Institute for Artificial Intelligence in Medicine, University Hospital Essen, Essen, Germany.
Deptartment of Hematology and Stem Cell Transplantation, West German Cancer Center, German Cancer Consortium Partner Site Essen, Center for Molecular Biotechnology, University Hospital Essen, Essen, Germany.
J Med Internet Res. 2024 Oct 31;26:e55148. doi: 10.2196/55148.
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.
This study aimed to design and implement a conceptual medical intelligence framework to leverage real-world care data for clinical decision-making.
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.
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 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.
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.
FHIR（快速医疗互操作性资源）被提议用于实现医疗数据的互操作性。到目前为止，它的适用性已经在具有有限数据的选定研究项目中得到了证明。
本研究旨在设计和实施一个概念性的医疗智能框架，以便利用实际护理数据进行临床决策。
开发了一个用于使用多模态 FHIR 数据的 Python 包（FHIRPACK[FHIR Python 分析转换工具包]），并在 5 个实际临床用例中进行了先驱性研究，即心肌梗死、中风、糖尿病、脓毒症和前列腺癌。基于 ICD-10（国际疾病分类，第十版）代码识别患者，从实验室检查、处方、程序和诊断报告中得出结果。结果以基于浏览器的仪表板提供。
2022 年，共分析了 1302988 例患者就诊记录。（1）心肌梗死：在 261/359（72.7%）例患者中，药物治疗方案符合指南建议。（2）中风：在 1277 例患者中，165 例接受溶栓治疗，108 例接受血栓切除术。（3）糖尿病：在来自 35494 位不同患者的 443866 次血清葡萄糖和 16180 次糖化血红蛋白 A 测量中，发现 39%（13887/35494）的患者存在血糖异常。在血糖异常的患者中，有 44.2%（6138/13887）的患者被编码了诊断。（4）脓毒症：在 1803 例患者中，表皮葡萄球菌是主要分离病原体（773/2672，28.9%），哌拉西林他唑巴坦是主要处方抗生素（593/1593，37.2%）。（5）前列腺癌：在 54 例患者中，发现 3 例接受根治性前列腺切除术的患者为前列腺特异性抗原持续存在或生化复发的病例。
通过大规模分析利用 FHIR 数据可以提高 5 个临床专业的医疗质量和改善患者结局。我们发现（1）需要较少广谱抗生素治疗的脓毒症患者，（2）可以从他汀类药物和抗血小板治疗中获益的心肌梗死患者，（3）接受治疗的时间长于推荐时间的中风患者，（4）需要专科转诊的高血糖患者，（5）癌症标志物早期升高的前列腺癌患者。
