Benjamin A Goldstein's research while affiliated with Profil Institute for Clinical Research and other places

Publications (171)

Chapter
Randomized clinical trials have been the accepted standard for addressing key questions in medicine for well over 60 years. The structure and process, while well documented and characterized, have been historically described in the context of “efficacy” in a targeted population as opposed to “effectiveness” objectives in the greater population. Eff...
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Artificial intelligence/machine learning models are being rapidly developed and used in clinical practice. However, many models are deployed without a clear understanding of clinical or operational impact and frequently lack monitoring plans that can detect potential safety signals. There is a lack of consensus in establishing governance to deploy,...
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Background: Extracranial multisystem organ failure is a common sequela of severe traumatic brain injury (TBI). Risk factors for developing circulatory shock and long-term functional outcomes of this patient subset are poorly understood. Objective: To identify emergency department predictors of circulatory shock after moderate-severe TBI and exam...
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Background In the early stages of the COVID-19 pandemic our institution was interested in forecasting how long surgical patients receiving elective procedures would spend in the hospital. Initial examination of our models indicated that, due to the skewed nature of the length of stay, accurate prediction was challenging and we instead opted for a s...
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Background Asthma exacerbations are triggered by a variety of clinical and environmental factors, but their relative impacts on exacerbation risk are unclear. There is a critical need to develop methods to identify children at high-risk for future exacerbation to allow targeted prevention measures. We sought to evaluate the utility of models using...
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Background Clinical decision support (CDS) tools built using adult data do not typically perform well for children. We explored how best to leverage adult data to improve the performance of such tools. This study assesses whether it is better to build CDS tools for children using data from children alone or to use combined data from both adults and...
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OBJECTIVE Over 6 million pediatric SARS-CoV-2 infections have occurred in the United States, but risk factors for infection remain poorly defined. We sought to evaluate the association between asthma and SARS-CoV-2 infection risk among children. METHODS We conducted a retrospective cohort study of children 5 to 17 years of age receiving care throu...
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Introduction Reducing unplanned hospital readmissions is an important priority for all hospitals and health systems. Hospital discharge can be complicated by discrepancies in the medication reconciliation and/or prescribing processes. Clinical pharmacist involvement in the medication reconciliation process at discharge can help prevent these discre...
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Objective Electronic health records have incomplete capture of patient outcomes. We consider the case when observability is differential across a predictor. Including such a predictor (sensitive variable) can lead to algorithmic bias, potentially exacerbating health inequities. Materials and Methods We define bias for a clinical prediction model (...
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Although local policies aimed at reducing childhood health inequities can benefit from local data, sample size constraints in population representative health surveys often prevent rigorous evaluations of child health disparities and health care patterns at local levels. Electronic Health Records (EHRs) offer a possible solution as they contain lar...
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Objectives To evaluate feasibility and acceptability of post-hospitalization telemedicine video visits (TMVV) during hospital-to-home transitions for children with medical complexity (CMC); and explore associations with hospital utilization, caregiver self-efficacy (CSE), and family self-management (FSM). Method This non-randomized pilot study ass...
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Data on patterns of weight change among adults with overweight or obesity are minimal. We aimed to examine patterns of weight change and associated hospitalizations in a large health system, and to develop a model to predict 2-year significant weight gain. Data from the Duke University Health System was abstracted from 1/1/13-12/31/16 on patients w...
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Background: Early hypotension following moderate to severe traumatic brain injury (TBI) is associated with increased mortality and poor long-term outcomes. Current guidelines suggest the use of intravenous vasopressors to support blood pressure following TBI; however, guidelines do not specify vasopressor type, resulting in variation in clinical p...
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The COVID-19 pandemic has had a profound impact on healthcare access and utilization, which could have important implications for children with chronic diseases, including asthma. We sought to evaluate changes in healthcare utilization and outcomes in children with asthma during the COVID-19 pandemic. We used electronic health records data to evalu...
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Combining the increasing availability and abundance of healthcare data and the current advances in machine learning methods have created renewed opportunities to improve clinical decision support systems. However, in healthcare risk prediction applications, the proportion of cases with the condition (label) of interest is often very low relative to...
Article
Objectives: Traumatic brain injury is a leading cause of death and disability in the United States. While the impact of early multiple organ dysfunction syndrome has been studied in many critical care paradigms, the clinical impact of early multiple organ dysfunction syndrome in traumatic brain injury is poorly understood. We examined the incidenc...
Preprint
Background and Objectives The COVID-19 pandemic has had a profound impact on healthcare access and utilization, which could have important implications for children with chronic diseases, including asthma. We sought to evaluate changes in healthcare utilization and outcomes in children with asthma during the COVID-19 pandemic. Methods We used elec...
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Importance Electronic health records (EHRs) are considered a potentially significant contributor to clinician burnout. Objective To describe the association of EHR usage, sex, and work culture with burnout for 3 types of clinicians at an academic medical institution. Design, Setting, and Participants This cross-sectional study of 1310 clinicians...
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Importance Comparisons of antimicrobial use among hospitals are difficult to interpret owing to variations in patient case mix. Risk-adjustment strategies incorporating larger numbers of variables haves been proposed as a method to improve comparisons for antimicrobial stewardship assessments. Objective To evaluate whether variables of varying com...
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Real-World Data (RWD), such as electronic health records (EHRs), reimbursement requests as adjudicated by health insurance companies, and health survey data as collected by government agencies or other research organizations, are increasingly used in drug development. Regulatory agencies, public-private partnerships and professional organizations h...
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Real-world evidence (RWE), derived from Data from “real-world” clinical practice and medical product utilization, is an increasingly important source of evidence that holds great potential to increase efficiency and improve clinical development and life cycle management of medical products. Regulatory agencies, public-private partnerships and healt...
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Background Statins failed to reduce cardiovascular (CV) events in trials of patients on dialysis. However, trial populations used criteria that often excluded those with atherosclerotic heart disease (ASHD), in whom statins have the greatest benefit, and included outcome composites with high rates of nonatherosclerotic CV events that may not be mod...
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Background The novel coronavirus disease (COVID-19) results in severe illness in a significant proportion of patients, necessitating a way to discern which patients will become critically ill and which will not. In one large case series, 5.0% of patients required an intensive care unit (ICU) and 1.4% died. Several models have been developed to asse...
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Background: Asthma remains a leading cause of hospitalization in US children. Well-child care (WCC) visits are routinely recommended, but how WCC adherence relates to asthma outcomes is poorly described. Methods: We conducted a retrospective longitudinal cohort study using electronic health records among 5 to 17 year old children residing in Dur...
Preprint
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Dealing with severe class imbalance poses a major challenge for real-world applications, especially when the accurate classification and generalization of minority classes is of primary interest. In computer vision, learning from long tailed datasets is a recurring theme, especially for natural image datasets. While existing solutions mostly appeal...
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To the Editor Mr Adibi and colleagues¹ argued that practitioners are developing too many clinical prediction models (CPMs) and not testing model performance enough. The authors suggested placing all models in a cloud-based environment and allowing for a natural-selection approach to determine the best models. We agree that the current process, in w...
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Full-text available
Importance Hospitals ceased most elective procedures during the height of coronavirus disease 2019 (COVID-19) infections. As hospitals begin to recommence elective procedures, it is necessary to have a means to assess how resource intensive a given case may be. Objective To evaluate the development and performance of a clinical decision support to...
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Background Asthma exacerbations in children often require medications, urgent care, and hospitalization. Multiple environmental triggers have been associated with asthma exacerbations, including particulate matter 2.5 (PM2.5) and ozone, which are primarily generated by motor vehicle exhaust. There is mixed evidence as to whether proximity to highwa...
Article
Combining the increasing availability and abundance of healthcare data and the current advances in machine learning methods have created renewed opportunities to improve clinical decision support systems. However, in healthcare risk prediction applications, the proportion of cases with the condition (label) of interest is often very low relative to...
Preprint
Combining the increasing availability and abundance of healthcare data and the current advances in machine learning methods have created renewed opportunities to improve clinical decision support systems. However, in healthcare risk prediction applications, the proportion of cases with the condition (label) of interest is often very low relative to...
Article
Full-text available
There is increasing application of machine learning tools to problems in healthcare, with an ultimate goal to improve patient safety and health outcomes. When applied appropriately, machine learning tools can augment clinical care provided to patients. However, even if a model has impressive performance characteristics, prospectively evaluating and...
Article
Objective To characterize operative care for cleft lip and/or palate (CL/P) based on location (ie, from American Cleft Palate Craniofacial Association [ACPA]–approved multidisciplinary teams or from community providers). Design Cross-sectional analysis of Healthcare Cost and Utilization Project State Inpatient Database and State Ambulatory Surgery...
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Full-text available
Unplanned hospital readmissions represent a significant health care value problem with high costs and poor quality of care. A significant percentage of readmissions could be prevented if clinical inpatient teams were better able to predict which patients were at higher risk for readmission. Many of the current clinical decision support models that...
Preprint
Full-text available
Background: Asthma exacerbations in children often require medications, urgent care, and hospitalization. Multiple environmental triggers have been associated with asthma exacerbations, including particulate matter 2.5 (PM2.5) and carbon monoxide (CO), which are primarily generated by motor vehicle exhaust. There is mixed evidence as to whether pro...
Preprint
Full-text available
Background: Asthma exacerbations in children often require medications, urgent care, and hospitalization. Multiple environmental triggers have been associated with asthma exacerbations, including particulate matter 2.5 (PM2.5) and ozone, which are primarily generated by motor vehicle exhaust. There is mixed evidence as to whether proximity to highw...
Preprint
Full-text available
Background: Asthma exacerbations in children often require medications, urgent care, and hospitalization. Multiple environmental triggers have been associated with asthma exacerbations, including particulate matter 2.5 (PM2.5) and ozone, which are primarily generated by motor vehicle exhaust. There is mixed evidence as to whether proximity to highw...
Article
Electronic health records data are becoming a key data resource in clinical research. Owing to issues of data efficiency, electronic health records data are being used for clinical trials. This includes both large-scale pragmatic trails and smaller—more focused—point-of-care trials. While electronic health records data open up a number of scientifi...
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Introduction Electronic health record (EHR) data have emerged as an important resource for population health and clinical research. There have been significant efforts to leverage EHR data for research; however, given data security concerns and the complexity of the data, EHR data are frequently difficult to access and use for clinical studies. We...
Preprint
Full-text available
Background Asthma exacerbations in children often require medications, urgent care, and hospitalization. Multiple environmental triggers have been associated with asthma exacerbations, including particulate matter 2.5 (PM2.5) and carbon monoxide (CO), which are primarily generated by motor vehicle exhaust. There is mixed evidence as to whether prox...
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Prediction models’ newfound importance and the emergence of model development based on machine learning raise questions about how to ensure their safety and efficacy, given their growing role in risk stratification, care pathways, and clinical outcomes.
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Objective: While electronic health record (EHR) systems store copious amounts of patient data, aggregating those data across patients can be challenging. Visual analytic tools that integrate with EHR systems allow clinicians to gain better insight and understanding into clinical care and management. We report on our experience building Tableau-bas...
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Background: Unanticipated respiratory compromise that lead to unplanned intubations is a known phenomenon in hospitalized patients. Most events occur in patients at high risk in well-monitored units; less is known about the incidence, risk factors, and trajectory of patients thought at low risk on lightly monitored general care wards. The aims of...
Preprint
UNSTRUCTURED As wearable technologies are being increasingly used for clinical research and healthcare, it is critical to understand their accuracy and determine how measurement errors may affect research conclusions and impact healthcare decision-making. Accuracy of wearable technologies has been a hotly debated topic in both the research and popu...
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As wearable technologies are being increasingly used for clinical research and healthcare, it is critical to understand their accuracy and determine how measurement errors may affect research conclusions and impact healthcare decision-making. Accuracy of wearable technologies has been a hotly debated topic in both the research and popular science l...
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Background. Identification of patients at risk of deteriorating during their hospitalization is an important concern. However, many off-shelf scores have poor in-center performance. In this article, we report our experience developing, implementing, and evaluating an in-hospital score for deterioration. Methods. We abstracted 3 years of data (2014–...
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Full-text available
Background Hospital antimicrobial stewardship program (ASP) assessments based on comparisons of antimicrobial use (AU) among multiple hospitals are difficult to interpret without risk-adjustment for patient case-mix. We aimed to determine whether variables of varying complexity, derived retrospectively from the electronic health record (EHR), were...
Article
Full-text available
Background Comparison of antimicrobial use (AU) rates among hospitals can identify areas to intervene for antimicrobial stewardship. Hospital AU interpretation is difficult without risk-adjustment for patient mix. Identifying high- or low-risk patient characteristics, or “electronic phenotypes,” for receipt of antimicrobials using data from electro...
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Appointment no-shows have a negative impact on patient health and have caused substantial loss in resources and revenue for health care systems. Intervention strategies to reduce no-show rates can be more effective if targeted to the subpopulations of patients with higher risk of not showing to their appointments. We use electronic health records (...
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Objective: Electronic health records (EHR) data have become a central data source for clinical research. One concern for using EHR data is that the process through which individuals engage with the health system, and find themselves within EHR data, can be informative. We have termed this process informed presence. In this study we use simulation...
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Background: Hospital referral regions (HRRs) are often used to characterize inpatient referral patterns, but it is unknown how well these geographic regions are aligned with variation in Medicare-financed hospice care, which is largely provided at home. Objective: Our objective was to characterize the variability in hospice use rates among elderly...
Chapter
Electronic health records (EHR) data have become a primary resource for developing risk prediction models. Not only do EHR data contain unprecedented access to dense, granular clinical data, additionally, since they derive directly from clinical health systems, EHR data provide a means to implement the models into clinical work flows as clinical de...
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Uptake of pre-exposure prophylaxis (PrEP) has been limited among black and Latino men who have sex with men (MSM), especially in the southern United States. Public health departments and federally qualified health centers (FQHCs) serving predominantly uninsured populations are uniquely positioned to improve access. We evaluated a novel PrEP collabo...
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Background The National Comprehensive Cancer Network (NCCN) Distress Thermometer (DT) uses a 10‐point scale (in which 0 indicates no distress and 10 indicates extreme distress) to measure patient‐reported distress. In the current study, the authors sought to examine the relationship between treatment and NCCN DT scores in patients with breast cance...
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Objective: Participants enrolled into randomized controlled trials (RCTs) often do not reflect real-world populations. Previous research in how best to transport RCT results to target populations has focused on weighting RCT data to look like the target data. Simulation work, however, has suggested that an outcome model approach may be preferable....
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Introduction: Current static approaches of CVD surveillance may not capture the true health of neighborhoods as the influx of younger, healthier, and wealthier individuals (i.e., gentrification) can impact long term residents (LTR) who can be older and of lower socioeconomic status (SES), potentially biasing prevalence estimates. Hypothesis: LTR in...
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The impact of the Patient Protection and Affordable Care Act (PPACA) on children’s access to surgical care is not well-defined. Our objective was to describe the early impact of PPACA on children’s surgical care before and after Medicaid expansion in 2014. We compared pediatric and young adult surgical outcomes in 2013 and 2014 in Medicaid expansio...
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Objective: This study evaluated whether there is a difference in the proportion of patients with type 2 diabetes who achieve a hemoglobin A1c (HbA1c) <7% within one year following treatment by an endocrinologist or primary care physician (PCP). Methods: We conducted a retrospective, propensity-matched study of patients with type 2 diabetes that we...
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Full-text available
Background While pre-exposure prophylaxis (PrEP) is a promising strategy for HIV prevention, some high-risk persons have limited access to care, particularly Black and Latino men who have sex with men (MSM). Disparities also exist by region: the Southern United States accounts for over half of new HIV diagnoses but only a third of PrEP prescription...
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Objective: The utilization of electronic health records (EHR) has become essential in the daily activities of physicians for documentation and as an information source. However, the amount of time spent by residents utilizing the EHR has not been thoroughly evaluated, particularly within surgical specialties. This study aims to analyze EHR usage b...
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Objectives: Previous studies have looked at National Early Warning Score performance in predicting in-hospital deterioration and death, but data are lacking with respect to patient outcomes following implementation of National Early Warning Score. We sought to determine the effectiveness of National Early Warning Score implementation on predicting...
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Importance Data from electronic health records (EHRs) are increasingly used for risk prediction. However, EHRs do not reliably collect sociodemographic and neighborhood information, which has been shown to be associated with health. The added contribution of neighborhood socioeconomic status (nSES) in predicting health events is unknown and may hel...