Emerging landscape of genomics in the Electronic Health Record for personalized medicine

The Information Technology (IT) roadmap for personalized medicine requires Electronic Health Records (EHRs), extension of Healthcare IT (HIT) standards, and understanding of how genetics/genomics should be integrated into the clinical applications. For reduced overall costs and development times, these three initiatives should run in parallel. EHRs must contain structured data and infrastructure that enables quality analysis, Clinical Decision Support (CDS) and messaging within the healthcare information network. Fortunately, as a result of sustained financial commitment to nongenetic-based healthcare, the industry has HIT data standards and understanding of EHR functionality that improves patient safety and outcomes while reducing overall healthcare costs. However, the HIT standards and EHR functional requirements, needed for personalized medicine, are only beginning to support simple genetic tests and need significant extension. In addition, our understanding of the clinical implications of genomic data is evolving and translation of new discovery into clinical care remains a challenge. Therefore, priority areas include CDS, educational resources, and knowledgebases for the EHR, clinical and research data warehouses, messaging frameworks, and continued review of healthcare policies and regulations supporting personalized medicine. Where core infrastructure remains to be developed and implemented, funding is needed for pilot projects, data standards, policy, and stakeholder collaboration.     

Increasing EHR system usability through standards: Conformance criteria in the HL7 EHR-system functional model

Though substantial work has been done on the usability of health information technology, improvements in electronic health record system (EHR) usability have been slow, creating frustration, distrust of EHRs and the use of potentially unsafe work-arounds. Usability standards could be part of the solution for improving EHR usability. EHR system functional requirements and standards have been used successfully in the past to specify system behavior, the criteria of which have been gradually implemented in EHR systems through certification programs and other national health IT strategies. Similarly, functional requirements and standards for usability can help address the multitude of sequelae associated with poor usability. This paper describes the evidence-based functional requirements for usability contained in the Health Level Seven (HL7) EHR System Functional Model, and the benefits of open and voluntary EHR system usability standards.     

Development, implementation and diffusion of EHR systems in Denmark

The Danish EHR-Observatory has monitored Danish EHR projects for several years with respect to a number of parameters such as diffusion, diffusion rate, barriers and limitations, and experience gained. The results of the 2002 monitoring reveal that investment in IT is relatively low and the diffusion rate is below the estimated level. The EHR projects gain a lot of valuable experience, but the coordination of evaluation results should be improved.     

Neptune: an environment for the delivery of genomic medicine

PurposeGenomic medicine holds great promise for improving health care, but integrating searchable and actionable genetic data into electronic health records (EHRs) remains a challenge. Here we describe Neptune, a system for managing the interaction between a clinical laboratory and an EHR system during the clinical reporting process.MethodsWe developed Neptune and applied it to two clinical sequencing projects that required report customization, variant reanalysis, and EHR integration.ResultsNeptune has been applied for the generation and delivery of over 15,000 clinical genomic reports. This work spans two clinical tests based on targeted gene panels that contain 68 and 153 genes respectively. These projects demanded customizable clinical reports that contained a variety of genetic data types including single-nucleotide variants (SNVs), copy-number variants (CNVs), pharmacogenomics, and polygenic risk scores. Two variant reanalysis activities were also supported, highlighting this important workflow.ConclusionMethods are needed for delivering structured genetic data to EHRs. This need extends beyond developing data formats to providing infrastructure that manages the reporting process itself. Neptune was successfully applied on two high-throughput clinical sequencing projects to build and deliver clinical reports to EHR systems. The software is open source and available at https://gitlab.com/bcm-hgsc/neptune.     

Building a robust, scalable and standards-driven infrastructure for secondary use of EHR data: the SHARPn project

The Strategic Health IT Advanced Research Projects (SHARP) Program, established by the Office of the National Coordinator for Health Information Technology in 2010 supports research findings that remove barriers for increased adoption of health IT. The improvements envisioned by the SHARP Area 4 Consortium (SHARPn) will enable the use of the electronic health record (EHR) for secondary purposes, such as care process and outcomes improvement, biomedical research and epidemiologic monitoring of the nation's health. One of the primary informatics problem areas in this endeavor is the standardization of disparate health data from the nation's many health care organizations and providers. The SHARPn team is developing open source services and components to support the ubiquitous exchange, sharing and reuse or 'liquidity' of operational clinical data stored in electronic health records. One year into the design and development of the SHARPn framework, we demonstrated end to end data flow and a prototype SHARPn platform, using thousands of patient electronic records sourced from two large healthcare organizations: Mayo Clinic and Intermountain Healthcare. The platform was deployed to (1) receive source EHR data in several formats, (2) generate structured data from EHR narrative text, and (3) normalize the EHR data using common detailed clinical models and Consolidated Health Informatics standard terminologies, which were (4) accessed by a phenotyping service using normalized data specifications. The architecture of this prototype SHARPn platform is presented. The EHR data throughput demonstration showed success in normalizing native EHR data, both structured and narrative, from two independent organizations and EHR systems. Based on the demonstration, observed challenges for standardization of EHR data for interoperable secondary use are discussed.     

Improving electronic health record (EHR) accuracy and increasing compliance with health maintenance clinical guidelines through patient access and input

BACKGROUND: Health maintenance is crucial for preventing morbidity and premature mortality, but many patients do not receive preventive services at recommended intervals. One reason for this is the lack of up-to-date information accurately reflecting patients' history. Electronic health records (EHRs) can be useful, but are often incomplete. Patient input has the potential to improve the accuracy of this information. In this study, we assessed the current state of EHR completeness for preventive services and the added value of patient reported information. METHODS: Participants were sent a survey, pre-populated with health maintenance procedure information from their EHRs. They were asked to review this information and indicate whether it was accurate or if they had a procedure done more recently. Of 1098 patients recruited from a primary care practice, 163 returned the survey. When a patient reported a more recent test than was noted in the EHR, researchers updated the EHR to reflect the additional information. Data were also gathered from the EHR 6 months after surveys were completed to analyze whether providing due test information encouraged patients to get tested and vaccinated. A review of medical records was performed on a control group to analyze differences in adherence to preventive guidelines between those that were notified of their overdue status and those who were not notified. RESULTS: The EHR was frequently incomplete when compared to patient report. In particular, many patients were misidentified as being overdue for health maintenance procedures when they had obtained them in other places. Showing patients their information resulted in little impact on overall adherence. However, with the cumulative effects of additional patient-reported procedures and procedures performed after the survey, intervention patients had higher documented adherence rates for every procedure than the control group. CONCLUSIONS: Health maintenance data in EHRs were often incomplete. Patients were often able to provide useful information, demonstrating the value of patient contributions in keeping records up-to-date.     

Implications of non-stationarity on predictive modeling using EHRs

The rapidly increasing volume of clinical information captured in Electronic Health Records (EHRs) has led to the application of increasingly sophisticated models for purposes such as disease subtype discovery and predictive modeling. However, increasing adoption of EHRs implies that in the near future, much of the data available for such purposes will be from a time period during which both the practice of medicine and the clinical use of EHRs are in flux due to historic changes in both technology and incentives. In this work, we explore the implications of this phenomenon, called non-stationarity, on predictive modeling. We focus on the problem of predicting delayed wound healing using data available in the EHR during the first week of care in outpatient wound care centers, using a large dataset covering over 150,000 individual wounds and 59,958 patients seen over a period of four years. We manipulate the degree of non-stationarity seen by the model development process by changing the way data is split into training and test sets. We demonstrate that non-stationarity can lead to quite different conclusions regarding the relative merits of different models with respect to predictive power and calibration of their posterior probabilities. Under the non-stationarity exhibited in this dataset, the performance advantage of complex methods such as stacking relative to the best simple classifier disappears. Ignoring non-stationarity can thus lead to sub-optimal model selection in this task.     

Advanced and secure architectural EHR approaches

OBJECTIVES: Electronic Health Records (EHRs) provided as a lifelong patient record advance towards core applications of distributed and co-operating health information systems and health networks. For meeting the challenge of scalable, flexible, portable, secure EHR systems, the underlying EHR architecture must be based on the component paradigm and model driven, separating platform-independent and platform-specific models. METHODS: Allowing manageable models, real systems must be decomposed and simplified. The resulting modelling approach has to follow the ISO Reference Model - Open Distributing Processing (RM-ODP). The ISO RM-ODP describes any system component from different perspectives. Platform-independent perspectives contain the enterprise view (business process, policies, scenarios, use cases), the information view (classes and associations) and the computational view (composition and decomposition), whereas platform-specific perspectives concern the engineering view (physical distribution and realisation) and the technology view (implementation details from protocols up to education and training) on system components. Those views have to be established for components reflecting aspects of all domains involved in healthcare environments including administrative, legal, medical, technical, etc. Thus, security-related component models reflecting all view mentioned have to be established for enabling both application and communication security services as integral part of the system's architecture. Beside decomposition and simplification of system regarding the different viewpoint on their components, different levels of systems' granularity can be defined hiding internals or focusing on properties of basic components to form a more complex structure. The resulting models describe both structure and behaviour of component-based systems. RESULTS: The described approach has been deployed in different projects defining EHR systems and their underlying architectural principles. In that context, the Australian GEHR project, the openEHR initiative, the revision of CEN ENV 13606 "Electronic Health Record communication", all based on Archetypes, but also the HL7 version 3 activities are discussed in some detail. The latter include the HL7 RIM, the HL7 Development Framework, the HL7's clinical document architecture (CDA) as well as the set of models from use cases, activity diagrams, sequence diagrams up to Domain Information Models (DMIMs) and their building blocks Common Message Element Types (CMET) Constraining Models to their underlying concepts. CONCLUSION: The future-proof EHR architecture as open, user-centric, user-friendly, flexible, scalable, portable core application in health information systems and health networks has to follow advanced architectural paradigms.     

Assessing and comparing the usability of Chinese EHRs used in two Peking University hospitals to EHRs used in the US: A method of RUA

ObjectivesThe objective of this study was to investigate the usability level of Chinese hospital Electronic Health Records (EHRs) by assessing the completion times of EHRs for seven “meaningful use (MU)” relevant tasks conducted at two Chinese tertiary hospitals and comparing the results to those of relevant research conducted in US EHRs.MethodsUsing Rapid Usability Assessment (RUA) developed by the National Center for Cognitive Informatics and Decision Making (NCCD), the usability of EHRs from two Peking University hospitals was assessed using a three-step Keystroke Level Model (KLM) in a laboratory environment.Results(1) The total EHR task completion time for 7 MU relevant test tasks showed no significant differences between the two Chinese EHRs and their US counterparts, in which the time for thinking was relatively large and comprised 35.6% of the total time. The time for the electronic physician order was the largest. (2) For specific tasks, the mean completion times of the 2 hospital EHR systems spent on recording, modifying and searching (RMS) the medication orders were similar to those for the RMS radioactive tests; the mean time spent on the RMS laboratory test orders were much less. (3) There were 85 usability problems identified in the 2 hospital EHR systems.DiscussionIn Chinese EHRs, a substantial amount of time is required to complete tasks relevant to MU targets and many preventable usability problems can be discovered. The task completion time of the 2 Chinese EHR systems was a little shorter than in the 5 reported US EHR systems, while the differences in smoking status and CPOE tasks were obvious; one main reason for these differences was the use of structured data entry.ConclusionsThe efficiency of Chinese and US EHRs was not significantly different. The key to improving the efficiency of both systems lies in expediting the Computerized physician order entry (CPOE) task. Many usability problems can be identified using heuristic assessments and improved by corresponding actions.     

A qualitative study of prevalent laboratory information systems and data communication patterns for genetic test reporting

PurposeThe availability of genetic test data within the electronic health record (EHR) is a pillar of the US vision for an interoperable health IT infrastructure and a learning health system. Although EHRs have been highly investigated, evaluation of the information systems used by the genetic labs has received less attention—but is necessary for achieving optimal interoperability. This study aimed to characterize how US genetic testing labs handle their information processing tasks.MethodsWe followed a qualitative research method that included interviewing lab representatives and a panel discussion to characterize the information flow models.ResultsTen labs participated in the study. We identified three generic lab system models and their relevant characteristics: a backbone system with additional specialized systems for interpreting genetic results, a brokering system that handles housekeeping and communication, and a single primary system for results interpretation and report generation.ConclusionLabs have heterogeneous workflows and generally have a low adoption of standards when sending genetic test reports back to EHRs. Core interpretations are often delivered as free text, limiting their computational availability for clinical decision support tools. Increased provision of genetic test data in discrete and standard-based formats by labs will benefit individual and public health.     

Exploring the persistence of paper with the electronic health record

Objective

Healthcare organizations are increasingly implementing electronic health records (EHRs) and other related health information technology (IT). Even in institutions which have long adopted these computerized systems, employees continue to rely on paper to complete their work. The objective of this study was to explore and understand human-technology integration factors that may be causing employees to rely on paper alternatives to the EHR.

Methods

We conducted semi-structured interviews with 20 key-informants in a large Veterans Affairs Medical Center (VAMC), with a fully implemented EHR, to understand the use of paper-based alternatives. Participants included clinicians, administrators, and IT specialists across several service areas in the medical center.

Results

We found 11 distinct categories of paper-based workarounds to the use of the EHR. Paper use related to the following: (1) efficiency; (2) knowledge/skill/ease of use; (3) memory; (4) sensorimotor preferences; (5) awareness; (6) task specificity; (7) task complexity; (8) data organization; (9) longitudinal data processes; (10) trust; and (11) security. We define each of these and provide examples that demonstrate how these categories promoted paper use in spite of a fully implemented EHR.

Conclusions

In several cases, paper served as an important tool and assisted healthcare employees in their work. In other cases, paper use circumvented the intended EHR design, introduced potential gaps in documentation, and generated possible paths to medical error. We discuss implications of these findings for EHR design and implementation.     

Patient accessible electronic health records: exploring recommendations for successful implementation strategies

Background

Providing patients with access to their electronic health records offers great promise to improve patient health and satisfaction with their care, as well to improve professional and organizational approaches to health care. Although many benefits have been identified, there are many questions about best practices for the implementation of patient accessible Electronic Health Records (EHRs).

Objectives

To develop recommendations to assist health care organizations in providing patients with access to EHRs in a meaningful, responsible, and responsive manner.

Methods

A Patient Accessible Electronic Health Record (PAEHR) Workshop was held with nationally and internationally renowned experts to explore issues related to providing patient access to the EHR and managing institutional change.

Results

The PAEHR Workshop was attended by 45 participants who discussed recommendations for the implementation of patient accessible EHRs. Recommendations were discussed under four subject domains: (1) providing patient access to the EHR, (2) maintaining privacy and confidentiality related to the PAEHR, (3) patient education and navigation of the PAEHR, and (4) strategies for managing institutional change. The discussion focused on the need for national infrastructure, clear definitions for privacy, security and confidentiality, flexible, interoperable solutions, and patient and professional education. In addition, there was a strong call for research into all domains of patient accessible EHRs to ensure the adoption of evidence-based practices.

Conclusions

Patient access to personal health information is a fundamental issue for patient engagement and empowerment. Health care professionals and organizations should consider the potential benefits and risks of patient access when developing EHR strategies. Flexible, standardized, and interoperable solutions must be integrated with outcomes-based research to activate effectively patients as partners in their health care.     

A study of user requests regarding the fully electronic health record system at Seoul National University Bundang Hospital: Challenges for future electronic health record systems

ObjectiveAlthough the adoption rates for Electronic Health Records (EHRs) are growing, significant opportunities for further advances in EHR system design remain. The goal of this study was to identify issues that should be considered in the design process for the successful development of future systems by analyzing end users’ service requests gathered during a recent three-year period after a comprehensive EHR system was implemented at Seoul National University's Bundang Hospital in South Korea.MethodsData on 11,400 service requests from end users of the EHR system made from 2008 through 2010 were used in this study. The requests were categorized as program modification/development, data request, insurance-fee identification/generation, patient-record merging, or other. The authors further subcategorized the requests for program modification/development into the following nine areas of concern: (1) indicators and statistics, (2) patient safety and quality of care, (3) special task-oriented functionalities, (4) ease of use and user interface, (5) system speed, (6) interoperability and integration, (7) privacy and security, (8) customer service, and (9) miscellaneous. The system users were divided into four groups—direct care, care support, administrative/insurance, and general management—to identify each group's needs and concerns.ResultsThe service requests for program modification/development, data request, insurance-fee identification/generation, patient-record merging, and other issues constituted approximately 49.2%, 33.9%, 11.4%, 4.0%, and 1.5% of the total data set, respectively. The number of data-request service requests grew over the three years studied. Different groups of users were found to have different concerns according to their activities and tasks. Within the program-modification/development category, end users were most frequently concerned with ease of use and user interface (38.1% of the total) and special task-oriented functionalities (29.3% of the total) in their use of the EHR system, with increasing numbers of requests in both categories over the three years. Users in the direct-care group differed from the other groups in that they most frequently submitted requests related to ease of use and user interface, followed by special functionalities, patient safety and quality care, and customer service, while users in other groups submitted requests concerning ease of use and user interface and special functionalities with a similarly high frequency.ConclusionsUsers have continued to make suggestions about their needs and requirements, and the EHR system has evolved to optimize ease of use and special functionalities for particular groups of users and particular subspecialties. Based on our experiences and the lessons we have learned in the course of maintaining full-EHR systems, we suggest that the key goals to be considered for future EHR systems include innovative new user-interface technologies; special extended functions for each user group's specific task-oriented requirements; powerful, easy-to-use functions to support research; new flexible system architecture; and patient-directed functions.     

Comparison of Electronic Health Record System Functionalities to support the patient recruitment process in clinical trials

ObjectivesReusing data from electronic health records for clinical and translational research and especially for patient recruitment has been tackled in a broader manner since about a decade. Most projects found in the literature however focus on standalone systems and proprietary implementations at one particular institution often for only one singular trial and no generic evaluation of EHR systems for their applicability to support the patient recruitment process does yet exist. Thus we sought to assess whether the current generation of EHR systems in Germany provides modules/tools, which can readily be applied for IT-supported patient recruitment scenarios.MethodsWe first analysed the EHR portfolio implemented at German University Hospitals and then selected 5 sites with five different EHR implementations covering all major commercial systems applied in German University Hospitals. Further, major functionalities required for patient recruitment support have been defined and the five sample EHRs and their standard tools have been compared to the major functionalities.ResultsIn our analysis of the site's hospital information system environments (with four commercial EHR systems and one self-developed system) we found that – even though no dedicated module for patient recruitment has been provided – most EHR products comprise generic tools such as workflow engines, querying capabilities, report generators and direct SQL-based database access which can be applied as query modules, screening lists and notification components for patient recruitment support. A major limitation of all current EHR products however is that they provide no dedicated data structures and functionalities for implementing and maintaining a local trial registry.ConclusionsAt the five sites with standard EHR tools the typical functionalities of the patient recruitment process could be mostly implemented. However, no EHR component is yet directly dedicated to support research requirements such as patient recruitment. We recommend for future developments that EHR customers and vendors focus much more on the provision of dedicated patient recruitment modules.     

Classifying individuals based on a densely captured sequence of vital signs: An example using repeated blood pressure measurements during hemodialysis treatment

Electronic Health Records (EHRs) present the opportunity to observe serial measurements on patients. While potentially informative, analyzing these data can be challenging. In this work we present a means to classify individuals based on a series of measurements collected by an EHR. Using patients undergoing hemodialysis, we categorized people based on their intradialytic blood pressure. Our primary criteria were that the classifications were time dependent and independent of other subjects. We fit a curve of intradialytic blood pressure using regression splines and then calculated first and second derivatives to come up with four mutually exclusive classifications at different time points. We show that these classifications relate to near term risk of cardiac events and are moderately stable over a succeeding two-week period. This work has general application for analyzing dense EHR data.     

Crowd control: Effectively utilizing unscreened crowd workers for biomedical data annotation

Annotating unstructured texts in Electronic Health Records data is usually a necessary step for conducting machine learning research on such datasets. Manual annotation by domain experts provides data of the best quality, but has become increasingly impractical given the rapid increase in the volume of EHR data. In this article, we examine the effectiveness of crowdsourcing with unscreened online workers as an alternative for transforming unstructured texts in EHRs into annotated data that are directly usable in supervised learning models. We find the crowdsourced annotation data to be just as effective as expert data in training a sentence classification model to detect the mentioning of abnormal ear anatomy in radiology reports of audiology. Furthermore, we have discovered that enabling workers to self-report a confidence level associated with each annotation can help researchers pinpoint less-accurate annotations requiring expert scrutiny. Our findings suggest that even crowd workers without specific domain knowledge can contribute effectively to the task of annotating unstructured EHR datasets.     

Patient-centered communication in the era of electronic health records: What does the evidence say?

ObjectivePatient-physician communication is essential for patient-centered health care. Physicians are concerned that electronic health records (EHRs) negatively affect communication with patients. This study identified a framework for understanding communication functions that influence patient outcomes. We then conducted a systematic review of the literature and organized it within the framework to better understand what is known.MethodA comprehensive search of three databases (CINAHL, Medline, PsycINFO) yielded 41 articles for analysis.ResultsResults indicated that EHR use improves capture and sharing of certain biomedical information. However, it may interfere with collection of psychosocial and emotional information, and therefore may interfere with development of supportive, healing relationships. Patient access to the EHR and messaging functions may improve communication, patient empowerment, engagement, and self-management.ConclusionMore rigorous examination of EHR impacts on communication functions and their influences on patient outcomes is imperative for achieving patient-centered care. By focusing on the role of communication functions on patient outcomes, future EHRs can be developed to facilitate care.Practice implicationsTraining alone is likely to be insufficient to address disruptions to communication processes. Processes must be improved, and EHRs must be developed to capture useful data without interfering with physicians’ and patients’ abilities to effectively communicate.     

Informed consent and the security of the electronic health record (EHR): some policy considerations

Various codes of ethics, and in particular the IMIA Code of Ethics for Health Information Professionals (HIPs), stipulate that the subject of an electronic health record (EHR) has a series of security rights with respect to her/his EHR, and that to some degree these rights center in the notion of informed consent. This paper examines the ethical basis of this position, outlines its implications for professionals, institutions and society in general, and identifies its limits. Further issues that will be discussed include who carries the responsibility for informed consent, what nature it should take, whether web-based EHRs present ethically unique problems, and related security implications.