Helge Brandberg, Carl Johan Sundberg, Jonas Spaak, Sabine Koch, Thomas Kahan
{"title":"病史数据是否适合对急诊胸痛患者进行风险分层？在 CLEOS-CPDS 前瞻性队列研究中，将使用电脑病史采集系统收集的患者数据与医生在电子健康记录中记录的数据进行比较。","authors":"Helge Brandberg, Carl Johan Sundberg, Jonas Spaak, Sabine Koch, Thomas Kahan","doi":"10.1093/jamia/ocae110","DOIUrl":null,"url":null,"abstract":"<p><strong>Objective: </strong>In acute chest pain management, risk stratification tools, including medical history, are recommended. We compared the fraction of patients with sufficient clinical data obtained using computerized history taking software (CHT) versus physician-acquired medical history to calculate established risk scores and assessed the patient-by-patient agreement between these 2 ways of obtaining medical history information.</p><p><strong>Materials and methods: </strong>This was a prospective cohort study of clinically stable patients aged ≥ 18 years presenting to the emergency department (ED) at Danderyd University Hospital (Stockholm, Sweden) in 2017-2019 with acute chest pain and non-diagnostic ECG and serum markers. Medical histories were self-reported using CHT on a tablet. Observations on discrete variables in the risk scores were extracted from electronic health records (EHR) and the CHT database. The patient-by-patient agreement was described by Cohen's kappa statistics.</p><p><strong>Results: </strong>Of the total 1000 patients included (mean age 55.3 ± 17.4 years; 54% women), HEART score, EDACS, and T-MACS could be calculated in 75%, 74%, and 83% by CHT and in 31%, 7%, and 25% by EHR, respectively. The agreement between CHT and EHR was slight to moderate (kappa 0.19-0.70) for chest pain characteristics and moderate to almost perfect (kappa 0.55-0.91) for risk factors.</p><p><strong>Conclusions: </strong>CHT can acquire and document data for chest pain risk stratification in most ED patients using established risk scores, achieving this goal for a substantially larger number of patients, as compared to EHR data. The agreement between CHT and physician-acquired history taking is high for traditional risk factors and lower for chest pain characteristics.</p><p><strong>Clinical trial registration: </strong>ClinicalTrials.gov NCT03439449.</p>","PeriodicalId":50016,"journal":{"name":"Journal of the American Medical Informatics Association","volume":" ","pages":"1529-1539"},"PeriodicalIF":4.7000,"publicationDate":"2024-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11187423/pdf/","citationCount":"0","resultStr":"{\"title\":\"Are medical history data fit for risk stratification of patients with chest pain in emergency care? Comparing data collected from patients using computerized history taking with data documented by physicians in the electronic health record in the CLEOS-CPDS prospective cohort study.\",\"authors\":\"Helge Brandberg, Carl Johan Sundberg, Jonas Spaak, Sabine Koch, Thomas Kahan\",\"doi\":\"10.1093/jamia/ocae110\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Objective: </strong>In acute chest pain management, risk stratification tools, including medical history, are recommended. We compared the fraction of patients with sufficient clinical data obtained using computerized history taking software (CHT) versus physician-acquired medical history to calculate established risk scores and assessed the patient-by-patient agreement between these 2 ways of obtaining medical history information.</p><p><strong>Materials and methods: </strong>This was a prospective cohort study of clinically stable patients aged ≥ 18 years presenting to the emergency department (ED) at Danderyd University Hospital (Stockholm, Sweden) in 2017-2019 with acute chest pain and non-diagnostic ECG and serum markers. Medical histories were self-reported using CHT on a tablet. Observations on discrete variables in the risk scores were extracted from electronic health records (EHR) and the CHT database. The patient-by-patient agreement was described by Cohen's kappa statistics.</p><p><strong>Results: </strong>Of the total 1000 patients included (mean age 55.3 ± 17.4 years; 54% women), HEART score, EDACS, and T-MACS could be calculated in 75%, 74%, and 83% by CHT and in 31%, 7%, and 25% by EHR, respectively. The agreement between CHT and EHR was slight to moderate (kappa 0.19-0.70) for chest pain characteristics and moderate to almost perfect (kappa 0.55-0.91) for risk factors.</p><p><strong>Conclusions: </strong>CHT can acquire and document data for chest pain risk stratification in most ED patients using established risk scores, achieving this goal for a substantially larger number of patients, as compared to EHR data. The agreement between CHT and physician-acquired history taking is high for traditional risk factors and lower for chest pain characteristics.</p><p><strong>Clinical trial registration: </strong>ClinicalTrials.gov NCT03439449.</p>\",\"PeriodicalId\":50016,\"journal\":{\"name\":\"Journal of the American Medical Informatics Association\",\"volume\":\" \",\"pages\":\"1529-1539\"},\"PeriodicalIF\":4.7000,\"publicationDate\":\"2024-06-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11187423/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of the American Medical Informatics Association\",\"FirstCategoryId\":\"91\",\"ListUrlMain\":\"https://doi.org/10.1093/jamia/ocae110\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, INFORMATION SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of the American Medical Informatics Association","FirstCategoryId":"91","ListUrlMain":"https://doi.org/10.1093/jamia/ocae110","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
Are medical history data fit for risk stratification of patients with chest pain in emergency care? Comparing data collected from patients using computerized history taking with data documented by physicians in the electronic health record in the CLEOS-CPDS prospective cohort study.
Objective: In acute chest pain management, risk stratification tools, including medical history, are recommended. We compared the fraction of patients with sufficient clinical data obtained using computerized history taking software (CHT) versus physician-acquired medical history to calculate established risk scores and assessed the patient-by-patient agreement between these 2 ways of obtaining medical history information.
Materials and methods: This was a prospective cohort study of clinically stable patients aged ≥ 18 years presenting to the emergency department (ED) at Danderyd University Hospital (Stockholm, Sweden) in 2017-2019 with acute chest pain and non-diagnostic ECG and serum markers. Medical histories were self-reported using CHT on a tablet. Observations on discrete variables in the risk scores were extracted from electronic health records (EHR) and the CHT database. The patient-by-patient agreement was described by Cohen's kappa statistics.
Results: Of the total 1000 patients included (mean age 55.3 ± 17.4 years; 54% women), HEART score, EDACS, and T-MACS could be calculated in 75%, 74%, and 83% by CHT and in 31%, 7%, and 25% by EHR, respectively. The agreement between CHT and EHR was slight to moderate (kappa 0.19-0.70) for chest pain characteristics and moderate to almost perfect (kappa 0.55-0.91) for risk factors.
Conclusions: CHT can acquire and document data for chest pain risk stratification in most ED patients using established risk scores, achieving this goal for a substantially larger number of patients, as compared to EHR data. The agreement between CHT and physician-acquired history taking is high for traditional risk factors and lower for chest pain characteristics.
期刊介绍：
JAMIA is AMIA''s premier peer-reviewed journal for biomedical and health informatics. Covering the full spectrum of activities in the field, JAMIA includes informatics articles in the areas of clinical care, clinical research, translational science, implementation science, imaging, education, consumer health, public health, and policy. JAMIA''s articles describe innovative informatics research and systems that help to advance biomedical science and to promote health. Case reports, perspectives and reviews also help readers stay connected with the most important informatics developments in implementation, policy and education.
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