Publications by authors named "Steven Asch"
Background: Humanitarian crises frequently garner solidarity and robust volunteer recruitment among health care communities. However, a common obstacle is matching providers to those in need across geographic and other barriers. We examined the application of a decentralised governance strategy in establishing an emergency telemedicine response, TeleHelp Ukraine (THU).
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- The study aimed to understand the values and preferences of caregivers for children with complex medical needs, specifically focusing on surgical decisions for neuromuscular scoliosis to help develop a decision support tool.
- Qualitative interviews were conducted with caregivers from different backgrounds, analyzing their experiences to identify key themes related to treatment choices and concerns.
- The findings revealed that caregivers prioritize pain management, mobility, quality of life, peer support, and the uncertainty of outcomes, highlighting the need for better decision-making support that considers their values and addresses uncertainties in treatment.
Article Synopsis
- - The study highlights the critical role of home and community-based services (HCBS) for Veterans, particularly in easing the burden on family caregivers, but notes that these services are underutilized despite the resources available through the VA.
- - Researchers conducted interviews with 23 caregivers of Veterans to identify unmet needs and barriers to accessing HCBS, uncovering themes such as the need for timely information, limited caregiver time (especially during COVID-19), desire for respite, and challenges in the caregiver-patient relationship.
- - The findings suggest that besides common barriers like service delays and caregiver stress, disagreements between Veterans and their caregivers can hinder access to HCBS, indicating that a comprehensive strategy is needed to improve service utilization.
Importance: Metabolic dysfunction-associated steatotic liver disease (MASLD) is an increasing cause of cirrhosis. Glucagon-like peptide 1 receptor agonists (GLP-1 RAs) are effective in improving liver inflammation in patients with MASLD.
Objective: To determine whether use of GLP-1 RAs is associated with lower risk of developing cirrhosis and its complications, including decompensation and hepatocellular cancer (HCC), among patients with MASLD.
Importance: US veterans may be at an increased risk of developing various dermatologic conditions compared with nonveterans.
Objectives: To compare the prevalence and the odds of dermatologic conditions (eg, skin cancers, dermatitis/eczema/rash, psoriasis) between veterans and nonveterans.
Design, Setting, And Participants: This population-based cross-sectional study leveraged nationally representative data from the National Health and Nutrition Examination Survey (NHANES).
Governments should evaluate advanced models and if needed impose safety measures.
View Article and Find Full Text PDFObjective: Evaluate whether cost-sharing decreases led high-deductible health plans (HDHP) enrollees to increase their use of healthcare.
Data Sources, Study Setting: National sample of chronically-ill patients age 18-64 from 2018 to 2020 (n = 1,318,178).
Study Design: Difference-in-differences analyses using entropy-balancing weights were used to evaluate the effect of a policy shift to $0 cost-sharing for telehealth on utilization for HDHP compared with non-HDHP enrollees.
Background: Many healthcare systems have implemented intensive outpatient primary care programs with the hopes of reducing healthcare costs.
Objective: The Veterans Health Administration (VHA) piloted primary care intensive management (PIM) for patients at high risk for hospitalization or death, or "high-risk." We evaluated whether a referral model would decrease high-risk patient costs.
Article Synopsis
- * Large language models (LLMs) show potential for automated fall detection by analyzing unstructured data from clinical notes, leading to promising results in two healthcare systems.
- * The Mixtral-8×7B zero-shot model performed best, achieving high positive predictive value and recall in both Stanford Health Care and the Veterans Health Administration, paving the way for future LLM applications in fall prediction and prevention.
Importance: Inpatient clinical deterioration is associated with substantial morbidity and mortality but may be easily missed by clinicians. Early warning scores have been developed to alert clinicians to patients at high risk of clinical deterioration, but there is limited evidence for their effectiveness.
Objective: To evaluate the effectiveness of an artificial intelligence deterioration model-enabled intervention to reduce the risk of escalations in care among hospitalized patients using a study design that facilitates stronger causal inference.
Background: Although methamphetamine use associated heart failure (MU-HF) is increasing, data on its clinical course are limited due to a preponderance of single center studies and significant heterogeneity in the definition of MU-HF in the published literature. Our objective was to evaluate left ventricular ejection fraction (LVEF) distribution, methamphetamine use treatment engagement and postdischarge healthcare utilization among Veterans with heart failure hospitalization in the department of Veterans Affairs (VA) medical centers for MU-HF versus HF not associated with methamphetamine use (other-HF).
Methods: Observational study including a cohort of Veterans with a first heart failure hospitalization during 2007 - 2020 using data in the VA Corporate Data Warehouse.
Background: Predictive models show promise in healthcare, but their successful deployment is challenging due to limited generalizability. Current external validation often focuses on model performance with restricted feature use from the original training data, lacking insights into their suitability at external sites. Our study introduces an innovative methodology for evaluating features during both the development phase and the validation, focusing on creating and validating predictive models for post-surgery patient outcomes with improved generalizability.
View Article and Find Full Text PDFDesign: Retrospective cohort study.
Objective: We sought to examine whether disruptions in follow-up intervals contributed to hypertension control.
Background: Disruptions in health care were widespread during the coronavirus disease 2019 pandemic.
Objective: Pain is experienced by most patients with cancer and opioids are a cornerstone of management. Our objectives were (1) to identify patterns or trajectories of long-term opioid therapy (LTOT) and their correlates among patients with and without cancer and (2) to assess the association between trajectories and risk for opioid overdose, considering the potential moderating role of cancer.
Methods And Analysis: We conducted a retrospective cohort study among individuals in the US Veterans Health Administration (VHA) database with incident LTOT with and without cancer (N=44,351; N=285,772, respectively) between 2010-2017.
Background: Patient portals play an increasingly critical role in engaging patients in their health care. They have the potential to significantly impact the health of those living with chronic diseases, such as HIV, for whom consistent care engagement is both critical and complex.
Objective: The primary aim was to examine the longitudinal relationships between individual portal tool use and health-related outcomes in patients living with HIV.
Background: Normalization Process Theory (NPT) is an implementation theory that can be used to explain how and why implementation strategies work or not in particular circumstances. We used it to understand the mechanisms that lead to the adoption and routinization of palliative care within hemodialysis centers.
Methods: We employed a longitudinal, mixed methods approach to comprehensively evaluate the implementation of palliative care practices among ten hemodialysis centers participating in an Institute for Healthcare Improvement Breakthrough- Series learning collaborative.
Background: Peripheral arterial disease (PAD) is underdiagnosed, partially due to a high prevalence of atypical symptoms and a lack of physician and patient awareness. Implementing clinical decision support tools powered by machine learning algorithms may help physicians identify high-risk patients for diagnostic workup.
Objective: This study aims to evaluate barriers and facilitators to the implementation of a novel machine learning-based screening tool for PAD among physician and patient stakeholders using the Consolidated Framework for Implementation Research (CFIR).
Article Synopsis
- - The study looked at how to better engage patients in their healthcare, especially those who have complicated health needs.
- - Researchers interviewed both healthcare staff and patients in a Veterans Health Administration program to find out what methods worked well for getting patients involved.
- - They found two main types of strategies: "facilitative," which require staff support, and "self-sustaining," which help patients take charge of their own care.
Background: Opioids are commonly prescribed for postoperative pain, but may lead to prolonged use and addiction. Diabetes impairs nerve function, complicates pain management, and makes opioid prescribing particularly challenging.
Methods: This retrospective observational study included a cohort of postoperative patients from a multisite academic health system to assess the relationship between diabetes, pain, and prolonged opioid use (POU), 2008-2019.