Literature DB >> 30066031

Patients Decision Aid System Based on FHIR Profiles.

Ilia Semenov1, Georgy Kopanitsa2, Dmitry Denisov1, Yakovenko Alexandr3, Roman Osenev1, Yury Andreychuk1.   

Abstract

Patients are becoming more and more involved in clinical decision-making process. Several factors support this process. Advances in omics allows individualization of diagnosis and treatment. Patient awareness and easy availability of data on the Internet allows patients to become informed decision makers when it comes even to disease management. Mass media emphasize the issue of medical errors, making patients demanding for quality in medical care. In some healthcare settings, patents face a problem of interpreting medical data and making decisions on treatment tactics without having a doctor, who could potentially support them. Delegating this task to a Patient Decision Aide system can add automatically generated recommendations to result reports without adding significant workload on the doctors, increase patients' motivation and support their decisions. We have implemented a patient decision aid system based on the productions rules, which: Collects data from available sources; Automatically analyses and interprets laboratory test results; Recommends running additional tests for a more precise diagnostic; Delivers automatically generated reports to doctors and patients in a natural language. To achieve semantic interoperability with other systems we have implemented a FHIR engine. The knowledge base has been organized as a graph structure. The application is structured as a set of lightly coupled services, which implement the logic of the decision support system. In total, we have modelled 365 nodes of test components, 5084 nodes of inference rules, 49932 connections and 3072 blocks of text for medical certificates. The findings of the research provide a deep understanding of how the semantically interoperable clinical decision support systems are implemented. Advances in notification the patients with the elements of patient decision aid is important for clinical data management, and for patients' empowerment and protection. We suppose that the system empowering patients in such way can play a meaningful role in helping patients to make informed decisions during the process of diagnostics and treatment.

Entities:  

Keywords:  Decision support; First order predicates; Laboratory information system; Telemedicine

Mesh:

Year:  2018        PMID: 30066031     DOI: 10.1007/s10916-018-1016-4

Source DB:  PubMed          Journal:  J Med Syst        ISSN: 0148-5598            Impact factor:   4.460


  49 in total

1.  Knowledge acquisition in the fuzzy knowledge representation framework of a medical consultation system.

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Journal:  Artif Intell Med       Date:  2004-01       Impact factor: 5.326

2.  Model driven development of clinical information sytems using openEHR.

Authors:  Koray Atalag; Hong Yul Yang; Ewan Tempero; Jim Warren
Journal:  Stud Health Technol Inform       Date:  2011

3.  Implementation of a Clinical Decision Support System for Interpretation of Laboratory Tests for Patients.

Authors:  Ilya Semenov; Georgy Kopanitsa; Anatoly Karpov; Georgy Lakovenko; Andrey Laskovenko
Journal:  Stud Health Technol Inform       Date:  2016

4.  Problems in interpretation of clinical laboratory test results.

Authors:  J Romatowski
Journal:  J Am Vet Med Assoc       Date:  1994-10-15       Impact factor: 1.936

5.  Evaluation Study for an ISO 13606 Archetype Based Medical Data Visualization Method.

Authors:  Georgy Kopanitsa
Journal:  J Med Syst       Date:  2015-07-10       Impact factor: 4.460

6.  Implementation and evaluation of an integrated computerized asthma management system in a pediatric emergency department: a randomized clinical trial.

Authors:  Judith W Dexheimer; Thomas J Abramo; Donald H Arnold; Kevin Johnson; Yu Shyr; Fei Ye; Kang-Hsien Fan; Neal Patel; Dominik Aronsky
Journal:  Int J Med Inform       Date:  2014-08-08       Impact factor: 4.046

7.  Usability characteristics of self-administered computer-assisted interviewing in the emergency department: factors affecting ease of use, efficiency, and entry error.

Authors:  D B Herrick; A Nakhasi; B Nelson; S Rice; P A Abbott; A S Saber Tehrani; R E Rothman; H P Lehmann; D E Newman-Toker
Journal:  Appl Clin Inform       Date:  2013-06-19       Impact factor: 2.342

Review 8.  Maximizing the healthcare environment: a systematic review exploring the potential of computer technology to promote self-management of chronic illness in healthcare settings.

Authors:  Máirtín S McDermott; Alison E While
Journal:  Patient Educ Couns       Date:  2013-04-06

9.  Creating personalised clinical pathways by semantic interoperability with electronic health records.

Authors:  Hua-Qiong Wang; Jing-Song Li; Yi-Fan Zhang; Muneou Suzuki; Kenji Araki
Journal:  Artif Intell Med       Date:  2013-03-05       Impact factor: 5.326

10.  Regenstrief Institute's Medical Gopher: a next-generation homegrown electronic medical record system.

Authors:  Jon D Duke; Justin Morea; Burke Mamlin; Douglas K Martin; Linas Simonaitis; Blaine Y Takesue; Brian E Dixon; Paul R Dexter
Journal:  Int J Med Inform       Date:  2013-12-14       Impact factor: 4.046

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  4 in total

1.  Structurally Mapping Healthcare Data to HL7 FHIR through Ontology Alignment.

Authors:  Athanasios Kiourtis; Argyro Mavrogiorgou; Andreas Menychtas; Ilias Maglogiannis; Dimosthenis Kyriazis
Journal:  J Med Syst       Date:  2019-02-05       Impact factor: 4.460

2.  Study of patients' attitude to automatic interpretation of laboratory test results and its influence on follow-up rate.

Authors:  Georgy Kopanitsa
Journal:  BMC Med Inform Decis Mak       Date:  2022-03-27       Impact factor: 2.796

3.  Experience in Developing an FHIR Medical Data Management Platform to Provide Clinical Decision Support.

Authors:  Ilia Semenov; Roman Osenev; Sergey Gerasimov; Georgy Kopanitsa; Dmitry Denisov; Yuriy Andreychuk
Journal:  Int J Environ Res Public Health       Date:  2019-12-20       Impact factor: 3.390

Review 4.  New Standards for Clinical Decision Support: A Survey of The State of Implementation.

Authors:  Peter Taber; Christina Radloff; Guilherme Del Fiol; Catherine Staes; Kensaku Kawamoto
Journal:  Yearb Med Inform       Date:  2021-09-03
  4 in total

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