Suchergebnisse

There is increasing support for sharing individual-level data generated by medical and public health research. This scoping review of empirical research and conceptual literature examined stakeholders' perspectives of ethical best practices in data sharing, particularly in low- and middle-income settings. Sixty-nine empirical and conceptual articles were reviewed, of which, only five were empirical studies and eight were conceptual articles focusing on low- and middle-income settings. We conclude that support for sharing individual-level data is contingent on the development and implementation of international and local policies and processes to support ethical best practices. Further conceptual and empirical research is needed to ensure data sharing policies and processes in low- and middle-income settings are appropriately informed by stakeholders' perspectives.

Abstract Background Governments use fiscal interventions (FIs) on food and beverages to encourage healthy food behaviour and positive health outcomes. The objective of this review was to study the behavioural and health outcomes of implemented food and beverage FIs in the form of taxes and subsidies in countries of different income classifications. Methods The present systematic review was conducted in accordance with Cochrane protocols. The search was carried out on academic and grey literature in English, for studies conducted in different countries on implemented FIs on food and non-alcoholic beverages and health outcomes, with a special focus on the income of those countries. Results Eighteen studies met the inclusion criteria and 14 were from peer- reviewed journals. Thirteen studies came from high-income (HI) countries, four from upper middle-income (UMI) countries and only one came from a lower middle-income (LMI) country. There were no studies from lower-income (LI) countries. Of these 18 studies; nine focused on taxes, all of which were from HI countries. Evidence suggests that FIs on foods can influence consumption of taxed and subsidized foods and consequently have the potential to improve health. Conclusion Although this review supports previous findings that FIs can have an impact on healthy food consumption, it also highlights the lack of evidence available from UMI, LMI and LI countries on such interventions. Therefore, evidence from HI countries may not be directly applicable to middle-income and LI countries. Similar research conducted in middle and low income countries will be beneficial in advocating policy makers on the effectiveness of FIs in countering the growing issues of non-communicable diseases in these countries.

BACKGROUND: Non-communicable diseases are the leading global cause of death and disproportionately afflict those living in low-income and lower-middle-income countries (LLMICs). The association between socioeconomic status and non-communicable disease behavioural risk factors is well established in high-income countries, but it is not clear how behavioural risk factors are distributed within LLMICs. We aimed to systematically review evidence on the association between socioeconomic status and harmful use of alcohol, tobacco use, unhealthy diets, and physical inactivity within LLMICs. METHODS: We searched 13 electronic databases, including Embase and MEDLINE, grey literature, and reference lists for primary research published between Jan 1, 1990, and June 30, 2015. We included studies from LLMICs presenting data on multiple measures of socioeconomic status and tobacco use, alcohol use, diet, and physical activity. No age or language restrictions were applied. We excluded studies that did not allow comparison between more or less advantaged groups. We used a piloted version of the Cochrane Effective Practice and Organisation of Care Group data collection checklist to extract relevant data at the household and individual level from the included full text studies including study type, methods, outcomes, and results. Due to high heterogeneity, we used a narrative approach for data synthesis. We used descriptive statistics to assess whether the prevalence of each risk factor varied significantly between members of different socioeconomic groups. The study protocol is registered with PROSPERO, number CRD42015026604. FINDINGS: After reviewing 4242 records, 75 studies met our inclusion criteria, representing 2 135 314 individuals older than 10 years from 39 LLMICs. Low socioeconomic groups were found to have a significantly higher prevalence of tobacco and alcohol use than did high socioeconomic groups. These groups also consumed less fruit, vegetables, fish, and fibre than those of high socioeconomic status. High socioeconomic groups were found to be less physically active and consume more fats, salt, and processed food than individuals of low socioeconomic status. While the included studies presented clear patterns for tobacco use and physical activity, heterogeneity between dietary outcome measures and a paucity of evidence around harmful alcohol use limit the certainty of these findings. INTERPRETATION: Despite significant heterogeneity in exposure and outcome measures, clear evidence shows that the burden of behavioural risk factors is affected by socioeconomic position within LLMICs. Governments seeking to meet Sustainable Development Goal (SDG) 3.4-reducing premature non-communicable disease mortality by a third by 2030-should leverage their development budgets to address the poverty-health nexus in these settings. Our findings also have significance for health workers serving these populations and policy makers tasked with preventing and controlling the rise of non-communicable diseases. FUNDING: WHO.

Background Non-communicable diseases are the leading global cause of death and disproportionately afflict those living in low-income and lower-middle-income countries (LLMICs). The association between socioeconomic status and non-communicable disease behavioural risk factors is well established in high-income countries, but it is not clear how behavioural risk factors are distributed within LLMICs. We aimed to systematically review evidence on the association between socioeconomic status and harmful use of alcohol, tobacco use, unhealthy diets, and physical inactivity within LLMICs. Methods We searched 13 electronic databases, including Embase and MEDLINE, grey literature, and reference lists for primary research published between Jan 1, 1990, and June 30, 2015. We included studies from LLMICs presenting data on multiple measures of socioeconomic status and tobacco use, alcohol use, diet, and physical activity. No age or language restrictions were applied. We excluded studies that did not allow comparison between more or less advantaged groups. We used a piloted version of the Cochrane Effective Practice and Organisation of Care Group data collection checklist to extract relevant data at the household and individual level from the included full text studies including study type, methods, outcomes, and results. Due to high heterogeneity, we used a narrative approach for data synthesis. We used descriptive statistics to assess whether the prevalence of each risk factor varied significantly between members of different socioeconomic groups. The study protocol is registered with PROSPERO, number CRD42015026604. Findings After reviewing 4242 records, 75 studies met our inclusion criteria, representing 2 135 314 individuals older than 10 years from 39 LLMICs. Low socioeconomic groups were found to have a significantly higher prevalence of tobacco and alcohol use than did high socioeconomic groups. These groups also consumed less fruit, vegetables, fish, and fibre than those of high socioeconomic status. High socioeconomic groups were found to be less physically active and consume more fats, salt, and processed food than individuals of low socioeconomic status. While the included studies presented clear patterns for tobacco use and physical activity, heterogeneity between dietary outcome measures and a paucity of evidence around harmful alcohol use limit the certainty of these findings. Interpretation Despite significant heterogeneity in exposure and outcome measures, clear evidence shows that the burden of behavioural risk factors is affected by socioeconomic position within LLMICs. Governments seeking to meet Sustainable Development Goal (SDG) 3.4—reducing premature non-communicable disease mortality by a third by 2030—should leverage their development budgets to address the poverty-health nexus in these settings. Our findings also have significance for health workers serving these populations and policy makers tasked with preventing and controlling the rise of non-communicable diseases.

BACKGROUND: The association between poverty and health is highly context-specific; in high-income countries, low socioeconomic status is associated with use of tobacco and alcohol, physical inactivity, and poor diet. We lack good quality epidemiological evidence from developing countries, especially from low and lower middle-income countries (LLMICs). This systematic review sought to fill this gap. METHODS: We conducted a comprehensive literature search for primary research published between Jan 1, 1990, and June 30, 2015, using 13 electronic databases, including Embase and Medline, as well as a grey literature review and hand searching of references. Two reviewers independently screened papers retrieved from 13 databases with a search devised by an experienced medical librarian combining MeSH terms and synonyms for non-communicable diseases, behavioural risk factors, poverty, and the 84 LLMICs defined by the World Bank. We included studies from LLMICs that presented data on multiple measures of socioeconomic status and tobacco use, alcohol use, diet, and physical activity. We performed narrative data synthesis. FINDINGS: After review of 4242 records, 75 studies met our inclusion criteria, representing 2 135 314 individuals aged more than 10 years from 39 LLMICs. Most studies found that, compared with high socioeconomic groups, lower status groups had a high prevalence of tobacco and alcohol use (odds ratios up to 18·8 and 3·5, respectively). Most studies also found that lower socioeconomic groups consumed less fruit, vegetables, fish, and fibre (odds ratios negligible to 12·9, depending on context). Higher socioeconomic groups were up to 4·4 times less physically active and consumed more fats, salt, and processed food; however, these dietary studies tended to be smaller with wide confidence intervals. INTERPRETATION: Despite variation in exposure and outcome measures, there is clear evidence that the burden of behavioural risk factors is affected by socioeconomic position within LLMICs. Governments seeking to meet Sustainable Development Goal 3.4—reducing premature mortality from non-communicable diseases by a third by 2030—should leverage their development budgets to address the poverty–health nexus in these settings. Our findings are also important for health workers serving these populations, and for policymakers tasked with preventing and controlling the rise of non-communicable diseases.

BACKGROUND: Africa bears 24% of the global burden of disease but has only 3% of the world's health workers. Substantial variation in health worker performance adds to the negative impact of this significant shortfall. We therefore sought to identify interventions implemented in sub-Saharan African aiming to improve health worker performance and the contextual factors likely to influence local effectiveness. METHODS AND FINDINGS: A systematic search for randomised controlled trials of interventions to improve health worker performance undertaken in sub-Saharan Africa identified 41 eligible trials. Data were extracted to define the interventions' components, calculate the absolute improvement in performance achieved, and document the likelihood of bias. Within-study variability in effect was extracted where reported. Statements about contextual factors likely to have modified effect were subjected to thematic analysis. Interventions to improve health worker performance can be very effective. Two of the three trials assessing mortality impact showed significant reductions in death rates (age<5 case fatality 5% versus 10%, p<0.01; maternal in-hospital mortality 6.8/1000 versus 10.3/1000; p<0.05). Eight of twelve trials focusing on prescribing had a statistically significant positive effect, achieving an absolute improvement varying from 9% to 48%. However, reported range of improvement between centres within trials varied substantially, in many cases exceeding the mean effect. Nine contextual themes were identified as modifiers of intervention effect across studies; most frequently cited were supply-line failures, inadequate supervision or management, and failure to follow-up training interventions with ongoing support, in addition to staff turnover. CONCLUSIONS: Interventions to improve performance of existing staff and service quality have the potential to improve patient care in underserved settings. But in order to implement interventions effectively, policy makers need to understand and address the contextual factors which can contribute to differences in local effect. Researchers therefore must recognise the importance of reporting how context may modify effect size.

Abstract Background Currently there is no framework for those involved in the identification, evaluation and prioritisation of new diagnostic technologies. Therefore we aimed to develop prioritisation criteria for the assessment of new diagnostic technologies, by gaining international consensus on not only which criteria should be used, but also their relative importance. Methods A two-round Delphi process was used to generate consensus amongst an international panel of twenty-six experts on priority criteria for diagnostic health technology assessment. Participants represented a range of health care and related professions, including government, industry, health services and academia. Results Based on the responses to the first questionnaire 18 criteria were placed into three categories: high, intermediate and moderate priority. For 16 of the 18 criteria, agreement with the categorisation of the criteria into the high, intermediate and moderate categories was high at ≥ 70% (10 had agreement ≥ 80%). A further questionnaire and panel discussion reduced the criteria to 16 and two categories; seven were classified as high priority and nine intermediate. Conclusions This study proposes an objective structure of prioritisation criteria to use when assessing new diagnostic technologies, based on an expert consensus process. The value of these criteria is that no one single component should be used as the decisive driver for prioritisation of new diagnostic technologies for adoption in healthcare settings. Future studies should be directed at establishing the value of these prioritisation criteria across a range of healthcare settings.

INTRODUCTION: There has been a recent trend towards creating larger primary care practices with the assumption that interdisciplinary teams can deliver improved and more cost-effective services to patients with better accessibility. Micro-teams have been proposed to mitigate some of the potential challenges with practice expansion, including continuity of care. We aim to review the available literature to improve understanding of how micro-teams are described and the opportunities which primary care micro-teams can provide for practice staff and patients and limitations to their introduction and implementation. Our review asks: how is micro-team implementation described? What are the experiences of healthcare professionals and patients concerning micro-teams in primary care? What are the reported implications of micro-teams for patient care? METHODS AND ANALYSIS: CINAHL, Cochrane Library, Embase, MEDLINE and Scopus will be searched for studies in English. Grey literature will be sourced from Google Scholar, government websites, CCG websites, general practice directives and strategies with advice from stakeholders. Included studies will give evidence regarding the implementation of micro-teams. Data will be synthesised using framework analysis. We will use iterative stakeholder and public and patient participation to embed the perspectives of those whom micro-teams could impact. Included studies will be quality assessed using the Mixed Methods Appraisal Tool. The quality assessment will not be used to exclude any evidence but rather to develop a narrative discussion evaluating included literature. ETHICS AND DISSEMINATION: Ethical approval will not be necessary for this systematic review as there will only be a secondary analysis of data already available in scientific databases and the grey literature. This protocol has been submitted for registration to be made available on a review database (PROSPERO). Findings will be disseminated widely through peer-reviewed publication and in various media, for example, ...

The improvement of perinatal mental health forms part of the World Health Organization's Millennium Development goals. However, research suggests implementation of perinatal mental healthcare is variable. To ensure successful implementation, barriers and facilitators to implementing perinatal mental health services need to be identified. The objectives of this review were to determine the barriers and facilitators to implementing perinatal mental health assessment, care, referral and treatment into health and social care services. A systematic review was carried out by conducting literature searches in CINAHL (1982- present); Embase (1974 – present); Medline (1946- present); and PsycINFO (1806 – present). The date of the last search was 11th December 2019 and forward and backward were completed by the 31st March 2020. Studies were included if they made statements about factors that either facilitated or impeded implementation of perinatal mental health assessment, care, or treatment. Partial (10%) dual screening and data extraction was carried out. Data were analysed using thematic synthesis. A total of 46 studies were included in the review. Implementation occurred in a wide range of settings. Implementation was affected by individual (e.g. inability to attend), healthcare professional (e.g. training), interpersonal (e.g. trusting relationships), organisational (e.g. clear referral pathways), political (e.g. funding) and societal factors (stigma and culture). There are a complex range of barriers and facilitators that can support the implementation of perinatal mental health policy and practice. Perinatal mental health services should be flexible, woman-centred and delivered by well-trained healthcare professionals working within a structure that facilitates continuity of carer. Strategies that can be used to improve implementation include, but are not limited to, co-production of services, implementation team meetings, funding and coalition building. Future research should focus on implementation barriers and ...

The improvement of perinatal mental health formed part of WHO's Millennium Development Goals. Research suggests that the implementation of perinatal mental health care is variable. To ensure successful implementation, barriers and facilitators to implementing perinatal mental health services need to be identified. Therefore, we aimed to identify the barriers and facilitators to implementing assessment, care, referral, and treatment for perinatal mental health into health and social care services. In this systematic review, we searched CINAHL, Embase, MEDLINE, and PsycINFO with no language restrictions for primary research articles published between database inception and Dec 11, 2019. Forward and backward searches of included studies were completed by March 31, 2020. Studies were eligible if they made statements about factors that either facilitated or impeded the implementation of perinatal mental health assessment, care, referral, or treatment. Partial (10%) dual screening was done. Data were extracted with EPPI-Reviewer 4 and analysed by use of a thematic synthesis. The protocol is registered on PROSPERO, CRD42019142854. Database searching identified 21 535 citations, of which 46 studies were included. Implementation occurred in a wide range of settings and was affected by individual (eg, an inability to attend treatment), health-care professional (eg, training), interpersonal (eg, trusting relationships), organisational (eg, clear referral pathways), political (eg, funding), and societal factors (eg, stigma and culture). A complex range of barriers and facilitators affect the implementation of perinatal mental health policy and practice. Perinatal mental health services should be flexible and women-centred, and delivered by well trained health-care professionals working within a structure that facilitates continuity of carer. Strategies that can be used to improve implementation include, but are not limited to, co-production of services, implementation team meetings, funding, and coalition building. Future research should focus on implementation barriers and facilitators dependent on illness severity, the health-care setting, and inpatient care.