About
1,478
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Introduction
David W Bates currently works at the Division of General Internal Medicine and Primary Care, Brigham and Women's Hospital. David does research in medical informatics, patient safety, quality of care, health services research, epidemiology and primary care.
Additional affiliations
July 2000 - present
January 2000 - present
July 1986 - present
Publications
Publications (1,478)
More than 83 million people in the United States live in primary care shortage areas. As the US healthcare system faces a contracting primary care physician workforce, advanced practice providers are playing an increasingly important role in the delivery of primary care services. In parallel, public discourse regarding the differences in care deliv...
Importance
Surgeon stress can influence technical and nontechnical skills, but the consequences for patient outcomes remain unknown.
Objective
To investigate whether surgeon physiological stress, as assessed by sympathovagal balance, is associated with postoperative complications.
Design, Setting, and Participants
This multicenter prospective coh...
Background
Recent breakthroughs in the treatment of Alzheimer’s Disease underscore the critical needs for early detection. In clinical settings, the diagnosis of Alzheimer’s disease and related dementias (ADRD) is often delayed or overlooked, potentially missing critical opportunities for timely care and treatment. Cognitive symptoms can appear man...
Adverse drug events (ADEs) are understudied in the ambulatory care setting. We aim to estimate the prevalence and characteristics of ADEs in outpatient care using electronic health records (EHRs).
This cross-sectional study included EHR data for patients who had an outpatient encounter at an academic medical center from 1 October 2018 through 31 De...
Artificial intelligence (AI)-enabled decision aids can contribute to the shared decision-making process between patients and clinicians through personalised recommendations. This systematic review aims to understand users’ perceptions on using AI-enabled decision aids to inform shared decision-making. Four databases were searched. The population, i...
BACKGROUND
The rapid rise of healthcare chatbots, valued at $787.1 million in 2022 and projected to grow at 23.9% annually through 2030, underscores the need for robust evaluation frameworks. Despite their potential, the absence of standardized evaluation criteria and rapid AI advancements complicate assessments.
OBJECTIVE
This study addresses the...
Objectives
To estimate the frequency, severity, and preventability of adverse events associated with perioperative care, and to describe the setting and professions concerned.
Design
Multicenter retrospective cohort study.
Setting
11 US hospitals.
Participants
1009 patients from a randomly selected sample of 64 121 adults admitted for surgery du...
Objectives
The purpose of this study was to examine the impact of a contact-free continuous monitoring system on clinical outcomes including unplanned intensive care unit (ICU) transfer (primary), length of stay (LOS), code blue, and mortality. A secondary aim was to evaluate the return on investment associated with implementing the contact-free co...
Although opioids continue to be used internationally for noncancer pain, evidence to date on the comparative safety of different opioids is sparse and conflicting. The aim of this study was to examine the comparative risk of all-cause mortality in patients newly initiated on opioids for noncancer pain, across 3 jurisdictions in the United Kingdom (...
Background
Multimorbid patients are at higher risk of hospital readmission due to the complex nature of their conditions. Identifying those who may be at particularly high risk would allow us to intervene early and potentially delay or prevent such readmissions occurring, thus reducing healthcare costs. We conducted a systematic review investigatin...
Background
Large language models (LLMs) have shown promising performance in various healthcare domains, but their effectiveness in identifying specific clinical conditions in real medical records is less explored. This study evaluates LLMs for detecting signs of cognitive decline in real electronic health record (EHR) clinical notes, comparing thei...
Background
Antibiotic resistant infections cause over 700,000 deaths worldwide annually. As antimicrobial stewardship (AMS) helps minimise the emergence of antibiotic resistance resulting from inappropriate use of antibiotics in healthcare, we developed ePAMS+ (ePrescribing-based Anti-Microbial Stewardship), an ePrescribing and Medicines Administra...
Objectives This study aimed to evaluate implementation of a digital remote symptom monitoring intervention that delivered weekly symptom questionnaires and included the option to receive nurse callbacks via a mobile app for asthma patients in primary care.
Methods Research questions were structured by the NASSS (Nonadoption, Abandonment, Scale-up S...
Background
Patient safety culture is crucial for improving health care quality, however, there is no consensus on its definition.
Purpose
This study aimed to clarify and update the concept of patient safety culture.
Methods
We employed Norris’ 6-step concept clarification method. The content was organized through a scoping review of 4 databases....
Opioid prescription records in existing electronic health record (EHR) databases are a potentially useful, high-fidelity data source for opioid use-related risk phenotyping in genetic analyses. Prescriptions for codeine derived from EHR records were used as targeting traits by screening 16 million patient-level medication records. Genome-wide assoc...
Background
Adverse event surveillance approaches underestimate the prevalence of harmful diagnostic errors (DEs) related to hospital care.
Methods
We conducted a single-centre, retrospective cohort study of a stratified sample of patients hospitalised on general medicine using four criteria: transfer to intensive care unit (ICU), death within 90 d...
Integrating modern machine learning and clinical decision-making has great promise for mitigating healthcare's increasing cost and complexity. We introduce the Enhanced Transformer for Health Outcome Simulation (ETHOS), a novel application of the transformer deep-learning architecture for analyzing high-dimensional, heterogeneous, and episodic heal...
Objectives This study aimed to pilot an application-based patient diagnostic questionnaire (PDQ) and assess the concordance of the admission diagnosis reported by the patient and entered by the clinician.
Methods Eligible patients completed the PDQ assessing patients' understanding of and confidence in the diagnosis 24 hours into hospitalization ei...
Background
Medication-related harm has a significant impact on global healthcare costs and patient outcomes, accounting for deaths in 4.3 per 1000 patients. Generative artificial intelligence (GenAI) has emerged as a promising tool in mitigating risks of medication-related harm. In particular, large language models (LLMs) and well-developed generat...
Purpose: Our purpose was to understand the completeness of sex and gender fields in electronic health record (EHR) data and patient-level factors associated with completeness of those fields. In doing so, we aimed to inform approaches to EHR sex and gender data collection. Methods: This was a retrospective observational study using 2016-2021 deiden...
Background: Generative Large language models (LLMs) represent a significant advancement in natural language processing, achieving state-of-the-art performance across various tasks. However, their application in clinical settings using real electronic health records (EHRs) is still rare and presents numerous challenges.
Objective: This study aims to...
Objective
Racial and ethnic differences in presentation and outcomes have been reported in systemic sclerosis (SSc) and SSc-interstitial lung disease (ILD). However, prior studies have limited diversity. We aim to evaluate if there are racial/ethnic differences associated with ILD, time intervals between SSc and ILD and with emergency department (E...
Integrating modern machine learning and clinical decision-making has great promise for mitigating healthcare's increasing cost and complexity. We introduce the Enhanced Transformer for Health Outcome Simulation (ETHOS), a novel application of the transformer deep-learning architecture for analyzing high-dimensional, heterogeneous, and episodic heal...
Background
Although primary hyperparathyroidism (PHPT) is readily diagnosed biochemically and can be cured with low-risk surgery, it is often underrecognized and undertreated. Our objectives were to characterize, within our health system, how often patients with hypercalcemia were evaluated for PHPT and how often patients with PHPT underwent defini...
The rapid rise of healthcare chatbots, valued at $787.1 million in 2022 and projected to grow at 23.9% annually through 2030, underscores the need for robust evaluation frameworks. Despite their potential, the absence of standardized evaluation criteria and rapid AI advancements complicate assessments. This study addresses these challenges by devel...
Background
Limited data exist regarding adverse drug events (ADEs) in the outpatient setting. The objective of this study was to determine the incidence, severity, and preventability of ADEs in the outpatient setting and identify potential prevention strategies.
Methods
We conducted an analysis of ADEs identified in a retrospective electronic heal...
A risk factor for a potentially fatal ventricular arrhythmia Torsade de Pointes is a prolongation in the heart rate-corrected QT interval (QTc) ≥ 500 milliseconds (ms) or an increase of ≥ 60 ms from a patient’s baseline value, which can cause sudden cardiac death. The Tisdale risk score calculator uses clinical variables to predict which hospitaliz...
Background
Adverse drug events (ADEs) are a frequent cause of injury in patients. Our aim was to assess whether pharmacist interventions compared with no pharmacist intervention results in reduced ADEs and potential adverse drug events (PADEs).
Methods
We searched MEDLINE, Embase, and two other databases through September 19, 2022 for any RCT asse...
Background
Sodium-glucose cotransporter type 2 inhibitors (SGLT2i) have revolutionized the management of type 2 diabetes, heart failure, and chronic kidney disease (CKD), all comorbidities which are also highly prevalent among individuals with gout. SGLT2i have also been reported to lower serum urate (SU), the causal mediator of gout, by up to 1.8...
Background
Opioids have contributed to an epidemic in several Western countries, and have been associated with a multitude of adverse outcomes and unintentional deaths. Despite increased awareness of potential harms, they remain commonly prescribed in most countries internationally for non-cancer pain due to limited therapeutic options. As a drug c...
Background
Despite restrictive opioid management guidelines, opioid use disorder (OUD) remains a major public health concern. Machine learning (ML) offers a promising avenue for identifying and alerting clinicians about OUD, thus supporting better clinical decision-making regarding treatment.
Objective
This study aimed to assess the clinical valid...
Importance
Late predictions of hospitalized patient deterioration, resulting from early warning systems (EWS) with limited data sources and/or a care team’s lack of shared situational awareness, contribute to delays in clinical interventions. The COmmunicating Narrative Concerns Entered by RNs (CONCERN) Early Warning System (EWS) uses real-time nur...
Background: Adverse drug events (ADEs) are a frequent cause of injury in patients. Our aim was to assess pharmacist interventions and their association with ADEs and potential adverse drug events (PADE). Methods: The search criteria: a published RCT, evidence of a pharmacist intervention, a comparison control group, and measurement of ADEs or PADEs...
Background:
Despite considerable emphasis on delivering safe care, substantial patient harm occurs. Although most care occurs in the outpatient setting, knowledge of outpatient adverse events (AEs) remains limited.
Objective:
To measure AEs in the outpatient setting.
Design:
Retrospective review of the electronic health record (EHR).
Setting:...
Unmet social needs (SNs) often coexist in distinct patterns within specific population subgroups, yet these patterns are understudied.
To identify patterns of social needs (PSNs) and characterize their associations with health-related quality-of-life (HRQoL) and healthcare utilization (HCU).
Observational study using data on SNs screening, HRQoL (i...
This cross-sectional study assesses the implication of patients’ English language skills for telehealth use and visit experience.
Importance
Time on the electronic health record (EHR) is associated with burnout among physicians. Newer virtual scribe models, which enable support from either a real-time or asynchronous scribe, have the potential to reduce the burden of the EHR and EHR-related documentation.
Objective
To characterize the association of use of virtual scribes wi...
Background
Quality in healthcare is a subject in need of continuous attention. Quality improvement (QI) programmes with the purpose of increasing service quality are therefore of priority for healthcare leaders and governments. This study explores the implementation process of two different QI programmes, one externally driven implementation and on...
Aim: This study aimed to identify and analyze the top 100 most cited digital health and mobile health (m-health) publications. It could aid researchers in the identification of promising new research avenues, additionally supporting the establishment of international scientific collaboration between interdisciplinary research groups with demonstrat...
Objective:
To assess primary care physicians' (PCPs) perception of the need for serious illness conversations (SIC) or other palliative care interventions in patients flagged by a machine learning tool for high one-year mortality risk.
Materials and methods:
We surveyed PCPs from four Brigham and Women's Hospital primary care practice sites. Mul...
Background
The COVID-19 pandemic had a major impact on healthcare services globally. In care settings such as small rural nursing homes and homes care services leaders were forced to confront, and adapt to, both new and ongoing challenges to protect their employees and patients and maintain their organization's operation. The aim of this study was...
Artificial intelligence (AI) has the potential to transform care delivery by improving health outcomes, patient safety, and the affordability and accessibility of high-quality care. AI will be critical to building an infrastructure capable of caring for an increasingly aging population, utilizing an ever-increasing knowledge of disease and options...
Background
The quality of patient-reported outcome measures (PROMs) used to assess the outcomes of primary hyperparathyroidism (PHPT), a common endocrine disorder that can negatively affect patients’ health-related quality of life due to chronic symptoms, has not been rigorously examined. This systematic review aimed to summarize and evaluate evide...
Background
The COVID-19 pandemic has caused significant disruptions to everyday life and has had social, political, and financial consequences that will persist for years. Several initiatives with intensive use of technology were quickly developed in this scenario. However, technologies that enhance epidemiological surveillance in contexts with low...
Objectives:
Large language models (LLMs) are poised to change care delivery, but their impact on health equity is unclear. While marginalized populations have been historically excluded from early technology developments, LLMs present an opportunity to change our approach to developing, evaluating, and implementing new technologies. In this perspe...
Objective
The COVID-19 pandemic presented a challenge to inpatient safety. It is unknown whether there were spillover effects due to COVID-19 into non–COVID-19 care and safety. We sought to evaluate the changes in inpatient Agency for Healthcare Research and Quality patient safety indicators (PSIs) in the United States before and during the first s...
Importance
Chronic kidney disease (CKD) affects 37 million adults in the United States, and for patients with CKD, hypertension is a key risk factor for adverse outcomes, such as kidney failure, cardiovascular events, and death.
Objective
To evaluate a computerized clinical decision support (CDS) system for the management of uncontrolled hypertens...
Integrating modern machine learning and clinical decision-making has great promise for mitigating healthcares increasing cost and complexity. We introduce the Enhanced Transformer for Health Outcome Simulation (ETHOS), a novel application of the transformer deep-learning architecture for analyzing high-dimensional, heterogeneous, and episodic healt...
This Viewpoint discusses how artificial intelligence can be used to increase efficiency of primary care processes for clinicians and patients.
Rationale: Racial and ethnic differences in presentation and outcomes have been reported in systemic sclerosis (SSc) and SSc-interstitial lung disease (ILD). However, diverse cohorts and additional modeling can improve understanding of risk features and outcomes, which is important for reducing associated disparities.
Objective(s): To determine if...
Objectives
Despite federally mandated collection of sex and gender demographics in the electronic health record (EHR), longitudinal assessments are lacking. We assessed sex and gender demographic field utilization using EHR metadata.
Materials and methods
Patients ≥18 years of age in the Mass General Brigham health system with a first Legal Sex en...
This Viewpoint offers 3 recommendations for health care organizations and other stakeholders to consider as part of the Health and Human Services’ artificial intelligence safety program.
Objective: Survival analysis is widely utilized in healthcare to predict the timing of disease onset. Traditional methods of survival analysis are usually based on Cox Proportional Hazards model and assume proportional risk for all subjects. However, this assumption is rarely true for most diseases, as the underlying factors have complex, non-linea...
Background
While many falls are preventable, they remain a leading cause of injury and death in older adults. Primary care clinics largely rely on screening questionnaires to identify people at risk of falls. Limitations of standard fall risk screening questionnaires include suboptimal accuracy, missing data, and non‐standard formats, which hinder...
Objective
To evaluate the ability of DynaMedex, an evidence-based drug and disease Point of Care Information (POCI) resource, in answering clinical queries using keyword searches.
Methods
Real-world disease-related questions compiled from clinicians at an academic medical center, DynaMedex search query data, and medical board review resources were...
Background The purpose of the Ambulatory Electronic Health Record (EHR) Evaluation Tool is to provide outpatient clinics with an assessment that they can use to measure the ability of the EHR system to detect and prevent common prescriber errors. The tool consists of a medication safety test and a medication reconciliation module.
Objectives The go...
Introduction
There is an urgent need for scalable strategies for treating overweight and obesity in clinical settings. PROPS 2.0 (Partnerships for Reducing Overweight and Obesity with Patient-Centered Strategies 2.0) aims to adapt and implement the combined intervention from the PROPS Study at scale, in a diverse cross-section of patients and provi...
Many areas of medicine would benefit from deeper, more accurate phenotyping, but there are limited approaches for phenotyping using clinical notes without substantial annotated data. Large language models (LLMs) have demonstrated immense potential to adapt to novel tasks with no additional training by specifying task-specific instructions. Here we...
Background:
Digital transformation using widely available electronic data is a key component to improving health outcomes and customer choice and decreasing cost and measurement burden. Despite these benefits, existing information on the potential cost savings from electronic clinical quality measures (eCQMs) is limited.
Methods:
We assessed the...
Objectives:
Adverse events (AEs) represent an important cause of morbidity and mortality for pediatric inpatients; however, reports on their epidemiology in pediatrics, especially outside Western countries, are scarce. We investigated the incidence and nature of AEs in pediatric inpatients in Japan.
Methods:
Trained pediatrician and pediatric nu...
The growing recognition of differences in health outcomes across populations has led to a slow but increasing shift towards transparent reporting of patient outcomes. In addition, pay-for-equity initiatives, such as those proposed by the Centers for Medicare and Medicaid, will require the reporting of health outcomes across subgroups over time. Das...
Importance
Primary care physicians (PCPs) spend the most time on the electronic health record (EHR) of any specialty. Thus, it is critical to understand what factors contribute to varying levels of PCP time spent on EHRs.
Objective
To characterize variation in EHR time across PCPs and primary care clinics, and to describe how specific PCP, patient...
Background
The COVID-19 pandemic led to new and unfamiliar changes in healthcare services globally. Most COVID-19 patients were cared for in primary healthcare services, demanding major adjustments and adaptations in care delivery. Research addressing how rural primary healthcare services coped during the COVID-19 pandemic, and the possible learnin...
Infants in the neonatal intensive care unit (NICU) are among the most vulnerable patient populations and medication errors are a significant source of risk and harm to neonates. Smart infusion pumps have been implemented to support the safe medication administration process; however, the effect of using smart infusion pumps on medication safety in...
Introduction:
Although the transfer of patients between acute care hospitals (interhospital transfer, IHT) is common, health information exchange (HIE) during IHT remains inadequate, with fragmented communication and unreliable access to clinical information. This study aims to design, implement, and rigorously evaluate the implementation of a HIE...
Objective
To evaluate and synthesise the factors determining patient safety culture in hospitals.
Methods
The scoping review protocol was based on the criteria of the Joanna Briggs Institute. Eligibility criteria were as follows: (1) empirical study published in a peer-reviewed journal; (2) used methods or tools to assess, study or measure safety...
This Viewpoint looks at digital communication between patients and physicians, including approaches to provide adequate support for these efforts that balance patient needs with appropriate time investments from clinicians.