POC assays for identification of various pathogens have been successfully rolled out in SSA countries. While implementation studies have mostly highlighted impressive test performance of POC assays, there is limited data on the impact of implementation on clinical outcomes and cost-effectiveness. We did not encounter local studies of host-directed POC assays relevant to AMR. Novel POC assays using real-time polymerase chain reaction, isothermal amplification, microfluidics, and other technologies are in various stages of development.

CONCLUSIONS

Available literature shows that POC testing for AMR applications is implementable in SSA and holds the potential to reduce the diagnostic gap. Implementation will require effective regulatory pathways, incorporation of POC testing in clinical and laboratory guidelines, and adequate value capture in existing health financing models.

Electronic Integrated Management of Childhood Illness (eIMCI): a randomized controlled trial to evaluate an electronic clinical decision-making support system for management of sick children in primary health care facilities in South Africa

BACKGROUND

Electronic clinical decision-making support systems (eCDSS) aim to assist clinicians making complex patient management decisions and improve adherence to evidence-based guidelines. Integrated management of Childhood Illness (IMCI) provides guidelines for management of sick children attending primary health care clinics and is widely implemented globally. An electronic version of IMCI (eIMCI) was developed in South Africa.

METHODS

We conducted a cluster randomized controlled trial comparing management of sick children with eIMCI to the management when using paper-based IMCI (pIMCI) in one district in KwaZulu-Natal. From 31 clinics in the district, 15 were randomly assigned to intervention (eIMCI) or control (pIMCI) groups. Computers were deployed in eIMCI clinics, and one IMCI trained nurse was randomly selected to participate from each clinic. eIMCI participants received a one-day computer training, and all participants received a similar three-day IMCI update and two mentoring visits. A quantitative survey was conducted among mothers and sick children attending participating clinics to assess the quality of care provided by IMCI practitioners. Sick child assessments by participants in eIMCI and pIMCI groups were compared to assessment by an IMCI expert.

RESULTS

Self-reported computer skills were poor among all nurse participants. IMCI knowledge was similar in both groups. Among 291 enrolled children: 152 were in the eIMCI group; 139 in the pIMCI group. The mean number of enrolled children was 9.7 per clinic (range 7-12). IMCI implementation was sub-optimal in both eIMCI and pIMCI groups. eIMCI consultations took longer than pIMCI consultations (median duration 28 minutes vs 25 minutes; p = 0.02). eIMCI participants were less likely than pIMCI participants to correctly classify children for presenting symptoms, but were more likely to correctly classify for screening conditions, particularly malnutrition. eIMCI participants were less likely to provide all required medications (124/152; 81.6% vs 126/139; 91.6%, p= 0.026), and more likely to prescribe unnecessary medication (48/152; 31.6% vs 20/139; 14.4%, p = 0.004) compared to pIMCI participants.

CONCLUSIONS

Implementation of eIMCI failed to improve management of sick children, with poor IMCI implementation in both groups. Further research is needed to understand barriers to comprehensive implementation of both pIMCI and eIMCI. (349) CLINICAL TRIALS REGISTRATION: Clinicaltrials.gov ID: BFC157/19, August 2019.

Evaluation of three protocols for direct susceptibility testing for gram negative-Enterobacteriaceae from patient samples in Uganda with SMS reporting

In Uganda, the challenge of generating and timely reporting essential antimicrobial resistance (AMR) data has led to overreliance on empirical antibiotic therapy, exacerbating the AMR crisis. To address this issue, this study aimed to adapt a one-step AMR testing protocol alongside an SMS (Short Message Service) result relay system (SRRS), with the potential to reduce the turnaround time for AMR testing and result communication from 4 days or more to 1 day in Ugandan clinical microbiology laboratories. Out of the 377 samples examined, 54 isolates were obtained. Notably, E. coli (61%) and K. pneumoniae (33%) were the most frequently identified, majority testing positive for ESBL. Evaluation of three AMR testing protocols revealed varying sensitivity and specificity, with Protocol A (ChromID ESBL-based) demonstrating high sensitivity (100%) but no calculable specificity, Protocol B (ceftazidime-based) showing high sensitivity (100%) and relatively low specificity (7.1%), and Protocol C (cefotaxime-based) exhibiting high sensitivity (97.8%) but no calculable specificity. ESBL positivity strongly correlated with resistance to specific antibiotics, including cefotaxime, ampicillin, and aztreonam (100%), cefuroxime (96%), ceftriaxone (93%), and trimethoprim sulfamethoxazole (87%). The potential of integrating an SRRS underscored the crucial role this could have in enabling efficient healthcare communication in AMR management. This study underscores the substantial potential of the tested protocols for accurately detecting ESBL production in clinical samples, potentially, providing a critical foundation for predicting and reporting AMR patterns. Although considerations related to specificity warrant careful assessment before widespread clinical adoption.

A digital health algorithm to guide antibiotic prescription in pediatric outpatient care: a cluster randomized controlled trial

Excessive antibiotic use and antimicrobial resistance are major global public health threats. We developed ePOCT+, a digital clinical decision support algorithm in combination with C-reactive protein test, hemoglobin test, pulse oximeter and mentorship, to guide health-care providers in managing acutely sick children under 15 years old. To evaluate the impact of ePOCT+ compared to usual care, we conducted a cluster randomized controlled trial in Tanzanian primary care facilities. Over 11 months, 23,593 consultations were included from 20 ePOCT+ health facilities and 20,713 from 20 usual care facilities. The use of ePOCT+ in intervention facilities resulted in a reduction in the coprimary outcome of antibiotic prescription compared to usual care (23.2% versus 70.1%, adjusted difference -46.4%, 95% confidence interval (CI) -57.6 to -35.2). The coprimary outcome of day 7 clinical failure was noninferior in ePOCT+ facilities compared to usual care facilities (adjusted relative risk 0.97, 95% CI 0.85 to 1.10). There was no difference in the secondary safety outcomes of death and nonreferred secondary hospitalizations by day 7. Using ePOCT+ could help address the urgent problem of antimicrobial resistance by safely reducing antibiotic prescribing. Clinicaltrials.gov Identifier: NCT05144763.

A Community-Based, Mobile Electronic Medical Record System App for High-Quality, Integrated Antiretroviral Therapy in Lilongwe, Malawi: Design Process and Pilot Implementation

BACKGROUND

Differentiated service delivery (DSD) increases antiretroviral therapy (ART) access in sub-Saharan Africa by moving clients out of congested ART clinics to communities for care. However, DSD settings challenge provider adherence to complex, chronic care treatment guidelines and have burdensome systems for client monitoring and evaluation (M&E), reducing data for decision-making. Electronic medical record systems (EMRS) improve client outcomes and reduce M&E workload. Traditional EMRS cannot operate in most DSD settings with unreliable power and poor connectivity.

OBJECTIVE

This study aims to detail the human-centered design (HCD) process of developing a mobile EMRS for community-based DSD services in Lilongwe, Malawi.

METHODS

Lighthouse Trust (LT) operates 2 Ministry of Health (MoH) clinics in Lilongwe, Malawi, with a combined total of >35,000 ART clients. LT's real-time, point-of-care EMRS collects complex client M&E data and provides decision-making support, ensuring adherence to integrated HIV and tuberculosis guidelines that optimize client and program outcomes. LT's EMRS scaled to all large MoH ART clinics. LT also implements a nurse-led community-based ART program (NCAP), a DSD model to provide ART and rapid assessment for 2400 stable LT clients in the community. LT, alongside collaborators, from the University of Washington's International Training and Education Center for Health and technology partner, Medic, used the open-source Community Health Toolkit (CHT) and HCD to develop an open-source, offline-first, mobile EMRS-like app, "community-based ART retention and suppression" (CARES). CARES aims to bring EMRS-like provider benefits to NCAP's DSD clients.

RESULTS

CARES design took approximately 12 months and used an iterative process of highly participatory feedback sessions with provider, data manager, and M&E team inputs to ensure CARES optimization for the NCAP and LT settings. The CARES mobile EMRS prototype supports NCAP providers with embedded prompts and alerts to ensure adherence to integrated MoH ART guidelines, aiming to improve the quality of client care. CARES facilitates improved data quality and flow for NCAP M&E, aiming to reduce data gaps between community and clinic settings. The CARES pilot demonstrates the potential of a mobile, point-of-care EMRS-like app that could benefit NCAP clients, providers, and program teams with integrated client care and complete M&E data for decision-making. CARES challenges include app speed, search features to align longitudinal records, and CARES to EMRS integration that supports timely care alerts.

CONCLUSIONS

Leveraging the CHT and HCD processes facilitated the design of a locally specified and optimized mobile app with the promise to bring EMRS-like benefits to DSD settings. Moving from the CARES prototype to routine NCAP implementation should result in improved client care and strengthened M&E while reducing workload. Our transparent and descriptive process shares the progress and pitfalls of the CARES design and development, helping others in this digital innovation area to learn from our experiences at this stage.

Antimicrobial stewardship in primary health care programs in humanitarian settings: the time to act is now

Fragile and conflict-affected settings bear a disproportionate burden of antimicrobial resistance, due to the compounding effects of weak health policies, disrupted medical supply chains, and lack of knowledge and awareness about antibiotic stewardship both among health care providers and health service users. Until now, humanitarian organizations intervening in these contexts have confronted the threat of complex multidrug resistant infections mainly in their surgical projects at the secondary and tertiary levels of care, but there has been limited focus on ensuring the implementation of adequate antimicrobial stewardship in primary health care, which is known to be setting where the highest proportion of antibiotics are prescribed. In this paper, we present the experience of two humanitarian organizations, Médecins sans Frontières and the International Committee of the Red Cross, in responding to antimicrobial resistance in their medical interventions, and we draw from their experience to formulate practical recommendations to include antimicrobial stewardship among the standards of primary health care service delivery in conflict settings. We believe that expanding the focus of humanitarian interventions in unstable and fragile contexts to include antimicrobial stewardship in primary care will strengthen the global response to antimicrobial resistance and will decrease its burden where it is posing the highest toll in terms of mortality.

Digitalizing Clinical Guidelines: Experiences in the Development of Clinical Decision Support Algorithms for Management of Childhood Illness in Resource-Constrained Settings

Clinical decision support systems (CDSSs) can strengthen the quality of integrated management of childhood illness (IMCI) in resource-constrained settings. Several IMCI-related CDSSs have been developed and implemented in recent years. Yet, despite having a shared starting point, the IMCI-related CDSSs are markedly varied due to the need for interpretation when translating narrative guidelines into decision logic combined with considerations of context and design choices. Between October 2019 and April 2021, we conducted a comparative analysis of 4 IMCI-related CDSSs. The extent of adaptations to IMCI varied, but common themes emerged. Scope was extended to cover a broader range of conditions. Content was added or modified to enhance precision, align with new evidence, and support rational resource use. Structure was modified to increase efficiency, improve usability, and prioritize care for severely ill children. The multistakeholder development processes involved syntheses of recommendations from existing guidelines and literature; creation and validation of clinical algorithms; and iterative development, implementation, and evaluation. The common themes surrounding adaptations of IMCI guidance highlight the complexities of digitalizing evidence-based recommendations and reinforce the rationale for leveraging standards for CDSS development, such as the World Health Organization's SMART Guidelines. Implementation through multistakeholder dialogue is critical to ensure CDSSs can effectively and equitably improve quality of care for children in resource-constrained settings.

ePOCT+ and the medAL-suite: Development of an electronic clinical decision support algorithm and digital platform for pediatric outpatients in low- and middle-income countries

Electronic clinical decision support algorithms (CDSAs) have been developed to address high childhood mortality and inappropriate antibiotic prescription by helping clinicians adhere to guidelines. Previously identified challenges of CDSAs include their limited scope, usability, and outdated clinical content. To address these challenges we developed ePOCT+, a CDSA for the care of pediatric outpatients in low- and middle-income settings, and the medical algorithm suite (medAL-suite), a software for the creation and execution of CDSAs. Following the principles of digital development, we aim to describe the process and lessons learnt from the development of ePOCT+ and the medAL-suite. In particular, this work outlines the systematic integrative development process in the design and implementation of these tools required to meet the needs of clinicians to improve uptake and quality of care. We considered the feasibility, acceptability and reliability of clinical signs and symptoms, as well as the diagnostic and prognostic performance of predictors. To assure clinical validity, and appropriateness for the country of implementation the algorithm underwent numerous reviews by clinical experts and health authorities from the implementing countries. The digitalization process involved the creation of medAL-creator, a digital platform which allows clinicians without IT programming skills to easily create the algorithms, and medAL-reader the mobile health (mHealth) application used by clinicians during the consultation. Extensive feasibility tests were done with feedback from end-users of multiple countries to improve the clinical algorithm and medAL-reader software. We hope that the development framework used for developing ePOCT+ will help support the development of other CDSAs, and that the open-source medAL-suite will enable others to easily and independently implement them. Further clinical validation studies are underway in Tanzania, Rwanda, Kenya, Senegal, and India.

Challenges of using e-health technologies to support clinical care in rural Africa: a longitudinal mixed methods study exploring primary health care nurses' experiences of using an electronic clinical decision support system (CDSS) in South Africa

BACKGROUND

Electronic decision-making support systems (CDSSs) can support clinicians to make evidence-based, rational clinical decisions about patient management and have been effectively implemented in high-income settings. Integrated Management of Childhood Illness (IMCI) uses clinical algorithms to provide guidelines for management of sick children in primary health care clinics and is widely implemented in low income countries. A CDSS based on IMCI (eIMCI) was developed in South Africa.

METHODS

We undertook a mixed methods study to prospectively explore experiences of implementation from the perspective of newly-trained eIMCI practitioners. eIMCI uptake was monitored throughout implementation. In-depth interviews (IDIs) were conducted with selected participants before and after training, after mentoring, and after 6 months implementation. Participants were then invited to participate in focus group discussions (FGDs) to provide further insights into barriers to eIMCI implementation.

RESULTS

We conducted 36 IDIs with 9 participants between October 2020 and May 2021, and three FGDs with 11 participants in October 2021. Most participants spoke positively about eIMCI reporting that it was well received in the clinics, was simple to use, and improved the quality of clinical assessments. However, uptake of eIMCI across participating clinics was poor. Challenges reported included lack of computer skills which made simple tasks, like logging in or entering patient details, time consuming. Technical support was provided, but was time consuming to access so that eIMCI was sometimes unavailable. Other challenges included heavy workloads, and the perception that eIMCI took longer and disrupted participant's work. Poor alignment between recording requirements of eIMCI and other clinic programmes increased participant's administrative workload. All these factors were a disincentive to eIMCI uptake, frequently leading participants to revert to paper IMCI which was quicker and where they felt more confident.

CONCLUSION

Despite the potential of CDSSs to increase adherence to guidelines and improve clinical management and prescribing practices in resource constrained settings where clinical support is scarce, they have not been widely implemented. Careful attention should be paid to the work environment, work flow and skills of health workers prior to implementation, and ongoing health system support is required if health workers are to adopt these approaches (350).

Using the Implementation Research Logic Model to design and implement community-based management of possible serious bacterial infection during COVID-19 pandemic in Ethiopia

BACKGROUND

Community-based treatment of possible serious bacterial infection (PSBI) in young infants, when referral to a hospital is not possible, can result in high treatment coverage and low case fatality. However, in Ethiopia, the coverage of PSBI treatment remains low, worsened by COVID-19. To understand the challenges of delivery of PSBI treatment and design and test adaptative strategies to mitigate the impact of COVID-19 on neonatal mortality, we did implementation research (IR) employing Implementation Research Logic Model (IRLM). In this paper, we describe IRLM application experiences in designing, implementing, and evaluating strategies to improve community-based treatment of PSBI during the COVID-19 pandemic in Ethiopia.

METHODS

This IR was conducted between November 2020-April 2022 at Dembecha and Lume woredas of Amhara and Oromia regions, respectively. We employed narrative reviews, formative assessment and facilitated stakeholder engagement to develop the PSBI treatment IRLM to identify barriers, understand the conceptual linkages among determinants, choose implementation strategies, elicit mechanisms, and link to implementation outcomes. In addition, we used the IRLM to structure the capture of emerging implementation challenges and resulting strategy adaptations throughout implementation.

RESULTS

This IR identified COVID-19 and multiple pre-existing contextual factors. We designed and implemented implementation strategies to address these challenges. These adaptive strategies were implemented with sufficient strength to maintain the delivery of PSBI services and improve mothers' care-seeking behavior for their sick young infants. The IRLM offers us a clear process and path to prioritize implementation challenges, choose strategies informed by mechanisms of action, and where the adaptive implementation of community-based management of PSBI would lead to high-implementation fidelity and change in mother behavior to seek care for their sick young infants. The IRLM was also an effective tool for stakeholder engagement, easily explained and used to structure discussion and decision-making during co-design meetings.

CONCLUSIONS

The use of the IRLM helps us to specify the conceptual links between the implementation challenges, strategies, mechanisms of action, and outcomes to explore the complex community-based management of PSBI during complex contexts to improve high-fidelity implementation and integration of PSBI treatment in the primary healthcare delivery systems through active engagement of stakeholders.

A Systematic Review of Applications of Machine Learning and Other Soft Computing Techniques for the Diagnosis of Tropical Diseases

This systematic literature aims to identify soft computing techniques currently utilized in diagnosing tropical febrile diseases and explore the data characteristics and features used for diagnoses, algorithm accuracy, and the limitations of current studies. The goal of this study is therefore centralized around determining the extent to which soft computing techniques have positively impacted the quality of physician care and their effectiveness in tropical disease diagnosis. The study has used PRISMA guidelines to identify paper selection and inclusion/exclusion criteria. It was determined that the highest frequency of articles utilized ensemble techniques for classification, prediction, analysis, diagnosis, etc., over single machine learning techniques, followed by neural networks. The results identified dengue fever as the most studied disease, followed by malaria and tuberculosis. It was also revealed that accuracy was the most common metric utilized to evaluate the predictive capability of a classification mode. The information presented within these studies benefits frontline healthcare workers who could depend on soft computing techniques for accurate diagnoses of tropical diseases. Although our research shows an increasing interest in using machine learning techniques for diagnosing tropical diseases, there still needs to be more studies. Hence, recommendations and directions for future research are proposed.

Effectiveness of an electronic clinical decision support system in improving the management of childhood illness in primary care in rural Nigeria: an observational study

OBJECTIVES

To evaluate the impact of ALgorithm for the MANAgement of CHildhood illness ('ALMANACH'), a digital clinical decision support system (CDSS) based on the Integrated Management of Childhood Illness, on health and quality of care outcomes for sick children attending primary healthcare (PHC) facilities.

DESIGN

Observational study, comparing outcomes of children attending facilities implementing ALMANACH with control facilities not yet implementing ALMANACH.

SETTING

PHC facilities in Adamawa State, North-Eastern Nigeria.

PARTICIPANTS

Children 2-59 months presenting with an acute illness. Children attending for routine care or nutrition visits (eg, immunisation, growth monitoring), physical trauma or mental health problems were excluded.

INTERVENTIONS

The ALMANACH intervention package (CDSS implementation with training, mentorship and data feedback) was rolled out across Adamawa's PHC facilities by the Adamawa State Primary Health Care Development Agency, in partnership with the International Committee of the Red Cross and the Swiss Tropical and Public Health Institute. Tablets were donated, but no additional support or incentives were provided. Intervention and control facilities received supportive supervision based on the national supervision protocol.

PRIMARY AND SECONDARY OUTCOME MEASURES

The primary outcome was caregiver-reported recovery at day 7, collected over the phone. Secondary outcomes were antibiotic and antimalarial prescription, referral, and communication of diagnosis and follow-up advice, assessed at day 0 exit interview.

RESULTS

We recruited 1929 children, of which 1021 (53%) attended ALMANACH facilities, between March and September 2020. Caregiver-reported recovery was significantly higher among children attending ALMANACH facilities (adjusted OR=2·63, 95% CI 1·60 to 4·32). We observed higher parenteral and lower oral antimicrobial prescription rates (adjusted OR=2·42 (1·00 to 5·85) and adjusted OR=0·40 (0·22 to 0·73), respectively) in ALMANACH facilities as well as markedly higher rates for referral, communication of diagnosis, and follow-up advice.

CONCLUSION

Implementation of digital CDSS with training, mentorship and feedback in primary care can improve quality of care and recovery of sick children in resource-constrained settings, likely mediated by better guideline adherence. These findings support the use of CDSS for health systems strengthening to progress towards universal health coverage.

The feasibility and ongoing use of electronic decision support to strengthen the implementation of IMCI in KwaZulu-Natal, South Africa

Background

Continued efforts are required to reduce preventable child deaths. User-friendly Integrated Management of Childhood Illness (IMCI) implementation tools and supervision systems are needed to strengthen the quality of child health services in South Africa. A 2018 pilot implementation of electronic IMCI case management algorithms in KwaZulu-Natal demonstrated good uptake and acceptance at primary care clinics. We aimed to investigate whether ongoing electronic IMCI implementation is feasible within the existing Department of Health infrastructure and resources.

Methods

In a mixed methods descriptive study, the electronic IMCI (eIMCI) implementation was extended to 22 health facilities in uMgungundlovu district from November 2019 to February 2021. Training, mentoring, supervision and IT support were provided by a dedicated project team. Programme use was tracked, quarterly assessments of the service delivery platform were undertaken and in-depth interviews were conducted with facility managers.

Results

From December 2019 – January 2021, 9 684 eIMCI records were completed across 20 facilities, with a median uptake of 29 records per clinic per month and a mean (range) proportion of child consultations using eIMCI of 15% (1–46%). The local COVID-19-related movement restrictions and epidemic peaks coincided with declines in the monthly eIMCI uptake. Substantial inter- and intra-facility variations in use were observed, with the use being positively associated with the allocation of an eIMCI trained nurse (p < 0.001) and the clinician workload (p = 0.032).

Conclusion

The ongoing eIMCI uptake was sporadic and the implementation undermined by barriers such as low post-training deployment of nurses; poor capacity in the DoH for IT support; and COVID-19-related disruptions in service delivery. Scaling eIMCI in South Africa would rely on resolving these challenges.

Effect of mobile application user interface improvements on minimum expected home visit coverage by community health workers in Mali: a randomised controlled trial

BACKGROUND

Proactive community case management (ProCCM) has shown promise to advance goals of universal health coverage (UHC). ProCCM community health workers (CHWs) face operational challenges when pursuing their goal of visiting every household in their service area at least twice monthly to proactively find sick patients. We developed a software extension (UHC Mode) to an existing CHW mobile application featuring user interface design improvements to support CHWs in planning daily home visits. We evaluated the effect of UHC Mode on minimum expected home visit coverage.

METHODS

We conducted a parallel-group, two-arm randomised controlled trial of ProCCM CHWs in two separate regions in Mali. CHWs were randomly assigned to UHC Mode or the standard mobile application (control) with a 1:1 allocation. Randomisation was stratified by health catchment area. CHWs and other programme personnel were not masked to arm allocation. CHWs used their assigned intervention for 4 months. Using a difference-in-differences analysis, we estimated the mean change in minimum expected home visit coverage from preintervention to postintervention between arms.

RESULTS

Enrolment occurred in January 2019. Of 199 eligible CHWs randomised to the intervention or control arm, 196 were enrolled and 195 were included in the analysis. Households whose CHW used UHC Mode had 2.41 times higher odds of minimum expected home visit coverage compared with households whose CHW used the control (95% CI 1.68 to 3.47; p<0.0005). Minimum expected home visit coverage in the UHC Mode arm increased 13.6 percentage points (95% CI 8.1 to 19.0) compared with the control arm.

CONCLUSION

Our findings suggest UHC Mode is an effective tool that can improve home visit coverage and promote progress towards UHC when implemented in the ProCCM context. User interface design of health information systems that supports health workers' daily practices and meets their requirements can have a positive impact on health worker performance and home visit coverage.

TRIAL REGISTRATION NUMBER

NCT04106921.

Anticipating the future: prognostic tools as a complementary strategy to improve care for patients with febrile illnesses in resource-limited settings

In low-income and middle-income countries, most patients with febrile illnesses present to peripheral levels of the health system where diagnostic capacity is very limited. In these contexts, accurate risk stratification can be particularly impactful, helping to guide allocation of scarce resources to ensure timely and tailored care. However, reporting of prognostic research is often imprecise and few prognostic tests or algorithms are translated into clinical practice.

Here, we review the often-conflated concepts of prognosis and diagnosis, with a focus on patients with febrile illnesses. Drawing on a recent global stakeholder consultation, we apply these concepts to propose three use-cases for prognostic tools in the management of febrile illnesses in resource-limited settings: (1) guiding referrals from the community to higher-level care; (2) informing resource allocation for patients admitted to hospital and (3) identifying patients who may benefit from closer follow-up post-hospital discharge. We explore the practical implications for new technologies and reflect on the challenges and knowledge gaps that must be addressed before this approach could be incorporated into routine care settings.

Our intention is that these use-cases, alongside other recent initiatives, will help to promote a harmonised yet contextualised approach for prognostic research in febrile illness. We argue that this is especially important given the heterogeneous settings in which care is often provided for patients with febrile illnesses living in low-income and middle-income countries.

Health workers' perspectives of a mobile health tool to improve diagnosis and management of paediatric acute respiratory illnesses in Uganda: a qualitative study

OBJECTIVES

Mobile health tools have potential to improve the diagnosis and management of acute lower respiratory illnesses (ALRI), a leading cause of paediatric mortality worldwide. The objectives were to evaluate health workers' perceptions of acceptability, usability and feasibility of Acute Lower Respiratory Illness Treatment and Evaluation (ALRITE), a novel mobile health tool to help frontline health workers diagnose, treat and provide education about ALRI in children <5 years.

DESIGN

A qualitative study including semistructured interviews with health facility administrators and focus groups with primary care health workers.

SETTING

Two federally funded Ugandan primary care health facilities, one peri-urban and one rural.

PARTICIPANTS

We enrolled 3 health administrators and 28 health workers (clinical officers and nurses).

INTERVENTION

The ALRITE smartphone application was developed to help frontline health workers adhere to ALRI guidelines and differentiate wheezing illnesses from pneumonia in children under 5 years of age. ALRITE contains a simple decision tree, a partially automated respiratory rate counter, educational videos and an adapted respiratory assessment score to determine bronchodilator responsiveness. We performed a demonstration of ALRITE for participants at the beginning of interviews and focus groups. No participant had used ALRITE prior.

RESULTS

Themes impacting the potential implementation of ALRITE were organised using individual-level, clinic-level and health-system level determinants. Individual-level determinants were acceptability and perceived benefit, usability, provider needs and provider-patient relationship. Clinic-level determinants were limited resources and integration within the health centre. Systems-level determinants included medication shortages and stakeholder engagement.

CONCLUSIONS

Incorporation of these themes will ready ALRITE for field testing. Early engagement of end users provides insights critical to the development of tailored mHealth decision support tools.

Bayesian network models with decision tree analysis for management of childhood malaria in Malawi

BACKGROUND

Malaria is a major cause of death in children under five years old in low- and middle-income countries such as Malawi. Accurate diagnosis and management of malaria can help reduce the global burden of childhood morbidity and mortality. Trained healthcare workers in rural health centers manage malaria with limited supplies of malarial diagnostic tests and drugs for treatment. A clinical decision support system that integrates predictive models to provide an accurate prediction of malaria based on clinical features could aid healthcare workers in the judicious use of testing and treatment. We developed Bayesian network (BN) models to predict the probability of malaria from clinical features and an illustrative decision tree to model the decision to use or not use a malaria rapid diagnostic test (mRDT).

METHODS

We developed two BN models to predict malaria from a dataset of outpatient encounters of children in Malawi. The first BN model was created manually with expert knowledge, and the second model was derived using an automated method. The performance of the BN models was compared to other statistical models on a range of performance metrics at multiple thresholds. We developed a decision tree that integrates predictions with the costs of mRDT and a course of recommended treatment.

RESULTS

The manually created BN model achieved an area under the ROC curve (AUC) equal to 0.60 which was statistically significantly higher than the other models. At the optimal threshold for classification, the manual BN model had sensitivity and specificity of 0.74 and 0.42 respectively, and the automated BN model had sensitivity and specificity of 0.45 and 0.68 respectively. The balanced accuracy values were similar across all the models. Sensitivity analysis of the decision tree showed that for values of probability of malaria below 0.04 and above 0.40, the preferred decision that minimizes expected costs is not to perform mRDT.

CONCLUSION

In resource-constrained settings, judicious use of mRDT is important. Predictive models in combination with decision analysis can provide personalized guidance on when to use mRDT in the management of childhood malaria. BN models can be efficiently derived from data to support clinical decision making.

Adherence to standard treatment guidelines among prescribers in primary healthcare facilities in the Dodoma region of Tanzania

Background

Tanzania’s primary healthcare system suffers from a scarcity of financial and human resources that impedes its effectiveness to deliver dependable and uniform quality healthcare. Adherence to standard treatment guidelines (STG) can help provide more consistent and correct diagnoses and treatments and limit the irrational use of medicines and the negative health consequences that can occur as a result. The purpose of this study was to investigate prescribers’ adherence of their diagnoses and respective treatments to national STG and to identify potential areas for planning interventions.

Methods

A cross-sectional study on prescribers’ adherence to diagnosis and treatment, according to national STG, was conducted in 2012 in public primary healthcare facilities (HCF) in the Dodoma region of Tanzania. Information on 2886 patients was collected, prospectively and retrospectively, from 120 HCF across the Dodoma region using a structured questionnaire. Twenty-five broadly defined main illness groups were recorded and the nine most prevalent and relevant conditions were statistically analysed in detail.

Results

Diagnoses and related treatments were recorded and analysed in 2872 cases. The nine most prevalent conditions were upper respiratory tract infections (25%), malaria (18%), diarrhoea (9.9%), pneumonia (6.1%), skin problems (5.8%), gastrointestinal diagnoses (5%), urinary tract infections (4%), worm infestations (3.6%) and eye problems (2.1%). Only 1.8% of all diagnoses were non-communicable diseases. The proportion of prescribers’ primary diagnoses that completely adhered to national STG was 599 (29.9%), those that partially adhered totalled 775 (38.7%), wrong medication was given in 621 cases (30.9%) and no diagnosis or medication was given in nine cases (0.5%). Sixty-one percent of all patients received an antibiotic regardless of the diagnoses. Complete adherence was highest when worms were diagnosed and lowest for diarrhoea. The proportion of cases that did not adhere to STG was highest with patients with skin problems and lowest for malaria.

Conclusion

Prescribers’ general adherence to national STG in primary HCF in the public sector in Dodoma region is sub-optimal. The reasons are multifaceted and focused attention, directed at improving prescribing and pharmacotherapy, is required with a view of improving patient care and health outcomes.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12913-021-06257-y.

Prediction of disease severity in young children presenting with acute febrile illness in resource-limited settings: a protocol for a prospective observational study

INTRODUCTION

In rural and difficult-to-access settings, early and accurate recognition of febrile children at risk of progressing to serious illness could contribute to improved patient outcomes and better resource allocation. This study aims to develop a prognostic clinical prediction tool to assist community healthcare providers identify febrile children who might benefit from referral or admission for facility-based medical care.

METHODS AND ANALYSIS

This prospective observational study will recruit at least 4900 paediatric inpatients and outpatients under the age of 5 years presenting with an acute febrile illness to seven hospitals in six countries across Asia. A venous blood sample and nasopharyngeal swab is collected from each participant and detailed clinical data recorded at presentation, and each day for the first 48 hours of admission for inpatients. Multianalyte assays are performed at reference laboratories to measure a panel of host biomarkers, as well as targeted aetiological investigations for common bacterial and viral pathogens. Clinical outcome is ascertained on day 2 and day 28.Presenting syndromes, clinical outcomes and aetiology of acute febrile illness will be described and compared across sites. Following the latest guidance in prediction model building, a prognostic clinical prediction model, combining simple clinical features and measurements of host biomarkers, will be derived and geographically externally validated. The performance of the model will be evaluated in specific presenting clinical syndromes and fever aetiologies.

ETHICS AND DISSEMINATION

The study has received approval from all relevant international, national and institutional ethics committees. Written informed consent is provided by the caretaker of all participants. Results will be shared with local and national stakeholders, and disseminated via peer-reviewed open-access journals and scientific meetings.

TRIAL REGISTRATION NUMBER

NCT04285021.

Prognostic Accuracy of Soluble Triggering Receptor Expressed on Myeloid Cells (sTREM-1)-based Algorithms in Febrile Adults Presenting to Tanzanian Outpatient Clinics

BACKGROUND

The inability to identify individuals with acute fever at risk of death is a barrier to effective triage and management of severe infections, especially in low-resource settings. Since endothelial and immune activation contribute to the pathogenesis of various distinct life-threatening infections, we hypothesized that measuring mediators of these pathways at clinical presentation would identify febrile adults at risk of death.

METHODS

Plasma concentrations of markers of endothelial (angiopoetin-1/2, soluble fms-like tyrosine kinase-1, soluble vascular cell adhesion molecule-1, soluble intercellular adhesion molecule-1) and immune (soluble triggering receptor expressed on myeloid cells [sTREM-1], interleukin-6, interleukin-8, chitinase-3-like protein-1, soluble tumor necrosis factor receptor-1, procalcitonin [PCT], C-reactive protein [CRP]) activation pathways were determined in consecutive adults with acute fever (≥38°C) at presentation to outpatient clinics in Dar es Salaam, Tanzania. We evaluated the accuracy of these mediators in predicting all-cause mortality and examined whether markers could improve the prognostic accuracy of clinical scoring systems, including the quick sequential organ failure assessment (qSOFA) and Glasgow coma scale (GCS).

RESULTS

Of 507 febrile adults, 32 died (6.3%) within 28 days of presentation. We found that sTREM-1 was the best prognostic marker for 28-day mortality (area under the receiver operating characteristic [AUROC] 0.87, 95% confidence interval [CI] 0.81-0.92) and was significantly better than CRP (P < .0001) and PCT (P = .0001). The prognostic accuracy of qSOFA and the GCS were significantly enhanced when sTREM-1 was added (0.80 [95% CI 0.76-0.83] to 0.91 [95% CI 0.88-0.94; P < .05] and 0.72 [95% CI 0.63-0.80] to 0.94 [95% CI 0.91-0.97; P < .05], respectively).

CONCLUSIONS

Measuring sTREM-1 at clinical presentation can identify febrile individuals at risk of all-cause febrile mortality. Adding severity markers such as sTREM-1 to simple clinical scores could improve the recognition and triage of patients with life-threatening infections in resource-limited settings.

Predictors of disease severity in children presenting from the community with febrile illnesses: a systematic review of prognostic studies

INTRODUCTION

Early identification of children at risk of severe febrile illness can optimise referral, admission and treatment decisions, particularly in resource-limited settings. We aimed to identify prognostic clinical and laboratory factors that predict progression to severe disease in febrile children presenting from the community.

METHODS

We systematically reviewed publications retrieved from MEDLINE, Web of Science and Embase between 31 May 1999 and 30 April 2020, supplemented by hand search of reference lists and consultation with an expert Technical Advisory Panel. Studies evaluating prognostic factors or clinical prediction models in children presenting from the community with febrile illnesses were eligible. The primary outcome was any objective measure of disease severity ascertained within 30 days of enrolment. We calculated unadjusted likelihood ratios (LRs) for comparison of prognostic factors, and compared clinical prediction models using the area under the receiver operating characteristic curves (AUROCs). Risk of bias and applicability of studies were assessed using the Prediction Model Risk of Bias Assessment Tool and the Quality In Prognosis Studies tool.

RESULTS

Of 5949 articles identified, 18 studies evaluating 200 prognostic factors and 25 clinical prediction models in 24 530 children were included. Heterogeneity between studies precluded formal meta-analysis. Malnutrition (positive LR range 1.56-11.13), hypoxia (2.10-8.11), altered consciousness (1.24-14.02), and markers of acidosis (1.36-7.71) and poor peripheral perfusion (1.78-17.38) were the most common predictors of severe disease. Clinical prediction model performance varied widely (AUROC range 0.49-0.97). Concerns regarding applicability were identified and most studies were at high risk of bias.

CONCLUSIONS

Few studies address this important public health question. We identified prognostic factors from a wide range of geographic contexts that can help clinicians assess febrile children at risk of progressing to severe disease. Multicentre studies that include outpatients are required to explore generalisability and develop data-driven tools to support patient prioritisation and triage at the community level.

PROSPERO REGISTRATION NUMBER

CRD42019140542.

Management of uncomplicated malaria among children under five years at public and private sector facilities in Mali

Background

Prompt and effective malaria diagnosis and treatment is a cornerstone of malaria control. Case management guidelines recommend confirmatory testing of suspected malaria cases, then prescription of specific drugs for uncomplicated malaria and for severe malaria. This study aims to describe case management practices for children aged 1–59 months seeking treatment with current or recent fever from public and private, rural and urban health providers in Mali.

Methods

Data were collected at sites in Sikasso Region and Bamako. Health workers recorded key information from the consultation including malaria diagnostic testing and result, their final diagnosis, and all drugs prescribed. Children with signs of severe diseases were ineligible. Consultations were not independently observed. Appropriate case management was defined as both 1) tested for malaria using rapid diagnostic test or microscopy, and 2) receiving artemisinin combination therapy (ACT) and no other antimalarials if test-positive, or receiving no antimalarials if test-negative.

Results

Of 1602 participating children, 23.7% were appropriately managed, ranging from 5.3% at public rural facilities to 48.4% at community health worker sites. The most common reason for ‘inappropriate’ management was lack of malaria diagnostic testing (50.4% of children). Among children with confirmed malaria, 50.8% received a non-ACT antimalarial (commonly artesunate injection or artemether), either alone or in combination with ACT. Of 215 test-negative children, 44.2% received an antimalarial drug, most commonly ACT. Prescription of multiple drugs was common: 21.7% of all children received more than one type of antimalarial, while 51.9% received an antibiotic and antimalarial. Inappropriate case management increased in children with increasing axillary temperatures and those seeking care over weekends.

Conclusions

Multiple limitations in management of febrile children under five were identified, including inconsistent use of confirmatory testing and apparent use of severe malaria drugs for uncomplicated malaria. While we cannot confirm the reasons for these shortcomings, there is a need to address the high use of non-ACT antimalarials in this context; to minimize potential for drug resistance, reduce unnecessary expense, and preserve life-saving treatment for severe malaria cases. These findings highlight the challenge of managing febrile illness in young children in a high transmission setting.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-020-09873-1.

End-user perspectives of two mHealth decision support tools: Electronic Community Case Management in Northern Malawi

BACKGROUND

The introduction of a paper-based Community Case Management (CCM) in Malawi has contributed to a reduction of child morbidity and mortality rates. In addition, the introduction of electronic Community Case Management (eCCM) (smartphones with built in CCM apps) may help to reduce the under-five mortality rates even further.

PURPOSE

It is not uncommon for Apps with a similar area of interest to develop different features to assist the end users. Such differences between Apps may have a significant role to play in its overall adoption and integration. The purpose of this research was to explore end users perspectives of two eCCM decision support tools developed and implemented by the Supporting LIFE project (SL eCCM App) and D-Tree International's (Mangologic eCCM App)in Northern Malawi.

METHODS

A mixed methods approach was applied, involving a survey of 109 users (106 Health Surveillance Assistants (HSAs), and 3 Integrated Management of Childhood Il6lnesses (IMCI) coordinators). This was followed up with semi-structured interviews with 34 respondents (31 HSAs, and 3 IMCI coordinators). Quantitative data was analyzed using SPSS version 20 where descriptive statistics and Chi-Squared tests were generated. Qualitative data were analyzed based on thematic analysis.

RESULTS

Participants reported that both Apps could assist the HSAs in the management of childhood illnesses. However, usability differed between the two apps where the Supporting LIFE eCCM App was found to be easier to use (61%) compared to the Mangologic eCCM App (4%). Both Apps were perceived to provide credible and accurate information.

CONCLUSION

It is essential that the quality of the data within Mobile Health (mHealth) Apps is high, however even Apps with excellent levels of data quality may not succeed if the overall usability of the App is low. Therefore it is essential that the Apps has high levels of data quality, usability and credibility. The results of this study will help inform mobile Health (mHealth) App designers in developing future eCCM Apps as well as researchers and policy makers when considering the adoption of mHealth solutions in the future in Malawi and other LMICs.

Acceptability and uptake of an electronic decision-making tool to support the implementation of IMCI in primary healthcare facilities in KwaZulu-Natal, South Africa

Background: Despite progress in reducing child mortality, preventable child deaths remain a challenge in South Africa. Poor implementation of Integrated Management of Childhood Illness (IMCI) guidelines has been well described, and the reported barriers to implementation include a lack of user-friendly implementation tools. Aim: To investigate whether an electronic decision support tool to strengthen IMCI implementation is acceptable to nurses, clinic managers and caregivers at primary care facilities in KwaZulu-Natal, South Africa. Methods: The electronic IMCI (eIMCI) software was tested in 15 health facilities in uMgungundlovu district from May to July 2018. System use was tracked and qualitative data obtained from three user groups. IMCI practitioners participated in questionnaires and focus groups, operational managers in in-depth interviews and caregivers in exit interviews. Results: Thirty-two IMCI practitioners, six operational managers and 30 caregivers were included. Acceptance was high among caregivers and operational managers, albeit less conclusive among IMCI practitioners whose eIMCI uptake indicated higher variability in acceptance than the qualitative reports. Despite suboptimal staff deployment after training and low baseline computer literacy levels, 3626 eIMCI records were captured across 12 sites over 14 weeks, with a median of 19 records per facility per week. Practitioners' indicators of self-efficacy improved significantly (p < 0.05) post-implementation compared to baseline. Seventy-six percent of caregivers reported a marked difference in experience compared to previous consultations, emphasising the comprehensiveness and efficiency of care. Conclusion: Uptake was promising and acceptance was good, with themes converging across participant groups to highlight improved comprehensiveness and efficiency of service. Limited computer literacy was the principal barrier to uptake. The next steps include incremental scale-up with stronger mentoring and supervision components and evaluations to assess the feasibility, effectiveness and cost-effectiveness of eIMCI implementation. Abbreviations: CDSS: clinical decision support system; CHCs: community health centres; DoH: Department of Health; eIMCI: electronic IMCI; eHealth: electronic health; EHR: electronic health records; ICT: information and communication technology; IMCI: Integrated Management of Childhood Illness; OM: operational managers; PHCs: primary healthcare clinics; SA: South Africa; SSA: sub-Saharan Africa.

Clinical relevance of low-density Plasmodium falciparum parasitemia in untreated febrile children: A cohort study

BACKGROUND

Low-density (LD) Plasmodium infections are missed by standard malaria rapid diagnostic tests (standard mRDT) when the blood antigen concentration is below the detection threshold. The clinical impact of these LD infections is unknown. This study investigates the clinical presentation and outcome of untreated febrile children with LD infections attending primary care facilities in a moderately endemic area of Tanzania.

METHODS/FINDINGS

This cohort study includes 2,801 febrile pediatric outpatients (median age 13.5 months [range 2-59], female:male ratio 0.8:1.0) recruited in Dar es Salaam, Tanzania between 01 December 2014 and 28 February 2016. Treatment decisions were guided by a clinical decision support algorithm run on a mobile app, which also collected clinical data. Only standard mRDT+ cases received antimalarials. Outcomes (clinical failure, secondary hospitalization, and death) were collected in follow-up visits or interviews on days 3, 7, and 28. After patient recruitment had ended, frozen blood from all 2,801 patients was tested for Plasmodium falciparum (Pf) by ultrasensitive-quantitative polymerase chain reaction (qPCR), standard mRDT, and "ultrasensitive" mRDT. As the latter did not improve sensitivity beyond standard mRDT, it is hereafter excluded. Clinical features and outcomes in LD patients (standard mRDT-/ultrasensitive-qPCR+, not given antimalarials) were compared with those with no detectable (ND) parasitemia (standard mRDT-/ultrasensitive-qPCR-) or high-density (HD) infections (standard mRDT+/ultrasensitive-qPCR+, antimalarial-treated). Pf positivity rate was 7.1% (n = 199/2,801) and 9.8% (n = 274/2,801) by standard mRDT and ultrasensitive qPCR, respectively. Thus, 28.0% (n = 76/274) of ultrasensitive qPCR+ cases were not detected by standard mRDT and labeled "LD". LD patients were, on average, 10.6 months younger than those with HD infections (95% CI 7.0-14.3 months, p < 0.001). Compared with ND, LD patients more frequently had the diagnosis of undifferentiated fever of presumed viral origin (risk ratio [RR] = 2.0, 95% CI 1.3-3.1, p = 0.003) and were more often suffering from severe malnutrition (RR = 3.2, 95% CI 1.1-7.5, p = 0.03). Despite not receiving antimalarials, outcomes for the LD group did not differ from ND regarding clinical failures (2.6% [n = 2/76] versus 4.0% [n = 101/2,527], RR = 0.7, 95% CI 0.2-3.5, p = 0.7) or secondary hospitalizations (2.6% [n = 2/76] versus 2.8% [n = 72/2,527], RR = 0.7,95% CI 0.2-3.2, p = 0.9), and no deaths were reported in any Pf-positive groups. HD patients experienced more secondary hospitalizations (10.1% [n = 20/198], RR = 0.3, 95% CI 0.1-1.0, p = 0.005) than LD patients. All the patients in this cohort were febrile children; thus, the association between parasitemia and fever cannot be investigated, nor can the conclusions be extrapolated to neonates and adults.

CONCLUSIONS

During a 28-day follow-up period, we did not find evidence of a difference in negative outcomes between febrile children with untreated LD Pf parasitemia and those without Pf parasitemia. These findings suggest LD parasitemia may either be a self-resolving fever or an incidental finding in children with other infections, including those of viral origin. These findings do not support a clinical benefit nor additional risk (e.g. because of missed bacterial infections) to using ultrasensitive malaria diagnostics at a primary care level.

The Promise of Clinical Decision Support Systems Targetting Low-Resource Settings

Low-resource clinical settings are plagued by low physician-to-patient ratios and a shortage of high-quality medical expertise and infrastructure. Together, these phenomena lead to over-burdened healthcare systems that under-serve the needs of the community. Alleviating this burden can be undertaken by the introduction of clinical decision support systems (CDSSs); systems that support stakeholders (ranging from physicians to patients) within the clinical setting in their day-to-day activities. Such systems, which have proven to be effective in the developed world, remain to be under-explored in low-resource settings. This review attempts to summarize the research focused on clinical decision support systems that either target stakeholders within low-resource clinical settings or diseases commonly found in such environments. When categorizing our findings according to disease applications, we find that CDSSs are predominantly focused on dealing with bacterial infections and maternal care, do not leverage deep learning, and have not been evaluated prospectively. Together, these highlight the need for increased research in this domain in order to impact a diverse set of medical conditions and ultimately improve patient outcomes.

Point-of-Care Biomarkers to Guide Antibiotic Prescription for Acute Febrile Illness in Sub-Saharan Africa: Promises and Caveats

Empiric malaria treatment in Sub-Saharan Africa has significantly decreased with the scaling-up of malaria rapid diagnostic tests; this coincided with a pronounced increase in empiric antibiotic prescriptions. In high-income countries, guidance for antibiotic prescriptions using biomarkers such as C-reactive protein (CRP) and procalcitonin (PCT) has reduced antibiotic use while safe-guarding patient safety. Importantly, several low-cost point-of-care CRP/PCT tests are currently available. However, only a few studies on the role of CRP/PCT in differentiating bacterial vs viral infections in acute febrile illness have been conducted in Sub-Saharan Africa. Studies from Central and West Africa (most of which is malaria-endemic) are particularly scarce, and only 1 has included adults. The evidence base for point-of-care use of CRP/PCT biomarkers in acute fever in Sub-Saharan Africa should be urgently built. Before engaging in clinical trials to assess clinical impact, pilot studies should be conducted to address key knowledge gaps including recommended CRP/PCT cutoff values and the effect of malaria coinfection.

Paving the Way for the Implementation of a Decision Support System for Antibiotic Prescribing in Primary Care in West Africa: Preimplementation and Co-Design Workshop With Physicians

Background

Suboptimal use of antibiotics is a driver of antimicrobial resistance (AMR). Clinical decision support systems (CDSS) can assist prescribers with rapid access to up-to-date information. In low- and middle-income countries (LMIC), the introduction of CDSS for antibiotic prescribing could have a measurable impact. However, interventions to implement them are challenging because of cultural and structural constraints, and their adoption and sustainability in routine clinical care are often limited. Preimplementation research is needed to ensure relevant adaptation and fit within the context of primary care in West Africa.

Objective

This study examined the requirements for a CDSS adapted to the context of primary care in West Africa, to analyze the barriers and facilitators of its implementation and adaptation, and to ensure co-designed solutions for its adaptation and sustainable use.

Methods

We organized a workshop in Burkina Faso in June 2019 with 47 health care professionals representing 9 West African countries and 6 medical specialties. The workshop began with a presentation of Antibioclic, a publicly funded CDSS for antibiotic prescribing in primary care that provides personalized antibiotic recommendations for 37 infectious diseases. Antibioclic is freely available on the web and as a smartphone app (iOS, Android). The presentation was followed by a roundtable discussion and completion of a questionnaire with open-ended questions by participants. Qualitative data were analyzed using thematic analysis.

Results

Most of the participants had access to a smartphone during their clinical consultations (35/47, 74%), but only 49% (23/47) had access to a computer and none used CDSS for antibiotic prescribing. The participants considered that CDSS could have a number of benefits including updating the knowledge of practitioners on antibiotic prescribing, improving clinical care and reducing AMR, encouraging the establishment of national guidelines, and developing surveillance capabilities in primary care. The most frequently mentioned contextual barrier to implementing a CDSS was the potential risk of increasing self-medication in West Africa, where antibiotics can be bought without a prescription. The need for the CDSS to be tailored to the local epidemiology of infectious diseases and AMR was highlighted along with the availability of diagnostic tests and antibiotics using national guidelines where available. Participants endorsed co-design involving all stakeholders, including nurses, midwives, and pharmacists, as central to any introduction of CDSS. A phased approach was suggested by initiating and evaluating CDSS at a pilot site, followed by dissemination using professional networks and social media. The lack of widespread internet access and computers could be circumvented by a mobile app with an offline mode.

Conclusions

Our study provides valuable information for the development and implementation of a CDSS for antibiotic prescribing among primary care prescribers in LMICs and may, in turn, contribute to improving antibiotic use, clinical outcomes and decreasing AMR.

Results from one-year use of an electronic Clinical Decision Support System in a post-conflict context: An implementation research

BACKGROUND

In 2017, the Adamawa State Primary Healthcare Development Agency introduced ALMANACH, an electronic clinical decision support system based on a modified version of IMCI. The target area was the Federal State of Adamawa (Nigeria), a region recovering after the Boko Haram insurgency. The aim of this implementation research was to assess the improvement in terms of quality care offered after one year of utilization of the tool.

METHODS

We carried out two cross-sectional studies in six Primary Health Care Centres to assess the improvements in comparison with the baseline carried out before the implementation. One survey was carried out inside the consultation room and was based on the direct observation of 235 consultations of children aged from 2 to 59 months old. The second survey questioned 189 caregivers outside the health facility for their opinion about the consultation carried out through using the tablet, the prescriptions and medications given.

RESULTS

In comparison with the baseline, more children were checked for danger signs (60.0% vs. 37.1% at baseline) and in addition, children were actually weighed (61.1% vs. 27.7%) during consultation. Malnutrition screening was performed in 35.1% of children (vs. 12.1%). Through ALMANACH, also performance of preventive measures was significantly improved (p<0.01): vaccination status was checked in 39.8% of cases (vs. 10.6% at baseline), and deworming and vitamin A prescription was increased to 46.5% (vs. 0.7%) and 48.3% (vs. 2.8%) respectively. Furthermore, children received a complete physical examination (58.3% vs. 45.5%, p<0.01) and correct treatment (48.4% vs. 29.5%, p<0.01). Regarding antibiotic prescription, 69.3% patients received at least one antibiotic (baseline 77.7%, p<0.05).

CONCLUSIONS

Our findings highlight major improvements in terms of quality of care despite many questions still pending to be answered in relation to a full integration of the tool in the Adamawa health system.

Performance of prediction rules and guidelines in detecting serious bacterial infections among Tanzanian febrile children

Background

Health-workers in developing countries rely on clinical algorithms, such as the Integrated Management of Childhood Illnesses (IMCI), for the management of patients, including diagnosis of serious bacterial infections (SBI). The diagnostic accuracy of IMCI in detecting children with SBI is unknown. Prediction rules and guidelines for SBI from well-resourced countries at outpatient level may help to improve current guidelines; however, their diagnostic performance has not been evaluated in resource-limited countries, where clinical conditions, access to care, and diagnostic capacity differ. The aim of this study was to estimate the diagnostic accuracy of existing prediction rules and clinical guidelines in identifying children with SBI in a cohort of febrile children attending outpatient health facilities in Tanzania.

Methods

Structured literature review to identify available prediction rules and guidelines aimed at detecting SBI and retrospective, external validation on a dataset containing 1005 febrile Tanzanian children with acute infections. The reference standard, SBI, was established based on rigorous clinical and microbiological criteria.

Results

Four prediction rules and five guidelines, including IMCI, could be validated. All examined rules and guidelines had insufficient diagnostic accuracy for ruling-in or ruling-out SBI with positive and negative likelihood ratios ranging from 1.04–1.87 to 0.47–0.92, respectively. IMCI had a sensitivity of 36.7% (95% CI 29.4–44.6%) at a specificity of 70.3% (67.1–73.4%). Rules that use a combination of clinical and laboratory testing had better performance compared to rules and guidelines using only clinical and or laboratory elements.

Conclusions

Currently applied guidelines for managing children with febrile illness have insufficient diagnostic accuracy in detecting children with SBI. Revised clinical algorithms including simple point-of-care tests with improved accuracy for detecting SBI targeting in tropical resource-poor settings are needed. They should undergo careful external validation against clinical outcome before implementation, given the inherent limitations of gold standards for SBI.

Electronic supplementary material

The online version of this article (10.1186/s12879-019-4371-y) contains supplementary material, which is available to authorized users.

Diagnostic tools for tackling febrile illness and enhancing patient management

Most patients with acute infectious diseases develop fever, which is frequently a reason to visit health facilities in resource-limited settings. The symptomatic overlap between febrile diseases impedes their diagnosis on clinical grounds. Therefore, the World Health Organization promotes an integrated management of febrile illness. Along this line, we present an overview of endemic and epidemic etiologies of fever and state-of-the-art diagnostic tools used in the field. It becomes evident that there is an urgent need for the development of novel technologies to fulfill end-users' requirements. This need can be met with point-of-care and near-patient diagnostic platforms, as well as e-Health clinical algorithms, which co-assess test results with key clinical elements and biosensors, assisting clinicians in patient triage and management, thus enhancing disease surveillance and outbreak alerts. This review gives an overview of diagnostic technologies featuring a platform based approach: (i) assay (nucleic acid amplification technologies are examined); (ii) cartridge (microfluidic technologies are presented); (iii) instrument (various detection technologies are discussed); and at the end proposes a way that such technologies can be interfaced with electronic clinical decision-making algorithms towards a broad and complete diagnostic ecosystem.