Interoperable Electronic Health Record Research Articles

Similarity Analyzer for Semantic Interoperability of Electronic Health Records Using Artificial Intelligence (AI)

The introduction of Electronic Health Records (EHR) has opened possibilities for solving interoperability issues within the healthcare sector. However, even with the introduction of EHRs, healthcare systems like hospitals and pharmacies remain isolated with no sharing of EHRs due to semantic interoperability issues. This paper extends our previous work in which we proposed a framework that dealt with semantic interoperability and security of EHR. The extension is the proposal of a cloud-based similarity analyzer for data structuring, data mapping, data modeling and conflict removal using Word2vec Artificial Intelligence (AI) technique. Different types of conflicts are removed from data in order to model data into common data types which can be interpreted by different stakeholders.

Bridging Community Mental Health and Primary Care to Improve Medication Monitoring and Outcomes for Patients With Mental Illness Taking Second-Generation Antipsychotics-HDC/DFMC Bridge Project, Phase 1: Group Concept Mapping.

Patients with severe mental illness often lack care coordination between primary care and mental health providers. Siloed patient care across separate health care systems can negatively impact quality and safety of patient care. The purpose of the project discussed in this article is to effectively engage stakeholders from separate primary care and mental health organizations to develop an ideal cross-organization communication system to improve metabolic monitoring for their comanaged patients prescribed second-generation antipsychotics (SGAs). The mixed method approach of group concept mapping was used to engage stakeholders across a nonaffiliated primary care clinic and a community mental health organization over the time period of March 2018 through May 2018. Three important domains in communication were identified: (1) process/workflow, (2) advocacy, and (3) a patient-centered focus. Seven high priority/easier to implement brainstormed items were identified and resulted in practice changes across both organizations, including developing a standard release of information, identifying a point person from each clinic focused on cross-organization care coordination, endorsing an SGA monitoring protocol across organizations, agreeing that metabolic monitoring of SGAs will be the responsibility of the primary care clinicians, beginning monthly medication reconciliation and cross-organization care conferences, developing standard electronic health record documentation, and providing education. Care coordination across all health systems is critical to optimize patient care for chronic medical and psychiatric conditions. Group concept mapping provides a strategic process to allow shared decision-making among stakeholders to take steps toward solving more complex systematic problems such as poor electronic health record interoperability across health systems.

Actionable digital phenotyping: a framework for the delivery of just-in-time and longitudinal interventions in clinical healthcare

Designed to improve health, today numerous wearables and smartphone apps are used by millions across the world. Yet the wealth of data generated from the many sensors on these wearables and smartwatches has not yet transformed routine clinical care. One central reason for this gap between data and clinical insights is the lack of transparency and standards around data generated from mobile device that hinders interoperability and reproducibility. The clinical informatics community has offered solutions via the Fast Healthcare Interoperability Resources (FHIR) standard which facilities electronic health record interoperability but is less developed towards precision temporal contextually-tagged sensor measurements generated from today's ubiquitous mobile devices. In this paper we explore the opportunities and challenges of various theoretical approaches towards FHIR compatible digital phenotyping, and offer a concrete example implementing one such framework as an Application Programming Interface (API) for the open-source mindLAMP platform. We aim to build a community with contributions from statisticians, clinicians, patients, family members, researchers, designers, engineers, and more.

Impact of Patient-Controlled Analgesia (PCA) Smart Pump-Electronic Health Record (EHR) Interoperability with Auto-Documentation on Chart Completion in a Community Hospital Setting.

IntroductionComplete and accurate documentation of opioids administered by patient-controlled analgesia (PCA) pumps is critical for ensuring a high-quality medication record and an accurate conversion of the intravenous (IV) regimen to oral therapy. Incomplete charting of PCA usage through a manual process may be associated with fragmented documentation of delivered therapy affecting the completeness of the medical record and the IV to oral dose conversion. This study is the first to evaluate the association between auto-documentation of opioid administration provided by PCA smart pump—electronic health record (EHR) interoperability and the completion of PCA opioid administration charting tasks.MethodsThis retrospective cohort study was conducted at Lancaster General Hospital, Lancaster, Pennsylvania. Patients were assigned to pre-auto-documentation (n = 55) or post-auto-documentation groups (n = 58) based on whether they received PCA therapy prior to or after PCA-EHR interoperability was implemented. Charting of PCA therapy included documentation of the number of patient attempts, number of doses given, and total volume infused for both pre- and post-auto-documentation groups. In addition, total dose delivered was documented for the post-auto-documentation group. The overall chart-field completion rate was evaluated as the primary outcome. Individual chart completion percentages were assessed by stratified groups as secondary outcomes.ResultsPCA smart pump—EHR interoperability with auto-documentation was associated with an increase in overall chart-field completion rate from 69.9 to 97.0% (p < 0.001). Auto-documentation was also associated with an increase in fully completed charts from 38 to 91% (139.3% increase, p < 0.001) and reductions of incomplete records in each stratified group (p < 0.001).ConclusionsPCA smart pump—EHR interoperability with auto-documentation is associated with significant improvements in the completion of opioid administration chart-fields. Improved documentation of PCA administered opioids may have implications for the safety of opioid administration. Additional studies will be needed to assess the potential clinical impact of these results.FundingICU Medical, Inc.

Interoperable Electronic Health Records and Health Information Exchanges: Systematic Review.

BackgroundAs the availability of interoperable electronic health records (iEHRs) or health information exchanges (HIEs) continues to increase, there is greater need and opportunity to assess the current evidence base on what works and what does not regarding the adoption, use, and impact of iEHRs.ObjectiveThe purpose of this project is to assess the international evidence base on the adoption, use, and impact of iEHRs.MethodsWe conducted a systematic review, searching multiple databases—MEDLINE, Embase, and the Cumulative Index to Nursing and Allied Health Literature (CINAHL)—with supplemental searches conducted in Google Scholar and grey literature sources (ie, Google, Grey Literature Report, and OpenGrey). All searches were conducted in January and February 2017. Articles were eligible for inclusion if they were published in English, were published from 2006 to 2017, and were either an original research study or a literature review. In order to be included, articles needed to focus on iEHRs and HIEs across multiple health care settings, as well as on the impact and effectiveness of iEHR adoption and use.ResultsWe included 130 articles in the synthesis (113 primary studies, 86.9%; 17 reviews, 13.1%), with the majority focused on the United States (88/130, 67.7%). The primary studies focused on a wide range of health care settings; the three most prevalent settings studied included acute care (59/113, 52.2%), primary care (44/113, 38.9%), and emergency departments (34/113, 30.1%). We identified 29 distinct measurement items in the 113 primary studies that were linked to 522 specific measurement outcomes. Productivity and quality were the two evaluation dimensions that received the most attention, accounting for 14 of 29 (48%) measurement items and 306 of 522 (58.6%) measurement outcomes identified. Overall, the majority of the 522 measurement outcomes were positive (298/522, 57.1%). We also identified 17 reviews on iEHR use and impact, 6 (35%) that focused on barriers and facilitators to adoption and implementation and 11 (65%) that focused on benefits and impacts, with the more recent reviews finding little generalizable evidence of benefit and impact.ConclusionsThis review captures the status of an evolving and active field focused on the use and impact of iEHRs. While the overall findings suggest many positive impacts, the quality of the primary studies were not evaluated systematically. When broken down by specific measurement item, the results directed attention both to measurement outcomes that were consistently positive and others that were mostly negative or equivocal.

Discovering Clinical Information Models Online to Promote Interoperability of Electronic Health Records: A Feasibility Study of OpenEHR.

BackgroundClinical information models (CIMs) enabling semantic interoperability are crucial for electronic health record (EHR) data use and reuse. Dual model methodology, which distinguishes the CIMs from the technical domain, could help enable the interoperability of EHRs at the knowledge level. How to help clinicians and domain experts discover CIMs from an open repository online to represent EHR data in a standard manner becomes important.ObjectiveThis study aimed to develop a retrieval method to identify CIMs online to represent EHR data.MethodsWe proposed a graphical retrieval method and validated its feasibility using an online CIM repository: openEHR Clinical Knowledge Manager (CKM). First, we represented CIMs (archetypes) using an extended Bayesian network. Then, an inference process was run in the network to discover relevant archetypes. In the evaluation, we defined three retrieval tasks (medication, laboratory test, and diagnosis) and compared our method with three typical retrieval methods (BM25F, simple Bayesian network, and CKM), using mean average precision (MAP), average precision (AP), and precision at 10 (P@10) as evaluation metrics.ResultsWe downloaded all available archetypes from the CKM. Then, the graphical model was applied to represent the archetypes as a four-level clinical resources network. The network consisted of 5513 nodes, including 3982 data element nodes, 504 concept nodes, 504 duplicated concept nodes, and 523 archetype nodes, as well as 9867 edges. The results showed that our method achieved the best MAP (MAP=0.32), and the AP was almost equal across different retrieval tasks (AP=0.35, 0.31, and 0.30, respectively). In the diagnosis retrieval task, our method could successfully identify the models covering “diagnostic reports,” “problem list,” “patients background,” “clinical decision,” etc, as well as models that other retrieval methods could not find, such as “problems and diagnoses.”ConclusionsThe graphical retrieval method we propose is an effective approach to meet the uncertainty of finding CIMs. Our method can help clinicians and domain experts identify CIMs to represent EHR data in a standard manner, enabling EHR data to be exchangeable and interoperable.

Improving Oral-Systemic Healthcare through the Interoperability of Electronic Medical and Dental Records: An Exploratory Study.

Electronic health records (EHRs) are rarely shared among medical and dental providers. The purpose of this study was to assess current information sharing and the value of improved electronic information sharing among physicians and dentists in Germany and the United States. A survey was validated and distributed electronically to physicians and dentists at four academic medical centers. Respondents were asked anonymously about EHR use and the medical and dental information most valuable to their practice. There were 118 responses, a response rate of 23.2%. The majority (63.9%) of respondents were dentists and the remainder were physicians. Most respondents (66.3%) rated the importance of sharing information an 8 or above on a 1-to-10 Likert scale. Dentists rated the importance of sharing clinical information significantly higher than physicians (p = 0.0033). Most (68.5%) providers could recall an instance when access to medical or dental information would have improved patient care. Dentists were significantly more likely to report this than physicians (p = 0.008). Physicians would value a standardized measure of "oral health" in their EHR. Dentists were less likely to find specific medical diagnostic test results of value. Both dentists and physicians agreed that oral-systemic health was important; interoperable EHRs could facilitate information transfer between providers and enhance research on oral-systemic health connections. Both dentists and physicians believed that an interoperable EHR would be useful to practice, but desired information was different between these groups. Refinement of the information needed for shared practice is required.

Interoperability of Electronic Health Record

Interoperability of Electronic Health Record

An Assessment of the Interoperability of Electronic Health Record Exchanges Among Hospitals and Clinics in Taiwan.

BackgroundThe rapid aging of the Taiwanese population in recent years has led to high medical needs for the elderly and increasing medical costs. Integrating patient information through electronic health records (EHRs) to reduce unnecessary medications and tests and enhance the quality of care has currently become an important issue. Although electronic data interchanges among hospitals and clinics have been implemented for many years in Taiwan, the interoperability of EHRs has not adequately been assessed.ObjectiveThe study aimed to analyze the efficiency of data exchanges and provide suggestions for future improvements.MethodsWe obtained 30 months of uploaded and downloaded data of EHRs among hospitals and clinics. The research objects of this study comprised 19 medical centers, 57 regional hospitals, 95 district hospitals, and 5520 clinics. We examined 4 exchange EHR forms: laboratory test reports, medical images, discharge summaries, and outpatient medical records. We used MySQL (Oracle Corporation) software (to save our data) and phpMyAdmin, which is a Personal Home Page program, to manage the database and then analyzed the data using SPSS 19.0 statistical software.ResultsThe quarterly mean uploaded volume of EHRs among hospitals was 52,790,721 (SD 580,643). The quarterly mean downloaded volume of EHRs among hospitals and clinics was 650,323 (SD 215,099). The ratio of uploaded to downloaded EHRs was about 81:1. The total volume of EHRs was mainly downloaded by medical centers and clinics, which accounted for 53.82% (mean 318,717.80) and 45.41% (mean 269,082.10), respectively, and the statistical test was significant among different hospital accreditation levels (F2=7.63; P<.001). A comparison of EHR download volumes among the 6 National Health Insurance (NHI) branches showed that the central NHI branch downloaded 11,366,431 records (21.53%), which was the highest, and the eastern branch downloaded 1,615,391 records (3.06%), which was the lowest. The statistical test among the 6 NHI branches was significant (F5=8.82; P<.001). The download volumes of laboratory tests reports and outpatient medical records were 26,980,425 (50.3%) and 21,747,588 records (40.9%), respectively, and were much higher than medical images and discharge summaries. The statistical test was also significant (F=17.72; P<.001). Finally, the download time showed that the average for x-rays was 32.05 seconds, which was the longest, and was 9.92 seconds for electrocardiogram, which was the shortest, but there was no statistically significant difference among download times for various medical images.ConclusionsAfter years of operation, the Electronic Medical Record Exchange Center has achieved the initial goal of EHR interoperability, and data exchanges are running quite stably in Taiwan. However, the meaningful use of EHRs among hospitals and clinics still needs further encouragement and promotion. We suggest that the government’s leading role and collective collaboration with health care organizations are important for providing effective health information exchanges.

Fuzzy aggregation of similarity values for electronic health record interoperability

Fuzzy aggregation of similarity values for electronic health record interoperability

Smart Pump-Electronic Health Record (EHR) Interoperability with Auto-Documentation is Associated with Increased Submission of Infusion-Therapy Billing Claims at a Community Hospital.

BackgroundSmart pump–electronic health record (EHR) interoperability has been demonstrated to reduce adverse events and increase documentation and billing accuracy. However, relatively little is known about the impact of interoperability on infusion therapy billing claims and hospital finances.ObjectiveOur objective was to evaluate the association between smart pump–EHR interoperability with auto-documentation and current procedural terminology (CPT®)-coded infusion-therapy billing claims submissions.MethodsAt Penn Medicine Lancaster General Health (Lancaster, PA, USA), infusion-therapy billing data were collected for 158,379 patient days (a visit to the emergency department [ED] or 24 h admission to a non-ED unit) and divided into two groups: 78,241 pre- and 80,138 post-auto-documentation. The count and types of submitted CPT-coded claims were analyzed for ED/non-ED groups, inpatient/outpatient status and non-ED unit where the infusion was administered. Dollar amounts for CPT codes were calculated using Medicare Addendum B 2017. Patient day and CPT code counts were converted to annualized values to facilitate analysis.ResultsPatient days did not increase significantly from pre- to post-auto-documentation, whereas annualized submitted CPT-coded claims increased significantly by 14.5% (p < 0.001). The corresponding billing claim dollar value increased by $US1,147,652 (13.5%). ED patient days increased by 2.0% (p = 0.44), whereas submitted CPT-coded claims increased significantly by 4.0% (p < 0.001) and $US478,980 (7.4%). Non-ED patient days increased by 2.8% (p = 0.2), whereas CPT-coded claims increased significantly by 31.7% (p < 0.001) and $US668,672 (34.0%). The total number of submitted CPT-coded claims increased by 13.4% for inpatients and 12.3% for outpatients.ConclusionOur findings suggest that auto-documentation of infusion-therapy services may have a positive impact on hospital financial performance, which could help drive adoption of this technology.

Analyzing the performance of a blockchain-based personal health record implementation.

The Personal Health Record (PHR) and Electronic Health Record (EHR) play a key role in more efficient access to health records by health professionals and patients. It is hard, however, to obtain a unified view of health data that is distributed across different health providers. In particular, health records are commonly scattered in multiple places and are not integrated. This article presents the implementation and evaluation of a PHR model that integrates distributed health records using blockchain technology and the openEHR interoperability standard. We thus follow OmniPHR architecture model, which describes an infrastructure that supports the implementation of a distributed and interoperable PHR. Our method involves implementing a prototype and then evaluating the integration and performance of medical records from different production databases. In addition to evaluating the unified view of records, our evaluation criteria also focused on non-functional performance requirements, such as response time, CPU usage, memory occupation, disk, and network usage. We evaluated our model implementation using the data set of more than 40 thousand adult patients anonymized from two hospital databases. We tested the distribution and reintegration of the data to compose a single view of health records. Moreover, we profiled the model by evaluating a scenario with 10 superpeers and thousands of competing sessions transacting operations on health records simultaneously, resulting in an average response time below 500 ms. The blockchain implemented in our prototype achieved 98% availability. Our performance results indicated that data distributed via a blockchain could be recovered with low average response time and high availability in the scenarios we tested. Our study also demonstrated how OmniPHR model implementation can integrate distributed data into a unified view of health records.

SNOMED CT Concept Hierarchies for Computable Clinical Phenotypes From Electronic Health Record Data: Comparison of Intensional Versus Extensional Value Sets.

BackgroundDefining clinical phenotypes from electronic health record (EHR)–derived data proves crucial for clinical decision support, population health endeavors, and translational research. EHR diagnoses now commonly draw from a finely grained clinical terminology—either native SNOMED CT or a vendor-supplied terminology mapped to SNOMED CT concepts as the standard for EHR interoperability. Accordingly, electronic clinical quality measures (eCQMs) increasingly define clinical phenotypes with SNOMED CT value sets. The work of creating and maintaining list-based value sets proves daunting, as does insuring that their contents accurately represent the clinically intended condition.ObjectiveThe goal of the research was to compare an intensional (concept hierarchy-based) versus extensional (list-based) value set approach to defining clinical phenotypes using SNOMED CT–encoded data from EHRs by evaluating value set conciseness, time to create, and completeness.MethodsStarting from published Centers for Medicare and Medicaid Services (CMS) high-priority eCQMs, we selected 10 clinical conditions referenced by those eCQMs. For each, the published SNOMED CT list-based (extensional) value set was downloaded from the Value Set Authority Center (VSAC). Ten corresponding SNOMED CT hierarchy-based intensional value sets for the same conditions were identified within our EHR. From each hierarchy-based intensional value set, an exactly equivalent full extensional value set was derived enumerating all included descendant SNOMED CT concepts. Comparisons were then made between (1) VSAC-downloaded list-based (extensional) value sets, (2) corresponding hierarchy-based intensional value sets for the same conditions, and (3) derived list-based (extensional) value sets exactly equivalent to the hierarchy-based intensional value sets. Value set conciseness was assessed by the number of SNOMED CT concepts needed for definition. Time to construct the value sets for local use was measured. Value set completeness was assessed by comparing contents of the downloaded extensional versus intensional value sets. Two measures of content completeness were made: for individual SNOMED CT concepts and for the mapped diagnosis clinical terms available for selection within the EHR by clinicians.ResultsThe 10 hierarchy-based intensional value sets proved far simpler and faster to construct than exactly equivalent derived extensional value set lists, requiring a median 3 versus 78 concepts to define and 5 versus 37 minutes to build. The hierarchy-based intensional value sets also proved more complete: in comparison, the 10 downloaded 2018 extensional value sets contained a median of just 35% of the intensional value sets’ SNOMED CT concepts and 65% of mapped EHR clinical terms.ConclusionsIn the EHR era, defining conditions preferentially should employ SNOMED CT concept hierarchy-based (intensional) value sets rather than extensional lists. By doing so, clinical guideline and eCQM authors can more readily engage specialists in vetting condition subtypes to include and exclude, and streamline broad EHR implementation of condition-specific decision support promoting guideline adherence for patient benefit.

A modular cloud-based ontology framework for context-aware EHR services

Healthcare providers in a heterogeneous distributed environment depend on many non-functional requirements or cross-cutting concerns that could affect the entire Healthcare Information System (HIS). The implementation of crosscutting concerns could potentially lead to a significant impact on the integrity of Electronic Health Records (EHRs), as well as code quality. Aspect-Oriented Programming (AOP) encapsulates the crosscutting concerns to improve the overall quality of software development by reducing the required code to implement collection modules. In this paper, we propose an AOP-based novel approach to improve the elasticity of cloud-based EHR services. We propose an abstract framework for cloud-based HIS, which provides EHR interoperability through incorporating crosscutting concerns. The proposed framework eliminates the need to change the core code by adding high-level abstractions to complex cloud applications. We implement a prototype of the proposed framework to validate its ability in both separation of concerns and the ability to reuse EHR services.

Privacy Risks of Interoperable Electronic Health Records: Segmentation of Sensitive Information Will Help.

The proposed interoperability rules for electronic health records (EHRs) issued on March 4, 2019, by the Centers for Medicare and Medicaid Services address the last major element of the nation’s system of EHRs. The ability of health care providers and other users to supplement, exchange, and access comprehensive EHRs is essential to achieve efficient and high quality medical care. Interoperability, however, also increases the privacy risks of EHRs by enabling the unnecessary disclosure of sensitive health information to individuals and entities without a need to access them. This article reviews some leading proposals to protect health privacy within an interoperable system, highlighting the proposal from the National Committee on Vital and Health Statistics to permit patients to segment certain fields of sensitive information from the main body of their EHRs.

Emergency Physician Use of the Alberta Netcare Portal, a Province-Wide Interoperable Electronic Health Record: Multi-Method Observational Study.

BackgroundThe adoption and use of an electronic health record (EHR) can facilitate real-time access to key health information and support improved outcomes. Many Canadian provinces use interoperable EHRs (iEHRs) to facilitate health information exchange, but the clinical use and utility of iEHRs has not been well described.ObjectiveThe aim of this study was to describe the use of a provincial iEHR known as the Alberta Netcare Portal (ANP) in 4 urban Alberta emergency departments. The secondary objectives were to characterize the time spent using the respective electronic tools and identify the aspects that were perceived as most useful by emergency department physicians.MethodsIn this study, we have included 4 emergency departments, 2 using paper-based ordering (University of Alberta Hospital [UAH] and Grey Nuns Community Hospital [GNCH]) and 2 using a commercial vendor clinical information system (Peter Lougheed Centre [PLC] and Foothills Medical Centre [FMC]). Structured clinical observations of ANP use and system audit logs analysis were compared at the 4 sites from October 2014 to March 2016.ResultsObservers followed 142 physicians for a total of 566 hours over 376 occasions. The median percentage of observed time spent using ANP was 8.5% at UAH (interquartile range, IQR, 3.7%-13.3%), 4.4% at GNCH (IQR 2.4%-4.4%), 4.6% at FMC (IQR 2.4%-7.6%), and 5.1% at PLC (IQR 3.0%-7.7%). By combining administrative and access audit data, the median number of ANP screens (ie, results and reports displayed on a screen) accessed per patient visit were 20 at UAH (IQR 6-67), 9 at GNCH (IQR 4-29), 7 at FMC (IQR 2-18), and 5 at PLC (IQR 2-14). When compared with the structured clinical observations, the statistical analysis of screen access data showed that ANP was used more at UAH than the other sites.ConclusionsThis study shows that the iEHR is well utilized at the 4 sites studied, and the usage patterns implied clinical value. Use of the ANP was highest in a paper-based academic center and lower in the centers using a commercial emergency department clinical information system. More study about the clinical impacts of using iEHRs in the Canadian context including longer term impacts on quality of practice and safety are required.

Modeling EHR with the openEHR approach: an exploratory study in China

BackgroundThe openEHR approach can improve the interoperability of electronic health record (EHR) through two-level modeling. Developing archetypes for the complete EHR dataset is essential for implementing a large-scale interoperable EHR system with the openEHR approach. Although the openEHR approach has been applied in different domains, the feasibility of archetyping a complete EHR dataset in a hospital has not been reported in academic literature, especially in a country where using openEHR is still in its infancy stage, like China. This paper presents a case study of modeling an EHR in China aiming to investigate the feasibility and challenges of archetyping a complete EHR dataset with the openEHR approach.MethodsWe proposed an archetype modeling method including an iterative process of collecting requirements, normalizing data elements, organizing concepts, searching corresponding archetypes, editing archetypes and reviewing archetypes. Two representative EHR systems from Chinese vendors and the existing Chinese EHR standards have been used as resources to identify the requirements of EHR in China, and a case study of modeling EHR in China has been conducted. Based on the models developed in this case study, we have implemented a clinical data repository (CDR) to verify the feasibility of modeling EHR with archetypes.ResultsSixty four archetypes were developed to represent all requirements of a complete EHR dataset. 59 (91%) archetypes could be found in Clinical Knowledge Manager (CKM), of which 35 could be reused directly without change, and 23 required further development including two revisions, two new versions, 18 extensions and one specialization. Meanwhile, 6 (9%) archetypes were newly developed. The legacy data of the EHR system in hospitals could be integrated into the CDR developed with these archetypes successfully.ConclusionsThe existing archetypes in CKM can faithfully represent most of the EHR requirements in China except customizations for local hospital management. This case study verified the feasibility of modeling EHR with the openEHR approach and identified the fact that the challenges such as localization, tool support, and an agile publishing process still exist for a broader application of the openEHR approach.

Proposal for an eHealth Based Ecosystem Serving National Healthcare.

The European Union (EU)'s keen concern about citizens' health and well-being advancement has been expressed at all levels. It has been understood that at present, these can only be achieved through coordinated actions at the individual member states' level based on EU directives, as well as through promoting and funding R&D and expanding the use of eHealth technologies. Despite the diversities and particularities among member states, common values such as universal access to good quality healthcare, equity, and solidarity have been widely accepted across EU. That demanded the adoption of policies and follow directives, which streamlined actions to bridge healthcare gaps, and facilitate cross-border healthcare. This paper articulates a framework for deriving a national healthcare system, based on interoperable Electronic Health Record (EHR) with safeguarding healthcare quality, enabling quadruple helix (Public, Academia, Industry, NGOs) driven R&D and guided by a patient-centered approach. A methodology to develop an integrated EHR at National level is proposed as a prerequisite for eHealth and put into perspective. Recommendations are given for the steps needed, from the managerial, legal, technical, and financial concerns in developing an open access, patient-centered national healthcare system based on the context and constraints of a country. The example of a small country to apply the proposed methodology is demonstrated. Stakeholders, including citizens, healthcare professionals, academia, and the industry are mobilized, enabled, and incentivized for implementing the methodology. Experiences are aspired to be offered as lessons learned for other countries to adapt on their environment.

A clinical decision support system algorithm for intravenous to oral antibiotic switch therapy: validity, clinical relevance and usefulness in a three-step evaluation study.

To evaluate a clinical decision support system (CDSS) based on consensus-based intravenous to oral switch criteria, which identifies intravenous to oral switch candidates. A three-step evaluation study of a stand-alone CDSS with electronic health record interoperability was performed at the Erasmus University Medical Centre in the Netherlands. During the first step, we performed a technical validation. During the second step, we determined the sensitivity, specificity, negative predictive value and positive predictive value in a retrospective cohort of all hospitalized adult patients starting at least one therapeutic antibacterial drug between 1 and 16 May 2013. ICU, paediatric and psychiatric wards were excluded. During the last step the clinical relevance and usefulness was prospectively assessed by reports to infectious disease specialists. An alert was considered clinically relevant if antibiotics could be discontinued or switched to oral therapy at the time of the alert. During the first step, one technical error was found. The second step yielded a positive predictive value of 76.6% and a negative predictive value of 99.1%. The third step showed that alerts were clinically relevant in 53.5% of patients. For 43.4% it had already been decided to discontinue or switch the intravenous antibiotics by the treating physician. In 10.1%, the alert resulted in advice to change antibiotic policy and was considered useful. This prospective cohort study shows that the alerts were clinically relevant in >50% (n = 449) and useful in 10% (n = 85). The CDSS needs to be evaluated in hospitals with varying activity of infectious disease consultancy services as this probably influences usefulness.

Interoperability of Electronic Health Record

Interoperability of Electronic Health Record