scholarly journals Clinical Decision Supports in Electronic Health Records to Promote Childhood Obesity-Related Care: Results from a 2015 Survey of Healthcare Providers

2019 ◽  
Vol 8 (4) ◽  
pp. 255
Author(s):  
Megan R. Harrison ◽  
Elizabeth A. Lundeen ◽  
Brook Belay ◽  
Alyson B. Goodman
Keyword(s):  
Childhood Obesity ◽  
Electronic Health Records ◽  
Healthcare Providers ◽  
Clinical Decision ◽  
Health Records ◽  
Electronic Health ◽  
Clinical Decision Supports

Electronic Health Records Implementation in Jordan: Perceptions of Healthcare Providers and Determinant Factors (Preprint)

2020 ◽  
Author(s):  
Tamadur Shudayfat ◽  
Çağdaş Akyürek ◽  
Noha Al-Shdayfat ◽  
Hatem Alsaqqa
Keyword(s):  
Electronic Health Records ◽  
Electronic Health Record ◽  
Technology Acceptance ◽  
Technology Acceptance Model ◽  
Healthcare Providers ◽  
Health Record ◽  
Health Records ◽  
Context Factors ◽  
Electronic Health ◽  
Acceptance Model

BACKGROUND Acceptance of Electronic Health Record systems is considered an essential factor for an effective implementation among the Healthcare providers. In an attempt to understand the healthcare providers’ perceptions on the Electronic Health Record systems implementation and evaluate the factors influencing healthcare providers’ acceptance of Electronic Health Records, the current research examines the effects of individual (user) context factors, and organizational context factors, using Technology Acceptance Model. OBJECTIVE The current research examines the effects of individual (user) context factors, and organizational context factors, using Technology Acceptance Model. METHODS A quantitative cross-sectional survey design was used, in which 319 healthcare providers from five public hospital participated in the present study. Data was collected using a self-administered questionnaire, which was based on the Technology Acceptance Model. RESULTS Jordanian healthcare providers demonstrated positive perceptions of the usefulness and ease of use of Electronic Health Record systems, and subsequently, they accepted the technology. The results indicated that they had a significant effect on the perceived usefulness and perceived ease of use of Electronic Health Record, which in turn was related to positive attitudes towards Electronic Health Record systems as well as the intention to use them. CONCLUSIONS User attributes, organizational competency, management support and training and education are essential variables in predicting healthcare provider’s acceptance toward Electronic Health records. These findings should be considered by healthcare organizations administration to introduce effective system to other healthcare organizations.

A Global Socio-economic-medico-legal Model for the Sustainability of Longitudinal Electronic Health Records

2006 ◽  
Vol 45 (03) ◽  
pp. 240-245 ◽  
Author(s):  
A. Shabo
Keyword(s):  
Electronic Health Records ◽  
Healthcare Providers ◽  
Financial Assets ◽  
Healthcare Organizations ◽  
Health Records ◽  
Record Keeping ◽  
Proposed Model ◽  
Legal Model ◽  
Electronic Health

Summary Objectives: This paper pursues the challenge of sustaining lifetime electronic health records (EHRs) based on a comprehensive socio-economic-medico-legal model. The notion of a lifetime EHR extends the emerging concept of a longitudinal and cross-institutional EHR and is invaluable information for increasing patient safety and quality of care. Methods: The challenge is how to compile and sustain a coherent EHR across the lifetime of an individual. Several existing and hypothetical models are described, analyzed and compared in an attempt to suggest a preferred approach. Results: The vision is that lifetime EHRs should be sustained by new players in the healthcare arena, who will function as independent health record banks (IHRBs). Multiple competing IHRBs would be established and regulated following preemptive legislation. They should be neither owned by healthcare providers nor by health insurer/payers or government agencies. The new legislation should also stipulate that the records located in these banks be considered the medico-legal copies of an individual’s records, and that healthcare providers no longer serve as the legal record keepers. Conclusions: The proposed model is not centered on any of the current players in the field; instead, it is focussed on the objective service of sustaining individual EHRs, much like financial banks maintain and manage financial assets. This revolutionary structure provides two main benefits: 1) Healthcare organizations will be able to cut the costs of long-term record keeping, and 2) healthcare providers will be able to provide better care based on the availability of a lifelong EHR of their new patients.

scholarly journals Desiderata for computable representations of electronic health records-driven phenotype algorithms

2015 ◽  
Vol 22 (6) ◽  
pp. 1220-1230 ◽  
Author(s):  
Huan Mo ◽  
William K Thompson ◽  
Luke V Rasmussen ◽  
Jennifer A Pacheco ◽  
Guoqian Jiang ◽  
...  
Keyword(s):  
Electronic Health Records ◽  
Language Processing ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Relational Algebra ◽  
Common Data Model ◽  
Health Records ◽  
Electronic Health ◽  
Value Sets ◽  
Text Searching

Abstract Background Electronic health records (EHRs) are increasingly used for clinical and translational research through the creation of phenotype algorithms. Currently, phenotype algorithms are most commonly represented as noncomputable descriptive documents and knowledge artifacts that detail the protocols for querying diagnoses, symptoms, procedures, medications, and/or text-driven medical concepts, and are primarily meant for human comprehension. We present desiderata for developing a computable phenotype representation model (PheRM). Methods A team of clinicians and informaticians reviewed common features for multisite phenotype algorithms published in PheKB.org and existing phenotype representation platforms. We also evaluated well-known diagnostic criteria and clinical decision-making guidelines to encompass a broader category of algorithms. Results We propose 10 desired characteristics for a flexible, computable PheRM: (1) structure clinical data into queryable forms; (2) recommend use of a common data model, but also support customization for the variability and availability of EHR data among sites; (3) support both human-readable and computable representations of phenotype algorithms; (4) implement set operations and relational algebra for modeling phenotype algorithms; (5) represent phenotype criteria with structured rules; (6) support defining temporal relations between events; (7) use standardized terminologies and ontologies, and facilitate reuse of value sets; (8) define representations for text searching and natural language processing; (9) provide interfaces for external software algorithms; and (10) maintain backward compatibility. Conclusion A computable PheRM is needed for true phenotype portability and reliability across different EHR products and healthcare systems. These desiderata are a guide to inform the establishment and evolution of EHR phenotype algorithm authoring platforms and languages.

scholarly journals Integrating Genomic Resources with Electronic Health Records using the HL7 Infobutton Standard

2016 ◽  
Vol 07 (03) ◽  
pp. 817-831 ◽  
Author(s):  
Casey Overby ◽  
Guilherme Del Fiol ◽  
Wendy Rubinstein ◽  
Donna Maglott ◽  
Tristan Nelson ◽  
...  
Keyword(s):  
Electronic Health Records ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Search Interface ◽  
Health Records ◽  
Knowledge Resources ◽  
Genomic Resources ◽  
Full Compliance ◽  
Genomic Knowledge ◽  
Electronic Health

SummaryThe Clinical Genome Resource (ClinGen) Electronic Health Record (EHR) Workgroup aims to integrate ClinGen resources with EHRs. A promising option to enable this integration is through the Health Level Seven (HL7) Infobutton Standard. EHR systems that are certified according to the US Meaningful Use program provide HL7-compliant infobutton capabilities, which can be leveraged to support clinical decision-making in genomics.To integrate genomic knowledge resources using the HL7 infobutton standard. Two tactics to achieve this objective were: (1) creating an HL7-compliant search interface for ClinGen, and (2) proposing guidance for genomic resources on achieving HL7 Infobutton standard accessibility and compliance.We built a search interface utilizing OpenInfobutton, an open source reference implementation of the HL7 Infobutton standard. ClinGen resources were assessed for readiness towards HL7 compliance. Finally, based upon our experiences we provide recommendations for publishers seeking to achieve HL7 compliance.Eight genomic resources and two sub-resources were integrated with the ClinGen search engine via OpenInfobutton and the HL7 infobutton standard. Resources we assessed have varying levels of readiness towards HL7-compliance. Furthermore, we found that adoption of standard terminologies used by EHR systems is the main gap to achieve compliance.Genomic resources can be integrated with EHR systems via the HL7 Infobutton standard using OpenInfobutton. Full compliance of genomic resources with the Infobutton standard would further enhance interoperability with EHR systems. Citation: Heale BSE, Overby CL, Del Fiol G, Rubinstein WS, Maglott DR, Nelson TH, Milosavljevic A, Martin CL, Goehringer SR, Freimuth RR, Williams MS. Integrating genomic resources with electronic health records using the HL7 Infobutton standard.

scholarly journals Linking electronic health records with community-level data to understand childhood obesity risk

2015 ◽  
Vol 10 (6) ◽  
pp. 436-441 ◽  
Author(s):  
E. J. Tomayko ◽  
T. L. Flood ◽  
A. Tandias ◽  
L. P. Hanrahan
Keyword(s):  
Childhood Obesity ◽  
Electronic Health Records ◽  
Community Level ◽  
Obesity Risk ◽  
Health Records ◽  
Level Data ◽  
Electronic Health

Integrating genomic-based clinical decision support into electronic health records

2010 ◽  
Vol 7 (2) ◽  
pp. 163-170 ◽  
Author(s):  
Amr Al Mallah ◽  
Paul Guelpa ◽  
Sharon Marsh ◽  
Tibor van Rooij
Keyword(s):  
Decision Support ◽  
Electronic Health Records ◽  
Clinical Decision Support ◽  
Clinical Decision ◽  
Health Records ◽  
Electronic Health

scholarly journals Convergence of Blockchain, Autonomous Agents, and Knowledge Graph to Share Electronic Health Records

2021 ◽  
Vol 4 ◽  
Author(s):  
Yao Yao ◽  
Meghana Kshirsagar ◽  
Gauri Vaidya ◽  
Jens Ducrée ◽  
Conor Ryan
Keyword(s):  
Electronic Health Records ◽  
Autonomous Agents ◽  
Knowledge Integration ◽  
Clinical Decision Making ◽  
User Authentication ◽  
Clinical Decision ◽  
Knowledge Graph ◽  
Autonomous Agent ◽  
Health Records ◽  
Electronic Health

In this article, we discuss a data sharing and knowledge integration framework through autonomous agents with blockchain for implementing Electronic Health Records (EHR). This will enable us to augment existing blockchain-based EHR Systems. We discuss how major concerns in the health industry, i.e., trust, security and scalability, can be addressed by transitioning from existing models to convergence of the three technologies – blockchain, agent-based modeling, and knowledge graph in a decentralized ecosystem. Each autonomous agent is responsible for instantiating key processes, such as user authentication and authorization, smart contracts, and knowledge graph generation through data integration among the participating stakeholders in the network. We discuss a layered approach for the design of the proposed system leading to an enhanced, safer clinical decision-making system. This can pave the way toward more informed and engaged patients and citizens by delivering personalized healthcare.

scholarly journals Economic impact of clinical decision support interventions based on electronic health records

2020 ◽  
Author(s):  
Daniel Lewkowicz ◽  
Attila Wohlbrandt ◽  
Erwin Boettinger
Keyword(s):  
Decision Support ◽  
Economic Evaluation ◽  
Electronic Health Records ◽  
Economic Impact ◽  
Clinical Decision Support ◽  
Healthcare Expenditure ◽  
Clinical Decision ◽  
Health Records ◽  
Cost Drivers ◽  
Electronic Health

Abstract Background Unnecessary healthcare utilization, non-adherence to current clinical guidelines, or insufficient personalized care are perpetual challenges and remain potential major cost-drivers for healthcare systems around the world. Implementing decision support systems into clinical care is promised to improve quality of care and thereby yield substantial effects on reducing healthcare expenditure. In this article, we evaluate the economic impact of clinical decision support (CDS) interventions based on electronic health records (EHR).Methods We searched for studies published after 2014 using MEDLINE, CENTRAL, WEB OF SCIENCE, EBSCO, and TUFTS CEA registry databases that encompass an economic evaluation or consider cost outcome measures of EHR based CDS interventions. Thereupon, we identified best practice application areas and categorized the investigated interventions according to an existing taxonomy of front-end CDS tools. Results and discussion Twenty-seven studies are investigated in this review. Of those, twenty-two studies indicate a reduction of healthcare expenditure after implementing an EHR based CDS system, especially towards prevalent application areas, such as unnecessary laboratory testing, duplicate order entry, efficient transfusion practice, or reduction of antibiotic prescriptions. On the contrary, order facilitators and undiscovered malfunctions revealed to be threats and could lead to new cost drivers in healthcare. While high upfront and maintenance costs of CDS systems are a worldwide implementation barrier, most studies do not consider implementation cost. Finally, four included economic evaluation studies report mixed monetary outcome results and thus highlight the importance of further high-quality economic evaluations for these CDS systems. Conclusion Current research studies lack consideration of comparative cost-outcome metrics as well as detailed cost components in their analyses. Nonetheless, the positive economic impact of EHR based CDS interventions is highly promising, especially with regard to reducing waste in healthcare.

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