Electronic medical record-assisted design of a cluster-randomized trial to improve diabetes care and outcomes

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.

Evaluating a post-implementation electronic medical record training intervention for diabetes management in primary care

OBJECTIVE

This study evaluated the potential for electronic medical record (EMR) video tutorials to improve diabetes (type 1 and 2) care processes by primary care physicians (PCP) using OSCAR EMR.

DESIGN

A QUAN(qual) mixed methods approach with an embedded design was used for the overall research study. EMR video tutorials were developed based on the chronic care model (CCM), value-adding EMR use, best practice guidelines for designing software video tutorials and clinician-led EMR training.

RESULTS

In total, 18 PCPs from British Columbia, Canada, participated in the study. The video EMR intervention elicited a statistically significant increase in EMR advanced feature use for diabetes care, with a large effect size (ie, F(1,51)=6.808, p<0.001, partial η2=0.286).

CONCLUSION

This small-scale efficacy study demonstrates the potential of CCM-based EMR video tutorials to improve EMR use for chronic diseases, such as diabetes. A larger-scale effectiveness study with a control group is needed to further validate the study findings and determine their generalisability. The demonstrated efficacy of the intervention suggests that EMR video tutorials may be a cost-effective, sustainable and scalable strategy for supporting EMR optimisation and the continuous learning and development of PCPs. Health informatics practitioners may develop video tutorials for their respective EMR/electronic health record software based on theory and best practices for video tutorial design. For patients, EMR video tutorials may lead to improved tracking of processes of care for diabetes, and potentially other chronic conditions.

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.

Data Quality in Electronic Health Records Research: Quality Domains and Assessment Methods

The proliferation of the electronic health record (EHR) has led to increasing interest and opportunities for nurse scientists to use EHR data in a variety of research designs. However, methodological problems pertaining to data quality may arise when EHR data are used for nonclinical purposes. Therefore, this article describes common domains of data quality and approaches for quality appraisal in EHR research. Common data quality domains include data accuracy, completeness, consistency, credibility, and timeliness. Approaches for quality appraisal include data validation with data rules, evaluation and verification of data abstraction methods with statistical measures, data comparisons with manual chart review, management of missing data using statistical methods, and data triangulation between multiple EHR databases. Quality data enhance the validity and reliability of research findings, form the basis for conclusions derived from the data, and are, thus, an integral component in EHR-based study design and implementation.

Development and Implementation of Team-Based Panel Management Tools: Filling the Gap between Patient and Population Information Systems

Effective team-based models of care, such as the Patient-Centered Medical Home, require electronic tools to support proactive population management strategies that emphasize care coordination and quality improvement. Despite the spread of electronic health records (EHRs) and vendors marketing population health tools, clinical practices still may lack the ability to have: (1) local control over types of data collected/reports generated, (2) timely data (eg, up-to-date data, not several months old), and accordingly (3) the ability to efficiently monitor and improve patient outcomes. This article describes a quality improvement project at the hospital system level to develop and implement a flexible panel management (PM) tool to improve care of subpopulations of patients (eg, panels of patients with diabetes) by clinical teams. An in-depth case analysis approach is used to explore barriers and facilitators in building a PM registry tool for team-based management needs using standard data elements (eg, laboratory values, pharmacy records) found in EHRs. Also described are factors that may contribute to sustainability; to date the tool has been adapted to 6 disease-focused subpopulations encompassing more than 200,000 patients. Two key lessons emerged from this initiative: (1) though challenging, team-based clinical end users and information technology needed to work together consistently to refine the product, and (2) locally developed population management tools can provide efficient data tracking for frontline clinical teams and leadership. The preliminary work identified critical gaps that were successfully addressed by building local PM registry tools from EHR-derived data and offers lessons learned for others engaged in similar work. (Population Health Management 2016;19:232-239).

Managing diabetes mellitus using information technology: a systematic review

Objective

To review published evidences about using information technology interventions in diabetes care and determine their effects on managing diabetes.

Design

Systematic review of information technology based interventions.

Research design and methods

MEDLINE®/PubMed were electronically searched for articles published between 2004/07/01 and 2014/07/01. A comprehensive, electronic search strategy was used to identify eligible articles.

Inclusion criteria were defined based on type of study and effect of information technology based intervention in relation to glucose control and other clinical outcomes in diabetic patients. Studies must have used a controlled design to evaluate an information technology based intervention.

A total of 3613 articles were identified based on the searches conducted in MEDLINE from PubMed. After excluding duplicates (n = 6), we screened titles and abstracts of 3607 articles based on inclusion criteria. The remaining articles matched with inclusion criteria (n = 277) were reviewed in full text, and 210 articles were excluded based on exclusion criteria. Finally, 67 articles complied with our eligibility criteria and were included in this study.

Results

In this study, the effect of various information technology based interventions on clinical outcomes in diabetic patients extracted and measured from selected articles is described and compared to each other.

Conclusion

Information technology based interventions combined with the usual care are associated with improved glycemic control with different efficacy on various clinical outcomes in diabetic patients.

Hepatitis C: improving the quality of screening in a community hospital by implementing an electronic medical record intervention

Both the Centers for Disease Control and Prevention (CDC) and the U.S. Preventive Services Task Force (USPSTF) have recommended that adults born between the years of 1945-1965 should receive one-time testing for Hepatitis C Virus (HCV). In fact, Governor Andrew Cuomo of the State of New York had signed a bill on October 23, 2013 which mandated NY hospitals and healthcare providers to offer HCV testing to all “Baby Boomers.” For our project, we wanted to increase our community hospital's compliance with this law and improve the quality of patient care in doing so.

An electronic medical record intervention was implemented in conjunction with our information technology services department. This intervention would flag eligible patients and would run them through a predetermined algorithm to see if they needed HCV testing. Multiple plan, do, study, act (PDSA) cycles were run during the length of the study and many changes were made in order to achieve maximum effect.

We ended up increasing our HCV testing rate from 47.2% (pre-intervention) to 87.9% (final month of the study), which was statistically significant with a p-value of <0.0000001. We also ended up with a framework that is both generalizable to other projects and is also self-sustaining, so that it can continue to run itself once all the project members have finished working there as house staff.

Comparative outcome studies of clinical decision support software: limitations to the practice of evidence-based system acquisition

Clinical decision support systems (CDSSs) assist clinicians with patient diagnosis and treatment. However, inadequate attention has been paid to the process of selecting and buying systems. The diversity of CDSSs, coupled with research obstacles, marketplace limitations, and legal impediments, has thwarted comparative outcome studies and reduced the availability of reliable information and advice for purchasers. We review these limitations and recommend several comparative studies, which were conducted in phases; studies conducted in phases and focused on limited outcomes of safety, efficacy, and implementation in varied clinical settings. Additionally, we recommend the increased availability of guidance tools to assist purchasers with evidence-based purchases. Transparency is necessary in purchasers' reporting of system defects and vendors' disclosure of marketing conflicts of interest to support methodologically sound studies. Taken together, these measures can foster the evolution of evidence-based tools that, in turn, will enable and empower system purchasers to make wise choices and improve the care of patients.

Application of routine electronic health record databases for pharmacogenetic research

Inter-individual variability in drug responses is a common problem in pharmacotherapy. Several factors (non-genetic and genetic) influence drug responses in patients. When aiming to obtain an optimal benefit-risk ratio of medicines and with the emergence of genotyping technology, pharmacogenetic studies are important for providing recommendations on drug treatments. Advances in electronic healthcare information systems can contribute to increasing the quality and efficiency of such studies. This review describes the definition of pharmacogenetics, gene selection and study design for pharmacogenetic research. It also summarizes the potential of linking pharmacoepidemiology and pharmacogenetics (along with its strengths and limitations) and provides examples of pharmacogenetic studies utilizing electronic health record databases.

The challenge of detecting alpha-1 antitrypsin deficiency

Alpha-1 antitrypsin deficiency (AATD) is relatively common but under-recognized. Indeed, fewer than 10% of the estimated 100,000 Americans with AATD have been diagnosed currently, with common reports of long delays between initial symptoms and first detection and the need to see multiple physicians before diagnosis. Because detection can confer benefits (e.g., identification of at-risk family members, lower smoking likelihood, consideration of augmentation therapy), targeted detection of AATD in at-risk groups such as all symptomatic adults with COPD has been endorsed. Two general approaches to detection have been studied: population-based screening (in which testing is performed in a group for whom no increased risk of having AATD exists) and targeted detection or case-finding (in which testing is confined to those with an attributable condition such as COPD or chronic liver disease). Studies to date have suggested that population-based screening is not cost-effective, whereas targeted detection of AATD has been advocated by official society guidelines. Efforts to enhance detection of AATD individuals have included various approaches, including educational campaigns, provision of free test kits, issuance of reminders with medical reports or within an electronic medical record, and empowering respiratory therapists to conduct testing for AATD in pulmonary function laboratories. Such programs have identified individuals with severe deficiency of alpha-1 antitrypsin in up to 12% of subjects, with considerable variation across series by testing criteria. Overall, the persistence of under-recognition of AATD underscores the need for continued efforts to optimize detection of this potentially debilitating genetic disease.

Blocking for Sequential Political Experiments

In typical political experiments, researchers randomize a set of households, precincts, or individuals to treatments all at once, and characteristics of all units are known at the time of randomization. However, in many other experiments, subjects "trickle in" to be randomized to treatment conditions, usually via complete randomization. To take advantage of the rich background data that researchers often have (but underutilize) in these experiments, we develop methods that use continuous covariates to assign treatments sequentially. We build on biased coin and minimization procedures for discrete covariates and demonstrate that our methods outperform complete randomization, producing better covariate balance in simulated data. We then describe how we selected and deployed a sequential blocking method in a clinical trial and demonstrate the advantages of our having done so. Further, we show how that method would have performed in two larger sequential political trials. Finally, we compare causal effect estimates from differences in means, augmented inverse propensity weighted estimators, and randomization test inversion.

Cluster randomized trial in the general practice research database: 2. Secondary prevention after first stroke (eCRT study): study protocol for a randomized controlled trial

BACKGROUND

The purpose of this research is to develop and evaluate methods for conducting pragmatic cluster randomized trials in a primary care electronic database. The proposal describes one application, in a less frequent chronic condition of public health importance, secondary prevention of stroke. A related protocol in antibiotic prescribing was reported previously.

METHODS/DESIGN

The study aims to implement a cluster randomized trial (CRT) using the electronic patient records of the General Practice Research Database (GPRD) as a sampling frame and data source. The specific objective of the trial is to evaluate the effectiveness of a computer-delivered intervention at enhancing the delivery of stroke secondary prevention in primary care. GPRD family practices will be allocated to the intervention or usual care. The intervention promotes the use of electronic prompts to support adherence with the recommendations of the UK Intercollegiate Stroke Working Party and NICE guidelines for the secondary prevention of stroke in primary care. Primary outcome measure will be the difference in systolic blood pressure between intervention and control trial arms at 12-month follow-up. Secondary outcomes will be differences in serum cholesterol, prescribing of antihypertensive drugs, statins, and antiplatelet therapy. The intervention will continue for 12 months. Information on the utilization of the decision-support tools will also be analyzed.

DISCUSSION

The CRT will investigate the effectiveness of using a computer-delivered intervention to reduce the risk of stroke recurrence following a first stroke event. The study will provide methodological guidance on the implementation of CRTs in electronic databases in primary care.

TRIAL REGISTRATION

Current Controlled Trials ISRCTN35701810.

Electronic health records and quality of diabetes care

BACKGROUND

Available studies have shown few quality-related advantages of electronic health records (EHRs) over traditional paper records. We compared achievement of and improvement in quality standards for diabetes at practices using EHRs with those at practices using paper records. All practices, including many safety-net primary care practices, belonged to a regional quality collaborative and publicly reported performance.

METHODS

We used generalized estimating equations to calculate the percentage-point difference between EHR-based and paper-based practices with respect to achievement of composite standards for diabetes care (including four component standards) and outcomes (five standards), after adjusting for covariates and accounting for clustering. In addition to insurance type (Medicare, commercial, Medicaid, or uninsured), patient-level covariates included race or ethnic group (white, black, Hispanic, or other), age, sex, estimated household income, and level of education. Analyses were conducted separately for the overall sample and for safety-net practices.

RESULTS

From July 2009 through June 2010, data were reported for 27,207 adults with diabetes seen at 46 practices; safety-net practices accounted for 38% of patients. After adjustment for covariates, achievement of composite standards for diabetes care was 35.1 percentage points higher at EHR sites than at paper-based sites (P<0.001), and achievement of composite standards for outcomes was 15.2 percentage points higher (P=0.005). EHR sites were associated with higher achievement on eight of nine component standards. Such sites were also associated with greater improvement in care (a difference of 10.2 percentage points in annual improvement, P<0.001) and outcomes (a difference of 4.1 percentage points in annual improvement, P=0.02). Across all insurance types, EHR sites were associated with significantly higher achievement of care and outcome standards and greater improvement in diabetes care. Results confined to safety-net practices were similar.

CONCLUSIONS

These findings support the premise that federal policies encouraging the meaningful use of EHRs may improve the quality of care across insurance types.

Impact of a clinical decision support system in an electronic health record to enhance detection of α₁-antitrypsin deficiency

BACKGROUND

Because α(1)-antitrypsin deficiency (AATD) is underrecognized, strategies to enhance guideline-based diagnostic testing are warranted.

METHODS

We studied the impact of issuing a guideline-based alert within an electronic health record (EHR) to test for AATD on the rate of testing for and detection of AATD. For patients at the Cleveland Clinic whose physician-ordered pulmonary function test results showed airflow obstruction, the rates of testing for and detection of AATD were determined during a baseline (prealert) period and again after implementing the alert.

RESULTS

During the baseline period, among 979 eligible subjects, 4.7% were tested; 8.9% of those who had phenotype testing performed were found to have AATD (serum levels < 100 mg/dL), of whom 3.2% had the PI*ZZ genotype. After the alert, among the 624 eligible subjects, the rate of testing increased severalfold (15.1%, P < .001), though neither the rate of detecting AATD (5.3%) nor PI*ZZ (2.6%) differed from the rates during the baseline period. Having an alternate diagnosis (other than asthma) that could explain airflow obstruction (eg, congestive heart failure, sarcoidosis, Langerhans cell histiocytosis) was associated with a lower rate of testing (P = .041), while carrying a diagnosis of asthma tended to increase the testing frequency (P = .15). Multivariate analysis showed that younger age and a smoking history were associated with being tested.

CONCLUSIONS

Issuing an alert within an EHR was associated with a severalfold increase in the frequency of testing for α(1)-antitrypsin without a higher rate of diagnosing severe AATD. While the lack of more frequent diagnosis of AATD may reflect a high rate of baseline detection, these results prompt consideration of additional strategies to enhance detection of AATD.

Electronic health records and quality of care for heart failure

BACKGROUND

Electronic health records (EHRs) are considered an important technology to improve the quality of health care, yet few data exist regarding their effect on delivery of evidence-based care in the outpatient setting.

METHODS

IMPROVE HF is a prospective cohort study of 15,381 patients with HF or post myocardial infarction and left ventricular ejection fraction < or =35% cared for in 167 US outpatient cardiology practices. Baseline patient characteristics and quality data were collected by chart abstraction. To quantify care, 7 HF quality measures were assessed; practices with and without EHR were compared.

RESULTS

Among practices, 52% had EHR systems (30% EHR-only; 22% both EHR and paper) and 48% paper-only systems. Conformity with indicated care for practices with EHR systems was modestly higher for 2 of 7 quality measures compared to those without. After controlling for patient and site characteristics, use of EHR was associated with improved delivery of 3 of 7 quality measures (angiotensin-converting enzyme inhibitor/angiotensin receptor blocker, aldosterone antagonist, and HF education), similar care for 3 measures (beta-blocker, anticoagulation for atrial fibrillation, and cardiac resynchronization therapy), and worse for 1 measure (implantable cardioverter-defibrillator).

CONCLUSIONS

These data are among the first to assess the potential influence of EHR on conformity with HF guidelines in the outpatient setting and suggest that EHR systems as currently deployed are associated with only modest differences in some, but not other, quality measures provided to HF patients compared with use of paper-only systems.

Using electronic medical records to measure and improve performance

Clinical performance measurement and public reporting are taking center stage nationwide, linked to transparency initiatives and incentive systems that reward physicians for meeting endorsed quality standards. While electronic medical records (EMRs) are increasingly available to measure and improve quality of care, performance measurement continues to be dominated by the use of insurance claims. Limitations to claims-based measurement include challenges in assigning attribution of care to specific physicians, inefficient and incomplete sampling methods, and the coarseness of measures frequently available to insurers. Practice improvement using claims-based approaches is further limited by the inability to provide timely and specific feedback to physicians and their patients. Finally, in claims-based approaches, care is not measured for the 47 million uninsured patients in the United States. In the current presentation I describe how these limitations are being addressed using EMRs, highlighting the design and selected preliminary results of a large trial to improve the care of patients with diabetes.