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Effectiveness of a clinical decision support algorithm (ePOCT+) in improving quality of care for sick children in primary health facilities in Tanzania (DYNAMIC project): results from a cluster randomized trial
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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.
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
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.
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 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). 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 (TB, HIV and nutrition). However, this did not increase identification of children who screened positive. 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. (350)
Clinical Trials Registration: BFC157/19
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.
Background
Cluster randomised trials (CRTs) are often designed with a small number of clusters, but it is not clear which analysis methods are optimal when the outcome is binary. This simulation study aimed to determine (i) whether cluster-level analysis (CL), generalised linear mixed models (GLMM), and generalised estimating equations with sandwich variance (GEE) approaches maintain acceptable type-one error including the impact of non-normality of cluster effects and low prevalence, and if so (ii) which methods have the greatest power. We simulated CRTs with 8–30 clusters, altering the cluster-size, outcome prevalence, intracluster correlation coefficient, and cluster effect distribution. We analysed each dataset with weighted and unweighted CL; GLMM with adaptive quadrature and restricted pseudolikelihood; GEE with Kauermann-and-Carroll and Fay-and-Graubard sandwich variance using independent and exchangeable working correlation matrices. P-values were from a t-distribution with degrees of freedom (DoF) as clusters minus cluster-level parameters; GLMM pseudolikelihood also used Satterthwaite and Kenward-Roger DoF.
Results
Unweighted CL, GLMM pseudolikelihood, and Fay-and-Graubard GEE with independent or exchangeable working correlation matrix controlled type-one error in > 97% scenarios with clusters minus parameters DoF. Cluster-effect distribution and prevalence of outcome did not usually affect analysis method performance. GEE had the least power. With 20–30 clusters, GLMM had greater power than CL with varying cluster-size but similar power otherwise; with fewer clusters, GLMM had lower power with common cluster-size, similar power with medium variation, and greater power with large variation in cluster-size.
Conclusion
We recommend that CRTs with ≤ 30 clusters and a binary outcome use an unweighted CL or restricted pseudolikelihood GLMM both with DoF clusters minus cluster-level parameters.
Background:
The ubiquity of mobile devices has made it possible for clinical decision-support systems (CDSS) to become available to healthcare providers on handheld devices at the point-of-care, including in low- and middle-income countries. The use of CDSS by providers can potentially improve adherence to treatment protocols and patient outcomes. However, the evidence on the effect of the use of CDSS on mobile devices needs to be synthesized. This review was carried out to support a World Health Organization (WHO) guideline that aimed to inform investments on the use of decision-support tools on digital devices to strengthen primary healthcare.
Objectives:
To assess the effects of digital clinical decision-support systems (CDSS) accessible via mobile devices by primary healthcare providers in the context of primary care settings.
Search methods:
We searched CENTRAL, MEDLINE, Embase, Global Index Medicus, POPLINE, and two trial registries from 1 January 2000 to 9 October 2020. We conducted a grey literature search using mHealthevidence.org and issued a call for papers through popular digital health communities of practice. Finally, we conducted citation searches of included studies.
Selection criteria:
Study design: we included randomized trials, including full-text studies, conference abstracts, and unpublished data irrespective of publication status or language of publication. Types of participants: we included studies of all cadres of healthcare providers, including lay health workers and other individuals (administrative, managerial, and supervisory staff) involved in the delivery of primary healthcare services using clinical decision-support tools; and studies of clients or patients receiving care from primary healthcare providers using digital decision-support tools. Types of interventions: we included studies comparing digital CDSS accessible via mobile devices with non-digital CDSS or no intervention, in the context of primary care. CDSS could include clinical protocols, checklists, and other job-aids which supported risk prioritization of patients. Mobile devices included mobile phones of any type (but not analogue landline telephones), as well as tablets, personal digital assistants, and smartphones. We excluded studies where digital CDSS were used on laptops or integrated with electronic medical records or other types of longitudinal tracking of clients.
Data collection and analysis:
A machine learning classifier that gave each record a probability score of being a randomized trial screened all search results. Two review authors screened titles and abstracts of studies with more than 10% probability of being a randomized trial, and one review author screened those with less than 10% probability of being a randomized trial. We followed standard methodological procedures expected by Cochrane and the Effective Practice and Organisation of Care group. We used the GRADE approach to assess the certainty of the evidence for the most important outcomes.
Main results:
Eight randomized trials across varying healthcare contexts in the USA,. India, China, Guatemala, Ghana, and Kenya, met our inclusion criteria. A range of healthcare providers (facility and community-based, formally trained, and lay workers) used digital CDSS. Care was provided for the management of specific conditions such as cardiovascular disease, gastrointestinal risk assessment, and maternal and child health. The certainty of evidence ranged from very low to moderate, and we often downgraded evidence for risk of bias and imprecision. We are uncertain of the effect of this intervention on providers' adherence to recommended practice due to the very low certainty evidence (2 studies, 185 participants). The effect of the intervention on patients' and clients' health behaviours such as smoking and treatment adherence is mixed, with substantial variation across outcomes for similar types of behaviour (2 studies, 2262 participants). The intervention probably makes little or no difference to smoking rates among people at risk of cardiovascular disease but probably increases other types of desired behaviour among patients, such as adherence to treatment. The effect of the intervention on patients'/clients' health status and well-being is also mixed (5 studies, 69,767 participants). It probably makes little or no difference to some types of health outcomes, but we are uncertain about other health outcomes, including maternal and neonatal deaths, due to very low-certainty evidence. The intervention may slightly improve patient or client acceptability and satisfaction (1 study, 187 participants). We found no studies that reported the time between the presentation of an illness and appropriate management, provider acceptability or satisfaction, resource use, or unintended consequences.
Authors' conclusions:
We are uncertain about the effectiveness of mobile phone-based decision-support tools on several outcomes, including adherence to recommended practice. None of the studies had a quality of care framework and focused only on specific health areas. We need well-designed research that takes a systems lens to assess these issues.
Background
The Integrated eDiagnosis Approach (IeDA), centred on an electronic Clinical Decision Support System (eCDSS) developed in line with national Integrated Management of Childhood Illness (IMCI) guidelines, was implemented in primary health facilities of two regions of Burkina Faso. An evaluation was performed using a stepped-wedge cluster randomised design with the aim of determining whether the IeDA intervention increased Health Care Workers’ (HCW) adherence to the IMCI guidelines.
Methods
Ten randomly selected facilities per district were visited at each step by two trained nurses: One observed under-five consultations and the second conducted a repeat consultation. The primary outcomes were: overall adherence to clinical assessment tasks; overall correct classification ignoring the severity of the classifications; and overall correct prescription according to HCWs’ classifications. Statistical comparisons between trial arms were performed on cluster/step-level summaries.
Results
On average, 54 and 79% of clinical assessment tasks were observed to be completed by HCWs in the control and intervention districts respectively (cluster-level mean difference = 29.9%; P -value = 0.002). The proportion of children for whom the validation nurses and the HCWs recorded the same classifications (ignoring the severity) was 73 and 79% in the control and intervention districts respectively (cluster-level mean difference = 10.1%; P -value = 0.004). The proportion of children who received correct prescriptions in accordance with HCWs’ classifications were similar across arms, 78% in the control arm and 77% in the intervention arm (cluster-level mean difference = − 1.1%; P -value = 0.788).
Conclusion
The IeDA intervention improved substantially HCWs’ adherence to IMCI’s clinical assessment tasks, leading to some overall increase in correct classifications but to no overall improvement in correct prescriptions. The largest improvements tended to be observed for less common conditions. For more common conditions, HCWs in the control districts performed relatively well, thus limiting the scope to detect an overall impact.
Trial registration
ClinicalTrials.gov NCT02341469 ; First submitted August 272,014, posted January 19, 2015.
Objective
Assess the quality of healthcare across African countries based on health providers’ clinical knowledge, their clinic attendance and drug availability, with a focus on seven conditions accounting for a large share of child and maternal mortality in sub-Saharan Africa: malaria, tuberculosis, diarrhoea, pneumonia, diabetes, neonatal asphyxia and postpartum haemorrhage.
Methods
With nationally representative, cross-sectional data from ten countries in sub-Saharan Africa, collected using clinical vignettes (to assess provider knowledge), unannounced visits (to assess provider absenteeism) and visual inspections of facilities (to assess availability of drugs and equipment), we assess whether health providers are available and have sufficient knowledge and means to diagnose and treat patients suffering from common conditions amenable to primary healthcare. We draw on data from 8061 primary and secondary care facilities in Kenya, Madagascar, Mozambique, Nigeria, Niger, Senegal, Sierra Leone, Tanzania, Togo and Uganda, and 22 746 health workers including doctors, clinical officers, nurses and community health workers. Facilities were selected using a multistage cluster-sampling design to ensure data were representative of rural and urban areas, private and public facilities, and of different facility types. These data were gathered under the Service Delivery Indicators programme.
Results
Across all conditions and countries, healthcare providers were able to correctly diagnose 64% (95% CI 62% to 65%) of the clinical vignette cases, and in 45% (95% CI 43% to 46%) of the cases, the treatment plan was aligned with the correct diagnosis. For diarrhoea and pneumonia, two common causes of under-5 deaths, 27% (95% CI 25% to 29%) of the providers correctly diagnosed and prescribed the appropriate treatment for both conditions. On average, 70% of health workers were present in the facilities to provide care during facility hours when those workers are scheduled to be on duty. Taken together, we estimate that the likelihood that a facility has at least one staff present with competency and key inputs required to provide child, neonatal and maternity care that meets minimum quality standards is 14%. On average, poor clinical knowledge is a greater constraint in care readiness than drug availability or health workers’ absenteeism in the 10 countries. However, we document substantial heterogeneity across countries in the extent to which drug availability and absenteeism matter quantitatively.
Conclusion
Our findings highlight the need to boost the knowledge of healthcare workers to achieve greater care readiness. Training programmes have shown mixed results, so systems may need to adopt a combination of competency-based preservice and in-service training for healthcare providers (with evaluation to ensure the effectiveness of the training), and hiring practices that ensure the most prepared workers enter the systems. We conclude that in settings where clinical knowledge is poor, improving drug availability or reducing health workers’ absenteeism would only modestly increase the average care readiness that meets minimum quality standards.
Background:
Mobile health (mHealth), refers to healthcare practices supported by mobile devices, such as mobile phones and tablets. Within primary care, health workers often use mobile devices to register clients, track their health, and make decisions about care, as well as to communicate with clients and other health workers. An understanding of how health workers relate to, and experience mHealth, can help in its implementation.
Objectives:
To synthesise qualitative research evidence on health workers' perceptions and experiences of using mHealth technologies to deliver primary healthcare services, and to develop hypotheses about why some technologies are more effective than others.
Search methods:
We searched MEDLINE, Embase, CINAHL, Science Citation Index and Social Sciences Citation Index in January 2018. We searched Global Health in December 2015. We screened the reference lists of included studies and key references and searched seven sources for grey literature (16 February to 5 March 2018). We re-ran the search strategies in February 2020. We screened these records and any studies that we identified as potentially relevant are awaiting classification.
Selection criteria:
We included studies that used qualitative data collection and analysis methods. We included studies of mHealth programmes that were part of primary healthcare services. These services could be implemented in public or private primary healthcare facilities, community and workplace, or the homes of clients. We included all categories of health workers, as well as those persons who supported the delivery and management of the mHealth programmes. We excluded participants identified as technical staff who developed and maintained the mHealth technology, without otherwise being involved in the programme delivery. We included studies conducted in any country.
Data collection and analysis:
We assessed abstracts, titles and full-text papers according to the inclusion criteria. We found 53 studies that met the inclusion criteria and sampled 43 of these for our analysis. For the 43 sampled studies, we extracted information, such as country, health worker category, and the mHealth technology. We used a thematic analysis process. We used GRADE-CERQual to assess our confidence in the findings.
Main results:
Most of the 43 included sample studies were from low- or middle-income countries. In many of the studies, the mobile devices had decision support software loaded onto them, which showed the steps the health workers had to follow when they provided health care. Other uses included in-person and/or text message communication, and recording clients' health information. Almost half of the studies looked at health workers' use of mobile devices for mother, child, and newborn health. We have moderate or high confidence in the following findings. mHealth changed how health workers worked with each other: health workers appreciated being more connected to colleagues, and thought that this improved co-ordination and quality of care. However, some described problems when senior colleagues did not respond or responded in anger. Some preferred face-to-face connection with colleagues. Some believed that mHealth improved their reporting, while others compared it to "big brother watching". mHealth changed how health workers delivered care: health workers appreciated how mHealth let them take on new tasks, work flexibly, and reach clients in difficult-to-reach areas. They appreciated mHealth when it improved feedback, speed and workflow, but not when it was slow or time consuming. Some health workers found decision support software useful; others thought it threatened their clinical skills. Most health workers saw mHealth as better than paper, but some preferred paper. Some health workers saw mHealth as creating more work. mHealth led to new forms of engagement and relationships with clients and communities: health workers felt that communicating with clients by mobile phone improved care and their relationships with clients, but felt that some clients needed face-to-face contact. Health workers were aware of the importance of protecting confidential client information when using mobile devices. Some health workers did not mind being contacted by clients outside working hours, while others wanted boundaries. Health workers described how some community members trusted health workers that used mHealth while others were sceptical. Health workers pointed to problems when clients needed to own their own phones. Health workers' use and perceptions of mHealth could be influenced by factors tied to costs, the health worker, the technology, the health system and society, poor network access, and poor access to electricity: some health workers did not mind covering extra costs. Others complained that phone credit was not delivered on time. Health workers who were accustomed to using mobile phones were sometimes more positive towards mHealth. Others with less experience, were sometimes embarrassed about making mistakes in front of clients or worried about job security. Health workers wanted training, technical support, user-friendly devices, and systems that were integrated into existing electronic health systems. The main challenges health workers experienced were poor network connections, access to electricity, and the cost of recharging phones. Other problems included damaged phones. Factors outside the health system also influenced how health workers experienced mHealth, including language, gender, and poverty issues. Health workers felt that their commitment to clients helped them cope with these challenges.
Authors' conclusions:
Our findings propose a nuanced view about mHealth programmes. The complexities of healthcare delivery and human interactions defy simplistic conclusions on how health workers will perceive and experience their use of mHealth. Perceptions reflect the interplay between the technology, contexts, and human attributes. Detailed descriptions of the programme, implementation processes and contexts, alongside effectiveness studies, will help to unravel this interplay to formulate hypotheses regarding the effectiveness of mHealth.
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.
Background:
The use of mobile health (mHealth) technologies to improve population-level health outcomes around the world has surged in the last decade. Research supports the use of mHealth apps to improve health outcomes such as maternal and infant mortality, treatment adherence, immunization rates, and prevention of communicable diseases. However, developing countries face significant barriers to successfully implement, sustain, and expand mHealth initiatives to improve the health of vulnerable populations.
Objective:
We aimed to identify and synthesize barriers to the use of mHealth technologies such as text messaging (short message service [SMS]), calls, and apps to change and, where possible, improve the health behaviors and health outcomes of populations in developing countries.
Methods:
We followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses checklist. Deriving search criteria from the review's primary objective, we searched PubMed and CINAHL using an exhaustive terms search (eg, mHealth, text messaging, and developing countries, with their respective Medical Subject Headings) limited by publication date, English language, and full text. At least two authors thoroughly reviewed each article's abstract to verify the articles were germane to our objective. We then applied filters and conducted consensus meetings to confirm that the articles met the study criteria.
Results:
Review of 2224 studies resulted in a final group of 30 articles for analysis. mHealth initiatives were used extensively worldwide for applications such as maternal health, prenatal care, infant care, HIV/AIDS prevention, treatment adherence, cardiovascular disease, diabetes, and health education. Studies were conducted in several developing countries in Africa, Asia, and Latin America. From each article, we recorded the specific health outcome that was improved, mHealth technology used, and barriers to the successful implementation of the intervention in a developing country. The most prominent health outcomes improved with mHealth were infectious diseases and maternal health, accounting for a combined 20/30 (67%) of the total studies in the analysis. The most frequent mHealth technology used was SMS, accounting for 18/30 (60%) of the studies. We identified 73 individual barriers and grouped them into 14 main categories. The top 3 barrier categories were infrastructure, lack of equipment, and technology gap, which together accounted for 28 individual barriers.
Conclusions:
This systematic review shed light on the most prominent health outcomes that can be improved using mHealth technology interventions in developing countries. The barriers identified will provide leaders of future intervention projects a solid foundation for their design, thus increasing the chances for long-term success. We suggest that, to overcome the top three barriers, project leaders who wish to implement mHealth interventions must establish partnerships with local governments and nongovernmental organizations to secure funding, leadership, and the required infrastructure.
Background
Quality of care is a difficult parameter to measure. With the introduction of digital algorithms based on the Integrated Management of Childhood Illness (IMCI), we are interested to understand if the adherence to the guidelines improved for a better quality of care for children under 5 years old.
Methods
More than one year after the introduction of digital algorithms, we carried out two cross sectional studies to assess the improvements in comparison with the situation prior to the implementation of the project, in two Basic Health Centres in Kabul province. One survey was carried out inside the consultation room and was based on the direct observation of 181 consultations of children aged 2 months to 5 years old, using a checklist completed by a senior physicians. The second survey queried 181 caretakers of children outside the health facility for their opinion about the consultation carried out through the tablet and prescriptions and medications given.
Results
We measured the quality of care as adherence to the IMCI’s guidelines. The study evaluated the quality of the physical examination and the therapies prescribed with a special attention to antibiotic prescription. We noticed a dramatic improvement (p<0.05) of several indicators following the introduction of digital algorithms. The baseline physical examination was appropriate only for 23.8% [IC% 19.9–28.1] of the patients, 34.5% [IC% 30.0–39.2] received a correct treatment and 86.1% [IC% 82.4–89.2] received at least one antibiotic. With the introduction of digital algorithms, these indicators statistically improved respectively to 84.0% [IC% 77.9–88.6], >85% and less than 30%.
Conclusions
Our findings suggest that digital algorithms improve quality of care by applying the guidelines more effectively. Our experience should encourage to test this tool in different settings and to scale up its use at province/state level.
Effective supportive supervision of healthcare services is crucial for improving and maintaining quality of care. However, this process can be challenging in an environment with chronic shortage of qualified human resources, overburdened healthcare providers, multiple roles of district managers, weak supply chains, high donor fragmentation and inefficient allocation of limited financial resources. Operating in this environment, we systematically evaluated an approach developed in Tanzania to strengthen the implementation of routine supportive supervision of primary healthcare providers. The approach included a systematic quality assessment at health facilities using an electronic tool and subsequent result dissemination at council level. Mixed methods were used to compare the new supportive supervision approach with routine supportive supervision. Qualitative data was collected through in-depth interviews in three councils. Observational data and informal communication as well as secondary data complemented the data set. Additionally, an economic costing analysis was carried out in the same councils. Compared to routine supportive supervision, the new approach increased healthcare providers’ knowledge and skills, as well as quality of data collected and acceptance of supportive supervision amongst stakeholders involved. It also ensured better availability of evidence for follow-up actions, including budgeting and planning, and higher stakeholder motivation and ownership of subsequent quality improvement measures. The new approach reduced time and cost spent during supportive supervision. This increased feasibility of supportive supervision and hence the likelihood of its implementation. Thus, the results presented together with previous findings suggested that if used as the standard approach for routine supportive supervision the new approach offers a suitable option to make supportive supervision more efficient and effective and therewith more sustainable. Moreover, the new approach also provides informed guidance to overcome several problems of supportive supervision and healthcare quality assessments in low- and middle income countries.
Objective
To assess the extent to which Integrated Management of Childhood Illness (IMCI) has been adopted and scaled up in countries.
Setting
The 95 countries that participated in the survey are home to 82% of the global under-five population and account for 95% of the 5.9 million deaths that occurred among children less than 5 years of age in 2015; 93 of them are low-income and middle-income countries (LMICs).
Methods
We conducted a cross-sectional self-administered survey. Questionnaires and data analysis focused on (1) giving a general overview of current organisation and financing of IMCI at country level, (2) describing implementation of IMCI’s three original components and (3) reporting on innovations, barriers and opportunities for expanding access to care for children. A single data file was created using all information collected. Analysis was performed using STATA V.11.
Participants
In-country teams consisting of representatives of the ministry of health and country offices of WHO and Unicef.
Results
Eighty-one per cent of countries reported that IMCI implementation encompassed all three components. Almost half (46%; 44 countries) reported implementation in 90% or more districts as well as all three components in place (full implementation). These full-implementer countries were 3.6 (95% CI 1.5 to 8.9) times more likely to achieve Millennium Development Goal 4 than other (not full implementer) countries. Despite these high reported implementation rates, the strategy is not reaching the children who need it most, as implementation is lowest in high mortality countries (39%; 7/18).
Conclusion
This survey provides a unique opportunity to better understand how implementation of IMCI has evolved in the 20 years since its inception. Results can be used to assist in formulating strategies, policies and activities to support improvements in the health and survival of children and to help achieve the health-related, post-2015 Sustainable Development Goals.
Background:
Integrated Management of Childhood Illness (IMCI) is regarded as a standard public health approach to lowering child mortality in developing countries. However, little is known about how health workers adhere to the guidelines at the national level in sub-Saharan African countries.
Methods:
Data from the Service Provision Assessment surveys of Namibia (NA) (survey year: 2009), Kenya (KE) (2010), Tanzania (TZ) (2006) and Uganda (UG) (2007) were analysed for adherence to the IMCI guidelines by health workers. Potential influencing factors included the survey country, patient's age, the different levels of the national health system, the training level of the health care provider (physician, non-physician clinician, nurse-midwife, auxiliary staff), and the status of re-training in IMCI.
Results:
In total, 6856 children (NA: 1495; KE: 1890; TZ: 2469; UG: 1002 / male 51.2-53.5%) aged 2-73 months (2-24 months, 65.3%; median NA: 19 months; KE: 18 months; TZ: 16 months; UG: 15 months) were clinically assessed by 2006 health workers during the surveys. Less than 33% of the workers carried out assessment of all three IMCI danger signs, namely inability to eat/drink, vomiting everything, and febrile convulsions (NA: 11%; KE: 11%; TZ: 14%; UG: 31%) while the rate for assessing all three of the IMCI main symptoms of cough/difficult breathing, diarrhoea, and fever was < 60% (NA: 48%; KE: 34%; TZ: 50%; UG: 57%). Physical examination rates for fever (temperature) (NA: 97%; KE: 87%; TZ: 73%; UG: 90%), pneumonia (respiration rate/auscultation) (NA: 43%; KE: 24%; TZ: 25%; UG: 20%) and diarrhoea (dehydration status) (NA: 29%; KE: 19%; TZ: 20%; UG: 39%) varied widely and were highest when assessing children with the actual diagnosis of pneumonia and diarrhoea. Adherence rates tended to be higher in children ≤ 24 months, at hospitals, among higher-qualified staff (physician/non-physician clinician) and among those with recent IMCI re-training.
Conclusion:
Despite nationwide training in IMCI the adherence rates for assessment and physical examination remained low in all four countries. IMCI training should continue to be provided to all health staff, particularly nurses, midwives, and auxiliary staff, with periodic re-training and an emphasis to equally target children of all age groups.
Background
The management of childhood infections remains inadequate in resource-limited countries, resulting in high mortality and irrational use of antimicrobials. Current disease management tools, such as the Integrated Management of Childhood Illness (IMCI) algorithm, rely solely on clinical signs and have not made use of available point-of-care tests (POCTs) that can help to identify children with severe infections and children in need of antibiotic treatment. e-POCT is a novel electronic algorithm based on current evidence; it guides clinicians through the entire consultation and recommends treatment based on a few clinical signs and POCT results, some performed in all patients (malaria rapid diagnostic test, hemoglobin, oximeter) and others in selected subgroups only (C-reactive protein, procalcitonin, glucometer). The objective of this trial was to determine whether the clinical outcome of febrile children managed by the e-POCT tool was non-inferior to that of febrile children managed by a validated electronic algorithm derived from IMCI (ALMANACH), while reducing the proportion with antibiotic prescription.
Methods and findings
We performed a randomized (at patient level, blocks of 4), controlled non-inferiority study among children aged 2–59 months presenting with acute febrile illness to 9 outpatient clinics in Dar es Salaam, Tanzania. In parallel, routine care was documented in 2 health centers. The primary outcome was the proportion of clinical failures (development of severe symptoms, clinical pneumonia on/after day 3, or persistent symptoms at day 7) by day 7 of follow-up. Non-inferiority would be declared if the proportion of clinical failures with e-POCT was no worse than the proportion of clinical failures with ALMANACH, within statistical variability, by a margin of 3%. The secondary outcomes included the proportion with antibiotics prescribed on day 0, primary referrals, and severe adverse events by day 30 (secondary hospitalizations and deaths). We enrolled 3,192 patients between December 2014 and February 2016 into the randomized study; 3,169 patients (e-POCT: 1,586; control [ALMANACH]: 1,583) completed the intervention and day 7 follow-up. Using e-POCT, in the per-protocol population, the absolute proportion of clinical failures was 2.3% (37/1,586), as compared with 4.1% (65/1,583) in the ALMANACH arm (risk difference of clinical failure −1.7, 95% CI −3.0, −0.5), meeting the prespecified criterion for non-inferiority. In a non-prespecified superiority analysis, we observed a 43% reduction in the relative risk of clinical failure when using e-POCT compared to ALMANACH (risk ratio [RR] 0.57, 95% CI 0.38, 0.85, p = 0.005). The proportion of severe adverse events was 0.6% in the e-POCT arm compared with 1.5% in the ALMANACH arm (RR 0.42, 95% CI 0.20, 0.87, p = 0.02). The proportion of antibiotic prescriptions was substantially lower, 11.5% compared to 29.7% (RR 0.39, 95% CI 0.33, 0.45, p < 0.001). Using e-POCT, the most common indication for antibiotic prescription was severe disease (57%, 103/182 prescriptions), while it was non-severe respiratory infections using the control algorithm (ALMANACH) (70%, 330/470 prescriptions). The proportion of clinical failures among the 544 children in the routine care cohort was 4.6% (25/544); 94.9% (516/544) of patients received antibiotics on day 0, and 1.1% (6/544) experienced severe adverse events. e-POCT achieved a 49% reduction in the relative risk of clinical failure compared to routine care (RR 0.51, 95% CI 0.31, 0.84, p = 0.007) and lowered antibiotic prescriptions to 11.5% from 94.9% (p < 0.001). Though this safety study was an important first step to evaluate e-POCT, its true utility should be evaluated through future implementation studies since adherence to the algorithm will be an important factor in making use of e-POCT’s advantages in terms of clinical outcome and antibiotic prescription.
Conclusions
e-POCT, an innovative electronic algorithm using host biomarker POCTs, including C-reactive protein and procalcitonin, has the potential to improve the clinical outcome of children with febrile illnesses while reducing antibiotic use through improved identification of children with severe infections, and better targeting of children in need of antibiotic prescription.
Trial registration
ClinicalTrials.gov NCT02225769
Background:
More than 7.5 million children younger than age five living in low- and middle-income countries die every year. The World Health Organization (WHO) developed the integrated management of childhood illness (IMCI) strategy to reduce mortality and morbidity and to improve quality of care by improving the delivery of a variety of curative and preventive medical and behavioral interventions at health facilities, at home, and in the community.
Objectives:
To evaluate the effects of programs that implement the IMCI strategy in terms of death, nutritional status, quality of care, coverage with IMCI deliverables, and satisfaction of beneficiaries.
Search methods:
We searched the Cochrane Central Register of Controlled Trials (CENTRAL; 2015, Issue 3), including the Cochrane Effective Practice and Organisation of Care (EPOC) Group Specialised Register; MEDLINE; EMBASE, Ovid; the Cumulative Index to Nursing and Allied Health Literature (CINAHL), EbscoHost; the Latin American Caribbean Health Sciences Literature (LILACS), Virtual Health Library (VHL); the WHO Library & Information Networks for Knowledge Database (WHOLIS); the Science Citation Index and Social Sciences Citation Index, Institute for Scientific Information (ISI) Web of Science; Population Information Online (POPLINE); the WHO International Clinical Trials Registry Platform (WHO ICTRP); and the Global Health, Ovid and Health Management, ProQuest database. We performed searches until 30 June 2015 and supplemented these by searching revised bibliographies and by contacting experts to identify ongoing and unpublished studies.
Selection criteria:
We sought to include randomised controlled trials (RCTs) and controlled before-after (CBA) studies with at least two intervention and two control sites evaluating the generic IMCI strategy or its adaptation in children younger than age five, and including at minimum efforts to improve health care worker skills for case management. We excluded studies in which IMCI was accompanied by other interventions including conditional cash transfers, food supplementation, and employment. The comparison group received usual health services without provision of IMCI.
Data collection and analysis:
Two review authors independently screened searches, selected trials, and extracted, analysed and tabulated data. We used inverse variance for cluster trials and an intracluster co-efficient of 0.01 when adjustment had not been made in the primary study. We used the GRADE (Grades of Recommendation, Assessment, Development and Evaluation Working Group) approach to assess the certainty of evidence.
Main results:
Two cluster-randomised trials (India and Bangladesh) and two controlled before-after studies (Tanzania and India) met our inclusion criteria. Strategies included training of health care staff, management strengthening of health care systems (all four studies), and home visiting (two studies). The two studies from India included care packages targeting the neonatal period.One trial in Bangladesh estimated that child mortality may be 13% lower with IMCI, but the confidence interval (CI) included no effect (risk ratio (RR) 0.87, 95% CI 0.68 to 1.10; 5090 participants; low-certainty evidence). One CBA study in Tanzania gave almost identical estimates (RR 0.87, 95% CI 0.72 to 1.05; 1932 participants).One trial in India examined infant and neonatal mortality by implementing the integrated management of neonatal and childhood illness (IMNCI) strategy including post-natal home visits. Neonatal and infant mortality may be lower in the IMNCI group compared with the control group (infant mortality hazard ratio (HR) 0.85, 95% CI 0.77 to 0.94; neonatal mortality HR 0.91, 95% CI 0.80 to 1.03; one trial, 60,480 participants; low-certainty evidence).We estimated the effect of IMCI on any mortality measured by combining infant and child mortality in the one IMCI and the one IMNCI trial. Mortality may be reduced by IMCI (RR 0.85, 95% CI 0.78 to 0.93; two trials, 65,570 participants; low-certainty evidence).Two trials (India, Bangladesh) evaluated nutritional status and noted that there may be little or no effect on stunting (RR 0.94, 95% CI 0.84 to 1.06; 5242 participants, two trials; low-certainty evidence) and there is probably little or no effect on wasting (RR 1.04, 95% CI 0.87 to 1.25; two trials, 4288 participants; moderate-certainty evidence).The Tanzania CBA study showed similar results.Investigators measured quality of care by observing prescribing for common illnesses at health facilities (727 observations, two studies; very low-certainty evidence) and by observing prescribing by lay health care workers (1051 observations, three studies; very low-certainty evidence). We could not confirm a consistent effect on prescribing at health facilities or by lay health care workers, as certainty of the evidence was very low.For coverage of IMCI deliverables, we examined vaccine and vitamin A coverage, appropriate care seeking, and exclusive breast feeding. Two trials (India, Bangladesh) estimated vaccine coverage for measles and reported that there is probably little or no effect on measles vaccine coverage (RR 0.92, 95% CI 0.80 to 1.05; two trials, 4895 participants; moderate-certainty evidence), with similar effects seen in the Tanzania CBA study. Two studies measured the third dose of diphtheria, pertussis, and tetanus vaccine; and two measured vitamin A coverage, all providing little or no evidence of increased coverage with IMCI.Four studies (2 from India, and 1 each from Tanzania and Bangladesh) reported appropriate care seeking and derived information from careful questioning of mothers about recent illness. Some studies on effects of IMCI may report better care seeking behavior, but others do not report this.All four studies recorded maternal responses on exclusive breast feeding. They provided mixed results and very low-certainty evidence. Therefore, we do not know whether IMCI impacts exclusive breast feeding.No studies reported on the satisfaction of mothers and service users.
Authors' conclusions:
The mix of interventions examined in research studies evaluating the IMCI strategy varies, and some studies include specific inputs to improve neonatal health. Most studies were conducted in South Asia. Implementing the integrated management of childhood illness strategy may reduce child mortality, and packages that include interventions for the neonatal period may reduce infant mortality. IMCI may have little or no effect on nutritional status and probably has little or no effect on vaccine coverage. Maternal care seeking behavior may be more appropriate with IMCI, but study results have been mixed, providing evidence of very low certainty about whether IMCI has effects on adherence to exclusive breast feeding.
The decline of malaria and scale-up of rapid diagnostic tests calls for a revision of IMCI. A new algorithm (ALMANACH) running on mobile technology was developed based on the latest evidence. The objective was to ensure that ALMANACH was safe, while keeping a low rate of antibiotic prescription.
Consecutive children aged 2-59 months with acute illness were managed using ALMANACH (2 intervention facilities), or standard practice (2 control facilities) in Tanzania. Primary outcomes were proportion of children cured at day 7 and who received antibiotics on day 0.
130/842 (15∙4%) in ALMANACH and 241/623 (38∙7%) in control arm were diagnosed with an infection in need for antibiotic, while 3∙8% and 9∙6% had malaria. 815/838 (97∙3%;96∙1-98.4%) were cured at D7 using ALMANACH versus 573/623 (92∙0%;89∙8-94∙1%) using standard practice (p<0∙001). Of 23 children not cured at D7 using ALMANACH, 44% had skin problems, 30% pneumonia, 26% upper respiratory infection and 13% likely viral infection at D0. Secondary hospitalization occurred for one child using ALMANACH and one who eventually died using standard practice. At D0, antibiotics were prescribed to 15∙4% (12∙9-17∙9%) using ALMANACH versus 84∙3% (81∙4-87∙1%) using standard practice (p<0∙001). 2∙3% (1∙3-3.3) versus 3∙2% (1∙8-4∙6%) received an antibiotic secondarily.
Management of children using ALMANACH improve clinical outcome and reduce antibiotic prescription by 80%. This was achieved through more accurate diagnoses and hence better identification of children in need of antibiotic treatment or not. The building on mobile technology allows easy access and rapid update of the decision chart.
Pan African Clinical Trials Registry PACTR201011000262218.
To review the available knowledge on epidemiology and diagnoses of acute infections in children aged 2 to 59 months in primary care setting and develop an electronic algorithm for the Integrated Management of Childhood Illness to reach optimal clinical outcome and rational use of medicines.
A structured literature review in Medline, Embase and the Cochrane Database of Systematic Review (CDRS) looked for available estimations of diseases prevalence in outpatients aged 2-59 months, and for available evidence on i) accuracy of clinical predictors, and ii) performance of point-of-care tests for targeted diseases. A new algorithm for the management of childhood illness (ALMANACH) was designed based on evidence retrieved and results of a study on etiologies of fever in Tanzanian children outpatients.
The major changes in ALMANACH compared to IMCI (2008 version) are the following: i) assessment of 10 danger signs, ii) classification of non-severe children into febrile and non-febrile illness, the latter receiving no antibiotics, iii) classification of pneumonia based on a respiratory rate threshold of 50 assessed twice for febrile children 12-59 months; iv) malaria rapid diagnostic test performed for all febrile children. In the absence of identified source of fever at the end of the assessment, v) urine dipstick performed for febrile children <2years to consider urinary tract infection, vi) classification of 'possible typhoid' for febrile children >2 years with abdominal tenderness; and lastly vii) classification of 'likely viral infection' in case of negative results.
This smartphone-run algorithm based on new evidence and two point-of-care tests should improve the quality of care of <5 year children and lead to more rational use of antimicrobials.
Integrated Management of Childhood Illness (IMCI) was developed by the World Health Organization (WHO) and the United Nations International Children's Fund (UNICEF) and aims at reducing childhood morbidity and mortality in resource-limited settings including Tanzania. It was introduced in 1996 and has been scaled up in all districts in the country. The purpose of this study was to identify factors influencing the implementation of IMCI in the health facilities in Mwanza, Tanzania since reports indicates that the guidelines are not full adhered to by the healthcare workers.
A cross-sectional study design was used and a sample size of 95 healthcare workers drawn from health centers and dispensaries within Mwanza city were interviewed using self-administered questionnaires. Structured interview was also used to get views from the city IMCI focal person and the 2 facilitators. Data were analyzed using SPSS and presented using figures and tables.
Only 51% of healthcare workers interviewed had been trained. 69% of trained Healthcare workers expressed understanding of the IMCI approach. Most of the respondents (77%) had a positive attitude that IMCI approach was a better approach in managing common childhood illnesses especially with the reality of resource constraint in the health facilities. The main challenges identified in the implementation of IMCI are low initial training coverage among health care workers, lack of essential drugs and supplies, lack of onsite mentoring and lack of refresher courses and regular supportive supervision. Supporting the healthcare workers through training, onsite mentoring, supportive supervision and strengthening the healthcare system through increasing access to essential medicines, vaccines, strengthening supply chain management, increasing healthcare financing, improving leadership & management were the major interventions that could assist in IMCI implementation.
The healthcare workers can implement better IMCI through the collaboration of supervisors, IMCI focal person, Council Health Management Teams (CHMT) and other stakeholders interested in child health. However, significant barriers impede a sustainable IMCI implementation. Recommendations have been made related to supportive supervision and HealthCare system strengthening among others.
To determine the effectiveness of different types of interventions in improving health professional performance and health outcomes.
MEDLINE, SCISEARCH, CINAHL and the Research and Development Resource Base in CME were searched for trials of educational interventions in the health care professions published between 1970 and 1993 inclusive.
Studies were selected if they provided objective measurements of health professional performance or health outcomes and employed random or quasi-random allocation methods in their study designs to assign individual subjects or groups. Interventions included such activities as conferences, outreach visits, the use of local opinion leaders, audit and feedback, and reminder systems.
Details extracted from the studies included the study design; the unit of allocation (e.g., patient, provider, practice, hospital); the characteristics of the targeted health care professionals, educational interventions and patients (when appropriate); and the main outcome measure.
The inclusion criteria were met by 102 trials. Areas of behaviour change included general patient management, preventive services, prescribing practices, treatment of specific conditions such as hypertension or diabetes, and diagnostic service or hospital utilization. Dissemination-only strategies, such as conferences or the mailing of unsolicited materials, demonstrated little or no changes in health professional behaviour or health outcome when used alone. More complex interventions, such as the use of outreach visits or local opinion leaders, ranged from ineffective to highly effective but were most often moderately effective (resulting in reductions of 20% to 50% in the incidence of inappropriate performance).
There are no "magic bullets" for improving the quality of health care, but there are a wide range of interventions available that, if used appropriately, could lead to important improvements in professional practice and patient outcomes.
To assess the effectiveness of tailored interventions to implement guidelines for urinary tract infections in women and sore throat.
Unblinded, cluster randomised pretest-post-test trial.
142 general practices in Norway.
72 practices received interventions to implement guidelines for urinary tract infection and 70 practices received interventions to implement guidelines for sore throat, serving as controls for each other. 59 practices in the urinary tract infection group and 61 practices in the sore throat group completed the study. Outcomes were measured in 16 939 consultations for sore throat and 9887 consultations for urinary tract infection.
Interventions were developed to overcome identified barriers to implementing the guidelines. The main components of the tailored interventions were patient educational material, computer based decision support and reminders, an increase in the fee for telephone consultations, and interactive courses for general practitioners and practice assistants.
Changes in rates of use of antibiotics, laboratory tests, and telephone consultations. Results: Patients in the sore throat group were 3% less likely to receive antibiotics after the intervention. Women with symptoms of urinary tract infection in the intervention group were 5.1% less likely to have a laboratory test ordered. No significant differences were found between the groups for the other outcomes. Large variation was found across the included practices in the rates of antibiotic prescription, use of laboratory tests and telephone consultations, and in the extent of change for all three outcome measures.
Passively delivered, complex interventions targeted at identified barriers to change had little effect in changing practice.
The complexity and cost of measuring weight-for-height make it unsuitable for use by community-based volunteers. This has led community therapeutic care programs to adopt a two-stage screening and admission procedure in which mid-upper-arm circumference (MUAC) is used for referral and weight-for-height is used for admission. Such a procedure results in many individuals being referred for care on the basis of MUAC but subsequently being refused treatment because they do not meet the weight-for-height admission criterion. This "problem of rejected referrals" has proved to be a major barrier to program uptake.
To systematically review methods to detect cases of severely malnourished children in the community for their admission into community-based therapeutic care programs.
Clinical and anthropometric methods for case detection of severely malnourished children in the community were reviewed with regard to their ability to reflect both mortality risk and nutritional status.
MUAC, with the addition of the presence of bipedal edema, was found to be the indicator best suited to screening and case detection of malnutrition in the community. The case definition "MUAC < 110 mm OR the presence of bipedal edema," with MUAC measured by a color-banded strap, is suitable for screening and case detection of malnutrition in the community for children aged between 6 and 59 months. Monitoring and discharge criteria were also reviewed.
There is no compelling evidence to support a move away from using weight in combination with clinical criteria for monitoring and discharge.
In this article, we introduce a new command, clan, that conducts a cluster-level analysis of cluster randomized trials. The command simplifies adjusting for individual- and cluster-level covariates and can also account for a stratified design. It can be used to analyze a continuous, binary, or rate outcome.
Effective, scalable and sustainable strategies to improve quality of care are needed to address the substantial burden of preventable deaths of children under-five in resource-constrained settings. Clinical decision support systems (CDSS), digital tools which generate recommendations for healthcare providers based on patient-specific information, show promise. By strengthening adherence to evidence-based assessment, diagnosis and management and generating high-quality data, CDSS can improve quality care - care that is effective, safe, people-centered, timely, equitable, integrated and efficient. Designing and implementing CDSS that deliver this impact is a complex and iterative process. We advocate for collaboration on developing and evaluating these tools to guide their implementation for maximal impact.
Children with malnutrition compared with those without are at higher risk of infection, with more severe outcomes. How clinicians assess nutritional risk factors in febrile children in primary care varies. We conducted a post hoc subgroup analysis of febrile children with severe malnutrition enrolled in a randomized, controlled trial in primary care centers in Tanzania. The clinical outcome of children with severe malnutrition defined by anthropometric measures and clinical signs was compared between two electronic clinical diagnostic algorithms: ePOCT, which uses weight-for-age and mid-upper arm circumference to identify and manage severe malnutrition, and ALMANACH, which uses the clinical signs of edema of both feet and visible severe wasting. Those identified as having severe malnutrition by the algorithms in each arm were prescribed antibiotics and referred to the hospital. From December 2014 to February 2016, 106 febrile children were enrolled and randomized in the parent study, and met the criteria to be included in the present analysis. ePOCT identified 56/57 children with severe malnutrition using anthropometric measures, whereas ALMANACH identified 2/49 children with severe malnutrition using clinical signs. The proportion of clinical failure, defined as the development of severe symptoms by day 7 or persisting symptoms at day 7 (per-protocol), was 1.8% (1/56) in the ePOCT arm versus 16.7% (8/48) in the Algorithm for the MANagement of Childhood illnesses arm (risk difference -14.9%, 95% CI -26.0%, -3.8%; risk ratio 0.11, 95% CI 0.01, 0.83). Using anthropometric measures to identify and manage febrile children with severe malnutrition may have resulted in better clinical outcomes than by using clinical signs alone.
Background:
Antibiotics are overprescribed for non-severe acute infections in children in primary care.
Aim:
To explore two different interventions that may reduce inappropriate antibiotic prescribing for non-severe acute infections.
Design and setting:
A cluster randomised, factorial controlled trial in primary care, in Flanders, Belgium.
Method:
Family physicians (FPs) enrolled children with non-severe acute infections into this study. The participants were allocated to one of four intervention groups according to whether the FPs performed: (1) a point-of-care C-reactive protein test (POC CRP); (2) a brief intervention to elicit parental concern combined with safety net advice (BISNA); (3) both POC CRP and BISNA; or (4) usual care (UC). Guidance on the interpretation of CRP was not provided. The main outcome was the immediate antibiotic prescribing rate. A mixed logistic regression was performed to analyse the data.
Results:
In this study 2227 non-severe acute infections in children were registered by 131 FPs. In comparison with UC, POC CRP did not influence antibiotic prescribing, (adjusted odds ratio [AOR] 1.01, 95% confidence interval [CI] = 0.57 to 1.79). BISNA increased antibiotic prescribing (AOR 2.04, 95% CI = 1.19 to 3.50). In combination with POC CRP, this increase disappeared.
Conclusion:
Systematic POC CRP testing without guidance is not an effective strategy to reduce antibiotic prescribing for non-severe acute infections in children in primary care. Eliciting parental concern and providing a safety net without POC CRP testing conversely increased antibiotic prescribing. FPs possibly need more training in handling parental concern without inappropriately prescribing antibiotics.
Introduction:
ALMANACH (ALgorithms for the MANagement of Acute CHildhood illnesses) is an electronic version of IMCI (Integrated Management of Childhood Illness) running on tablets. ALMANACH enhances its concept, it integrates well into health staff's daily consultation work and facilitates diagnosis and treatment. ALMANACH informs when to refer a child or to perform a rapid diagnostic test (RDT), recommends the right treatment dosage and synchronizes collected data real time with a Health Management Information System (DHIS2) for epidemiological evaluation and decision making.
Objectives:
Since May 2016, ALMANACH is under investigational deployment in three primary health care facilities in Afghanistan with the goal to improve the quality of care provided to children between 2 months and 5 years old.
Methods:
IMCI's algorithms were updated in considering latest scientific publications, national guidelines, innovations in RDTs, the target population's epidemiological profile and the local resources available. Before the implementation of the project, a direct observation of 599 consultations was carried out to assess the daily performance at three selected health facilities in Kabul.
Results:
The baseline survey showed that nutritional screening, vitamin A supplementation and deworming were not systematically performed: few patients were diagnosed for malnutrition (1.8%), received vitamin A (2.7%) or deworming (7.5%). Physical examination was appropriate only for 23.8% of the diagnoses of respiratory or gastrointestinal diseases, ear infection and sore throat. Respiratory rate was checked only in 33.5% of the children with fever and cough, dehydration status was assessed in only 16.5% of the diarrhoea cases. Forty-seven percent of patients received incorrect treatment. Sixty-four percent of the children, before the introduction of ALMANACH, received at least one antibiotic, although for 87.1% antibiotic therapy was unnecessary. The review of 8'047 paediatric consultations between May 2016 and September 2017 showed that with ALMANACH, malnutrition detection, deworming and Vitamin A supplementation increased respectively to 4.4%, 50.2% and 27.5%. Antibiotic prescription decreased to 21.83% and all children were examined and treated in compliance with the protocols.
Conclusion:
A survey will be conducted one year after the implementation to validate these initial promising results. If the efficacy of the approach is confirmed, ALMANACH could establish as a powerful innovation for primary health care.
In low-resource settings, where qualified health workers (HWs) are scarce and childhood mortality high, rational antimicrobial prescription for childhood illnesses is a challenge. To assess whether smartphones running guidelines, as compared with paper support, improve consultation process and rational use of medicines for children, a pilot cluster-randomized controlled study was conducted in Tanzania. Nine primary health-care facilities (HFs) were randomized into three arms: 1) paper algorithm, 2) electronic algorithm on a smartphone, and 3) control. All HWs attending children aged 2-59 months for acute illness in intervention HFs were trained on a new clinical algorithm for management of childhood illness (ALMANACH) either on 1) paper or 2) electronic support; 4 months after training, consultations were observed. An expert consultation was the reference for classification and treatment. Main outcomes were proportion of children checked for danger signs, and antibiotics prescription rate. A total of 504 consultations (166, 171, and 167 in control, paper, and phone arms, respectively) were observed. The use of smartphones versus paper was associated with a significant increase in children checked for danger signs (41% versus 74%, P = 0.04). Antibiotic prescriptions rate dropped from 70% in the control to 26%, and 25% in paper and electronic arms. The HWs-expert agreement on pneumonia classification remained low (expert's pneumonia identified by HWs in 26%, 30%, and 39% of patients, respectively).Mobile technology in low-income countries is implementable and has a potential to improve HWs' performance. Additional point-of-care diagnostic tests are needed to ensure appropriate management. Improving the rational use of antimicrobial is a challenge that ALMANACH can help to take up. © Copyright 2017 by The American Society of Tropical Medicine and Hygiene.
We evaluated an intervention to support health workers after training in Integrated Management of Childhood Illness (IMCI), a strategy that can improve outcomes for children in developing countries by encouraging workers' use of evidence-based guidelines for managing the leading causes of child mortality.
We conducted a randomized trial in Benin. We administered a survey in 1999 to assess health care quality before IMCI training. Health workers then received training plus either study supports (job aids, nonfinancial incentives, and supervision of workers and supervisors) or usual supports. Follow-up surveys conducted in 2001 to 2004 assessed recommended treatment, recommended or adequate treatment, and an index of overall guideline adherence.
We analyzed 1244 consultations. Performance improved in both intervention and control groups, with no significant differences between groups. However, training proceeded slowly, and low-quality care from health workers without IMCI training diluted intervention effects. Per-protocol analyses revealed that workers with IMCI training plus study supports provided better care than did those with training plus usual supports (27.3 percentage-point difference for recommended treatment; P < .05), and both groups outperformed untrained workers.
IMCI training was useful but insufficient. Relatively inexpensive supports can lead to additional improvements.
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