Global, regional, and national age-sex-specific mortality for 282 causes of death in 195 countries and territories, 1980-2017: a systematic analysis for the Global Burden of Disease Study 2017.

BACKGROUND: Global development goals increasingly rely on country-specific estimates for benchmarking a nation's progress. To meet this need, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2016 estimated global, regional, national, and, for selected locations, subnational cause-specific mortality beginning in the year 1980. Here we report an update to that study, making use of newly available data and improved methods. GBD 2017 provides a comprehensive assessment of cause-specific mortality for 282 causes in 195 countries and territories from 1980 to 2017. METHODS: The causes of death database is composed of vital registration (VR), verbal autopsy (VA), registry, survey, police, and surveillance data. GBD 2017 added ten VA studies, 127 country-years of VR data, 502 cancer-registry country-years, and an additional surveillance country-year. Expansions of the GBD cause of death hierarchy resulted in 18 additional causes estimated for GBD 2017. Newly available data led to subnational estimates for five additional countries-Ethiopia, Iran, New Zealand, Norway, and Russia. Deaths assigned International Classification of Diseases (ICD) codes for non-specific, implausible, or intermediate causes of death were reassigned to underlying causes by redistribution algorithms that were incorporated into uncertainty estimation. We used statistical modelling tools developed for GBD, including the Cause of Death Ensemble model (CODEm), to generate cause fractions and cause-specific death rates for each location, year, age, and sex. Instead of using UN estimates as in previous versions, GBD 2017 independently estimated population size and fertility rate for all locations. Years of life lost (YLLs) were then calculated as the sum of each death multiplied by the standard life expectancy at each age. All rates reported here are age-standardised

Building Compassionate Experience Through Compassionate Action: Qualitative Behavioral Analysis

BackgroundThe acceleration of technology-based primary care during the COVID-19 pandemic outpaced the ability to understand whether and how it impacts care delivery and outcomes. As technology-based care continues to evolve, focusing on the core construct of compassion in a primary care context will help ensure high-quality patient care and increased patient autonomy and satisfaction. The ability to successfully operationalize the use of technology in patient-clinician interactions hinges on understanding not only how compassionate care is experienced in this context but also how clinicians can create it. ObjectiveThe objectives of this study were to understand whether and how compassionate behaviors are experienced in technology-based primary care interactions and identify the individual and contextual drivers that influence whether and how these behaviors occur. MethodsWe conducted a series of qualitative one-on-one interviews with primary care physicians, nurses, and patients. Qualitative data were initially analyzed using an inductive thematic analysis approach to identify preliminary themes for each participant group independently. We then looked across participant groups to identify areas of alignment and distinction. Descriptions of key behaviors that participants identified as elements of a compassionate interaction and descriptions of key drivers of these behaviors were inductively coded and defined at this stage. ResultsA total of 74 interviews were conducted with 40 patients, 20 nurses, and 14 primary care physicians. Key behaviors that amplified the experience of compassion included asking the patient’s modality preference, using video to establish technology-based presence, sharing the screen, and practicing effective communication. Participants’ knowledge or skills as well as their beliefs and emotions influenced whether or not these behaviors occurred. Contextual elements beyond participants’ control influenced technology-based interactions, including resource access, funding structures, culture, regulatory standards, work structure, societal influence, and patient characteristics and needs. A high-yield, evidence-based approach to address the identified drivers of compassion-focused clinician behavior includes a combination of education, training, and enablement. ConclusionsMuch of the patient experience is influenced by clinician behavior; however, clinicians need a supportive system and adequate supports to evolve new ways of working to create the experience of compassionate care. The current state of technology-based care operationalization has led to widespread burnout, societal pressure, and shifting expectations of both clinicians and the health system more broadly, threatening the ability to deliver compassionate care. For clinicians to exhibit compassionate behaviors, they need more than just adequate supports; they also need to receive compassion from and experience the humanity of their patients

sj-docx-1-jtt-10.1177_1357633X231167905 - Supplemental material for Understanding how virtual care has shifted primary care interactions and patient experience: A qualitative analysis

Supplemental material, sj-docx-1-jtt-10.1177_1357633X231167905 for Understanding how virtual care has shifted primary care interactions and patient experience: A qualitative analysis by Kelly Wu, Marlena Dang Nguyen, Geneviève Rouleau, Rhea Azavedo, Diya Srinivasan, and Laura Desveaux in Journal of Telemedicine and Telecare</p