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Background The leading causes of mortality globally in children younger than five years of age (under‐fives), and particularly in the regions of sub‐Saharan Africa (SSA) and Southern Asia, in 2018 were infectious diseases, including pneumonia (15%), diarrhoea (8%), malaria (5%) and newborn sepsis (7%) (UNICEF 2019). Nutrition‐related factors contributed to 45% of under‐five deaths (UNICEF 2019). World Health Organization (WHO) and United Nations Children's Fund (UNICEF), in collaboration with other development partners, have developed an approach – now known as integrated community case management (iCCM) – to bring treatment services for children 'closer to home'. The iCCM approach provides integrated case management services for two or more illnesses – including diarrhoea, pneumonia, malaria, severe acute malnutrition or neonatal sepsis – among under‐fives at community level (i.e. outside of healthcare facilities) by lay health workers where there is limited access to health facility‐based case management services (WHO/UNICEF 2012). Objectives To assess the effects of the integrated community case management (iCCM) strategy on coverage of appropriate treatment for childhood illness by an appropriate provider, quality of care, case load or severity of illness at health facilities, mortality, adverse events and coverage of careseeking for children younger than five years of age in low‐ and middle‐income countries. Search methods We searched CENTRAL, MEDLINE, Embase and CINAHL on 7 November 2019, Virtual Health Library on 8 November 2019, and Popline on 5 December 2018, three other databases on 22 March 2019 and two trial registers on 8 November 2019. We performed reference checking, and citation searching, and contacted study authors to identify additional studies. Selection criteria Randomized controlled trials (RCTs), cluster‐RCTs, controlled before‐after studies (CBAs), interrupted time series (ITS) studies and repeated measures studies comparing generic WHO/UNICEF iCCM (or local adaptation thereof) for at least two iCCM diseases with usual facility services (facility treatment services) with or without single disease community case management (CCM). We included studies reporting on coverage of appropriate treatment for childhood illness by an appropriate provider, quality of care, case load or severity of illness at health facilities, mortality, adverse events and coverage of careseeking for under‐fives in low‐ and middle‐income countries. Data collection and analysis At least two review authors independently screened abstracts, screened full texts and extracted data using a standardised data collection form adapted from the EPOC Good Practice Data Collection Form. We resolved any disagreements through discussion or, if required, we consulted a third review author not involved in the original screening. We contacted study authors for clarification or additional details when necessary. We reported risk ratios (RR) for dichotomous outcomes and hazard ratios (HR) for time to event outcomes, with 95% confidence intervals (CI), adjusted for clustering, where possible. We used estimates of effect from the primary analysis reported by the investigators, where possible. We analysed the effects of randomized trials and other study types separately. We used the GRADE approach to assess the certainty of evidence. Main results We included seven studies, of which three were cluster RCTs and four were CBAs. Six of the seven studies were in SSA and one study was in Southern Asia. The iCCM components and inputs were fairly consistent across the seven studies with notable variation for the training and deployment component (e.g. on payment of iCCM providers) and the system component (e.g. on improving information systems). When compared to usual facility services, we are uncertain of the effect of iCCM on coverage of appropriate treatment from an appropriate provider for any iCCM illness (RR 0.96, 95% CI 0.77 to 1.19; 2 CBA studies, 5898 children; very low‐certainty evidence). iCCM may have little to no effect on neonatal mortality (HR 1.01, 95% 0.73 to 1.28; 2 trials, 65,209 children; low‐certainty evidence). We are uncertain of the effect of iCCM on infant mortality (HR 1.02, 95% CI 0.83 to 1.26; 2 trials, 60,480 children; very low‐certainty evidence) and under‐five mortality (HR 1.18, 95% CI 1.01 to 1.37; 1 trial, 4729 children; very low‐certainty evidence). iCCM probably increases coverage of careseeking to an appropriate provider for any iCCM illness by 68% (RR 1.68, 95% CI 1.24 to 2.27; 2 trials, 9853 children; moderate‐certainty evidence). None of the studies reported quality of care, severity of illness or adverse events for this comparison. When compared to usual facility services plus CCM for malaria, we are uncertain of the effect of iCCM on coverage of appropriate treatment from an appropriate provider for any iCCM illness (very low‐certainty evidence) and iCCM may have little or no effect on careseeking to an appropriate provider for any iCCM illness (RR 1.06, 95% CI 0.97 to 1.17; 1 trial, 811 children; low‐certainty evidence). None of the studies reported quality of care, case load or severity of illness at health facilities, mortality or adverse events for this comparison. Authors' conclusions iCCM probably increases coverage of careseeking to an appropriate provider for any iCCM illness. However, the evidence presented here underscores the importance of moving beyond training and deployment to valuing iCCM providers, strengthening health systems and engaging community systems., Plain language summary Integrated community case management of childhood illness in low‐ and middle‐income countries What was the aim of this review? This Cochrane Review aimed to assess the effects of integrated community case management (iCCM) for children under‐five in low‐ and middle‐income countries. The review authors collected and analysed all relevant studies to answer this question and found seven studies. Key messages When iCCM is compared to usual facility services, it probably increases the number of parents who seek care from a healthcare worker. But we do not know if more children get the correct treatment, and it may have no effect on the number of children who die. What was studied in the review? Each year, more than five million children die before the age of five. Most of these children live in sub‐Saharan Africa or Central and Southern Asia. Many of these children suffer from infectious diseases including pneumonia and diarrhoea; and from malaria and malnutrition. And many children have more than one of these illnesses at the same time. These children do not always have easy access to healthcare services. To address these problems, the World Health Organization, United Nations Children's Fund (UNICEF) and others have developed an approach known as iCCM. iCCM focuses on children under five years of age living in rural and hard‐to‐reach areas. They receive services from lay health workers who are based in the community, outside of healthcare facilities. There are three main components of iCCM: – Lay health workers are trained to assess children's health, provide services for common childhood illnesses and refer children to healthcare facilities where necessary. (A lay health worker is a lay person who has received some training to deliver healthcare services but is not a health professional.) – Systems are put in place to make sure that the lay health workers have good access to supplies, get regular supervision and can easily refer children on to healthcare facilities. – Families and communities receive communication and information about good practices for health and nutrition. What were the main results of the review? The review authors found seven relevant studies. Six were from sub‐Saharan Africa and one was from Southern Asia. Some of the studies compared settings that had iCCM with settings that only had usual healthcare facilities. Some of the other studies compared settings that had iCCM with settings that had usual healthcare facilities as well as community‐based management of malaria. When iCCM is compared to usual facility services: – It probably increases the number of parents who seek care from a healthcare worker when their children have common childhood illnesses. – We do not know if more children get the correct treatment for childhood illnesses because the certainty of the evidence was very low. – There may be no effect on the number of newborn children who die. – We do not know what the effect is on the number of infants and children under‐five years who die. – We do not know what the effect is on quality of care, side effects or the number of children who attend healthcare facilities because the studies did not measure this. When iCCM is compared to usual facility services plus community‐based management of malaria: – It may have no effect on the number of parents who seek care from a healthcare worker when their children have common childhood illnesses. – We do not know if more children get the correct treatment for childhood illnesses because the certainty of the evidence was very low. – We do not know what the effect is on the number of children who die. – We do not know what the effect is on quality of care, side effects or the number of children who attend healthcare facilities because the studies did not measure this. How up‐to‐date is this review? The review authors searched for studies that had been published up to 7 November 2019.

Background A well‐functioning routine health information system (RHIS) can provide the information needed for health system management, for governance, accountability, planning, policy making, surveillance and quality improvement, but poor information support has been identified as a major obstacle for improving health system management. Objectives To assess the effects of interventions to improve routine health information systems in terms of RHIS performance, and also, in terms of improved health system management performance, and improved patient and population health outcomes. Search methods We searched the Cochrane Central Register of Controlled Trials (CENTRAL) in the Cochrane Library, MEDLINE Ovid and Embase Ovid in May 2019. We searched Global Health, Ovid and PsycInfo in April 2016. In January 2020 we searched for grey literature in the Grey Literature Report and in OpenGrey, and for ongoing trials using the International Clinical Trials Registry Platform (ICTRP) and ClinicalTrials.gov. In October 2019 we also did a cited reference search using Web of Science, and a ‘similar articles’ search in PubMed. Selection criteria Randomised and non‐randomised trials, controlled before‐after studies and time‐series studies comparing routine health information system interventions, with controls, in primary, hospital or community health care settings. Participants included clinical staff and management, district management and community health workers using routine information systems. Data collection and analysis Two authors independently reviewed records to identify studies for inclusion, extracted data from the included studies and assessed the risk of bias. Interventions and outcomes were too varied across studies to allow for pooled risk analysis. We present a 'Summary of findings' table for each intervention comparisons broadly categorised into Technical and Organisational (or a combination), and report outcomes on data quality and service quality. We used the GRADE approach to assess the certainty of the evidence. Main results We included six studies: four cluster randomised trials and two controlled before‐after studies, from Africa and South America. Three studies evaluated technical interventions, one study evaluated an organisational intervention, and two studies evaluated a combination of technical and organisational interventions. Four studies reported on data quality and six studies reported on service quality. In terms of data quality, a web‐based electronic TB laboratory information system probably reduces the length of time to reporting of TB test results, and probably reduces the overall rate of recording errors of TB test results, compared to a paper‐based system (moderate certainty evidence). We are uncertain about the effect of the electronic laboratory information system on the recording rate of serious (misidentification) errors for TB test results compared to a paper‐based system (very low certainty evidence). Misidentification errors are inaccuracies in transferring test results between an electronic register and patients' clinical charts. We are also uncertain about the effect of the intervention on service quality (timeliness of starting or changing a patient's TB treatment) (very low certainty evidence). A hand‐held electronic device probably improves the length of time to report TB test results, and probably reduces the total frequency of recording errors in TB test results between the laboratory notebook and the electronic information record system, compared to a paper‐based system (moderate‐certainty evidence). We are, however, uncertain about the effect of the intervention on the frequency of serious (misidentification) errors in recording between the laboratory notebook and the electronic information record, compared to a paper‐based system (very low certainty evidence). We are uncertain about the effect of a hospital electronic health information system on service quality (length of time outpatients spend at hospital, length of hospital stay, and hospital revenue collection), compared to a paper‐based system (very low certainty evidence). High‐intensity brief text messaging (SMS) may make little or no difference to data quality (in terms of completeness of documentation of pregnancy outcomes), compared to low‐intensity brief text messaging (low‐certainty evidence). We are uncertain about the effect of electronic drug stock notification (with either data management support or product transfer support) on service quality (in terms of transporting stock and stock levels), compared to paper‐based stock notification (very low certainty evidence). We are uncertain about the effect of health information strengthening (where it is part of comprehensive service quality improvement intervention) on service quality (health worker motivation, receipt of training by health workers, health information index scores, quality of clinical observation of children and adults) (very low certainty evidence). Authors' conclusions The review indicates mixed effects of mainly technical interventions to improve data quality, with gaps in evidence on interventions aimed at enhancing data‐informed health system management. There is a gap in interventions studying information support beyond clinical management, such as for human resources, finances, drug supply and governance. We need to have a better understanding of the causal mechanisms by which information support may affect change in management decision‐making, to inform robust intervention design and evaluation methods., Plain language summary Making improvements to routine health information systems to strengthen the management of health systems For health services and systems to function well, managers need a routine information system that produces reliable information about how well these services are working and that supports the use of this information to improve services. The aim of this Cochrane Review was to see if different ways of improving the routine information system could improve the quality and use of this information and the quality and use of health services. The review authors collected and analysed all relevant studies to answer this question and found six studies. Key messages Moving from paper‐based information systems to electronic and digital systems probably allows staff at healthcare facilities to collect some types of routine health information faster and with fewer mistakes. But there are many evidence gaps, and we still need to know more about the effect of different approaches on information quality and use and on the quality of healthcare services and the broader health system. What was studied in the review? Staff at healthcare facilities usually routinely collect information about the services they provide. This often includes information about their patients’ health and the type of treatments and tests they receive. Managers at different levels of the health system also collect information, for instance about human resources, finances, medicines and supply systems. Managers can then use this information to make decisions about how to organise and improve the services. This is referred to as a “routine health information system”. It is often a paper‐based system, but information can also be gathered through electronic systems. In many countries, these routine systems do not work well. This is often because the information is of poor quality or not that useful. Where good quality information is available, managers do not always use the information effectively to improve services. This may be because they have problems accessing the information, they lack the skills to use the information correctly, or they are not encouraged or supported in their use of the information. In this review, we looked at different ways of improving routine health information systems and the effect this has on the quality and use of the information and the quality of healthcare services and the broader health system. What are the main results of the review? The review authors found six relevant studies from countries in Africa and South America. Some of the studies assessed whether electronic systems were better than paper‐based systems. Some of the studies also looked at other ways of improving the system, for instance by using SMS mobile‐phone systems to help health workers and other staff notify central systems about supply levels, register patients, or monitor patients’ health. What effect do these types of systems have on the quality and use of the information that is collected and on health service and systems quality? ‐ When healthcare staff use electronic and digital information systems to document and communicate tuberculosis (TB) laboratory test results, compared to paper‐based systems, test results are probably reported faster and with fewer mistakes overall. But we do not know if these new systems lead to fewer serious mistakes (such as giving the wrong test results for a patient when moving information from the laboratory system to the clinic system), because the certainty of the evidence is very low. ‐ When community health workers are sent frequent text‐messages (SMS) motivating them to collect information about pregnancies, births and newborn deaths, this may make little or no difference to the quality of the information that is reported, compared to less frequent messages. We do not know what the effects of other approaches to system improvements are on information quality and use or on the quality of the services because evidence is lacking or of very low certainty. How up to date is this review? The review authors searched for studies that had been published up to May 2019.

In a deinstitutionalised mental health care system, those with mental illness require complex, multidisciplinary and intersectoral care at the primary or community service setting. This paper describes an Evidence Map of different strategies to strengthen the provision of mental health care at the primary health care (PHC) setting, the quality of the evidence, and knowledge gaps. Electronic and reference searching yielded 2666 articles of which 306 qualified for data extraction. A systematic review methodology identified nine different strategies that strengthen the provision of mental healthcare and these strategies are mapped in line with the outcomes they affect. The top three strategies that were reported the most, included strategies to empower families, carers and patients; integration of care or collaborative interventions; and e-health interventions. The least reported strategy was task shifting. The Evidence Map further shows the amount and quality of evidence supporting each of the listed strategies, and this helps to inform policy design and research priorities around mental health. This is the first systematic Evidence Map to show the different strategies that strengthen the provision of mental healthcare at PHC setting and the impact these strategies have on patient, hospital and societal level indicators.

Background Contracting out of governmental health services is a financing strategy that governs the way in which public sector funds are used to have services delivered by non-governmental health service providers (NGPs). It represents a contract between the government and an NGP, detailing the mechanisms and conditions by which the latter should provide health care on behalf of the government. Contracting out is intended to improve the delivery and use of healthcare services. This Review updates a Cochrane Review first published in 2009. Objectives To assess effects of contracting out governmental clinical health services to non-governmental service provider/s, on (i) utilisation of clinical health services; (ii) improvement in population health outcomes; (iii) improvement in equity of utilisation of these services; (iv) costs and cost-effectiveness of delivering the services; and (v) improvement in health systems performance. Search methods We searched CENTRAL, MEDLINE, Embase, NHS Economic Evaluation Database, EconLit, ProQuest, and Global Health on 07 April 2017, along with two trials registers - ClinicalTrials.gov and the International Clinical Trials Registry Platform - on 17 November 2017. Selection criteria Individually randomised and cluster-randomised trials, controlled before-after studies, interrupted time series, and repeated measures studies, comparing government-delivered clinical health services versus those contracted out to NGPs, or comparing different models of non-governmental-delivered clinical health services. Data collection and analysis Two authors independently screened all records, extracted data from the included studies and assessed the risk of bias. We calculated the net effect for all outcomes. A positive value favours the intervention whilst a negative value favours the control. Effect estimates are presented with 95% confidence intervals. We used the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach to assess the certainty of the evidence and we prepared a Summary of Findings table. Main results We included two studies, a cluster-randomised trial conducted in Cambodia, and a controlled before-after study conducted in Guatemala. Both studies reported that contracting out over 12 months probably makes little or no difference in (i) immunisation uptake of children 12 to 24 months old (moderate-certainty evidence), (ii) the number of women who had more than two antenatal care visits (moderate-certainty evidence), and (iii) female use of contraceptives (moderate-certainty evidence).The Cambodia trial reported that contracting out may make little or no difference in the mortality over 12 months of children younger than one year of age (net effect = -4.3%, intervention effect P = 0.36, clustered standard error (SE) = 3.0%; low-certainty evidence), nor to the incidence of childhood diarrhoea (net effect = -16.2%, intervention effect P = 0.07, clustered SE = 19.0%; low-certainty evidence). The Cambodia study found that contracting out probably reduces individual out-of-pocket spending over 12 months on curative care (net effect = $ -19.25 (2003 USD), intervention effect P = 0.01, clustered SE = $ 5.12; moderate-certainty evidence). The included studies did not report equity in the use of clinical health services and in adverse effects. Authors' conclusions This update confirms the findings of the original review. Contracting out probably reduces individual out-of-pocket spending on curative care (moderate-certainty evidence), but probably makes little or no difference in other health utilisation or service delivery outcomes (moderate- to low-certainty evidence). Therefore, contracting out programmes may be no better or worse than government-provided services, although additional rigorously designed studies may change this result. The literature provides many examples of contracting out programmes, which implies that this is a feasible response when governments fail to provide good clinical health care. Future contracting out programmes should be framed within a rigorous study design to allow valid and reliable measures of their effects. Such studies should include qualitative research that assesses the views of programme implementers and beneficiaries, and records implementation mechanisms. This approach may reveal enablers for, and barriers to, successful implementation of such programmes.

Summary box Against a background of rapid scale-up of new policies and guidelines in the context of weak health systems in low/middle-income countries (LMIC), implementation research is especially important for understanding the ‘evidence-implementation’ gap. Implementation research investigates the various factors that affect how a new health policy or intervention may be implemented in usual practice settings and the contextual factors that affect implementation at scale.1–4 A wide range of qualitative and quantitative methods can be used in implementation research including: pragmatic trials, quality improvement studies, participatory action research and mixed methods evaluation studies where both quantitative and qualitative methods of data collection and analysis are used in the same study.1 There has been an increase in funder requests for research proposals that document and evaluate implementation strategies and impacts of large-scale health interventions aimed at supporting the delivery of health services, programmes and policies.5 The concomitant emergence of ‘global health’ as a field within North American and European universities (referred to here as the ‘Global North’) has led to a plethora of institutions who commission, undertake and collaborate on implementation research within LMIC settings (referred to here as the ‘Global South’), sometimes as part of countries’ overseas development assistance (ODA). …

Unfortunately, the original version of this article [1] contained an error in abstract S1. The corresponding author for the abstract ‘Gabriele Meyer’ was included in the 'Correspondence' section but accidentally omitted from the author list. The correct author list should be as below: Gabriele Meyer1*, Sascha Kopke2, Jane Noyes3, Jackie Chandler4 1Martin Luther University Halle-Wittenberg, Magdeburger Str. 8, D-06112 Halle (Saale), Germany 2University of Lubeck, Germany 3Bangor University, UK 4Cochrane Collaboration, Oxford, UK Correspondence: Gabriele Meyer (Gabriele.Meyer@medizin.uni-halle.de) – Martin Luther University Halle-Wittenberg, Magdeburger Str. 8, D-06112 Halle (Saale), Germany

In the 21st century, it is more obvious than ever before that health services research and its practitioners exist in an extremely complex contextual environment. Consequently, at the heart of unde ...

BACKGROUND: Formative programme evaluations assess intervention implementation processes, and are seen widely as a way of unlocking the 'black box' of any programme in order to explore and understand why a programme functions as it does. However, few critical assessments of the methods used in such evaluations are available, and there are especially few that reflect on how well the evaluation achieved its objectives. This paper describes a formative evaluation of a community-based lay health worker programme for TB and HIV/AIDS clients across three low-income communities in South Africa. It assesses each of the methods used in relation to the evaluation objectives, and offers suggestions on ways of optimising the use of multiple, mixed-methods within formative evaluations of complex health system interventions. METHODS: The evaluation's qualitative methods comprised interviews, focus groups, observations and diary keeping. Quantitative methods included a time-and-motion study of the lay health workers' scope of practice and a client survey. The authors conceptualised and conducted the evaluation, and through iterative discussions, assessed the methods used and their results. RESULTS: Overall, the evaluation highlighted programme issues and insights beyond the reach of traditional single methods evaluations. The strengths of the multiple, mixed-methods in this evaluation included a detailed description and nuanced understanding of the programme and its implementation, and triangulation of the perspectives and experiences of clients, lay health workers, and programme managers. However, the use of multiple methods needs to be carefully planned and implemented as this approach can overstretch the logistic and analytic resources of an evaluation. CONCLUSIONS: For complex interventions, formative evaluation designs including multiple qualitative and quantitative methods hold distinct advantages over single method evaluations. However, their value is not in the number of methods used, but in how each method matches the evaluation questions and the scientific integrity with which the methods are selected and implemented. BioMed Central open access