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Duda SN, Kennedy N, Conway D, Cheng AC, Nguyen V, Zayas-Cabán T, Harris PA. HL7 FHIR-based tools and initiatives to support clinical research: a scoping review. J Am Med Inform Assoc 2022; 29:1642-1653. [PMID: 35818340 PMCID: PMC9382376 DOI: 10.1093/jamia/ocac105] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2021] [Revised: 05/23/2022] [Accepted: 06/20/2022] [Indexed: 11/14/2022] Open
Abstract
OBJECTIVES The HL7® fast healthcare interoperability resources (FHIR®) specification has emerged as the leading interoperability standard for the exchange of healthcare data. We conducted a scoping review to identify trends and gaps in the use of FHIR for clinical research. MATERIALS AND METHODS We reviewed published literature, federally funded project databases, application websites, and other sources to discover FHIR-based papers, projects, and tools (collectively, "FHIR projects") available to support clinical research activities. RESULTS Our search identified 203 different FHIR projects applicable to clinical research. Most were associated with preparations to conduct research, such as data mapping to and from FHIR formats (n = 66, 32.5%) and managing ontologies with FHIR (n = 30, 14.8%), or post-study data activities, such as sharing data using repositories or registries (n = 24, 11.8%), general research data sharing (n = 23, 11.3%), and management of genomic data (n = 21, 10.3%). With the exception of phenotyping (n = 19, 9.4%), fewer FHIR-based projects focused on needs within the clinical research process itself. DISCUSSION Funding and usage of FHIR-enabled solutions for research are expanding, but most projects appear focused on establishing data pipelines and linking clinical systems such as electronic health records, patient-facing data systems, and registries, possibly due to the relative newness of FHIR and the incentives for FHIR integration in health information systems. Fewer FHIR projects were associated with research-only activities. CONCLUSION The FHIR standard is becoming an essential component of the clinical research enterprise. To develop FHIR's full potential for clinical research, funding and operational stakeholders should address gaps in FHIR-based research tools and methods.
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Affiliation(s)
- Stephany N Duda
- Vanderbilt Institute for Clinical and Translational Research, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- Department of Biomedical Informatics, Vanderbilt University School of Medicine, Nashville, Tennessee, USA
| | - Nan Kennedy
- Vanderbilt Institute for Clinical and Translational Research, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Douglas Conway
- Vanderbilt Institute for Clinical and Translational Research, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Alex C Cheng
- Vanderbilt Institute for Clinical and Translational Research, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- Department of Biomedical Informatics, Vanderbilt University School of Medicine, Nashville, Tennessee, USA
| | - Viet Nguyen
- Stratametrics LLC, Salt Lake City, Utah, USA
- HL7 Da Vinci Project, Ann Arbor, Michigan, USA
| | - Teresa Zayas-Cabán
- National Library of Medicine, National Institutes of Health, Bethesda, Maryland, USA
| | - Paul A Harris
- Vanderbilt Institute for Clinical and Translational Research, Vanderbilt University Medical Center, Nashville, Tennessee, USA
- Department of Biomedical Informatics, Vanderbilt University School of Medicine, Nashville, Tennessee, USA
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Tomlinson E, Goodman J, Loftus M, Bitto S, Carpenter E, Oddo R, Judis L, Ali S, Robinson WE, Carver M, Ganea M, McDonnell K, O'Neill D, Starbuck J, Johnson E, Meister E, Pohl J, Spildener J, Shurtleff S, Sovie S, Melendez C, Krebs P, Riley JD, Wensel C, Astbury C, Azzato EM, Bosler DS, Brock JE, Cook JR, Cheng YW, Tu ZJ, Cruise M, Henricks WH, Farkas DH. A Model for Design and Implementation of a Laboratory Information-Management System Specific for Molecular Pathology Laboratory Operations. J Mol Diagn 2022; 24:503-514. [PMID: 35101595 DOI: 10.1016/j.jmoldx.2022.01.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2021] [Revised: 12/07/2021] [Accepted: 01/18/2022] [Indexed: 11/16/2022] Open
Abstract
The Molecular Pathology Section, Cleveland Clinic (Cleveland, OH), has undergone enhancement of its testing portfolio and processes. An Excel 2013- and paper-based data-management system was replaced with a commercially available laboratory information-management system (LIMS) software application, a separate bioinformatics platform, customized test-interpretation applications, a dedicated sample-accessioning service, and a results-releasing software application. The customized LIMS solution manages complex workflows, large-scale data packets, and process automation. A customized approach was required because, in a survey of commercially available off-the-shelf software products, none met the diverse and complex needs of this molecular diagnostics service. The project utilized the expertise of clinical laboratorians, pathologists, genetics counselors, bioinformaticians, and systems analysts in partnering with software-engineering consultants to design and implement a solution. Concurrently, Agile software-building best practices were formulated, which may be emulated for scalable and cost-effective laboratory-authored software.
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Affiliation(s)
| | - Jennifer Goodman
- Robert J. Tomsich Pathology & Laboratory Medicine Institute, Cleveland Clinic, Cleveland, Ohio
| | - Margaret Loftus
- Robert J. Tomsich Pathology & Laboratory Medicine Institute, Cleveland Clinic, Cleveland, Ohio
| | - Stephen Bitto
- Robert J. Tomsich Pathology & Laboratory Medicine Institute, Cleveland Clinic, Cleveland, Ohio
| | - Erica Carpenter
- Robert J. Tomsich Pathology & Laboratory Medicine Institute, Cleveland Clinic, Cleveland, Ohio
| | - Richard Oddo
- Robert J. Tomsich Pathology & Laboratory Medicine Institute, Cleveland Clinic, Cleveland, Ohio
| | - LuAnn Judis
- Robert J. Tomsich Pathology & Laboratory Medicine Institute, Cleveland Clinic, Cleveland, Ohio
| | - Shabab Ali
- Semaphore Solutions, Victoria, British Columbia, Canada
| | | | - Miranda Carver
- Robert J. Tomsich Pathology & Laboratory Medicine Institute, Cleveland Clinic, Cleveland, Ohio
| | - Mariana Ganea
- Robert J. Tomsich Pathology & Laboratory Medicine Institute, Cleveland Clinic, Cleveland, Ohio
| | - Kristen McDonnell
- Robert J. Tomsich Pathology & Laboratory Medicine Institute, Cleveland Clinic, Cleveland, Ohio
| | - Diane O'Neill
- Robert J. Tomsich Pathology & Laboratory Medicine Institute, Cleveland Clinic, Cleveland, Ohio
| | - Jennifer Starbuck
- Robert J. Tomsich Pathology & Laboratory Medicine Institute, Cleveland Clinic, Cleveland, Ohio
| | - Eric Johnson
- Robert J. Tomsich Pathology & Laboratory Medicine Institute, Cleveland Clinic, Cleveland, Ohio
| | - Erik Meister
- Robert J. Tomsich Pathology & Laboratory Medicine Institute, Cleveland Clinic, Cleveland, Ohio
| | - Jonathan Pohl
- Robert J. Tomsich Pathology & Laboratory Medicine Institute, Cleveland Clinic, Cleveland, Ohio
| | - Jessica Spildener
- Robert J. Tomsich Pathology & Laboratory Medicine Institute, Cleveland Clinic, Cleveland, Ohio
| | - Sheila Shurtleff
- Robert J. Tomsich Pathology & Laboratory Medicine Institute, Cleveland Clinic, Cleveland, Ohio
| | - Sheryl Sovie
- Robert J. Tomsich Pathology & Laboratory Medicine Institute, Cleveland Clinic, Cleveland, Ohio
| | | | - Pamela Krebs
- Robert J. Tomsich Pathology & Laboratory Medicine Institute, Cleveland Clinic, Cleveland, Ohio
| | - Jacquelyn D Riley
- Robert J. Tomsich Pathology & Laboratory Medicine Institute, Cleveland Clinic, Cleveland, Ohio
| | - Christine Wensel
- Robert J. Tomsich Pathology & Laboratory Medicine Institute, Cleveland Clinic, Cleveland, Ohio
| | - Caroline Astbury
- Robert J. Tomsich Pathology & Laboratory Medicine Institute, Cleveland Clinic, Cleveland, Ohio
| | - Elizabeth M Azzato
- Robert J. Tomsich Pathology & Laboratory Medicine Institute, Cleveland Clinic, Cleveland, Ohio
| | - David S Bosler
- Robert J. Tomsich Pathology & Laboratory Medicine Institute, Cleveland Clinic, Cleveland, Ohio
| | - Jay E Brock
- Robert J. Tomsich Pathology & Laboratory Medicine Institute, Cleveland Clinic, Cleveland, Ohio
| | - James R Cook
- Robert J. Tomsich Pathology & Laboratory Medicine Institute, Cleveland Clinic, Cleveland, Ohio
| | - Yu-Wei Cheng
- Robert J. Tomsich Pathology & Laboratory Medicine Institute, Cleveland Clinic, Cleveland, Ohio
| | - Zheng Jin Tu
- Robert J. Tomsich Pathology & Laboratory Medicine Institute, Cleveland Clinic, Cleveland, Ohio
| | - Michael Cruise
- Robert J. Tomsich Pathology & Laboratory Medicine Institute, Cleveland Clinic, Cleveland, Ohio
| | - Walter H Henricks
- Robert J. Tomsich Pathology & Laboratory Medicine Institute, Cleveland Clinic, Cleveland, Ohio
| | - Daniel H Farkas
- Robert J. Tomsich Pathology & Laboratory Medicine Institute, Cleveland Clinic, Cleveland, Ohio.
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Alrahbi DA, Khan M, Gupta S, Modgil S, Chiappetta Jabbour CJ. Challenges for developing health-care knowledge in the digital age. JOURNAL OF KNOWLEDGE MANAGEMENT 2020. [DOI: 10.1108/jkm-03-2020-0224] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Purpose
Health-care knowledge is dispersed among different departments in a health care organization, which makes it difficult at times to provide quality care services to patients. Therefore, this study aims to identify the main challenges in adopting health information technology (HIT).
Design/methodology/approach
This study surveyed 148 stakeholders in 4 key categories [patients, health-care providers, United Arab Emirates (UAE) citizens and foresight experts] to identify the challenges they face in adopting health care technologies. Responses were analyzed using exploratory (EFA) and confirmatory factor analysis (CFA).
Findings
EFA revealed four key latent factors predicting resistance to HIT adoption, namely, organizational strategy (ORGS); technical barriers; readiness for big data and the internet of things (IoT); and orientation (ORI). ORGS accounted for the greatest amount of variance. CFA indicated that readiness for big data and the IoT was only moderately correlated with HIT adoption, but the other three factors were strongly correlated. Specific items relating to cost, the effectiveness and usability of the technology and the organization were strongly correlated with HIT adoption. These results indicate that, in addition to financial considerations, effective HIT adoption requires ensuring that technologies will be easy to implement to ensure their long-term use.
Research limitations/implications
The results indicate that readiness for big data and the IoT-related infrastructure poses a challenge to HIT adoption in the UAE context. Respondents believed that the infrastructure of big data can be helpful in more efficiently storing and sharing health-care information. On the technological side, respondents felt that they may experience a steep learning curve. Regarding ORI, stakeholders expected many more such initiatives from health-care providers to make it more knowledge-specific and proactive.
Practical implications
This study has implications for knowledge management in the health -care sector for information technologies. The HIT can help firms in creating a knowledge eco-system, which is not possible in a dispersed knowledge environment. The utilization of the knowledge base that emerged from the practices and data can help the health care sector to set new standards of information flow and other clinical services such as monitoring the self-health condition. The HIT can further influence the actions of the pharmaceutical and medical device industry.
Originality/value
This paper highlights the challenges in HIT adoption and the most prominent factors. The conceptual model was empirically tested after the collection of primary data from the UAE using stakeholder theory.
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Gullapalli RR. Evaluation of Commercial Next-Generation Sequencing Bioinformatics Software Solutions. J Mol Diagn 2019; 22:147-158. [PMID: 31751676 DOI: 10.1016/j.jmoldx.2019.09.007] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2019] [Revised: 09/03/2019] [Accepted: 09/23/2019] [Indexed: 12/14/2022] Open
Abstract
Next-generation sequencing (NGS) diagnostics continue to expand rapidly in clinical medicine. An ever-expanding menu of molecular biomarkers is deemed important for diagnostic, prognostic, and therapeutic assessment in patients. The increasing role of NGS in the clinic is driven mainly by the falling costs of sequencing. However, the data-intensive nature of NGS makes bioinformatic analysis a major challenge to many clinical laboratories. Critically needed NGS bioinformatics personnel are hard to recruit and retain in small- to mid-size clinical laboratories. Also, NGS software often lacks the scalability necessary for expanded clinical laboratory testing volumes. Commercial software solutions aim to bridge the bioinformatics barrier via turnkey informatics solutions tailored specifically for the clinical workplace. Yet, there has been no systematic assessment of these software solutions thus far. This article presents an end-to-end vendor evaluation experience of commercial NGS bioinformatics solutions. Six different commercial vendor solutions were assessed systematically. Key metrics of NGS software evaluation to aid in the robust assessment of software solutions are described. Comprehensive feedback, provided by the TriCore Reference Laboratories molecular pathology team, enabled the final vendor selection. Many key lessons were learned during the software evaluation process, which are described herein. This article aims to provide a detailed road map for small- to mid-size clinical laboratories interested in evaluating commercial bioinformatics solutions available in the marketplace.
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Affiliation(s)
- Rama R Gullapalli
- Departments of Pathology and Chemical and Biological Engineering, University of New Mexico, Albuquerque, New Mexico.
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