ABSTRACT
Whakarongorau Aotearoa/New Zealand Telehealth Services, formerly known as Homecare Medical, is New Zealand's largest digital healthcare service. It originated as a house call doctor service about 20 years ago and now delivers free 24/7 telehealth services to the New Zealand public 365 days a year. Whakarongorau Aotearoa changed its name in April 2021 to reflect the growing kaupapa and was gifted this whakataukî: He reo mārohirohi ka taringa rongohia-A brave voice deserves a listening ear. This viewpoint sets out to address a number of public and professional misconceptions about Whakarongorau Aotearoa and provide a more detailed description of the depth, breadth and complexity of the organisation, how it is structured, the range of services available to the public and its clinical governance, leadership and oversight.
ABSTRACT
BackgroundBubble CPAP may be used in infants with suspected or confirmed COVID-19. Electrostatic filters may reduce cross-infection. This study aims to determine if including a filter in the bubble CPAP circuit impacts stability of pressure delivery. MethodsA new electrostatic filter was placed before (pre) or after (post) the bubble CPAP generator, or with no filter (control) in an in vitro study. Pressure was recorded at the nasal interface for 18 h (6 L/min; 7 cmH2O) on three occasions for each configuration. Filter failure was defined as pressure >9 cmH20 for 60 continuous minutes. The filter was weighed before and after each experiment. ResultsMean (SD) time to reach the fail-point was 257 (116) min and 525 (566) min for filter placement pre- and post-CPAP generator, respectively. Mean pressure was higher throughout in the pre-generator position compared to control. The filter weight was heavier at study end in the pre-compared to the post-generator position. ConclusionsPlacement of the filter at the pre-generator position in a bubble CPAP circuit should be avoided due to unstable mean pressure. Filters are likely to become saturated with water over time. The post-generator position may accommodate a filter, but regular pressure monitoring and early replacement are required.
Subject(s)
COVID-19ABSTRACT
Background: Cancer and multiple non-cancer conditions are considered by the Centers for Disease Control and Prevention (CDC) as high risk conditions in the COVID-19 emergency. Professional societies have recommended changes in cancer service provision to minimize COVID-19 risks to cancer patients and health care workers. However, we do not know the extent to which cancer patients, in whom multi-morbidity is common, may be at higher overall risk of mortality as a net result of multiple factors including COVID-19 infection, changes in health services, and socioeconomic factors. Methods: We report multi-center, weekly cancer diagnostic referrals and chemotherapy treatments until April 2020 in England and Northern Ireland. We analyzed population-based health records from 3,862,012 adults in England to estimate 1-year mortality in 24 cancer sites and 15 non-cancer comorbidity clusters (40 conditions) recognized by CDC as high-risk. We estimated overall (direct and indirect) effects of COVID-19 emergency on mortality under different Relative Impact of the Emergency (RIE) and different Proportions of the population Affected by the Emergency (PAE). We applied the same model to the US, using Surveillance, Epidemiology, and End Results (SEER) program data. Results: Weekly data until April 2020 demonstrate significant falls in admissions for chemotherapy (45-66% reduction) and urgent referrals for early cancer diagnosis (70-89% reduction), compared to pre-emergency levels. Under conservative assumptions of the emergency affecting only people with newly diagnosed cancer (incident cases) at COVID-19 PAE of 40%, and an RIE of 1.5, the model estimated 6,270 excess deaths at 1 year in England and 33,890 excess deaths in the US. In England, the proportion of patients with incident cancer with [≥]1 comorbidity was 65.2%. The number of comorbidities was strongly associated with cancer mortality risk. Across a range of model assumptions, and across incident and prevalent cancer cases, 78% of excess deaths occur in cancer patients with [≥]1 comorbidity. Conclusion: We provide the first estimates of potential excess mortality among people with cancer and multimorbidity due to the COVID-19 emergency and demonstrate dramatic changes in cancer services. To better inform prioritization of cancer care and guide policy change, there is an urgent need for weekly data on cause-specific excess mortality, cancer diagnosis and treatment provision and better intelligence on the use of effective treatments for comorbidities.