Citations

Background Although online self-triage is easily accessible, little is known about the patients who use self-triage or their subsequent diagnoses. We compared ear/hearing self-triage subsequent diagnoses to ear/hearing visit diagnoses in emergency departments (ED) and ambulatory clinics across the United States. Methods We compared International Classification of Diseases version 10 (ICD10) coded diagnoses following online self-triage for ear/hearing concerns with those from national ED and ambulatory clinic samples. We used data from the Centers for Disease Control (CDC) National Hospital Ambulatory Medical Care Survey (NHAMCS) and National Ambulatory Medical Care Survey (NAMCS) for comparison. Using matched ear/hearing diagnostic categories for those aged 1 and over, we compared self-triage diagnosis frequencies with national ED and ambulatory diagnosis frequencies. Results Following ear/hearing self-triage, there were 1092 subsequent office visits with a primary diagnosis code. For five frequently diagnosed ear/hearing conditions (i.e., suppurative and nonsuppurative otitis media [OM], otalgia, otitis externa, and cerumen impaction), there was a strong correlation between diagnosis counts made following self-triage and estimated counts of national ED visit diagnoses (r = 0.94; CI 95% [0.37 to 0.99]; p = .016, adjusted r2 = 0.85). Seven diagnoses were available to compare with the national ambulatory sample; correlation was r = 0.79; CI 95% [0.08 to 0.97]; p = .037, adjusted r2 = 0.54. For ages 1 and over, estimated hospital admissions from the national ED visits for ear/hearing were 0.76%, CI 95% [0.28-2.1%]; estimated total national ear/hearing ED visits were 7.5 million (for 4 years, 2016 through 2019). Conclusion The strong correlation of ear-related self-triage diagnoses with national ED diagnoses and the low hospitalization risk for these diagnoses suggests that there is an opportunity for self-triage of ear/hearing concerns to decrease ED visits for these symptoms.

Background Self-triage is becoming more widespread, but little is known about the people who are using online self-triage tools and their outcomes. For self-triage researchers, there are significant barriers to capturing subsequent healthcare outcomes. Our integrated healthcare system was able to capture subsequent healthcare utilization of individuals who used self-triage integrated with self-scheduling of provider visits. Methods We retrospectively examined healthcare utilization and diagnoses after patients had used self-triage and self-scheduling for ear or hearing symptoms. Outcomes and counts of office visits, telemedicine interactions, emergency department visits, and hospitalizations were captured. Diagnosis codes associated with subsequent provider visits were dichotomously categorized as being associated with ear or hearing concerns or not. Nonvisit care encounters of patient-initiated messages, nurse triage calls, and clinical communications were also captured. Results For 2168 self-triage uses, we were able to capture subsequent healthcare encounters within 7 days of the self-triage for 80.5% (1745/2168). In subsequent 1092 office visits with diagnoses, 83.1% (891/1092) of the uses were associated with relevant ear, nose and throat diagnoses. Only 0.24% (4/1662) of patients with captured outcomes were associated with a hospitalization within 7 days. Self-triage resulted in a self-scheduled office visit in 7.2% (126/1745). Office visits resulting from a self-scheduled visit had significantly fewer combined non-visit care encounters per office visit (fewer combined nurse triage calls, patient messages, and clinical communication messages) than office visits that were not self-scheduled (−0.51; 95% CI, −0.72 to −0.29; P < .0001). Conclusion In an appropriate healthcare setting, self-triage outcomes can be captured in a high percentage of uses to examine for safety, patient adherence to recommendations, and efficiency of self-triage. With the ear or hearing self-triage, most uses had subsequent visit diagnoses relevant to ear or hearing, so most patients appeared to be selecting the appropriate self-triage pathway for their symptoms.

Objective: Compare demographics, treatment, and follow-up rates for patients with complaints of vulvovaginitis suggestive of candida infection evaluated via e-visit, face-to-face (F2F) visits, or nurse-administered phone protocol. Methods: Manual review of 150 vaginitis visits of each visit type (e-visit, F2F, and phone protocol) completed between May 5, 2018 through January 31, 2020 by Mayo Clinic patients residing in Minnesota. Outcomes: Comparison between the three visit types of patient characteristics, treatment rates, type of treatment, follow-up rates, and types of follow-up. Results: Patients utilizing phone visits were significantly older than those seeking care via e-visit ( p < 0.0001) or F2F ( p = 0.001) and were more likely to be treated with oral fluconazole than those treated by e-visit ( p < 0.0001) or F2F ( p < 0.0001) encounters. Patients were significantly less likely to receive fungal directed treatment at a F2F visit than an e-visit ( p < 0.0001) or phone encounter ( p < 0.0001). There was no significant difference in follow-up rates between the three groups. Conclusion: Virtual visits (non-F2F) for suspected vulvovaginal candidiasis are unlikely to result in more follow-up visits than F2F encounters; however, prescriptions for antifungals are significantly higher with virtual visits.

Background While socioeconomic status has been linked to hospital readmissions for several conditions, reliable measures of individual socioeconomic status are often not available. HOUSES, a new measure of individual socioeconomic status based upon objective public data about one's housing unit, is inversely associated with overall hospitalization rate but it has not been studied with respect to readmissions. Purpose To determine if patients in the lowest HOUSES quartile are more likely to be readmitted within 30 days (short-term) and 180 days (long-term). Methods A retrospective cohort study of 11 993 patients having 21 633 admissions was conducted using generalized linear mixed-effects models. Results HOUSES quartile did not show any significant association with early readmission. However, when compared to the lowest HOUSES quartile, the second quartile (OR = 0.90, 95%CI 0.83-0.98) and the third quartile (OR = 0.91, 95%CI 0.83-0.99) were associated with lower odds of late readmission while the highest quartile (OR = 0.91, 95%CI 0.82-1.01) was not statistically different. Conclusion HOUSES was associated with late readmission, but not early readmission. This may be because early readmissions are influenced by medical conditions and hospital care while late readmissions are influenced by ambulatory care and home-based factors. Since HOUSES relies on public county assessor data, it is generally available and may be used to focus interventions on those at highest risk for late readmission.

Background: Vitamin D deficiency may increase the risk of severe COVID-19 disease. Objectives: To determine if 25-hydroxyvitamin D [25(OH)D] levels in patients hospitalized for COVID-19 were associated with the clinical outcomes of days on oxygen, duration of hospitalization, ICU admission, need for assisted ventilation, or mortality. Methods: We conducted a retrospective study of 92 patients admitted to the hospital with SARS-CoV-2 infection between April 16, 2020 and October 17, 2020. Multivariable regression was performed to assess the independent relationship of 25(OH)D values on outcomes, adjusting for significant covariates and the hospitalization day the level was tested. Results: About 15 patients (16.3%) had 25(OH)D levels <20 ng/mL. Only 1 patient (3.4%) who had documented vitamin D supplementation prior to admission had 25(OH)D <20 ng/mL. Serum 25(OH)D concentrations were not significantly associated with any of our primary outcomes of days on oxygen, duration of hospitalization, intensive care unit (ICU) admission, need for mechanical ventilation, or mortality in any of the adjusted multivariable models. Adjusting for the hospital day of 25(OH)D sampling did not alter the relationship of 25(OH)D with any outcomes. Conclusion: Vitamin D status was not related to any of the primary outcomes reflecting severity of COVID-19 in hospitalized patients. However, our sample size may have lacked sufficient power to demonstrate a small effect of vitamin D status on these outcomes.

Known gaps exist between what patients value and institutions prioritize. We sought to incorporate patients’ reasons for valuing family medicine into a new Mission and Vision statement by deploying brief surveys to a convenience sample of patients. We conducted descriptive quantitative analyses of demographics and inductive content analysis of written responses. Patients returned 92 (20%) of 450 questionnaires. Responders were 63% female, mean age of 47 years. Patients noted distinguishing features of family medicine were (1) continuity of care, (2) all-encompassing care, and (3) trusted referrals. Some patients reported not knowing there was a distinction between family medicine and other primary care.

Introduction Acute sore throat is a common complaint traditionally completed with an in-person visit. However, non-face-to-face telemedicine visits offer greater access at reduced cost. We evaluated patient/caregiver asynchronous text-based electronic visits (eVisits) for acute sore throat and whether there was concordance for individual components and total McIsaac score compared to a clinician’s assessment. eVisits were completed by patients and/or their caregivers via a secure patient portal. Methods In this retrospective study, we manually reviewed charts between February 2017 and July 2019 of patients who had an eVisit, in-person visit and group A streptococcal (GAS) test performed on the same day for an acute sore throat. We calculated a McIsaac score for eVisits and in-person visits, and compared each component and total score using Cohen’s kappa agreement statistic. Results There were 320 instances of patients who had an eVisit, in-person visit and GAS testing done on the same day. Approximately a third of eVisits were missing at least one McIsaac component, with the physical examination elements missing most commonly. Individual score congruence was moderate for cough (0.41), fair for fever (0.34) and slight for tonsillar swelling/exudate and lymphadenopathy (0.17 and 0.08, respectively), with total congruence being slight to fair (0.09–0.37). A McIsaac score of ≤1 showed moderate agreement (0.44). Visits with complete individual score components demonstrated improved congruence: substantial for cough (0.64), moderate for fever (0.57), fair for tonsillar swelling (0.3) and slight for lymphadenopathy (0.13). Discussion Overall agreement for individual score components was better for symptoms than it was for examination components, and was improved when data were complete. A McIsaac score of 1 or 0 had moderate agreement and thus could reasonably be safely used to exclude patients from GAS testing.

Abstract Objective Financial impacts associated with a switch to a different electronic health record (EHR) have been documented. Less attention has been focused on the patient response to an EHR switch. The Mayo Clinic was involved in an EHR switch that occurred at 6 different locations and with 4 different “go-live” dates. We sought to understand the relationship between patient satisfaction and the transition to a new EHR. Materials and Methods We used patient satisfaction data collected by Press Ganey from July 2016 through December 2019. Our patient satisfaction measure was the percent of patients responding “very good” (top box) to survey questions. Twenty-four survey questions were summarized by Press Ganey into 6 patient satisfaction domains. Piecewise linear regression was used to model patient satisfaction before and after the EHR switch dates. Results Significant drops in patient satisfaction were associated with the EHR switch. Patient satisfaction with access (ease of getting clinic on phone, ease of scheduling appointments, etc.) was most affected (range of 6 sites absolute decline: -3.4% to -8.8%; all significant at 99% confidence interval). Satisfaction with providers was least affected (range of 6 sites absolute decline: -0.5% to -2.8%; 4 of 6 sites significant at 99% confidence interval). After 9-15 months, patient satisfaction with access climbed back to pre-EHR switch levels. Conclusions Patient satisfaction in several patient experience domains dropped significantly and stayed lower than pre–“go-live” for several months after a switch in EHR. Satisfaction with providers declined less than satisfaction with access.