More Like this

1. Criminalization of Care: Drug Testing Pregnant Patients

   https://doi.org/10.1177/00221465211058152  

   McCabe, Katharine (November 2021, Journal of Health and Social Behavior)

   This article reveals how law and legal interests transform medicine. Drawing on qualitative interviews with medical professionals, this study shows how providers mobilize law and engage in investigatory work as they deliver care. Using the case of drug testing pregnant patients, I examine three mechanisms by which medico-legal hybridity occurs in clinical settings. The first mechanism, clinicalization, describes how forensic tools and methods are cast in clinical terminology, effectively cloaking their forensic intent. In the second, medical professionals informally rank the riskiness of illicit substances using both medical and criminal-legal assessments. The third mechanism describes how gender, race, and class inform forensic decision-making and criminal suspicion in maternal health. The findings show that by straddling both medical and legal domains, medicine conforms to the standards and norms of neither institution while also suspending meaningful rights for patients seeking care. 

   more » « less
2. Distress and self-care among chaplains working in palliative care

   https://doi.org/10.1017/S1478951518001062  

   White, Kelsey B.; Murphy, Patricia E.; Jeuland, Jane; Fitchett, George (October 2019, Palliative and Supportive Care)

   Abstract Background The prevalence of burnout and distress among palliative care professionals has received much attention since research suggests it negatively impacts the quality of care. Although limited, research suggests low levels of burnout or distress among healthcare chaplains; however, there has been no research among chaplains working in specific clinical contexts, including palliative care. Objective This study explored the distress, self-care, and debriefing practices of chaplains working in palliative care. Method Exploratory, cross-sectional survey of professional chaplains. Electronic surveys were sent to members of four professional chaplaincy organizations between February and April 2015. Primary measures of interest included Professional Distress, Distress from Theodicy, Informal Self-care, Formal Self-care, and debriefing practices. Result More than 60% of chaplains working in palliative care reported feeling worn out in the past 3 months because of their work as a helper; at least 33% practice Informal Self-care weekly. Bivariate analysis suggested significant associations between Informal Self-care and both Professional Distress and Distress from Theodicy. Multivariate analysis also identified that distress decreased as Informal and Formal Self-care increased. Significance of results Chaplains working in palliative care appear moderately distressed, possibly more so than chaplains working in other clinical areas. These chaplains also use debriefing, with non-chaplain palliative colleagues, to process clinical experiences. Further research is needed about the role of religious or spiritual beliefs and practices in protecting against stress associated with care for people at the end of life. 

   more » « less
3. Machine learning-based prediction of low-value care for hospitalized patients

   https://doi.org/10.1016/j.ibmed.2023.100115  

   King, Andrew J; Tang, Lu; Davis, Billie S; Preum, Sarah M; Bukowski, Leigh A; Zimmerman, John; Kahn, Jeremy M (January 2023, Intelligence-Based Medicine)
4. Early prediction of level-of-care requirements in patients with COVID-19

   https://doi.org/10.7554/eLife.60519  

   Hao, Boran; Sotudian, Shahabeddin; Wang, Taiyao; Xu, Tingting; Hu, Yang; Gaitanidis, Apostolos; Breen, Kerry; Velmahos, George C; Paschalidis, Ioannis Ch (October 2020, eLife)

   null (Ed.)

   The new coronavirus (now named SARS-CoV-2) causing the disease pandemic in 2019 (COVID-19), has so far infected over 35 million people worldwide and killed more than 1 million. Most people with COVID-19 have no symptoms or only mild symptoms. But some become seriously ill and need hospitalization. The sickest are admitted to an Intensive Care Unit (ICU) and may need mechanical ventilation to help them breath. Being able to predict which patients with COVID-19 will become severely ill could help hospitals around the world manage the huge influx of patients caused by the pandemic and save lives. Now, Hao, Sotudian, Wang, Xu et al. show that computer models using artificial intelligence technology can help predict which COVID-19 patients will be hospitalized, admitted to the ICU, or need mechanical ventilation. Using data of 2,566 COVID-19 patients from five Massachusetts hospitals, Hao et al. created three separate models that can predict hospitalization, ICU admission, and the need for mechanical ventilation with more than 86% accuracy, based on patient characteristics, clinical symptoms, laboratory results and chest x-rays. Hao et al. found that the patients’ vital signs, age, obesity, difficulty breathing, and underlying diseases like diabetes, were the strongest predictors of the need for hospitalization. Being male, having diabetes, cloudy chest x-rays, and certain laboratory results were the most important risk factors for intensive care treatment and mechanical ventilation. Laboratory results suggesting tissue damage, severe inflammation or oxygen deprivation in the body's tissues were important warning signs of severe disease. The results provide a more detailed picture of the patients who are likely to suffer from severe forms of COVID-19. Using the predictive models may help physicians identify patients who appear okay but need closer monitoring and more aggressive treatment. The models may also help policy makers decide who needs workplace accommodations such as being allowed to work from home, which individuals may benefit from more frequent testing, and who should be prioritized for vaccination when a vaccine becomes available. 

   more » « less
5. Patients cannot consent to care unless they know how much it costs

   https://doi.org/10.1136/bmj.o1747  

   Pierson, Leah; Pierson, Emma (July 2022, BMJ)

   Given the impact that medical expenses have, disclosing them should be a part of the informed consent process, argue Leah Pierson and Emma Pierson 

   more » « less