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Study protocol for the SMART2D adaptive implementation trial: a cluster randomised trial comparing facility-only care with integrated facility and community care to improve type 2 diabetes outcomes in Uganda, South Africa and Sweden.

ABSTRACT: INTRODUCTION:Type 2 diabetes (T2D) is increasingly contributing to the global burden of disease. Health systems in most parts of the world are struggling to diagnose and manage T2D, especially in low-income and middle-income countries, and among disadvantaged populations in high-income countries. The aim of this study is to determine the added benefit of community interventions onto health facility interventions, towards glycaemic control among persons with diabetes, and towards reduction in plasma glucose among persons with prediabetes. METHODS AND ANALYSIS:An adaptive implementation cluster randomised trial is being implemented in two rural districts in Uganda with three clusters per study arm, in an urban township in South Africa with one cluster per study arm, and in socially disadvantaged suburbs in Stockholm, Sweden with one cluster per study arm. Clusters are communities within the catchment areas of participating primary healthcare facilities. There are two study arms comprising a facility plus community interventions arm and a facility-only interventions arm. Uganda has a third arm comprising usual care. Intervention strategies focus on organisation of care, linkage between health facility and the community, and strengthening patient role in self-management, community mobilisation and a supportive environment. Among T2D participants, the primary outcome is controlled plasma glucose; whereas among prediabetes participants the primary outcome is reduction in plasma glucose. ETHICS AND DISSEMINATION:The study has received approval in Uganda from the Higher Degrees, Research and Ethics Committee of Makerere University School of Public Health and from the Uganda National Council for Science and Technology; in South Africa from the Biomedical Science Research Ethics Committee of the University of the Western Cape; and in Sweden from the Regional Ethical Board in Stockholm. Findings will be disseminated through peer-reviewed publications and scientific meetings. TRIAL REGISTRATION NUMBER:ISRCTN11913581; Pre-results.

SUBMITTER: Guwatudde D

PROVIDER: S-EPMC5879646 | biostudies-literature | 2018 Mar

REPOSITORIES: biostudies-literature

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Study protocol for the SMART2D adaptive implementation trial: a cluster randomised trial comparing facility-only care with integrated facility and community care to improve type 2 diabetes outcomes in Uganda, South Africa and Sweden.

Guwatudde David D Absetz Pilvikki P Delobelle Peter P Östenson Claes-Göran CG Olmen Van Josefien J Alvesson Helle Molsted HM Mayega Roy William RW Ekirapa Kiracho Elizabeth E Kiguli Juliet J Sundberg Carl Johan CJ Sanders David D Tomson Göran G Puoane Thandi T Peterson Stefan S Daivadanam Meena M

BMJ open 20180317 3

<h4>Introduction</h4>Type 2 diabetes (T2D) is increasingly contributing to the global burden of disease. Health systems in most parts of the world are struggling to diagnose and manage T2D, especially in low-income and middle-income countries, and among disadvantaged populations in high-income countries. The aim of this study is to determine the added benefit of community interventions onto health facility interventions, towards glycaemic control among persons with diabetes, and towards reductio ...[more]

PMID: 29550780

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Project description:BackgroundThe effects of two interventions, Integrated Management of Infectious Disease (IMID) training program and On-Site Support (OSS), were tested on 23 facility performance indicators for emergency triage assessment and treatment (ETAT), malaria, pneumonia, tuberculosis, and HIV.MethodsThe trial was implemented in 36 primary care facilities in Uganda. From April 2010, two mid-level practitioners per facility participated in IMID training. Eighteen of 36 facilities were randomly assigned to Arm A, and received OSS in 2010 (nine monthly two-day sessions); 18 facilities assigned to Arm B did not receive OSS in 2010. Data were collected from Nov 2009 to Dec 2010 using a revised Ministry of Health outpatient medical form and nine registers. We analyzed the effect of IMID training alone by measuring changes before and during IMID training in Arm B, the combined effect of IMID training and OSS by measuring changes in Arm A, and the incremental effect of OSS by comparing changes across Arms A and B.ResultsIMID training was associated with statistically significant improvement in three indicators: outpatients triaged (adjusted relative risks (aRR)?=?1.29, 99%CI?=?1.01,1.64), emergency and priority patients admitted, detained, or referred (aRR?=?1.59, 99%CI?=?1.04,2.44), and pneumonia suspects assessed (aRR?=?2.31, 99%CI?=?1.50,3.55). IMID training and OSS combined was associated with improvements in six indicators: three ETAT indicators (outpatients triaged (aRR?=?2.03, 99%CI?=?1.13,3.64), emergency and priority patients admitted, detained or referred (aRR?=?3.03, 99%CI?=?1.40,6.56), and emergency patients receiving at least one appropriate treatment (aRR?=?1.77, 99%CI?=?1.10,2.84)); two malaria indicators (malaria cases receiving appropriate antimalarial (aRR?=?1.50, 99%CI?=?1.04,2.17), and patients with negative malaria test results prescribed antimalarial (aRR?=?0.67, 99%CI?=?0.46,0.97)); and enrollment in HIV care (aRR?=?1.58, 99%CI?=?1.32,1.89). OSS was associated with incremental improvement in emergency patients receiving at least one appropriate treatment (adjusted ratio of RR?=?1.84,99%CI?=?1.09,3.12).ConclusionThe trial showed that the OSS intervention significantly improved performance in one of 23 facility indicators.

Project description:BackgroundClassroom-based learning is often insufficient to ensure high quality care and application of health care guidelines. Educational outreach is garnering attention as a supplemental method to enhance health care worker capacity, yet there is little information about the timing and duration required to improve facility performance. We sought to evaluate the effects of an infectious disease training program followed by either immediate or delayed on-site support (OSS), an educational outreach approach, on nine facility performance indicators for emergency triage, assessment, and treatment; malaria; and pneumonia. We also compared the effects of nine monthly OSS visits to extended OSS, with three additional visits over six months.MethodsThis study was conducted at 36 health facilities in Uganda, covering 1,275,960 outpatient visits over 23 months. From April 2010 to December 2010, 36 sites received infectious disease training; 18 randomly selected sites in arm A received nine monthly OSS visits (immediate OSS) and 18 sites in arm B did not. From March 2011 to September 2011, arm A sites received three additional visits every two months (extended OSS), while the arm B sites received eight monthly OSS visits (delayed OSS). We compared the combined effect of training and delayed OSS to training followed by immediate OSS to determine the effect of delaying OSS implementation by nine months. We also compared facility performance in arm A during the extended OSS to immediate OSS to examine the effect of additional, less frequent OSS.ResultsDelayed OSS, when combined with training, was associated with significant pre/post improvements in four indicators: outpatients triaged (44% vs. 87%, aRR = 1.54, 99% CI = 1.11, 2.15); emergency and priority patients admitted, detained, or referred (16% vs. 31%, aRR = 1.74, 99% CI = 1.10, 2.75); patients with a negative malaria test result prescribed an antimalarial (53% vs. 34%, aRR = 0.67, 99% CI = 0.55, 0.82); and pneumonia suspects assessed for pneumonia (6% vs. 27%, aRR = 2.97, 99% CI = 1.44, 6.17). Differences between the delayed OSS and immediate OSS arms were not statistically significant for any of the nine indicators (all adjusted relative RR (aRRR) between 0.76-1.44, all p>0.06). Extended OSS was associated with significant improvement in two indicators (outpatients triaged: aRR = 1.09, 99% CI = 1.01; emergency and priority patients admitted, detained, or referred: aRR = 1.22, 99% CI = 1.01, 1.38) and decline in one (pneumonia suspects assessed for pneumonia: aRR: 0.93; 99% CI = 0.88, 0.98).ConclusionsEducational outreach held up to nine months after training had similar effects on facility performance as educational outreach started within one month post-training. Six months of bi-monthly educational outreach maintained facility performance gains, but incremental improvements were heterogeneous.

Project description:BackgroundRural access to health care remains a challenge in Sub-Saharan Africa due to urban bias, social determinants of health, and transportation-related barriers. Health systems in Sub-Saharan Africa often lack equity, leaving disproportionately less health center access for the poorest residents with the highest health care needs. Lack of health care equity in Sub-Saharan Africa has become of increasing concern as countries enter a period of simultaneous high infectious and non-communicable disease burdens, the second of which requires a robust primary care network due to a long continuum of care. Bicycle ownership has been proposed and promoted as one tool to reduce travel-related barriers to health-services among the poor.MethodsAn accessibility analysis was conducted to identify the proportion of Ugandans within one-hour travel time to government health centers using walking, bicycling, and driving scenarios. Statistically significant clusters of high and low travel time to health centers were calculated using spatial statistics. Random Forest analysis was used to explore the relationship between poverty, population density, health center access in minutes, and time saved in travel to health centers using a bicycle instead of walking. Linear Mixed-Effects Models were then used to validate the performance of the random forest models.ResultsThe percentage of Ugandans within a one-hour walking distance of the nearest health center II is 71.73%, increasing to 90.57% through bicycles. Bicycles increased one-hour access to the nearest health center III from 53.05 to 80.57%, increasing access to the tiered integrated national laboratory system by 27.52 percentage points. Significant clusters of low health center access were associated with areas of high poverty and urbanicity. A strong direct relationship between travel time to health center and poverty exists at all health center levels. Strong disparities between urban and rural populations exist, with rural poor residents facing disproportionately long travel time to health center compared to wealthier urban residents.ConclusionsThe results of this study highlight how the most vulnerable Ugandans, who are the least likely to afford transportation, experience the highest prohibitive travel distances to health centers. Bicycles appear to be a "pro-poor" tool to increase health access equity.

Project description:BackgroundBeart failure with reduced ejection fraction (HFrEF) is a leading cause of morbidity and mortality. However, shortfalls in prescribing of proven therapies, particularly mineralocorticoid receptor antagonist (MRA) therapy, account for several thousand preventable deaths per year nationwide. Electronic clinical decision support (CDS) is a potential low-cost and scalable solution to improve prescribing of therapies. However, the optimal timing and format of CDS tools is unknown.Methods and resultsWe developed two targeted CDS tools to inform cardiologists of gaps in MRA therapy for patients with HFrEF and without contraindication to MRA therapy: (1) an alert that notifies cardiologists at the time of patient visit, and (2) an automated electronic message that allows for review between visits. We designed these tools using an established CDS framework and findings from semistructured interviews with cardiologists. We then pilot tested both CDS tools (n = 596 patients) and further enhanced them based on additional semistructured interviews (n = 11 cardiologists). The message was modified to reduce the number of patients listed, include future visits, and list date of next visit. The alert was modified to improve noticeability, reduce extraneous information on guidelines, and include key information on contraindications.ConclusionsThe BETTER CARE-HF (Building Electronic Tools to Enhance and Reinforce CArdiovascular REcommendations for Heart Failure) trial aims to compare the effectiveness of the alert vs. the automated message vs. usual care on the primary outcome of MRA prescribing. To our knowledge, no study has directly compared the efficacy of these two different types of electronic CDS interventions. If effective, our findings can be rapidly disseminated to improve morbidity and mortality for patients with HFrEF, and can also inform the development of future CDS interventions for other disease states. (Trial registration: Clinicaltrials.gov NCT05275920).

Project description:BackgroundDepression is rarely screened for among People Living with Human Immunodeficiency Virus (PLHIV) although it is 2 to 3 times more prevalent among PLHIV than in the general population. In instances where depression is screened for using screening tools, it usually follows noticing depression risk factors. This practice of selectively screening for depression could be leaving some cases of depression unattended to. On the other hand, subjecting every client to screening tools (non-selective screening) offers every patient an opportunity to be managed for depression. However, this could require additional resources as compared to selective screening. We present and discuss results on whether non-selective and selective screening strategies differ in depression case detection, and in addition, we also present perceptions of the stake holders on the two screening strategies.MethodsThe study was conducted in Princess Diana Memorial Health Centre IV HIV clinic using a randomized controlled trial with a qualitative component. To determine whether there was a difference in depression case detection, consecutively sampled participants were randomly allocated to either non-selective or selective screening strategy. Participants allocated to selective screening were screened for depression using the patient health questionnaire (s) (PHQs) if they were at "crisis points". While those allocated to non-selective screening were screened regardless of whether the "crisis points" were noticed or not. The PHQ-2 and PHQ-9 were used in sequence. 326 PLHIV participated in the study. Outcomes of the MINI evaluation were analyzed for those with PHQ-9 scores of 10 or more to confirm major depressive disorder (MDD). Data was analyzed using the two sample Z-test for proportions with Stata 2013 software. To explore the perceptions of the stake holders, key informant interviews were performed with six stakeholders that experienced the study.ResultsCases of depression (PHQ-9 score ≥ 5) were more likely to be detected by the non-selective screening strategy 30.2% (49/162) compared to the selective screening strategy 19.5% (32/164) (difference in proportions 0.107, 95% confidence interval 0.014-0.200, Cohen's h = 0.25, P = 0.03). The stake holders thought it was important to screen for depression among PLHIV with preference to non-selective screening strategy.ConclusionEvidence from this data suggests that more cases of depression (PHQ-9 score ≥ 5) are likely to be detected with non-selective screening as opposed to selective screening.Trial registrationPACTR201802003141213 (name: comparison of routine versus selective screening for depression strategies among PLHIV attending Princess Diana Memorial Health Centre iv Soroti).

Dataset Information

Study protocol for the SMART2D adaptive implementation trial: a cluster randomised trial comparing facility-only care with integrated facility and community care to improve type 2 diabetes outcomes in Uganda, South Africa and Sweden.

Publications

Study protocol for the SMART2D adaptive implementation trial: a cluster randomised trial comparing facility-only care with integrated facility and community care to improve type 2 diabetes outcomes in Uganda, South Africa and Sweden.

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