Typical electronic health record use in primary care practices and the quality of diabetes care

The Key Digital Tool Features of Complex Telehealth Interventions Used for Type 2 Diabetes Self-Management and Monitoring With Health Professional Involvement: Scoping Review

BACKGROUND

Therapeutic education and patient self-management are crucial in diabetes prevention and treatment. Improving diabetes self-management requires multidisciplinary team intervention, nutrition education that facilitates self-management, informed decision-making, and the organization and delivery of appropriate health care services. The emergence of telehealth services has provided the public with various tools for educating themselves and for evaluating, monitoring, and improving their health and nutrition-related behaviors. Combining health technologies with clinical expertise, social support, and health professional involvement could help persons living with diabetes improve their disease self-management skills and prevent its long-term consequences.

OBJECTIVE

This scoping review's primary objective was to identify the key digital tool features of complex telehealth interventions used for type 2 diabetes or prediabetes self-management and monitoring with health professional involvement that help improve health outcomes. A secondary objective was to identify how these key features are developed and combined.

METHODS

A 5-step scoping review methodology was used to map relevant literature published between January 1, 2010 and March 31, 2022. Electronic searches were performed in the MEDLINE, CINAHL, and Embase databases. The searches were limited to scientific publications in English and French that either described the conceptual development of a complex telehealth intervention that combined self-management and monitoring with health professional involvement or evaluated its effects on the therapeutic management of patients with type 2 diabetes or prediabetes. Three reviewers independently identified the articles and extracted the data.

RESULTS

The results of 42 studies on complex telehealth interventions combining diabetes self-management and monitoring with the involvement of at least 1 health professional were synthesized. The health professionals participating in these studies were physicians, dietitians, nurses, and psychologists. The digital tools involved were smartphone apps or web-based interfaces that could be used with medical devices. We classified the features of these technologies into eight categories, depending on the intervention objective: (1) monitoring of glycemia levels, (2) physical activity monitoring, (3) medication monitoring, (4) diet monitoring, (5) therapeutic education, (6) health professional support, (7) other health data monitoring, and (8) health care management. The patient-logged data revealed behavior patterns that should be modified to improve health outcomes. These technologies, used with health professional involvement, patient self-management, and therapeutic education, translate into better control of glycemia levels and the adoption of healthier lifestyles. Likewise, they seem to improve monitoring by health professionals and foster multidisciplinary collaboration through data sharing and the development of more concise automatically generated reports.

CONCLUSIONS

This scoping review synthesizes multiple studies that describe the development and evaluation of complex telehealth interventions used in combination with health professional support. It suggests that combining different digital tools that incorporate diabetes self-management and monitoring features with a health professional's advice and interaction results in more effective interventions and outcomes.

Basic electronic health record (EHR) adoption in **Türkiye is nearly complete but challenges persist

BACKGROUND

The digitalization studies in public hospitals in Türkiye started with the Health Transformation Program in 2003. As digitalization was accomplished, the policymakers needed to measure hospitals' electronic health record (EHR) usage and adoptions. The ministry of health has been measuring the dissemination of meaningful usage and adoption of EHR since 2013 using Electronic Medical Record Adoption Model (EMRAM). The first published study about this analysis covered the surveys applied between 2013 and 2017. The results showed that 63.1% of all hospitals in Türkiye had at least basic EHR functions, and 36% had comprehensive EHR functions. Measuring the countrywide EHR adoption level is becoming popular in the world. This study aims to measure adoption levels of EHR in public hospitals in Türkiye, indicate the change to the previous study, and make a benchmark with other countries measuring national EHR adoption levels. The research question of this study is to reveal whether there has been a change in the adoption level of EHR in the three years since 2018 in Türkiye. Also, make a benchmark with other countries such as the US, Japan, and China in country-wide EHR adoption in 2021.

METHODS

In 2021, 717 public hospitals actively operating in Türkiye completed the EMRAM survey. The survey results, deals with five topics (General Stage Status, Information Technology Security, Electronic Health Record/Clinical Data Repository, Clinical Documentation, Closed-Loop Management), was reviewed by the authors. Survey data were compared according to hospital type (Specialty Hospitals, General Hospitals, Teaching and Research Hospitals) in terms of general stage status. The data obtained from the survey results were analyzed with QlikView Personal Edition. The availability and prevalence of medical information systems and EHR functions and their use were measured.

RESULTS

We found that 33.7% of public hospitals in Türkiye have only basic EHR functions, and 66.3% have extensive EHR functions, which yields that all hospitals (100%) have at least basic EHR functions. That means remarkable progress from the previous study covering 2013 and 2017. This level also indicates that Türkiye has slightly better adoption from the US (96%) and much better than China (85.3%) and Korea (58.1%).

CONCLUSIONS

Although there has been outstanding (50%) progress since 2017 in Turkish public hospitals, it seems there is still a long way to disseminate comprehensive EHR functions, such as closed-loop medication administration, clinical decision support systems, patient engagement, etc. Measuring the stage of EHR adoption at regular intervals and on analytical scales is an effective management tool for policymakers. The bottom-up adoption approach established for adopting and managing EHR functions in the US has also yielded successful results in Türkiye.

Assessment of Variation in Electronic Health Record Capabilities and Reported Clinical Quality Performance in Ambulatory Care Clinics, 2014-2017

IMPORTANCE

Electronic health records (EHRs) are widely promoted to improve the quality of health care, but information about the association of multifunctional EHRs with broad measures of quality in ambulatory settings is scarce.

OBJECTIVE

To assess the association between EHRs with different degrees of capabilities and publicly reported ambulatory quality measures in at least 3 clinical domains of care.

DESIGN, SETTING, AND PARTICIPANTS

This cross-sectional and longitudinal study was conducted using survey responses from 1141 ambulatory clinics in Minnesota, Washington, and Wisconsin affiliated with a health system that responded to the Healthcare Information and Management Systems Society Annual Survey and reported performance measures in 2014 to 2017. Statistical analysis was performed from July 10, 2019, through February 26, 2021.

MAIN OUTCOMES AND MEASURES

A composite measure of EHR capability that considered 50 EHR capabilities in 7 functional domains, grouped into the following ordered categories: no functional EHR, EHR underuser, EHR, neither underuser or superuser, EHR superuser; as well as a standardized composite of ambulatory clinical performance measures that included 3 to 25 individual measures (median, 13 individual measures).

RESULTS

In 2014, 381 of 746 clinics (51%) were EHR superusers; this proportion increased in each subsequent year (457 of 846 clinics [54%] in 2015, 510 of 881 clinics [58%] in 2016, and 566 of 932 clinics [61%] in 2017). In each cross-sectional analysis year, EHR superusers had better clinical quality performance than other clinics (adjusted difference in score: 0.39 [95% CI, 0.12-0.65] in 2014; 0.29 [95% CI, -0.01 to 0.59] in 2015; 0.26 [95% CI, -0.05 to 0.56] in 2016; and 0.20 [95% CI, -0.04 to 0.45] in 2017). This difference in scores translates into an approximately 9% difference in a clinic's rank order in clinical quality. In longitudinal analyses, clinics that progressed to EHR superuser status had only slightly better gains in clinical quality between 2014 and 2017 compared with the gains in clinical quality of clinics that were static in terms of their EHR status (0.10 [95% CI, -0.13 to 0.32]). In an exploratory analysis, different types of EHR capability progressions had different degrees of associated improvements in ambulatory clinical quality (eg, progression from no functional EHR to a status short of superuser, 0.06 [95% CI, -0.40 to 0.52]; progression from EHR underuser to EHR superuser, 0.18 [95% CI, -0.14 to 0.50]).

CONCLUSIONS AND RELEVANCE

Between 2014 and 2017, ambulatory clinics in Minnesota, Washington, and Wisconsin with EHRs having greater capabilities had better composite measures of clinical quality than other clinics, but clinics that gained EHR capabilities during this time had smaller increases in clinical quality that were not statistically significant.

Adoption rates of electronic health records in Turkish Hospitals and the relation with hospital sizes

BACKGROUND

Nation-wide adoption of electronic health records (EHRs) in hospitals has become a Turkish policy priority in recognition of their benefits in maintaining the overall quality of clinical care. The electronic medical record maturity model (EMRAM) is a widely used survey tool developed by the Healthcare Information and Management Systems Society (HIMSS) to measure the rate of adoption of EHR functions in a hospital or a secondary care setting. Turkey completed many standardizations and infrastructural improvement initiatives in the health information technology (IT) domain during the first phase of the Health Transformation Program between 2003 and 2017. Like the United States of America (USA), the Turkish Ministry of Health (MoH) applied a bottom-up approach to adopting EHRs in state hospitals. This study aims to measure adoption rates and levels of EHR use in state hospitals in Turkey and investigate any relationship between adoption and use and hospital size.

METHODS

EMRAM surveys were completed by 600 (68.9%) state hospitals in Turkey between 2014 and 2017. The availability and prevalence of medical information systems and EHR functions and their use were measured. The association between hospital size and the availability/prevalence of EHR functions was also calculated.

RESULTS

We found that 63.1% of all hospitals in Turkey have at least basic EHR functions, and 36% have comprehensive EHR functions, which compares favourably to the results of Korean hospitals in 2017, but unfavorably to the results of US hospitals in 2015 and 2017. Our findings suggest that smaller hospitals are better at adopting certain EHR functions than larger hospitals.

CONCLUSION

Measuring the overall adoption rates of EHR functions is an emerging approach and a beneficial tool for the strategic management of countries. This study is the first one covering all state hospitals in a country using EMRAM. The bottom-up approach to adopting EHR in state hospitals that was successful in the USA has also been found to be successful in Turkey. The results are used by the Turkish MoH to disseminate the nation-wide benefits of EHR functions.

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.

Feasibility of a voice-enabled automated platform for medical data collection: CardioCube

AIM

A feasibility study was conducted to evaluate implementation of a voice-enabled automated platform for collection of medical data from patients with cardiovascular disease: CardioCube.

METHODS

The study enrolled 22 individuals (10 males, 45.5%) including 9 patients with cardiovascular disease and 13 healthy participants. Utilizing (1) voice-enabled patient registration software implemented on the Amazon Echo and (2) web-based electronic health record (EHR) system, study participants verbally answered a set of clinical questions. Primary endpoint: accuracy of ​the ​CardioCube system. Secondary endpoints: acceptability, usability and technical performance. The study was performed at the Outpatient Cardiology Clinic, Cedars-Sinai Medical Center, Los Angeles, CA, USA.

RESULTS

The CardioCube system collected 432 data points with a high agreement level between verbally provided data and corresponding EHR information (accuracy 97.51%). The CardioCube was able to automatically generate a summarized medical report, which was instantly available for a doctor in the web-based EHR system. Patients reported CardioCube was "easy to use". Applicability of the system was graded excellent by the medical staff. A single session utilized less than 0.002% of available computational resources.

CONCLUSION

CardioCube can collect, index and document medical data using a voice interface. In this pilot study, CardioCube supported healthcare professionals by performing time-consuming paperwork during patient registration.

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.

Electronic clinical reminder and quality of primary diabetes care

AIMS

To study the association of EMR's clinical reminder use on a comprehensive set of diabetes quality metrics in U.S. office-based physicians and within solo- versus multi-physician practices. We conducted a retrospective cohort study on visits made by adults with diabetes identified from the National Ambulatory Medical Care Survey (2012-2014).

METHODS

Multiple logistic regression is used to test for associations between clinical reminder use and recommended services by the American Diabetes Association.

RESULTS

Of 5508 visits, nationally representing 112,978,791 visits, 31% received HbA1c tests, 13% received urinalysis test, and <10% received retinal or foot exams. Main effects of practice size and clinical reminder use were found for HbA1c, urinalysis, and foot exams. We find no statistically significant relationship to suggest that clinical reminder use improve diabetes process guidelines for solo practices.

CONCLUSIONS

Resource efforts, beyond clinical reminders, are needed to reduce gaps in primary diabetes care between solo and non-solo practices.

An Optimization Program to Help Practices Assess Data Quality and Workflow With Their Electronic Medical Records: Observational Study

Background

Electronic medical record (EMR) adoption among Canadian primary care physicians continues to grow. In Ontario, >80% of primary care providers now use EMRs. Adopting an EMR does not guarantee better practice management or patient care; however, EMR users must understand how to effectively use it before they can realize its full benefit. OntarioMD developed an EMR Practice Enhancement Program (EPEP) to overcome challenges of clinicians and staff in finding time to learn a new technology or workflow. EPEP deploys practice consultants to work with clinicians onsite to harness their EMR toward practice management and patient care goals.

Objective

This paper aims to illustrate the application of the EPEP approach to address practice-level factors that impede or enhance the effective use of EMRs to support patient outcomes and population health. The secondary objective is to draw attention to the potential impact of this practice-level work to population health (system-level), as priority population health indicators are addressed by quality improvement work at the practice-level.

Methods

EPEP’s team of practice consultants work with clinicians to identify gaps in their knowledge of EMR functionality, analyze workflow, review EMR data quality, and develop action plans with achievable tasks. Consultants establish baselines for data quality in key clinical indicators and EMR proficiency using OntarioMD-developed maturity assessment tools. We reassessed and compared postengagement, data quality, and maturity. Three examples illustrating the EPEP approach and results are presented to illuminate strengths, limitations, and implications for further analysis. In each example, a different consultant was responsible for engaging with the practice to conduct the EPEP method. No standard timeframe exists for an EPEP engagement, as requirements differ from practice to practice, and EPEP tailors its approach and timeframe according to the needs of the practice.

Results

After presenting findings of the initial data quality review, workflow, and gap analysis to the practice, consultants worked with practices to develop action plans and begin implementing recommendations. Each practice had different objectives in engaging the EPEP; here, we compared improvements across measures that were common priorities among all 3—screening (colorectal, cervical, and breast), diabetes diagnosis, and documentation of the smoking status. Consultants collected postengagement data at intervals (approximately 6, 12, and 18 months) to assess the sustainability of the changes. The postengagement assessment showed data quality improvements across several measures, and new confidence in their data enabled practices to implement more advanced functions (such as toolbars) and targeted initiatives for subpopulations of patients.

Conclusions

Applying on-site support to analyze gaps in EMR knowledge and use, identify efficiencies to improve workflow, and correct data quality issues can make dramatic improvements in a practice’s EMR proficiency, allowing practices to experience greater benefit from their EMR, and consequently, improve their patient care.

Designing health information technology tools for behavioral health clinicians integrated within a primary care team

Background

Electronic health records (EHRs) are a key tool for primary care practice. However, the EHR functionality is not keeping pace with the evolving informational and decision-support needs of behavioural health clinicians (BHCs) working on integrated teams.

Objective

Describe the workflows and tasks of integrated BHCs working with adult patients identify their health information technology (health IT) needs and develop EHR tools to address them.

Method

A mixed-methods, comparative case study of six community health centres (CHCs) in Oregon, each with at least one BHC integrated into their primary care team. We observed clinical work and conducted interviews to understand workflows and clinical tasks, aiming to identify how effectively current EHRs supported integrated care delivery, including transitions, documentation, information sharing and decision-making. We analysed these data and employed a user-centred design process to develop EHR tools addressing the identified needs.

Results

BHCs used the primary care EHR for documentation and communication with other team members, but the EHR lacked the functionality to fully support integrated care. Needs include the ability to: (1) automate and track paper-based screening; (2) document behavioural health history; (3) access patient social and medical history relevant to behavioural health issues and (4) rapidly document and track progress on goals. To meet these needs, we engaged users and developed a set of EHR tools called the Behavioural Health e-Suite (BH e-Suite).

Conclusion

US-based integrated primary care teams, and particularly BHCs working with adult populations, have unique information needs, workflows and tasks. These needs can be met and supported by the EHR with a moderate level of modification.

Smart Diabetic Screening and Managing Software, A Novel Decision Support System

BACKGROUND

Diabetes is a serious chronic disease, and its increasing prevalence is a global concern. If diabetes mellitus is left untreated, poor control of blood glucose may cause long-term complications. A big challenge encountered by clinicians is the clinical management of diabetes. Many IT-based interventions such ad CDSS have been made to improve the adherence to the standard care for chronic diseases.

OBJECTIVE

The aim of this study is to establish a decision support system of diabetes management based on diabetes care guidelines in order to reduce medical errors and increase adherence to guidelines.

MATERIALS AND METHODS

To start the process, at first the existing guidelines in the field of diabetes mellitus such as ADA 2017 and AACE guideline 2017 were reviewed, and accordingly, flowcharts and algorithms for screening and managing of diabetes were designed. Then, it was passed on to the information technology team to design software.

RESULTS

The most significant outcome of this research was to establish a smart diabetic screening and managing software, which is an important stride to promote patients' health status, control diabetes and save patients' information as an important and reliable source.

CONCLUSION

Health care technologies have the potential to improve the quality of diabetes care through IT-based intervention, such as clinical decision support systems. In a chronic disease like diabetes, the critical component is the disease management. The advantages of this web-based system are on-time registration, reports of diabetic prevalence, uncontrolled diabetes, diabetic complications and reducing the rate of mismanagement of diabetes, so that it helps the physicians in order to manage the patients in a better way.

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

BACKGROUND

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

METHOD

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

RESULTS

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

CONCLUSION

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

Consistency of denominator data in electronic health records in Australian primary healthcare services: enhancing data quality

The quality of data derived from primary healthcare electronic systems has been subjected to little critical systematic analysis, especially in relation to the purported benefits and substantial investment in electronic information systems in primary care. Many indicators of quality of care are based on numbers of certain types of patients as denominators. Consistency of denominator data is vital for comparison of indicators over time and between services. This paper examines the consistency of denominator data extracted from electronic health records (EHRs) for monitoring of access and quality of primary health care. Data collection and analysis were conducted as part of a prospective mixed-methods formative evaluation of the Commonwealth Government's Indigenous Chronic Disease Package. Twenty-six general practices and 14 Aboriginal Health Services (AHSs) located in all Australian States and Territories and in urban, regional and remote locations were purposively selected within geographically defined locations. Percentage change in reported number of regular patients in general practices ranged between -50% and 453% (average 37%). The corresponding figure for AHSs was 1% to 217% (average 31%). In approximately half of general practices and AHSs, the change was ≥ 20%. There were similarly large changes in reported numbers of patients with a diagnosis of diabetes or coronary heart disease (CHD), and Indigenous patients. Inconsistencies in reported numbers were due primarily to limited capability of staff in many general practices and AHSs to accurately enter, manage, and extract data from EHRs. The inconsistencies in data required for the calculation of many key indicators of access and quality of care places serious constraints on the meaningful use of data extracted from EHRs. There is a need for greater attention to quality of denominator data in order to realise the potential benefits of EHRs for patient care, service planning, improvement, and policy. We propose a quality improvement approach for enhancing data quality.

Electronic Health Records and Quality of Care: An Observational Study Modeling Impact on Mortality, Readmissions, and Complications

Electronic health records (EHRs) were implemented to improve quality of care and patient outcomes. This study assessed the relationship between EHR-adoption and patient outcomes.We performed an observational study using State Inpatient Databases linked to American Hospital Association survey, 2011. Surgical and medical patients from 6 large, diverse states were included. We performed univariate analyses and developed hierarchical regression models relating level of EHR utilization and mortality, readmission rates, and complications. We evaluated the effect of EHR adoption on outcomes in a difference-in-differences analysis, 2008 to 2011.Medical and surgical patients sought care at hospitals reporting no EHR (3.5%), partial EHR (55.2%), and full EHR systems (41.3%). In univariate analyses, patients at hospitals with full EHR had the lowest rates of inpatient mortality, readmissions, and Patient Safety Indicators followed by patients at hospitals with partial EHR and then patients at hospitals with no EHR (P < 0.05). However, these associations were not robust when accounting for other patient and hospital factors, and adoption of an EHR system was not associated with improved patient outcomes (P > 0.05).These results indicate that patients receiving medical and surgical care at hospitals with no EHR system have similar outcomes compared to patients seeking care at hospitals with a full EHR system, after controlling for important confounders.To date, we have not yet seen the promised benefits of EHR systems on patient outcomes in the inpatient setting. EHRs may play a smaller role than expected in patient outcomes and overall quality of care.

The impact of electronic health records and teamwork on diabetes care quality

OBJECTIVES

Evidence of the impact electronic health records (EHRs) have on clinical outcomes remains mixed. The impact of EHRs likely depends on the organizational context in which they are used. This study focuses on one aspect of the organizational context: cohesion of primary care teams. We examined whether team cohesion among primary care team members changed the association between EHR use and changes in clinical outcomes for patients with diabetes.

STUDY DESIGN

Retrospective longitudinal study.

METHODS

We combined provider-reported primary care team cohesion with lab values for patients with diabetes collected during the staggered EHR implementation (2005-2009). We used multivariate regression models with patient-level fixed effects to assess whether team cohesion levels changed the association between outpatient EHR use and clinical outcomes for patients with diabetes. Subjects were comprised of 80,611 patients with diabetes, in whom we measured changes in glycated hemoglobin (A1C) and low-density lipoprotein cholesterol (LDL-C).

RESULTS

For A1C, EHR use was associated with an average decrease of 0.11% for patients with higher-cohesion primary care teams compared with a decrease of 0.08% for patients with lower-cohesion teams (difference = 0.02% in A1C; 95% CI, 0.01%-0.03%). For LDL-C, EHR use was associated with a decrease of 2.15 mg/dL for patients with higher-cohesion primary care teams compared with a decrease of 1.42 mg/dL for patients with lower-cohesion teams (difference = 0.73 mg/dL; 95% CI, 0.41-1.11 mg/dL).

CONCLUSIONS

Patients cared for by higher cohesion primary care teams experienced modest but statistically significantly greater EHR-related health outcome improvements, compared with patients cared for by providers practicing in lower cohesion teams.

Supporting Practices to Adopt Registry-Based Care (SPARC): protocol for a randomized controlled trial

BACKGROUND

Diabetes is predicted to increase in incidence by 42% from 1995 to 2025. Although most adults with diabetes seek care from primary care practices, adherence to treatment guidelines in these settings is not optimal. Many practices lack the infrastructure to monitor patient adherence to recommended treatment and are slow to implement changes critical for effective management of patients with chronic conditions. Supporting Practices to Adopt Registry-Based Care (SPARC) will evaluate effectiveness and sustainability of a low-cost intervention designed to support work process change in primary care practices and enhance focus on population-based care through implementation of a diabetes registry.

METHODS

SPARC is a two-armed randomized controlled trial (RCT) of 30 primary care practices in the Virginia Ambulatory Care Outcomes Research Network (ACORN). Participating practices (including control groups) will be introduced to population health concepts and tools for work process redesign and registry adoption at a meeting of practice-level implementation champions. Practices randomized to the intervention will be assigned study peer mentors, receive a list of specific milestones, and have access to a physician informaticist. Peer mentors are clinicians who successfully implemented registries in their practices and will help champions in the intervention practices throughout the implementation process. During the first year, peer mentors will contact intervention practices monthly and visit them quarterly. Control group practices will not receive support or guidance for registry implementation. We will use a mixed-methods explanatory sequential design to guide collection of medical record, participant observation, and semistructured interview data in control and intervention practices at baseline, 12 months, and 24 months. We will use grounded theory and a template-guided approach using the Consolidated Framework for Implementation Research to analyze qualitative data on contextual factors related to registry adoption. We will assess intervention effectiveness by comparing changes in patient-level hemoglobin A1c scores from baseline to year 1 between intervention and control practices.

DISCUSSION

Findings will enhance our understanding of how to leverage existing practice resources to improve diabetes care in primary care practices by implementing and using a registry. SPARC has the potential to validate the effectiveness of low-cost implementation strategies that target practice change in primary care.

TRIAL REGISTRATION

NCT02318108.

Practice context affects efforts to improve diabetes care for primary care patients: a pragmatic cluster randomized trial

BACKGROUND

Efforts to improve primary care diabetes management have assessed strategies across heterogeneous groups of patients and practices. However, there is substantial variability in how well practices implement interventions and achieve desired outcomes.

OBJECTIVE

To examine practice contextual features that moderate intervention effectiveness.

DESIGN

Secondary analysis of data from a cluster randomized trial of three approaches for implementing the Chronic Care Model to improve diabetes care.

PARTICIPANTS

Forty small to mid-sized primary care practices participated, with 522 clinician and staff member surveys. Outcomes were assessed for 822 established patients with a diagnosis of type 2 diabetes who had at least one visit to the practice in the 18 months following enrollment.

MAIN MEASURES

The primary outcome was a composite measure of diabetes process of care, ascertained by chart audit, regarding nine quality measures from the American Diabetes Association Physician Recognition Program: HgA1c, foot exam, blood pressure, dilated eye exam, cholesterol, nephropathy screen, flu shot, nutrition counseling, and self-management support. Data from practices included structural and demographic characteristics and Practice Culture Assessment survey subscales (Change Culture, Work Culture, Chaos).

KEY RESULTS

Across the three implementation approaches, demographic/structural characteristics (rural vs. urban + .70(p = .006), +2.44(p < .001), -.75(p = .004)); Medicaid: < 20 % vs. ≥ 20 % (-.20(p = .48), +.75 (p = .08), +.60(p = .02)); practice size: < 4 clinicians vs. ≥ 4 clinicians (+.56(p = .02), +1.96(p < .001), +.02(p = .91)); practice Change Culture (high vs. low: -.86(p = .048), +1.71(p = .005), +.34(p = .22)), Work Culture (high vs. low: -.67(p = .18), +2.41(p < .001), +.67(p = .005)) and variability in practice Change Culture (high vs. low: -.24(p = .006), -.20(p = .0771), -.44(p = .0019) and Work Culture (high vs. low: +.56(p = .3160), -1.0(p = .008), -.25 (p = .0216) were associated with trajectories of change in diabetes process of care, either directly or differentially by study arm.

CONCLUSIONS

This study supports the need for broader use of methodological approaches to better examine contextual effects on implementation and effectiveness of quality improvement interventions in primary care settings.

Diabetes and hypertension quality measurement in four safety-net sites: lessons learned after implementation of the same commercial electronic health record

BACKGROUND

In this new era after the Health Information Technology for Economic and Clinical Health (HITECH) Act of 2009, the literature on lessons learned with electronic health record (EHR) implementation needs to be revisited.

OBJECTIVES

Our objective was to describe what implementation of a commercially available EHR with built-in quality query algorithms showed us about our care for diabetes and hypertension populations in four safety net clinics, specifically feasibility of data retrieval, measurements over time, quality of data, and how our teams used this data.

METHODS

A cross-sectional study was conducted from October 2008 to October 2012 in four safety-net clinics located in the Midwest and Western United States. A data warehouse that stores data from across the U.S was utilized for data extraction from patients with diabetes or hypertension diagnoses and at least two office visits per year. Standard quality measures were collected over a period of two to four years. All sites were engaged in a partnership model with the IT staff and a shared learning process to enhance the use of the quality metrics.

RESULTS

While use of the algorithms was feasible across sites, challenges occurred when attempting to use the query results for research purposes. There was wide variation of both process and outcome results by individual centers. Composite calculations balanced out the differences seen in the individual measures. Despite using consistent quality definitions, the differences across centers had an impact on numerators and denominators. All sites agreed to a partnership model of EHR implementation, and each center utilized the available resources of the partnership for Center-specific quality initiatives.

CONCLUSIONS

Utilizing a shared EHR, a Regional Extension Center-like partnership model, and similar quality query algorithms allowed safety-net clinics to benchmark and improve the quality of care across differing patient populations and health care delivery models.

An Indian eye to personalized medicine

Acknowledging the successful sequencing of the human genome and the valuable insights it has rendered, genetic drafting of non-human organisms can further enhance the understanding of modern biology. The price of sequencing technology has plummeted with time, and there is a noticeable enhancement in its implementation and recurrent usage. Sequenced genome information can be contained in a microarray chip, and then processed by a computer system for inferring analytics and predictions. Specifically, smart cards have been significantly applicable to assimilate and retrieve complex data, with ease and implicit mobility. Herein, we propose "The G-Card", a development with respect to the prevalent smart card, and an extension to the Electronic Health Record (EHR), that will hold the genome sequence of an individual, so that the medical practitioner can better investigate irregularities in a patient's health and hence recommend a precise prognosis.

Structuring clinical workflows for diabetes care: an overview of the OntoHealth approach

BACKGROUND

Electronic health records (EHRs) play an important role in the treatment of chronic diseases such as diabetes mellitus. Although the interoperability and selected functionality of EHRs are already addressed by a number of standards and best practices, such as IHE or HL7, the majority of these systems are still monolithic from a user-functionality perspective. The purpose of the OntoHealth project is to foster a functionally flexible, standards-based use of EHRs to support clinical routine task execution by means of workflow patterns and to shift the present EHR usage to a more comprehensive integration concerning complete clinical workflows.

OBJECTIVES

The goal of this paper is, first, to introduce the basic architecture of the proposed OntoHealth project and, second, to present selected functional needs and a functional categorization regarding workflow-based interactions with EHRs in the domain of diabetes.

METHODS

A systematic literature review regarding attributes of workflows in the domain of diabetes was conducted. Eligible references were gathered and analyzed using a qualitative content analysis. Subsequently, a functional workflow categorization was derived from diabetes-specific raw data together with existing general workflow patterns.

RESULTS

This paper presents the design of the architecture as well as a categorization model which makes it possible to describe the components or building blocks within clinical workflows. The results of our study lead us to identify basic building blocks, named as actions, decisions, and data elements, which allow the composition of clinical workflows within five identified contexts.

CONCLUSIONS

The categorization model allows for a description of the components or building blocks of clinical workflows from a functional view.

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.

A qualitative study identifying the cost categories associated with electronic health record implementation in the UK

OBJECTIVE

We conducted a prospective evaluation of different forms of electronic health record (EHR) systems to better understand the costs incurred during implementation and the factors that can influence these costs.

METHODS

We selected a range of diverse organizations across three different geographical areas in England that were at different stages of implementing three centrally procured applications, that is, iSOFT's Lorenzo Regional Care, Cerner's Millennium, and CSE's RiO. 41 semi-structured interviews were conducted with hospital staff, members of the implementation team, and those involved in the implementation at a national level.

RESULTS

Four main overarching cost categories were identified: infrastructure (eg, hardware and software), personnel (eg, training team), estates/facilities (eg, space), and other (eg, training materials). Many factors were felt to impact on these costs, with different hospitals choosing varying amounts and types of infrastructure, diverse training approaches for staff, and different software applications to integrate with the new system.

CONCLUSIONS

Improving the quality and safety of patient care through EHR adoption is a priority area for UK and US governments and policy makers worldwide. With cost considered one of the most significant barriers, it is important for hospitals and governments to be clear from the outset of the major cost categories involved and the factors that may impact on these costs. Failure to adequately train staff or to follow key steps in implementation has preceded many of the failures in this domain, which can create new safety hazards.

Electronic health records for cardiovascular medicine

Nowadays, many cardiology health care centers and hospitals adopt new technologies to improve interaction with their patients. The Electronic Health Records (EHR) offer health care centers and institutions the possibility to improve the management of their patients' health data. Currently, many physicians are using EHRs to improve health care quality and efficiency. A large number of companies have emerged to provide hospitals with the opportunity to adopt EHRs within a health care platform proposing different functionalities and services which achieve certain certification criteria. This paper identifies the current list of certified EHRs for cardiovascular medicine and assesses the specifications of the EHRs selected. The result of this paper may assist EHR seekers for cardiovascular medicine in their tasks.

The impact of electronic health records on workflow and financial measures in primary care practices

OBJECTIVE

To estimate a commercially available ambulatory electronic health record's (EHR's) impact on workflow and financial measures.

DATA SOURCES/STUDY SETTING

Administrative, payroll, and billing data were collected for 26 primary care practices in a fee-for-service network that rolled out an EHR on a staggered schedule from June 2006 through December 2008.

STUDY DESIGN

An interrupted time series design was used. Staffing, visit intensity, productivity, volume, practice expense, payments received, and net income data were collected monthly for 2004-2009. Changes were evaluated 1-6, 7-12, and >12 months postimplementation.

DATA COLLECTION/EXTRACTION METHODS

Data were accessed through a SQLserver database, transformed into SAS®, and aggregated by practice. Practice-level data were divided by full-time physician equivalents for comparisons across practices by month.

PRINCIPAL FINDINGS

Staffing and practice expenses increased following EHR implementation (3 and 6 percent after 12 months). Productivity, volume, and net income decreased initially but recovered to/close to preimplementation levels after 12 months. Visit intensity did not change significantly, and a secular trend offset the decrease in payments received.

CONCLUSIONS

Expenses increased and productivity decreased following EHR implementation, but not as much or as persistently as might be expected. Longer term effects still need to be examined.

Population prevalence and control of cardiovascular risk factors: what electronic medical records tell us

Objective

To analyze the prevalence, control, and management of hypertension, hypercholesterolemia, and diabetes mellitus type 2 (DM2).

Design

Cross-sectional analysis of all individuals attended in the Catalan primary care centers between 2006 and 2009.

Location

History of cardiovascular diseases, diagnosis and treatment of hypertension, hypercholesterolemia, DM2, lipid profile, glycemia and blood pressure data were extracted from electronic medical records. Age-standardized prevalence and levels of management and control were estimated.

Participants

Individuals aged 35–74 years using primary care databases.

Main measures

A total of 2,174,515 individuals were included (mean age 52 years [SD 11], 47% men).

Results

Hypertension was the most prevalent cardiovascular risk factor (39% in women, 41% in men) followed by hypercholesterolemia (38% and 40%) and DM2 (12% and 16%), respectively. Diuretics and angiotensin-converting enzyme inhibitors were most often prescribed for hypertension control (<140/90 mmHg, achieved in 68% of men and 60% of women treated). Hypercholesterolemia was controlled (low-density lipoprotein cholesterol <130 mg/dl) in just 31% of men and 26% of women with no history of cardiovascular disease, despite lipid-lowering treatment, primarily (90%) with statins. The percentage of women and men with DM2 and with glycated hemoglobin <7% was 64.7% and 59.2%, respectively; treatment was predominantly with oral hypoglycemic agents alone (70%), or combined with insulin (15%).

Conclusions

Hypertension was the most prevalent cardiovascular risk factor in the Catalan population attended at primary care centers. About two thirds of individuals with hypertension or DM2 were adequately controlled; hypercholesterolemia control was particularly low.

Implementation of an outpatient electronic health record and emergency department visits, hospitalizations, and office visits among patients with diabetes

IMPORTANCE

The US federal government is spending billions of dollars in physician incentives to encourage the meaningful use of electronic health records (EHRs). Although the use of EHRs has potential to improve patient health outcomes, the existing evidence has been limited and inconsistent.

OBJECTIVE

To examine the association between implementing a commercially available outpatient EHR and emergency department (ED) visits, hospitalizations, and office visits for patients with diabetes mellitus.

DESIGN, SETTING, AND POPULATION

Staggered EHR implementation across outpatient clinics in an integrated delivery system (Kaiser Permanente Northern California) between 2005 and 2008 created an opportunity for studying changes associated with EHR use. Among a population-based sample of 169,711 patients with diabetes between 2004 and 2009, we analyzed 4,997,585 person-months before EHR implementation and 4,648,572 person-months after an EHR was being used by patients' physicians.

MAIN OUTCOMES AND MEASURES

We examined the association between EHR use and unfavorable clinical events (ED visits and hospitalizations) and office visit use among patients with diabetes, using multivariable regression with patient-level fixed-effect analyses and adjustment for trends over time.

RESULTS

In multivariable analyses, use of the EHR was associated with a statistically significantly decreased number of ED visits, 28.80 fewer visits per 1000 patients annually (95% CI, 20.28 to 37.32), from a mean of 519.12 visits per 1000 patients annually without using the EHR to 490.32 per 1000 patients when using the EHR. The EHR was also associated with 13.10 fewer hospitalizations per 1000 patients annually (95% CI, 7.37 to 18.82), from a mean of 251.60 hospitalizations per 1000 patients annually with no EHR to 238.50 per 1000 patients annually when using the EHR. There were similar statistically significant reductions in nonelective hospitalizations (10.92 fewer per 1000 patients annually) and hospitalizations for ambulatory care-sensitive conditions (7.08 fewer per 1000 patients annually). There was no statistically significant association between EHR use and office visit rates.

CONCLUSIONS AND RELEVANCE

Among patients with diabetes, use of an outpatient EHR in an integrated delivery system was associated with modest reductions in ED visits and hospitalizations but not office visit rates. Further studies are needed to quantify the association of EHR use with changes in costs.

Electronic tools for health information exchange: an evidence-based analysis

BACKGROUND

As patients experience transitions in care, there is a need to share information between care providers in an accurate and timely manner. With the push towards electronic medical records and other electronic tools (eTools) (and away from paper-based health records) for health information exchange, there remains uncertainty around the impact of eTools as a form of communication.

OBJECTIVE

To examine the impact of eTools for health information exchange in the context of care coordination for individuals with chronic disease in the community.

DATA SOURCES

A literature search was performed on April 26, 2012, using OVID MEDLINE, OVID MEDLINE In-Process and Other Non-Indexed Citations, OVID EMBASE, EBSCO Cumulative Index to Nursing & Allied Health Literature (CINAHL), the Wiley Cochrane Library, and the Centre for Reviews and Dissemination database, for studies published until April 26, 2012 (no start date limit was applied).

REVIEW METHODS

A systematic literature search was conducted, and meta-analysis conducted where appropriate. Outcomes of interest fell into 4 categories: health services utilization, disease-specific clinical outcomes, process-of-care indicators, and measures of efficiency. The quality of the evidence was assessed individually for each outcome. Expert panels were assembled for stakeholder engagement and contextualization.

RESULTS

Eleven articles were identified (4 randomized controlled trials and 7 observational studies). There was moderate quality evidence of a reduction in hospitalizations, hospital length of stay, and emergency department visits following the implementation of an electronically generated laboratory report with recommendations based on clinical guidelines. The evidence showed no difference in disease-specific outcomes; there was no evidence of a positive impact on process-of-care indicators or measures of efficiency.

LIMITATIONS

A limited body of research specifically examined eTools for health information exchange in the population and setting of interest. This evidence included a combination of study designs and was further limited by heterogeneity in individual technologies and settings in which they were implemented.

CONCLUSIONS

There is evidence that the right eTools in the right environment and context can significantly impact health services utilization. However, the findings from this evidence-based analysis raise doubts about the ability of eTools with care-coordination capabilities to independently improve the quality of outpatient care. While eTools may be able to support and sustain processes, inefficiencies embedded in the health care system may require more than automation alone to resolve.

PLAIN LANGUAGE SUMMARY

Patients with chronic diseases often work with many different health care providers. To ensure smooth transitions from one setting to the next, health care providers must share information and coordinate care effectively. Electronic medical records (eTools) are being used more and more to coordinate patient care, but it is not yet known whether they are more effective than paper-based health records. In this analysis, we reviewed the evidence for the use of eTools to exchange information and coordinate care for people with chronic diseases in the community. There was some evidence that eTools reduced the number of hospital and emergency department visits, as well as patients' length of stay in the hospital, but there was no evidence that eTools improved the overall quality of patient care.

Optimizing chronic disease management mega-analysis: economic evaluation

BACKGROUND

As Ontario's population ages, chronic diseases are becoming increasingly common. There is growing interest in services and care models designed to optimize the management of chronic disease.

OBJECTIVE

To evaluate the cost-effectiveness and expected budget impact of interventions in chronic disease cohorts evaluated as part of the Optimizing Chronic Disease Management mega-analysis.

DATA SOURCES

Sector-specific costs, disease incidence, and mortality were calculated for each condition using administrative databases from the Institute for Clinical Evaluative Sciences. Intervention outcomes were based on literature identified in the evidence-based analyses. Quality-of-life and disease prevalence data were obtained from the literature.

METHODS

Analyses were restricted to interventions that showed significant benefit for resource use or mortality from the evidence-based analyses. An Ontario cohort of patients with each chronic disease was constructed and followed over 5 years (2006-2011). A phase-based approach was used to estimate costs across all sectors of the health care system. Utility values identified in the literature and effect estimates for resource use and mortality obtained from the evidence-based analyses were applied to calculate incremental costs and quality-adjusted life-years (QALYs). Given uncertainty about how many patients would benefit from each intervention, a system-wide budget impact was not determined. Instead, the difference in lifetime cost between an individual-administered intervention and no intervention was presented.

RESULTS

Of 70 potential cost-effectiveness analyses, 8 met our inclusion criteria. All were found to result in QALY gains and cost savings compared with usual care. The models were robust to the majority of sensitivity analyses undertaken, but due to structural limitations and time constraints, few sensitivity analyses were conducted. Incremental cost savings per patient who received intervention ranged between $15 per diabetic patient with specialized nursing to $10,665 per patient wth congestive heart failure receiving in-home care.

LIMITATIONS

Evidence used to inform estimates of effect was often limited to a single trial with limited generalizability across populations, interventions, and health care systems. Because of the low clinical fidelity of health administrative data sets, intermediate clinical outcomes could not be included. Cohort costs included an average of all health care costs and were not restricted to costs associated with the disease. Intervention costs were based on resource use specified in clinical trials.

CONCLUSIONS

Applying estimates of effect from the evidence-based analyses to real-world resource use resulted in cost savings for all interventions. On the basis of quality-of-life data identified in the literature, all interventions were found to result in a greater QALY gain than usual care would. Implementation of all interventions could offer significant cost reductions. However, this analysis was subject to important limitations.

PLAIN LANGUAGE SUMMARY

Chronic diseases are the leading cause of death and disability in Ontario. They account for a third of direct health care costs across the province. This study aims to evaluate the cost-effectiveness of health care interventions that might improve the management of chronic diseases. The evaluated interventions led to lower costs and better quality of life than usual care. Offering these options could reduce costs per patient. However, the studies used in this analysis were of medium to very low quality, and the methods had many limitations.

A typology of electronic health record workarounds in small-to-medium size primary care practices

OBJECTIVE

Electronic health record (EHR) use in ambulatory care can improve safety and quality; however, problems with design, implementation, and poor interface with other systems lead users to develop 'workarounds', or behaviors users adopt to overcome perceived limitations in a technical system. We documented workarounds used in independent, community-based primary care practices, and developed a typology of their key features.

MATERIALS AND METHODS

Comparative case study of EHR use in seven independent primary care practices. Field researchers spent approximately 1 month in each practice to observe EHR use, conduct patient pathways, and interview clinicians and staff.

RESULTS

We observed workarounds addressing a wide range of EHR-related problems, including: user interface issues (eg, insufficient data fields, limited templates), barriers to electronic health information exchange with external organizations, and struggles incorporating new technologies into existing office space. We analyzed the observed workarounds inductively to develop a typology that cuts across specific clinical or administrative processes to highlight the following key formal features of workarounds in general: temporary/routinized, which captures whether the workaround is taken for granted as part of daily workflow or is understood as a short-term solution; avoidable/unavoidable, referring to the extent to which the workaround is within the practice's power to eliminate; and deliberately chosen/unplanned, which differentiates strategically chosen adaptations from less thoughtful workarounds.

CONCLUSIONS

This workaround typology provides a framework for EHR users to identify and address workarounds in their own practices, and for researchers to examine the effect of different types of EHR workarounds on patient safety, care quality, and efficiency.

Electronic medical record features and seven quality of care measures in physician offices

The effect of electronic medical records (EMRs) on quality of care in physicians' offices is uncertain. This study used the 2008-2009 National Ambulatory Medical Care Survey to examine the relationship between EMRs features and quality in physician offices. The relationship between selected EMRs features and 7 quality measures was evaluated by testing 25 associations in multivariate models. Significant relationships include reminders for guideline-based interventions or screening tests associated with lower odds of inappropriate urinalysis and prescription of antibiotics for upper respiratory infection (URI), prescription order entry associated with lower odds of prescription of antibiotics for URI, and patient problem list associated with higher odds of inappropriate prescribing for elderly patients. EMRs system level was associated with lower odds of blood pressure check, inappropriate urinalysis, and prescription of antibiotics for URI compared with no EMRs. The results show both positive and inverse relationships between EMRs features and quality of care.

Diabetes prevention, health information technology, and meaningful use: challenges and opportunities

The U.S. health system has historically been poorly equipped to confront the growing impact of diabetes on the nation's health. The Affordable Care Act legislates a number of new strategies--such as innovative payment and delivery models and increased public health funding--intended to improve diabetes prevention and care quality. Health information technology (IT) is often cited as a critical part of these strategies. Through the Health Information Technology for Economic and Clinical Health (HITECH) Act of 2009, the federal government has been supporting the rapid adoption of health IT, and more specifically of electronic health records (EHRs) through the Centers for Medicare and Medicaid Services (CMS) EHR Incentive Program. Health IT has the potential to contribute to diabetes prevention and improved quality of care, but the evidence supporting its benefits is mixed. This article provides a brief overview of the CMS EHR Incentive Program and meaningful-use criteria. Then it examines health IT strategies for diabetes prevention in the context of current evidence and identifies areas of needed research and innovation.

The effects of on-screen, point of care computer reminders on processes and outcomes of care

BACKGROUND

The opportunity to improve care by delivering decision support to clinicians at the point of care represents one of the main incentives for implementing sophisticated clinical information systems. Previous reviews of computer reminder and decision support systems have reported mixed effects, possibly because they did not distinguish point of care computer reminders from e-mail alerts, computer-generated paper reminders, and other modes of delivering 'computer reminders'.

OBJECTIVES

To evaluate the effects on processes and outcomes of care attributable to on-screen computer reminders delivered to clinicians at the point of care.

SEARCH STRATEGY

We searched the Cochrane EPOC Group Trials register, MEDLINE, EMBASE and CINAHL and CENTRAL to July 2008, and scanned bibliographies from key articles.

SELECTION CRITERIA

Studies of a reminder delivered via a computer system routinely used by clinicians, with a randomised or quasi-randomised design and reporting at least one outcome involving a clinical endpoint or adherence to a recommended process of care.

DATA COLLECTION AND ANALYSIS

Two authors independently screened studies for eligibility and abstracted data. For each study, we calculated the median improvement in adherence to target processes of care and also identified the outcome with the largest such improvement. We then calculated the median absolute improvement in process adherence across all studies using both the median outcome from each study and the best outcome.

MAIN RESULTS

Twenty-eight studies (reporting a total of thirty-two comparisons) were included. Computer reminders achieved a median improvement in process adherence of 4.2% (interquartile range (IQR): 0.8% to 18.8%) across all reported process outcomes, 3.3% (IQR: 0.5% to 10.6%) for medication ordering, 3.8% (IQR: 0.5% to 6.6%) for vaccinations, and 3.8% (IQR: 0.4% to 16.3%) for test ordering. In a sensitivity analysis using the best outcome from each study, the median improvement was 5.6% (IQR: 2.0% to 19.2%) across all process measures and 6.2% (IQR: 3.0% to 28.0%) across measures of medication ordering. In the eight comparisons that reported dichotomous clinical endpoints, intervention patients experienced a median absolute improvement of 2.5% (IQR: 1.3% to 4.2%). Blood pressure was the most commonly reported clinical endpoint, with intervention patients experiencing a median reduction in their systolic blood pressure of 1.0 mmHg (IQR: 2.3 mmHg reduction to 2.0 mmHg increase).

AUTHORS' CONCLUSIONS

Point of care computer reminders generally achieve small to modest improvements in provider behaviour. A minority of interventions showed larger effects, but no specific reminder or contextual features were significantly associated with effect magnitude. Further research must identify design features and contextual factors consistently associated with larger improvements in provider behaviour if computer reminders are to succeed on more than a trial and error basis.