Computerized prompting and feedback of diabetes care: a review of the literature

Identification of barriers to insulin therapy and approaches to overcoming them

Poor glycaemic control in type 2 diabetes (T2D) is a global problem despite the availability of numerous glucose-lowering therapies and clear guidelines for T2D management. Tackling clinical or therapeutic inertia, where the person with diabetes and/or their healthcare providers do not intensify treatment regimens despite this being appropriate, is key to improving patients' long-term outcomes. This gap between best practice and current level of care is most pronounced when considering insulin regimens, with studies showing that insulin initiation/intensification is frequently and inappropriately delayed for several years. Patient- and physician-related factors both contribute to this resistance at the stages of insulin initiation, titration and intensification, impeding achievement of optimal glycaemic control. The present review evaluates the evidence and reasons for this delay, together with available methods for facilitation of insulin initiation or intensification.

Telemedicine for diabetes care: An Indian perspective - feasibility and efficacy

Diabetes is a chronic and costly disease. In India, the usual practice among patients is to visit the doctor once in every 2-3 months to get advice on changes in the dosages of medications. The Diabetes Tele Management System (DTMS(®)) is a telemedicine based follow-up program originally introduced at Jothydev's Diabetes Research Centre at Trivandrum South India in 1998. It is a chronic disease management system which enables patient to interact lively with a professionally trained multidisciplinary team comprising of diabetes educators, nurses, dieticians, pharmacists, psychologists, physicians, etc., in modifying the dosages of medications, diet, and physical activity either through telephone/email/secure website. The uniquely designed software and the trained multidisciplinary team overcomes the globally recognized major barriers to diabetes management namely fear of hypoglycemia, polypharmacy, discontinuation of stains, and antihypertensives or wrong injection techniques. DTMS is designed to provide individualized therapy advices on glycosylated hemoglobin, blood pressure, and low density lipoprotein customized to multiple patient characteristics which help attain goals of therapy. The system has been tested on various platforms over a decade and was shown to be a patient friendly approach with successful outcomes due to a live "round-the-clock" interactive communication in contrast to text or recorded messages. The major challenge to the widespread use of DTMS(®) is seeking a source of funding this unique telemedicine program.

Overcoming Clinical Inertia: A Randomized Clinical Trial of a Telehealth Remote Monitoring Intervention Using Paired Glucose Testing in Adults With Type 2 Diabetes

Background

Type 2 diabetes mellitus is a worldwide challenge. Practice guidelines promote structured self-monitoring of blood glucose (SMBG) for informing health care providers about glycemic control and providing patient feedback to increase knowledge, self-efficacy, and behavior change. Paired glucose testing—pairs of glucose results obtained before and after a meal or physical activity—is a method of structured SMBG. However, frequent access to glucose data to interpret values and recommend actions is challenging. A complete feedback loop—data collection and interpretation combined with feedback to modify treatment—has been associated with improved outcomes, yet there remains limited integration of SMBG feedback in diabetes management. Incorporating telehealth remote monitoring and asynchronous electronic health record (EHR) feedback from certified diabetes educators (CDEs)—specialists in glucose pattern management—employ the complete feedback loop to improve outcomes.

Objective

The purpose of this study was to evaluate a telehealth remote monitoring intervention using paired glucose testing and asynchronous data analysis in adults with type 2 diabetes. The primary aim was change in glycated hemoglobin (A_1c)—a measure of overall glucose management—between groups after 6 months. The secondary aims were change in self-reported Summary of Diabetes Self-Care Activities (SDSCA), Diabetes Empowerment Scale, and Diabetes Knowledge Test.

Methods

A 2-group randomized clinical trial was conducted comparing usual care to telehealth remote monitoring with paired glucose testing and asynchronous virtual visits. Participants were aged 30-70 years, not using insulin with A_1c levels between 7.5% and 10.9% (58-96 mmol/mol). The telehealth remote monitoring tablet computer transmitted glucose data and facilitated a complete feedback loop to educate participants, analyze actionable glucose data, and provide feedback. Data from paired glucose testing were analyzed asynchronously using computer-assisted pattern analysis and were shared with patients via the EHR weekly. CDEs called participants monthly to discuss paired glucose testing trends and treatment changes. Separate mixed-effects models were used to analyze data.

Results

Participants (N=90) were primarily white (64%, 56/87), mean age 58 (SD 11) years, mean body mass index 34.1 (SD 6.7) kg/m2, with diabetes for mean 8.2 (SD 5.4) years, and a mean A_1c of 8.3% (SD 1.1; 67 mmol/mol). Both groups lowered A_1c with an estimated average decrease of 0.70 percentage points in usual care group and 1.11 percentage points in the treatment group with a significant difference of 0.41 percentage points at 6 months (SE 0.08, t₁₅₉=–2.87, P=.005). Change in medication (SE 0.21, t₁₅₇=–3.37, P=.009) was significantly associated with lower A_1c level. The treatment group significantly improved on the SDSCA subscales carbohydrate spacing (P=.04), monitoring glucose (P=.001), and foot care (P=.02).

Conclusions

An eHealth model incorporating a complete feedback loop with telehealth remote monitoring and paired glucose testing with asynchronous data analysis significantly improved A_1c levels compared to usual care.

Trial Registration

Clinicaltrials.gov NCT01715649; https://www.clinicaltrials.gov/ct2/show/NCT01715649 (Archived by WebCite at http://www.webcitation.org/6ZinLl8D0).

A randomized controlled trial to provide adherence information and motivational interviewing to improve diabetes and lipid control

PURPOSE

The purpose of this study was to assess whether providing medication adherence information with or without motivational interviewing improves diabetes and lipid control.

METHODS

Study participants were adult members of a health system in southeast Michigan, were using both oral diabetes and lipid-lowering medications, and had glycated hemoglobin (A1C) or low-density lipoprotein cholesterol (LDL-C) levels not at goal. Participants were randomly assigned to receive usual care (UC), n = 567; have medication adherence information (AI) provided to their physician, n = 569; or have AI and receive motivational interviewing (MI) though trained staff (AI + MI), n = 556. Primary outcomes were A1C and LDL-C levels at 18 months post randomization.

RESULTS

Primary outcomes were not significantly different between patients in the AI or AI + MI study arms when compared with UC. Similarly, neither oral diabetes nor lipid-lowering medication adherence was significantly different between groups. Patient participation in the AI + MI arm was low and limit the interpretation of the study results, but post hoc analysis of the AI + MI study arm showed that the number of MI sessions received was positively associated with only oral diabetes medication adherence.

CONCLUSION

Neither AI nor MI significantly improved diabetes and lipid control when compared with UC. Moreover, patient participation appeared to be a particular barrier for MI.

Interventions to improve safe and effective medicines use by consumers: an overview of systematic reviews

BACKGROUND

Many systematic reviews exist on interventions to improve safe and effective medicines use by consumers, but research is distributed across diseases, populations and settings. The scope and focus of such reviews also vary widely, creating challenges for decision-makers seeking to inform decisions by using the evidence on consumers' medicines use.This is an update of a 2011 overview of systematic reviews, which synthesises the evidence, irrespective of disease, medicine type, population or setting, on the effectiveness of interventions to improve consumers' medicines use.

OBJECTIVES

To assess the effects of interventions which target healthcare consumers to promote safe and effective medicines use, by synthesising review-level evidence.

METHODS

SEARCH METHODS

We included systematic reviews published on the Cochrane Database of Systematic Reviews and the Database of Abstracts of Reviews of Effects. We identified relevant reviews by handsearching databases from their start dates to March 2012.

SELECTION CRITERIA

We screened and ranked reviews based on relevance to consumers' medicines use, using criteria developed for this overview.

DATA COLLECTION AND ANALYSIS

We used standardised forms to extract data, and assessed reviews for methodological quality using the AMSTAR tool. We used standardised language to summarise results within and across reviews; and gave bottom-line statements about intervention effectiveness. Two review authors screened and selected reviews, and extracted and analysed data. We used a taxonomy of interventions to categorise reviews and guide syntheses.

MAIN RESULTS

We included 75 systematic reviews of varied methodological quality. Reviews assessed interventions with diverse aims including support for behaviour change, risk minimisation and skills acquisition. No reviews aimed to promote systems-level consumer participation in medicines-related activities. Medicines adherence was the most frequently-reported outcome, but others such as knowledge, clinical and service-use outcomes were also reported. Adverse events were less commonly identified, while those associated with the interventions themselves, or costs, were rarely reported.Looking across reviews, for most outcomes, medicines self-monitoring and self-management programmes appear generally effective to improve medicines use, adherence, adverse events and clinical outcomes; and to reduce mortality in people self-managing antithrombotic therapy. However, some participants were unable to complete these interventions, suggesting they may not be suitable for everyone.Other promising interventions to improve adherence and other key medicines-use outcomes, which require further investigation to be more certain of their effects, include:· simplified dosing regimens: with positive effects on adherence;· interventions involving pharmacists in medicines management, such as medicines reviews (with positive effects on adherence and use, medicines problems and clinical outcomes) and pharmaceutical care services (consultation between pharmacist and patient to resolve medicines problems, develop a care plan and provide follow-up; with positive effects on adherence and knowledge).Several other strategies showed some positive effects, particularly relating to adherence, and other outcomes, but their effects were less consistent overall and so need further study. These included:· delayed antibiotic prescriptions: effective to decrease antibiotic use but with mixed effects on clinical outcomes, adverse effects and satisfaction;· practical strategies like reminders, cues and/or organisers, reminder packaging and material incentives: with positive, although somewhat mixed effects on adherence;· education delivered with self-management skills training, counselling, support, training or enhanced follow-up; information and counselling delivered together; or education/information as part of pharmacist-delivered packages of care: with positive effects on adherence, medicines use, clinical outcomes and knowledge, but with mixed effects in some studies;· financial incentives: with positive, but mixed, effects on adherence.Several strategies also showed promise in promoting immunisation uptake, but require further study to be more certain of their effects. These included organisational interventions; reminders and recall; financial incentives; home visits; free vaccination; lay health worker interventions; and facilitators working with physicians to promote immunisation uptake. Education and/or information strategies also showed some positive but even less consistent effects on immunisation uptake, and need further assessment of effectiveness and investigation of heterogeneity.There are many different potential pathways through which consumers' use of medicines could be targeted to improve outcomes, and simple interventions may be as effective as complex strategies. However, no single intervention assessed was effective to improve all medicines-use outcomes across all diseases, medicines, populations or settings.Even where interventions showed promise, the assembled evidence often only provided part of the picture: for example, simplified dosing regimens seem effective for improving adherence, but there is not yet sufficient information to identify an optimal regimen.In some instances interventions appear ineffective: for example, the evidence suggests that directly observed therapy may be generally ineffective for improving treatment completion, adherence or clinical outcomes.In other cases, interventions may have variable effects across outcomes. As an example, strategies providing information or education as single interventions appear ineffective to improve medicines adherence or clinical outcomes, but may be effective to improve knowledge; an important outcome for promoting consumers' informed medicines choices.Despite a doubling in the number of reviews included in this updated overview, uncertainty still exists about the effectiveness of many interventions, and the evidence on what works remains sparse for several populations, including children and young people, carers, and people with multimorbidity.

AUTHORS' CONCLUSIONS

This overview presents evidence from 75 reviews that have synthesised trials and other studies evaluating the effects of interventions to improve consumers' medicines use.Systematically assembling the evidence across reviews allows identification of effective or promising interventions to improve consumers' medicines use, as well as those for which the evidence indicates ineffectiveness or uncertainty.Decision makers faced with implementing interventions to improve consumers' medicines use can use this overview to inform decisions about which interventions may be most promising to improve particular outcomes. The intervention taxonomy may also assist people to consider the strategies available in relation to specific purposes, for example, gaining skills or being involved in decision making. Researchers and funders can use this overview to identify where more research is needed and assess its priority. The limitations of the available literature due to the lack of evidence for important outcomes and important populations, such as people with multimorbidity, should also be considered in practice and policy decisions.

Telehealth Remote Monitoring Systematic Review: Structured Self-monitoring of Blood Glucose and Impact on A1C

The aim was to summarize research on telehealth remote patient monitoring interventions that incorporate key elements of structured self-monitoring of blood glucose (SMBG) identified as essential for improving A1C. A systematic review was conducted using the Medline, Cumulative Index to Nursing and Allied Health Literature, EMBASE, and OVID Medline databases with search terms "Telemedicine" AND "Monitoring, Physiologic" AND "Diabetes Mellitus, Type 2." Study selection criteria included original randomized clinical trials evaluating the impact of telehealth remote patient monitoring on A1C among adults with type 2 diabetes and incorporated 1 or more essential elements of SMBG identified by the International Diabetes Federation (patient education, provider education, structured SMBG profile, SMBG goals, feedback, data used to modify treatment, interactive communication or shared decision making). Fifteen studies were included, with interventions ranging from 3 to 12 months (mean 8 months) with sample sizes from 30 to 1665. Key SMBG elements were grouped into 3 categories: education, SMBG protocols, and feedback. Research incorporating 5 of the 7 elements consistently achieved significant A1C improvements between study groups. Interventions using more SMBG elements are associated with an improvement in A1C. Studies with the largest A1C decrease incorporated 6 of the 7 elements and computer decision support. Two studies with 5 of the 7 elements and active medication management achieved significant A1C decreases. Telehealth remote patient monitoring interventions in type 2 diabetes have not included all structured monitoring elements recommended by the IDF. Incorporating more elements of structured SMBG is associated with improved A1C.

Improving treatment intensification to reduce cardiovascular disease risk: a cluster randomized trial

Background

Blood pressure, lipid, and glycemic control are essential for reducing cardiovascular disease (CVD) risk. Many health care systems have successfully shifted aspects of chronic disease management, including population-based outreach programs designed to address CVD risk factor control, to non-physicians. The purpose of this study is to evaluate provision of new information to non-physician outreach teams on need for treatment intensification in patients with increased CVD risk.

Methods

Cluster randomized trial (July 1-December 31, 2008) in Kaiser Permanente Northern California registry of members with diabetes mellitus, prior CVD diagnoses and/or chronic kidney disease who were high-priority for treatment intensification: blood pressure ≥ 140 mmHg systolic, LDL-cholesterol ≥ 130 mg/dl, or hemoglobin A1c ≥ 9%; adherent to current medications; no recent treatment intensification). Randomization units were medical center-based outreach teams (4 intervention; 4 control). For intervention teams, priority flags for intensification were added monthly to the registry database with recommended next pharmacotherapeutic steps for each eligible patient. Control teams used the same database without this information. Outcomes included 3-month rates of treatment intensification and risk factor levels during follow-up.

Results

Baseline risk factor control rates were high (82-90%). In eligible patients, the intervention was associated with significantly greater 3-month intensification rates for blood pressure (34.1 vs. 30.6%) and LDL-cholesterol (28.0 vs 22.7%), but not A1c. No effects on risk factors were observed at 3 months or 12 months follow-up. Intervention teams initiated outreach for only 45-47% of high-priority patients, but also for 27-30% of lower-priority patients. Teams reported difficulties adapting prior outreach strategies to incorporate the new information.

Conclusions

Information enhancement did not improve risk factor control compared to existing outreach strategies at control centers. Familiarity with prior, relatively successful strategies likely reduced uptake of the innovation and its potential for success at intervention centers.

Trial registration

ClinicalTrials.gov Identifier NCT00517686