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

Abstract

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.

Clinical trial registration: ClinicalTrials.gov NCT03439449.

Keywords: acute coronary syndrome; artificial intelligence; chest pain; medical history taking; medical informatics.

Graphical abstract

Figure 1.

User interface and examples of questions in the CHT program on a tablet.

Figure 2.

Proportions of calculations of a complete risk score using CHT data, stratified by age. Data are presented as mean values with 95% CIs.

Figure 3.

Proportions of calculations of a complete risk score using CHT data, stratified by birth region. Data are presented as mean values with 95% CIs. Europe: birth region in Europe outside the Nordic countries.

Figure 4.

Proportions of calculations of a complete risk score using CHT data, stratified by occupation status. Data are presented as mean values with 95% CIs.

Figure 5.

Reclassifications if risk scores derived from CHT had been used for management instead of standard care, and the potential impact on admission rates. Standard care (left) vs risk scores using CHT (right). Analysis made in cases with sufficient data to calculate a clinically decisive risk score and available data on disposition in the ED. Flows indicate patient transitions from discharged or admitted to low risk and not low risk categories, had risk scores derived from CHT been used. Admission was defined as admission to a ward or cardiology inpatient day-care-unit and discharged as sent home from the ED.