Individualized electronic decision support and reminders to improve diabetes care in the community: COMPETE II randomized trial

Barriers, facilitators, and recommendations to increase the use of a clinical decision support tool for managing chronic pain in primary care

BACKGROUND AND OBJECTIVE

Primary care providers (PCPs) use poorly organized patient information in electronic health records (EHR) within a limited time when treating patients with chronic pain. Clinical decision support (CDS) tools assist PCPs by synthesizing patient information and prompting guideline-concordant treatment decisions. A CDS tool- Chronic Pain OneSheet was developed through a user-centered design process to support PCP's decision-making for patients with chronic noncancer pain. OneSheet aggregates relevant patient information in one place in the EHR. OneSheet also guides PCPs in completing guideline-recommended opioid risk management tasks, tracking patient treatments, and documenting pain-related symptoms. Our objective was to identify barriers, facilitators, and recommendations to increase OneSheet use for chronic noncancer pain management in primary care.

METHODS

We conducted 19 qualitative interviews with PCPs from two academic health systems who had access to OneSheet in their EHR. Interview transcripts were coded to identify common themes using a modified thematic approach.

RESULTS

PCPs identified several barriers to using OneSheet, including limited time to address patient needs associated with multiple chronic conditions, resistance to changing established workflows, and complex OneSheet display. PCPs reported several facilitators to using OneSheet, such as OneSheet's ability to serve as a hub for chronic pain data, easy access to features that facilitate completing mandatory tasks and improved planning for certain patient visits. PCPs recommended prioritizing access to commonly used features, adding display customization capabilities, and expanding access to patients and other team members to increase OneSheet use.

CONCLUSION

Our findings highlight the importance of acknowledging the PCP workflow and task load when designing CDS tools. Future CDS tools should balance the extent of information provided with assisting PCPs to fulfill mandatory tasks. Expanding CDS tools to multiple care team members and patients can also lead to higher use by facilitating data entry, leading to more streamlined care delivery.

Efficacy of using telecare services for community-dwelling people with diabetes: A systematic review and meta-analysis

OBJECTIVE

To evaluate the glycated hemoglobin (HbA1c), blood pressure, self-efficacy, and quality of life efficacy of using telecare services for community-dwelling people with diabetes.

METHODS

Cochrane Library, Web of Science, PsycINFO, PubMed, EMBASE, CINAHL, and Scopus databases were systematically searched from their inception dates to June 22, 2023. Two evaluators independently selected and evaluated eligible studies. A protocol was registered in PROSPERO.

RESULTS

An analysis of 17 studies that included 3586 subjects showed that telecare significantly improved the management of patients with diabetes. Compared to controls, intervention care had significant benefits regarding HbA1c (MD = -0.30, 95 % CI = -0.44 - -0.17, 16 studies), systolic blood pressure (MD = -2.45, 95 % CI = -4.53 - -0.36, P = 0.02), self-efficacy (MD = 0.36, 95 % CI = 0.04 - 0.67, P = 0.03) and quality of life (MD = 0.37, 95 % CI = 0.05 - 0.70, P = 0.02). However, diastolic blood pressure (MD = -1.37, 95 % CI = -3.34 - -0.61, P = 0.17) was not found to be significantly affected.

CONCLUSIONS

Telecare is effective in improving self-management among community-dwelling people with diabetes, suggesting an effective means for them to achieve self-management.

A telemonitoring intervention design for patients with poorly controlled type 2 diabetes: protocol for a feasibility study

BACKGROUND

Maintaining optimal glycemic control in type 2 diabetes (T2D) is difficult. Telemedicine has the potential to support people with poorly regulated T2D in the achievement of glycemic control, especially if the telemedicine solution includes a telemonitoring component. However, the ideal telemonitoring design for people with T2D remains unclear. Therefore, the aim of this feasibility study is to evaluate the feasibility of two telemonitoring designs for people with non-insulin-dependent T2D with a goal of identifying the optimal telemonitoring intervention for a planned future large-scale randomized controlled trial.

METHOD

This 3-month randomized feasibility study will be conducted in four municipalities in North Denmark starting in January 2024. There will be 15 participants from each municipality. Two different telemonitoring intervention designs will be tested. One intervention will include self-monitoring of blood glucose (SMBG) combined with sleep and mental health monitoring. The second intervention will include an identical setup but with the addition of blood pressure and activity monitoring. Two municipalities will be allocated to one intervention design, whereas the other two municipalities will be allocated to the second intervention design. Qualitative interviews with participants and clinicians will be conducted to gain insight into their experiences with and acceptance of the intervention designs and trial procedures (e.g., blood sampling and questionnaires). In addition, sources of differences in direct intervention costs between the two alternative interventions will be investigated.

DISCUSSION

Telemonitoring has the potential to support people with diabetes in achieving glycemic control, but the existing evidence is inconsistent, and thus, the optimal design of interventions remains unclear. The results of this feasibility study are expected to produce relevant information about telemonitoring designs for people with T2D and help guide the design of future studies. A well-tested telemonitoring design is essential to ensure the quality of telemedicine initiatives, with goals of user acceptance and improved patient outcomes.

TRIAL REGISTRATION

ClinicalTrials.gov, ID: NCT06134934 . Registered November 1, 2023. The feasibility trial has been approved (N-20230026) by the North Denmark Region Committee on Health Research Ethics (June 5, 2023).

Tailoring remote patient management in cardiovascular risk management for healthcare professionals using panel management: a qualitative study

BACKGROUND

While remote patient management (RPM) has the potential to assist in achieving treatment targets for cardiovascular risk factors in primary care, its effectiveness may vary among different patient subgroups. Panel management, which involves proactive care for specific patient risk groups, could offer a promising approach to tailor RPM to these groups. This study aims to (i) assess the perception of healthcare professionals and other stakeholders regarding the adoption and (ii) identify the barriers and facilitators for successfully implementing such a panel management approach.

METHODS

In total, nineteen semi-structured interviews and two focus groups were conducted in the Netherlands. Three authors reviewed the audited transcripts. The Consolidated Framework for Implementation Strategies (CFIR) domains were used for the thematic analysis.

RESULTS

A total of 24 participants (GPs, nurses, health insurers, project managers, and IT consultants) participated. Overall, a panel management approach to RPM in primary care was considered valuable by various stakeholders. Implementation barriers encompassed concerns about missing necessary risk factors for patient stratification, additional clinical and technical tasks for nurses, and reimbursement agreements. Facilitators included tailoring consultation frequency and early detection of at-risk patients, an implementation manager accountable for supervising project procedures and establishing agreements on assessing implementation metrics, and ambassador roles.

CONCLUSION

Panel management could enhance proactive care and accurately identify which patients could benefit most from RPM to mitigate CVD risk. For successful implementation, we recommend having clear agreements on technical support, financial infrastructure and the criteria for measuring evaluation outcomes.

Applications of Clinical Decision Support Systems in Diabetes Care: Scoping Review

BACKGROUND

Providing comprehensive and individualized diabetes care remains a significant challenge in the face of the increasing complexity of diabetes management and a lack of specialized endocrinologists to support diabetes care. Clinical decision support systems (CDSSs) are progressively being used to improve diabetes care, while many health care providers lack awareness and knowledge about CDSSs in diabetes care. A comprehensive analysis of the applications of CDSSs in diabetes care is still lacking.

OBJECTIVE

This review aimed to summarize the research landscape, clinical applications, and impact on both patients and physicians of CDSSs in diabetes care.

METHODS

We conducted a scoping review following the Arksey and O'Malley framework. A search was conducted in 7 electronic databases to identify the clinical applications of CDSSs in diabetes care up to June 30, 2022. Additional searches were conducted for conference abstracts from the period of 2021-2022. Two researchers independently performed the screening and data charting processes.

RESULTS

Of 11,569 retrieved studies, 85 (0.7%) were included for analysis. Research interest is growing in this field, with 45 (53%) of the 85 studies published in the past 5 years. Among the 58 (68%) out of 85 studies disclosing the underlying decision-making mechanism, most CDSSs (44/58, 76%) were knowledge based, while the number of non-knowledge-based systems has been increasing in recent years. Among the 81 (95%) out of 85 studies disclosing application scenarios, the majority of CDSSs were used for treatment recommendation (63/81, 78%). Among the 39 (46%) out of 85 studies disclosing physician user types, primary care physicians (20/39, 51%) were the most common, followed by endocrinologists (15/39, 39%) and nonendocrinology specialists (8/39, 21%). CDSSs significantly improved patients' blood glucose, blood pressure, and lipid profiles in 71% (45/63), 67% (12/18), and 38% (8/21) of the studies, respectively, with no increase in the risk of hypoglycemia.

CONCLUSIONS

CDSSs are both effective and safe in improving diabetes care, implying that they could be a potentially reliable assistant in diabetes care, especially for physicians with limited experience and patients with limited access to medical resources.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR2-10.37766/inplasy2022.9.0061.

Harnessing the power of clinical decision support systems: challenges and opportunities

Clinical decision support systems (CDSSs) are increasingly integrated into healthcare settings to improve patient outcomes, reduce medical errors and enhance clinical efficiency by providing clinicians with evidence-based recommendations at the point of care. However, the adoption and optimisation of these systems remain a challenge. This review aims to provide an overview of the current state of CDSS, discussing their development, implementation, benefits, limitations and future directions. We also explore the potential for enhancing their effectiveness and provide an outlook for future developments in this field. There are several challenges in CDSS implementation, including data privacy concerns, system integration and clinician acceptance. While CDSS have demonstrated significant potential, their adoption and optimisation remain a challenge.

Quality improvement strategies for diabetes care: Effects on outcomes for adults living with diabetes

BACKGROUND

There is a large body of evidence evaluating quality improvement (QI) programmes to improve care for adults living with diabetes. These programmes are often comprised of multiple QI strategies, which may be implemented in various combinations. Decision-makers planning to implement or evaluate a new QI programme, or both, need reliable evidence on the relative effectiveness of different QI strategies (individually and in combination) for different patient populations.

OBJECTIVES

To update existing systematic reviews of diabetes QI programmes and apply novel meta-analytical techniques to estimate the effectiveness of QI strategies (individually and in combination) on diabetes quality of care.

SEARCH METHODS

We searched databases (CENTRAL, MEDLINE, Embase and CINAHL) and trials registers (ClinicalTrials.gov and WHO ICTRP) to 4 June 2019. We conducted a top-up search to 23 September 2021; we screened these search results and 42 studies meeting our eligibility criteria are available in the awaiting classification section.

SELECTION CRITERIA

We included randomised trials that assessed a QI programme to improve care in outpatient settings for people living with diabetes. QI programmes needed to evaluate at least one system- or provider-targeted QI strategy alone or in combination with a patient-targeted strategy. - System-targeted: case management (CM); team changes (TC); electronic patient registry (EPR); facilitated relay of clinical information (FR); continuous quality improvement (CQI). - Provider-targeted: audit and feedback (AF); clinician education (CE); clinician reminders (CR); financial incentives (FI). - Patient-targeted: patient education (PE); promotion of self-management (PSM); patient reminders (PR). Patient-targeted QI strategies needed to occur with a minimum of one provider or system-targeted strategy.

DATA COLLECTION AND ANALYSIS

We dual-screened search results and abstracted data on study design, study population and QI strategies. We assessed the impact of the programmes on 13 measures of diabetes care, including: glycaemic control (e.g. mean glycated haemoglobin (HbA1c)); cardiovascular risk factor management (e.g. mean systolic blood pressure (SBP), low-density lipoprotein cholesterol (LDL-C), proportion of people living with diabetes that quit smoking or receiving cardiovascular medications); and screening/prevention of microvascular complications (e.g. proportion of patients receiving retinopathy or foot screening); and harms (e.g. proportion of patients experiencing adverse hypoglycaemia or hyperglycaemia). We modelled the association of each QI strategy with outcomes using a series of hierarchical multivariable meta-regression models in a Bayesian framework. The previous version of this review identified that different strategies were more or less effective depending on baseline levels of outcomes. To explore this further, we extended the main additive model for continuous outcomes (HbA1c, SBP and LDL-C) to include an interaction term between each strategy and average baseline risk for each study (baseline thresholds were based on a data-driven approach; we used the median of all baseline values reported in the trials). Based on model diagnostics, the baseline interaction models for HbA1c, SBP and LDL-C performed better than the main model and are therefore presented as the primary analyses for these outcomes. Based on the model results, we qualitatively ordered each QI strategy within three tiers (Top, Middle, Bottom) based on its magnitude of effect relative to the other QI strategies, where 'Top' indicates that the QI strategy was likely one of the most effective strategies for that specific outcome. Secondary analyses explored the sensitivity of results to choices in model specification and priors.  Additional information about the methods and results of the review are available as Appendices in an online repository. This review will be maintained as a living systematic review; we will update our syntheses as more data become available.

MAIN RESULTS

We identified 553 trials (428 patient-randomised and 125 cluster-randomised trials), including a total of 412,161 participants. Of the included studies, 66% involved people living with type 2 diabetes only. Participants were 50% female and the median age of participants was 58.4 years. The mean duration of follow-up was 12.5 months. HbA1c was the commonest reported outcome; screening outcomes and outcomes related to cardiovascular medications, smoking and harms were reported infrequently. The most frequently evaluated QI strategies across all study arms were PE, PSM and CM, while the least frequently evaluated QI strategies included AF, FI and CQI. Our confidence in the evidence is limited due to a lack of information on how studies were conducted.  Four QI strategies (CM, TC, PE, PSM) were consistently identified as 'Top' across the majority of outcomes. All QI strategies were ranked as 'Top' for at least one key outcome. The majority of effects of individual QI strategies were modest, but when used in combination could result in meaningful population-level improvements across the majority of outcomes. The median number of QI strategies in multicomponent QI programmes was three.  Combinations of the three most effective QI strategies were estimated to lead to the below effects:  - PR + PSM + CE: decrease in HbA1c by 0.41% (credibility interval (CrI) -0.61 to -0.22) when baseline HbA1c < 8.3%; - CM + PE + EPR: decrease in HbA1c by 0.62% (CrI -0.84 to -0.39) when baseline HbA1c > 8.3%;  - PE + TC + PSM: reduction in SBP by 2.14 mmHg (CrI -3.80 to -0.52) when baseline SBP < 136 mmHg; - CM + TC + PSM: reduction in SBP by 4.39 mmHg (CrI -6.20 to -2.56) when baseline SBP > 136 mmHg;  - TC + PE + CM: LDL-C lowering of 5.73 mg/dL (CrI -7.93 to -3.61) when baseline LDL < 107 mg/dL; - TC + CM + CR: LDL-C lowering by 5.52 mg/dL (CrI -9.24 to -1.89) when baseline LDL > 107 mg/dL. Assuming a baseline screening rate of 50%, the three most effective QI strategies were estimated to lead to an absolute improvement of 33% in retinopathy screening (PE + PR + TC) and 38% absolute increase in foot screening (PE + TC + Other).

AUTHORS' CONCLUSIONS

There is a significant body of evidence about QI programmes to improve the management of diabetes. Multicomponent QI programmes for diabetes care (comprised of effective QI strategies) may achieve meaningful population-level improvements across the majority of outcomes. For health system decision-makers, the evidence summarised in this review can be used to identify strategies to include in QI programmes. For researchers, this synthesis identifies higher-priority QI strategies to examine in further research regarding how to optimise their evaluation and effects. We will maintain this as a living systematic review.

The Effectiveness of Telemedicine Solutions for the Management of Type 2 Diabetes: A Systematic Review, Meta-Analysis, and Meta-Regression

BACKGROUND

Previous systematic reviews have aimed to clarify the effect of telemedicine on diabetes. However, such reviews often have a narrow focus, which calls for a more comprehensive systematic review within the field. Hence, the objective of the present systematic review, meta-analysis, and meta-regression is to evaluate the effectiveness of telemedicine solutions versus any comparator without the use of telemedicine on diabetes-related outcomes among adult patients with type 2 diabetes (T2D).

METHODS

This review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. We considered telemedicine randomized controlled trials (RCT) including adults (≥18 years) diagnosed with T2D. Change in glycated hemoglobin (HbA1c, %) was the primary outcome. PubMed, EMBASE, and the Cochrane Library Central Register of Controlled Trials (CENTRAL) were searched on October 14, 2020. An overall treatment effect was estimated using a meta-analysis performed on the pool of included studies based on the mean difference (MD). The revised Cochrane risk-of-bias tool was applied and the certainty of evidence was graded using the Grading of Recommendations, Assessment, Development and Evaluations (GRADE) approach.

RESULTS

The final sample of papers included a total of 246, of which 168 had sufficient information to calculate the effect of HbA1c%. The results favored telemedicine, with an MD of -0.415% (95% confidence interval [CI] = -0.482% to -0.348%). The heterogeneity was great (I2 = 93.05%). A monitoring component gave rise to the higher effects of telemedicine.

CONCLUSIONS

In conclusion, telemedicine may serve as a valuable supplement to usual care for patients with T2D. The inclusion of a telemonitoring component seems to increase the effect of telemedicine.

Chronic disease IMPACT (chronic disease early detection and improved management in primary care project): An Australian stepped wedge cluster randomised trial

Background

Interrelated chronic vascular diseases (chronic kidney disease (CKD), type 2 diabetes (T2D) and cardiovascular disease (CVD)) are common with high morbidity and mortality. This study aimed to assess if an electronic-technology-based quality improvement intervention in primary care could improve detection and management of people with and at risk of these diseases.

Methods

Stepped-wedge trial with practices randomised to commence intervention in one of five 16-week periods. Intervention included (1) electronic-technology tool extracting data from general practice electronic medical records and generating graphs and lists for audit; (2) education regarding chronic disease and the electronic-technology tool; (3) assistance with quality improvement audit plan development, benchmarking, monitoring and support. De-identified data analysis using R 3.5.1 conducted using Bayesian generalised linear mixed model with practice and time-specific random intercepts.

Results

At baseline, eight included practices had 37,946 active patients (attending practice ≥3 times within 2 years) aged ≥18 years. Intervention was associated with increased OR (95% CI) for: kidney health checks (estimated glomerular filtration rate, urine albumin:creatinine ratio (uACR) and blood pressure) in those at risk 1.34 (1.26-1.42); coded diagnosis of CKD 1.18 (1.09-1.27); T2D diagnostic testing (fasting glucose or HbA1c) in those at risk 1.15 (1.08-1.23); uACR in patients with T2D 1.78 (1.56-2.05). Documented eye checks within recommended frequency in patients with T2D decreased 0.85 (0.77-0.96). There were no significant changes in other assessed variables.

Conclusions

This electronic-technology-based intervention in primary care has potential to help translate guidelines into practice but requires further refining to achieve widespread improvements across the interrelated chronic vascular diseases.

Effectiveness of the chronic care model for adults with type 2 diabetes in primary care: a systematic review and meta-analysis

BACKGROUND

Mixed evidence exists regarding the effectiveness of the Chronic Care Model (CCM) with patient outcomes. The aim of this review is to examine the effectiveness of CCM interventions on hemoglobin A1c (HbA1c), systolic BP (SBP), diastolic BP (DBP), LDL cholesterol and body mass index (BMI) among primary care adults with type 2 diabetes.

METHODS

PubMed, Embase, CINAHL, Cochrane Central Registry of Controlled Trials, Scopus and Web of Science were searched from January 1990 to June 2021 for randomized controlled trials (RCTs) comparing CCM interventions against usual care among adults with type 2 diabetes mellitus in primary care with HbA1c, SBP, DBP, LDL cholesterol and BMI as outcomes. An abbreviated search was performed from 2021 to April 2022. This study followed the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines for data extraction and Cochrane risk of bias assessment. Two reviewers independently extracted the data. Meta-analysis was performed using Review Manager software. Heterogeneity was evaluated using χ2 and I2 test statistics. Overall effects were evaluated using Z statistic.

RESULTS

A total of 17 studies involving 16485 patients were identified. Most studies had low risks of bias. Meta-analysis of all 17 studies revealed that CCM interventions significantly decreased HbA1c levels compared to usual care, with a mean difference (MD) of -0.21%, 95% CI -0.30, -0.13; Z = 5.07, p<0.00001. Larger effects were experienced among adults with baseline HbA1c ≥8% (MD -0.36%, 95% CI -0.51, -0.21; Z = 5.05, p<0.00001) and when four or more CCM elements were present in the interventions (MD -0.25%, 95% CI -0.35, -0.15; Z = 4.85, p<0.00001). Interventions with CCM decreased SBP (MD -2.93 mmHg, 95% CI -4.46, -1.40, Z = 3.75, p=0.0002) and DBP (MD -1.35 mmHg, 95% CI -2.05, -0.65, Z = 3.79, p=0.0002) compared to usual care but there was no impact on LDL cholesterol levels or BMI.

CONCLUSIONS

CCM interventions, compared to usual care, improve glycaemic control among adults with type 2 diabetes in primary care, with greater reductions when the mean baseline HbA1c is ≥8% and with interventions containing four or more CCM elements.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO  CRD42021273959.

Use of video-based telehealth services using a mobile app for workers in underserved areas during the COVID-19 pandemic: A prospective observational study

BACKGROUND

The COVID-19 pandemic has limited face-to-face treatment, triggering a change in the structure of existing healthcare services. Unlike other groups, workers in underserved areas have relatively poor access to healthcare.

OBJECTIVE

This study aimed to investigate the effects of video-based telehealth services using a mobile personal health record (PHR) app for vulnerable workers with metabolic risk factors.

METHODS

A prospective observational study was conducted with 117 participants and 27 healthcare professionals for 16 weeks. Participants visited the research institution three times (at weeks 1, 8, and 16) and underwent health check-ups and used various features of the mobile PHR app. Healthcare professionals observed the participants's data using the monitoring system and performed appropriate interventions. The primary outcome measures were to evaluate the effects of services on changes in the participants' metabolic risk factors, and secondary outcome measures were to analyze changes in the participants' lifestyle and service satisfaction, and to observe service use through usage logs. One-way repeated measures ANOVA and Scheffé's test were performed to observe changes in participants' health status and lifestyle, and a paired t-test was performed to analyze changes in service satisfaction. Finally, in-depth interviews with healthcare professionals were performed using semi-structured questionnaires to understand service providers' perspectives after the end of the study.

RESULTS

Systolic blood pressure (F = 7.32, P <.001), diastolic blood pressure (F = 11.30, P <.001), body weight (F = 29.53, P <.001), BMI (F = 17.31, P <.001), waist circumference (F = 17.33, P <.001), fasting blood glucose (F = 5.11, P =.007), and triglycerides (F = 4.66, P =.01) showed significant improvements with time points, whereas high-density lipoprotein cholesterol (F = 3.35, P =.067) did not. The dietary score (F = 3.26, P =.04) showed a significant improvement with time points, whereas physical activity (F = 1.06, P =.34) did not. In terms of service satisfaction, only lifestyle improvement (P <.001) showed a significant difference. COVID-19 has affected the performance of healthcare professionals, thereby changing the perspectives toward healthcare technology services.

CONCLUSIONS

We evaluated the effectiveness of video-based telehealth services supporting workers' health status and lifestyle interventions using healthcare technologies such as the mobile PHR app, tele-monitoring, and video teleconsultation. Our results indicate that as a complementary means, its utility can be expanded in the field of occupational safety and health to overcome the limitations of face-to-face treatment due to COVID-19 in the future.

Investigating the Potential for Clinical Decision Support in Sub-Saharan Africa With AFYA (Artificial Intelligence-Based Assessment of Health Symptoms in Tanzania): Protocol for a Prospective, Observational Pilot Study

BACKGROUND

Low- and middle-income countries face difficulties in providing adequate health care. One of the reasons is a shortage of qualified health workers. Diagnostic decision support systems are designed to aid clinicians in their work and have the potential to mitigate pressure on health care systems.

OBJECTIVE

The Artificial Intelligence-Based Assessment of Health Symptoms in Tanzania (AFYA) study will evaluate the potential of an English-language artificial intelligence-based prototype diagnostic decision support system for mid-level health care practitioners in a low- or middle-income setting.

METHODS

This is an observational, prospective clinical study conducted in a busy Tanzanian district hospital. In addition to usual care visits, study participants will consult a mid-level health care practitioner, who will use a prototype diagnostic decision support system, and a study physician. The accuracy and comprehensiveness of the differential diagnosis provided by the diagnostic decision support system will be evaluated against a gold-standard differential diagnosis provided by an expert panel.

RESULTS

Patient recruitment started in October 2021. Participants were recruited directly in the waiting room of the outpatient clinic at the hospital. Data collection will conclude in May 2022. Data analysis is planned to be finished by the end of June 2022. The results will be published in a peer-reviewed journal.

CONCLUSIONS

Most diagnostic decision support systems have been developed and evaluated in high-income countries, but there is great potential for these systems to improve the delivery of health care in low- and middle-income countries. The findings of this real-patient study will provide insights based on the performance and usability of a prototype diagnostic decision support system in low- or middle-income countries.

TRIAL REGISTRATION

ClinicalTrials.gov NCT04958577; http://clinicaltrials.gov/ct2/show/NCT04958577.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/34298.

Composite measures of quality of health care: Evidence mapping of methodology and reporting

Background

Quality indicators are used to quantify the quality of care. A large number of quality indicators makes assessment of overall quality difficult, time consuming and impractical. There is consequently an increasing interest for composite measures based on a combination of multiple indicators.

Objective

To examine the use of different approaches to construct composite measures of quality of care and to assess the use of methodological considerations and justifications.

Methods

We conducted a literature search on PubMed and EMBASE databases (latest update 1 December 2020). For each publication, we extracted information on the weighting and aggregation methodology that had been used to construct composite indicator(s).

Results

A total of 2711 publications were identified of which 145 were included after a screening process. Opportunity scoring with equal weights was the most used approach (86/145, 59%) followed by all-or-none scoring (48/145, 33%). Other approaches regarding aggregation or weighting of individual indicators were used in 32 publications (22%). The rationale for selecting a specific type of composite measure was reported in 36 publications (25%), whereas 22 papers (15%) addressed limitations regarding the composite measure.

Conclusion

Opportunity scoring and all-or-none scoring are the most frequently used approaches when constructing composite measures of quality of care. The attention towards the rationale and limitations of the composite measures appears low.

Discussion

Considering the widespread use and the potential implications for decision-making of composite measures, a high level of transparency regarding the construction process of the composite and the functionality of the measures is crucial.

Effectiveness of Remotely Delivered Interventions to Simultaneously Optimize Management of Hypertension, Hyperglycemia and Dyslipidemia in People With Diabetes: A Systematic Review and Meta-Analysis of Randomized Controlled Trials

Background

Remotely delivered interventions may be more efficient in controlling multiple risk factors in people with diabetes.

Purpose

To pool evidence from randomized controlled trials testing remote management interventions to simultaneously control blood pressure, blood glucose and lipids.

Data Sources

PubMed/Medline, EMBASE, CINAHL and the Cochrane library were systematically searched for randomized controlled trials (RCTs) until 20th June 2021.

Study Selection

Included RCTs were those that reported participant data on blood pressure, blood glucose, and lipid outcomes in response to a remotely delivered intervention.

Data Extraction

Three authors extracted data using a predefined template. Primary outcomes were glycated hemoglobin (HbA1c), total cholesterol (TC), low-density lipoprotein cholesterol (LDL-c), systolic and diastolic blood pressure (SBP & DBP). Risk of bias was assessed using the Cochrane collaboration RoB-2 tool. Meta-analyses are reported as standardized mean difference (SMD) with 95% confidence intervals (95%CI).

Data Synthesis

Twenty-seven RCTs reporting on 9100 participants (4581 intervention and 4519 usual care) were included. Components of the remote management interventions tested were identified as patient education, risk factor monitoring, coaching on monitoring, consultations, and pharmacological management. Comparator groups were typically face-to-face usual patient care. Remote management significantly reduced HbA1c (SMD -0.25, 95%CI -0.33 to -0.17, p<0.001), TC (SMD -0.17, 95%CI -0.29 to -0.04, p<0.0001), LDL-c (SMD -0.11, 95%CI -0.19 to -0.03, p=0.006), SBP (SMD -0.11, 95%CI -0.18 to -0.04, p=0.001) and DBP (SMD -0.09, 95%CI -0.16 to -0.02, p=0.02), with low to moderate heterogeneity (I²= 0 to 75). Twelve trials had high risk of bias, 12 had some risk and three were at low risk of bias.

Limitations

Heterogeneity and potential publication bias may limit applicability of findings.

Conclusions

Remote management significantly improves control of modifiable risk factors.

Systematic Review Registration

[https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=258433], identifier PROSPERO (CRD42021258433).

Developing a User-Centered Digital Clinical Decision Support App for Evidence-Based Medication Recommendations for Type 2 Diabetes Mellitus: Prototype User Testing and Validation Study

Background

Closing the gap between care recommended by evidence-based guidelines and care delivered in practice is an ongoing challenge across systems and delivery models. Clinical decision support systems (CDSSs) are widely deployed to augment clinicians in their complex decision-making processes. Despite published success stories, the poor usability of many CDSSs has contributed to fragmented workflows and alert fatigue.

Objective

This study aimed to validate the application of a user-centered design (UCD) process in the development of a standards-based medication recommender for type 2 diabetes mellitus in a simulated setting. The prototype app was evaluated for effectiveness, efficiency, and user satisfaction.

Methods

We conducted interviews with 8 clinical leaders with 8 rounds of iterative user testing with 2-8 prescribers in each round to inform app development. With the resulting prototype app, we conducted a validation study with 43 participants. The participants were assigned to one of two groups and completed a 2-hour remote user testing session. Both groups reviewed mock patient facts and ordered diabetes medications for the patients. The Traditional group used a mock electronic health record (EHR) for the review in Period 1 and used the prototype app in Period 2, while the Tool group used the prototype app during both time periods. The perceived cognitive load associated with task performance during each period was assessed with the National Aeronautics and Space Administration Task Load Index. Participants also completed the System Usability Scale (SUS) questionnaire and Kano Survey.

Results

Average SUS scores from the questionnaire, taken at the end of 5 of the 8 user testing sessions, ranged from 68-86. The results of the validation study are as follows: percent adherence to evidence-based guidelines was greater with the use of the prototype app than with the EHR across time periods with the Traditional group (prototype app mean 96.2 vs EHR mean 72.0, P<.001) and between groups during Period 1 (Tool group mean 92.6 vs Traditional group mean 72.0, P<.001). Task completion times did not differ between groups (P=.23), but the Tool group completed medication ordering more quickly in Period 2 (Period 1 mean 130.7 seconds vs Period 2 mean 107.7 seconds, P<.001). Based on an adjusted α level owing to violation of the assumption of homogeneity of variance (Ps>.03), there was no effect on screens viewed and on perceived cognitive load (all Ps>.14).

Conclusions

Through deployment of the UCD process, a point-of-care medication recommender app holds promise of improving adherence to evidence-based guidelines; in this case, those from the American Diabetes Association. Task-time performance suggests that with practice the T2DM app may support a more efficient ordering process for providers, and SUS scores indicate provider satisfaction with the app.

A MIXED-METHODS EVALUATION OF STANDALONE PERSONAL HEALTH RECORD USE BY PATIENTS WITH TYPE 2 DIABETES

Background

Self-management of diabetes is key for achieving positive clinical outcomes, with personal health records (PHRs) proposed as a patient-centered technology for facilitating self-care. However, few studies have described patient engagement with a PHR, including facilitators and barriers to use from the perspective of actual users.

Objectives

To compare use of a standalone PHR by patients with Type 2 diabetes to usual care through assessment of self-care behaviors, and short-term impact on social cognitive outcomes and hemoglobin A1c (HbA1c).

Methods

A mixed-methods design combining a comparative effectiveness pilot with qualitative interviews was used. Qualitative interviews explored the primary outcome of changes in self-care behaviors, while quantitative data obtained from health records and a survey focused on social cognitive and clinical outcomes.

Results

A total of 117 participants completed the study (intervention group = 56, control group = 61). Only 23 individuals used the PHR at least once after baseline. Five themes emerged from the qualitative analysis describing participants' experiences with the PHR and identifying reasons for lack of engagement. Quantitative findings supported qualitative results with no significant changes in HbA1c and only a significant increase in diabetes knowledge in the intervention group.

Conclusions

Study findings revealed low PHR uptake and minimal impact on study outcomes, including lack of communication and information-sharing between patients and providers. Future research should explore the fit of PHRs within the context of other self-management tools, integration with provider workflow, and the need for enhanced functionalities beyond an information repository to optimally support patient self-care.

Lessons learned from Integrated Management Program Advancing Community Treatment of Atrial Fibrillation (IMPACT-AF): a pragmatic clinical trial of computerized decision support in primary care

Background

Integrated Management Program Advancing Community Treatment of Atrial Fibrillation (IMPACT-AF) was a pragmatic, cluster randomized trial assessing the effectiveness of a clinical decision support (CDS) tool in primary care, Nova Scotia, Canada. We evaluated if CDS software versus Usual Care could help primary care providers (PCPs) deliver individualized guideline-based AF patient care.

Methods

Key study challenges including CDS development and implementation, recruitment, and data integration documented over the trial duration are presented as lessons learned.

Results

Adequate resources must be allocated for software development, updates and feasibility testing. Development took longer than projected. End-user feedback suggested network access and broadband speeds impeded uptake; they felt further that the CDS was not sufficiently user-friendly or efficient in supporting AF care (i.e., repetitive alerts).

Integration across e-platforms is crucial. Intellectual property and other issues prohibited CDS integration within electronic medical records and provincial e-health platforms. Double login and data entry were impediments to participation or reasons for provider withdrawal. Data integration challenges prevented easy and timely data access, analysis, and reporting.

Primary care study recruitment is resource intensive. Altogether, 203 PCPs and 1145 of their patients participated, representing 25% of eligible providers and 12% of AF patients in Nova Scotia, respectively. The most effective provider recruitment strategy was in-office, small group lunch-and-learns. PCPs with past research experience or who led patient consent were top recruiters. The study office played a pivotal role in achieving patient recruitment targets.

Conclusions

A rapid growth in healthcare data is leading to widespread development of CDS. Our experience found practical issues to address for such applications to succeed. Feasibility testing to assess the utility of any healthcare CDS prior to implementation is recommended. Adequate resources are necessary to support successful recruitment for future pragmatic trials. CDS tools that integrate multiple co-morbid guidelines across eHealth platforms should be pursued.

Trial registration

ClinicalTrials.gov NCT01927367. Registered on August 22, 2013

Harnessing Digital Health Technologies to Remotely Manage Diabetic Foot Syndrome: A Narrative Review

About 422 million people worldwide have diabetes and approximately one-third of them have a major risk factor for diabetic foot ulcers, including poor sensation in their feet from peripheral neuropathy and/or poor perfusion to their feet from peripheral artery disease. The current healthcare ecosystem, which is centered on the treatment of established foot disease, often fails to adequately control key reversible risk factors to prevent diabetic foot ulcers leading to unacceptable high foot disease amputation rate, 40% recurrence of ulcers rate in the first year, and high hospital admissions. Thus, the latest diabetic foot ulcer guidelines emphasize that a paradigm shift in research priority from siloed hospital treatments to innovative integrated community prevention is now critical to address the high diabetic foot ulcer burden. The widespread uptake and acceptance of wearable and digital health technologies provide a means to timely monitor major risk factors associated with diabetic foot ulcer, empower patients in self-care, and effectively deliver the remote monitoring and multi-disciplinary prevention needed for those at-risk people and address the health care access disadvantage that people living in remote areas. This narrative review paper summarizes some of the latest innovations in three specific areas, including technologies supporting triaging high-risk patients, technologies supporting care in place, and technologies empowering self-care. While many of these technologies are still in infancy, we anticipate that in response to the Coronavirus Disease 2019 pandemic and current unmet needs to decentralize care for people with foot disease, we will see a new wave of innovations in the area of digital health, smart wearables, telehealth technologies, and “hospital-at-home” care delivery model. These technologies will be quickly adopted at scale to improve remote management of diabetic foot ulcers, smartly triaging those who need to be seen in outpatient or inpatient clinics, and supporting acute or subacute care at home.

Adult patient access to electronic health records

BACKGROUND

To support patient-centred care, healthcare organisations increasingly offer patients access to data stored in the institutional electronic health record (EHR).

OBJECTIVES

Primary objective 1. To assess the effects of providing adult patients with access to electronic health records (EHRs) alone or with additional functionalities on a range of patient, patient-provider, and health resource consumption outcomes, including patient knowledge and understanding, patient empowerment, patient adherence, patient satisfaction with care, adverse events, health-related quality of life, health-related outcomes, psychosocial health outcomes, health resource consumption, and patient-provider communication. Secondary objective 1. To assess whether effects of providing adult patients with EHR access alone versus EHR access with additional functionalities differ among patient groups according to age, educational level, or different status of disease (chronic or acute).

SEARCH METHODS

We searched CENTRAL, MEDLINE, Embase, PsycINFO, CINAHL, and Scopus in June 2017 and in April 2020.

SELECTION CRITERIA

Randomised controlled trials and cluster-randomised trials of EHR access with or without additional functionalities for adults with any medical condition.

DATA COLLECTION AND ANALYSIS

We used standard Cochrane methodological procedures.

MAIN RESULTS

We included 10 studies with 78 to 4500 participants and follow-up from 3 to 24 months. Nine studies assessed the effects of EHR with additional functionalities, each addressing a subset of outcomes sought by this review. Five studies focused on patients with diabetes mellitus, four on patients with specific diseases, and one on all patients. All studies compared EHR access alone or with additional functionalities plus usual care versus usual care only. No studies assessing the effects of EHR access alone versus EHR access with additional functionalities were identified. Interventions required a variety of data within the EHR, such as patient history, problem list, medication, allergies, and lab results. In addition to EHR access, eight studies allowed patients to share self-documented data, seven offered individualised disease management functions, seven offered educational disease-related information, six supported secure communication, and one offered preventive reminders. Only two studies were at low or unclear risk of bias across domains. Meta-analysis could not be performed, as participants, interventions, and outcomes were too heterogeneous, and most studies presented results based on different adjustment methods or variables. The quality of evidence was rated as low or very low across outcomes. Overall differences between intervention and control groups, if any, were small. The relevance of any small effects remains unclear for most outcomes because in most cases, trial authors did not define a minimal clinically important difference. Overall, results suggest that the effects of EHR access alone and with additional functionalities are mostly uncertain when compared with usual care. Patient knowledge and understanding: very low-quality evidence is available from one study, so we are uncertain about effects of the intervention on patient knowledge about diabetes and blood glucose testing. Patient empowerment: low-quality evidence from three studies suggests that the intervention may have little or no effect on patient empowerment measures. Patient adherence: low-quality evidence from two studies suggests that the intervention may slightly improve adherence to the process of monitoring risk factors and preventive services. Effects on medication adherence are conflicting in two studies; this may or may not improve to a clinically relevant degree. Patient satisfaction with care: low-quality evidence from three studies suggests that the intervention may have little or no effect on patient satisfaction, with conflicting results. Adverse events: two small studies reported on mortality; one of these also reported on serious and other adverse events, but sample sizes were too small for small differences to be detected. Therefore, low-quality evidence suggests that the intervention may have little to no effect on mortality and other adverse events. Health-related quality of life: only very low-quality evidence from one study is available. We are uncertain whether the intervention improves disease-specific quality of life of patients with asthma. Health-related outcomes: low-quality evidence from eight studies suggests that the intervention may have little to no effect on asthma control, glycosylated haemoglobin (HbA1c) levels, blood pressure, low-density lipoprotein or total cholesterol levels, body mass index or weight, or 10-year Framingham risk scores. Low-quality evidence from one study suggests that the composite scores of risk factors for diabetes mellitus may improve slightly with the intervention, but there is uncertainty about effects on ophthalmic medications or intraocular pressure. Psychosocial health outcomes: no study investigated psychosocial health outcomes in a more than anecdotal way. Health resource consumption: low-quality evidence for adult patients in three studies suggests that there may be little to no effect of the intervention on different measures of healthcare use. Patient-provider communication: very low-quality evidence is available from a single small study, and we are uncertain whether the intervention improves communication measures, such as the number of messages sent.

AUTHORS' CONCLUSIONS

The effects of EHR access with additional functionalities in comparison with usual care for the most part are uncertain. Only adherence to the process of monitoring risk factors and providing preventive services as well as a composite score of risk factors for diabetes mellitus may improve slightly with EHR access with additional functionalities. Due to inconsistent terminology in this area, our search may have missed relevant studies. As the overall quality of evidence is very low to low, future research is likely to change these results. Further trials should investigate the impact of EHR access in a broader range of countries and clinical settings, including more patients over a longer period of follow-up, as this may increase the likelihood of detecting effects of the intervention, should these exist. More studies should focus on assessing outcomes such as patient empowerment and behavioural outcomes, rather than concentrating on health-related outcomes alone. Future studies should distinguish between effects of EHR access only and effects of additional functionalities, and investigate the impact of mobile EHR tools. Future studies should include information on usage patterns, and consider the potential for widening health inequalities with implementation of EHR access. A taxonomy for EHR access and additional functionalities should be developed to promote consistency and comparability of outcome measures, and facilitate future reviews by better enabling cross-study comparisons.

Implementation of Electronic Decision Support for Diabetic Care in a Student-Run Clinic

Background and objectives Type 2 diabetes mellitus (T2DM) is a complex disease that can lead to complications. Electronic decision support in the electronic medical record (EMR) aids management. There is no study demonstrating the effectiveness of electronic decision support in assisting medical student providers in student-run free clinics. Methods There were 71 T2DM patients seen by medical students. Twenty-three encounters used a Diabetes Progress Note (DPN) that was created from consensus, opinion-based guidelines. Each note received a total composite score based on an eight-point scale for adherence to guidelines. Statistical comparisons between mean composite scores were performed using independent t-tests. Results The mean total composite score of DPN users was significantly greater than DPN non-users (5.35 vs. 4.23, p = 0.008), with a significant difference in the physical exam component (1.70 vs. 1.31, p = 0.002). Conclusions In this exploratory study, medical student providers at an attending-supervised, student-run free clinic that used electronic decision support during T2DM patient visits improved adherence to screening for diabetic complications and standard of care.

Implementation of Electronic Decision Support for Diabetic Care in a Student-Run Clinic

Background and objectives Type 2 diabetes mellitus (T2DM) is a complex disease that can lead to complications. Electronic decision support in the electronic medical record (EMR) aids management. There is no study demonstrating the effectiveness of electronic decision support in assisting medical student providers in student-run free clinics. Methods There were 71 T2DM patients seen by medical students. Twenty-three encounters used a Diabetes Progress Note (DPN) that was created from consensus, opinion-based guidelines. Each note received a total composite score based on an eight-point scale for adherence to guidelines. Statistical comparisons between mean composite scores were performed using independent t-tests. Results The mean total composite score of DPN users was significantly greater than DPN non-users (5.35 vs. 4.23, p = 0.008), with a significant difference in the physical exam component (1.70 vs. 1.31, p = 0.002). Conclusions In this exploratory study, medical student providers at an attending-supervised, student-run free clinic that used electronic decision support during T2DM patient visits improved adherence to screening for diabetic complications and standard of care.

A Decision Support System for Diabetes Chronic Care Models Based on General Practitioner Engagement and EHR Data Sharing

Objective Decision support systems (DSS) have been developed and promoted for their potential to improve quality of health care. However, there is a lack of common clinical strategy and a poor management of clinical resources and erroneous implementation of preventive medicine. Methods To overcome this problem, this work proposed an integrated system that relies on the creation and sharing of a database extracted from GPs' Electronic Health Records (EHRs) within the Netmedica Italian (NMI) cloud infrastructure. Although the proposed system is a pilot application specifically tailored for improving the chronic Type 2 Diabetes (T2D) care it could be easily targeted to effectively manage different chronic-diseases. The proposed DSS is based on EHR structure used by GPs in their daily activities following the most updated guidelines in data protection and sharing. The DSS is equipped with a Machine Learning (ML) method for analyzing the shared EHRs and thus tackling the high variability of EHRs. A novel set of T2D care-quality indicators are used specifically to determine the economic incentives and the T2D features are presented as predictors of the proposed ML approach. Results The EHRs from 41237 T2D patients were analyzed. No additional data collection, with respect to the standard clinical practice, was required. The DSS exhibited competitive performance (up to an overall accuracy of 98%±2% and macro-recall of 96%±1%) for classifying chronic care quality across the different follow-up phases. The chronic care quality model brought to a significant increase (up to 12%) of the T2D patients without complications. For GPs who agreed to use the proposed system, there was an economic incentive. A further bonus was assigned when performance targets are achieved. Conclusions The quality care evaluation in a clinical use-case scenario demonstrated how the empowerment of the GPs through the use of the platform (integrating the proposed DSS), along with the economic incentives, may speed up the improvement of care.

Guiding Glucose Management Discussions Among Adults With Type 2 Diabetes in General Practice: Development and Pretesting of a Clinical Decision Support Tool Prototype Embedded in an Electronic Medical Record

BACKGROUND

Managing type 2 diabetes (T2D) requires progressive lifestyle changes and, sometimes, pharmacological treatment intensification. General practitioners (GPs) are integral to this process but can find pharmacological treatment intensification challenging because of the complexity of continually emerging treatment options.

OBJECTIVE

This study aimed to use a co-design method to develop and pretest a clinical decision support (CDS) tool prototype (GlycASSIST) embedded within an electronic medical record, which uses evidence-based guidelines to provide GPs and people with T2D with recommendations for setting glycated hemoglobin (HbA1c) targets and intensifying treatment together in real time in consultations.

METHODS

The literature on T2D-related CDS tools informed the initial GlycASSIST design. A two-part co-design method was then used. Initial feedback was sought via interviews and focus groups with clinicians (4 GPs, 5 endocrinologists, and 3 diabetes educators) and 6 people with T2D. Following refinements, 8 GPs participated in mock consultations in which they had access to GlycASSIST. Six people with T2D viewed a similar mock consultation. Participants provided feedback on the functionality of GlycASSIST and its role in supporting shared decision making (SDM) and treatment intensification.

RESULTS

Clinicians and people with T2D believed that GlycASSIST could support SDM (although this was not always observed in the mock consultations) and individualized treatment intensification. They recommended that GlycASSIST includes less information while maintaining relevance and credibility and using graphs and colors to enhance visual appeal. Maintaining clinical autonomy was important to GPs, as they wanted the capacity to override GlycASSIST's recommendations when appropriate. Clinicians requested easier screen navigation and greater prescribing guidance and capabilities.

CONCLUSIONS

GlycASSIST was perceived to achieve its purpose of facilitating treatment intensification and was acceptable to people with T2D and GPs. The GlycASSIST prototype is being refined based on these findings to prepare for quantitative evaluation.

Impact of providing patients access to electronic health records on quality and safety of care: a systematic review and meta-analysis

Objective

To evaluate the impact of sharing electronic health records (EHRs) with patients and map it across six domains of quality of care (ie, patient-centredness, effectiveness, efficiency, timeliness, equity and safety).

Design

Systematic review and meta-analysis.

Data sources

CINAHL, Cochrane, Embase, HMIC, Medline/PubMed and PsycINFO, from 1997 to 2017.

Eligibility criteria

Randomised trials focusing on adult subjects, testing an intervention consisting of sharing EHRs with patients, and with an outcome in one of the six domains of quality of care.

Data analysis

The Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines were followed. Title and abstract screening were performed by two pairs of investigators and assessed using the Cochrane Risk of Bias Tool. For each domain, a narrative synthesis of the results was performed, and significant differences in results between low risk and high/unclear risk of bias studies were tested (t-test, p<0.05). Continuous outcomes evaluated in four studies or more (glycated haemoglobin (HbA1c), systolic blood pressure (SBP) and diastolic blood pressure (DBP)) were pooled as weighted mean difference (WMD) using random effects meta-analysis. Sensitivity analyses were performed for low risk of bias studies, and long-term interventions only (lasting more than 12 months).

Results

Twenty studies were included (17 387 participants). The domain most frequently assessed was effectiveness (n=14), and the least were timeliness and equity (n=0). Inconsistent results were found for patient-centredness outcomes (ie, satisfaction, activation, self-efficacy, empowerment or health literacy), with 54.5% of the studies (n=6) demonstrating a beneficial effect. Meta-analyses showed a beneficial effect in effectiveness by reducing absolute values of HbA1c (unit: %; WMD=−0.316; 95% CI −0.540 to −0.093, p=0.005, I²=0%), which remained significant in the sensitivity analyses for low risk of bias studies (WMD= −0.405; 95% CI −0.711 to −0.099), and long-term interventions only (WMD=−0.272; 95% CI −0.482 to −0.062). A significant reduction of absolute values of SBP (unit: mm Hg) was found but lost in sensitivity analysis for studies with low risk of bias (WMD= −1.375; 95% CI −2.791 to 0.041). No significant effect was found for DBP (unit: mm Hg; WMD=−0.918; 95% CI −2.078 to 0.242, p=0.121, I²=0%). Concerning efficiency, most studies (80%, n=4) found either a reduction of healthcare usage or no change. A beneficial effect was observed in a range of safety outcomes (ie, general adherence, medication safety), but not in medication adherence. The proportion of studies reporting a beneficial effect did not differ between low risk and high/unclear risk studies, for the domains evaluated.

Discussion

Our analysis supports that sharing EHRs with patients is effective in reducing HbA1c levels, a major predictor of mortality in type 2 diabetes (mean decrease of −0.405, unit: %) and could improve patient safety. More studies are necessary to enhance meta-analytical power and assess the impact in other domains of care.

Protocol registration

http://www.crd.york.ac.uk/PROSPERO (CRD42017070092).

Impact of a "Chart Closure" Hard Stop Alert on Prescribing for Elevated Blood Pressures Among Patients With Diabetes: Quasi-Experimental Study

BACKGROUND

University of California at Los Angeles Health implemented a Best Practice Advisory (BPA) alert for the initiation of an angiotensin-converting enzyme inhibitor (ACEI) or angiotensin-receptor blocker (ARB) for individuals with diabetes. The BPA alert was configured with a "chart closure" hard stop, which demanded a response before closing the chart.

OBJECTIVE

The aim of the study was to evaluate whether the implementation of the BPA was associated with changes in ACEI and ARB prescribing during primary care encounters for patients with diabetes.

METHODS

We defined ACEI and ARB prescribing opportunities as primary care encounters in which the patient had a diabetes diagnosis, elevated blood pressure in recent encounters, no active ACEI or ARB prescription, and no contraindications. We used a multivariate logistic regression model to compare the change in the probability of an ACEI or ARB prescription during opportunity encounters before and after BPA implementation in primary care sites that did (n=30) and did not (n=31) implement the BPA. In an additional subgroup analysis, we compared ACEI and ARB prescribing in BPA implementation sites that had also implemented a pharmacist-led medication management program.

RESULTS

We identified a total of 2438 opportunity encounters across 61 primary care sites. The predicted probability of an ACEI or ARB prescription increased significantly from 11.46% to 22.17% during opportunity encounters in BPA implementation sites after BPA implementation. However, in the subgroup analysis, we only observed a significant improvement in ACEI and ARB prescribing in BPA implementation sites that had also implemented the pharmacist-led program. Overall, the change in the predicted probability of an ACEI or ARB prescription from before to after BPA implementation was significantly greater in BPA implementation sites compared with nonimplementation sites (difference-in-differences of 11.82; P<.001).

CONCLUSIONS

A BPA with a "chart closure" hard stop is a promising tool for the treatment of patients with comorbid diabetes and hypertension with an ACEI or ARB, especially when implemented within the context of team-based care, wherein clinical pharmacists support the work of primary care providers.

Sample size recalculation in multicenter randomized controlled clinical trials based on noncomparative data

Many late-phase clinical trials recruit subjects at multiple study sites. This introduces a hierarchical structure into the data that can result in a power-loss compared to a more homogeneous single-center trial. Building on a recently proposed approach to sample size determination, we suggest a sample size recalculation procedure for multicenter trials with continuous endpoints. The procedure estimates nuisance parameters at interim from noncomparative data and recalculates the sample size required based on these estimates. In contrast to other sample size calculation methods for multicenter trials, our approach assumes a mixed effects model and does not rely on balanced data within centers. It is therefore advantageous, especially for sample size recalculation at interim. We illustrate the proposed methodology by a study evaluating a diabetes management system. Monte Carlo simulations are carried out to evaluate operation characteristics of the sample size recalculation procedure using comparative as well as noncomparative data, assessing their dependence on parameters such as between-center heterogeneity, residual variance of observations, treatment effect size and number of centers. We compare two different estimators for between-center heterogeneity, an unadjusted and a bias-adjusted estimator, both based on quadratic forms. The type 1 error probability as well as statistical power are close to their nominal levels for all parameter combinations considered in our simulation study for the proposed unadjusted estimator, whereas the adjusted estimator exhibits some type 1 error rate inflation. Overall, the sample size recalculation procedure can be recommended to mitigate risks arising from misspecified nuisance parameters at the planning stage.

Computerized clinical decision support system for diabetes in primary care does not improve quality of care: a cluster-randomized controlled trial

Background

The EBMeDS system is the computerized clinical decision support (CCDS) system of EBPNet, a national computerized point-of-care information service in Belgium. There is no clear evidence of more complex CCDS systems to manage chronic diseases in primary care practices (PCPs). The objective of this study was to assess the effectiveness of EBMeDS use in improving diabetes care.

Methods

A cluster-randomized trial with before-and-after measurements was performed in Belgian PCPs over 1 year, from May 2017 to May 2018. We randomly assigned 51 practices to either the intervention group (IG), to receive the EBMeDS system, or to the control group (CG), to receive usual care. Primary and secondary outcomes were the 1-year pre- to post-implementation change in HbA1c, LDL cholesterol, and systolic and diastolic blood pressure. Composite patient and process scores were calculated. A process evaluation was added to the analysis. Results were analyzed at 6 and 12 months. Linear mixed models and logistic regression models based on generalized estimating equations were used where appropriate.

Results

Of the 51 PCPs that were enrolled and randomly assigned (26 PCPs in the CG and 25 in the IG), 29 practices (3815 patients) were analyzed in the study: 2464 patients in the CG and 1351 patients in the IG. No change differences existed between groups in primary or secondary outcomes. Change difference between CG and IG after 1-year follow-up was − 0.09 (95% CI − 0.18; 0.01, p-value = 0.06) for HbA1c; 1.76 (95% CI − 0.46; 3.98, p-value = 0.12) for LDL cholesterol; and 0.13 (95% CI − 0.91; 1.16, p-value = 0.81) and 0.12 (95% CI − 1.25;1.49, p-value = 0.86) for systolic and diastolic blood pressure respectively. The odds ratio of the IG versus the CG for the probability of no worsening and improvement was 1.09 (95% CI 0.73; 1.63, p-value = 0.67) for the process composite score and 0.74 (95% CI 0.49; 1.12, p-value = 0.16) for the composite patient score. All but one physician was satisfied with the EBMeDS system.

Conclusions

The CCDS system EBMeDS did not improve diabetes care in Belgian primary care. The lack of improvement was mainly caused by imperfections in the organizational context of Belgian primary care for chronic disease management and shortcomings in the system requirements for the correct use of the EBMeDS system (e.g., complete structured records). These shortcomings probably caused low-use rates of the system.

Trial registration

ClinicalTrials.gov, NCT01830569, Registered 12 April 2013.

A dashboard-based system for supporting diabetes care

Objective

To describe the development, as part of the European Union MOSAIC (Models and Simulation Techniques for Discovering Diabetes Influence Factors) project, of a dashboard-based system for the management of type 2 diabetes and assess its impact on clinical practice.

Methods

The MOSAIC dashboard system is based on predictive modeling, longitudinal data analytics, and the reuse and integration of data from hospitals and public health repositories. Data are merged into an i2b2 data warehouse, which feeds a set of advanced temporal analytic models, including temporal abstractions, care-flow mining, drug exposure pattern detection, and risk-prediction models for type 2 diabetes complications. The dashboard has 2 components, designed for (1) clinical decision support during follow-up consultations and (2) outcome assessment on populations of interest. To assess the impact of the clinical decision support component, a pre-post study was conducted considering visit duration, number of screening examinations, and lifestyle interventions. A pilot sample of 700 Italian patients was investigated. Judgments on the outcome assessment component were obtained via focus groups with clinicians and health care managers.

Results

The use of the decision support component in clinical activities produced a reduction in visit duration (P ≪ .01) and an increase in the number of screening exams for complications (P < .01). We also observed a relevant, although nonstatistically significant, increase in the proportion of patients receiving lifestyle interventions (from 69% to 77%). Regarding the outcome assessment component, focus groups highlighted the system's capability of identifying and understanding the characteristics of patient subgroups treated at the center.

Conclusion

Our study demonstrates that decision support tools based on the integration of multiple-source data and visual and predictive analytics do improve the management of a chronic disease such as type 2 diabetes by enacting a successful implementation of the learning health care system cycle.

Improving HbA1c with Glucose Self-Monitoring in Diabetic Patients with EpxDiabetes, a Phone Call and Text Message-Based Telemedicine Platform: A Randomized Controlled Trial

Background: We conducted a randomized controlled trial of EpxDiabetes, a novel digital health intervention as an adjunct therapy to reduce HbA_1c and fasting blood glucose (FBG) among patients with type 2 diabetes mellitus (T2DM). In addition, we examined the effect of social determinants of health on our system. Methods: Sixty-five (n = 65) patients were randomized at a primary care clinic. Self-reported FBG data were collected by EpxDiabetes automated phone calls or text messages. Only intervention group responses were shared with providers, facilitating follow-up and bidirectional communication. ΔHbA_1c and ΔFBG were analyzed after 6 months. Results: There was an absolute HbA_1c reduction of 0.69% in the intervention group (95% confidence interval [CI], -1.41 to 0.02) and an absolute reduction of 0.03% in the control group (95% CI, -0.88 to 0.82). For those with baseline HbA_1c >8%, HbA_1c decreased significantly by 1.17% in the intervention group (95% CI, -1.90 to -0.44), and decreased by 0.02% in the control group (95% CI, -0.99 to 0.94). FBG decreased in the intervention group by 21.6 mg/dL (95% CI, -37.56 to -5.639), and increased 13.0 mg/dL in the control group (95% CI, -47.67 to 73.69). Engagement (proportion responding to ≥25% of texts or calls over 4 weeks) was 58% for the intervention group (95% CI, 0.373-0.627) and 48% for the control group (95% CI, 0.296-0.621). Smoking, number of comorbidities, and response rate were significant predictors of ΔHbA_1c. Conclusions: EpxDiabetes helps to reduce HbA_1c in patients with uncontrolled T2DM and fosters patient-provider communication; it has definite merit as an adjunct therapy in diabetes management. Future work will focus on improving the acceptability of the system and implementation on a larger scale trial.

Diabetes Care and Management Using Electronic Medical Records: A Systematic Review

BACKGROUND

Diabetes treatment and management provide a unique opportunity for examination of the effectiveness of electronic health records (EHRs) on patient health outcomes, continuity of care, and areas for further development. This systematic literature review was designed to identify the strengths and limitations of EHR and opportunities for improvement proposed in original research and recent rigorous systematic reviews.

METHODS

This review utilized methodology adapted from PRISMA. Inclusion criteria for original research were published between March 2003 and November 2017; included randomized controlled trial design with participants ≥18 years of age with diabetes diagnosis ≥1 year; measured outcomes included HbA1c, blood pressure, and LDL cholesterol levels. Criteria for systematic reviews included research focused on EHR outcomes, improvement of care for patients with diabetes, prevention of adverse outcomes, web-based communication, and limitations of EHR regarding chronic disease management. Thirteen articles qualified for inclusion.

RESULTS

Meta-synthesis of articles suggests that chronic disease patients benefit most by decision support tools that alert physicians of drug interactions, communication tools that keep them informed and engaged in their treatment regimens and detailed reporting and tracking designed to inform progress. Collective results suggest that EHR technology is advancing rapidly; however, patient outcomes documented via EHR systems remain largely unknown.

CONCLUSION

A fertile area for inquiry designed to enhance patient outcomes in diabetes and chronic disease management is determining how EHR systems can be utilized for new drug and treatment options in addition to enhancing the quality, cost-effectiveness, and continuity of care.

What are the current 'top five' perceived educational needs of Irish general practitioners?

INTRODUCTION

Doctors' continuing medical educational and professional development (CME and CPD) needs are known to be strongly influenced by national and local contextual characteristics. A crucial step in the development of effective education and training programmes is the assessment of learner needs.

METHODS

A national needs assessment was conducted among general practitioners (GPs) in the Republic of Ireland who attended continuing medical education small group learning meetings (CME-SGL) in late 2017. Doctors completed a self-administered anonymous three-page questionnaire which gathered demographic data and asked them to choose their 'top five' perceived educational needs from separate lists of topics for CME and CPD.

RESULTS

There were 1669 responses (98% of monthly attendance). The topics most commonly identified as a priority for further CME were prescribing (updates/therapeutics), elderly medicine, management of common chronic conditions, dermatology, and patient safety/medical error. The most commonly selected CPD topics were applying evidence-based guidelines to practice, appraising performance/conducting practice audits, coping with change, and managing risk and legal medicine. There was no difference between urban and rural practice settings regarding the most commonly chosen topics in each category; however, more rural GPs selected pre-hospital/emergency care as one of their 'top five'.

CONCLUSION

Our findings identified priority areas where CME and CPD for GPs in Ireland should focus. The topics selected may reflect the changing nature of general practice, which increasingly requires delivery of care to an ageing population with more multi-morbidity and chronic disease management, while trying to apply evidence-based medicine and consider patient safety issues. CME/CPD programmes need to adapt accordingly.

The effect of computerized decision support systems on cardiovascular risk factors: a systematic review and meta-analysis

Background

Cardiovascular risk management (CVRM) is notoriously difficult because of multi-morbidity and the different phenotypes and severities of cardiovascular disease. Computerized decision support systems (CDSS) enable the clinician to integrate the latest scientific evidence and patient information into tailored strategies. The effect on cardiovascular risk factor management is yet to be confirmed.

Methods

We performed a systematic review and meta-analysis evaluating the effects of CDSS on CVRM, defined as the change in absolute values and attainment of treatment goals of systolic blood pressure (SBP), low density lipoprotein cholesterol (LDL-c) and HbA1c. Also, CDSS characteristics related to more effective CVRM were identified. Eligible articles were methodologically appraised using the Cochrane risk of bias tool. We calculated mean differences, relative risks, and if appropriate (I² < 70%), pooled the results using a random-effects model.

Results

Of the 14,335 studies identified, 22 were included. Four studies reported on SBP, 3 on LDL-c, 10 on CVRM in patients with type II diabetes and 5 on guideline adherence. The CDSSs varied considerably in technical performance and content. Heterogeneity of results was such that quantitative pooling was often not appropriate. Among CVRM patients, the results tended towards a beneficial effect of CDSS, but only LDL-c target attainment in diabetes patients reached statistical significance. Prompting, integration into the electronical health record, patient empowerment, and medication support were related to more effective CVRM.

Conclusion

We did not find a clear clinical benefit from CDSS in cardiovascular risk factor levels and target attainment. Some features of CDSS seem more promising than others. However, the variability in CDSS characteristics and heterogeneity of the results – emphasizing the immaturity of this research area - limit stronger conclusions. Clinical relevance of CDSS in CVRM might additionally be sought in the improvement of shared decision making and patient empowerment.

Electronic supplementary material

The online version of this article (10.1186/s12911-019-0824-x) contains supplementary material, which is available to authorized users.

Toward Standardized Monitoring of Patients With Chronic Diseases in Primary Care Using Electronic Medical Records: Systematic Review

Background

Long-term care for patients with chronic diseases poses a huge challenge in primary care. In particular, there is a deficit regarding monitoring and structured follow-up. Appropriate electronic medical records (EMRs) could help improving this but, so far, there are no evidence-based specifications concerning the indicators that should be monitored at regular intervals.

Objective

The aim was to identify and collect a set of evidence-based indicators that could be used for monitoring chronic conditions at regular intervals in primary care using EMRs.

Methods

We searched MEDLINE (Ovid), Embase (Elsevier), the Cochrane Library (Wiley), the reference lists of included studies and relevant reviews, and the content of clinical guidelines. We included primary studies and guidelines reporting about indicators that allow for the assessment of care and help monitor the status and process of disease for five chronic conditions, including type 2 diabetes mellitus, asthma, arterial hypertension, chronic heart failure, and osteoarthritis.

Results

The use of the term “monitoring” in terms of disease management and long-term care for patients with chronic diseases is not widely used in the literature. Nevertheless, we identified a substantial number of disease-specific indicators that can be used for routine monitoring of chronic diseases in primary care by means of EMRs.

Conclusions

To our knowledge, this is the first systematic review summarizing the existing scientific evidence on the standardized long-term monitoring of chronic diseases using EMRs. In a second step, our extensive set of indicators will serve as a generic template for evaluating their usability by means of an adapted Delphi procedure. In a third step, the indicators will be summarized into a user-friendly EMR layout.

Sample size calculation in multi-centre clinical trials

Background

Multi-centre randomized controlled clinical trials play an important role in modern evidence-based medicine. Advantages of collecting data from more than one site are numerous, including accelerated recruitment and increased generalisability of results. Mixed models can be applied to account for potential clustering in the data, in particular when many small centres contribute patients to the study. Previously proposed methods on sample size calculation for mixed models only considered balanced treatment allocations which is an unlikely outcome in practice if block randomisation with reasonable choices of block length is used.

Methods

We propose a sample size determination procedure for multi-centre trials comparing two treatment groups for a continuous outcome, modelling centre differences using random effects and allowing for arbitrary sample sizes. It is assumed that block randomisation with fixed block length is used at each study site for subject allocation. Simulations are used to assess operation characteristics such as power of the sample size approach. The proposed method is illustrated by an example in disease management systems.

Results

A sample size formula as well as a lower and upper boundary for the required overall sample size are given. We demonstrate the superiority of the new sample size formula over the conventional approach of ignoring the multi-centre structure and show the influence of parameters such as block length or centre heterogeneity. The application of the procedure on the example data shows that large blocks require larger sample sizes, if centre heterogeneity is present.

Conclusion

Unbalanced treatment allocation can result in substantial power loss when centre heterogeneity is present but not considered at the planning stage. When only few patients by centre will be recruited, one has to weigh the risk of imbalance between treatment groups due to large blocks and the risk of unblinding due to small blocks. The proposed approach should be considered when planning multi-centre trials.

Electronic supplementary material

The online version of this article (10.1186/s12874-018-0602-y) contains supplementary material, which is available to authorized users.

The role of the chronic care model in promoting the management of the patient with rare liver disease

INTRODUCTION

The chronic care model (CCM) provides a holistic approach for managing chronic illnesses. Patients with rare liver diseases (RLD) have complex needs, impaired quality of life and often life-threatening complications. Most RLD meet the criteria for a long-term chronic condition and should be viewed through the prism of CCM. We aimed to ascertain whether the CCM has been considered for the frequently-encountered RLD.

METHODS

MEDLINE®/PubMed®/Cochrane/EMBASE were searched to identify publications relating to the use of the CCM for the management of six RLD. We identified 33 articles eligible for inclusion.

RESULTS

Six, eleven, one, thirteen, two and zero studies, discussed individual components of the CCM for autoimmune hepatitis (AIH), primary biliary cholangitis (PBC), primary sclerosing cirrhosis (PSC), Wilsons disease (WD), alpha-1 antitrypsin deficiency (A1AD) and lysosomal acid lipase deficiency (LALd) respectively. We have not identified studies using the full CCM for any of the aforementioned RLD.

DISCUSSION

Unlike in common chronic conditions e.g. diabetes, there has been limited consideration of the use of CCM (or its components) for the management of RLD. This may reflect a reluctance of the clinical community to view these diseases as chronic or lack of healthcare policy investment in rare diseases in general.

The Impact of Patient Online Access to Computerized Medical Records and Services on Type 2 Diabetes: Systematic Review

Background

Online access to computerized medical records has the potential to improve convenience, satisfaction, and care for patients, and to facilitate more efficient organization and delivery of care.

Objective

The objective of this review is to explore the use and impact of having online access to computerized medical records and services for patients with type 2 diabetes mellitus in primary care.

Methods

Multiple international databases including Medline, Embase, CINAHL, PsycINFO and the Cochrane Library were searched between 2004 and 2016. No limitations were placed on study design, though we applied detailed inclusion and exclusion criteria to each study. Thematic analysis was used to synthesize the evidence. The Mixed Methods Appraisal Toolkit was used to appraise study quality.

Results

A search identified 917 studies, of which 28 were included. Five themes were identified: (1) disparities in uptake by age, gender, ethnicity, educational attainment, and number of comorbidities, with young men in full-time employment using these services most; (2) improved health outcomes: glycemic control was improved, but blood pressure results were mixed; (3) self-management support from improved self-care and shared management occurred especially soon after diagnosis and when complications emerged. There was a generally positive effect on physician-patient relationships; (4) accessibility: patients valued more convenient access when online access to computerized medical records and services work; and (5) technical challenges, barriers to use, and system features that impacted patient and physician use. The Mixed Methods Appraisal Toolkit rated 3 studies as 100%, 19 studies as 75%, 4 studies as 50%, and 1 study scored only 25%.

Conclusions

Patients valued online access to computerized medical records and services, although in its current state of development it may increase disparities. Online access to computerized medical records appears to be safe and is associated with improved glycemic control, but there was a lack of rigorous evidence in terms of positive health outcomes for other complications, such as blood pressure. Patients remain concerned about how these systems work, the rules, and timeliness of using these systems.

Diabetes care providers' opinions and working methods after four years of experience with a diabetes patient web portal; a survey among health care providers in general practices and an outpatient clinic

BACKGROUND

To gain insight into the opinions and working methods of diabetes care providers after using a diabetes web portal for 4 years in order to understand the role of the provider in patients' web portal use.

METHODS

Survey among physicians and nurses from general practices and an outpatient clinic, correlated with data from the common web portal.

RESULTS

One hundred twenty-eight questionnaires were analysed (response rate 56.6%). Responders' mean age was 46.2 ± 9.8 years and 43.8% were physicians. The majority was of opinion that the portal improves patients' diabetes knowledge (90.6%) and quality of care (72.7%). Although uploading glucose diary (93.6%) and patient access to laboratory and clinical notes (91.2 and 71.0%) were considered important, these features were recommended to patients in only 71.8 and 19.5% respectively. 64.8% declared they informed their patients about the portal and 45.3% handed-out the information leaflet and website address. The portal was especially recommended to type 1 diabetes patients (78.3%); those on insulin (84.3%) and patients aged< 65 years (72.4%). Few found it timesaving (21.9%). Diabetes care providers' opinions were not associated with patients' portal use.

CONCLUSIONS

Providers are positive about patients web portals but still not recommend or encourage the use to all patients. There seems room for improvement in their working methods.

Comprehensive process model of clinical information interaction in primary care: results of a "best-fit" framework synthesis

Objective

To describe a new, comprehensive process model of clinical information interaction in primary care (Clinical Information Interaction Model, or CIIM) based on a systematic synthesis of published research.

Materials and Methods

We used the "best fit" framework synthesis approach. Searches were performed in PubMed, Embase, the Cumulative Index to Nursing and Allied Health Literature (CINAHL), PsycINFO, Library and Information Science Abstracts, Library, Information Science and Technology Abstracts, and Engineering Village. Two authors reviewed articles according to inclusion and exclusion criteria. Data abstraction and content analysis of 443 published papers were used to create a model in which every element was supported by empirical research.

Results

The CIIM documents how primary care clinicians interact with information as they make point-of-care clinical decisions. The model highlights 3 major process components: (1) context, (2) activity (usual and contingent), and (3) influence. Usual activities include information processing, source-user interaction, information evaluation, selection of information, information use, clinical reasoning, and clinical decisions. Clinician characteristics, patient behaviors, and other professionals influence the process.

Discussion

The CIIM depicts the complete process of information interaction, enabling a grasp of relationships previously difficult to discern. The CIIM suggests potentially helpful functionality for clinical decision support systems (CDSSs) to support primary care, including a greater focus on information processing and use. The CIIM also documents the role of influence in clinical information interaction; influencers may affect the success of CDSS implementations.

Conclusion

The CIIM offers a new framework for achieving CDSS workflow integration and new directions for CDSS design that can support the work of diverse primary care clinicians.

The effectiveness of telemedicine on body mass index: A systematic review and meta-analysis

OBJECT

The purpose of this study was to evaluate the clinical effectiveness of telemedicine on changes in body mass index for overweight and obese people as well as for diabetes and hypertension patients.

METHODS

A systematic review of articles published before 31 August 2014, was conducted using searches of Medline, Cochrane Library, EMBASE, and CINAHL Plus. The inclusion criteria were randomised controlled trials that compared telemedicine interventions with usual care or standard treatment in adults and reported a change in body mass index. A meta-analysis was conducted for eligible studies, and the primary outcome was a change in body mass index. Subgroup analysis was performed for the type of telemedicine, main purpose of intervention, and length of intervention.

RESULTS

Twenty-five randomised controlled trials comprising 6253 people were included in the qualitative and quantitative analyses. The length of intervention ranged from nine weeks to two years. The meta-analysis revealed significant differences in body mass index changes (pooled difference in means = -0.49, 95% confidence interval -0.63 to -0.34, p < 0.001) between the telemedicine and control groups. The subgroup analyses found that either Internet-based or telephone-based intervention was associated with greater changes in body mass index than in controls. Telemedicine intervention was effective in improving body mass index whether it was used for diabetes control, hypertension control, weight loss, or increasing physical activity and was also effective for people with and without diabetes or hypertension. However, only interventions with a duration ≥ 6 months significantly decreased body mass index compared to controls.

CONCLUSION

Both patients with chronic disease and overweight/obese people could benefit from telemedicine interventions. We suggest that an effective telemedicine approach should be longer than six months and emphasise the importance of post-interventional follow-ups.

Designing Decision-Support Technologies for Patient-Generated Data in Type 1 Diabetes

People living with type 1 diabetes generate data as a byproduct of diabetes management. The development of decision support technologies can be enabled by harnessing these patient-generated data, but a major challenge is for these technologies to provide meaningful and highly personalized guidance to support individual patients' decision-making processes. In this paper, results from a year-long qualitative study were reported. Twenty-six people with type 1 diabetes were interviewed regarding the types of self-generated data they use for decision-making, their decision-making processes using self-generated data, and the difficulties they experience when attempting to use this data for decision-making. These patients' behaviors and difficulties point to new approaches to designing decision support technologies for personal use, including patient-centered and automated data entry, automated and individualized data analysis, and humanized output.

Importance of an alternative approach to measuring quality in a volume-to-value world: a case study of diabetes care

Background

To develop a statistical tool that allows practitioners and/or their practice managers to easily select the relevant range in which volume and value are maximised.

Methods

Data for the study were based on 55 primary care practices that participated in the Colorado Improving Performance in Practice programme in 2014. We used two composite variables including the volume of processes of care variables listed in Diabetes Practice Guidelines and value (quality) as measured by changes in the intermediate outcomes. We assessed volume/value trade-offs using a multilevel model with a time-varying covariate partitioned into a between-practice and within-practice effect.

Results

The study revealed a strong linear relationship between volume and value (P<0.0001). Specifically, practices with an above-average volume of care as measured by their process of care scores also had above-average quality outcomes (expected value 57; average volume 49.48) as quantified by their intermediate outcome scores. Additionally, in those months when practices provided a volume of care that exceeded their average process of care score, further improvements occurred in quality as measured by intermediate outcome scores (P<0.0001).

Conclusion

Such findings suggest an inherent linkage between volume of care and quality. This statistical approach, if provided as an app containing an easy-to-use statistical calculator, will allow practice managers and clinicians to systematically identify volume/quality trade-offs, thereby reducing undertreatment and/or overtreatment among patients with chronicities.

Effects of consumer-oriented health information technologies in diabetes management over time: a systematic review and meta-analysis of randomized controlled trials

Objective

To reveal the effects of consumer-oriented health information technologies (CHITs) on patient outcomes in diabetes management over time through systematic review and meta-analysis.

Methods

We searched 5 electronic databases (from database inception to July 2016) for studies that reported on randomized controlled trials examining the effects of CHITs on glycemic control and other patient outcomes in diabetes management. Data were analyzed using either meta-analysis or a narrative synthesis approach.

Results

Eighty randomized controlled trial studies, representing 87 individual trials, were identified and included for analysis. Overall, the meta-analysis showed that the use of CHITs resulted in significant improvement in glycemic control compared to usual care (standardized mean difference = -0.31%, 95% confidence interval -0.38 to -0.23, P  < .001) in patients with diabetes. Specifically, improvement in glycemic control was significant at intervention durations of 3, 6, 8, 9, 12, 15, 30, and 60 months, while no significant differences were found at other time points reported. The narrative synthesis provided mixed effects of CHITs on other clinical, psychosocial, behavioral, and knowledge outcomes.

Conclusions

The use of CHITs appears to be more effective than usual care in improving glycemic control for patients with diabetes. However, their effectiveness did not remain consistent over time and in other patient outcomes. Further efforts are required to examine long-term effects of CHITs and to explore factors that can moderate the effects over time.

E-healthcare for Diabetes Mellitus Type 2 Patients - A Randomised Controlled Trial in Slovenia

BACKGROUND

Telemonitoring and web-based interventions are increasingly used in primary-care practices in many countries for more effective management of patients with diabetes mellitus (DM). A new approach in treating patients with diabetes mellitus in family practices, based on ICT use and nurse practitioners, has been introduced and evaluated in this study.

METHOD

Fifteen Slovene family practices enrolled 120 DM patients treated only with a diet regime and/or tablets into the study. 58 of them were included into the interventional group, and the other 62 DM patients into the control group, within one-year-long interventional, randomised controlled trial. Patients in the control group had conventional care for DM according to Slovenian professional guidelines, while the patients in the interventional group were using also the eDiabetes application. Patients were randomised through a balanced randomisation process.

RESULTS

Significant reductions of glycated haemoglobin (HbA1c) values were found after 6 and 12 months among patients using this eDiabetes application (p<0.05). Among these patients, a significant correlation was also found between self-monitored blood pressure and the final HbA1c values. Diabetic patients' involvement in web-based intervention had only transient impact on their functional health status.

CONCLUSION

This eDiabetes application was confirmed to be an innovative approach for better self-management of DM type 2 patients not using insulin. Both a significant reduction of HbA1c values and a significant correlation between the average self-measured blood pressure and the final HbA1c values in the interventional group were found. Nurse practitioners - as diabetes care coordinators - could contribute to better adherence in diabetes e-care.

COMBAT study - Computer based assessment and treatment - A clinical trial evaluating impact of a computerized clinical decision support tool on pain in cancer patients

BACKGROUND AND AIMS

The prevalence of pain in cancer patients are relatively high and indicate inadequate pain management strategies. Therefore, it is necessary to develop new methods and to improve implementation of guidelines to assess and treat pain. The vast improvement in information technology facilitated development of a computerized symptom assessment and decision support system (CCDS) - the Combat system - which was implemented in an outpatient cancer clinic to evaluate improvement in pain management.

METHODS

We conducted a controlled before-and-after study between patient cohorts in two consecutive study periods: before (n=80) and after (n=134) implementation of the Combat system. Patients in the first cohort completed questionnaires with the paper-and-pencil method and this data was not shown to physicians. Patients in the latter cohort completed an electronic questionnaire by using an iPad and the data were automatically transferred and presented to physicians at point of care. Additionally, the system provided computerized decision support at point of care for the physician based on the electronic questionnaires completed by the patients, an electronic CRF completed by physicians and clinical guidelines.

RESULTS

The Combat system did not improve pain intensity and there were no significant alterations in the prescribed dose of opiates compared to the cohort of patients managed without the Combat system.

CONCLUSION

The Combat system did not improve pain management. This may be explained by several factors, however, we consider lack of proper implementation of the CCDS in the clinic to be the most important factor. As a result, we did not manage to change the behaviour of the physicians in the clinic.

IMPLICATIONS

There is a need to conduct larger prospective studies to evaluate the efficacy of modern information technology to improve pain management in cancer patients. Before introducing new information technology in the clinics, it is important to have a well thought out implementation strategy. The trial is registered at Clinialtrials.gov, number NCT01795157.

Monitoring-Based Model for Personalizing the Clinical Process of Crohn's Disease

Crohn’s disease is a chronic pathology belonging to the group of inflammatory bowel diseases. Patients suffering from Crohn’s disease must be supervised by a medical specialist for the rest of their lives; furthermore, each patient has its own characteristics and is affected by the disease in a different way, so health recommendations and treatments cannot be generalized and should be individualized for a specific patient. To achieve this personalization in a cost-effective way using technology, we propose a model based on different information flows: control, personalization, and monitoring. As a result of the model and to perform a functional validation, an architecture based on services and a prototype of the system has been defined. In this prototype, a set of different devices and technologies to monitor variables from patients and their environment has been integrated. Artificial intelligence algorithms are also included to reduce the workload related to the review and analysis of the information gathered. Due to the continuous and automated monitoring of the Crohn’s patient, this proposal can help in the personalization of the Crohn’s disease clinical process.

Effectiveness of shared goal setting and decision making to achieve treatment targets in type 2 diabetes patients: A cluster-randomized trial (OPTIMAL)

Objective

About 20% of patients with type 2 diabetes achieve all their treatment targets. Shared decision making (SDM) using a support aid based on the 5‐years results of the ADDITION study on multifactorial treatment, could increase this proportion.

Research design and methods

Cluster‐randomized trial in 35 former ADDITION primary care practices. Practices were randomized to SDM or care as usual (1:1). Both ADDITION and non‐ADDITION type 2 diabetes patients, 60‐80 years, known with diabetes for 8‐12 years, were included. In the intervention group, patients were presented evidence about the relationship between treatment intensity and cardiovascular events. They chose intensive or less intensive treatment and prioritized their targets. After 1 year priorities could be rearranged. Follow‐up: 24 months. Intention‐to‐treat analysis. Main outcome measure: proportion of patients that achieved all three treatment targets.

Results

At baseline 26.4% in the SDM group (n=72) had already achieved all three treatment goals (CG: 23.5%, n=81). In the SDM group 44 patients chose intensive treatment, 25 continued their former less intensive treatment and three people switched from the more to the less intensive protocol. After 24 months 31.8% of the patients in the SDM group achieved all three treatment targets (CG: 25.3%), RR 1.26 (95% CI 0.81‐1.95). Mean systolic blood pressure decreased in the SDM group (−5.4 mm Hg, P<.01), mean HbA1c and total cholesterol did not change.

Conclusions

Despite an already high baseline level of diabetes care, we found strong indications that SDM on both intensity of treatment and prioritizing treatment goals further improved outcomes.

Effect of telemedicine on glycated hemoglobin in diabetes: a systematic review and meta-analysis of randomized trials

BACKGROUND

Telemedicine, the use of telecommunications to deliver health services, expertise and information, is a promising but unproven tool for improving the quality of diabetes care. We summarized the effectiveness of different methods of telemedicine for the management of diabetes compared with usual care.

METHODS

We searched MEDLINE, Embase and the Cochrane Central Register of Controlled Trials databases (to November 2015) and reference lists of existing systematic reviews for randomized controlled trials (RCTs) comparing telemedicine with usual care for adults with diabetes. Two independent reviewers selected the studies and assessed risk of bias in the studies. The primary outcome was glycated hemoglobin (HbA1C) reported at 3 time points (≤ 3 mo, 4-12 mo and > 12 mo). Other outcomes were quality of life, mortality and episodes of hypoglycemia. Trials were pooled using randomeffects meta-analysis, and heterogeneity was quantified using the I2 statistic.

RESULTS

From 3688 citations, we identified 111 eligible RCTs (n = 23 648). Telemedicine achieved significant but modest reductions in HbA1C in all 3 follow-up periods (difference in mean at ≤ 3 mo: -0.57%, 95% confidence interval [CI] -0.74% to -0.40% [39 trials]; at 4-12 mo: -0.28%, 95% CI -0.37% to -0.20% [87 trials]; and at > 12 mo: -0.26%, 95% CI -0.46% to -0.06% [5 trials]). Quantified heterogeneity (I2 statistic) was 75%, 69% and 58%, respectively. In meta-regression analyses, the effect of telemedicine on HbA1C appeared greatest in trials with higher HbA1C concentrations at baseline, in trials where providers used Web portals or text messaging to communicate with patients and in trials where telemedicine facilitated medication adjustment. Telemedicine had no convincing effect on quality of life, mortality or hypoglycemia.

INTERPRETATION

Compared with usual care, the addition of telemedicine, especially systems that allowed medication adjustments with or without text messaging or a Web portal, improved HbA1C but not other clinically relevant outcomes among patients with diabetes.

Impact of Information Technology-Based Interventions for Type 2 Diabetes Mellitus on Glycemic Control: A Systematic Review and Meta-Analysis

BACKGROUND

Information technology-based interventions are increasingly being used to manage health care. However, there is conflicting evidence regarding whether these interventions improve outcomes in people with type 2 diabetes.

OBJECTIVE

The objective of this study was to conduct a systematic review and meta-analysis of clinical trials, assessing the impact of information technology on changes in the levels of hemoglobin A_1c (HbA_1c) and mapping the interventions with chronic care model (CCM) elements.

METHODS

Electronic databases PubMed and EMBASE were searched to identify relevant studies that were published up until July 2016, a method that was supplemented by identifying articles from the references of the articles already selected using the electronic search tools. The study search and selection were performed by independent reviewers. Of the 1082 articles retrieved, 32 trials (focusing on a total of 40,454 patients) were included. A random-effects model was applied to estimate the pooled results.

RESULTS

Information technology-based interventions were associated with a statistically significant reduction in HbA_1c levels (mean difference -0.33%, 95% CI -0.40 to -0.26, P<.001). Studies focusing on electronic self-management systems demonstrated the largest reduction in HbA_1c (0.50%), followed by those with electronic medical records (0.17%), an electronic decision support system (0.15%), and a diabetes registry (0.05%). In addition, the more CCM-incorporated the information technology-based interventions were, the more improvements there were in HbA_1c levels.

CONCLUSIONS

Information technology strategies combined with the other elements of chronic care models are associated with improved glycemic control in people with diabetes. No clinically relevant impact was observed on low-density lipoprotein levels and blood pressure, but there was evidence that the cost of care was lower.

Implementing an evidence-based computerized decision support system linked to electronic health records to improve care for cancer patients: the ONCO-CODES study protocol for a randomized controlled trial

BACKGROUND

Computerized decision support systems (CDSSs) are computer programs that provide doctors with person-specific, actionable recommendations, or management options that are intelligently filtered or presented at appropriate times to enhance health care. CDSSs might be integrated with patient electronic health records (EHRs) and evidence-based knowledge.

METHODS/DESIGN

The Computerized DEcision Support in ONCOlogy (ONCO-CODES) trial is a pragmatic, parallel group, randomized controlled study with 1:1 allocation ratio. The trial is designed to evaluate the effectiveness on clinical practice and quality of care of a multi-specialty collection of patient-specific reminders generated by a CDSS in the IRCCS Istituto Scientifico Romagnolo per lo Studio e la Cura dei Tumori (IRST) hospital. We hypothesize that the intervention can increase clinician adherence to guidelines and, eventually, improve the quality of care offered to cancer patients. The primary outcome is the rate at which the issues reported by the reminders are resolved, aggregating specialty and primary care reminders. We will include all the patients admitted to hospital services. All analyses will follow the intention-to-treat principle.

DISCUSSION

The results of our study will contribute to the current understanding of the effectiveness of CDSSs in cancer hospitals, thereby informing healthcare policy about the potential role of CDSS use. Furthermore, the study will inform whether CDSS may facilitate the integration of primary care in cancer settings, known to be usually limited. The increasing use of and familiarity with advanced technology among new generations of physicians may support integrated approaches to be tested in pragmatic studies determining the optimal interface between primary and oncology care.

TRIAL REGISTRATION

ClinicalTrials.gov, NCT02645357.