Making Digital Health Equitable.

Most agree that the current healthcare system is broken. Fortunately, technology is increasing at an exponential rate and provides a solution for the future. Digital Health is an integrator concept that has the potential to take advantage of technological advantages. Digital Health converges health, healthcare, research, and everyday life. It includes technologies, platforms, and systems that engage consumers in all aspects of life. It makes health and healthcare be people-centered and personalized. Digital health requires total interoperability - standards, common data elements, and the integration of data from all sources. It demands data sharing. Digital Health brings together a wide range of stakeholders for similar goals using the same resources. Digital Health uses mobile devices and wearable sensors and uses Artificial Intelligence and Machine Learning to handle the vast amount of data Digital Health engages. Finally, Digital Health has the potential to open the gap between the different social and economic classes that must be addressed.

Economic analysis of a single institutional review board data exchange standard in multisite clinical studies.

BACKGROUND: Single Institutional Review Boards (sIRB) are not achieving the benefits envisioned by the National Institutes of Health. The recently published Health Level Seven (HL7®) Fast Healthcare Interoperability Resources (FHIR®) data exchange standard seeks to improve sIRB operational efficiency. METHODS AND RESULTS: We conducted a study to determine whether the use of this standard would be economically attractive for sIRB workflows collectively and for Reviewing and Relying institutions. We examined four sIRB-associated workflows at a single institution: (1) Initial Study Protocol Application, (2) Site Addition for an Approved sIRB study, (3) Continuing Review, and (4) Medical and Non-Medical Event Reporting. Task-level information identified personnel roles and their associated hour requirements for completion. Tasks that would be eliminated by the data exchange standard were identified. Personnel costs were estimated using annual salaries by role. No tasks would be eliminated in the Initial Study Protocol Application or Medical and Non-Medical Event Reporting workflows through use of the proposed data exchange standard. Site Addition workflow hours would be reduced by 2.50 h per site (from 15.50 to 13.00 h) and Continuing Review hours would be reduced by 9.00 h per site per study year (from 36.50 to 27.50 h). Associated costs savings were $251 for the Site Addition workflow (from $1609 to $1358) and $1033 for the Continuing Review workflow (from $4110 to $3076). CONCLUSION: Use of the proposed HL7 FHIR® data exchange standard would be economically attractive for sIRB workflows collectively and for each entity participating in the new workflows.

Goodbye Electronic Health Record?

The Electronic Health Record has failed to meet its intended purpose. We propose a new approach focusing on the use of data for health and health care. The first step is to create a repository of all patient data with data storage independent of data use. All use functionality is external to data storage. We propose the development of a common data model in which data elements have a rich set of attributes including actionable knowledge. Finally, functionality is provided through a series of application program interfaces (API). New APIs will address directly new methods for using data to increase the effectiveness of data application to improve management of the health and care of a patient. Together these components will open a pathway to finally accomplish the goals of a better future health system.

Clinician Burnout Associated With Sex, Clinician Type, Work Culture, and Use of Electronic Health Records.

Importance: Electronic health records (EHRs) are considered a potentially significant contributor to clinician burnout. Objective: To describe the association of EHR usage, sex, and work culture with burnout for 3 types of clinicians at an academic medical institution. Design, Setting, and Participants: This cross-sectional study of 1310 clinicians at a large tertiary care academic medical center analyzed EHR usage metrics for the month of April 2019 with results from a well-being survey from May 2019. Participants included attending physicians, advanced practice providers (APPs), and house staff from various specialties. Data were analyzed between March 2020 and February 2021. Exposures: Clinician demographic characteristics, EHR metadata, and an institution-wide survey. Main Outcomes and Measures: Study metrics included clinician demographic data, burnout score, well-being measures, and EHR usage metadata. Results: Of the 1310 clinicians analyzed, 542 (41.4%) were men (mean [SD] age, 47.3 [11.6] years; 448 [82.7%] White clinicians, 52 [9.6%] Asian clinicians, and 21 [3.9%] Black clinicians) and 768 (58.6%) were women (mean [SD] age, 42.6 [10.3] years; 573 [74.6%] White clinicians, 105 [13.7%] Asian clinicians, and 50 [6.5%] Black clinicians). Women reported more burnout (survey score ≥50: women, 423 [52.0%] vs men, 258 [47.6%]; P = .008) overall. No significant differences in EHR usage were found by sex for multiple metrics of time in the EHR, metrics of volume of clinical encounters, or differences in products of clinical care. Multivariate analysis of burnout revealed that work culture domains were significantly associated with self-reported results for commitment (odds ratio [OR], 0.542; 95% CI, 0.427-0.688; P < .001) and work-life balance (OR, 0.643; 95% CI, 0.559-0.739; P < .001). Clinician sex significantly contributed to burnout, with women having a greater likelihood of burnout compared with men (OR, 1.33; 95% CI, 1.01-1.75; P = .04). An increased number of days spent using the EHR system was associated with less likelihood of burnout (OR, 0.966; 95% CI, 0.937-0.996; P = .03). Overall, EHR metrics accounted for 1.3% of model variance (P = .001) compared with work culture accounting for 17.6% of variance (P < .001). Conclusions and Relevance: In this cross-sectional study, sex-based differences in EHR usage and burnout were found in clinicians. These results also suggest that local work culture factors may contribute more to burnout than metrics of EHR usage.

eSource for Standardized Health Information Exchange in Clinical Research: A Systematic Review.

The availability of research and outcomes data is the primary limitation to evidence-based practice. Today, only a fraction of clinical decisions are based upon evidence derived from randomized control trials (RCTs), the gold-standard of knowledge discovery. At the same time, clinical trial complexity has steadily increased as has the effort required at clinical investigational sites. Direct use of electronic health record (EHR) data for clinical trials has the potential to address some of these needs, improving data quality and reducing cost.

Evaluative Outcomes in Direct Extraction and Use of EHR Data in Clinical Trials.

Use of electronic health record (EHR) data in clinical trials has long been a goal for researchers. However, few demonstrations and fewer evaluative studies have been published. The variability in outcome choice and measurement hinders synthesis of the extant literature. In collaboration with a contemporaneous systematic review of EHR data use in clinical trial data collection, we analyze reported outcomes and recommend a standardized measure set for the evaluation of human safety, data quality, operational efficiency and cost of eSource solutions.

Pragmatic (trial) informatics: a perspective from the NIH Health Care Systems Research Collaboratory.

Pragmatic clinical trials (PCTs) are research investigations embedded in health care settings designed to increase the efficiency of research and its relevance to clinical practice. The Health Care Systems Research Collaboratory, initiated by the National Institutes of Health Common Fund in 2010, is a pioneering cooperative aimed at identifying and overcoming operational challenges to pragmatic research. Drawing from our experience, we present 4 broad categories of informatics-related challenges: (1) using clinical data for research, (2) integrating data from heterogeneous systems, (3) using electronic health records to support intervention delivery or health system change, and (4) assessing and improving data capture to define study populations and outcomes. These challenges impact the validity, reliability, and integrity of PCTs. Achieving the full potential of PCTs and a learning health system will require meaningful partnerships between health system leadership and operations, and federally driven standards and policies to ensure that future electronic health record systems have the flexibility to support research.

Innovative information visualization of electronic health record data: a systematic review.

OBJECTIVE: This study investigates the use of visualization techniques reported between 1996 and 2013 and evaluates innovative approaches to information visualization of electronic health record (EHR) data for knowledge discovery. METHODS: An electronic literature search was conducted May-July 2013 using MEDLINE and Web of Knowledge, supplemented by citation searching, gray literature searching, and reference list reviews. General search terms were used to assure a comprehensive document search. RESULTS: Beginning with 891 articles, the number of articles was reduced by eliminating 191 duplicates. A matrix was developed for categorizing all abstracts and to assist with determining those to be excluded for review. Eighteen articles were included in the final analysis. DISCUSSION: Several visualization techniques have been extensively researched. The most mature system is LifeLines and its applications as LifeLines2, EventFlow, and LifeFlow. Initially, research focused on records from a single patient and visualization of the complex data related to one patient. Since 2010, the techniques under investigation are for use with large numbers of patient records and events. Most are linear and allow interaction through scaling and zooming to resize. Color, density, and filter techniques are commonly used for visualization. CONCLUSIONS: With the burgeoning increase in the amount of electronic healthcare data, the potential for knowledge discovery is significant if data are managed in innovative and effective ways. We identify challenges discovered by previous EHR visualization research, which will help researchers who seek to design and improve visualization techniques.

A comparison of phenotype definitions for diabetes mellitus.

OBJECTIVE: This study compares the yield and characteristics of diabetes cohorts identified using heterogeneous phenotype definitions. MATERIALS AND METHODS: Inclusion criteria from seven diabetes phenotype definitions were translated into query algorithms and applied to a population (n=173 503) of adult patients from Duke University Health System. The numbers of patients meeting criteria for each definition and component (diagnosis, diabetes-associated medications, and laboratory results) were compared. RESULTS: Three phenotype definitions based heavily on ICD-9-CM codes identified 9-11% of the patient population. A broad definition for the Durham Diabetes Coalition included additional criteria and identified 13%. The electronic medical records and genomics, NYC A1c Registry, and diabetes-associated medications definitions, which have restricted or no ICD-9-CM criteria, identified the smallest proportions of patients (7%). The demographic characteristics for all seven phenotype definitions were similar (56-57% women, mean age range 56-57 years).The NYC A1c Registry definition had higher average patient encounters (54) than the other definitions (range 44-48) and the reference population (20) over the 5-year observation period. The concordance between populations returned by different phenotype definitions ranged from 50 to 86%. Overall, more patients met ICD-9-CM and laboratory criteria than medication criteria, but the number of patients that met abnormal laboratory criteria exclusively was greater than the numbers meeting diagnostic or medication data exclusively. DISCUSSION: Differences across phenotype definitions can potentially affect their application in healthcare organizations and the subsequent interpretation of data. CONCLUSIONS: Further research focused on defining the clinical characteristics of standard diabetes cohorts is important to identify appropriate phenotype definitions for health, policy, and research.

Electronic health records based phenotyping in next-generation clinical trials: a perspective from the NIH Health Care Systems Collaboratory.

Widespread sharing of data from electronic health records and patient-reported outcomes can strengthen the national capacity for conducting cost-effective clinical trials and allow research to be embedded within routine care delivery. While pragmatic clinical trials (PCTs) have been performed for decades, they now can draw on rich sources of clinical and operational data that are continuously fed back to inform research and practice. The Health Care Systems Collaboratory program, initiated by the NIH Common Fund in 2012, engages healthcare systems as partners in discussing and promoting activities, tools, and strategies for supporting active participation in PCTs. The NIH Collaboratory consists of seven demonstration projects, and seven problem-specific working group 'Cores', aimed at leveraging the data captured in heterogeneous 'real-world' environments for research, thereby improving the efficiency, relevance, and generalizability of trials. Here, we introduce the Collaboratory, focusing on its Phenotype, Data Standards, and Data Quality Core, and present early observations from researchers implementing PCTs within large healthcare systems. We also identify gaps in knowledge and present an informatics research agenda that includes identifying methods for the definition and appropriate application of phenotypes in diverse healthcare settings, and methods for validating both the definition and execution of electronic health records based phenotypes.

Data standard ≠ data quality.

The relationship between data quality and data standards has not been clearly articulated. While some directly state that data standards increase data quality, others claim the opposite. Depending on the type of data standard and the aspects of data quality considered, both arguments may in fact be correct. We deconstruct a typology of data standards and ap ply a dimensional definition of data quality to clearly articulate the relationship between the two, providing a framework for data quality planning.

Connecting information to improve health.

Effective health information systems require timely access to all health data from all sources, including sites of direct care. In most parts of the world today, these data most likely come from many different and unconnected systems-but must be organized into a composite whole. We use the word interoperability to capture what is required to accomplish this goal. We discuss five priority areas for achieving interoperability in health care applications (patient identifier, semantic interoperability, data interchange standards, core data sets, and data quality), and we contrast differences in developing and developed countries. Important next steps for health policy makers are to define a vision, develop a strategy, identify leadership, assign responsibilities, and harness resources.

eHealth interoperability.

For improving quality and safety of patient's care, for keeping the costs of health services, but also for successfully managing public health communication and cooperation between all stakeholders is inevitable. Such interoperability can be provided at different levels from simple data exchange up to business interoperability. The paper introduces those interoperability levels and international standards specifying and facilitating them. In that context, the expression of business requirements by domain analysis models or story boards as well as by functional models of the core applications enabling interoperability like EHR systems have been tackled. The role of decision support systems and infrastructural services has been considered as well.

The clinical document architecture and the continuity of care record: a critical analysis.

Health care provides many opportunities in which the sharing of data between independent sites is highly desirable. Several standards are required to produce the functional and semantic interoperability necessary to support the exchange of such data: a common reference information model, a common set of data elements, a common terminology, common data structures, and a common transport standard. This paper addresses one component of that set of standards: the ability to create a document that supports the exchange of structured data components. Unfortunately, two different standards development organizations have produced similar standards for that purpose based on different information models: Health Level 7 (HL7)'s Clinical Document Architecture (CDA) and The American Society for Testing and Materials (ASTM International) Continuity of Care Record (CCR). The coexistence of both standards might require mapping from one standard to the other, which could be accompanied by a loss of information and functionality. This paper examines and compares the two standards, emphasizes the strengths and weaknesses of each, and proposes a strategy of harmonization to enhance future progress. While some of the authors are members of HL7 and/or ASTM International, the authors stress that the viewpoints represented in this paper are those of the authors and do not represent the official viewpoints of either HL7 or of ASTM International.

The making and adoption of health data standards.

Health data standards are key to the U.S. quest to create an aggregated, patient-centric electronic health record; to build regional health information networks; to interchange data among independent sites involved in a person's care; to create a population database for health surveillance and for bioterrorism defense; and to create a personal health record. This paper discusses why health data standards are required, the process of creating those standards, the groups creating those standards, and some of the problems and issues that are affecting the progress and acceptance of standards. It makes a recommendation for dealing with those issues.

Accelerating U.S. EHR adoption: how to get there from here. recommendations based on the 2004 ACMI retreat.

Despite growing support for the adoption of electronic health records (EHR) to improve U.S. healthcare delivery, EHR adoption in the United States is slow to date due to a fundamental failure of the healthcare information technology marketplace. Reasons for the slow adoption of healthcare information technology include a misalignment of incentives, limited purchasing power among providers, variability in the viability of EHR products and companies, and limited demonstrated value of EHRs in practice. At the 2004 American College of Medical Informatics (ACMI) Retreat, attendees discussed the current state of EHR adoption in this country and identified steps that could be taken to stimulate adoption. In this paper, based upon the ACMI retreat, and building upon the experiences of the authors developing EHR in academic and commercial settings we identify a set of recommendations to stimulate adoption of EHR, including financial incentives, promotion of EHR standards, enabling policy, and educational, marketing, and supporting activities for both the provider community and healthcare consumers.

The role of standards in electronic prescribing.

The focus on preventing medical errors has advanced the arguments for widespread implementation of electronic prescribing. The choice of systems as well as the variation in functionality is large. Value and return on investment depend on the functionality provided. The paper by Douglas Bell and colleagues defines the functionalities that are required and desirable to ensure patient safety and quality of care. Health data standards are a prerequisite for the interoperability to support electronic prescribing. This paper discusses some of the barriers and problems in producing and adopting those standards.

Making the boundaries clearer: revisiting information systems with fading boundaries.

PURPOSE: To address issues of importance in 1994 and what has happened in those issues. METHODS: A number of questions and issues will be examined. Were we right in our focus at that time and what did we miss? What has happened that perhaps changed our perspectives and philosophies? Has the need changed? Is the model of fading boundaries a correct one, and how far have we gone in realizing a communication system in dealing with those boundaries? What progress have we made internationally on these issues? How are we working internationally to solve these problems? RESULTS: The fifth working conference relating to hospital information systems (HIS) was held in Durham, North Carolina in August 1994. The Institute of Medicine publication The Computer-based Patient Record: An Essential Technology for Health Care had been published in 1991 and had begun influencing thinking and direction for clinical information systems. The difference between and relationship of HIS and Computer-based Patients Records was the topic of much discussion and debate. The 1994 conference strongly recognized the need for standards specifically for data exchange, unique patient identifier, data definitions and common clinical data sets and for clinical terminology. Interconnectivity and interoperability were identified as separate but related problems to be solved. Technology was not considered to be a barrier, and projections for bandwidth to meet data dissemination requirements were favorable. In the 7 years after the Durham conference, many things have changed dramatically. Progress has been made in a number of areas, and some of the projections have been realized. However, it is surprising to note what areas still remain problems, particularly noting what problems have been worked on without success and what problems have not even been addressed. It is interesting to speculate that if the Durham conference was repeated today, would it be accepted as a current event?