Telemedicine Use across Medical Specialties and Diagnoses.

BACKGROUND: The COVID-19 (coronavirus disease 2019) pandemic rapidly expanded telemedicine scale and scope. As telemedicine becomes routine, understanding how specialty and diagnosis combine with demographics to impact telemedicine use will aid in addressing its current limitations. OBJECTIVES: To analyze the relationship between medical specialty, diagnosis, and telemedicine use, and their interplay with patient demographics in determining telemedicine usage patterns. METHODS: We extracted encounter and patient data of all adults who scheduled outpatient visits from June 1, 2020 to June 30, 2021 from the electronic health record of an integrated academic health system encompassing a broad range of subspecialties. Extracted variables included medical specialty, primary visit diagnosis, visit modality (video, audio, or in-person), and patient age, sex, self-reported race/ethnicity and 2013 rural-urban continuum code. Six specialties (General Surgery, Family Medicine, Gastroenterology, Oncology, General Internal Medicine, and Psychiatry) ranging from the lowest to the highest quartile of telemedicine use (video and audio) were chosen for analysis. Relative proportions of video, audio, and in-person modalities were compared. We examined diagnoses associated with the most and least frequent telemedicine use within each specialty. Finally, we analyzed associations between patient characteristics and telemedicine modality (video vs. audio/in-person, and video/audio vs. in-person) using a mixed-effects logistic regression model. RESULTS: A total of 2,494,296 encounters occurred during the study period, representing 420,876 unique patients (mean age: 44 years, standard deviation: 24 years, 54% female). Medical diagnoses requiring physical examination or minor procedures were more likely to be conducted in-person. Rural patients were more likely than urban patients to use video telemedicine in General Surgery and Gastroenterology and less likely to use video for all other specialties. Within most specialties, male patients and patients of nonwhite race were overall less likely to use video modality and video/audio telemedicine. In Psychiatry, members of several demographic groups used video telemedicine more commonly than expected, while in other specialties, members of these groups tended to use less telemedicine overall. CONCLUSION: Medical diagnoses requiring physical examination or minor procedures are more likely to be conducted in-person. Patient characteristics (age, sex, rural vs. urban, race/ethnicity) affect video and video/audio telemedicine use differently depending on medical specialty. These factors contribute to a unique clinical scenario which impacts perceived usefulness and accessibility of telemedicine to providers and patients, and are likely to impact rates of telemedicine adoption.

Predictors of colorectal cancer screening variation among primary-care providers and clinics.

OBJECTIVES: Colorectal cancer (CRC) screening is underutilized. To effect change, we must understand reasons for underuse at multiple levels of the health-care system. We evaluated patient, provider, and clinic factors that predict variation in CRC screening among primary-care clinics and primary-care providers (PCPs). METHODS: We analyzed electronic medical record (EMR) data for 34,319 adults eligible for CRC screening, 19 clinics, and 97 PCPs in a large, academic physician group. Detailed data on potential patient, provider, and clinic predictors of CRC screening were obtained from the EMR. PCP perceptions of CRC screening barriers were measured via survey. The outcome was completion of CRC screening at the patient level. Multivariate logistic regression with clustering on clinics obtained adjusted odds ratios and 95% confidence intervals for potential predictors of CRC screening at each level. RESULTS: Seventy-one percentage of patients completed CRC screening. Variation in screening rates was seen among clinics (51-80%) and among PCPs (51-82%). Significant predictors of completing CRC screening were identified at all levels: patient (older age, white race, being married, primarily English-speaking, having commercial insurance plans vs. Medicare or Medicaid, and higher health-care resource utilization), provider (larger panel size of patients eligible for CRC screening), and clinic (hospital-owned, shorter distance to nearest optical colonoscopy center). CONCLUSIONS: Variation in CRC screening exists among primary-care clinics and providers within a single clinic. Predictors of variation can be identified at patient, provider, and clinic levels. Quality improvement interventions addressing CRC screening need to be directed at multiple levels of the health-care system.

Minority status and diabetes screening in an ambulatory population.

OBJECTIVE: Ethnicity has been identified as a risk factor not only for having type 2 diabetes but for increased morbidity and mortality with the disease. Current American Diabetes Association (ADA) guidelines advocate screening high-risk minorities for diabetes. This study investigates the effect of minority status on diabetes screening practices in an ambulatory, insured population presenting for yearly health care. RESEARCH DESIGN AND METHODS: This is a retrospective population-based study of patients in a large, Midwestern, academic group practice. Included patients were insured, had ≥1 primary care visit yearly from 2003 to 2007, and did not have diabetes but met ADA criteria for screening. Odds ratios (ORs), 95% confidence intervals (CI), and predicted probabilities were calculated to determine the relationship between screening with fasting glucose, glucose tolerance test, or hemoglobin A(1c) and patient and visit characteristics. RESULTS: Of the 15,557 eligible patients, 607 (4%) were of high-risk ethnicity, 61% were female, and 86% were ≥45 years of age. Of the eight high-risk factors studied, after adjustment, ethnicity was the only factor not associated with higher diabetes screening (OR = 0.90 [95% CI 0.76-1.08]) despite more primary care visits in this group. In overweight patients <45 years, where screening eligibility is based on having an additional risk factor, high-risk ethnicity (OR 1.01 [0.70-1.44]) was not associated with increased screening frequency. CONCLUSIONS: In an insured population presenting for routine care, high-risk minority status did not independently lead to diabetes screening as recommended by ADA guidelines. Factors other than insurance or access to care appear to affect minority-preventive care.