Years of life lost during the Covid-19 pandemic in Sweden considering variation in life expectancy by level of geriatric care.

The Covid-19 pandemic has not affected the population evenly. This must be acknowledged when it comes to understanding the Covid-19 death toll and answering the question of how many life years have been lost. We use level of geriatric care to account for variation in remaining life expectancy among individuals that died during 2020. Based on a linkage of administrative registers, we estimate remaining life expectancy stratified by age, sex, and care status using an incidence-based multistate model and analyze the number of years of life lost (YLL) during 2020 in Sweden. Our results show that remaining life expectancy between individuals with and without care differs substantially. More than half of all Covid-19 deaths had a remaining life expectancy lower than 4 years. Yet, in a 1-year perspective, Covid-19 did not seem to replace other causes of death. Not considering the differences in remaining life expectancy in the affected populations overestimated YLL by 40% for women and 30% for men, or around 2 years per death. While the unadjusted YLL from Covid-19 amounted to an average of 7.5 years for women and 8.6 years for men, the corresponding YLL adjusted for care status were 5.4 and 6.6, respectively. The total number of YLL to Covid-19 in 2020 is comparable to YLL from ischemic heart disease in 2019 and 2020. Our results urge the use of subgroup specific mortality when counting the burden of Covid-19. YLL are considerably reduced when the varying susceptibility for death is considered, but even if most lifespans were cut in the last years of life, the YLL are still substantial.

Health System Success in Delivering Bamlanivimab Within Post-acute and Long-Term Care Facilities.

OBJECTIVES: Post-acute and long-term care (PALTC) residents are disproportionately affected by coronavirus 2019 (COVID-19). We describe a health system approach that incorporated PALTC stakeholders to treat residents effectively and efficiently with monoclonal antibodies during the pandemic. DESIGN: Retrospective observational. SETTING AND PARTICIPANTS: Integrated health system headquartered in Sioux Falls, South Dakota, with urban hub and surrounding rural communities. Patients of the health system include PALTC and assisted living (AL) residents of facilities. METHODS: Monoclonal Data Registry captured time to infusion after a positive COVID-19 test, residency (independent or PALTC), and site of infusion (PALTC, hospital outpatient, infusion center). AL residents are included in PALTC data. Registry limited to patients living in SD. Communication and operational resources were tailored to support PALTC infusions. The monoclonal antibody therapy administered to PALTC residents during the first 6 weeks after emergency use authorization (EUA) of monoclonal antibodies was bamlanivimab. The EUA for bamlanivimab was revoked due to lack of effectiveness against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants on April 16, 2021. RESULTS: The results are analyzed for the 6 weeks after bamlanivimab EUA. In PALTC, there was a median of 3 days between positive test and infusion. The total number of monoclonal antibody infusions captured in the registry during this time was 87 PALTC on-site infusions. CONCLUSION AND IMPLICATIONS: A collaborative approach between health system executives and PALTC experts quickly enabled access to potentially life-saving therapy to a vulnerable population. PALTC settings should be routinely included in health system investment and planning to improve the capacity of the system to achieve optimal outcomes, prevent unnecessary mortality, and preserve health care resources.

Video Visit: A New Tool for Diabetes Post-hospitalization Follow-up

Background: UPMC Diabetes Inpatient Service has been offering follow-up appointments to patients in endocrine clinic one week after discharge as an intervention to decrease readmissions. Unfortunately, these appointments have a very high no show rate and are only offered to a select group of patients who can show up to clinic in person. During COVID19 public health emergency as CMS started to reimburse video visits, our clinic switched to offer video visits one week following hospital stay. Whether video visits are effective for post-hospital follow-up is not known. Objective: The aim of this study is to understand the impact of post-hospital video visits in diabetic population outcomes and clinic utilization. Methods: We completed a retrospective chart review of patients with diabetes who had a follow-up appointment one week after discharge in 2019(August, September and October) and 2020(August, September and October). We compared no-show rates, utilization of physicians versus APPs, reduction in A1c between two groups. Results: August to November 2019, 42 office appointments were scheduled. 24/42 appointments were completed, and the no show rate was at 42%. Previsit (hospital) average A1c was 8.03%, which improved to an average of 7.4% 3 months following appointment. 92% of all appointments were completed by physicians, and 8% were completed by an APP. August to November 2020, 100 posthospital appointments were scheduled for diabetes service patients. 70 of 100(70%) agreed to complete video visits, 29/100 preferred office appointments. In video visit group, no show rate was only (8/70) 11%. Video visit group had a previsit (hospital) average A1c: 8.3%, 3 months after video visit average A1c improved to 6.3%. 32% of post-discharge visits were completed by a physician, 67% of were completed by an APP. Conclusion: In patients with diabetes, post-discharge video visits decreased no show rates, increased utilization of APPs while achieving to improve A1c.