Evaluation of Telehealth Visit Attendance After Implementation of a Patient Navigator Program.

Importance: The dramatic rise in use of telehealth accelerated by COVID-19 created new telehealth-specific challenges as patients and clinicians adapted to technical aspects of video visits. Objective: To evaluate a telehealth patient navigator pilot program to assist patients in overcoming barriers to video visit access. Design, Setting, and Participants: This quality improvement study investigated visit attendance outcomes among those who received navigator outreach (intervention group) compared with those who did not (comparator group) at 2 US academic primary care clinics during a 12-week study period from April to July 2021. Eligible participants had a scheduled video visit without previous successful telehealth visits. Interventions: The navigator contacted patients with next-day scheduled video appointments by phone to offer technical assistance and answer questions on accessing the appointment. Main Outcomes and Measures: The primary outcome was appointment attendance following the intervention. Return on investment (ROI) accounting for increased clinic adherence and costs of implementation was examined as a secondary outcome. Results: A total 4066 patients had video appointments scheduled (2553 [62.8%] women; median [IQR] age: intervention, 55 years [38-66 years] vs comparator, 52 years [36-66 years]; P = .02). Patients who received the navigator intervention had significantly increased odds of attending their appointments (odds ratio, 2.0; 95% CI, 1.6-2.6) when compared with the comparator group, with an absolute increase of 9% in appointment attendance for the navigator group (949 of 1035 patients [91.6%] vs 2511 of 3031 patients [82.8%]). The program's ROI was $11 387 over the 12-week period. Conclusions and Relevance: In this quality improvement study, we found that a telehealth navigator program was associated with significant improvement in video visit adherence with a net financial gain. Our findings have relevance for efforts to reduce barriers to telehealth-based health care and increase equity.

Trends in Filled Naloxone Prescriptions Before and During the COVID-19 Pandemic in the United States.

This cohort study analyzes the trends in filled naloxone prescriptions during the COVID-19 pandemic in the United States and compare these to opioid prescriptions and overall prescriptions.

Assessment of a Crisis Standards of Care Scoring System for Resource Prioritization and Estimated Excess Mortality by Race, Ethnicity, and Socially Vulnerable Area During a Regional Surge in COVID-19.

Importance: Crisis standards of care (CSOC) scores designed to allocate scarce resources during the COVID-19 pandemic could exacerbate racial disparities in health care. Objective: To analyze the association of a CSOC scoring system with resource prioritization and estimated excess mortality by race, ethnicity, and residence in a socially vulnerable area. Design, Setting, and Participants: This retrospective cohort analysis included adult patients in the intensive care unit during a regional COVID-19 surge from April 13 to May 22, 2020, at 6 hospitals in a health care network in greater Boston, Massachusetts. Participants were scored by acute severity of illness using the Sequential Organ Failure Assessment score and chronic severity of illness using comorbidity and life expectancy scores, and only participants with complete scores were included. The score was ordinal, with cutoff points suggested by the Massachusetts guidelines. Exposures: Race, ethnicity, Social Vulnerability Index. Main Outcomes and Measures: The primary outcome was proportion of patients in the lowest priority score category stratified by self-reported race. Secondary outcomes were discrimination and calibration of the score overall and by race, ethnicity, and neighborhood Social Vulnerability Index. Projected excess deaths were modeled by race, using the priority scoring system and a random lottery. Results: Of 608 patients in the intensive care unit during the study period, 498 had complete data and were included in the analysis; this population had a median (IQR) age of 67 (56-75) years, 191 (38.4%) female participants, 79 (15.9%) Black participants, and 225 patients (45.7%) with COVID-19. The area under the receiver operating characteristic curve for the priority score was 0.79 and was similar across racial groups. Black patients were more likely than others to be in the lowest priority group (12 [15.2%] vs 34 [8.1%]; P = .046). In an exploratory simulation model using the score for ventilator allocation, with only those in the highest priority group receiving ventilators, there were 43.9% excess deaths among Black patients (18 of 41 patients) and 28.6% (58 of 203 patients among all others (P = .05); when the highest and intermediate priority groups received ventilators, there were 4.9% (2 of 41 patients) excess deaths among Black patients and 3.0% (6 of 203) among all others (P = .53). A random lottery resulted in more excess deaths than the score. Conclusions and Relevance: In this study, a CSOC priority score resulted in lower prioritization of Black patients to receive scarce resources. A model using a random lottery resulted in more estimated excess deaths overall without improving equity by race. CSOC policies must be evaluated for their potential association with racial disparities in health care.

Patterns of Recovery in Cardiovascular Care after the COVID-19 Pandemic Surge.

BACKGROUND: Cardiovascular disease remains the number one cause of death globally. Patients with cardiovascular disease are at risk of poor outcomes from deferral of healthcare during the coronavirus disease 2019 (COVID-19) pandemic. Little is known about recovery of cardiovascular hospitalizations or procedural volume following the COVID-19 surges. We sought to examine the cardiovascular diagnoses requiring healthcare utilization surrounding the first and second COVID-19 waves and characterize trends in return to pre-pandemic levels at a tertiary care center in Massachusetts. MATERIALS AND METHODS: Using electronic health records and administrative claims data, we performed a retrospective analysis of patients undergoing cardiovascular procedures and admitted to inpatient cardiology services throughout the first two COVID surges. ICD-10 codes were used to categorize admissions. RESULTS: Patients who presented for care during the initial COVID-19 surge were younger, had higher comorbidity burden, and longer length-of-stay compared with pre- and post-surge. Marked declines in admissions in the first wave (to 29% of pre-surge levels) followed eventually by complete recovery were noted across all cardiac diagnoses, with smaller declines seen in the second wave. Cardiac procedural volume declined significantly during the initial surge but quickly rebounded post-surge, eventually eclipsing pre-COVID volume. CONCLUSIONS: There was a gradual but initially incomplete recovery to pre-surge levels of hospitalizations and procedures during the reopening phase, which eventually rebounded to meet or exceed pre-COVID-19 levels. To the extent that this reflects deferred or foregone essential care, it may adversely affect long-term cardiovascular outcomes. These results should inform planning for cardiovascular care delivery during future pandemic surges.

Secondary Use of COVID-19 Symptom Incidence Among Hospital Employees as an Example of Syndromic Surveillance of Hospital Admissions Within 7 Days.

Importance: Alternative methods for hospital occupancy forecasting, essential information in hospital crisis planning, are necessary in a novel pandemic when traditional data sources such as disease testing are limited. Objective: To determine whether mandatory daily employee symptom attestation data can be used as syndromic surveillance to estimate COVID-19 hospitalizations in the communities where employees live. Design, Setting, and Participants: This cohort study was conducted from April 2, 2020, to November 4, 2020, at a large academic hospital network of 10 hospitals accounting for a total of 2384 beds and 136 000 discharges in New England. The participants included 6841 employees who worked on-site at hospital 1 and lived in the 10 hospitals' service areas. Exposure: Daily employee self-reported symptoms were collected using an automated text messaging system from a single hospital. Main Outcomes and Measures: Mean absolute error (MAE) and weighted mean absolute percentage error (MAPE) of 7-day forecasts of daily COVID-19 hospital census at each hospital. Results: Among 6841 employees living within the 10 hospitals' service areas, 5120 (74.8%) were female individuals and 3884 (56.8%) were White individuals; the mean (SD) age was 40.8 (13.6) years, and the mean (SD) time of service was 8.8 (10.4) years. The study model had a MAE of 6.9 patients with COVID-19 and a weighted MAPE of 1.5% for hospitalizations for the entire hospital network. The individual hospitals had an MAE that ranged from 0.9 to 4.5 patients (weighted MAPE ranged from 2.1% to 16.1%). For context, the mean network all-cause occupancy was 1286 during this period, so an error of 6.9 is only 0.5% of the network mean occupancy. Operationally, this level of error was negligible to the incident command center. At hospital 1, a doubling of the number of employees reporting symptoms (which corresponded to 4 additional employees reporting symptoms at the mean for hospital 1) was associated with a 5% increase in COVID-19 hospitalizations at hospital 1 in 7 days (regression coefficient, 0.05; 95% CI, 0.02-0.07; P < .001). Conclusions and Relevance: This cohort study found that a real-time employee health attestation tool used at a single hospital could be used to estimate subsequent hospitalizations in 7 days at hospitals throughout a larger hospital network in New England.

Trends in telehealth and in-person transitional care management visits during the COVID-19 pandemic.

BACKGROUND/OBJECTIVES: Transitional care management (TCM) visits delivered following hospitalization have been associated with reductions in mortality, readmissions, and total costs; however, uptake remains low. We sought to describe trends in TCM visit delivery during the COVID-19 pandemic. DESIGN: Cross-sectional study of ambulatory electronic health records from December 30, 2019 and January 3, 2021. SETTING: United States. PARTICIPANTS: Forty four thousand six hundred and eighty-one patients receiving transitional care management services. MEASUREMENTS: Weekly rates of in-person and telehealth TCM visits before COVID-19 was declared a national emergency (December 30, 2019 to March 15, 2020), during the initial pandemic period (March 16, 2020 to April 12, 2020) and later period (April 12, 2020 to January 3, 2021). Characteristics of patients receiving in-person and telehealth TCM visits were compared. RESULTS: A total of 44,681 TCM visits occurred during the study period with the majority of patients receiving TCM visits age 65 years and older (68.0%) and female (55.0%) Prior to the COVID-19 pandemic, nearly all TCM visits were conducted in-person. In the initial pandemic, there was an immediate decline in overall TCM visits and a rise in telehealth TCM visits, accounting for 15.4% of TCM visits during this period. In the later pandemic, the average weekly number of TCM visits was 841 and 14.0% were telehealth. During the initial and later pandemic periods, 73.3% and 33.6% of COVID-19-related TCM visits were conducted by telehealth, respectively. Across periods, patterns of telehealth use for TCM visits were similar for younger and older adults. CONCLUSION: The study findings highlight a novel and sustained shift to providing TCM services via telehealth during the COVID-19 pandemic, which may reduce barriers to accessing a high-value service for older adults during a vulnerable transition period. Further investigations comparing outcomes of in-person and telehealth TCM visits are needed to inform innovation in ambulatory post-discharge care.

Implementing Electronic Patient-Reported Outcomes for Patients With New Oral Chemotherapy Prescriptions at an Academic Site and a Community Site.

PURPOSE: Oral chemotherapy challenges providers' abilities to safely monitor patients' symptoms, adherence, and financial toxicity. COVID-19 has increased the urgency of caring for patients remotely. Collection of electronic patient-reported outcomes (ePROs) has demonstrated efficacy for patients on intravenous chemotherapy, but limited data support their use in oral chemotherapy. We undertook a pilot project to assess the feasibility of implementing an ePRO system for patients starting oral chemotherapy at our cancer center, which includes both an academic site and a community site. METHODS: Patients initiating oral chemotherapy were asked to participate. A five-question tool was built in REDCap. Concerning responses triggered outreach within one business day. The primary outcome was time to first symptom assessment. For comparison, we used a historical cohort of patients who had been prescribed oral chemotherapies by providers in the same disease groups at the cancer center. RESULTS: Twenty-five of 62 (40%) patients completed ePRO assessments. Fifty historical charts were reviewed. Time to first symptom assessment was 7 days (IQR, 4-14 days) in the historical group compared with 3 days (IQR, 2-4 days) in the ePRO group. Time to clinical action was 14 days (7-35 days) in the historical group compared with 8 days (4-19 days) in the ePRO group. No statistically significant differences were detected in 30-day emergency department visit or hospitalization (12% for both groups) or 90-day emergency department visit or hospitalization rates (historical 28% and ePRO 20%). CONCLUSION: An ePRO tool monitoring patient concerns about adherence, cost, and toxicities for patients with new oral chemotherapy regimens is feasible and improves time to symptom assessment. Further investigation is needed to improve patient engagement with ePROs and evaluate the long-term impacts for patients on oral chemotherapy.

Reopening businesses and risk of COVID-19 transmission.

The true risk of a COVID-19 resurgence as states reopen businesses is unknown. In this paper, we used anonymized cell-phone data to quantify the potential risk of COVID-19 transmission in business establishments by building a Business Risk Index that measures transmission risk over time. The index was built using two metrics, visits per square foot and the average duration of visits, to account for both density of visits and length of time visitors linger in the business. We analyzed trends in traffic patterns to 1,272,260 businesses across eight states from January 2020 to June 2020. We found that potentially risky traffic behaviors at businesses decreased by 30% by April. Since the end of April, the risk index has been increasing as states reopen. There are some notable differences in trends across states and industries. Finally, we showed that the time series of the average Business Risk Index is useful for forecasting future COVID-19 cases at the county-level (P < 0.001). We found that an increase in a county's average Business Risk Index is associated with an increase in positive COVID-19 cases in 1 week (IRR: 1.16, 95% CI: (1.1-1.26)). Our risk index provides a way for policymakers and hospital decision-makers to monitor the potential risk of COVID-19 transmission from businesses based on the frequency and density of visits to businesses. This can serve as an important metric as states monitor and evaluate their reopening strategies.