Variation in electronic health record adoption and readiness for meaningful use: 2008-2011

Predicting pressure injury risk in hospitalised patients using machine learning with electronic health records: a US multilevel cohort study

OBJECTIVE

To predict the risk of hospital-acquired pressure injury using machine learning compared with standard care.

DESIGN

We obtained electronic health records (EHRs) to structure a multilevel cohort of hospitalised patients at risk for pressure injury and then calibrate a machine learning model to predict future pressure injury risk. Optimisation methods combined with multilevel logistic regression were used to develop a predictive algorithm of patient-specific shifts in risk over time. Machine learning methods were tested, including random forests, to identify predictive features for the algorithm. We reported the results of the regression approach as well as the area under the receiver operating characteristics (ROC) curve for predictive models.

SETTING

Hospitalised inpatients.

PARTICIPANTS

EHRs of 35 001 hospitalisations over 5 years across 2 academic hospitals.

MAIN OUTCOME MEASURE

Longitudinal shifts in pressure injury risk.

RESULTS

The predictive algorithm with features generated by machine learning achieved significantly improved prediction of pressure injury risk (p<0.001) with an area under the ROC curve of 0.72; whereas standard care only achieved an area under the ROC curve of 0.52. At a specificity of 0.50, the predictive algorithm achieved a sensitivity of 0.75.

CONCLUSIONS

These data could help hospitals conserve resources within a critical period of patient vulnerability of hospital-acquired pressure injury which is not reimbursed by US Medicare; thus, conserving between 30 000 and 90 000 labour-hours per year in an average 500-bed hospital. Hospitals can use this predictive algorithm to initiate a quality improvement programme for pressure injury prevention and further customise the algorithm to patient-specific variation by facility.

Digital technology, tele-medicine and artificial intelligence in ophthalmology: A global perspective

The simultaneous maturation of multiple digital and telecommunications technologies in 2020 has created an unprecedented opportunity for ophthalmology to adapt to new models of care using tele-health supported by digital innovations. These digital innovations include artificial intelligence (AI), 5th generation (5G) telecommunication networks and the Internet of Things (IoT), creating an inter-dependent ecosystem offering opportunities to develop new models of eye care addressing the challenges of COVID-19 and beyond. Ophthalmology has thrived in some of these areas partly due to its many image-based investigations. Tele-health and AI provide synchronous solutions to challenges facing ophthalmologists and healthcare providers worldwide. This article reviews how countries across the world have utilised these digital innovations to tackle diabetic retinopathy, retinopathy of prematurity, age-related macular degeneration, glaucoma, refractive error correction, cataract and other anterior segment disorders. The review summarises the digital strategies that countries are developing and discusses technologies that may increasingly enter the clinical workflow and processes of ophthalmologists. Furthermore as countries around the world have initiated a series of escalating containment and mitigation measures during the COVID-19 pandemic, the delivery of eye care services globally has been significantly impacted. As ophthalmic services adapt and form a "new normal", the rapid adoption of some of telehealth and digital innovation during the pandemic is also discussed. Finally, challenges for validation and clinical implementation are considered, as well as recommendations on future directions.

Capturing the Impact of Patient Portals Based on the Quadruple Aim and Benefits Evaluation Frameworks: Scoping Review

Background

Despite extensive and continuing research in the area of patient portals, measuring the impact of patient portals remains a convoluted process.

Objective

This study aims to explore what is known about patient portal evaluations and to provide recommendations for future endeavors. The focus is on mapping the measures used to assess the impact of patient portals on the dimensions of the Quadruple Aim (QA) framework and the Canada Health Infoway’s Benefits Evaluation (BE) framework.

Methods

A scoping review was conducted using the methodological framework of Arksey and O’Malley. Reporting was guided by the PRISMA (Preferred Reporting Items for Systematic reviews and Meta-Analyses) extension for scoping reviews. A systematic and comprehensive search was conducted using the Ovid platform, and the following databases were searched: Ovid MEDLINE (R) ALL (including epub ahead of print, in-process, and other nonindexed citations), EMBASE, and PsycINFO. CINAHL on the EBSCO platform and Web of Science were searched for studies published between March 2015 and June 2020. A systematic gray literature search was conducted using the Google search engine. Extracted data were tabulated based on a coding template developed to categorize the literature into themes and areas of interest.

Results

A total of 96 studies were included for data extraction. The studies were categorized based on the QA dimensions, with strict adherence to the definitions for each dimension. From the patients’ perspective, it was determined that most evaluations focused on benefits and barriers to access, access to test results, medication adherence, condition management, medical notes, and secure messaging. From the population perspective, the evaluations focused on the increase in population outreach, decrease in disparities related to access to care services, and improvement in quality of care. From the health care workforce perspective, the evaluations focused on the impact of patients accessing medical records, impact on workflow, impact of bidirectional secure messaging, and virtual care. From the health system perspective, the evaluations focused on decreases in no-show appointments, impact on office visits and telephone calls, impact on admission and readmission rates and emergency department visits, and impact on health care use. Overall, 77 peer-reviewed studies were mapped on the expanded version of the BE framework. The mapping was performed using subdimensions to create a more precise representation of the areas that are currently explored when studying patient portals. Most of the studies evaluated more than one subdimension.

Conclusions

The QA and BE frameworks provide guidance in identifying gaps in the current literature by providing a way to show how an impact was assessed. This study highlights the need to appropriately plan how the impact will be assessed and how the findings will be translated into effective adaptations.

Going digital: a checklist in preparing for hospital-wide electronic medical record implementation and digital transformation

Objective In an era of rapid digitisation of Australian hospitals, practical guidance is needed in how to successfully implement electronic medical records (EMRs) as both a technical innovation and a major transformative change in clinical care. The aim of the present study was to develop a checklist that clearly and comprehensively defines the steps that best prepare hospitals for EMR implementation and digital transformation. Methods The checklist was developed using a formal methodological framework comprised of: literature reviews of relevant issues; an interactive workshop involving a multidisciplinary group of digital leads from Queensland hospitals; a draft document based on literature and workshop proceedings; and a review and feedback from senior clinical leads. Results The final checklist comprised 19 questions, 13 related to EMR implementation and six to digital transformation. Questions related to the former included organisational considerations (leadership, governance, change leaders, implementation plan), technical considerations (vendor choice, information technology and project management teams, system and hardware alignment with clinician workflows, interoperability with legacy systems) and training (user training, post-go-live contingency plans, roll-out sequence, staff support at point of care). Questions related to digital transformation included cultural considerations (clinically focused vision statement and communication strategy, readiness for change surveys), management of digital disruption syndromes and plans for further improvement in patient care (post-go-live optimisation of digital system, quality and benefit evaluation, ongoing digital innovation). Conclusion This evidence-based, field-tested checklist provides guidance to hospitals planning EMR implementation and separates readiness for EMR from readiness for digital transformation. What is known about the topic? Many hospitals throughout Australia have implemented, or are planning to implement, hospital wide electronic medical records (EMRs) with varying degrees of functionality. Few hospitals have implemented a complete end-to-end digital system with the ability to bring about major transformation in clinical care. Although the many challenges in implementing EMRs have been well documented, they have not been incorporated into an evidence-based, field-tested checklist that can practically assist hospitals in preparing for EMR implementation as both a technical innovation and a vehicle for major digital transformation of care. What does this paper add? This paper outlines a 19-question checklist that was developed using a formal methodological framework comprising literature review of relevant issues, proceedings from an interactive workshop involving a multidisciplinary group of digital leads from hospitals throughout Queensland, including three hospitals undertaking EMR implementation and one hospital with complete end-to-end EMR, and review of a draft checklist by senior clinical leads within a statewide digital healthcare improvement network. The checklist distinguishes between issues pertaining to EMR as a technical innovation and EMR as a vehicle for digital transformation of patient care. What are the implications for practitioners? Successful implementation of a hospital-wide EMR requires senior managers, clinical leads, information technology teams and project management teams to fully address key operational and strategic issues. Using an issues checklist may help prevent any one issue being inadvertently overlooked or underemphasised in the planning and implementation stages, and ensure the EMR is fully adopted and optimally used by clinician users in an ongoing digital transformation of care.

Can structured EHR data support clinical coding? A data mining approach

Structured data formats are gaining momentum in electronic health records and can be leveraged for decision support and research. Nevertheless, such structured data formats have not been explored for clinical coding, which is an essential process requiring significant manual workload in health organisations. This article explores the extent to which fully structured clinical data can support assignment of clinical codes to inpatient episodes, through a methodology that tackles high dimensionality issues, addresses the multi-label nature of coding and optimises model parameters. The methodology encompasses transformation of raw data to define a feature set, build a data matrix representation, and testing combinations of feature selection methods with machine learning models to predict code assignment. The methodology was tested with a real hospital dataset and showed varying predictive power across codes, while demonstrating the potential of leveraging structuring data to reduce workload and increase efficiency in clinical coding.

Health information technology:Fallacies and Sober realities - Redux A homage to Bentzi Karsh and Robert Wears

Since the publication of "Health Information Technology: Fallacies and Sober Realities" in 2010, health information technology (HIT) has become nearly ubiquitous in US healthcare facilities. Yet, HIT has yet to achieve its putative benefits of higher quality, safer, and lower cost care. There has been variable but largely marginal progress at addressing the 12 HIT fallacies delineated in the original paper. Here, we revisit several of the original fallacies and add five new ones. These fallacies must be understood and addressed by all stakeholders for HIT to be a positive force in achieving the high value healthcare system the nation deserves. Foundational cognitive and human factors engineering research and development continue to be essential to HIT development, deployment, and use.

Medicare Incentive Payments to United States Ophthalmologists for Use of Electronic Health Records: 2011-2016

PURPOSE

To investigate ophthalmologists' rate of attestation to meaningful use (MU) of their electronic health record (EHR) systems in the Medicare EHR Incentive Program and their continuity and success in receiving payments in comparison with other specialties.

DESIGN

Administrative database study.

PARTICIPANTS

Eligible professionals participating in the Medicare EHR Incentive Program.

METHODS

Based on publicly available data sources, subsets of payment and attestation data were created for ophthalmologists and for other specialties. The number of eligible professionals attesting was determined using the attestation data for each year and stage of the program. The proportion of attestations by EHR vendor was calculated using all attestations for each vendor.

MAIN OUTCOME MEASURES

Numbers of ophthalmologists attesting by year and stage of the Medicare EHR Incentive Program, incentive payments, and number of attestations by EHR vendor.

RESULTS

In the peak year of participation, 51.6% of ophthalmologists successfully attested to MU, compared with 37.1% of optometrists, 50.2% of dermatologists, 54.5% of otolaryngologists, and 64.4% of urologists. Across the 6 years of the program, ophthalmologists received an average of $17 942 in incentive payments compared with $11 105 for optometrists, $16 617 for dermatologists, $20 203 for otolaryngologists, and $23 821 for urologists. Epic and Nextgen were the most frequently used EHRs for attestation by ophthalmologists.

CONCLUSIONS

Ophthalmology as a specialty performed better than optometry and dermatology, but worse than otolaryngology and urology, in terms of the proportion of eligible professionals attesting to MU of EHRs. Ophthalmologists were more likely to remain in the program after their initial year of attestation compared with all eligible providers. The top 4 EHR vendors accounted for 50% of attestations by ophthalmologists.

Using the consolidated framework for implementation research to understand safety net health system efforts to increase colorectal cancer screening rates

Guided by the Consolidated Framework for Implementation Research (CFIR), this study aimed to identify factors that influence implementation of evidence-based provider and client-oriented strategies to promote colorectal cancer (CRC) screening in safety net health systems. Site visits and key informant interviews (n=33) were conducted with project leaders and staff in five health systems funded by an American Cancer Society grants program. Within- and cross-site analyses identified CFIR constructs that influenced implementation of provider and client-oriented strategies to promote CRC screening through colonoscopies and fecal immunochemical tests. Of the five CFIR domains, constructs within four CFIR domains (inner setting, outer setting, individual characteristics and process domains) were particularly salient in discussions of implementation while constructs within one CFIR domain (characteristics of the intervention) were not. This study provides a detailed description of how facilitating and inhibiting factors influenced the implementation of evidence-based practices related to CRC screening within safety net health systems. These findings can inform future efforts to promote evidence-based strategies to increase CRC screening rates in safety net health systems.

Using Health IT to Coordinate Care and Improve Quality in Safety-Net Clinics

BACKGROUND

Health centers provide care to vulnerable and high-need populations. Recent investments have promoted use of health information technology (HIT) capabilities for improving care coordination and quality of care in health centers. This study examined factors associated with use of these HIT capabilities and the association between these capabilities and quality of care in a census of health centers in the United States.

METHODS

Cross-sectional secondary data from the 2015 Health Resources and Services Administration's Uniform Data System was used to examine 6 measures of HIT capability related to care coordination and clinical decision support and 16 measures of quality (12 process measures, 3 outcome measures, 1 composite measure) for health centers in the United States. Adjusted logistic regressions were used to examine health center characteristics associated with use of HIT capabilities, and adjusted linear regressions were used to examine associations between HIT capabilities and quality of care.

RESULTS

Many health centers reported using HIT for care coordination activities, including coordinating enabling services (67.3%) or engaging patients (81.0%). Health center size and medical home recognition were associated with significantly greater odds of using HIT for enabling services and engaging patients. These HIT capabilities were associated with higher overall quality and higher rates of six process measures (adult screening and maternal and child health) and hemoglobin A1c control.

CONCLUSION

Use of HIT for such activities as arranging enabling services and engaging patients are underleveraged tools for care coordination. There may be opportunities to further improve quality of care for vulnerable patients by promoting health centers' use of these HIT capabilities.

Errors in Electronic Health Record-Based Data Query of Statin Prescriptions in Patients With Coronary Artery Disease in a Large, Academic, Multispecialty Clinic Practice

BACKGROUND

With the recent implementation of the Medicare Quality Payment Program, providers face increasing accountability for delivering high-quality care. Such pay-for-performance programs aim to leverage systematic data captured by electronic health record (EHR) systems to measure performance; however, the fidelity of EHR query for assessing performance has not been validated compared with manual chart review. We sought to determine whether our institution's methodology of EHR query could accurately identify cases in which providers failed to prescribe statins for eligible patients with coronary artery disease.

METHODS AND RESULTS

A total of 9459 patients with coronary artery disease were seen at least twice at the Emory Clinic between July 2014 and June 2015, of whom 1338 (14.1%, 95% confidence interval 13.5-14.9%) had no statin prescription or exemption per EHR query. A total of 120 patient cases were randomly selected and reviewed by 2 physicians for further adjudication. Of the 120 cases initially classified as statin prescription failures, only 21 (17.5%; 95% confidence interval, 11.7-25.3%) represented true failure following physician review.

CONCLUSIONS

Sole reliance on EHR data query to measure quality metrics may lead to significant errors in assessing provider performance. Institutions should be cognizant of these potential sources of error, provide support to medical providers, and form collaborative data management teams to promote and improve meaningful use of EHRs. We propose actionable steps to improve the accuracy of EHR data query that require hypothesis testing and prospective validation in future studies.

Comparison of Health Information Technology Use Between American Adults With and Without Chronic Health Conditions: Findings From The National Health Interview Survey 2012

BACKGROUND

Health information technology (HIT) is utilized by people with different chronic conditions such as diabetes and hypertension. However, there has been no comparison of HIT use between persons without a chronic condition, with one chronic condition, and multiple (≥2) chronic conditions (MCCs).

OBJECTIVE

The aim of the study was to assess the difference in HIT use between persons without a chronic condition, with one chronic condition, and with MCCs, to describe the characteristics of HIT use among those with chronic conditions and to identify the predictors of HIT use of the persons with one chronic condition and MCCs.

METHODS

A secondary data analysis was conducted in spring 2017 using the National Health Interview Survey (NHIS) 2012 Family Core and Sample Adult Core datasets that yielded 34,525 respondents aged 18 years and older. Measures included overall HIT use (ie, any use of the following five HIT on the Internet: seeking health information, ordering prescription, making appointment, emailing health provider, and using health chat groups), as well as sociodemographic and health-related characteristics. Sociodemographic and health characteristics were compared between HIT users and nonusers among those who reported having at least one chronic condition using chi-square tests. Independent predictors of HIT use were identified using multiple logistic regression analyses for those with one chronic condition, with MCCs, and without a chronic condition. Analyses were weighted and performed at significance level of .005.

RESULTS

In 2012, adults with one health chronic condition (raw count 4147/8551, weighted percentage 48.54%) was significantly higher than among those with MCCs (3816/9637, 39.55%) and those with none of chronic condition (7254/16,337, 44.40%, P<.001). Seeking health information was the most prevalent HIT use. Chi-square tests revealed that among adults with chronic conditions, those who used HIT were significantly different from their counterpart peers who did not use HIT in terms of sociodemographic and health characteristics (P<.001). Overall, the significant factors related to HIT use were similar among the adults with one chronic condition, with MCCs, or without a chronic condition: younger age, female sex, non-Hispanic white, higher education level, and higher income level were shown to be positively related to the HIT use.

CONCLUSIONS

This study provides a snapshot of HIT use among those with chronic conditions and potential factors related to such use. Clinical care and public health communication efforts attempting to leverage more HIT use should acknowledge differential HIT usage as identified in this study to better address communication inequalities and persistent disparities in socioeconomic status.

EMR-Radiological Phenotypes in Diseases of the Optic Nerve and their Association with Visual Function

Multi-modal analyses of diseases of the optic nerve, that combine radiological imaging with other electronic medical records (EMR), improve understanding of visual function. We conducted a study of 55 patients with glaucoma and 32 patients with thyroid eye disease (TED). We collected their visual assessments, orbital CT imaging, and EMR data. We developed an image-processing pipeline that segmented and extracted structural metrics from CT images. We derive EMR phenotype vectors with the help of PheWAS (from diagnostic codes) and ProWAS (from treatment codes). Next, we performed a principal component analysis and multiple-correspondence analysis to identify their association with visual function scores. We find that structural metrics derived from CT imaging are significantly associated with functional visual score for both glaucoma (R²=0.32) and TED (R²=0.4). Addition of EMR phenotype vectors to the model significantly improved (p<1E-04) the R² to 0.4 for glaucoma and 0.54 for TED.

Health Information Technology (HIT) Adaptation: Refocusing on the Journey to Successful HIT Implementation

In past years, policies and regulations required hospitals to implement advanced capabilities of certified electronic health records (EHRs) in order to receive financial incentives. This has led to accelerated implementation of health information technologies (HIT) in health care settings. However, measures commonly used to evaluate the success of HIT implementation, such as HIT adoption, technology acceptance, and clinical quality, fail to account for complex sociotechnical variability across contexts and the different trajectories within organizations because of different implementation plans and timelines. We propose a new focus, HIT adaptation, to illuminate factors that facilitate or hinder the connection between use of the EHR and improved quality of care as well as to explore the trajectory of changes in the HIT implementation journey as it is impacted by frequent system upgrades and optimizations. Future research should develop instruments to evaluate the progress of HIT adaptation in both its longitudinal design and its focus on adaptation progress rather than on one cross-sectional outcome, allowing for more generalizability and knowledge transfer.

DQe-v: A Database-Agnostic Framework for Exploring Variability in Electronic Health Record Data Across Time and Site Location

Data variability is a commonly observed phenomenon in Electronic Health Records (EHR) data networks. A common question asked in scientific investigations of EHR data is whether the cross-site and -time variability reflects an underlying data quality error at one or more contributing sites versus actual differences driven by various idiosyncrasies in the healthcare settings. Although research analysts and data scientists have commonly used various statistical methods to detect and account for variability in analytic datasets, self service tools to facilitate exploring cross-organizational variability in EHR data warehouses are lacking and could benefit from meaningful data visualizations. DQ^e-v, an interactive, database-agnostic tool for visually exploring variability in EHR data provides such a solution. DQ^e-v is built on an open source platform, R statistical software, with annotated scripts and a readme document that makes it fully reproducible. To illustrate and describe functionality of DQ^e-v, we describe the DQ^e-v’s readme document which includes a complete guide to installation, running the program, and interpretation of the outputs. We also provide annotated R scripts and an example dataset as supplemental materials. DQ^e-v offers a self service tool to visually explore data variability within EHR datasets irrespective of the data model. GitHub and CIELO offer hosting and distribution of the tool and can facilitate collaboration across any interested community of users as we target improving usability, efficiency, and interoperability.

An Approach to Acquiring, Normalizing, and Managing EHR Data From a Clinical Data Repository for Studying Pressure Ulcer Outcomes

Changes in the methods that individual facilities follow to collect and store data related to hospital-acquired pressure ulcer (HAPU) occurrences are essential for improving patient outcomes and advancing our understanding the science behind this clinically relevant issue. Using an established electronic health record system at a large, urban, tertiary-care academic medical center, we investigated the process required for taking raw data of HAPU outcomes and submitting these data to a normalization process. We extracted data from 1.5 million patient shifts and filtered observations to those with a Braden score and linked tables in the electronic health record, including (1) Braden scale scores, (2) laboratory outcomes data, (3) surgical time, (4) provider orders, (5) medications, and (6) discharge diagnoses. Braden scores are important measures specific to HAPUs since these scores clarify the daily risk of a hospitalized patient for developing a pressure ulcer. The other more common measures that may be associated with HAPU outcomes are important to organize in a single data frame with Braden scores according to each patient. Primary keys were assigned to each table, and the data were processed through 3 normalization steps and 1 denormalization step. These processes created 8 tables that can be stored efficiently in a clinical database of HAPU outcomes. As hospitals focus on organizing data for review of HAPUs and other types of hospital-acquired conditions, the normalization process we describe in this article offers directions for collaboration between providers and informatics teams using a common language and structure.

Overcoming the Challenges of Unstructured Data in Multisite, Electronic Medical Record-based Abstraction

BACKGROUND

Unstructured data encountered during retrospective electronic medical record (EMR) abstraction has routinely been identified as challenging to reliably abstract, as these data are often recorded as free text, without limitations to format or structure. There is increased interest in reliably abstracting this type of data given its prominent role in care coordination and communication, yet limited methodological guidance exists.

OBJECTIVES

As standard abstraction approaches resulted in substandard data reliability for unstructured data elements collected as part of a multisite, retrospective EMR study of hospital discharge communication quality, our goal was to develop, apply and examine the utility of a phase-based approach to reliably abstract unstructured data. This approach is examined using the specific example of discharge communication for warfarin management.

RESEARCH DESIGN

We adopted a "fit-for-use" framework to guide the development and evaluation of abstraction methods using a 4-step, phase-based approach including (1) team building; (2) identification of challenges; (3) adaptation of abstraction methods; and (4) systematic data quality monitoring.

MEASURES

Unstructured data elements were the focus of this study, including elements communicating steps in warfarin management (eg, warfarin initiation) and medical follow-up (eg, timeframe for follow-up).

RESULTS

After implementation of the phase-based approach, interrater reliability for all unstructured data elements demonstrated κ's of ≥0.89-an average increase of +0.25 for each unstructured data element.

CONCLUSIONS

As compared with standard abstraction methodologies, this phase-based approach was more time intensive, but did markedly increase abstraction reliability for unstructured data elements within multisite EMR documentation.

Psychiatrists' Comfort Using Computers and Other Electronic Devices in Clinical Practice

This report highlights findings from the Study of Psychiatrists' Use of Informational Resources in Clinical Practice, a cross-sectional Web- and paper-based survey that examined psychiatrists' comfort using computers and other electronic devices in clinical practice. One-thousand psychiatrists were randomly selected from the American Medical Association Physician Masterfile and asked to complete the survey between May and August, 2012. A total of 152 eligible psychiatrists completed the questionnaire (response rate 22.2 %). The majority of psychiatrists reported comfort using computers for educational and personal purposes. However, 26 % of psychiatrists reported not using or not being comfortable using computers for clinical functions. Psychiatrists under age 50 were more likely to report comfort using computers for all purposes than their older counterparts. Clinical tasks for which computers were reportedly used comfortably, specifically by psychiatrists younger than 50, included documenting clinical encounters, prescribing, ordering laboratory tests, accessing read-only patient information (e.g., test results), conducting internet searches for general clinical information, accessing online patient educational materials, and communicating with patients or other clinicians. Psychiatrists generally reported comfort using computers for personal and educational purposes. However, use of computers in clinical care was less common, particularly among psychiatrists 50 and older. Information and educational resources need to be available in a variety of accessible, user-friendly, computer and non-computer-based formats, to support use across all ages. Moreover, ongoing training and technical assistance with use of electronic and mobile device technologies in clinical practice is needed. Research on barriers to clinical use of computers is warranted.

Meaningful Use of the Indian Health Service Electronic Health Record

OBJECTIVE

To understand the use of electronic health record (EHR) functionalities by physicians practicing in an underserved setting.

DATA SOURCE/STUDY SETTING

A total of 333 Indian Health Service physicians (55 percent response rate) in August 2012.

STUDY DESIGN

Cross-sectional.

DATA COLLECTION

The survey assessed routine use of EHR functionalities, perceived usefulness, and barriers to adoption.

PRINCIPAL FINDINGS

Physicians routinely used a median 7 of 10 EHR functionalities targeted by the Meaningful Use program, but only 5 percent used all 10. Most (63 percent) felt the EHR improved quality of care. Many (76 percent) reported increased documentation time and poorer quality patient-physician interactions (45 percent). Primary care specialty and time using the EHR were positively associated with use of EHR functionalities, while perceived productivity loss was negatively associated.

CONCLUSIONS

Significant opportunities exist to increase use of EHR functionalities and preserve physician-patient interactions and productivity in a resource-limited environment.

Relationship Between Clerical Burden and Characteristics of the Electronic Environment With Physician Burnout and Professional Satisfaction

OBJECTIVE

To evaluate associations between the electronic environment, clerical burden, and burnout in US physicians.

PARTICIPANTS AND METHODS

Physicians across all specialties in the United States were surveyed between August and October 2014. Physicians provided information regarding use of electronic health records (EHRs), computerized physician order entry (CPOE), and electronic patient portals. Burnout was measured using validated metrics.

RESULTS

Of 6375 responding physicians in active practice, 5389 (84.5%) reported that they used EHRs. Of 5892 physicians who indicated that CPOE was relevant to their specialty, 4858 (82.5%) reported using CPOE. Physicians who used EHRs and CPOE had lower satisfaction with the amount of time spent on clerical tasks and higher rates of burnout on univariate analysis. On multivariable analysis, physicians who used EHRs (odds ratio [OR]=0.67; 95% CI, 0.57-0.79; P<.001) or CPOE (OR=0.72; 95% CI, 0.62-0.84; P<.001) were less likely to be satisfied with the amount of time spent on clerical tasks after adjusting for age, sex, specialty, practice setting, and hours worked per week. Use of CPOE was also associated with a higher risk of burnout after adjusting for these same factors (OR=1.29; 95% CI, 1.12-1.48; P<.001). Use of EHRs was not associated with burnout in adjusted models controlling for CPOE and other factors.

CONCLUSION

In this large national study, physicians' satisfaction with their EHRs and CPOE was generally low. Physicians who used EHRs and CPOE were less satisfied with the amount of time spent on clerical tasks and were at higher risk for professional burnout.

Adoption Factors of the Electronic Health Record: A Systematic Review

Background

The Health Information Technology for Economic and Clinical Health (HITECH) was a significant piece of legislation in America that served as a catalyst for the adoption of health information technology. Following implementation of the HITECH Act, Health Information Technology (HIT) experienced broad adoption of Electronic Health Records (EHR), despite skepticism exhibited by many providers for the transition to an electronic system. A thorough review of EHR adoption facilitator and barriers provides ongoing support for the continuation of EHR implementation across various health care structures, possibly leading to a reduction in associated economic expenditures.

Objective

The purpose of this review is to compile a current and comprehensive list of facilitators and barriers to the adoption of the EHR in the United States.

Methods

Authors searched Cumulative Index of Nursing and Allied Health Literature (CINAHL) and MEDLINE, 01/01/2012–09/01/2015, core clinical/academic journals, MEDLINE full text, and evaluated only articles germane to our research objective. Team members selected a final list of articles through consensus meetings (n=31). Multiple research team members thoroughly read each article to confirm applicability and study conclusions, thereby increasing validity.

Results

Group members identified common facilitators and barriers associated with the EHR adoption process. In total, 25 adoption facilitators were identified in the literature occurring 109 times; the majority of which were efficiency, hospital size, quality, access to data, perceived value, and ability to transfer information. A total of 23 barriers to adoption were identified in the literature, appearing 95 times; the majority of which were cost, time consuming, perception of uselessness, transition of data, facility location, and implementation issues.

Conclusions

The 25 facilitators and 23 barriers to the adoption of the EHR continue to reveal a preoccupation on cost, despite incentives in the HITECH Act. Limited financial backing and outdated technology were also common barriers frequently mentioned during data review. Future public policy should include incentives commensurate with those in the HITECH Act to maintain strong adoption rates.

Building towards precision medicine: empowering medical professionals for the next revolution

A new paradigm in disease classification, diagnosis and treatment is rapidly approaching. Known as precision medicine, this new healthcare model incorporates and integrates genetic information, microbiome data, and information on patients’ environment and lifestyle to better identify and classify disease processes, and to provide custom-tailored therapeutic solutions. In spite of its promises, precision medicine faces several challenges that need to be overcome to successfully implement this new healthcare model. In this paper we identify four main areas that require attention: data, tools and systems, regulations, and people. While there are important ongoing efforts for addressing the first three areas, we argue that the human factor needs to be taken into consideration as well. In particular, we discuss several studies that show how primary care physicians and clinicians in general feel underequipped to interpret genetic tests and direct-to-consumer genomic tests. Considering the importance of genetic information for precision medicine applications, this is a pressing issue that needs to be addressed. To increase the number of professionals with the necessary expertise to correctly interpret the genomics profiles of their patients, we propose several strategies that involve medical curriculum reforms, specialist training, and ongoing physician training.

Evaluation of the patient with an exposure-related disease: the occupational and environmental history

PURPOSE OF REVIEW

Although the process of taking an occupational and environmental history has remained largely the same, the context in which it is done has changed dramatically over recent years. This review examines the role of the occupational and environmental history in the context of the changing nature of medical practice and discusses methods for evaluating patients with contemporary exposure-related respiratory illnesses.

RECENT FINDINGS

Surveillance for occupational lung disease using mnemonic devices, screening questions and the use of structured questionnaires can significantly increase the likelihood and accuracy of detection. Electronic health records likewise can be adapted to include the most important elements of the occupational and environmental history.

SUMMARY

The emergence of new technologies and industries will lead to respiratory diseases in novel occupational and environmental contexts. Using the methods described herein can make detecting these diseases easier and less time-consuming.

Variability in Electronic Health Record Usage and Perceptions among Specialty vs. Primary Care Physicians

Despite federal incentives for adoption of electronic health records (EHRs), surveys have shown that EHR use is less common among specialty physicians than generalists. Concerns have been raised that current-generation EHR systems are inadequate to meet the unique information gathering needs of specialists. This study sought to identify whether information gathering needs and EHR usage patterns are different between specialists and generalists, and if so, to characterize their precise nature. We found that specialists and generalists have significantly different perceptions of which elements of the EHR are most important and how well these systems are suited to displaying clinical information. Resolution of these disparities could have implications for clinical productivity and efficiency, patient and physician satisfaction, and the ability of clinical practices to achieve Meaningful Use incentives.

Associations Between Practice Characteristics and Demonstration of Stage 1 Meaningful Use for the Electronic Health Record Incentive Program

BACKGROUND

The Medicare and Medicaid meaningful use (MU) incentive programs promote adoption and "meaningful use" of certified electronic health records among hospitals and eligible providers in outpatient settings, with a goal of improving the quality of patient care. Despite the potential importance of MU for providers and patients, little is currently known about the practice characteristics that facilitate providers' demonstration of MU. This study examined whether selected practice characteristics were associated with providers' meeting Stage 1 MU objectives at the end of 1 year in a single large North Carolina integrated delivery system.

METHODS

Our retrospective database analysis included all 702 eligible providers from 54 ambulatory care practices on the main campus of the University of North Carolina Health Care System. We assessed associations between providers' ability to meet Stage 1 MU objectives as of December 2012 and the following practice characteristics: practice specialty, size, and mix of Medicare- and Medicaid-eligible providers.

RESULTS

The following practice characteristics were associated with providers' ability to meet MU objectives: primary care practices as compared to specialty practices (odds ratio [OR] = 2.49; 95% CI, 1.11-5.62), small practices as compared to medium-sized practices (OR = 0.29; 95% CI, 0.09-0.89), and the presence of only Medicare-eligible providers in the practice as compared to the presence of only Medicaid-eligible providers (OR = 6.48; 95% Cl, 1.08-38.97).

LIMITATIONS

Because our sample was drawn from a single integrated delivery system, results may not be generalizable to all ambulatory practice settings.

CONCLUSIONS

This study suggests that larger practices, primary care practices, and practices comprised of Medicare-eligible providers may be better able to meet MU objectives. Further research is needed to evaluate strategies that account for practice characteristics and other contextual factors in the MU implementation process.

In emergency departments, radiologists' access to EHRs may influence interpretations and medical management

The adoption of electronic health records (EHRs) that meet federal meaningful-use standards is a major US national policy priority. Policy makers recognize the potential of electronic communication in delivering high-quality health care, particularly in an environment of expanding remote access to medical care and the ever-increasing need to transmit health care records across institutions. To demonstrate this principle, we sought to estimate the significance of EHR access in emergent neuroradiologic interpretations. Three neuroradiologists conducted a prospective expert-rater analysis of 2,000 consecutive head computed tomography (CT) exams ordered by emergency department (ED) physicians. For each head CT exam, the neuroradiologists compared medical information generated by ED physicians to information generated by the interpreting radiologists who had access to additional EHR-derived patient data. In 6.1 percent of the head CT exams, the neuroradiologists reached consensus--meaning two out of three agreed--that the additional clinical data derived from the EHR was "very likely" to influence radiological interpretations and that the lack of that data would have adversely affected medical management in those patients. Health care providers must recognize the value of implementing EHRs and foster their widespread adoption.

Are family physicians comprehensively using electronic medical records such that the data can be used for secondary purposes? A Canadian perspective

Background

With the introduction and implementation of a variety of government programs and policies to encourage adoption of electronic medical records (EMRs), EMRs are being increasingly adopted in North America. We sought to evaluate the completeness of a variety of EMR fields to determine if family physicians were comprehensively using their EMRs and the suitability of use of the data for secondary purposes in Ontario, Canada.

Methods

We examined EMR data from a convenience sample of family physicians distributed throughout Ontario within the Electronic Medical Record Administrative data Linked Database (EMRALD) as extracted in the summer of 2012. We identified all physicians with at least one year of EMR use. Measures were developed and rates of physician documentation of clinical encounters, electronic prescriptions, laboratory tests, blood pressure and weight, referrals, consultation letters, and all fields in the cumulative patient profile were calculated as a function of physician and patient time since starting on the EMR.

Results

Of the 167 physicians with at least one year of EMR use, we identified 186,237 patients. Overall, the fields with the highest level of completeness were for visit documentations and prescriptions (>70 %). Improvements were observed with increasing trends of completeness overtime for almost all EMR fields according to increasing physician time on EMR. Assessment of the influence of patient time on EMR demonstrated an increasing likelihood of the population of EMR fields overtime, with the largest improvements occurring between the first and second years.

Conclusions

All of the data fields examined appear to be reasonably complete within the first year of adoption with the biggest increase occurring the first to second year. Using all of the basic functions of the EMR appears to be occurring in the current environment of EMR adoption in Ontario. Thus the data appears to be suitable for secondary use.

Point-of-Care Child Psychiatry Expertise: The Massachusetts Child Psychiatry Access Project

OBJECTIVE

Since 2005, after a pilot program, the Massachusetts Child Psychiatry Access Project (MCPAP) has provided point-of-care psychiatry expertise and referral assistance by telephone to primary care providers. We examined its adoption and use and the practice characteristics associated with different adoption timelines and use patterns.

METHODS

We merged data on calls to MCPAP in 2005 to 2011 with practice data (enrollment year, panel size, regional team assignment). We categorized practices' days from enrollment to first call (adoption) (0-100, 101-365, > 365 days) and quartile of call frequency (use) (annual highest, middle, and lowest quartiles of number of calls per 1000 empanelled patients). We determined associations between adoption and use and practice characteristics using multivariate models.

RESULTS

Among 285 practices, adoption and use varied: 55% called 0 to 100 days from enrollment and 16% called >365 days from enrollment. Practices in the highest quartile of use made a mean 15.5 calls/year per 1000 patients, whereas the lowest quartile made 0.4 calls/year per 1000 patients. Adoption within 100 days was associated with enrollment during or after 2007 (odds ratio [OR] 4.09, 95% confidence interval [CI] 2.23-7.49) and assignment to the team at the pilot site (OR 4.42, 95% CI 2.16-9.04 for central Massachusetts). Highest-quartile use was associated with team assignment (OR 3.58, 95% CI 1.86-6.87 for central Massachusetts) and panel size (OR 0.10, 95% CI 0.03-0.31 for ≥ 10,000 vs < 2000 patients).

CONCLUSIONS

Adoption and use of MCPAP varied widely. Timing of enrollment, assignment to the team from the program's pilot site, and panel size were associated with patterns of adoption and use. Findings may help other programs design effective implementation strategies.

The impact of adopting EHRs: how losing connectivity affects clinical reasoning

CONTEXT

As electronic health records (EHRs) are adopted by teaching hospitals, educators must examine how this change impacts trainee development.

OBJECTIVES

We investigate this influence by studying clinician experiences of a hospital's move from paper charts to an EHR. We ask: how does each chart modality present conceptions of time and data interconnections? How do these conceptions affect clinical reasoning?

METHODS

This two-phase, longitudinal study employed constructivist grounded theory. Data were collected at a paediatric teaching hospital before (Phase 1), during and after (Phase 2) the transition from a paper chart to an EHR system. Data collection consisted of field observations (146 hours involving 300 health care providers, 22 patients and 32 patient family members), think-aloud (n = 13) and think-after (n = 11) sessions, interviews (n = 39) and document retrieval (n = 392). Theories of rhetorical genre studies and visual rhetoric informed analysis.

RESULTS

In the paper flowsheet, clinicians recorded and viewed patient data in chronologically organised displays that emphasised data interconnections. In the EHR flowsheet, clinicians viewed and recorded individual data points that were largely chronologically and contextually isolated. Clinicians reported that this change resulted in: (i) not knowing the patient's evolving status; (ii) increased cognitive workload, and (iii) loss of clinical reasoning support mechanisms.

CONCLUSIONS

Understanding how patient data are interconnected is essential to clinical reasoning. The use of EHRs supports this goal because the EHR is a tool for collecting dispersed data; however, these collections often deconstruct data interconnections. Where the paper flowsheet emphasises chronology and interconnectedness, the EHR flowsheet emphasises individual data values that are largely independent of time and other patient data. To prepare trainees to work with EHRs, the ways of thinking and acting that were implicitly learned through the use of paper charts must be made explicit. To support clinical reasoning, medical educators should provide lessons in connectivity – the chronologically framed data interconnections upon which clinicians rely to provide patient care.

Diffusion and Use of Tethered Personal Health Records in Primary Care

BACKGROUND

Personal health records (PHRs) enable patients to access their healthcare information in a secure environment, increasing patient engagement in medical care. PHRs can be tethered to a patient's electronic health record (EHR). Tethered PHRs, also known as patient portals, allow patients to access relevant medical information from their provider. Despite recent policy efforts to promote the use of health information technology and increased availability of PHRs in the clinical setting, PHR adoption rates remain relatively low overall. This article examines physician characteristics of high vs. low PHR adopters.

OBJECTIVE

The objectives of this study were to (1) examine PHR use patterns in the primary care setting, (2) identify physician characteristics affecting PHR adoption, and (3) explore physician perspectives encouraging and deterring use.

METHODS

Information technology records provided data on primary care patient portal use at a large Midwestern academic medical center. Electronic surveys were administered to affiliated primary care physicians to measure their perceived use of patient portals. A focus group consisting of physician providers who completed the survey was used to further elucidate the trends and perceived utilization of the patient portal in the clinical setting.

RESULTS

While they expended significant time communicating with patients using the portal, physicians generally overestimated the time spent per week on the system. Physicians who had been in practice longer estimated a higher average time spent on the system when compared to newer physicians. Patient portal activation rates and use decreased with increased years in practice. During the focus groups, physicians voiced motivation to use patient portals because they perceived improved patient communication and satisfaction with use. However, continued lack of reimbursement for time spent in portal communication was reported as a major barrier to providers' engagement with this technology.

DISCUSSION

Physician endorsement and engagement is critical to achieve widespread adoption of PHRs. Such endorsement can be obtained through (1) providing rewards from health system employers for high use of PHRs, (2) providing financial reimbursement for time spent electronically communicating with patients via the PHR from federal initiatives incentivizing meaningful use of health information technology, (3) building robust support staff assistance for PHR communication into primary care workflows, and (4) integrating more PHR-specific education into providers' EHR training.

Visualizing Anomalies in Electronic Health Record Data: The Variability Explorer Tool

As Electronic Health Record (EHR) systems are becoming more prevalent in the U.S. health care domain, the utility of EHR data in translational research and clinical decision-making gains prominence. Leveraging primay· care-based. multi-clinic EHR data, this paper introduces a web-based visualization tool, the Variability Explorer Tool (VET), to assist researchers with profiling variability among diagnosis codes. VET applies a simple statistical method to approximate probability distribution functions for the prevalence of any given diagnosis codes to visualize between-clinic and across-year variability. In a depression diagnoses use case, VET outputs demonstrated substantial variability in code use. Even though data quality research often characterizes variability as an indicator for data quality, variability can also reflect real characteristics of data, such as practice-level, and patient-level issues. Researchers benefit from recognizing variability in early stages of research to improve their research design and ensure validity and generalizability of research findings.

Convergent evolution of health information management and health informatics: a perspective on the future of information professionals in health care

Clearly defined boundaries are disappearing among the activities, sources, and uses of health care data and information managed by health information management (HIM) and health informatics (HI) professionals. Definitions of the professional domains and scopes of practice for HIM and HI are converging with the proliferation of information and communication technologies in health care settings. Convergence is changing both the roles that HIM and HI professionals serve in their organizations as well as the competencies necessary for training future professionals. Many of these changes suggest a blurring of roles and responsibilities with increasingly overlapping curricula, job descriptions, and research agendas. Blurred lines in a highly competitive market create confusion for students and employers. In this essay, we provide some perspective on the changing landscape and suggest a course for the future. First we review the evolving definitions of HIM and HI. We next compare the current domains and competencies, review the characteristics as well as the education and credentialing of both disciplines, and examine areas of convergence. Given the current state, we suggest a path forward to strengthen the contributions HIM and HI professionals and educators make to the evolving health care environment.

Do family physicians electronic health records support meaningful use?

BACKGROUND

Spurred by government incentives, the use of electronic health records (EHRs) in the United States has increased; however, whether these EHRs have the functionality necessary to meet meaningful use (MU) criteria remains unknown. Our objective was to characterize family physician access to MU functionality when using a MU-certified EHR.

METHODS

Data were obtained from a convenience survey of family physicians accessing their American Board of Family Medicine online portfolio in 2011. A brief survey queried MU functionality. We used descriptive statistics to characterize the responses and bivariate statistics to test associations between MU and patient communication functions by presence of a MU-certified EHR.

RESULTS

Out of 3855 respondents, 60% reported having an EHR that supports MU. Physicians with MU-certified EHRs were more likely than physicians without MU-certified EHRs to report patient registry activities (49.7% vs. 32.3%, p-value<0.01), tracking quality measures (74.1% vs. 56.4%, p-value<0.01), access to labs or consultation notes, and electronic prescribing; but electronic communication abilities were low regardless of EHR capabilities.

CONCLUSIONS

Family physicians with MU-certified EHRs are more likely to report MU functionality; however, a sizeable minority does not report MU functions.

IMPLICATIONS

Many family physicians with MU-certified EHRs may not successfully meet the successively stringent MU criteria and may face significant upgrade costs to do so.

LEVEL OF EVIDENCE

Cross sectional survey.

Does it get easier to use an EHR? Report from an urban regional extension center

BACKGROUND

Little is known about whether more experience with an electronic health record (EHR) makes it easier for providers to meaningfully use EHRs.

OBJECTIVE

To assess whether the length of time that small practice providers have been using the EHR is associated with greater ease in performing meaningful use-related tasks and fewer EHR-related concerns.

DESIGN/PARTICIPANTS

We administered a web-based survey to 400 small practice providers in medically underserved communities in New York City participating in an EHR implementation and technical assistance project. We used logistic regression to estimate the association between the length of time a provider had been using the EHR (i.e., "live") and the ease of performing meaningful use-related tasks and EHR-related concerns, controlling for provider and practice characteristics.

KEY RESULTS

Compared to providers who had been live 6 to 12 months, providers who had been live 2 years or longer had 2.02 times greater odds of reporting it was easy to e-prescribe new prescriptions (p < 0.05), 2.12 times greater odds of reporting it was easy to e-prescribe renewal prescriptions (p < 0.05), 2.02 times greater odds of reporting that quality measures were easy to report (p < 0.05), 2.64 times greater odds of reporting it was easy to incorporate lab results as structured data (p < 0.001), and 2.00 times greater odds of reporting it was easy to generate patient lists by condition (p < 0.05). Providers who had been live 2 years or longer had 0.40 times lower odds of reporting financial costs were a concern (p < 0.001), 0.46 times lower odds of reporting that productivity loss was a concern (p < 0.05), 0.54 times lower odds of reporting that EHR unreliability was a concern (p < 0.05), and 0.50 times lower odds of reporting that privacy/security was a concern (p < 0.05).

CONCLUSIONS

Providers can successfully adjust to the EHR and over time are better able to meaningfully use the EHR.

Geographic variation in health IT and health care outcomes: A snapshot before the meaningful use incentive program began

BACKGROUND

The 2009 Health Information Technology for Economic and Clinical Health (HITECH) Act, which includes the Meaningful Use (MU) incentive program, was designed to increase the adoption of health information technology (IT) by physicians and hospitals. Policymakers hope that increased use of health IT to exchange health information will in turn enhance the quality and efficiency of health care delivery. In this study, we analyze the extent to which key outcomes vary based on the levels of health ITness among physicians and hospitals before the HITECH and MU programs led to increases in adoption and changes in use. Our findings provide an important baseline for a future evaluation of the impact of these programs on population-level outcomes.

METHODS

We constructed measures of the degree of hospital and physician adoption and use ("health ITness") at the level of the hospital referral region (HRR). We used data from the 2010 IT Supplement of the American Hospital Association (AHA) Annual Survey of Hospitals to capture hospital health ITness and data from the 2010 survey of ambulatory health care sites produced by SK&A Information Services for the physician measure. We conducted cross-sectional analyses of the relationship between market-level Medicare costs and use and three measures: (1) physician health ITness, (2) hospital health ITness, and (3) an overall measure of health ITness.

RESULTS

In general, greater levels of physician health ITness are associated with decreasing costs and use. Many of these relationships lose statistical significance, however, when we control for population and market characteristics such as the average age and health status of Medicare beneficiaries, mean household income, and the HMO penetration rate. Several of the relationships also change according to the level of hospital health ITness.

CONCLUSIONS

Our findings suggest that greater levels of physician health ITness are associated with decreasing costs and use for a number of services, including inpatient costs and stays, imaging services, and lab tests, in 2010. Our health ITness and outcomes measures are aggregated at the HRR level; as such, these results do not suggest that the adoption and use of health IT by individual physicians or hospitals leads to decreases in costs or use for their individual patients. Nevertheless, these baseline findings provide important information to be considered in future research analyzing the impact of HITECH and the MU incentives.

Health data use, stewardship, and governance: ongoing gaps and challenges: a report from AMIA's 2012 Health Policy Meeting

Large amounts of personal health data are being collected and made available through existing and emerging technological media and tools. While use of these data has significant potential to facilitate research, improve quality of care for individuals and populations, and reduce healthcare costs, many policy-related issues must be addressed before their full value can be realized. These include the need for widely agreed-on data stewardship principles and effective approaches to reduce or eliminate data silos and protect patient privacy. AMIA's 2012 Health Policy Meeting brought together healthcare academics, policy makers, and system stakeholders (including representatives of patient groups) to consider these topics and formulate recommendations. A review of a set of Proposed Principles of Health Data Use led to a set of findings and recommendations, including the assertions that the use of health data should be viewed as a public good and that achieving the broad benefits of this use will require understanding and support from patients.

Where are we on the diffusion curve? Trends and drivers of primary care physicians' use of health information technology

OBJECTIVE

To describe trends in primary care physicians' use of health information technology (HIT) between 2009 and 2012, examine practice characteristics associated with greater HIT capacity in 2012, and explore factors such as delivery system and payment reforms that may affect adoption and functionality.

DATA

We used data from the 2012 and 2009 Commonwealth Fund International Health Policy Surveys of Primary Care Physicians. The data were collected in both years by postal mail between March and July among a nationally representative sample of primary care physicians in the United States.

STUDY DESIGN

We compared primary care physicians' HIT capacity in 2009 and 2012. We employed multivariable logistic regression to analyze whether participating in an integrated delivery system, sharing resources and support with other practices, and being eligible for financial incentives were associated with greater HIT capacity in 2012.

PRINCIPAL FINDINGS

Primary care physicians' HIT capacity has significantly expanded since 2009, although solo practices continue to lag. Practices that are part of an integrated delivery system or share resources with other practices have higher rates of electronic medical record (EMR) adoption, multifunctional HIT, electronic information exchange, and electronic access for patients. Receiving or being eligible for financial incentives is associated with greater adoption of EMRs and information exchange.

CONCLUSIONS

Federal efforts to increase adoption have coincided with a rapid increase in HIT capacity. Delivery system and payment reforms and federally funded extension programs could offer promising pathways for further diffusion.

Geographic variation in ambulatory electronic health record adoption: implications for underserved communities

OBJECTIVE

To describe small area variation in ambulatory electronic health record (EHR) adoption and assess evidence of a "digital divide" in whether adoption is lagging in traditionally underserved communities.

DATA SOURCES

Survey data on U.S. ambulatory health care sites (261,973 sites representing 716,160 providers) collected by SK&A Information Services in 2011.

STUDY DESIGN

We examined cross-sectional variation in two measures of local area EHR adoption: share of providers at sites using an EHR with e-prescribing functionality; and predicted probability of EHR adoption for the average site. Local areas were defined as Public Use Microdata Areas (n = 2,068). Using multivariate regression, we examined the association between adoption and three area characteristics: high concentration of minority population; high concentration of low-income population; and metropolitan status.

PRINCIPAL FINDINGS

EHR adoption varied significantly across local areas, ranging from 8 to 88 percent with a median of 41 percent. Adoption was lower in large metropolitan areas; areas with high concentration of minority population in the Northeast and West; and areas with high concentration of low-income population in the Midwest.

CONCLUSIONS

Our 2011 estimates suggest there was substantial room for increased EHR adoption across the United States, including some underserved areas with relatively low EHR adoption rates. Further research should monitor policy initiatives in these areas and examine sources of heterogeneity in low- and high-adoption communities.

An informatics approach to medication adherence assessment and improvement using clinical, billing, and patient-entered data

The aim of this study was to describe an integrated informatics approach to aggregating and displaying clinically relevant data that can identify problems with medication adherence and facilitate patient-provider communication about strategies to improve medication use. We developed a clinical dashboard within an electronic health record (EHR) system that uses data from three sources: the medical record, pharmacy claims, and a personal health record. The data are integrated to inform clinician-patient discussions about medication adherence. Whereas prior research on assessing patterns of medication adherence focused on a single approach using the EHR, pharmacy data, or patient-entered data, we present an approach that integrates multiple electronic data sources increasingly found in practice. Medication adherence is a complex challenge that requires patient and provider team input, necessitating an integrated approach using advanced EHR, clinical decision support, and patient-controlled technologies. Future research should focus on integrated strategies to provide patients and providers with the right combination of informatics tools to help them adequately address the challenge of adherence to complex medication therapies.

Electronic medical records and physician stress in primary care: results from the MEMO Study

BACKGROUND

Little has been written about physician stress that may be associated with electronic medical records (EMR).

OBJECTIVE

We assessed relationships between the number of EMR functions, primary care work conditions, and physician satisfaction, stress and burnout.

DESIGN AND PARTICIPANTS

379 primary care physicians and 92 managers at 92 clinics from New York City and the upper Midwest participating in the 2001-5 Minimizing Error, Maximizing Outcome (MEMO) Study. A latent class analysis identified clusters of physicians within clinics with low, medium and high EMR functions.

MAIN MEASURES

We assessed physician-reported stress, burnout, satisfaction, and intent to leave the practice, and predictors including time pressure during visits. We used a two-level regression model to estimate the mean response for each physician cluster to each outcome, adjusting for physician age, sex, specialty, work hours and years using the EMR. Effect sizes (ES) of these relationships were considered small (0.14), moderate (0.39), and large (0.61).

KEY RESULTS

Compared to the low EMR cluster, physicians in the moderate EMR cluster reported more stress (ES 0.35, p=0.03) and lower satisfaction (ES -0.45, p=0.006). Physicians in the high EMR cluster indicated lower satisfaction than low EMR cluster physicians (ES -0.39, p=0.01). Time pressure was associated with significantly more burnout, dissatisfaction and intent to leave only within the high EMR cluster.

CONCLUSIONS

Stress may rise for physicians with a moderate number of EMR functions. Time pressure was associated with poor physician outcomes mainly in the high EMR cluster. Work redesign may address these stressors.