Disparities in Use of Virtual Primary Care During the Early COVID-19 Pandemic.

Background: The COVID-19 pandemic increased the use of virtual health care. However, certain factors may disparately affect some patients' utilization of virtual care. Associations between age, racial categories (White or Black), and socioeconomic disadvantage were evaluated during the early COVID-19 pandemic. Methods: This cross-sectional retrospective study included adult patients with virtual or in-person primary care encounters at a large, midwestern hospital system with widespread urban and suburban offices between March 1, 2020, and June 30, 2020. Virtual visits included synchronous video and telephone visits and asynchronous patient portal E-visits. Chi-squared tests and multivariable logistic analysis assessed the associations between ages and racial categories, and area deprivation index with the use of virtual versus in-person primary care. Results: Of 72,153 patient encounters, 43.0% were virtual visits, 54.6% were White patients, and 45.4% were Black. Across equivalent age ranges, black patients were slightly less likely to utilize virtual care than similarly aged White patients, but not consistently across virtual modalities. Women were more likely to use virtual care across all modalities, and individuals >65 years were more likely to use telephone visits and less likely to use video and E-visits, regardless of race. Patients residing in areas with the greatest socioeconomic advantage were more likely to utilize video and E-visits. Conclusions: Differential patterns of utilization emerged across racial categories and age ranges, suggesting that racial disparities are exacerbated depending upon patient age and mode of utilization.

Using a Frontline Staff Intervention to Improve Cervical Cancer Screening in a Large Academic Internal Medicine Clinic.

BACKGROUND: Cervical cancer is the third most common malignancy affecting women. Screening with Papanicolaou (Pap) tests effectively identifies precancerous lesions and early-stage cervical cancer. While the nationwide rate of cervical cancer screening (CCS) is 84%, our urban general internal medicine (GIM) clinic population had a CCS rate of 70% in 2016. OBJECTIVE: To improve our clinic's CCS rate to match or exceed the national average within 18 months by identifying barriers and testing solutions. DESIGN: A quality improvement project led by a multidisciplinary group of healthcare providers. PARTICIPANTS: Our GIM clinic includes 16 attending physicians, 116 resident physicians, and 20 medical assistants (MAs) with an insured and underserved patient population. INTERVENTION: Phase 1 lasted 9 months and implemented CCS patient outreach, patient financial incentives, and clinic staff education. Phase 2 lasted 9 months and involved a workflow change in which MAs identified candidates for CCS during patient check-in. Feedback spanned the entire study period. MAIN MEASURES: Our primary outcome was the number of Pap tests completed per month during the 2 study phases. Our secondary outcome was the clinic population's CCS rate for all eligible clinic patients. KEY RESULTS: After interventions, the average number of monthly Pap tests increased from 35 to 56 in phase 1 and to 75 in phase 2. Of 385 patients contacted in phase 1, 283 scheduled a Pap test and 115 (41%) completed it. Compared to baseline, both interventions improved cervical cancer screening (phase 1 relative risk, 1.86; 95% CI, 1.64-2.10; P < 0.001; phase 2 relative risk, 2.70; 95% CI, 2.40-3.02; P < 0.001). Our clinic's CCS rate improved from 70% to 75% after the 18-month intervention. CONCLUSIONS: The rate of CCS increased by 5% after a systematic 2-phase organizational intervention that empowered MAs to remind, identify, and prepare candidates during check-in for CCS.

Visual Analytics Dashboard Promises to Improve Hypertension Guideline Implementation.

BACKGROUND: Primary care management of hypertension under new guidelines incorporates assessment of cardiovascular disease risk and commonly requires review of electronic health record (EHR) data. Visual analytics can streamline the review of complex data and may lessen the burden clinicians face using the EHR. This study sought to assess the utility of a visual analytics dashboard in addition to EHR in managing hypertension in a primary care setting. METHODS: Primary care physicians within an urban, academic internal medicine clinic were tasked with performing 2 simulated patient encounters for hypertension management: the first using standard EHR, and the second using EHR paired with a visual dashboard. The dashboard included graphical blood pressure trends with guideline-directed targets, calculated atherosclerotic cardiovascular disease risk score, and relevant medications. Guideline-appropriate antihypertensive prescribing, correct target blood pressure goal, and total encounter time were assessed. RESULTS: We evaluated 70 case simulations. Use of the dashboard with the EHR compared with use of the EHR alone was associated with greater adherence to prescribing guidelines (95% vs. 62%, P < 0.001) and more correct identification of blood pressure target (95% vs. 57%, P < 0.01). Total encounter time fell an average of 121 seconds (95% confidence interval 69-157 seconds, P < 0.001) in encounters that used the dashboard combined with the EHR. CONCLUSIONS: The integration of a hypertension-specific visual analytics dashboard with EHR demonstrates the potential to reduce time and improve hypertension guideline implementation. Further widespread testing in clinical practice is warranted.

The Applicability of New Orleans Criteria for Head Computed Tomography in Inpatient Falls With Injury.

BACKGROUND: Inpatient falls are a patient safety concern. Limited data exist on the utility of head computed tomography (CT) for inpatient falls. The New Orleans Criteria (NOC) is a validated tool to determine the appropriateness of neuroimaging in the emergency department for falls with minor head injury. This study aimed to evaluate whether the NOC could be applied to inpatient falls. METHODS: This retrospective cohort study assessed 1 year of inpatient falls with injury at 5 inpatient facilities. Records were reviewed for demographic data, fall circumstances, laboratory results, components of the NOC, and head CT results. Cohorts included positive NOC (≥1 NOC finding) and negative NOC. Sensitivity and specificity were calculated for the NOC alone, NOC plus coagulopathy, and NOC or coagulopathy for acute intracranial process. RESULTS: Of 332 inpatient falls with injury, 188 (57%) received a head CT. Of the 250 (75.3%) NOC-positive cases, 159 (63.6%) received a head CT. Of all patients who received a head CT, 7 (2.1%) showed a significant acute intracranial process. The NOC was positive in 6 of the 7 cases (sensitivity 85.7% and specificity 23.8%); the other case had a significant coagulopathy. New Orleans Criteria or coagulopathy had 100% sensitivity and 23.4% specificity. CONCLUSIONS: Our findings show that use of the NOC to evaluate potential intracranial injury in inpatient falls is limited. Adding criteria to the NOC may improve its test characteristics, with a sensitivity of 100% for the NOC or coagulopathy, suggesting potential clinical utility.

Cross-Cover Documentation: Multicenter Development of Assessment Tool for Quality Improvement.

Construct: We aimed to develop an assessment tool to measure the quality of electronic health record inpatient documentation of cross-cover events. Background: Cross-cover events occur in hospitalized patients when the primary team is absent. Documentation is critical for safe transitions of care. The quality of documentation for cross-cover events remains unknown, and no standardized tool exists for assessment. Approach: We created an assessment tool for cross-cover note quality with content validation based on input from 15 experts. We measured interrater reliability of the tool and scored cross-cover note quality for hospitalized patients with overnight rapid response team activation on internal medicine services at 2 academic hospitals for 1 year. Patients with a code blue or a clinically insignificant event were excluded. The presence of a note, writer identity (resident or faculty), time from rapid response to documentation, note content (subjective and objective information, diagnosis, and plan), and patient outcomes were compared. Results: The instrument included 8 items to determine quality of cross-cover documentation: reason for physician notification, note written within 6 hours, subjective and objective patient information, diagnosis, treatment, level of care, and whether the attending physician was notified. The mean Cohen's kappa coefficient demonstrated good interrater agreement at 0.76. The instrument was scored in 222 patients with cross-cover notes. Notes documented by faculty scored higher in quality than residents (89% vs. 74% of 8 items present, p < .001). Cross-cover notes often lacked subjective information, diagnosis, and notification of attending, which was present in 60%, 62%, and 7% of notes, respectively. Conclusions: This study presents reliability evidence for an 8-item assessment tool to measure quality of documentation of cross-cover events and indicates improvement is needed for cross-cover education and safe transitions of care in acutely decompensating medical patients.

Does Timing of Internal Medicine Residency Interview Affect Likelihood of Matching?

OBJECTIVES: Applicants to our internal medicine (IM) residency program consistently have shared concerns about whether the interview date influences their ability to match via the National Residency Matching Program. We performed a retrospective study to assess whether interview timing was associated with successful matching at our IM program. METHODS: We identified all of the applicants who interviewed for a first-year position with our IM residency program from 2010 to 2014. Each year's interview dates were totaled and divided equally into three categories: early, middle, or late. Baseline demographics, United States Medical Licensing Examination scores, and type of medical school (American or international) were compared among the interview date groups and between those who did and did not match at our program. RESULTS: Of 914 interviewees, 311 interviewed early (October/November), 299 interviewed in the middle (December), and 304 interviewed late (January). The proportion to match at our program was similar in each interview group (12.5%, 18.4%, 15.1%, respectively; P = 0.133). Logistic regression analysis showed that the middle interview group had increased odds to match compared with the early group (odds ratio 1.590; P = 0.044). The late-versus-early group showed no difference (P = 0.362). No significant differences were found with type of medical school or United States Medical Licensing Examination scores. Of all of the interviewees participating in the match, nearly all matched into a program somewhere, with no significant difference based on interview timing. CONCLUSIONS: When considering all of the interviewees, interview date showed no major influence on matching. Only the middle interview time period showed a slight increased chance of matching to our IM program, but the significance was marginal.

Racial and Economic Disparities in Diabetes in a Large Primary Care Patient Population.

OBJECTIVE: We sought to determine if, after adjusting for economic status, race is an independent risk factor for glycemic control among diabetic patients in a large primary care patient population. DESIGN SETTING PARTICIPANTS: We performed a retrospective chart review of 264,000 primary care patients at our large, urban academic medical center to identify patients with a diagnosis of diabetes (n=25,123). Zip code was used to derive median income levels using US Census Bureau demographic information. Self-reported race was extracted from registration data. MAIN OUTCOME MEASURES: The prevalence of diabetes, average glycated hemoglobin (A1c), and prevalence of uncontrolled diabetes of White and Black patients at all income levels were determined. RESULTS: White patients had a lower average A1c level and a lower prevalence of diabetes than Black patients in all income quartiles (P<.001). Among White patients, the prevalence of diabetes (P<.001), uncontrolled diabetes (P<.001), and A1c level (P=.014) were inversely proportional to income level. No significant difference in the prevalence of diabetes (P=.214), A1c level (P=.282), or uncontrolled diabetes related to income was seen in Black patients (P=.094). CONCLUSIONS: Race had an independent association with diabetes prevalence and glycemic control. Our study does not support two prominent theories that economic and insurance status are the main factors in diabetes disparities, as we attempted to control for economic status and nearly every patient had insurance. It will be important for future analysis to explore how health care system factors affect these observed gaps in quality.