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| Verfasst von: | Brehmer, Alexander [VerfasserIn]  |
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| | Sauer, Christopher Martin [VerfasserIn] |
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| | Rodríguez, Jayson Salazar [VerfasserIn] |
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| | Herrmann, Kelsey [VerfasserIn] |
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| | Kim, Moon [VerfasserIn] |
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| | Keyl, Julius [VerfasserIn] |
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| | Bahnsen, Fin Hendrik [VerfasserIn] |
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| | Frank, Benedikt [VerfasserIn] |
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| | Köhrmann, Martin [VerfasserIn] |
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| | Rassaf, Tienush [VerfasserIn] |
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| | Mahabadi, Amir-Abbas [VerfasserIn] |
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| | Hadaschik, Boris [VerfasserIn] |
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| | Darr, Christopher [VerfasserIn] |
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| | Herrmann, Ken [VerfasserIn] |
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| | Tan, Susanne [VerfasserIn] |
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| | Buer, Jan [VerfasserIn] |
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| | Brenner, Thorsten [VerfasserIn] |
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| | Reinhardt, Christian [VerfasserIn] |
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| | Nensa, Felix [VerfasserIn] |
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| | Gertz, Michael [VerfasserIn] |
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| | Egger, Jan [VerfasserIn] |
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| | Kleesiek, Jens Philipp [VerfasserIn] |
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| Titel: | Establishing medical intelligence |
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| Titelzusatz: | leveraging fast healthcare interoperability resources to improve clinical management : retrospective cohort and clinical implementation study |
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| Verf.angabe: | Alexander Brehmer, MSc; Christopher Martin Sauer, MD, MPH, PhD; Jayson Salazar Rodríguez, MSc; Kelsey Herrmann, MD; Moon Kim, MD; Julius Keyl, MD; Fin Hendrik Bahnsen, MSc; Benedikt Frank, MD; Martin Köhrmann, Prof Dr Med; Tienush Rassaf, Prof Dr Med; Amir-Abbas Mahabadi, MD; Boris Hadaschik, MD; Christopher Darr, MD; Ken Herrmann, Prof Dr Med; Susanne Tan, Prof Dr Med; Jan Buer, Prof Dr Med; Thorsten Brenner, Prof Dr Med; Hans Christian Reinhardt, Prof Dr Med; Felix Nensa, PhD, Prof Dr Med; Michael Gertz, Prof Dr; Jan Egger, PhD; Jens Kleesiek, PhD, Prof Dr Med |
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| E-Jahr: | 2024 |
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| Jahr: | 31.10.2024 |
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| Umfang: | 12 S. |
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| Illustrationen: | Illustrationen |
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| Fussnoten: | Gesehen am 02.07.2025 |
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| Titel Quelle: | Enthalten in: Journal of medical internet research |
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| Ort Quelle: | Richmond, Va. : Healthcare World, 1999 |
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| Jahr Quelle: | 2024 |
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| Band/Heft Quelle: | 26(2024), 1, Artikel-ID e55148, Seite 1-12 |
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| ISSN Quelle: | 1438-8871 |
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| Abstract: | Background: FHIR (Fast Healthcare Interoperability Resources) has been proposed to enable health data interoperability. So far, its applicability has been demonstrated for selected research projects with limited data. Objective: This study aimed to design and implement a conceptual medical intelligence framework to leverage real-world care data for clinical decision-making. Methods: A Python package for the use of multimodal FHIR data (FHIRPACK [FHIR Python Analysis Conversion Kit]) was developed and pioneered in 5 real-world clinical use cases, that is, myocardial infarction, stroke, diabetes, sepsis, and prostate cancer. Patients were identified based on the ICD-10 (International Classification of Diseases, Tenth Revision) codes, and outcomes were derived from laboratory tests, prescriptions, procedures, and diagnostic reports. Results were provided as browser-based dashboards. Results: For 2022, a total of 1,302,988 patient encounters were analyzed. (1) Myocardial infarction: in 72.7% (261/359) of cases, medication regimens fulfilled guideline recommendations. (2) Stroke: out of 1277 patients, 165 received thrombolysis and 108 thrombectomy. (3) Diabetes: in 443,866 serum glucose and 16,180 glycated hemoglobin A1c measurements from 35,494 unique patients, the prevalence of dysglycemic findings was 39% (13,887/35,494). Among those with dysglycemia, diagnosis was coded in 44.2% (6138/13,887) of the patients. (4) Sepsis: In 1803 patients, Staphylococcus epidermidis was the primarily isolated pathogen (773/2672, 28.9%) and piperacillin and tazobactam was the primarily prescribed antibiotic (593/1593, 37.2%). (5) PC: out of 54, three patients who received radical prostatectomy were identified as cases with prostate-specific antigen persistence or biochemical recurrence. Conclusions: Leveraging FHIR data through large-scale analytics can enhance health care quality and improve patient outcomes across 5 clinical specialties. We identified (1) patients with sepsis requiring less broad antibiotic therapy, (2) patients with myocardial infarction who could benefit from statin and antiplatelet therapy, (3) patients who had a stroke with longer than recommended times to intervention, (4) patients with hyperglycemia who could benefit from specialist referral, and (5) patients with PC with early increases in cancer markers. |
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| DOI: | doi:10.2196/55148 |
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| URL: | Bitte beachten Sie: Dies ist ein Bibliographieeintrag. Ein Volltextzugriff für Mitglieder der Universität besteht hier nur, falls für die entsprechende Zeitschrift/den entsprechenden Sammelband ein Abonnement besteht oder es sich um einen OpenAccess-Titel handelt.
Volltext: https://doi.org/10.2196/55148 |
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| | Volltext: https://www.jmir.org/2024/1/e55148 |
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| | DOI: https://doi.org/10.2196/55148 |
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| Datenträger: | Online-Ressource |
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| Sprache: | eng |
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| K10plus-PPN: | 1929536178 |
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| Verknüpfungen: | → Zeitschrift |
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Establishing medical intelligence / Brehmer, Alexander [VerfasserIn]; 31.10.2024 (Online-Ressource)
