Alexander Brehmer, Christopher Martin Sauer, Jayson Salazar Rodríguez, Kelsey Herrmann, Moon Kim, Julius Keyl, Fin Hendrik Bahnsen, Benedikt Frank, Martin Köhrmann, Tienush Rassaf, Amir-Abbas Mahabadi, Boris Hadaschik, Christopher Darr, Ken Herrmann, Susanne Tan, Jan Buer, Thorsten Brenner, Hans Christian Reinhardt, Felix Nensa, Michael Gertz, Jan Egger, Jens Kleesiek
{"title":"建立医疗智能--利用 FHIR 改善临床管理:一项回顾性队列和临床实施研究。","authors":"Alexander Brehmer, Christopher Martin Sauer, Jayson Salazar Rodríguez, Kelsey Herrmann, Moon Kim, Julius Keyl, Fin Hendrik Bahnsen, Benedikt Frank, Martin Köhrmann, Tienush Rassaf, Amir-Abbas Mahabadi, Boris Hadaschik, Christopher Darr, Ken Herrmann, Susanne Tan, Jan Buer, Thorsten Brenner, Hans Christian Reinhardt, Felix Nensa, Michael Gertz, Jan Egger, Jens Kleesiek","doi":"10.2196/55148","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>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.</p><p><strong>Objective: </strong>This study aimed to design and implement a conceptual medical intelligence framework to leverage real-world care data for clinical decision-making.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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 A<sub>1c</sub> 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.</p><p><strong>Conclusions: </strong>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.</p>","PeriodicalId":16337,"journal":{"name":"Journal of Medical Internet Research","volume":" ","pages":"e55148"},"PeriodicalIF":5.8000,"publicationDate":"2024-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11565078/pdf/","citationCount":"0","resultStr":"{\"title\":\"Establishing Medical Intelligence-Leveraging Fast Healthcare Interoperability Resources to Improve Clinical Management: Retrospective Cohort and Clinical Implementation Study.\",\"authors\":\"Alexander Brehmer, Christopher Martin Sauer, Jayson Salazar Rodríguez, Kelsey Herrmann, Moon Kim, Julius Keyl, Fin Hendrik Bahnsen, Benedikt Frank, Martin Köhrmann, Tienush Rassaf, Amir-Abbas Mahabadi, Boris Hadaschik, Christopher Darr, Ken Herrmann, Susanne Tan, Jan Buer, Thorsten Brenner, Hans Christian Reinhardt, Felix Nensa, Michael Gertz, Jan Egger, Jens Kleesiek\",\"doi\":\"10.2196/55148\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>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.</p><p><strong>Objective: </strong>This study aimed to design and implement a conceptual medical intelligence framework to leverage real-world care data for clinical decision-making.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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 A<sub>1c</sub> 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.</p><p><strong>Conclusions: </strong>Leveraging FHIR data through large-scale analytics can enhance health care quality and improve patient outcomes across 5 clinical specialties. 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Establishing Medical Intelligence-Leveraging Fast Healthcare Interoperability Resources to Improve Clinical Management: Retrospective Cohort and Clinical Implementation Study.
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.
期刊介绍:
The Journal of Medical Internet Research (JMIR) is a highly respected publication in the field of health informatics and health services. With a founding date in 1999, JMIR has been a pioneer in the field for over two decades.
As a leader in the industry, the journal focuses on digital health, data science, health informatics, and emerging technologies for health, medicine, and biomedical research. It is recognized as a top publication in these disciplines, ranking in the first quartile (Q1) by Impact Factor.
Notably, JMIR holds the prestigious position of being ranked #1 on Google Scholar within the "Medical Informatics" discipline.