Implementation of Technology-Delivered Diabetes Self-care Interventions in Clinical Care: a Narrative Review.
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ABSTRACT: Purpose of review
Evidence is growing for the positive effects of technology-delivered diabetes self-care interventions on behavioral and clinical outcomes. However, our understanding of how to effectively implement these interventions into routine clinical practice is limited. This article provides an overview of the methods and results of studies examining the implementation of technology-delivered diabetes self-care interventions into clinical care. We focus specifically on patient-facing behavioral interventions delivered with technology (e.g., text messaging, apps, websites).Recent findings
Eleven articles were included in the review. Most studies (n = 9) examined barriers and facilitators to implementation, while about half (n = 5) integrated the intervention into clinical care and evaluated implementation and/or effectiveness. Only six studies applied a theory or framework. The most common determinants of implementation were time constraints for clinic staff, familiarity with technology, knowledge of the intervention, and perceived value. We found substantial variation in implementation outcomes, including which were reported, how they were assessed, and the results. In the four studies that evaluated effectiveness, hemoglobin A1c improved. Successful implementation of technology-delivered interventions has the potential to transform healthcare delivery and improve diabetes health on a population level. Promising strategies to address common determinants of implementation include appointing a clinic champion, developing staff training and educational materials, and adapting intervention processes to the clinic context. Future research should evaluate these implementation strategies to understand when and how they impact outcomes. Frameworks such as Reach Effectiveness Adoption Implementation Maintenance (RE-AIM) can help ensure outcomes are systematically reported and allow for comparison across studies.
SUBMITTER: Nelson LA
PROVIDER: S-EPMC8188808 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:IntroductionDiabetes is a major risk factor for cardiovascular disease, which is the most significant contributor to increased mortality due to natural causes in those with severe mental illness (SMI). Self-management interventions for diabetes have been shown to be effective in the general population, however, effects of these interventions in those with SMI is still unclear. Psychiatric admission could be used opportunistically to deliver interventions of this kind and help improve diabetes self-management. This review aims to assess whether interventions of this kind improve diabetes outcomes and have an effect on reducing cardiovascular risk.Methods and analysisThis review will include studies assessing diabetes self-management interventions designed to be delivered to those aged 18 and over with comorbid type 2 diabetes and SMI during admission to psychiatric inpatient settings. Databases including the Cochrane Library, Medline, Psychinfo, CINAHL, Embase, WHO's International Clinical Trials Registry Platform, International Health Technology Assessment Database, UK Clinical Research Network and ClinicalTrials.gov will be searched from inception to September 2022. Where possible, meta-analysis of included studies will be conducted. If heterogeneity is high and meta-analysis is not possible, we will use other means of data synthesis and will include a narrative description of included studies.Ethics and disseminationEthical approval is not required as the systematic review will only include data from existing studies. The results will be disseminated via peer-reviewed publication and presentation at relevant national and international conferences.Prospero registration numberCRD42022357672.
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Project description:BackgroundThere is growing interest in enhancing stroke self-management support using mobile health (mHealth) technology (eg, smartphones and apps). Despite this growing interest, "self-management support" is inconsistently defined and applied in the poststroke mHealth intervention literature, which limits efforts to synthesize and compare evidence. To address this gap in conceptual clarity, a scoping review was conducted.ObjectiveThe objectives were to (1) identify and describe the types of poststroke mHealth interventions evaluated using a randomized controlled trial design, (2) determine whether (and how) such interventions align with well-accepted conceptualizations of self-management support (the theory by Lorig and Holman and the Practical Reviews in Self-Management Support [PRISMS] taxonomy by Pearce and colleagues), and (3) identify the mHealth functions that facilitate self-management.MethodsA scoping review was conducted according to the methodology by Arksey and O'Malley and Levac et al. In total, 7 databases were searched. Article screening and data extraction were performed by 2 reviewers. The data were analyzed using descriptive statistics and content analysis.ResultsA total of 29 studies (26 interventions) were included. The interventions addressed 7 focal areas (physical exercise, risk factor management, linguistic exercise, activities of daily living training, medication adherence, stroke education, and weight management), 5 types of mobile devices (mobile phones or smartphones, tablets, wearable sensors, wireless monitoring devices, and laptops), and 7 mHealth functions (educating, communicating, goal setting, monitoring, providing feedback, reminding, and motivating). Collectively, the interventions aligned well with the concept of self-management support. However, on an individual basis (per intervention), the alignment was less strong.ConclusionsOn the basis of the results, it is recommended that future research on poststroke mHealth interventions be more theoretically driven, more multidisciplinary, and larger in scale.
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Project description:Mobile technology interventions (MTI) are becoming increasingly popular in the management of chronic health behaviors. Most MTI allow individuals to monitor medication use, record symptoms, or store and activate disease-management action plans. Therefore, MTI may have the potential to improve low adherence to medication and action plans for individuals with asthma, which is associated with poor clinical outcomes.A systematic review and meta-analysis were conducted to evaluate the efficacy of MTI on clinical outcomes as well as adherence in individuals with asthma. As the use of evidence-based behavior change techniques (BCT) has been shown to improve intervention effects, we also conducted exploratory analyses to determine the role of BCT and engagement with MTI as moderators of MTI efficacy.We searched electronic databases for randomized controlled trials up until June 2016. Random effect models were used to assess the effect of MTI on clinical outcomes as well as adherence to preventer medication or symptom monitoring. Mixed effects models assessed whether the features of the MTI (ie, use of BCT) and how often a person engaged with MTI moderated the effects of MTI.The literature search located 11 studies meeting the inclusion criteria, with 9 providing satisfactory data for meta-analysis. Compared with standard treatment, MTI had moderate to large effect sizes (Hedges g) on medication adherence and clinical outcomes. MTI had no additional effects on adherence or clinical outcomes when compared with paper-based monitoring. No moderator effects were found, and the number of studies was small. A narrative review of the two studies, which are not included in the meta-analysis, found similar results.This review indicated the efficacy of MTI for self-management in individuals with asthma and also indicated that MTI appears to be as efficacious as paper-based monitoring. This review also suggested a need for robust studies to examine the effects of BCT use and engagement on MTI efficacy to inform the evidence base for MTI in individuals with asthma.
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Project description:Primary care providers (PCPs) play an important role in providing medical care for patients with type 2 diabetes. Advancements in diabetes technologies can assist PCPs in providing personalised care that addresses each patient's individual needs. Diabetes technologies fall into two major categories: devices for glycaemic self-monitoring and insulin delivery systems. Monitoring technologies encompass self-measured blood glucose (SMBG), where blood glucose is intermittently measured by a finger prick blood sample, and continuous glucose monitoring (CGM) devices, which use an interstitial sensor and are capable of giving real-time information. Studies show people using real-time CGM have better glucose control compared to SMBG. CGM allows for new parameters including time in range (the time spent within the desired target glucose range), which is an increasingly relevant real-time metric of glycaemic control. Insulin pens have increased the ease of administration of insulin and connected pens that can calculate and capture data on dosing are becoming available. There are a number of websites, software programs, and applications that can help PCPs and patients to integrate diabetes technology into their diabetes management schedules. In this article, we summarise these technologies and provide practical information to inform PCPs about utility in their clinical practice. The guiding principle is that use of technology should be individualised based on a patient's needs, desires, and availability of devices. Diabetes technology can help patients improve their clinical outcomes and achieve the quality of life they desire by decreasing disease burden.KEY MESSAGESIt is important to understand the role that diabetes technologies can play in primary care to help deliver high-quality care, taking into account patient and community resources. Diabetes technologies fall into two major categories: devices for glycaemic self-monitoring and insulin delivery systems. Modern self-measured blood glucose devices are simple to use and can help guide decision making for self-management plans to improve clinical outcomes, but cannot provide "live" data and may under- or overestimate blood glucose; patients' monitoring technique and compliance should be reviewed regularly. Importantly, before a patient is provided with monitoring technology, they must receive suitably structured education in its use and interpretation.Continuous glucose monitoring (CGM) is now standard of care for people with type 1 diabetes and people with type 2 diabetes on meal-time (prandial) insulin. Real-time CGM can tell both the patient and the healthcare provider when glucose is in the normal range, and when they are experiencing hyper- or hypoglycaemia. Using CGM data, changes in lifestyle, eating habits, and medications, including insulin, can help the patient to stay in a normal glycaemic range (70-180 mg/dL). Real-time CGM allows for creation of an ambulatory glucose profile and monitoring of time in range (the time spent within target blood glucose of 70-180 mg/dL), which ideally should be at least 70%; avoiding time above range (>180 mg/dL) is associated with reduced diabetes complications and avoiding time below range (<70 mg/dL) will prevent hypoglycaemia. Insulin pens are simpler to use than syringes, and connected pens capture information on insulin dose and injection timing.There are a number of websites, software programs and applications that can help primary care providers and patients to integrate diabetes technology into their diabetes management schedules. The guiding principle is that use of technology should be individualised based on a patient's needs, desires, skill level, and availability of devices.
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