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Determining Time of Symptom Onset in Patients With Acute Coronary Syndromes: Agreement Between Medical Record and Interview Data.

ABSTRACT: Prehospital delay, the time of symptom onset until the time of hospital arrival, for patients with symptoms of acute coronary syndrome (ACS) is frequently used to determine the course of care. Total ischemic time (time for symptom onset until the time of first coronary artery balloon inflation) is another criterion for quality of care for patients experiencing ST-segment elevation myocardial infarction. However, obtaining the exact time of symptom onset, the starting point of both time intervals, is challenging. Currently 2 methods are used to obtain the time of symptom onset: abstraction of data from the medical record and structured interviews done after the acute event. It is not clear whether these methods are equally accurate.Using identified search terms, PubMed and the Cumulative Index to Nursing and Allied Health Literature were searched for articles published from 1990 to 2014 to identify studies that examined agreement between the 2 data sources to determine prehospital delay in patients with ACS.Five studies examined the accuracy and/or agreement of prehospital delay by medical record review and structured patient interviews. In these studies, the percentage of missing/incomplete data in the medical record was higher compared with interviews (14%-40% vs 12%-13%). Three of the 4 studies that compared the 2 data sources reported more than 50% disagreement, with the time of symptom onset starting sooner when obtained by interview compared with the time recorded in their medical record at hospital presentation.There is a need for a consistent, reliable method to assess the time of symptom onset in patients with ACS. To ensure the accuracy of data collected for the medical record, training of emergency and critical care clinicians should (1) emphasize the importance of assessing symptoms broadly, (2) provide tips on interviewing techniques to help patients pinpoint the time of symptom onset, and (3) instill the value of complete documentation.

SUBMITTER: Davis LL

PROVIDER: S-EPMC4459521 | biostudies-literature | 2015 Jul-Aug

REPOSITORIES: biostudies-literature

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Determining Time of Symptom Onset in Patients With Acute Coronary Syndromes: Agreement Between Medical Record and Interview Data.

Davis Leslie L LL

Dimensions of critical care nursing : DCCN 20150701 4

<h4>Background</h4>Prehospital delay, the time of symptom onset until the time of hospital arrival, for patients with symptoms of acute coronary syndrome (ACS) is frequently used to determine the course of care. Total ischemic time (time for symptom onset until the time of first coronary artery balloon inflation) is another criterion for quality of care for patients experiencing ST-segment elevation myocardial infarction. However, obtaining the exact time of symptom onset, the starting point of ...[more]

PMID: 26050056

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Project description:Past research has shown discrepancies between the time of symptom onset for patients with acute coronary syndrome (ACS) as documented in the medical record (MR) and patients' recall of the time assessed through subject interviews done later by researchers.The aim of this study is to determine if there were differences between the time of symptom onset documented in the MR and subject interview taking into consideration sex, age group, and recall period for patients admitted to the emergency department for symptoms suggestive of ACS.A secondary analysis was conducted on data from the PROMOTION (Patient Response to Myocardial Infarction Following a Teaching Intervention Offered by Nurses) trial, a multicenter randomized clinical trial to reduce patient prehospital delay to treatment in ACS.Of the 3522 subjects with CAD enrolled into the trial, 3087 subjects completed 2-year follow-up. Of these, 331 subjects sought treatment in the emergency department for ACS symptoms and 276 patients (83%) had complete information on the time of symptom onset from both sources. Of the 276 patients, 25 (9%) had differing times more than 48 hours and were thus excluded. The median difference between the 2 sources was 45.0 minutes. When both times were examined, there were no significant differences in time by sex (P = .720) or by age group (P = .188). The median number of days between the interview and the date of symptom onset was 29.5 days. There was a significant correlation between differences in the time of symptom onset and the length of recall period (rs = 0.148, P = .023). In multivariable modeling, a longer recall period was associated with greater median differences in the symptom onset time (b = 13.2, P = .023).These results suggest that the time of symptom onset obtained at the time of the index event and documented in the MR is not interchangeable with data obtained later by research staff, especially if the interview is not conducted near the time of the index event.

Project description:ImportanceAccurate documentation of patient symptoms in the electronic medical record (EMR) is important for high-quality patient care.ObjectiveTo explore inconsistencies between patient self-report on an Eye Symptom Questionnaire (ESQ) and documentation in the EMR.Design, setting, and participantsThis investigation was an observational study in comprehensive ophthalmology and cornea clinics at an academic institution among a convenience sample of 192 consecutive eligible patients, of whom 30 declined participation. Patients were recruited at the Kellogg Eye Center from October 1, 2015, to January 31, 2016. Patients were eligible to be included in the study if they were 18 years or older.Main outcomes and measuresConcordance of symptoms reported on an ESQ with data recorded in the EMR. Agreement of symptom report was analyzed using κ statistics and McNemar tests. Disagreement was defined as a negative symptom report or no mention of a symptom in the EMR for patients who reported moderate to severe symptoms on the ESQ. Logistic regression was used to investigate if patient factors, physician characteristics, or diagnoses were associated with the probability of disagreement for symptoms of blurry vision, pain or discomfort, and redness.ResultsA total of 162 patients (324 eyes) were included. The mean (SD) age of participants was 56.6 (19.4) years, 62.3% (101 of 162) were female, and 84.9% (135 of 159) were white. At the participant level, 33.8% (54 of 160) had discordant reporting of blurry vision between the ESQ and EMR. Likewise, documentation was discordant for reporting glare (48.1% [78 of 162]), pain or discomfort (26.5% [43 of 162]), and redness (24.7% [40 of 162]), with poor to fair agreement (κ range, -0.02 to 0.42). Discordance of symptom reporting was more frequently characterized by positive reporting on the ESQ and lack of documentation in the EMR (Holm-adjusted McNemar P < .03 for 7 of 8 symptoms except for blurry vision [P = .59]). Return visits at which the patient reported blurry vision on the ESQ had increased odds of not reporting the symptom in the EMR compared with new visits (odds ratio, 5.25; 95% CI, 1.69-16.30; Holm-adjusted P = .045).Conclusions and relevanceSymptom reporting was inconsistent between patient self-report on an ESQ and documentation in the EMR, with symptoms more frequently recorded on a questionnaire. These results suggest that documentation of symptoms based on EMR data may not provide a comprehensive resource for clinical practice or "big data" research.

Project description:ObjectivesThis study set out to obtain a general profile of physician time expenditure and electronic health record (EHR) limitations in a large university medical center in Germany. We also aim to illustrate the merit of a tool allowing for easier capture and prioritization of specific clinical needs at the point of care for which the current study will inform development in subsequent work.MethodsNineteen physicians across six different departments participated in this study. Direct clinical observations were conducted with 13 out of 19 physicians for a total of 2,205 minutes, and semistructured interviews were conducted with all participants. During observations, time was measured for larger activity categories (searching information, reading information, documenting information, patient interaction, calling, and others). Semistructured interviews focused on perceived limitations, frustrations, and desired improvements regarding the EHR environment.ResultsOf the observed time, 37.1% was spent interacting with the health records (9.0% searching, 7.7% reading, and 20.5% writing), 28.0% was spent interacting with patients corrected for EHR use (26.9% of time in a patient's presence), 6.8% was spent calling, and 28.1% was spent on other activities. Major themes of discontent were a spread of patient information, high and often repeated documentation burden, poor integration of (new) information into workflow, limits in information exchange, and the impact of such problems on patient interaction. Physicians stated limited means to address such issues at the point of care.ConclusionIn the study hospital, over one-third of physicians' time was spent interacting with the EHR, environment, with many aspects of used systems far from optimal and no convenient way for physicians to address issues as they occur at the point of care. A tool facilitating easier identification and registration of issues, as they occur, may aid in generating a more complete overview of limitations in the EHR environment.

Dataset Information

Determining Time of Symptom Onset in Patients With Acute Coronary Syndromes: Agreement Between Medical Record and Interview Data.

Publications

Determining Time of Symptom Onset in Patients With Acute Coronary Syndromes: Agreement Between Medical Record and Interview Data.

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