A methodology based on openEHR archetypes and software agents for developing e-health applications reusing legacy systems

Moraes, João Luís Cardoso de; Souza, Wanderley Lopes de; Pires, Luís Ferreira; Prado, Antonio Francisco do

doi:10.1016/j.cmpb.2016.07.013

Cited by 26 publications

(7 citation statements)

References 23 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Yuksel et al [53] developed the SALUS platform (Scalable, standard-based Interoperability Framework for Sustainable Proactive Post Market Safety Studies), an ontology-based interoperability framework designed to conduct observational studies from data extracted from different data sources. Moraes et al [54] proposed a methodology for the exchange of information through multi-agent systems based on OpenEHR used for cardiac surgery planning. Rac-Albu et al [55] proposed a method, based on HL7 v2, for exchanging medical documents seeking the interoperability of health data in Romania.…”

Section: Discussionmentioning

confidence: 99%

An eHealth Platform for the Support of a Brazilian Regional Network of Mental Health Care (eHealth-Interop): Development of an Interoperability Platform for Mental Care Integration

et al. 2018

View full text Add to dashboard Cite

BackgroundThe electronic exchange of health-related data can support different professionals and services to act in a more coordinated and transparent manner and make the management of health service networks more efficient. Although mental health care is one of the areas that can benefit from a secure health information exchange (HIE), as it usually involves long-term and multiprofessional care, there are few published studies on this topic, particularly in low- and middle-income countries.ObjectiveThe aim of this study was to design, implement, and evaluate an electronic health (eHealth) platform that allows the technical and informational support of a Brazilian regional network of mental health care. This solution was to enable HIE, improve data quality, and identify and monitor patients over time and in different services.MethodsThe proposed platform is based on client-server architecture to be deployed on the Web following a Web services communication model. The interoperability information model was based on international and Brazilian health standards. To test platform usage, we have utilized the case of the mental health care network of the XIII Regional Health Department of the São Paulo state, Brazil. Data were extracted from 5 different sources, involving 26 municipalities, and included national demographic data, data from primary health care, data from requests for psychiatric hospitalizations performed by community services, and data obtained from 2 psychiatric hospitals about hospitalizations. Data quality metrics such as accuracy and completeness were evaluated to test the proposed solution.ResultsThe eHealth-Interop integration platform was designed, developed, and tested. It contains a built-in terminology server and a record linkage module to support patients’ identification and deduplication. The proposed interoperability environment was able to integrate information in the mental health care network case with the support of 5 international and national terminologies. In total, 27,353 records containing demographic and clinical data were integrated into eHealth-Interop. Of these records, 34.91% (9548/27,353) were identified as patients who were present in more than 1 data source with different levels of accuracy and completeness. The data quality analysis was performed on 26 demographic attributes for each integrable patient record, totaling 248,248 comparisons. In general, it was possible to achieve an improvement of 18.40% (45,678/248,248) in completeness and 1.10% (2731/248,248) in syntactic accuracy over the test dataset after integration and deduplication.ConclusionsThe proposed platform established an eHealth solution to fill the gap in the availability and quality of information within a network of health services to improve the continuity of care and the health services management. It has been successfully applied in the context of mental health care and is flexible to be tested in other areas of care.

show abstract

Section: Discussionmentioning

confidence: 99%

An eHealth Platform for the Support of a Brazilian Regional Network of Mental Health Care (eHealth-Interop): Development of an Interoperability Platform for Mental Care Integration

et al. 2018

View full text Add to dashboard Cite

show abstract

“…Furthermore, there are four main categories of archetypes, including COMPOSITION, SECTION, ENTRY, and CLUSTER, each defined as part of the openEHR RM. A COMPOSITION is a container class, whereas a SECTION is an organizing class, each containing ENTRY objects [16]. The ENTRY class is further specialized into ADMIN_ENTRY, OBSERVATION, EVALUATION, INSTRUCTION, and ACTION subclasses, of which the latter four are kinds of CARE_ENTRY.…”

Section: Methodsmentioning

confidence: 99%

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

Yang

Huang

2019

J Med Internet Res

View full text Add to dashboard Cite

2 For purposes this framework, unless otherwise noted, the term drug refers both to a drug approved under section 505(c) or (j) of the Federal Food, Drug, and Cosmetic Act (FD&C Act) and to biological products licensed under section 351 of the Public Health Service Act (PHS Act) 42 USC 262. 3 In this document, when we refer to the use of RWE to support a regulatory decision, we mean that the evidence provides support for or helps provide support for the regulatory decision. 4 FDA issued the guidance Use of Real-World Evidence to Support Regulatory Decision-Making for Medical Devices on August 31, 2017. Real-World Data (RWD) are data relating to patient health status and/or the delivery of health care routinely collected from a variety of sources. Real-World Evidence (RWE) is the clinical evidence about the usage and potential benefits or risks of a medical product derived from analysis of RWD.

show abstract

“…datatypes, eligible values, cardinalities etc. [3].…”

Section: Introductionmentioning

confidence: 99%

Preliminary Analysis of Structured Reporting in the HiGHmed Use Case Cardiology: Challenges and Measures

Kindermann

Tute

Benda

et al. 2021

German Medical Data Sciences: Bringing Data to Life

View full text Add to dashboard Cite

The HiGHmed consortium aims to create a shared information governance framework to integrate clinical routine data. One challenge is the replacement of unstructured reporting (e.g. doctoral letters) with structured reporting in clinical routine. The Heidelberg cardiology department evaluates dynamic PDF forms for structured data reporting of heart failure (HF) patients. In this use case, we aim to identify potential caveats or shortcomings in data processing at an early stage. We employed data mining strategies to detect patterns related to incomplete or false data, which we found to be present among all data types. We then discuss the characteristics of the baseline patient cohort in Heidelberg to find out about specific peculiarities and potential biases, which may be site-specific. Briefly, our patient population is predominantly male (67%), NYHA I & II are the most common severity classes, NYHA IV is missing entirely. Most patients have a dilated cardiomyopathy (DCM) or coronary heart disease (CHD) diagnosed as their cause of HF. Finally, we also analyzed how comorbidities and risk factors relate to specific disease entities of heart failure patients. Family anamnesis was more frequent among cardiomyopathy patients than among CHD patients, who show a more dominating presence of dyslipidemia instead. Generally, the most dominant risk factor was arterial hypertension, while at the other end of the scale alcoholism appears to be underreported.

show abstract

A methodology based on openEHR archetypes and software agents for developing e-health applications reusing legacy systems

Cited by 26 publications

References 23 publications

An eHealth Platform for the Support of a Brazilian Regional Network of Mental Health Care (eHealth-Interop): Development of an Interoperability Platform for Mental Care Integration

An eHealth Platform for the Support of a Brazilian Regional Network of Mental Health Care (eHealth-Interop): Development of an Interoperability Platform for Mental Care Integration

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

Preliminary Analysis of Structured Reporting in the HiGHmed Use Case Cardiology: Challenges and Measures

Contact Info

Product

Resources

About