Lesson 1 The loosening of federal government regulations enabled the rapid scaling of telehealth, as it enabled providers to be reimbursed for video visits at the same rate as in-person services. Lesson 2 While resistance to change was the norm, the COVID-19 crisis motivated improvements to four major internal operational workflows (scheduling, appointment conversions, patient support and Virtual Rooming Assistants) for video visits, which were met with acceptance by both clinical and non-clinical staff. Lesson 3 Leveraging prior intraorganizational relationships and active collaboration between different stakeholders, helped drive rapid operational change. An ongoing centralized communication and support strategy, ensured all stakeholders were informed and engaged during these uncertain times. Lesson 4 Regular electronic health record (EHR) training and educational material increased end-user knowledge of video visits and helped ensure the visit was safe, medically effective and maintained patient-provider relationships. Lesson 5 A clearly defined intake and evaluation process to filter out technologies that do not integrate with the patient portal or the EHR, ensures operational consistency and long-term sustainability. Lesson 6 Personalized support to patients of different levels of technical literacy with using the preferred patient portal and application, was vital to its use, adoption and overall patient experience.There has been longstanding interest in virtual care in oncology, but outdated reimbursement structures and a paradoxical lack of agility within electronic systems limited widespread adoption. Through the example of the Province of Ontario, Canada and the Princess Margaret Cancer Centre, we describe how a collective sense of action from COVID-19, a system of distributed leadership and decision-making, and the use of a Service Design process to map the ambulatory encounter onto a digital workflow were critical enablers of a large-scale virtual transition. Rigorous evaluation of virtual care models will be essential to maintain integration of virtual care post-pandemic.
  To describe the association between longitudinal enrollment in Medicare Advantage (MA) and utilization, access, quality of care, and health outcomes for beneficiaries with complex health needs.
 
  Beneficiary characteristics, enrollment, and outcomes data from the 2004-2016 waves of the Health and Retirement Study (HRS).
 
  Using the HRS panel structure, we identified beneficiaries consistently reporting high needs as well as enrollment in MA versus traditional Medicare (TM).  https://www.selleckchem.com/products/Gefitinib.html  We first evaluated a robust set of beneficiary characteristics to identify those that distinguish beneficiaries who consistently enrolled in MA versus TM. We then described adjusted differences in outcomes between high-needs beneficiaries who consistently enrolled in MA versus TM.
 
  Among high-needs beneficiaries, there was a modest amount of favorable selection into MA based on health. Controlling for several characteristics, MA enrollees used less care (with a 6.6 percentage point (pp) lower probability of hospitalization, 4.7 fewer physician visits, and a 5.1 pp lower probability of using home health care), had a 4.1 pp greater probability of being unable to afford their care, and had a 5.7 pp lower probability of reporting that they were very satisfied with their care. Compared to associations between MA and outcomes for high-needs beneficiaries, for non-high-needs beneficiaries MA enrollment was associated with smaller decreases in utilization and no statistically significant difference in the inability to afford care.
 
  Our descriptive findings raise the possibility that high-needs beneficiaries may experience unique challenges in MA compared to their non-high-needs counterparts.
 Our descriptive findings raise the possibility that high-needs beneficiaries may experience unique challenges in MA compared to their non-high-needs counterparts.The COVID-19 pandemic has created unique challenges for the U.S. healthcare system due to the staggering mismatch between healthcare system capacity and patient demand. The healthcare industry has been a relatively slow adopter of digital innovation due to the conventional belief that humans need to be at the center of healthcare delivery tasks. However, in the setting of the COVID-19 pandemic, artificial intelligence (AI) may be used to carry out specific tasks such as pre-hospital triage and enable clinicians to deliver care at scale. Recognizing that the majority of COVID-19 cases are mild and do not require hospitalization, Partners HealthCare (now Mass General Brigham) implemented a digitally-automated pre-hospital triage solution to direct patients to the appropriate care setting before they showed up at the emergency department and clinics, which would otherwise consume resources, expose other patients and staff to potential viral transmission, and further exacerbate supply-and-demand mismatching. Although the use of AI has been well-established in other industries to optimize supply and demand matching, the introduction of AI to perform tasks remotely that were traditionally performed in-person by clinical staff represents a significant milestone in healthcare operations strategy.We examined Bartonella prevalence in 281 bat flies collected from 114 eastern bent-wing bats (Miniopterus fuliginosus) in Japan and phylogenetically analyzed with other bat fly and bat strains. The bat flies were identified as Penicilidia jenynsii (PJ; n = 45), Nycteribia allotopa (NA; n = 157), and novel Nycteribia species (NS; n = 79). Bartonella DNAs were detected in 31.7 % (89/281) of bat flies by PCR targeting the citrate synthase (gltA) gene. The prevalence of Bartonella DNA among the bat flies was 47.1 % (74/157) in NA, 15.2 % (12/79) in NS, and 6.7 % (3/45) in PJ. Bartonella bacteria were also isolated from two NA and one NS. A phylogenetic analysis of the gltA sequences revealed that bat fly-associated strains were classified into three lineages and the same lineages of Bartonella were commonly detected from both Nycteribia bat flies and Miniopterus bats. These results suggest that Nycteribia bat flies are potential vectors for transmitting Bartonella among Miniopterus bats.