Identifying Optimal Acute Care Comparators to Inform the Evaluation of an Advanced Care at Home Pilot Program.

BACKGROUND: Hospital at Home (H@H) programs-which seek to deliver acute care within a patient's home-have become more prevalent over time. However, existing literature exhibits heterogeneity in program structure, evaluation design, and target population size, making it difficult to draw generalizable conclusions to inform future H@H program design. OBJECTIVE: The objective of this work was to develop a quality improvement evaluation strategy for a H@H program-the Kaiser Permanente Advanced Care at Home (KPACAH) program in Northern California-leveraging electronic health record data, chart review, and patient surveys to compare KPACAH patients with inpatients in traditional hospital settings. METHODS: The authors developed a 3-step recruitment workflow that used electronic health record filtering tools to generate a daily list of potential comparators, a manual chart review of potentially eligible comparator patients to assess individual clinical and social criteria, and a phone interview with patients to affirm eligibility and interest from potential comparator patients. RESULTS: This workflow successfully identified and enrolled a population of 446 comparator patients in a 5-month period who exhibited similar demographics, reasons for hospitalization, comorbidity burden, and utilization measures to patients enrolled in the KPACAH program. CONCLUSION: These initial findings provide promise for a workflow that can facilitate the identification of similar inpatients hospitalized at traditional brick and mortar facilities to enhance outcomes evaluations for the H@H programs, as well as to identify the potential volume of enrollees as the program expands.

[Light-curing effectiveness using led lamps: a review]. / Efectividad de fotopolimerización usando lámparas led: una revisión.

Introduction: LED lamps have a new light-curing technology which can be monowave or polywave, which allows it to reach more initiators such as camphorquinone, Lucirin TPO and Propanodione, which have a wide variety of advantages and disadvantages. These lamps have evolved over time, as have different ergonomics, longevity, systems and quality standards. Objective: The objective of this literature review is to improve the clinician on the proper use of different LED lamps and how they influence the efficiency of resin photopolymerization. Material and methods: Extensive research has been carried out in the existing literature on this topic. From the beginning of this information until April 18, 2022, the bibliographic search carried out includes 86 articles published in the Medline database through PubMed, LILACS, Science Direct and SciELO, and there is no language restriction. Results: The photopolymerization effects of Polywave and Monowave LED lamps present significant differences between the compressive strength of the light-cured resin, with single-wave and polyvalent LED lamps where the types of light and lamp directly influence the compressive strength of the resin. composite resins. Conclusion: The type of light and lamp directly affects the efficiency of the photopolymerization of the composite resin, so it is concluded that LED lamps with single wave technology (Monowave) produce a greater depth of photopolymerization than those with multiple wave technology (Polywave).

Alternative Strategies for the Estimation of a Disease's Basic Reproduction Number: A Model-Agnostic Study.

This work presents a model-agnostic evaluation of four different models that estimate a disease's basic reproduction number. The evaluation presented is twofold: first, the theory behind each of the models is reviewed and compared; then, each model is tested with eight impartial simulations. All scenarios were constructed in an experimental framework that allows each model to fulfill its assumptions and hence, obtain unbiased results for each case. Among these models is the one proposed by Thompson et al. (Epidemics 29:100356, 2019), i.e., a Bayesian estimation method well established in epidemiological practice. The other three models include a novel state-space method and two simulation-based approaches based on a Poisson infection process. The advantages and flaws of each model are discussed from both theoretical and practical standpoints. Finally, we present the evolution of Covid-19 outbreak in Colombia as a case study for computing the basic reproduction number with each one of the reviewed methods.

Assessment of Value of Neighborhood Socioeconomic Status in Models That Use Electronic Health Record Data to Predict Health Care Use Rates and Mortality.

Importance: Prediction models are widely used in health care as a way of risk stratifying populations for targeted intervention. Most risk stratification has been done using a small number of predictors from insurance claims. However, the utility of diverse nonclinical predictors, such as neighborhood socioeconomic contexts, remains unknown. Objective: To assess the value of using neighborhood socioeconomic predictors in the context of 1-year risk prediction for mortality and 6 different health care use outcomes in a large integrated care system. Design, Setting, and Participants: Diagnostic study using data from all adults age 18 years or older who had Kaiser Foundation Health Plan membership and/or use in the Kaiser Permantente Northern California: a multisite, integrated health care delivery system between January 1, 2013, and June 30, 2014. Data were recorded before the index date for each patient to predict their use and mortality in a 1-year post period using a test-train split for model training and evaluation. Analyses were conducted in fall of 2019. Main Outcomes and Measures: One-year encounter counts (doctor office, virtual, emergency department, elective hospitalizations, and nonelective), total costs, and mortality. Results: A total of 2 951 588 patients met inclusion criteria (mean [SD] age, 47.2 [17.4] years; 47.8% were female). The mean (SD) Neighborhood Deprivation Index was -0.32 (0.84). The areas under the receiver operator curve ranged from 0.71 for emergency department use (using the LASSO method and electronic health record predictors) to 0.94 for mortality (using the random forest method and electronic health record predictors). Neighborhood socioeconomic status predictors did not meaningfully increase the predictive performance of the models for any outcome. Conclusions and Relevance: In this study, neighborhood socioeconomic predictors did not improve risk estimates compared with what is obtainable using standard claims data regardless of model used.

The Impact of Pharmacy-specific Predictors on the Performance of 30-Day Readmission Risk Prediction Models.

RESEARCH OBJECTIVE: Pharmacists are an expensive and limited resource in the hospital and outpatient setting. A pharmacist can spend up to 25% of their day planning. Time spent planning is time not spent delivering an intervention. A readmission risk adjustment model has potential to be used as a universal outcome-based prioritization tool to help pharmacists plan their interventions more efficiently. Pharmacy-specific predictors have not been used in the constructs of current readmission risk models. We assessed the impact of adding pharmacy-specific predictors on performance of readmission risk prediction models. STUDY DESIGN: We used an observational retrospective cohort study design to assess whether pharmacy-specific predictors such as an aggregate pharmacy score and drug classes would improve the prediction of 30-day readmission. A model of age, sex, length of stay, and admission category predictors was used as the reference model. We added predictor variables in sequential models to evaluate the incremental effect of additional predictors on the performance of the reference. We used logistic regression to regress the outcomes on predictors in our derivation dataset. We derived and internally validated our models through a 50:50 split validation of our dataset. POPULATION STUDIED: Our study population (n=350,810) was of adult admissions at hospitals in a large integrated health care delivery system. PRINCIPAL FINDINGS: Individually, the aggregate pharmacy score and drug classes caused a nearly identical but moderate increase in model performance over the reference. As a single predictor, the comorbidity burden score caused the greatest increase in model performance when added to the reference. Adding the severity of illness score, comorbidity burden score and the aggregate pharmacy score to the reference caused a cumulative increase in model performance with good discrimination (c statistic, 0.712; Nagelkerke R, 0.112). The best performing model included all predictors: severity of illness score, comorbidity burden score, aggregate pharmacy score, diagnosis groupings, and drug subgroups. CONCLUSIONS: Adding the aggregate pharmacy score to the reference model significantly increased the c statistic but was out-performed by the comorbidity burden score model in predicting readmission. The need for a universal prioritization tool for pharmacists may therefore be potentially met with the comorbidity burden score model. However, the aggregate pharmacy score and drug class models still out-performed current Medicare readmission risk adjustment models. IMPLICATIONS FOR POLICY OR PRACTICE: Pharmacists have a great role in preventing readmission, and therefore can potentially use one of our models: comorbidity burden score model, aggregate pharmacy score model, drug class model or complex model (a combination of all 5 major predictors) to prioritize their interventions while exceeding Medicare performance measures on readmission. The choice of model to use should be based on the availability of these predictors in the health care system.

Periadolescent Maturation of GABAergic Hyperpolarization at the Axon Initial Segment.

Neuronal chloride levels are developmentally regulated. Early in life, high intracellular concentrations support chloride efflux and depolarization at GABAergic synapses. In mouse, intracellular chloride decreases over the first postnatal week in the somatodendritic compartment, eventually supporting mature, hyperpolarizing GABAergic inhibition. In contrast to this dendritic switch, it is less clear how GABAergic signaling at the axon initial segment (AIS) functions in mature pyramidal cells, as reports of both depolarization and hyperpolarization have been reported in the AIS past the first postnatal week. Here, we show that GABAergic signaling at the AIS of prefrontal pyramidal cells, indeed, switches polarity from depolarizing to hyperpolarizing but does so over a protracted periadolescent period. This is the most delayed maturation in chloride reversal in any structure studied to date and suggests that chandelier cells, which mediate axo-axonic inhibition, play a unique role in the periadolescent maturation of prefrontal circuits.