A characterization of Samuel in terms of the psychological model of Erikson

Bibliography: leaves [131]-133.The story of Samuel forms an integral part of the Hebrew saga, marking the transition from the period of Judges to the Israelite monarchy. Book I of Samuel is unusual in that it portrays the birth, death and major episodes of the prophet's life. In fact, Samuel, along with Moses and Jeremiah, is one of the few characters whose full life history is documented in the Biblical text: we not only have the significant events which lead up to his birth, but he makes an appearance again after his death. Given this detail, the purpose of this study is to investigate whether a re-reading of the character of Samuel through a psychological model can throw fresh insights on how the Israelites effected the transition from a theocracy to a monarchy. The choice of Erikson is motivated by two considerations. In the first, Erikson extended the boundaries of Freudian psychoanalysis by describing both normal as well as abnormal development. His ego-psychology, with its eight-stage developmental plan, its theses and antitheses, is particularly suitable in the case of Samuel, whose life-cycle for the most part can be viewed as problematic, a series of crises. In the second, though he wrote prolifically on numerous leading historical figures and literary characters, Erikson himself never analysed a Biblical figure. This work is, however, not confined to a psychological typification of the character of Samuel. It is intended to be an interdisciplinary study: it deals with the text as an integrated literary unit and relies on the insights of classical Biblical scholarship to support many of its conclusions

Inadequate sensitivity of laboratory risk indicator to rule out necrotizing fasciitis in the emergency department

Introduction: Necrotizing fasciitis (NF) is a life-threatening illness, particularly when surgical debridement is delayed. The Laboratory Risk Indicator for Necrotizing Fasciitis (LRINEC) score was developed to identify patients at higher risk for NF. Despite limited information in this regard, the LRINEC score is often used to rule out NF if negative. We describe the sensitivity of the LRINEC score in emergency department (ED) patients for the diagnosis of NF. Methods: We conducted a chart review of ED patients in whom coding of hospital discharge diagnoses included NF. We employed standard methods to minimize bias. We used laboratory data to calculate the LRINEC score, and confirmed the diagnosis of NF via explicit chart review. We then calculated the sensitivity of a positive LRINEC score (standardly defined as six or greater) in our cohort. We examined the role of patient characteristics in the performance of the LRINEC score. Finally, we performed sensitivity analyses to estimate whether missing data for c-reactive protein (CRP) results were likely to impact our results. Results: Of 266 ED patients coded as having a discharge diagnosis of NF, we were able to confirm the diagnosis, by chart review, in 167. We were able to calculate a LRINEC score in only 80 patients (due to absence of an initial CRP value); an LRINEC score of 6 or greater had a sensitivity of 77%. Sensitivity analyses of missing data supported our finding of inadequate sensitivity to rule out NF. In sub-analysis, NF patients with concurrent diabetes were more likely to be accurately categorized by the LRINEC score. Conclusion: Used in isolation, the LRINEC score is not sufficiently sensitive to rule out NF in a general ED population. © 2016 Koenig et al

Association between state payment parity policies and telehealth usage at community health centers during COVID-19

OBJECTIVE: We study the association between payment parity policies and telehealth utilization at community health centers (CHCs) before, during, and after the onset of the pandemic. MATERIALS AND METHODS: We use aggregated, de-identified data from FAIR Health for privately insured patients at CHC sites. Descriptive statistics and time trends are calculated. Logistic regression models were used to quantify the factors associated with telehealth utilization for each of our time periods: 1) pre-pandemic (March-June 2019), 2) immediate pandemic response (March-June 2020), and 3) sustained pandemic response (March-June 2021). RESULTS: Telehealth usage rates at CHC sites surged to approximately 61% in April 2020. By April 2021, only 29% of CHC sites in states without payment parity policies used telehealth versus 42% in states without. Controlling for other characteristics, we find that CHC sites in states with payment parity were more likely to utilize telehealth one year after the onset of the pandemic (OR:1.740, p\u3c0.001) than states without, but did not find this association in 2019 or 2020. DISCUSSION: The public health emergency drove widespread use of telehealth, making the virtual care environment inherently different in 2021 than in 2019. Due to the unique fiscal constraints facing CHCs, the financial sustainability of telehealth may be highly relevant to the relationship between telehealth utilization and payment parity we find in this paper. CONCLUSION: Supportive payment policy and continued investments in broadband availability in rural and undeserved communities should enable CHCs to offer telehealth services to populations in these areas

Inadequate Sensitivity of Laboratory Risk Indicator to Rule Out Necrotizing Fasciitis in the Emergency Department

Introduction: Necrotizing fasciitis (NF) is a life-threatening illness, particularly when surgical debridement is delayed. The Laboratory Risk Indicator for Necrotizing Fasciitis (LRINEC) score was developed to identify patients at higher risk for NF. Despite limited information in this regard, the LRINEC score is often used to “rule out” NF if negative. We describe the sensitivity of the LRINEC score in emergency department (ED) patients for the diagnosis of NF. Methods: We conducted a chart review of ED patients in whom coding of hospital discharge diagnoses included NF. We employed standard methods to minimize bias. We used laboratory data to calculate the LRINEC score, and confirmed the diagnosis of NF via explicit chart review. We then calculated the sensitivity of a positive LRINEC score (standardly defined as six or greater) in our cohort. We examined the role of patient characteristics in the performance of the LRINEC score. Finally, we performed sensitivity analyses to estimate whether missing data for c-reactive protein (CRP) results were likely to impact our results. Results: Of 266 ED patients coded as having a discharge diagnosis of NF, we were able to confirm the diagnosis, by chart review, in 167. We were able to calculate a LRINEC score in only 80 patients (due to absence of an initial CRP value); an LRINEC score of 6 or greater had a sensitivity of 77%. Sensitivity analyses of missing data supported our finding of inadequate sensitivity to rule out NF. In sub-analysis, NF patients with concurrent diabetes were more likely to be accurately categorized by the LRINEC score. Conclusion: Used in isolation, the LRINEC score is not sufficiently sensitive to rule out NF in a general ED population

Improving Specialty Care Access via Telemedicine

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