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Schleyer T, Robinson B, Parmar S, Janowiak D, Gibson PJ, Spangler V. Toxicology Test Results for Public Health Surveillance of the Opioid Epidemic: Retrospective Analysis. Online J Public Health Inform 2023; 15:e50936. [PMID: 38046561 PMCID: PMC10689049 DOI: 10.2196/50936] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2020] [Accepted: 01/11/2023] [Indexed: 12/05/2023] Open
Abstract
Background Addressing the opioid epidemic requires timely insights into population-level factors, such as trends in prevalence of legal and illegal substances, overdoses, and deaths. Objective This study aimed to examine whether toxicology test results of living individuals from a variety of sources could be useful in surveilling the opioid epidemic. Methods A retrospective analysis standardized, merged, and linked toxicology results from 24 laboratories in Marion County, Indiana, United States, from September 1, 2018, to August 31, 2019. The data set consisted of 33,787 Marion County residents and their 746,681 results. We related the data to general Marion County demographics and compared alerts generated by toxicology results to opioid overdose-related emergency department visits. Nineteen domain experts helped prototype analytical visualizations. Main outcome measures included test positivity in the county and by ZIP code; selected demographics of individuals with toxicology results; and correlation of toxicology results with opioid overdose-related emergency department visits. Results Four percent of Marion County residents had at least 1 toxicology result. Test positivity rates ranged from 3% to 19% across ZIP codes. Males were underrepresented in the data set. Age distribution resembled that of Marion County. Alerts for opioid toxicology results were not correlated with opioid overdose-related emergency department visits. Conclusions Analyzing toxicology results at scale was impeded by varying data formats, completeness, and representativeness; changes in data feeds; and patient matching difficulties. In this study, toxicology results did not predict spikes in opioid overdoses. Larger, more rigorous and well-controlled studies are needed to assess the utility of toxicology tests in predicting opioid overdose spikes.
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Affiliation(s)
- Titus Schleyer
- Center for Biomedical Informatics Regenstrief Institute, Inc Indianapolis, IN United States
- School of Medicine Indiana University Indianapolis, IN United States
| | | | | | | | - P Joseph Gibson
- Marion County Public Health Department Indianapolis, GA United States
| | - Val Spangler
- hc1 Insights, Inc Indianapolis, IN United States
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Tamposis I, Tsougos I, Karatzas A, Vassiou K, Vlychou M, Tzortzis V. PCaGuard: A Software Platform to Support Optimal Management of Prostate Cancer. Appl Clin Inform 2022; 13:91-99. [PMID: 35045583 PMCID: PMC8769808 DOI: 10.1055/s-0041-1741481] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023] Open
Abstract
Background and Objective
Prostate cancer (PCa) is a severe public health issue and the most common cancer worldwide in men. Early diagnosis can lead to early treatment and long-term survival. The addition of the multiparametric magnetic resonance imaging in combination with ultrasound (mpMRI-U/S fusion) biopsy to the existing diagnostic tools improved prostate cancer detection. Use of both tools gradually increases in every day urological practice. Furthermore, advances in the area of information technology and artificial intelligence have led to the development of software platforms able to support clinical diagnosis and decision-making using patient data from personalized medicine.
Methods
We investigated the current aspects of implementation, architecture, and design of a health care information system able to handle and store a large number of clinical examination data along with medical images, and produce a risk calculator in a seamless and secure manner complying with data security/accuracy and personal data protection directives and standards simultaneously. Furthermore, we took into account interoperability support and connectivity to legacy and other information management systems. The platform was implemented using open source, modern frameworks, and development tools.
Results
The application showed that software platforms supporting patient follow-up monitoring can be effective, productive, and of extreme value, while at the same time, aiding toward the betterment medicine clinical workflows. Furthermore, it removes access barriers and restrictions to specialized care, especially for rural areas, providing the exchange of medical images and patient data, among hospitals and physicians.
Conclusion
This platform handles data to estimate the risk of prostate cancer detection using current state-of-the-art in eHealth systems and services while fusing emerging multidisciplinary and intersectoral approaches. This work offers the research community an open architecture framework that encourages the broader adoption of more robust and comprehensive systems in standard clinical practice.
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Affiliation(s)
- Ioannis Tamposis
- Department of Computer Science and Biomedical Informatics, University of Thessaly, Lamia, Greece
| | - Ioannis Tsougos
- Department of Medical Physics, Medical School, University of Thessaly, Larisa, Greece
| | - Anastasios Karatzas
- Department of Urology, Medical School, University of Thessaly, Larisa, Greece
| | - Katerina Vassiou
- Radiology and Anatomy Department, Medical School, University of Thessaly, Larisa, Greece
| | - Marianna Vlychou
- Radiology Department, Medical School, University of Thessaly, Larisa, Greece
| | - Vasileios Tzortzis
- Department of Urology, Medical School, University of Thessaly, Larisa, Greece
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iT2DMS: a Standard-Based Diabetic Disease Data Repository and its Pilot Experiment on Diabetic Retinopathy Phenotyping and Examination Results Integration. J Med Syst 2018; 42:131. [DOI: 10.1007/s10916-018-0939-0] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2018] [Accepted: 03/14/2018] [Indexed: 01/18/2023]
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Information Architecture for Perinatal Registration in the Netherlands. J Obstet Gynecol Neonatal Nurs 2017; 46:310-321. [PMID: 28089579 DOI: 10.1016/j.jogn.2016.11.011] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/01/2016] [Indexed: 11/21/2022] Open
Abstract
In the Netherlands, the perinatal registry has undergone significant changes in the past decades. The purpose of this article is to describe the current health care information architecture for the national perinatal registry, including how the national data set is arranged and how electronic messages are used to submit data. We provide implications for women's health care providers based on the creation and implementation of the Dutch perinatal registry system.
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Not The Ghost in The Machine: Transforming Patient Data into E-Learning Cases Within A Case-Based Blended Learning Framework For Medical Education. ACTA ACUST UNITED AC 2015. [DOI: 10.1016/j.sbspro.2015.04.106] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
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Pahl C, Zare M, Nilashi M, de Faria Borges MA, Weingaertner D, Detschew V, Supriyanto E, Ibrahim O. Role of OpenEHR as an open source solution for the regional modelling of patient data in obstetrics. J Biomed Inform 2015; 55:174-87. [PMID: 25900270 DOI: 10.1016/j.jbi.2015.04.004] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2014] [Revised: 03/19/2015] [Accepted: 04/10/2015] [Indexed: 10/23/2022]
Abstract
This work investigates, whether openEHR with its reference model, archetypes and templates is suitable for the digital representation of demographic as well as clinical data. Moreover, it elaborates openEHR as a tool for modelling Hospital Information Systems on a regional level based on a national logical infrastructure. OpenEHR is a dual model approach developed for the modelling of Hospital Information Systems enabling semantic interoperability. A holistic solution to this represents the use of dual model based Electronic Healthcare Record systems. Modelling data in the field of obstetrics is a challenge, since different regions demand locally specific information for the process of treatment. Smaller health units in developing countries like Brazil or Malaysia, which until recently handled automatable processes like the storage of sensitive patient data in paper form, start organizational reconstruction processes. This archetype proof-of-concept investigation has tried out some elements of the openEHR methodology in cooperation with a health unit in Colombo, Brazil. Two legal forms provided by the Brazilian Ministry of Health have been analyzed and classified into demographic and clinical data. LinkEHR-Ed editor was used to read, edit and create archetypes. Results show that 33 clinical and demographic concepts, which are necessary to cover data demanded by the Unified National Health System, were identified. Out of the concepts 61% were reused and 39% modified to cover domain requirements. The detailed process of reuse, modification and creation of archetypes is shown. We conclude that, although a major part of demographic and clinical patient data were already represented by existing archetypes, a significant part required major modifications. In this study openEHR proved to be a highly suitable tool in the modelling of complex health data. In combination with LinkEHR-Ed software it offers user-friendly and highly applicable tools, although the complexity built by the vast specifications requires expert networks to define generally excepted clinical models. Finally, this project has pointed out main benefits enclosing high coverage of obstetrics data on the Clinical Knowledge Manager, simple modelling, and wide network and support using openEHR. Moreover, barriers described are enclosing the allocation of clinical content to respective archetypes, as well as stagnant adaption of changes on the Clinical Knowledge Manager leading to redundant efforts in data contribution that need to be addressed in future works.
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Affiliation(s)
- Christina Pahl
- Department of Biomechatronics, Ilmenau University of Technology, Ilmenau, Thuringia, Germany; IJN-UTM Cardiovascular Engineering Centre, University of Technology Malaysia, Skudai, Johor, Malaysia.
| | - Mojtaba Zare
- Faculty of Computing, Universiti Technologi Malaysia, Johor, Malaysia
| | | | | | - Daniel Weingaertner
- Department of Informatics, Universidade Federal do Paraná, Curitiba, Paraná, Brazil
| | - Vesselin Detschew
- Institute of Biomedical Engineering and Informatics, Department of Biomedical Engineering, Ilmenau, Thuringia, Germany
| | - Eko Supriyanto
- IJN-UTM Cardiovascular Engineering Centre, University of Technology Malaysia, Skudai, Johor, Malaysia
| | - Othman Ibrahim
- Faculty of Computing, Universiti Technologi Malaysia, Johor, Malaysia
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Warner JL, Maddux SE, Hughes KS, Krauss JC, Yu PP, Shulman LN, Mayer DK, Hogarth M, Shafarman M, Stover Fiscalini A, Esserman L, Alschuler L, Koromia GA, Gonzaga Z, Ambinder EP. Development, implementation, and initial evaluation of a foundational open interoperability standard for oncology treatment planning and summarization. J Am Med Inform Assoc 2015; 22:577-86. [PMID: 25604811 DOI: 10.1093/jamia/ocu015] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2014] [Accepted: 10/28/2014] [Indexed: 11/13/2022] Open
Abstract
OBJECTIVE Develop and evaluate a foundational oncology-specific standard for the communication and coordination of care throughout the cancer journey, with early-stage breast cancer as the use case. MATERIALS AND METHODS Owing to broad uptake of the Health Level Seven (HL7) Consolidated Clinical Document Architecture (C-CDA) by health information exchanges and large provider organizations, we developed an implementation guide in congruence with C-CDA. The resultant product was balloted through the HL7 process and subsequently implemented by two groups: the Health Story Project (Health Story) and the Athena Breast Health Network (Athena). RESULTS The HL7 Implementation Guide for CDA, Release 2: Clinical Oncology Treatment Plan and Summary, DSTU Release 1 (eCOTPS) was successfully balloted and published as a Draft Standard for Trial Use (DSTU) in October 2013. Health Story successfully implemented the eCOTPS the 2014 meeting of the Healthcare Information and Management Systems Society (HIMSS) in a clinical vignette. During the evaluation and implementation of eCOPS, Athena identified two practical concerns: (1) the need for additional CDA templates specific to their use case; (2) the many-to-many mapping of Athena-defined data elements to eCOTPS. DISCUSSION Early implementation of eCOTPS has demonstrated successful vendor-agnostic transmission of oncology-specific data. The modularity enabled by the C-CDA framework ensures the relatively straightforward expansion of the eCOTPS to include other cancer subtypes. Lessons learned during the process will strengthen future versions of the standard. CONCLUSION eCOTPS is the first oncology-specific CDA standard to achieve HL7 DSTU status. Oncology standards will improve care throughout the cancer journey by allowing the efficient transmission of reliable, meaningful, and current clinical data between the many involved stakeholders.
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Affiliation(s)
- Jeremy L Warner
- Department of Medicine, Division of Hematology & Oncology, Vanderbilt University, Nashville, TN, USA Department of Biomedical Informatics, Vanderbilt University, Nashville, TN, USA
| | - Suzanne E Maddux
- Quality and Guidelines Division, American Society of Clinical Oncology, Alexandria, VA, USA
| | - Kevin S Hughes
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - John C Krauss
- Department of Internal Medicine, Division of Hematology/Oncology, University of Michigan, Ann Arbor, MI, USA
| | | | | | - Deborah K Mayer
- UNC Lineberger Comprehensive Cancer Center, Chapel Hill, NC, USA
| | - Mike Hogarth
- Department of Pathology and Laboratory Medicine, University of California, Davis, Sacramento, CA, USA
| | | | | | - Laura Esserman
- Department of Surgery, University of California, San Francisco, CA, USA Department of Radiology, University of California, San Francisco, CA, USA
| | | | | | | | - Edward P Ambinder
- Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
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