Reliability study of clinical electronic records with paper records in the NSW Public Oral Health Service.

It is unknown whether observational studies evaluating the association between antidiabetic medications and mortality adequately account for frailty. Our objectives were to evaluate if frailty was a potential confounder in the relationship between antidiabetic medication regimen and mortality and how well administrative and clinical electronic health record (EHR) data account for frailty. We conducted a retrospective cohort study in a single Veterans Health Administration (VHA) healthcare system of 500 hospitalizations-the majority due to heart failure-of Veterans who received regular VHA care and initiated type 2 diabetes treatment from 2001 to 2008. We measured frailty using a modified frailty index (FI, >0.21 frail). We obtained antidiabetic medication regimen and time-to-death from administrative sources. We compared FI among patients on different antidiabetic regimens. Stepwise Cox proportional hazards regression estimated time-to-death by demographic, administrative, clinical EHR, and FI data. Median FI was 0.22 (interquartile range 0.18, 0.27). Frailty differed across antidiabetic regimens (p < .001). An FI increase of 0.05 was associated with an increased risk of death (hazard ratio 1.45, 95% confidence interval 1.32, 1.60). Cox proportional hazards model for time-to-death including demographic, administrative, and clinical EHR data had a c-statistic of 0.70; adding FI showed marginal improvement (c-statistic 0.72). Frailty was associated with antidiabetic regimen and death, and may confound that relationship. Demographic, administrative, and clinical EHR data, commonly used to balance differences among exposure groups, performed moderately well in assessing risk of death, with minimal gain from adding frailty. Study design and analytic techniques can help minimize potential confounding by frailty in observational studies.

This paper presents the history of the use of the computer for maintaining patient medical care information. An electronic record generated with a computer, which is non-specific for any healthcare specialty, is referred to as the electronic health record. The electronic health record was previously called the computer-based patient record. "Electronic" replaced the earlier term "computer-based" because "electronic" better describes the medium in which the patient record is managed. The electronic health record and its application to dentistry are discussed. The electronic health record is a "database" of patient information that has been entered by any healthcare provider; the electronic oral health record is an "electronic record" of oral health information that has been entered by an oral healthcare provider. The significant differences between the electronic health record and the electronic oral health record are outlined and highlighted. Included is a template describing a procedure to be used by dental personnel during the decision making process of purchasing an electronic oral health record. A brief description of a practice template is also provided. These completed templates can be shared with dental software vendors to clarify their understanding of and to clearly describe the needs of today's dental practice. The challenge of introducing information technology into educational institutions' curricula is identified. Finally, the potential benefit of using electronic technology for managing oral healthcare information is outlined.

“Meaningful Use” Means Process Redesign

Digital dystopias: will the electronic health record ever fulfil its potential?

The electronic health record: An essential tool for advancing patient safety

BackgroundClinical trials constitute an important pillar in medical research. It is beneficial to support recruitment for clinical trials using software tools, so-called patient recruitment support systems; however, such information technology systems have not been frequently used to date. Because medical information systems' underlying data collection methods strongly influence the benefits of implementing patient recruitment support systems, we investigated patient recruitment support system requirements and corresponding electronic record types such as electronic medical record, electronic health record, electronic medical case record, personal health record, and personal cross-enterprise health record.ObjectiveThe aim of this study was to (1) define requirements for successful patient recruitment support system deployment and (2) differentiate and compare patient recruitment support system–relevant properties of different electronic record types.MethodsIn a previous study, we gathered requirements for patient recruitment support systems from literature and unstructured interviews with stakeholders (15 patients, 3 physicians, 5 data privacy experts, 4 researchers, and 5 staff members of hospital administration). For this investigation, the requirements were amended and categorized based on input from scientific sessions. Based on literature with a focus on patient recruitment support system–relevant properties, different electronic record types (electronic medical record, electronic health record, electronic medical case record, personal health record and personal cross-enterprise health record) were described in detail. We also evaluated which patient recruitment support system requirements can be achieved for each electronic record type.ResultsPatient recruitment support system requirements (n=16) were grouped into 4 categories (consent management, patient recruitment management, trial management, and general requirements). All 16 requirements could be partially met by at least 1 type of electronic record. Only 1 requirement was fully met by all 5 types. According to our analysis, personal cross-enterprise health records fulfill most requirements for patient recruitment support systems. They demonstrate advantages especially in 2 domains (1) supporting patient empowerment and (2) granting access to the complete medical history of patients.ConclusionsIn combination with patient recruitment support systems, personal cross-enterprise health records prove superior to other electronic record types, and therefore, this integration approach should be further investigated.

Patient portals provide patients and their caregivers online access to limited health results. Health care employees with electronic health record (EHR) access may be able to view their health information not available in the patient portal by looking in the EHR. In this study, we examine how employees use the patient portal when they also have access to the tethered EHR. We obtained patient portal and EHR usage logs corresponding to all employees who viewed their health data at our institution between January 1, 2013 and November 1, 2017. We formed three cohorts based on the systems that employees used to view their health data: employees who used the patient portal only, employees who viewed health data in the EHR only, and employees who used both systems. We compared system accesses and usage patterns for each employee cohort. During the study period, 35,172 employees accessed the EHR as part of patients' treatment and 28,631 employees accessed their health data: 25,193 of them used the patient portal and 13,318 accessed their clinical data in EHR. All employees who accessed their records in the EHR viewed their clinical notes at least once. Among EHR accesses, clinical note accesses comprised more than 42% of all EHR accesses. Provider messaging and appointment scheduling were the most commonly used functions in the patient portal. Employees who had access to their health data in both systems were more likely to engage with providers through portal messages. Employees at a large medical center accessed clinical notes in the EHR to obtain information about their health. Employees also viewed other health data not readily available in the patient portal.

Big Data, Predictive Analytics, and Quality Improvement in Kidney Transplantation: A Proof of Concept.

Is Electronic Health Record Safety a Paradox?

Meaningful Use and Electronic Medical Records for the Gastroenterology Practice

After being indexed in National Library of Medicine (NLM) Catalog and PubMed Central in 2012, Healthcare Informatics Research (HIR) took another step forward in 2013 with its new position as a listed journal in Scopus. We also finished our application for Science Citation Index (SCI) at beginning of this year and are now in process of being evaluated. We are also happy to announce that HIR was recognized as one of best academic journals in Korea by The Korean Federation of Science and Technology Societies, as it was in previous years. At last, Issue 4 of Volume 19 is now officially published, ready to be read. The collaboration of this issue with International CODATA Conference marks another move forward in our development. In April 2013, Dr. William T. F. Goossen, an Editorial Board member of HIR, suggested publishing a set of papers presented in CODATA Conference held in Taipei, Taiwan in 2012. The CODATA is a conference organized by Committee on Data for Science and Technology of International Council for Science, and focus of conference is dealing with topic and methods used for preservation of data in Electronic Health Record (EHR). The HIR Editorial Committee decided to publish this special issue with a focus on aspects of preservation of data in EHR, because electronic health-related data and information is vital for clinical care as well as healthcare research, but systems interoperability for preservation, storage, and accessibility of such health data have not yet been established for If preservation of healthcare information is not addressed, valuable and irreplaceable information will become inaccessible or even disappear over time with disastrous consequences for patient care and research. Thus challenge is to preserve and provide access to electronic clinical data as EHR for a sufficiently long period of time to maximize value to patients, caregivers, and scientists. Healthcare informatics is a data-intensive scientific field, and HIR can highlight role that data-intensive science plays in transforming raw observations into applicable, intelligible results and discoveries. For health care, such discoveries will be increasingly based on observational data that come from EHR and clinical data warehouses. Of course, this development implies storage of petabytes, exabytes, zettabytes and even more of patient related data. This data must be stored for lifetimes of individuals and grouped into meaningful datamarts for population research. An additional issue is need to integrate diverse health records that have been captured in different settings and different EHR systems and data from various source systems and in recent smartphone apps and other e-Health applications. Hence question regarding permanence of clinical data becomes obvious. Consequently, hardware on which data is stored and software used become less significant compared to informational structures and meta-data about clinical data. Hence for health care, preservation of EHR and other health-related data is a very important theme. To publish this special issue, papers that we accepted fell under two categories. For articles from CODATA Conference, authors were requested to rewrite their article following HIR author guideline in format of either their original article or case report and submit it through on-line submission system. In other category, a public invitation was put out to send in articles covering theme of preservation of data in All manuscripts submitted from both categories underwent standard HIR peer-review procedure by three anonymous reviewers in order to guarantee quality and originality of research and its clinical and scientific significance. Therefore, only three of seven recommended articles from CODATA Conference were included. This issue consists of twelve unique contributions on topic EHR data preservation: One review article, five original research papers, five case reports, and one book review. The review article by Schultza, et al. clarifies challenges in biomedical knowledge research and describes how focus of research has moved from medical concept representation to medical ontologies. The first original paper by Singh, et al. uses Medical Subject Heading (MeSH) terms to find expert systems required for specific IT healthcare related projects, and paper by Kobayashi, et al. discusses use of Ruby programming language in implementation of OpenEHR specifications and archetypes. The other three original articles deal with topics of reusability of EHR data, use of health insurance claim data, and smartphone applications. The remaining five case reports discuss EHR interoperability through ISO 13606, health information exchange connectivity with legacy systems, semantic interoperability in electronic nursing record systems, mobile EHR applications, and Web-based integrated public healthcare information systems. These contributions state that besides overall structure of EHR, close attention must be paid to data definitions and data semantics in order to obtain sustainable EHR and improve quality of healthcare and research. The methods described here can be applicable to many areas of expertise. This issue is result of collaborating with CODATA Conference on topic of the preservation of data in EHR. To ascertain current practices for preservation and management of EHR, further studies should be conducted to establish an interoperability framework that supports a wide variety of data types, formats, records, and data delivery mechanisms, and to provide technology-independent infrastructures that acquire, store, search, retrieve, migrate, replicate, and distribute EHRs over time. It is our hope that we can continue to collaborate with conferences, workshops, colloquiums, and other academic dialogues in order to realize these goals.

BackgroundDecreased salivary secretion is not only a risk factor for carious lesions in Sjögren’s disease (SD) but also an indicator of deterioration of teeth with every restorative replacement. This study determined the longevity of direct dental restorations placed in patients with SD using matched electronic dental record (EDR) and electronic health record (EHR) data.MethodsWe conducted a retrospective cohort study using EDR and EHR data of Indiana University School of Dentistry patients who have a SD diagnosis in their EHR. Treatment history of patients during 15 years with SD (cases) and their matched controls with at least one direct dental restoration were retrieved from the EDR. Descriptive statistics summarized the study population characteristics. Cox regression models with random effects analyzed differences between cases and controls for time to direct restoration failure. Further the model explored the effect of covariates such as age, sex, race, dental insurance, medical insurance, medical diagnosis, medication use, preventive dental visits per year, and the number of tooth surfaces on time to restoration failure.ResultsAt least one completed direct restoration was present for 102 cases and 42 controls resulting in a cohort of 144 patients’ EDR and EHR data. The cases were distributed as 21 positives, 57 negatives, and 24 uncertain cases based on clinical findings. The average age was 56, about 93% were females, 54% were White, 74% had no dental insurance, 61% had public medical insurance, < 1 preventive dental visit per year, 94% used medications and 93% had a medical diagnosis that potentially causes dry mouth within the overall study cohort. About 529 direct dental restorations were present in cases with SD and 140 restorations in corresponding controls. Hazard ratios of 2.99 (1.48–6.03; p = 0.002) and 3.30 (1.49–7.31, p-value: 0.003) showed significantly decreased time to restoration failure among cases and positive for SD cases compared to controls, respectively. Except for the number of tooth surfaces, no other covariates had a significant influence on the survival time.ConclusionConsidering the rapid failure of dental restorations, appropriate post-treatment assessment, management, and evaluation should be implemented while planning restorative dental procedures among cases with SD. Since survival time is decreased with an increase in the number of surfaces, guidelines for restorative procedures should be formulated specifically for patients with SD.

Clinical registries play an important role in measuring healthcare delivery and supporting quality improvement for individuals with cardiovascular disease and stroke. Well-designed clinical registry programs provide important mechanisms to monitor patterns of care, evaluate healthcare effectiveness and safety, and improve clinical outcomes. The use of clinical registries is likely to grow given the increasing focus on measuring and improving healthcare delivery and patient outcomes by stakeholders in both the private and public sectors. The American Heart Association (AHA) has a longstanding commitment to promoting the innovative and effective use of clinical registries. The importance of clinical registries was highlighted recently in an AHA Scientific Statement on “Essential Features of a Surveillance System to Support the Prevention and Management of Heart Disease and Stroke” in the United States.1 This policy statement expands on the previous scientific statement by providing recommendations to policy makers and the healthcare community for expansion of the applications of existing and future clinical registries. The term “clinical registry” is defined here as an observational database of a clinical condition, procedure, therapy, or population in which there are often no registry-mandated approaches to therapy and relatively few inclusion or exclusion criteria. The focus of clinical registries is to capture data that reflect “real-world” clinical practice in large patient populations. The data from clinical registries do not replace the need for traditional randomized controlled trials. Rather, registries and trials are complementary approaches, each with unique advantages and imperfections.2 Such clinical registries do not solely contain claims or administrative data yet may be linked to such data sources. There are at least 3 classifications of clinical registries based on the patient population, including procedure/therapy/encounter-based, disease-based, and population-based registries. Registries also can be classified from a functional perspective, such as whether the registry is used to conduct clinical research, …

Electronic Health Records: Promises and Realities: A 3-Part Series Part I: The Digital Sea Change, Ready or Not

In the era of advanced healthcare technology, the adoption of Electronic Health Records (EHRs) has led to the accumulation of vast troves of clinical data. While EHRs primarily serve as a central repository for patient care, they are increasingly being utilized for secondary purposes, such as clinical research, disease surveillance, and quality improvement initiatives. This study systematically examines the diverse secondary uses of EHR data and their implications for patient privacy. Employing a mixed-methods approach, the research delves into the perceptions and perspectives of key stakeholders, including healthcare providers, hospital administrators, policymakers, and patient advocacy groups, through in-depth interviews. Additionally, the study analyses the prevalence and trends of secondary EHR data utilization using quantitative data. Crucially, the study provides a critical evaluation of the existing regulatory frameworks, namely the (GDPR) and (HIPAA).