Finding the time: Hourly variation in average daily census on a hospital medicine service.

Monitoring the average daily census (ADC) is crucial for managing patient flow and allocating resources. This study analyzed hourly fluctuations in the ADC on a hospital medicine service at an academic medical center. Data from 8342 encounters and 6178 unique patients were collected over a year. The ADC peaked at 11 a.m. (164.1 patients/day) and was lowest at 7 p.m. (155.0 patients/day), accounting for a variation of up to 9.1 patients (5.5% of peak census) depending on the time of day the measurement was taken. Understanding how ADC changes throughout the day will help hospital medicine programs to partner with administrators to optimize resource allocation and staffing. Measuring ADC at midnight, as traditionally done, may underestimate workload and therefore contribute to staffing shortages and physician burnout. Hospitals should consider measuring ADC at its peak, between 7 a.m. and 11 a.m., to ensure adequate staffing and high-quality patient care.

Impact of an automated peri-procedural digital health intervention on rates of emergency department visits and readmissions.

BACKGROUND: Providing timely peri-procedural education, reminders, and check-ins can improve patient adherence and clinical outcomes. We sought to retrospectively evaluate the impact of a peri-procedural digital health tool on emergency department (ED) visits and readmissions. METHODS: A digital health tool for peri-procedural care engaged patients at scheduled intervals, resulting in an overall engagement score. Multivariate models determined predictors of tool engagement and post-procedural 30- and 90-day rehospitalizations and ED visits. RESULTS: 11,737 unique completed procedures were analyzed from 10,438 patients. Patients of Black and Latinx race/ethnicity (vs White), those with Medicare and Medicaid insurance (vs commercial), and those with non-activated patient portals (vs activated) were less likely to engage. After adjustment for confounders, higher engagement with the tool was associated with lower rates of 30-day hospitalizations (OR 0.64), 90-day hospitalizations (OR 0.65), and 90-day ED visits (OR 0.77). CONCLUSIONS: Highly engaged patients had fewer 30-day and 90-day ED visit and readmissions, even after adjustment for key confounders. Engagement, and thus the resulting benefits, were not equitably distributed.

Association of protective behaviors with SARS-CoV-2 infection: results from a longitudinal cohort study of adults in the San Francisco Bay Area.

PURPOSE: In an effort to decrease transmission during the first years of the COVID-19 pandemic, public health officials encouraged masking, social distancing, and working from home, and restricted travel. However, many studies of the effectiveness of these measures had significant methodologic limitations. In this analysis, we used data from the TrackCOVID study, a longitudinal cohort study of a population-based sample of 3846 adults in the San Francisco Bay Area, to evaluate the association between self-reported protective behaviors and incidence of SARS-CoV-2 infection. METHODS: Participants without SARS-CoV2 infection were enrolled from August to December 2020 and followed monthly with testing and surveys (median of four visits). RESULTS: A total of 118 incident infections occurred (3.0% of participants). At baseline, 80.0% reported always wearing a mask; 56.0% avoided contact with nonhousehold members some/most of the time; 9.6% traveled outside the state; and 16.0% worked 20 or more hours per week outside the home. Factors associated with incident infection included being Black or Latinx, having less than a college education, and having more household residents. The only behavioral factor associated with incident infection was working outside the home (adjusted hazard ratio 1.62, 95% confidence interval 1.02-2.59). CONCLUSIONS: Focusing on protecting people who cannot work from home could help prevent infections during future waves of COVID-19, or future pandemics from respiratory viruses. This focus must be balanced with the known importance of directing resources toward those at risk of severe infections.

Patient Perceptions of e-Visits: Qualitative Study of Older Adults to Inform Health System Implementation.

BACKGROUND: Electronic visits (e-visits) are billable, asynchronous patient-initiated messages that require at least five minutes of medical decision-making by a provider. Unequal use of patient portal tools like e-visits by certain patient populations may worsen health disparities. To date, no study has attempted to qualitatively assess perceptions of e-visits in older adults. OBJECTIVE: In this qualitative study, we aimed to understand patient perceptions of e-visits, including their perceived utility, barriers to use, and care implications, with a focus on vulnerable patient groups. METHODS: We conducted a qualitative study using in-depth structured individual interviews with patients from diverse backgrounds to assess their knowledge and perceptions surrounding e-visits as compared with unbilled portal messages and other visit types. We used content analysis to analyze interview data. RESULTS: We conducted 20 interviews, all in adults older than 65 years. We identified 4 overarching coding categories or themes. First, participants were generally accepting of the concept of e-visits and willing to try them. Second, nearly two-thirds of the participants voiced a preference for synchronous communication. Third, participants had specific concerns about the name "e-visit" and when to choose this type of visit in the patient portal. Fourth, some participants indicated discomfort using or accessing technology for e-visits. Financial barriers to the use of e-visits was not a common theme. CONCLUSIONS: Our findings suggest that older adults are generally accepting of the concept of e-visits, but uptake may be limited due to their preference for synchronous communication. We identified several opportunities to improve e-visit implementation.

Impact of patient portal-based self-scheduling of diagnostic imaging studies on health disparities.

While many case studies have described the implementation of self-scheduling tools, which allow patients to schedule visits and imaging studies asynchronously online, none have explored the impact of self-scheduling on equitable access to care.1 Using an electronic health record patient portal, University of California San Francisco deployed a self-scheduling tool that allowed patients to self-schedule diagnostic imaging studies. We analyzed electronic health record data for the imaging modalities with the option to be self-scheduled from January 1, 2021 to September 1, 2021. We used descriptive statistics to compare demographic characteristics and created a multivariable logistic regression model to identify predictors of patient self-scheduling utilization. Among all active patient portal users, Latinx, Black/African American, and non-English speaking patients were less likely to self-schedule studies. Patients with Medi-Cal, California's Medicaid program, and Medicare insurance were also less likely to self-schedule when compared with commercially insured patients. Efforts to facilitate use of patient portal-based applications are necessary to increase equitability and decrease disparities in access.

Utilization patterns and efficiency gains from use of a fully EHR-integrated COVID-19 self-triage and self-scheduling tool: a retrospective analysis.

OBJECTIVE: Symptom checkers can help address high demand for SARS-CoV2 (COVID-19) testing and care by providing patients with self-service access to triage recommendations. However, health systems may be hesitant to invest in these tools, as their associated efficiency gains have not been studied. We aimed to quantify the operational efficiency gains associated with use of an online COVID-19 symptom checker as an alternative to a telephone hotline. METHODS: In our health system, ambulatory patients can either use an online symptom checker or a telephone hotline to be triaged and connected to COVID-19 care. We performed a retrospective analysis of adults who used either method between October 20, 2021 and January 10, 2022, using call logs, electronic health record data, and local wages to calculate labor costs. RESULTS: Of the 15 549 total COVID-19 triage encounters, 1820 (11.7%) used only the telephone hotline and 13 729 (88.3%) used the symptom checker. Only 271 (2%) of the patients who used the symptom checker also called the hotline. Hotline encounters required more clinician time compared to those involving the symptom checker (17.8 vs 0.4 min/encounter), resulting in higher average labor costs ($24.21 vs $0.55 per encounter). The symptom checker resulted in over 4200 clinician labor hours saved. CONCLUSION: When given the option, most patients completed COVID-19 triage and visit scheduling online, resulting in substantial efficiency gains. These benefits may encourage health system investment in such tools.

Patient Experience and Feedback After Using an Electronic Health Record-Integrated COVID-19 Symptom Checker: Survey Study.

BACKGROUND: Symptom checkers have been widely used during the COVID-19 pandemic to alleviate strain on health systems and offer patients a 24-7 self-service triage option. Although studies suggest that users may positively perceive web-based symptom checkers, no studies have quantified user feedback after use of an electronic health record-integrated COVID-19 symptom checker with self-scheduling functionality. OBJECTIVE: In this paper, we aimed to understand user experience, user satisfaction, and user-reported alternatives to the use of a COVID-19 symptom checker with self-triage and self-scheduling functionality. METHODS: We launched a patient-portal-based self-triage and self-scheduling tool in March 2020 for patients with COVID-19 symptoms, exposures, or questions. We made an optional, anonymous Qualtrics survey available to patients immediately after they completed the symptom checker. RESULTS: Between December 16, 2021, and March 28, 2022, there were 395 unique responses to the survey. Overall, the respondents reported high satisfaction across all demographics, with a median rating of 8 out of 10 and 288/395 (47.6%) of the respondents giving a rating of 9 or 10 out of 10. User satisfaction scores were not associated with any demographic factors. The most common user-reported alternatives had the web-based tool not been available were calling the COVID-19 telephone hotline and sending a patient-portal message to their physician for advice. The ability to schedule a test online was the most important symptom checker feature for the respondents. The most common categories of user feedback were regarding other COVID-19 services (eg, telephone hotline), policies, or procedures, and requesting additional features or functionality. CONCLUSIONS: This analysis suggests that COVID-19 symptom checkers with self-triage and self-scheduling functionality may have high overall user satisfaction, regardless of user demographics. By allowing users to self-triage and self-schedule tests and visits, tools such as this may prevent unnecessary calls and messages to clinicians. Individual feedback suggested that the user experience for this type of tool is highly dependent on the organization's operational workflows for COVID-19 testing and care. This study provides insight for the implementation and improvement of COVID-19 symptom checkers to ensure high user satisfaction.

Design of a population-based longitudinal cohort study of SARS-CoV-2 incidence and prevalence among adults in the San Francisco Bay Area.

PURPOSE: We describe the design of a longitudinal cohort study to determine SARS-CoV-2 incidence and prevalence among a population-based sample of adults living in six San Francisco Bay Area counties. METHODS: Using an address-based sample, we stratified households by county and by census-tract risk. Risk strata were determined by using regression models to predict infections by geographic area using census-level sociodemographic and health characteristics. We disproportionately sampled high and medium risk strata, which had smaller population sizes, to improve precision of estimates, and calculated a desired sample size of 3400. Participants were primarily recruited by mail and were followed monthly with PCR testing of nasopharyngeal swabs, testing of venous blood samples for antibodies to SARS-CoV-2 spike and nucleocapsid antigens, and testing of the presence of neutralizing antibodies, with completion of questionnaires about socio-demographics and behavior. Estimates of incidence and prevalence will be weighted by county, risk strata and sociodemographic characteristics of non-responders, and will take into account laboratory test performance. RESULTS: We enrolled 3842 adults from August to December 2020, and completed follow-up March 31, 2021. We reached target sample sizes within most strata. CONCLUSIONS: Our stratified random sampling design will allow us to recruit a robust general population cohort of adults to determine the incidence of SARS-CoV-2 infection. Identifying risk strata was unique to the design and will help ensure precise estimates, and high-performance testing for presence of virus and antibodies will enable accurate ascertainment of infections.

Building a Targeted Automatic e-Consult (TACo) Program.

DRIVING FORCES: Traditional specialty consults are resource intensive and may be delayed or omitted if the treating physician does not recognize the need for specialty advice. Targeted automatic e-consults (TACos) address these limitations by prospectively identifying patients using the electronic health record (EHR) and presenting pertinent information on a dashboard, enabling consultants to provide a virtual consult with written recommendations. The TACo model may improve value by facilitating more expert input without a proportional increase in cost. BUILDING A TACO: Through our experience developing a TACo program, we have identified four key steps. First, identify appropriate conditions that have support from the health system and from frontline clinicians. Second, design the digital infrastructure, including lists and dashboards. Third, create a funding plan to support the consultant's time, either through internal grants, external grants, e-consult billing codes, or some combination of the three. Fourth, pilot on a select number of services, iterate, and scale. CHALLENGES: Funding for TACos has been a major barrier to adoption. Fortunately, new e-consult billing codes may make it possible to recoup as least part of the program's cost. Technological hurdles also exist, particularly in building real-time lists within the EHR to prospectively identify patients based on complex criteria. NEXT STEPS: We look for this model to gain popularity as evidence of clinical and operational benefit mounts. We anticipate reimbursement policies may be updated to support this type of consult. Finally, we expect machine learning to play a role in identifying patients and providing recommendations in the future.

Race-ethnicity and COVID-19 Vaccination Beliefs and Intentions: A Cross-Sectional Study among the General Population in the San Francisco Bay Area.

OBJECTIVE: The study was designed to compare intentions to receive COVID-19 vaccination by race-ethnicity, to identify beliefs that may mediate the association between race-ethnicity and intention to receive the vaccine and to identify the demographic factors and beliefs most strongly predictive of intention to receive a vaccine. DESIGN: Cross-sectional survey conducted from November 2020 to January 2021, nested within a longitudinal cohort study of the prevalence and incidence of SARS-CoV-2 among a general population-based sample of adults in six San Francisco Bay Area counties (called TrackCOVID). Study Cohort: In total, 3161 participants among the 3935 in the TrackCOVID parent cohort responded. RESULTS: Rates of high vaccine willingness were significantly lower among Black (41%), Latinx (55%), Asian (58%), Multi-racial (59%), and Other race (58%) respondents than among White respondents (72%). Black, Latinx, and Asian respondents were significantly more likely than White respondents to endorse lack of trust of government and health agencies as a reason not to get vaccinated. Participants' motivations and concerns about COVID-19 vaccination only partially explained racial-ethnic differences in vaccination willingness. Concerns about a rushed government vaccine approval process and potential bad reactions to the vaccine were the two most important factors predicting vaccination intention. CONCLUSIONS: Vaccine outreach campaigns must ensure that the disproportionate toll of COVID-19 on historically marginalized racial-ethnic communities is not compounded by inequities in vaccination. Efforts must emphasize messages that speak to the motivations and concerns of groups suffering most from health inequities to earn their trust to support informed decision making.

Reimagining the inpatient palliative care consult: lessons from COVID-19.

As the number of inpatients with advanced age and chronic conditions rises, so too does the need for inpatient palliative care (PC). Despite the strong evidence base for PC, less than 50% of all inpatient PC needs are met by inpatient consults. Over the past several months in epicenters of the COVID-19 pandemic, PC providers have responded to the increased need for PC services through innovative digital programs including telepalliative care programs. In this article, we explore how PC innovations during COVID-19 could transform the PC consult to address workforce shortages and expand access to PC services during and beyond the pandemic. We propose a 3-pronged strategy of bolstering inpatient telepalliative care services, expanding electronic consults, and increasing training and educational tools for providers to help meet the increased need for PC services in the future.

Implementation of a digital chatbot to screen health system employees during the COVID-19 pandemic.

The screening of healthcare workers for COVID-19 (coronavirus disease 2019) symptoms and exposures prior to every clinical shift is important for preventing nosocomial spread of infection but creates a major logistical challenge. To make the screening process simple and efficient, University of California, San Francisco Health designed and implemented a digital chatbot-based workflow. Within 1 week of forming a team, we conducted a product development sprint and deployed the digital screening process. In the first 2 months of use, over 270 000 digital screens have been conducted. This process has reduced wait times for employees entering our hospitals during shift changes, allowed for physical distancing at hospital entrances, prevented higher-risk individuals from coming to work, and provided our healthcare leaders with robust, real-time data for make staffing decisions.

Rapid design and implementation of an integrated patient self-triage and self-scheduling tool for COVID-19.

OBJECTIVE: To rapidly deploy a digital patient-facing self-triage and self-scheduling tool in a large academic health system to address the COVID-19 pandemic. MATERIALS AND METHODS: We created a patient portal-based COVID-19 self-triage and self-scheduling tool and made it available to all primary care patients at the University of California, San Francisco Health, a large academic health system. Asymptomatic patients were asked about exposure history and were then provided relevant information. Symptomatic patients were triaged into 1 of 4 categories-emergent, urgent, nonurgent, or self-care-and then connected with the appropriate level of care via direct scheduling or telephone hotline. RESULTS: This self-triage and self-scheduling tool was designed and implemented in under 2 weeks. During the first 16 days of use, it was completed 1129 times by 950 unique patients. Of completed sessions, 315 (28%) were by asymptomatic patients, and 814 (72%) were by symptomatic patients. Symptomatic patient triage dispositions were as follows: 193 emergent (24%), 193 urgent (24%), 99 nonurgent (12%), 329 self-care (40%). Sensitivity for detecting emergency-level care was 87.5% (95% CI 61.7-98.5%). DISCUSSION: This self-triage and self-scheduling tool has been widely used by patients and is being rapidly expanded to other populations and health systems. The tool has recommended emergency-level care with high sensitivity, and decreased triage time for patients with less severe illness. The data suggests it also prevents unnecessary triage messages, phone calls, and in-person visits. CONCLUSION: Patient self-triage tools integrated into electronic health record systems have the potential to greatly improve triage efficiency and prevent unnecessary visits during the COVID-19 pandemic.

Saving without compromising: Teaching trainees to safely provide high value care.

Hospitals are increasingly shifting toward value-based reimbursement and focusing on cost consciousness and patient experience. These concepts are crucial to high-quality, affordable healthcare. However, physicians are not well-trained in factoring cost and patient experience into clinical decisions. The addition of these ideas may create the opportunity for patient harm by depriving patients of necessary care. We discuss ways for physicians to mitigate this risk by engaging in online high value care curricula, using a "5-Question High Value Care Time Out," getting mentorship from master clinicians and using clinical decision support tools.