Computerized decision support systems in primary care for type 2 diabetes patients only improve patients' outcomes when combined with feedback on performance and case management: a systematic review

Protocol of a patient randomized clinical trial to improve medication adherence in primary care

BACKGROUND

Enhanced awareness of poor medication adherence could improve patient care. This article describes the original and adapted protocols of a randomized trial to improve medication adherence for cardiometabolic conditions.

METHODS

The original protocol entailed a cluster randomized trial of 28 primary care clinics allocated to either (i) medication adherence enhanced chronic disease care clinical decision support (eCDC-CDS) integrated within the electronic health record (EHR) or (ii) usual care (non-enhanced CDC-CDS). Enhancements comprised (a) electronic interfaces printed for patients and clinicians at primary care encounters that encouraged discussion about specific medication adherence issues that were identified, and (b) pharmacist phone outreach. Study subjects were individuals who at an index visit were aged 18-74 years and not at evidence-based care goals for hypertension (HTN), diabetes mellitus (DM), or lipid management, along with low medication adherence (proportion of days covered [PDC] <80%) for a corresponding medication. The primary study outcomes were improved medication adherence and clinical outcomes (BP and A1C) at 12 months. Protocol adaptation became imperative in response to major implementation challenges: (a) the availability of EHR system-wide PDC calculations that superseded our ability to limit PDC adherence information solely to intervention clinics; (b) the unforeseen closure of pharmacies committed to conducting the pharmacist outreach; and (c) disruptions and clinic closures due to the Covid-19 pandemic.

CONCLUSION

This manuscript details the protocol of a study to assess whether enhanced awareness of medication adherence issues in primary care settings could improve patient outcomes. The need for protocol adaptation arose in response to multiple implementation challenges.

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.

The levels and trends of diabetes prevalence at national and sub-national levels in Iran (1990 - 2016)

Background

The increasing trends in Diabetes prevalence and its attributed burden emphasized as an important issue that needs serious and urgent attention, all over the word. We estimated the mean Fasting Plasma Glucose (FPG) and the prevalence of Diabetes in aged 25 years or older Iranian adults, by sex, age, province, and year through the time period of 1990 to 2016.

Methods

In order to access the most comprehensive relevant data at the same time the systematic data searched added to the data of 5 national surveys and 7 sub-national population based investigations. Two round of modeling, including the Age-Spatio-Temporal and Gaussian Process Regression were used for estimation of mean FPG trend and uncertainties. To estimate Diabetes estimations in target groups, a crosswalk model was applies to the FPG estimates. The model reiterated separately for women and men. All of estimations standardized based on the Iran national census population of 2016 by year, age groups and sexes at national and sub-national levels.

Results

In 2016, the number of the diabetic population was 4.43 (3.93-4.99) million (2.38 million women). Between 1990 and 2016, the age-standardized mean of FPG increased from 84.69 mg/dl (79.8-89.8) to 100.5 mg/dl (97.9-103.3) in women and from 82.7 mg/dl (78.3-87.5) to 98.8 mg/dl (96.2-101.4) in men. Simultaneously, with considerable difference, the Diabetes prevalence, has increased from 6.1% (4.7-7.8) to 9.8% (8.7-11.1) in women and from 5.0% 18 (3.8-6.3) to 8.1% (7.2-9.2) in men (75% attributed to population growth). Considering the geographical patterns, the greatest increment in the prevalence of Diabetes detected in the northwestern and the central provinces.

Conclusion

Significant increasing trends of Diabetes led to alarming threat, which can make the strategies and goals of our prevention programs out of control. We should plan for more effective communicative interventions for prevention and management of Diabetes, to be designed, implemented and monitored based on the updated scientific evidence.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40200-023-01197-2.

Effect of Clinical Decision Support at Community Health Centers on the Risk of Cardiovascular Disease: A Cluster Randomized Clinical Trial

IMPORTANCE

Management of cardiovascular disease (CVD) risk in socioeconomically vulnerable patients is suboptimal; better risk factor control could improve CVD outcomes.

OBJECTIVE

To evaluate the impact of a clinical decision support system (CDSS) targeting CVD risk in community health centers (CHCs).

DESIGN, SETTING, AND PARTICIPANTS

This cluster randomized clinical trial included 70 CHC clinics randomized to an intervention group (42 clinics; 8 organizations) or a control group that received no intervention (28 clinics; 7 organizations) from September 20, 2018, to March 15, 2020. Randomization was by CHC organization accounting for organization size. Patients aged 40 to 75 years with (1) diabetes or atherosclerotic CVD and at least 1 uncontrolled major risk factor for CVD or (2) total reversible CVD risk of at least 10% were the population targeted by the CDSS intervention.

INTERVENTIONS

A point-of-care CDSS displaying real-time CVD risk factor control data and personalized, prioritized evidence-based care recommendations.

MAIN OUTCOMES AND MEASURES

One-year change in total CVD risk and reversible CVD risk (ie, the reduction in 10-year CVD risk that was considered achievable if 6 key risk factors reached evidence-based levels of control).

RESULTS

Among the 18 578 eligible patients (9490 [51.1%] women; mean [SD] age, 58.7 [8.8] years), patients seen in control clinics (n = 7419) had higher mean (SD) baseline CVD risk (16.6% [12.8%]) than patients seen in intervention clinics (n = 11 159) (15.6% [12.3%]; P < .001); baseline reversible CVD risk was similarly higher among patients seen in control clinics. The CDSS was used at 19.8% of 91 988 eligible intervention clinic encounters. No population-level reduction in CVD risk was seen in patients in control or intervention clinics; mean reversible risk improved significantly more among patients in control (-0.1% [95% CI, -0.3% to -0.02%]) than intervention clinics (0.4% [95% CI, 0.3% to 0.5%]; P < .001). However, when the CDSS was used, both risk measures decreased more among patients with high baseline risk in intervention than control clinics; notably, mean reversible risk decreased by an absolute 4.4% (95% CI, -5.2% to -3.7%) among patients in intervention clinics compared with 2.7% (95% CI, -3.4% to -1.9%) among patients in control clinics (P = .001).

CONCLUSIONS AND RELEVANCE

The CDSS had low use rates and failed to improve CVD risk in the overall population but appeared to have a benefit on CVD risk when it was consistently used for patients with high baseline risk treated in CHCs. Despite some limitations, these results provide preliminary evidence that this technology has the potential to improve clinical care in socioeconomically vulnerable patients with high CVD risk.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier: NCT03001713.

Clinical decision support systems with team-based care on type 2 diabetes improvement for Medicaid patients: A quality improvement project

BACKGROUND

The prevalence of clinical inertia, the failure of appropriate treatment intensification in diabetes treatment, is a well-documented worldwide phenomenon. This project addresses the problem of clinical inertia through three interrelated activities, clinical decision support (CDSS), team-based care, and patient engagement in diabetes management.

OBJECTIVES

The purpose of this research is to provide analysis under the State-University Partnership Learning Network regarding the impact of an electronic decision support tool combined with team-based care workflow on provider decision-making and patient outcomes for the treatment of poorly controlled diabetes mellitus (diabetes) among patients receiving Kentucky Medicaid. The objectives of this study are to 1) assess clinical outcomes of type 2 diabetes in the Medicaid population with team-based care using CDSS, 2) evaluate physicians' and pharmacists' experience on CDSS.

METHODS

This is a quality improvement project using a mixed-method - longitudinal and control group comparison of outcomes based upon clinical measures and online surveys of providers and pharmacists involved in this project.

RESULTS

Patients treated by providers who changed the treatment regimen to one that either fully or partially followed the recommendation of the CDSS tool had a statistically significant reduction in HbA1c with an average initial HbA1c of 10.1 and the final HbA1c of 8. The online survey of physicians shows that more than 80% of physicians agree the use of CDSS will support improved patient outcomes. The use of a team-based care approach that includes pharmacists in implementing treatment changes was broadly supported by both physicians and pharmacists.

CONCLUSION

CDSS combined with team-based care can be effective in reducing HbA1c to targeted therapeutic levels. The use of CDSS provides a way to efficiently assess more than 160 potential frontline drugs and properly accelerate treatment. Consistent with the research literature, the inclusion of pharmacists can play a key role in team-based care to assess treatment alternatives and provide for improvement in outcomes and patient adherence for diabetes. The user surveys show both physicians and pharmacists have a positive attitude toward CDSS.

Using Electronic Health Record-Based Clinical Decision Support to Provide Social Risk-Informed Care in Community Health Centers: Protocol for the Design and Assessment of a Clinical Decision Support Tool

Background

Consistent and compelling evidence demonstrates that social and economic adversity has an impact on health outcomes. In response, many health care professional organizations recommend screening patients for experiences of social and economic adversity or social risks—for example, food, housing, and transportation insecurity—in the context of care. Guidance on how health care providers can act on documented social risk data to improve health outcomes is nascent. A strategy recommended by the National Academy of Medicine involves using social risk data to adapt care plans in ways that accommodate patients’ social risks.

Objective

This study’s aims are to develop electronic health record (EHR)–based clinical decision support (CDS) tools that suggest social risk–informed care plan adaptations for patients with diabetes or hypertension, assess tool adoption and its impact on selected clinical quality measures in community health centers, and examine perceptions of tool usability and impact on care quality.

Methods

A systematic scoping review and several stakeholder activities will be conducted to inform development of the CDS tools. The tools will be pilot-tested to obtain user input, and their content and form will be revised based on this input. A randomized quasi-experimental design will then be used to assess the impact of the revised tools. Eligible clinics will be randomized to a control group or potential intervention group; clinics will be recruited from the potential intervention group in random order until 6 are enrolled in the study. Intervention clinics will have access to the CDS tools in their EHR, will receive minimal implementation support, and will be followed for 18 months to evaluate tool adoption and the impact of tool use on patient blood pressure and glucose control.

Results

This study was funded in January 2020 by the National Institute on Minority Health and Health Disparities of the National Institutes of Health. Formative activities will take place from April 2020 to July 2021, the CDS tools will be developed between May 2021 and November 2022, the pilot study will be conducted from August 2021 to July 2022, and the main trial will occur from December 2022 to May 2024. Study data will be analyzed, and the results will be disseminated in 2024.

Conclusions

Patients’ social risk information must be presented to care teams in a way that facilitates social risk–informed care. To our knowledge, this study is the first to develop and test EHR-embedded CDS tools designed to support the provision of social risk–informed care. The study results will add a needed understanding of how to use social risk data to improve health outcomes and reduce disparities.

International Registered Report Identifier (IRRID)

PRR1-10.2196/31733

The Impact of Guideline Integration into Electronic Medical Records on Outcomes for Patients with Diabetes: A Systematic Review

Optimal strategies for integration of clinical practice guidelines into electronic medical records and its impact on processes of care and clinical outcomes in diabetic patients are not well understood. A systematic review of CINAHL, MEDLINE, PubMed, and Cochrane Library databases in August 2016, November 2017, and June 2020 was conducted. Studies investigating integration of diabetes guidelines into ambulatory care electronic medical records reporting quantitative results were included. After screening 15,783 records, 21 articles were included. Lipid and blood pressure control consistently improved with guideline integration, but A1c control remained equivocal. Electronic guideline integration improved microvascular complication screening, vaccination, and documentation of cardiovascular risk factors, while medication prescription and blood pressure, lipid, and A1c documentation did not improve. Studies employing a combination of electronic record intervention strategies were associated with improvement in monitoring and attainment of guideline and screening targets. Thus, strategies employing combinations of interventions to incorporate guidelines into electronic records may improve processes of care and some clinical outcomes.

Clinical efficacy and plausibility of a smartphone-based integrated online real-time diabetes care system via glucose and diet data management: a pilot study

BACKGROUND

Smartphones have become novel healthcare tools for patients with diabetes. However, it is uncertain whether the smartphone application support system helps in glycaemic control in patients with type 2 diabetes.

AIMS

To evaluate the efficacy and plausibility of smartphone-based integrated online real-time diabetes care.

METHODS

Forty patients with type 2 diabetes were randomly assigned to the smartphone-based care (SC) (n = 20) and conventional care (CC) (n = 20) groups for 12 weeks. The SC group was instructed to use smartphone application (Noom Coach) and a glucose meter, and was provided medical supervision based on blood glucose level and food intake information sent to the central database server. The efficacy was evaluated by glycated haemoglobin (A1C ≤ 6.5%). The Summary of Diabetes Self-Care Activities (SDSCA) questionnaire was collected at baseline and at week 12.

RESULTS

Seventeen and 18 patients of the SC and CC groups completed the study respectively. In the SC group, more patients achieved target A1C compared with the CC group (47.1% vs 11.1%, P = 0.019). In both group, SDSCA scores excluding the exercise item showed overall improvement (general diet, 1.4 ± 2.0 → 2.6 ± 2.3 vs 0.4 ± 1.1 → 1.8 ± 2.2; specific diet, 4.2 ± 1.7 → 5.4 ± 1.2 vs 3.8 ± 1.6 → 5.1 ± 1.1; blood glucose test, 3.3 ± 2.8 → 4.9 ± 2.3 vs 1.0 ± 2.2 → 4.7 ± 2.3; foot care, 1.5 ± 1.6 → 3.6 ± 2.8 vs 1.4 ± 1.9 → 6.1 ± 1.4; all P < 0.05). There was no difference between both groups other than the aspect of foot care (P = 0.008).

CONCLUSIONS

The smartphone-based integrated online real-time diabetes care system through glucose and diet data management showed clinical plausibility in glucose control in real clinical practice.

Comparison of Two Electronic Systems for Obtaining Diabetes Care Indicators in Clinical Practice

We compared the completeness of data captured by physicians in a diabetes outpatient clinic using a general electronic health record system versus one that was specifically geared to diabetes. Use of a diabetes-oriented data system was found to allow for greater capture of crucial variables required for diabetes care than a general electronic record and was well accepted by health care providers.

Worldwide inertia to the use of cardiorenal protective glucose-lowering drugs (SGLT2i and GLP-1 RA) in high-risk patients with type 2 diabetes

The disclosure of proven cardiorenal benefits with certain antidiabetic agents was supposed to herald a new era in the management of type 2 diabetes (T2D), especially for the many patients with T2D who are at high risk for cardiovascular and renal events. However, as the evidence in favour of various sodium-glucose transporter-2 inhibitor (SGLT2i) and glucagon-like peptide-1 receptor agonists (GLP-1 RA) accumulates, prescriptions of these agents continue to stagnate, even among eligible, at-risk patients. By contrast, dipeptidyl peptidase-4 inhibitors (DPP-4i) DPP-4i remain more widely used than SGLT2i and GLP-1 RA in these patients, despite a similar cost to SGLT2i and a large body of evidence showing no clear benefit on cardiorenal outcomes. We are a group of diabetologists united by a shared concern that clinical inertia is preventing these patients from receiving life-saving treatments, as well as placing them at greater risk of hospitalisation for heart failure and progression of renal disease. We propose a manifesto for change, in order to increase uptake of SGLT2i and GLP-1 RA in appropriate patients as a matter of urgency, especially those who could be readily switched from an agent without proven cardiorenal benefit. Central to our manifesto is a shift from linear treatment algorithms based on HbA1c target setting to parallel, independent considerations of atherosclerotic cardiovascular disease, heart failure and renal risks, in accordance with newly updated guidelines. Finally, we call upon all colleagues to play their part in implementing our manifesto at a local level, ensuring that patients do not pay a heavy price for continued clinical inertia in T2D.

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.

Supporting care for suboptimally controlled type 2 diabetes mellitus in general practice with a clinical decision support system: a mixed methods pilot cluster randomised trial

OBJECTIVES

We developed a complex intervention called DECIDE (ComputeriseD dECisIonal support for suboptimally controlleD typE 2 Diabetes mellitus in Irish General Practice) which used a clinical decision support system to address clinical inertia and support general practitioner (GP) intensification of treatment for adults with suboptimally controlled type2 diabetes mellitus (T2DM). The current study explored the feasibility and potential impact of DECIDE.

DESIGN

A pilot cluster randomised controlled trial.

SETTING

Conducted in 14 practices in Irish General Practice.

PARTICIPANTS

The DECIDE intervention was targeted at GPs. They applied DECIDE to patients with suboptimally controlled T2DM, defined as a glycated haemoglobin (HbA1c) ≥70 mmol/mol and/or blood pressure ≥150/95 mmHg.

INTERVENTION

The intervention incorporated training and a web-based clinical decision support system which supported; (i) medication intensification actions; and (ii) non-pharmacological actions to support care. Control practices delivered usual care.

PRIMARY AND SECONDARY OUTCOME MEASURES

Feasibility and acceptability was determined using thematic analysis of semi-structured interviews with GPs, combined with data from the DECIDE website. Clinical outcomes included HbA1c, medication intensification, blood pressure and lipids.

RESULTS

We recruited 14 practices and 134 patients. At 4-month follow-up, all practices and 114 patients were followed up. GPs reported finding decision support helpful navigating increasingly complex medication algorithms. However, the majority of GPs believed that the target patient group had poor engagement with GP and hospital services for a range of reasons. At follow-up, there was no difference in glycaemic control (-3.6 mmol/mol (95% CI -11.2 to 4.0)) between intervention and control groups or in secondary outcomes including, blood pressure, total cholesterol, medication intensification or utilisation of services. Continuation criteria supported proceeding to a definitive randomised trial with some modifications.

CONCLUSION

The DECIDE study was feasible and acceptable to GPs but wider impacts on glycaemic and blood pressure control need to be considered for this patient population going forward.

TRIAL REGISTRATION NUMBER

ISRCTN69498919.

Therapeutic Inertia: Still a Long Way to Go That Cannot Be Postponed

In the context of type 2 diabetes, the definition of therapeutic inertia should include the failure not only to intensify therapy, but also to deintensify treatment when appropriate and should be distinguished from appropriate inaction in cases justified by particular circumstances. Therapy should be intensified when glycemic control deteriorates to prevent long periods of hyperglycemia, which increase the risk of complications. Strategic plans to overcome therapeutic inertia must include actions focused on patients, prescribers, health systems, and payers. Therapeutic inertia affects the management of glycemia, hypertension, and lipid disorders, all of which increase the risk for cardiovascular diseases. Thus, multifactorial interventions that act on additional therapeutic goals beyond glycemia are needed.

Unintended adverse consequences of a clinical decision support system: two cases

Many institutions have implemented clinical decision support systems (CDSSs). While CDSS research papers have focused on benefits of these systems, there is a smaller body of literature showing that CDSSs may also produce unintended adverse consequences (UACs). Detailed here are 2 cases of UACs resulting from a CDSS. Both of these cases were related to external systems that fed data into the CDSS. In the first case, lack of knowledge of data categorization in an external pharmacy system produced a UAC; in the second case, the change of a clinical laboratory instrument produced the UAC. CDSSs rely on data from many external systems. These systems are dynamic and may have changes in hardware, software, vendors, or processes. Such changes can affect the accuracy of CDSSs. These cases point to the need for the CDSS team to be familiar with these external systems. This team (manager and alert builders) should include members in specific clinical specialties with deep knowledge of these external systems.

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.

Clinical inertia, reverse clinical inertia, and medication non-adherence in type 2 diabetes

PURPOSE

Clinical inertia and medication non-adherence are thought to contribute largely to the suboptimal glycemic control in many patients with type 2 diabetes. The present review explores the relations between A1C targets, clinical inertia and medication non-adherence in type 2 diabetes.

METHODS

We searched PubMed for English-language studies published from 2001 through June 1, 2018. We also manually searched the references of selected articles, reviews, meta-analyses, and practice guidelines. Selected articles were mutually agreed upon by the authors.

RESULTS

Clinical inertia is the failure of clinicians to initiate or intensify therapy when indicated, while medication non-adherence is the failure of patients to start or continue therapy that a clinician has recommended. Although clinical inertia may occur at all stages of diabetes treatment, the longest delays were reported for initiation or intensification of insulin. Medication non-adherence to antidiabetic drugs may range from 53 to 65% at 1 year and may be responsible for uncontrolled A1C in about 23% of cases. Reverse clinical inertia can be acknowledged as the failure to reduce or change therapy when no longer needed or indicated. Clinical inertia and medication non-adherence are difficult to address: clinician-and patient-targeted educational programs, more connected communications between clinicians and patients, the help of other health professional figures (nurse, pharmacist) have been explored with mixed results.

CONCLUSIONS

Both clinical inertia and medication non-adherence remain significant barriers to optimal glycemic targets in type 2 diabetes. Moreover, part of clinical inertia may be a way through which clinicians face current uncertainty in medicine, including some dissonance among therapeutic guidelines. Scientific associations should find an agreement about how to measure and report clinical inertia in clinical practice and should exhort clinicians to consider reverse clinical inertia as a cause of persisting inappropriate therapy in vulnerable patients.

Evaluation of clinical decision support systems for diabetes care: An overview of current evidence

BACKGROUND

Systematic reviews (SRs) have shown that clinical decision support systems (CDSSs) have the potential to improve diabetes care. However, methods of measuring and presenting outcomes are varied, and conclusions have been inconsistent. In addition, the reporting and methodological quality in this field is unknown, which could affect the integrity and accuracy of research. Therefore, it is difficult to confirm whether CDSSs are effective in improving diabetes care.

OBJECTIVE

To comprehensively evaluate the effects of CDSS on diabetes care and to examine the methodological and reporting qualities.

METHODS

We searched PubMed, EMBASE, and Cochrane Library from their inception to February 2017. Systematic reviews investigating the effects of CDSS on diabetes care were included. Outcomes were determined in advance and assessed separately for process of care and patient outcomes. Methodological and reporting qualities were assessed by AMSTAR and PRISMA, respectively.

RESULTS

Seventeen SRs, consisting of 222 unique randomized controlled trials and 102 nonrandomized controlled trials, were included. Evidence that CDDS significantly impacted patient outcomes was found in 32 of 102 unique studies of the 15 SRs that examined this effect (31%). A significant impact of CDSS on process of care was found in 117 out of 143 unique studies of the 11 SRs that examined this effect (82%). Ratings for overall scores of AMSTAR resulted in a mean score of 6.5 with a range of scores from 3.5 to 10.0. Reporting quality related to methodological domains was particularly incomplete.

CONCLUSIONS

Clinical decision support systems improved the quality of diabetes care by inconsistently improving process of care or patient outcomes. There is evidence that CDSS for providing alerts, reminders, or feedback to participants were most likely to impact diabetes care. Poor reporting of methodological domains, together with qualitative or narrative methods to combine findings, may limit the confidence in research evidence.

Effectiveness of an mHealth-Based Electronic Decision Support System for Integrated Management of Chronic Conditions in Primary Care: The mWellcare Cluster-Randomized Controlled Trial

BACKGROUND

The burden of noncommunicable diseases and their risk factors has rapidly increased worldwide, including in India. Innovative management strategies with electronic decision support and task sharing have been assessed for hypertension, diabetes mellitus, and depression individually, but an integrated package for multiple chronic condition management in primary care has not been evaluated.

METHODS

In a prospective, multicenter, open-label, cluster-randomized controlled trial involving 40 community health centers, using hypertension and diabetes mellitus as entry points, we evaluated the effectiveness of mWellcare, an mHealth system consisting of electronic health record storage and an electronic decision support for the integrated management of 5 chronic conditions (hypertension, diabetes mellitus, current tobacco and alcohol use, and depression) versus enhanced usual care among patients with hypertension and diabetes mellitus in India. At trial end (12-month follow-up), using intention-to-treat analysis, we examined the mean difference between arms in change in systolic blood pressure and glycated hemoglobin as primary outcomes and fasting blood glucose, total cholesterol, predicted 10-year risk of cardiovascular disease, depression score, and proportions reporting tobacco and alcohol use as secondary outcomes. Mixed-effects regression models were used to account for clustering and other confounding variables.

RESULTS

Among 3698 enrolled participants across 40 clusters (mean age, 55.1 years; SD, 11 years; 55.2% men), 3324 completed the trial. There was no evidence of difference between the 2 arms for systolic blood pressure (∆=-0.98; 95% CI, -4.64 to 2.67) and glycated hemoglobin (∆=0.11; 95% CI, -0.24 to 0.45) even after adjustment of several key variables (adjusted differences for systolic blood pressure: - 0.31 [95% CI, -3.91 to 3.29]; for glycated hemoglobin: 0.08 [95% CI, -0.27 to 0.44]). The mean withingroup changes in systolic blood pressure in mWellcare and enhanced usual care were -13.65 mmHg versus -12.66 mmHg, respectively, and for glycated hemoglobin were -0.48% and -0.58%, respectively. Similarly, there were no differences in the changes between the 2 groups for tobacco and alcohol use or other secondary outcomes.

CONCLUSIONS

We did not find an incremental benefit of mWellcare over enhanced usual care in the management of the chronic conditions studied.

CLINICAL TRIAL REGISTRATION

URL: http://www.clinicaltrials.gov. Unique identifier: NCT02480062.

Supporting general practitioner-based care for poorly controlled type 2 diabetes mellitus (the DECIDE study): feasibility study and protocol for a pilot cluster randomised controlled trial

BACKGROUND

Poorly controlled type 2 diabetes mellitus (T2DM) is associated with significant morbidity, mortality and healthcare costs. Control of T2DM can be challenging for healthcare professionals for a number of reasons, including poor concordance with medications, difficulties modifying lifestyle behaviour and also clinical inertia, which is defined as a reluctance among health professionals to intensify medications. A complex intervention, called ComputeriseD dECisIonal support for poorly controlleD typE 2 Diabetes mellitus in Irish General Practice (DECIDE), was developed, identifying T2DM patients with poor glycaemic and blood pressure control and aiming to target clinical inertia, by supporting therapeutic action, including GP-led medication intensification where appropriate. A small-scale, uncontrolled, non-randomised feasibility study highlighted the acceptability of the DECIDE intervention within Irish General Practice. This paper presents a protocol for a pilot cluster randomised controlled trial (RCT) of the DECIDE intervention.

METHODS/DESIGN

The pilot cluster RCT will involve 14 practices and 140 patients in Irish General Practice. Intervention GPs will participate in the DECIDE intervention, comprising (a) a training programme for the practices and (b) a web-based clinical decision support system supporting treatment escalation, tailored to specific patient information. Only patients who have poorly controlled T2DM (defined as HbA1c > 70 mmol/mol and/or BP > 150/95) will be included. The primary outcomes will include measures of feasibility such as recruitment and retention of practices and acceptability of the intervention and also HbA1c. Secondary outcomes will include medication intensification, blood pressure and lipids. Control GPs will continue to provide usual care. A process evaluation will be performed to determine whether the intervention is delivered as intended and treatment fidelity assessed to monitor and enhance the reliability and validity of interventions. An exploratory health economic analysis will examine the potential costs and cost effectiveness of the intervention relative to the control.

DISCUSSION

A pilot cluster RCT will establish the feasibility of a complex intervention which aims to support primary care for patients with poorly controlled T2DM in Irish General Practice.

TRIAL REGISTRATION

The protocol for the pilot cluster RCT is registered on the ISRCTN Registry at: ISRCTN69498919.

Glycaemic control and treatment of type 2 diabetes in adults aged 75 years or older

AIM

The aim of this study was to assess glycaemic control and prescribing practices of antihyperglycaemic treatment in patients with diabetes mellitus type 2 aged 75 years or older.

METHODS

We analysed data from health electronic records from 4,581 persons attended at primary healthcare centres of the Institut Català de la Salut (ICS), in the Girona Sud area of Catalonia, Spain, during 2013 and 2016. Variables such as age, gender, body mass index (BMI), diabetes duration, age at diabetes diagnosis, glycated haemoglobin (HbA1c), creatinine, glomerular filtrate rate and the albumin/creatinine ratio in urine were collected. A descriptive analysis of the study variables was done to determinate the percentage of persons on antidiabetic treatment.

RESULTS

We identified 4,421 persons aged 75 years or older who provided data on HbA1c and antidiabetic treatment. Mean age was 82.3 (5.1) years. In 58.1% of patients, the level of HbA1c was below 7.0%, while in 36.8% it was below 6.5%. Between patients with HbA1c below 7.0%, antidiabetic drugs were taken by 70.2%, where 15.2% were either on insulin, sulphonylureas or repaglinide therapy.

CONCLUSION

Intensive treatment among older adults with diabetes mellitus type 2 is common in primary care clinical practice in our area. Intensive glycaemic control confers an increased risk of hypoglycaemia and little benefit among older individuals with diabetes. Physicians should take care more not to harm those populations and treatment should be de-intensified to reduce the risk of hypoglycaemia.

Comparison of Two Sources of Clinical Audit Data to Assess the Delivery of Diabetes Care in Aboriginal Communities

The objective of this study was to determine the concordance between data extracted from two Clinical Decision Support Systems regarding diabetes testing and monitoring at Aboriginal Community Controlled Health Services in Australia. De-identified PenCAT and Communicare Systems data were extracted from the services allocated to the intervention arm of a diabetes care trial, and intra-class correlations for each extracted item were derived at a service level. Strong to very strong correlations between the two data sources were found regarding the total number of patients with diabetes per service (Intra-class correlation [ICC] = 0.99), as well as the number (ICC = 0.98–0.99) and proportion (ICC = 0.96) of patients with diabetes by gender. The correlation was moderate for the number and proportion of Type 2 diabetes patients per service in the group aged 18–34 years (ICC = 0.65 and 0.8–0.82 respectively). Strong to very strong correlations were found for numbers and proportions of patients being tested for diabetes, and for appropriate monitoring of patients known to have diabetes (ICC = 0.998–1.00). This indicated a generally high degree of concordance between whole-service data extracted by the two Clinical Decision Support Systems. Therefore, the less expensive or less complex option (depending on the individual circumstances of the service) may be appropriate for monitoring diabetes testing and care. However, the extraction of data about subgroups of patients may not be interchangeable.

Development of a complex intervention to promote appropriate prescribing and medication intensification in poorly controlled type 2 diabetes mellitus in Irish general practice

BACKGROUND

Poorly controlled type 2 diabetes mellitus (T2DM) can be seen as failure to meet recommended targets for management of key risk factors including glycaemic control, blood pressure and lipids. Poor control of risk factors is associated with significant morbidity, mortality and healthcare costs. Failure to intensify medications for patients with poor control of T2DM when indicated is called clinical inertia and is one contributory factor to poor control of T2DM. We aimed to develop a theory and evidence-based complex intervention to improve appropriate prescribing and medication intensification in poorly controlled T2DM in Irish general practice.

METHODS

The first stage of the Medical Research Council Framework for developing and evaluating complex interventions was utilised. To identify current evidence, we performed a systematic review to examine the effectiveness of interventions targeting patients with poorly controlled T2DM in community settings. The Behaviour Change Wheel theoretical approach was used to identify suitable intervention functions. Workshops, simulation, collaborations with academic partners and observation of physicians were utilised to operationalise the intervention functions and design the elements of the complex intervention.

RESULTS

Our systematic review highlighted that professional-based interventions, potentially through clinical decision support systems, could address poorly controlled T2DM. Appropriate intensification of anti-glycaemic and cardiovascular medications, by general practitioners (GPs), for adults with poorly controlled T2DM was identified as the key behaviour to address clinical inertia. Psychological capability was the key driver of the behaviour, which needed to change, suggesting five key intervention functions (education, training, enablement, environmental restructuring and incentivisation) and nine key behaviour change techniques, which were operationalised into a complex intervention. The intervention has three components: (a) a training program/academic detailing of target GPs, (b) a remote finder tool to help GPs identify patients with poor control of T2DM in their practice and (c) A web-based clinical decision support system.

CONCLUSIONS

This paper describes a multifaceted process including an exploration of current evidence and a thorough theoretical understanding of the predictors of the behaviour resulting in the design of a complex intervention to promote the implementation of evidence-based guidelines, through appropriate prescribing and medication intensification in poorly controlled T2DM.

Improving risk factor management for patients with poorly controlled type 2 diabetes: a systematic review of healthcare interventions in primary care and community settings

OBJECTIVES

Poorly controlled type 2 diabetes mellitus (T2DM) is a major international health problem. Our aim was to assess the effectiveness of healthcare interventions, specifically targeting patients with poorly controlled T2DM, which seek to improve glycaemic control and cardiovascular risk in primary care settings.

DESIGN

Systematic review.

SETTING

Primary care and community settings.

INCLUDED STUDIES

Randomised controlled trials (RCTs) targeting patients with poor glycaemic control were identified from Pubmed, Embase, Web of Science, Cochrane Library and SCOPUS. Poor glycaemic control was defined as HbA1c over 59 mmol/mol (7.5%).

INTERVENTIONS

Interventions were classified as organisational, patient-oriented, professional, financial or regulatory.

OUTCOMES

Primary outcomes were HbA1c, blood pressure and lipid control. Two reviewers independently assessed studies for eligibility, extracted data and assessed study quality. Meta-analyses were undertaken where appropriate using random-effects models. Subgroup analysis explored the effects of intervention type, baseline HbA1c, study quality and study duration. Meta-regression analyses were undertaken to investigate identified heterogeneity.

RESULTS

Forty-two RCTs were identified, including 11 250 patients, with most undertaken in USA. In general, studies had low risk of bias. The main intervention types were patient-directed (48%) and organisational (48%). Overall, interventions reduced HbA1c by -0.34% (95% CI -0.46% to -0.22%), but meta-analyses had high statistical heterogeneity. Subgroup analyses suggested that organisational interventions and interventions on those with baseline HbA1c over 9.5% had better improvements in HbA1c. Meta-regression analyses suggested that only interventions on those with population HbA1c over 9.5% were more effective. Interventions had a modest improvement of blood pressure and lipids, although baseline levels of control were generally good.

CONCLUSIONS

This review suggests that interventions for T2DM, in primary care, are better targeted at individuals with very poor glycaemic control and that organisational interventions may be more effective.

Clinical inertia and its impact on treatment intensification in people with type 2 diabetes mellitus

Many people with type 2 diabetes mellitus (T2DM) fail to achieve glycaemic control promptly after diagnosis and do not receive timely treatment intensification. This may be in part due to 'clinical inertia', defined as the failure of healthcare providers to initiate or intensify therapy when indicated. Physician-, patient- and healthcare-system-related factors all contribute to clinical inertia. However, decisions that appear to be clinical inertia may, in fact, be only 'apparent' clinical inertia and may reflect good clinical practice on behalf of the physician for a specific patient. Delay in treatment intensification can happen at all stages of treatment for people with T2DM, including prescription of lifestyle changes after diagnosis, introduction of pharmacological therapy, use of combination therapy where needed and initiation of insulin. Clinical inertia may contribute to people with T2DM living with suboptimal glycaemic control for many years, with dramatic consequences for the patient in terms of quality of life, morbidity and mortality, and for public health because of the huge costs associated with uncontrolled T2DM. Because multiple factors can lead to clinical inertia, potential solutions most likely require a combination of approaches involving fundamental changes in medical care. These could include the adoption of a person-centred model of care to account for the complex considerations influencing treatment decisions by patients and physicians. Better patient education about the progressive nature of T2DM and the risks inherent in long-term poor glycaemic control may also reinforce the need for regular treatment reviews, with intensification when required.

Designing Patient-Centered Text Messaging Interventions for Increasing Physical Activity Among Participants With Type 2 Diabetes: Qualitative Results From the Text to Move Intervention

Background

Type 2 diabetes mellitus (T2DM) is a disease affecting approximately 29.1 million people in the United States, and an additional 86 million adults have prediabetes. Diabetes self-management education, a complex health intervention composed of 7 behaviors, is effective at improving self-care behaviors and glycemic control. Studies have employed text messages for education, reminders, and motivational messaging that can serve as “cues to action,” aiming to improve glucose monitoring, self-care behaviors, appointment attendance, and medication adherence.

Objectives

The Text to Move (TTM) study was a 6-month 2-parallel group randomized controlled trial of individuals with T2DM to increase physical activity, measured by a pedometer. The intervention arm received text messages twice daily for 6 months that were tailored to the participant’s stage of behavior change as defined by the transtheoretical model of behavior change.

Methods

We assessed participants’ attitudes regarding their experience with text messaging, focusing on perceived barriers and facilitators, through two focus groups and telephone interviews. All interviews were audiorecorded, transcribed verbatim, coded, and analyzed using a grounded theory approach.

Results

The response rate was 67% (31/46 participants). The average age was 51.4 years and 61% (19/31 participants) were male. The majority of individuals were English speakers and married, had completed at least 12th grade and approximately half of the participants were employed full-time. Overall, participants were satisfied with the TTM program and recalled the text messages as educational, informational, and motivational. Program involvement increased the sense of connection with their health care center. The wearing of pedometers and daily step count information served as motivational reminders and created a sense of accountability through the sentinel effect. However, there was frustration concerning the automation of the text message program, including the repetitiveness, predictability of text time delivery, and lack of customization and interactivity of text message content. Participants recommended personalization of texting frequency as well as more contact time with personnel for a stronger sense of support, including greater surveillance and feedback based on their own results and comparison to other participants.

Conclusions

Participants in a theory-based text messaging intervention identified key facilitators and barriers to program efficacy that should be incorporated into future texting interventions to optimize participant satisfaction and outcomes.

Trial Registration

Clinicaltrials.gov NCT01569243; http://clinicaltrials.gov/ct2/show/NCT01569243 (Archived by Webcite at http://www.webcitation.org/6pfH6yXag)

Impact of implementing electronic clinical practice guidelines for the diagnosis, control and treatment of cardiovascular risk factors: A pre-post controlled study

OBJECTIVE

To evaluate the impact of computerized clinical practice guidelines on the management, diagnosis, treatment, control, and follow-up of the main cardiovascular risk factors: hypertension, hypercholesterolaemia, and type 2 diabetes mellitus.

DESIGN

Pre-post controlled study.

SETTING

Catalonia, autonomous community located in north-eastern Spain.

PARTICIPANTS

Individuals aged 35-74 years assigned to general practitioners of the Catalan Health Institute.

INTERVENTION

The intervention group consisted of individuals whose general practitioners had accessed the computerized clinical practice guidelines at least twice a day, while the control group consisted of individuals whose general practitioner had never accessed the computerized clinical practice guidelines platform.

MAIN OUTCOMES

The Chi-squared test was used to detect significant differences in the follow-up, control, and treatment variables for all three disorders (hypertension, hypercholesterolaemia, and type 2 diabetes mellitus) between individuals assigned to users and non-users of the computerized clinical practice guidelines, respectively.

RESULTS

A total of 189,067 patients were included in this study, with a mean age of 56 years (standard deviation 12), and 55.5% of whom were women. Significant differences were observed in hypertension management, treatment and control; type 2 diabetes mellitus management, treatment and diagnoses, and the management and control of hypercholesterolaemia in both sexes.

CONCLUSIONS

Computerized clinical practice guidelines are an effective tool for the control and follow-up of patients diagnosed with hypertension, type 2 diabetes mellitus, and hypercholesterolaemia. The usefulness of computerized clinical practice guidelines to diagnose and adequately treat individuals with these disorders remains unclear.

Development of a clinical decision support system for diabetes care: A pilot study

Management of complex chronic diseases such as diabetes requires the assimilation and interpretation of multiple laboratory test results. Traditional electronic health records tend to display laboratory results in a piecemeal and segregated fashion. This makes the assembly and interpretation of results related to diabetes care challenging. We developed a diabetes-specific clinical decision support system (Diabetes Dashboard) interface for displaying glycemic, lipid and renal function results, in an integrated form with decision support capabilities, based on local clinical practice guidelines. The clinical decision support system included a dashboard feature that graphically summarized all relevant laboratory results and displayed them in a color-coded system that allowed quick interpretation of the metabolic control of the patients. An alert module informs the user of tests that are due for repeat testing. An interactive graph module was also developed for better visual appreciation of the trends of the laboratory results of the patient. In a pilot study involving case scenarios administered via an electronic questionnaire, the Diabetes Dashboard, compared to the existing laboratory reporting interface, significantly improved the identification of abnormal laboratory results, of the long-term trend of the laboratory tests and of tests due for repeat testing. However, the Diabetes Dashboard did not significantly improve the identification of patients requiring treatment adjustment or the amount of time spent on each case scenario. In conclusion, we have developed and shown that the use of the Diabetes Dashboard, which incorporates several decision support features, can improve the management of diabetes. It is anticipated that this dashboard will be most helpful when deployed in an outpatient setting, where physicians can quickly make clinical decisions based on summarized information and be alerted to pertinent areas of care that require additional attention.

Behavior change interventions and policies influencing primary healthcare professionals' practice-an overview of reviews

BACKGROUND

There is a plethora of interventions and policies aimed at changing practice habits of primary healthcare professionals, but it is unclear which are the most appropriate, sustainable, and effective. We aimed to evaluate the evidence on behavior change interventions and policies directed at healthcare professionals working in primary healthcare centers.

METHODS

Study design: overview of reviews.

DATA SOURCE

MEDLINE (Ovid), Embase (Ovid), The Cochrane Library (Wiley), CINAHL (EbscoHost), and grey literature (January 2005 to July 2015).

STUDY SELECTION

two reviewers independently, and in duplicate, identified systematic reviews, overviews of reviews, scoping reviews, rapid reviews, and relevant health technology reports published in full-text in the English language.

DATA EXTRACTION AND SYNTHESIS

two reviewers extracted data pertaining to the types of reviews, study designs, number of studies, demographics of the professionals enrolled, interventions, outcomes, and authors' conclusions for the included studies. We evaluated the methodological quality of the included studies using the AMSTAR scale. For the comparative evaluation, we classified interventions according to the behavior change wheel (Michie et al.).

RESULTS

Of 2771 citations retrieved, we included 138 reviews representing 3502 individual studies. The majority of systematic reviews (91%) investigated behavior and practice changes among family physicians. Interactive and multifaceted continuous medical education programs, training with audit and feedback, and clinical decision support systems were found to be beneficial in improving knowledge, optimizing screening rate and prescriptions, enhancing patient outcomes, and reducing adverse events. Collaborative team-based policies involving primarily family physicians, nurses, and pharmacists were found to be most effective. Available evidence on environmental restructuring and modeling was found to be effective in improving collaboration and adherence to treatment guidelines. Limited evidence on nurse-led care approaches were found to be as effective as general practitioners in patient satisfaction in settings like asthma, cardiovascular, and diabetes clinics, although this needs further evaluation. Evidence does not support the use of financial incentives to family physicians, especially for long-term behavior change.

CONCLUSIONS

Behavior change interventions including education, training, and enablement in the context of collaborative team-based approaches are effective to change practice of primary healthcare professionals. Environmental restructuring approaches including nurse-led care and modeling need further evaluation. Financial incentives to family physicians do not influence long-term practice change.

Physician perspectives on de-intensifying diabetes medications

Guidelines for diabetes care recommend that physicians select individualized glycemic goals based on life expectancy, diabetes duration, comorbidity, and resources/support. When patients have stable hemoglobin A1C (HbA1C) levels, guidelines lack recommendations on when diabetes medications should be de-intensified.To understand physicians' perspectives on de-intensifying diabetes medications in patients with type 2 diabetes.Cross-sectional survey, (February-June, 2015).Academic medical center and suburban integrated health system.Primary care and endocrinology physicians.Physicians' self-reported: awareness, agreement, and frequency of individualizing HbA1C goals; practice of de-intensifying diabetes medications; HbA1C values at which physicians de-intensify diabetes medications; and other patient factors physicians consider when de-intensifying diabetes medications.Response rate was 73% (156/213). Most physicians (78%) responded they were familiar with recommendations to individualize HbA1C goals. For patients with stable HbA1C levels, 80% of physicians reported they had initiated conversations about stopping medications; however, physicians differed in predefined HbA1C levels used to initiate conversations (HbA1C < 5.7%: 14%; HbA1C < 6.0%: 31%; HbA1C < 6.5%: 22%; individualized level: 21%). In multiple logistic regression, women physicians (odds ratio [OR] 3.0; confidence interval [CI] 1.1-8.2; P = 0.03) and physicians practicing fewer than 20 years (OR 2.8; CI 1.01-7.7; P = 0.048) were more likely to report de-intensifying diabetes medications.Individualizing glycemic goals and de-intensifying treatments are concepts well accepted by physicians in our sample. However, physicians vary considerably in reporting how they carry out recommendations to individualize and may be missing opportunities to stop or taper diabetes medications based on patients' individualized glycemic goals.

Do false positive alerts in naïve clinical decision support system lead to false adoption by physicians? A randomized controlled trial

OBJECTIVES

False positive alerts in patient-safety-related clinical decision support systems (CDSS) are defined as alerts which incorrectly prompt when no-risk patients are encountered. It is an unfavorable condition which may potentially mislead physicians. The aim is to investigate physician responses toward false positive (FP) and true positive (TP) alerts in CDSS for the prevention of contrast-induced nephropathy (CIN).

METHODS

A two-arm cluster randomized controlled trial was conducted in university hospitals. Eligible physicians were randomized to receive alert intervention or no intervention (groups 1 and 2, respectively). The alert system was embedded with a deliberately non-specific risk detection tool in order to generate TP and FP alerts. The naïve alert system would alert the physician to cancel the order regardless of the patient being at-risk or not at-risk. CIN risk was stratified as at-risk and no-risk according to a patient's pre-existing renal function. Contrast imaging order-cancellation rate was measured as primary outcome.

RESULTS

3802 contrast-enhanced examination orders from 66 physicians were analyzed. Demographic data and risk distributions of patients were similar and well-balanced between two groups. In the intervention group, a total of 1892 alerts were generated (332 TP alerts and 1560 FP alerts). Order-cancellation rates were 5.1% versus 1.4% in groups 1 and 2 for at-risk patients (relative risk [RR] = 3.69) from TP alerts, and 1.0% versus 1.4% for no-risk patients (RR = 0.71) from FP alerts. Using generalized linear model with generalized estimating equation, the FP alerts had no order-cancellation effect when compared to the control arm (adjusted RR = 0.69; 95%CI, 0.36-1.32). The TP alerts had a larger order-cancellation effect than that of the control arm (adjusted RR = 2.95; 95%CI, 0.94-9.27), which revealed a marginal trend toward significance. However, the effect was not statistically significant (adjusted RR = 1.24; 95%CI, 0.71-2.18) if TP and FP alerts were mixed.

CONCLUSIONS

Physicians are not likely to adopt recommendations provided by false positive alerts in patient-safety-related CDSS. If reporting only the adoption rate of CDSS as a whole without differentiating between TP and FP alerts, the effects of TP and FP alerts will be mixed, and thus, will lead to an underestimation of system effectiveness.

Feasibility of a Patient-Centered, Smartphone-Based, Diabetes Care System: A Pilot Study

BACKGROUND

We developed a patient-centered, smartphone-based, diabetes care system (PSDCS). This study aims to test the feasibility of glycosylated hemoglobin (HbA1c) reduction with the PSDCS.

METHODS

This study was a single-arm pilot study. The participants with type 2 diabetes mellitus were instructed to use the PSDCS, which integrates a Bluetooth-connected glucometer, digital food diary, and wearable physical activity monitoring device. The primary end point was the change in HbA1c from baseline after a 12-week intervention.

RESULTS

Twenty-nine patients aged 53.9±9.1 years completed the study. HbA1c and fasting plasma glucose levels decreased significantly from baseline (7.7%±0.7% to 7.1%±0.6%, P<0.0001; 140.9±39.1 to 120.1±31.0 mg/dL, P=0.0088, respectively). The frequency of glucose monitoring correlated with the magnitude of HbA1c reduction (r=-0.57, P=0.0013). The components of the diabetes self-care activities, including diet, exercise, and glucose monitoring, were significantly improved, particularly in the upper tertile of HbA1c reduction. There were no severe adverse events during the intervention.

CONCLUSION

A 12-week application of the PSDCS to patients with inadequately controlled type 2 diabetes resulted in a significant HbA1c reduction with tolerable safety profiles; these findings require confirmation in a future randomized controlled trial.

Outpatient diabetes clinical decision support: current status and future directions

Outpatient clinical decision support systems have had an inconsistent impact on key aspects of diabetes care. A principal barrier to success has been low use rates in many settings. Here, we identify key aspects of clinical decision support system design, content and implementation that are related to sustained high use rates and positive impacts on glucose, blood pressure and lipid management. Current diabetes clinical decision support systems may be improved by prioritizing care recommendations, improving communication of treatment-relevant information to patients, using such systems for care coordination and case management and integrating patient-reported information and data from remote devices into clinical decision algorithms and interfaces.

Dulce Wireless Tijuana: A Randomized Control Trial Evaluating the Impact of Project Dulce and Short-Term Mobile Technology on Glycemic Control in a Family Medicine Clinic in Northern Mexico

BACKGROUND

The global epidemic of diabetes calls for innovative interventions. This study evaluated the effectiveness of the Project Dulce model, with and without wireless technology, on glycemic control and other clinical and self-reported outcomes in patients with poorly controlled type 2 diabetes in Mexico.

SUBJECTS AND METHODS

Adults with type 2 diabetes and a glycated hemoglobin A1c (HbA1c) level of ≥8% were recruited from Family Medical Unit #27 of the Instituto Mexicano del Seguro Social (IMSS) in Tijuana, México, and randomly assigned to one of three groups: Project Dulce-only (PD); Project Dulce technology-enhanced with mobile tools (PD-TE); or IMSS standard of care/control group (CG). Clinical and self-reported outcomes were assessed at baseline, Month 4, and Month 10. Time-by-group interactions and within-group changes were analyzed.

RESULTS

HbA1c reductions from baseline to Month 10 were significantly greater in PD-TE (-3.0% [-33 mmol/mol]) and PD (-2.6% [-28.7 mmol/mol]) compared with CG (-1.3% [-14.2 mmol/mol]) (P = 0.009 and 0.001, respectively). PD-TE and PD also exhibited significant improvement in diabetes knowledge when compared with CG (P < 0.05 for both). No statistically significant differences were detected between PD and PD-TE on these indicators (P = 0.54 and 0.86, respectively). Several within-group improvements were observed on other clinical and self-report indicators but did not vary significantly across groups.

CONCLUSIONS

Project Dulce with and without wireless technology substantially improved glycemic control and diabetes knowledge in high-risk patients with type 2 diabetes in a Mexican family medical unit, suggesting that integrating peer-led education, nurse coordination, and 3G wireless technology is an effective approach for improving diabetes outcomes in high-risk populations.

Eliminating disparities among Latinos with type 2 diabetes: Effective eHealth strategies

Latinos are at increased risk for obesity and type 2 diabetes (T2D). Well-designed information technology (IT) interventions have been shown to be generally efficacious in improving diabetes self-management. However, there are very few published IT intervention studies focused on Latinos. With the documented close of the digital divide, Latinos stand to benefit from such advances. There are limited studies on how best to address the unique socio-cultural-linguistic characteristics that would optimize adoption, use and benefit among Latinos. Successful e-health programs involve frequent communication, bidirectionality including feedback, and multimodal delivery of the intervention. The use of community health workers (CHWs) has been shown consistently to improve T2D outcomes in Latinos. Incorporating CHWs into eHealth interventions is likely to address barriers with technology literacy and improve patient activation, satisfaction and adherence. Additionally, tailored interventions are more successful in improving patient activation. It is important to note that tailoring is more than linguistic translation; tailoring interventions to the Latino population will need to address educational, language, literacy and acculturation levels, along with unique illness beliefs and attitudes about T2D found among Latinos. Interventions will need to go beyond the lone participant and include shared decision making models that incorporate family members and friends.

Translating What Works: A New Approach to Improve Diabetes Management

BACKGROUND

The most efficacious strategies to improve diabetes control include case management, health care team changes, patient education, and facilitated transmission of patient data to clinicians ("facilitated relay"), but these strategies have not been translated to permit general use in clinical practice.

METHODS

A web-based decision support program was developed to include these features, and assessed in patients who had A1c ≥7.0% despite using metformin with/without sulfonylureas or insulin. Staff entered patients' glucose data, obtained management recommendations, reviewed the plan with a clinician, and discussed the new plan with patients.

RESULTS

113 subjects were 96% male and 32% black, with average age 65.6 years and BMI 32.8. During prior primary care, A1c averaged 8.32 ± 0.16% (SEM). In all patients, baseline A1c was 8.18 ± 0.11%, and decreased to 7.54 ± 0.12%, 7.16 ± 0.13%, and 7.54 ± 0.16% at 3, 6, and 12 months, respectively, all P < .001. In 42 subjects who provided glucose data and made requested changes in medications, A1c was 8.12 ± 0.09% at baseline and fell to 7.29 ± 0.11%, 6.98 ± 0.10%, and 7.05 ± 0.10% at 3, 6, and 12 months, respectively, all P < .001. Chart review of 16 subjects followed for 12 months demonstrated that hypoglycemia (symptoms and/or glucose <70 mg/dl) averaged less than 1 episode/patient/month, and there was no severe hypoglycemia.

CONCLUSIONS

A novel decision support program improved A1c with little hypoglycemia. Use of this approach should allow primary care teams to keep patients well controlled, and reduce the need for specialist referrals.

Effectiveness and cost-effectiveness of knowledge transfer and behavior modification interventions in type 2 diabetes mellitus patients--the INDICA study: a cluster randomized controlled trial

BACKGROUND

Type 2 diabetes mellitus is a chronic disease whose health outcomes are related to patients and healthcare professionals' decision-making. The Diabetes Intervention study in the Canary Islands (INDICA study) aims to evaluate the effectiveness and cost-effectiveness of educational interventions supported by new technology decision tools for type 2 diabetes patients and primary care professionals in the Canary Islands.

METHODS/DESIGN

The INDICA study is an open, community-based, multicenter, clinical controlled trial with random allocation by clusters to one of three interventions or to usual care. The setting is primary care where physicians and nurses are invited to participate. Patients with diabetes diagnosis, 18-65 years of age, and regular users of mobile phone were randomly selected. Patients with severe comorbidities were excluded. The clusters are primary healthcare practices with enough professionals and available places to provide the intervention. The calculated sample size was 2,300 patients. Patients in group 1 are receiving an educational group program of eight sessions every 3 months led by trained nurses and monitored by means of logs and a web-based platform and tailored semi-automated SMS for continuous support. Primary care professionals in group 2 are receiving a short educational program to update their diabetes knowledge, which includes a decision support tool embedded into the electronic clinical record and a monthly feedback report of patients' results. Group 3 is receiving a combination of the interventions for patients and professionals. The primary endpoint is the change in HbA1c in 2 years. Secondary endpoints are cardiovascular risk factors, macrovascular and microvascular diabetes complications, quality of life, psychological outcomes, diabetes knowledge, and healthcare utilization. Data is being collected from interviews, questionnaires, clinical examinations, and records. Generalized linear mixed models with repeated time measurements will be used to analyze changes in outcomes. The cost-effectiveness analysis, from the healthcare services perspective, involves direct medical costs per quality-adjusted life year gained and two periods, a 'within-trial' period and a lifetime Markov model. Deterministic and probabilistic sensitivity analyses are planned.

DISCUSSION

This ongoing trial aims to set up the implementation of evidence-based programs in the clinical setting for chronic patients.

TRIAL REGISTRATION

Clinical Trial.gov NCT01657227.

A decision support tool for appropriate glucose-lowering therapy in patients with type 2 diabetes

BACKGROUND

Optimal glucose-lowering therapy in type 2 diabetes mellitus requires a patient-specific approach. Although a good framework, current guidelines are insufficiently detailed to address the different phenotypes and individual needs of patients seen in daily practice. We developed a patient-specific decision support tool based on a systematic analysis of expert opinion.

MATERIALS AND METHODS

Based on the American Diabetes Association (ADA)/European Association for the Study of Diabetes (EASD) 2012 position statement, a panel of 12 European experts rated the appropriateness (RAND/UCLA Appropriateness Method) of treatment strategies for 930 clinical scenarios, which were permutations of clinical variables considered relevant to treatment choice. These included current treatment, hemoglobin A1c difference from individualized target, risk of hypoglycemia, body mass index, life expectancy, and comorbidities. Treatment options included addition of a second or third agent, drug switches, and replacement by monotherapies if the patient was metformin-intolerant. Treatment costs were not considered. Appropriateness (appropriate, inappropriate, uncertain) was based on the median score and expert agreement. The panel recommendations were embedded in an online decision support tool (DiaScope(®); Novo Nordisk Health Care AG, Zürich, Switzerland).

RESULTS

Treatment appropriateness was associated with (combinations of) the patient variables mentioned above. As second-line agents, dipeptidyl peptidase-4 inhibitors were considered appropriate in all scenarios, followed by glucagon-like peptide-1 receptor agonists (50%), insulins (33%), and sulfonylureas (25%), but not pioglitazone (0%). Ratings of third-line combinations followed a similar pattern. Disagreement was highest for regimens including pioglitazone, sulfonylureas, or insulins and was partly due to differences in panelists' opinions and in drug availability and reimbursement across European countries (although costs were disregarded in the rating process).

CONCLUSIONS

A novel decision support tool based on the ADA/EASD 2012 position statement and a systematic analysis of expert opinion has been developed to help healthcare professionals to individualize glucose-lowering therapy in daily clinical situations.

Reducing CKD risks among vulnerable populations in primary care

Ethnic/racial and socioeconomic status disparities in the health-care and clinical outcomes of patients with chronic kidney disease (CKD) are pervasive. The vast majority of care to decrease incidence of CKD risk and progression occurs in primary care settings. High-quality primary care, therefore, represents a key strategy through which disparities in the incidence and progression of CKD may be eliminated. The Chronic Care Model provides a framework for the delivery of high-quality primary care for chronic diseases, and it is frequently used to guide health-care quality improvement initiatives. Evidence suggests that Chronic Care Model constructs, including provider and organizational quality improvement initiatives focused on team approaches to chronic care (eg, case management, community health workers), are effective in modifying patients' CKD risks among ethnic minority and low-income patients. Other Chronic Care Model constructs, including clinical information systems (eg, disease registries), decision support interventions, and the provision of patient-centered care have been shown to improve processes related to CKD care but with limited and/or mixed effects on patient outcomes. Few studies have examined the effect of these approaches on reducing disparities. Research is needed to examine the effectiveness of these strategies to eliminate CKD disparities among vulnerable populations.

Quality of care for OA: the effect of a point-of-care consultation recording template

Objective. The aims of this study were to determine the feasibility of introducing a computerized template for identifying quality of care during an OA consultation, describe quality of OA care in practices in which the template was introduced and assess the effect of the template on routinely recorded clinician behaviour in those practices.

Methods. A computerized template to assist the recording of care in consultations for patients with OA was installed in eight general practices. Eligible patients were those ≥45 years of age consulting for clinical OA during a 6 month period. The main outcomes were frequency of template triggering, achievement of quality indicators during the consultation (assessment of pain and function, assessment for first-line analgesics, provision of information, exercise advice, consideration of physiotherapy referral, weight loss advice) and change in routinely recorded clinician behaviour (diagnostic coding, prescribing, referral, use of radiography, weight records) compared with the 12 months prior to template installation.

Results. The template was triggered for 1730 patients. Achievement of indicators ranged from 36% (for consideration of physiotherapy referral) to 63% (for pain assessment), with substantial variability between clinicians. There was an increase in prescription of recommended first-line analgesics following the template installation: paracetamol [odds ratio (OR) 1.49 (95% CI 1.22, 1.82) compared with pre-template] and topical NSAIDs [OR 1.95 (95% CI 1.61, 2.35)].

Conclusion. This new template is a feasible tool for capturing data during OA consultations to aid assessment of quality of care. It was associated with significant improvements in recommended care processes. However, strategies are needed to ensure consistent approaches between clinicians.

Trial registration.http://www.controlled-trials.com/ISRCTN06984617/mosaics.

Computer-based interventions to improve self-management in adults with type 2 diabetes: a systematic review and meta-analysis

OBJECTIVE

Structured patient education programs can reduce the risk of diabetes-related complications. However, people appear to have difficulties attending face-to-face education and alternatives are needed. This review looked at the impact of computer-based diabetes self-management interventions on health status, cardiovascular risk factors, and quality of life of adults with type 2 diabetes.

RESEARCH DESIGN AND METHODS

We searched The Cochrane Library, Medline, Embase, PsycINFO, Web of Science, and CINAHL for relevant trials from inception to November 2011. Reference lists from relevant published studies were screened and authors contacted for further information when required. Two authors independently extracted relevant data using standard data extraction templates.

RESULTS

Sixteen randomized controlled trials with 3,578 participants met the inclusion criteria. Interventions were delivered via clinics, the Internet, and mobile phones. Computer-based diabetes self-management interventions appear to have small benefits on glycemic control: the pooled effect on HbA1c was -0.2% (-2.3 mmol/mol [95% CI -0.4 to -0.1%]). A subgroup analysis on mobile phone-based interventions showed a larger effect: the pooled effect on HbA1c from three studies was -0.50% (-5.46 mmol/mol [95% CI -0.7 to -0.3%]). There was no evidence of improvement in depression, quality of life, blood pressure, serum lipids, or weight. There was no evidence of significant adverse effects.

CONCLUSIONS

Computer-based diabetes self-management interventions to manage type 2 diabetes appear to have a small beneficial effect on blood glucose control, and this effect was larger in the mobile phone subgroup. There was no evidence of benefit for other biological, cognitive, behavioral, or emotional outcomes.

Rational use of electronic health records for diabetes population management

Population management is increasingly invoked as an approach to improve the quality and value of diabetes care. Recent emphasis is driven by increased focus on both costs and measures of care as the US moves from fee for service to payment models in which providers are responsible for costs incurred, and outcomes achieved, for their entire patient population. The capacity of electronic health records (EHRs) to create patient registries, apply analytic tools, and facilitate provider- and patient-level interventions has allowed rapid evolution in the scope of population management initiatives. However, findings on the efficacy of these efforts for diabetes are mixed, and work remains to achieve the full potential of an-EHR based population approach. Here we seek to clarify definitions and key domains, provide an overview of evidence for EHR-based diabetes population management, and recommend future directions for applying the considerable power of EHRs to diabetes care and prevention.