Hidden in plain sight: bias towards sick patients when sampling patients with sufficient electronic health record data for research

Rusanov, Alexander; Weiskopf, Nicole G.; Wang, Shuang; Weng, Chunhua

doi:10.1186/1472-6947-14-51

Cited by 104 publications

(76 citation statements)

References 32 publications

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“…[29] Interestingly, however, the numerical value of LDL cholesterol testing was not associated with its frequency of testing in that study, a finding the authors attributed to healthcare processes such as guidelines for screening and monitoring. Our analyses of outpatient measurements are also consistent with results from 10,000 patients receiving anesthetic services at one medical center, where illness severity was associated with a greater number of days with clinical data[30]. The decision of how to define the baseline timeframe of an EHR-derived cohort study can be viewed as a missing data problem,[31] with competing biases at either end of the spectrum.…”

Section: Discussionsupporting

confidence: 78%

Yield and bias in defining a cohort study baseline from electronic health record data

Vassy

Cho

et al. 2018

Journal of Biomedical Informatics

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Aims Despite growing interest in using electronic health records (EHR) to create longitudinal cohort studies, the distribution and missingness of EHR data might introduce selection bias and information bias to such analyses. We aimed to examine the yield and potential for these healthcare process biases in defining a study baseline using EHR data, using the example of cholesterol and blood pressure (BP) measurements. Methods We created a virtual cohort study of cardiovascular disease (CVD) from patients with eligible cholesterol profiles in the New England (NE) and Southeast (SE) networks of the Veterans Health Administration in the United States. Using clinical data from the EHR, we plotted the yield of patients with BP measurements within an expanding timeframe around an index date of cholesterol testing. We compared three groups: 1) patients with BP from the exact index date; 2) patients with BP not on the index date but within the network-specific 90th percentile around the index date; and 3) patients with no BP within the network-specific 90th percentile. Results Among 589,361 total patients in the two networks, 146,636 (61.0%) of 240,479 patients from NE and 289,906 (83.1%) of 348,882 patients from SE had BP measurements on the index date. Ninety percent had BP measured within 11 days of the index date in NE and within 5 days of the index date in SE. Group 3 in both networks had fewer available race data, fewer comorbidities and CVD medications, and fewer health system encounters. Conclusions Requiring same-day risk factor measurement in the creation of a virtual CVD cohort study from EHR data might exclude 40% of eligible patients, but including patients with infrequent visits might introduce bias. Data visualization can inform study-specific strategies to address these challenges for the research use of EHR data.

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Section: Discussionsupporting

confidence: 78%

Yield and bias in defining a cohort study baseline from electronic health record data

Vassy

Cho

et al. 2018

Journal of Biomedical Informatics

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“…This was done so as not to eliminate patients with missing vital signs values, who often present differently than patients with complete vital reports. 31 Hour of arrival was defined as the hour of day when the patient was registered in the ED and was included as a categorical variable to control for both variation in system resources and staffing intensity by time of day.…”

Section: Discussionmentioning

confidence: 99%

The Impact of Emergency Department Census on the Decision to Admit

Gorski

Batt

Ötleş

et al. 2017

Academic Emergency Medicine

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Objective: We evaluated the effect of emergency department (ED) census on disposition decisions made by ED physicians.Methods: We performed a retrospective analysis using 18 months of all adult patient encounters seen in the main ED at an academic tertiary care center. Patient census information was calculated at the time of physician assignment for each individual patient and included the number of patients in the waiting room (waiting room census) and number of patients being managed by the patient's attending (physician load census). A multiple logistic regression model was created to assess the association between these census variables and the disposition decision, controlling for potential confounders including Emergency Severity Index acuity, patient demographics, arrival hour, arrival mode, and chief complaint.Results: A total of 49,487 patient visits were included in this analysis, of whom 37% were admitted to the hospital. Both census measures were significantly associated with increased chance of admission; the odds ratio (OR) per patient increase for waiting room census was 1.011 (95% confidence interval [CI] = 1.001 to 1.020), and the OR for physician load census was 1.010 (95% CI = 1.002 to 1.019). To put this in practical terms, this translated to a modeled rise from 35.3% to 40.1% when shifting from an empty waiting room and zero patient load to a 12-patient wait and 16-patient load for a given physician. Conclusion:Waiting room census and physician load census at time of physician assignment were positively associated with the likelihood that a patient would be admitted, controlling for potential confounders. Our data suggest that disposition decisions in the ED are influenced not only by objective measures of a patient's disease state, but also by workflow-related concerns. E mergency care is receiving increasing scrutiny as a potential area for cost reductions.1-3 Management of emergency department (ED) costs begins with examining how ED operational characteristics contribute to both patient-level and system-level outcomes. One such characteristic under scrutiny is ED crowding, a phenomenon that can be partially attributed to rising practice intensity 4,5 and inpatient boarding. 6-8 As ED utilization rises, research on the effects of crowding has primarily focused on its influence on patient outcomes, including treatment delays 9-11 and patient mortality.12-15 Less well characterized are organizational responses to increasing operational pressure, such as changes to rates of admission.Highly relevant to the discussion of the cost of emergency care is the growing role of the ED as a "gatekeeper" for inpatient services. 1,16,17 In a 2013 RAND report, hospital admissions rose 4% from 34.7 The authors have no relevant financial information or potential conflicts to disclose. Author contributions: JKG, RJB, and BWP conceived the study; JKG conducted the primary data analysis, with advice and input from RJB and BWP; EO helped with data analysis and offered further methodologic input; JKG pri...

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“…Thus, we included patients with incomplete data to limit bias toward including only the most ill subset of patients. 19 As white blood cell (WBC) count remains a traditional variable often requested and performed in clinical practice, despite its known limitations regarding sensitivity and specificity for abdominal pathology, a test for interaction between WBC count and CT performance on return visits was performed, with the intent to include this variable in the model only if significant.…”

Section: Discussionmentioning

confidence: 99%

Abdominal Computed Tomography Utilization and 30-day Revisitation in Emergency Department Patients Presenting With Abdominal Pain

Patterson

Venkatesh²,

Alkhawam

et al. 2015

Acad Emerg Med

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Objectives: The objective was to explore which patient characteristics are associated with repeat emergency department (ED) visitation within 30 days of ED discharge for patients presenting with abdominal pain. Methods: A retrospective, observational study was conducted at a single, academic, urban ED with over 85,000 annual visits. A consecutive sample of adult patients with a chief complaint of abdominal pain from January 2010 through December 2010 who were discharged following ED evaluation were included in the analysis. A logistic regression model was used to determine which patient-level factors, including computed tomography (CT) utilization, were associated with the primary outcome of ED revisit within 30 days. Results: Of 80,619 total ED patient visits during the study period, 3,928 ED discharges with a chief complaint of abdominal pain were included. A total of 487 (12.4%) patients revisited the ED within 30 days. No deaths were recorded. CT imaging was associated with a lower 30-day revisit rate (odds ratio [OR] = 0.69, 95% confidence interval [CI] = 0.55 to 0.87) after controlling for multiple other patient-level factors associated with revisits. Increasing age (OR = 1.01, 95% CI = 1.00 to 1.02), increasing triage pain scores (OR = 1.13, 95% CI = 1.08 to 1.18), elevated triage heart rate (OR = 1.42, 95% CI = 1.07 to 1.89), low sodium levels (OR = 1.56, 95% CI = 1.07 to 2.23), and anemia (OR = 1.42, 95% CI = 1.04 to 1.95) were all associated with increased rate of return. Conclusions: Performance of an abdominal CT was associated with fewer 30-day revisits, suggesting that future measures of "imaging appropriateness" and "ED overuse" consider downstream utilization of health care resources in addition to the index visit. ACADEMIC EMERGENCY MEDICINE 2015;22:803-810 A growing number of patients present to the emergency department (ED) for complex and efficient diagnostic evaluation. 1 As such, the use of advanced imaging in the ED has increased, with computed tomography (CT) utilization increasing 330% in the United States from 1996 to 2007. 2 ED visits and use of imaging, however, are commonly viewed as inefficient or overused, with numerous publications focus-ing on reducing "unnecessary" ED visits or "unnecessary" CT scans. 3,4 As Americans increasingly rely on the ED for acute, unscheduled care, 5 increased scrutiny on return visits to the ED as a measure of lower quality and more costly care has emerged. 6 Current data suggest that 22% of all ED discharges gener

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Hidden in plain sight: bias towards sick patients when sampling patients with sufficient electronic health record data for research

Cited by 104 publications

References 32 publications

Yield and bias in defining a cohort study baseline from electronic health record data

Yield and bias in defining a cohort study baseline from electronic health record data

The Impact of Emergency Department Census on the Decision to Admit

Abdominal Computed Tomography Utilization and 30-day Revisitation in Emergency Department Patients Presenting With Abdominal Pain

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