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IntroductionHospitalizations related to the consequences of substance use are rising yet most hospitalized patients with substance use disorder do not receive evidence-based addiction treatment. Opportunities to leverage the hospitalist workforce could close this treatment gap.AimTo describe the development, implementation, and evaluation of a hospitalist-directed addiction consultation service (ACS) to provide in-hospital addiction treatment.SettingSix hundred fifty–bed university hospital in Aurora, Colorado.Program DescriptionHospitalists completed buprenorphine waiver training, participated in a 13-part addiction lecture series, and completed a minimum of 40 hours of online addiction training. Hospitalists participated in shadow shifts with an addiction-trained physician. Dedicated addiction social workers developed relationships with local addiction treatment services.Program Evaluation MetricsPhysician-related metrics included education, training, and clinical time spent in addiction practice. Patient and encounter-related metrics included a description of ACS care provision.ResultsEleven hospitalists completed an average of 95 hours of addiction-related didactics. Once addiction training was complete, hospitalists spent an average of 30 days over 12 months staffing a weekday ACS. Between October 2019 and November 2020, the ACS completed 1620 consultations on 1350 unique patients. Alcohol was the most common substance (n = 1279; 79%), followed by tobacco (979; 60.4%), methamphetamines/amphetamines (n = 494; 30.5%), and opioids (n = 400; 24.7%). Naltrexone was the most frequently prescribed medication (n = 350; 21.6%), followed by acamprosate (n = 93; 5.7%), and buprenorphine (n = 77, 4.8%). Trauma was a frequent discharge diagnoses (n = 1564; 96.5%). Leaving prior to treatment completion was commonly noted (n = 120, 7.4%). The ACS completed 47 in-hospital methadone enrollments.DiscussionThe hospitalist-directed ACS is a promising clinical initiative that could be implemented to expand hospital-based addiction treatment. Future research is needed to understand challenges to disseminating this model into other hospital settings, and to evaluate intended and unintended effects of broad implementation.

BACKGROUNDChronic opioid therapy for chronic pain treatment has increased. Hospital physicians, including hospitalists and medical/surgical resident physicians, care for many hospitalized patients, yet little is known about opioid prescribing at hospital discharge and future chronic opioid use.OBJECTIVEWe aimed to characterize opioid prescribing at hospital discharge among ‘opioid naïve’ patients. Opioid naïve patients had not filled an opioid prescription at an affiliated pharmacy 1 year preceding their hospital discharge. We also set out to quantify the risk of chronic opioid use and opioid refills 1 year post discharge among opioid naïve patients with and without opioid receipt at discharge.DESIGNThis was a retrospective cohort study.PARTICIPANTSFrom 1 January 2011 to 31 December 2011, 6,689 opioid naïve patients were discharged from a safety-net hospital.MAIN MEASUREChronic opioid use 1 year post discharge.KEY RESULTSTwenty-five percent of opioid naïve patients (n = 1,688) had opioid receipt within 72 hours of discharge. Patients with opioid receipt were more likely to have diagnoses including neoplasm (6.3 % versus 3.5 %, p < 0.001), acute pain (2.7 % versus 1.0 %, p < 0.001), chronic pain at admission (12.1 % versus 3.3 %, p < 0.001) or surgery during their hospitalization (65.1 % versus 18.4 %, p < 0.001) compared to patients without opioid receipt. Patients with opioid receipt were less likely to have alcohol use disorders (15.7 % versus 20.7 %, p < 0.001) and mental health disorders (23.9 % versus 31.4 %, p < 0.001) compared to patients without opioid receipt. Chronic opioid use 1 year post discharge was more common among patients with opioid receipt (4.1 % versus 1.3 %, p < 0.0001) compared to patients without opioid receipt. Opioid receipt was associated with increased odds of chronic opioid use (AOR = 4.90, 95 % CI 3.22-7.45) and greater subsequent opioid refills (AOR = 2.67, 95 % CI 2.29-3.13) 1 year post discharge compared to no opioid receipt.CONCLUSIONOpioid receipt at hospital discharge among opioid naïve patients increased future chronic opioid use. Physicians should inform patients of this risk prior to prescribing opioids at discharge.

Clinicians' time with patients has become increasingly limited due to regulatory burden, documentation and billing, administrative responsibilities, and market forces. These factors limit clinicians' time to deliver thorough explanations to patients. OpenNotes began as a research initiative exploring the ability of sharing medical notes with patients to help patients understand their health care. Providing patients access to their medical notes has been shown to have many benefits, including improved patient satisfaction and clinical outcomes. OpenNotes has since evolved into a national movement that helps clinicians share notes with patients. However, a significant barrier to the widespread adoption of OpenNotes has been clinicians' concerns that OpenNotes may cost additional time to correct patient confusion over medical language. Recent advances in artificial intelligence (AI) technology may help resolve this concern by converting medical notes to plain language with minimal time required of clinicians. This pilot study assesses patient comprehension and perceived benefits, concerns, and insights regarding an AI-simplified note through comprehension questions and guided interview. Synthea, a synthetic patient generator, was used to generate a standardized medical language which was then simplified using AI software. A multiple-choice comprehension assessment questionnaire was drafted with physician input. Study participants were recruited from inpatients at the University of Colorado Hospital. Participants were randomly assigned to be tested for their comprehension of the standardized medical language version or AI-generated plain-language version of the patient note. Following this, participants reviewed the opposite version of the note and participated in a guided interview. A Student t test was performed to assess for differences in comprehension assessment scores between plain-language and medical-language note groups. Multivariate modeling was performed to assess the impact of demographic variables on comprehension. Interview responses were thematically analyzed. Twenty patients agreed to participate. The mean number of comprehension assessment questions answered correctly was found to be higher in the plain-language group compared with the medical-language group; however, the Student t test was found to be underpowered to determine if this was significant. Age, ethnicity, and health literacy were found to have a significant impact on comprehension scores by multivariate modeling. Thematic analysis of guided interviews highlighted patients' perceived benefits, concerns, and suggestions regarding such notes. Major themes of benefits were that simplified plain-language notes may (1) be more useable than unsimplified medical-language notes, (2) improve the patient-clinician relationship, and (3) empower patients through an enhanced understanding of their health care. AI software may translate medical notes into plain-language notes that are perceived as beneficial by patients. Limitations included sample size, inpatient-only setting, and possible confounding factors. Larger studies are needed to assess comprehension. Insight from patient responses to guided interviews can guide the future study and development of this technology.

The study assessed the feasibility of using synthetic data to fine-tune various open-source LLMs for free text to structured data conversation in radiology, comparing their performance with GPT models. A training set of 3000 synthetic thyroid nodule dictations was generated to train six open-source models (Starcoderbase-1B, Starcoderbase-3B, Mistral-7B, Llama-3-8B, Llama-2-13B, and Yi-34B). ACR TI-RADS template was the target model output. The model performance was tested on 50 thyroid nodule dictations from MIMIC-III patient dataset and compared against 0-shot, 1-shot, and 5-shot performance of GPT-3.5 and GPT-4. GPT-4 5-shot and Yi-34B showed the highest performance with no statistically significant difference between the models. Various open models outperformed GPT models with statistical significance. Overall, models trained with synthetic data showed performance comparable to GPT models in structured text conversion in our study. Given privacy preserving advantages, open LLMs can be utilized as a viable alternative to proprietary GPT models.

Hospitalists are well poised to serve in key leadership roles and in frontline care in particular when facing a pandemic such as the SARS-CoV-2 (COVID-19) infection. Much of the disaster planning in hospitals around the country addresses overcrowded emergency departments and decompressing these locations; however, in the case of COVID-19, intensive care units, emergency departments, and medical wards ran the risk of being overwhelmed by a large influx of patients needing high-level medical care. In a matter of days, our Division of Hospital Medicine, in partnership with our hospital, health system, and academic institution, was able to modify and deploy existing disaster plans to quickly care for an influx of medically complex patients. We describe a scaled approach to managing hospitalist clinical operations during the COVID-19 pandemic.

Background The Coronavirus Disease 2019 (COVID-19) caused unprecedented challenges within medical centers, revealing inequities embedded in the medical community and exposing fragile social support systems. While faculty and staff faced extraordinary demands in workplace duties, personal responsibilities also increased. The goal of this study was to understand the impact of the COVID-19 pandemic on personal and professional activities of faculty and staff in order to illuminate current challenges and explore solutions. Methods Qualitative, semi-structured group interviews involved faculty and staff at four affiliate sites within the Department of Medicine at the University of Colorado, School of Medicine. Focus groups addressed the impact of COVID-19 on (1) Changes to roles and responsibilities at work and at home, (2) Resources utilized to manage these changes and, (3) Potential strategies for how the Department could assist faculty and staff. Thematic analysis was conducted using an inductive method at the semantic level to form themes and subthemes. Results Qualitative analysis of focus group transcripts revealed themes of: (1) Challenges and disparities experienced during the pandemic, (2) Disproportionate impact on women personally and professionally, (3) Institutional factors that contributed to wellness and burnout, and (4) Solutions and strategies to support faculty and staff. Within each of these themes were multiple subthemes including increased professional and personal demands, concern for personal safety, a sense of internal guilt, financial uncertainty, missed professional opportunities, and a negative impact on mentoring. Solutions were offered and included an emphasis on addressing preexisting inequities, the importance of community, and workplace flexibility. Conclusions The COVID-19 pandemic created burdens for already challenged faculty and staff in both their personal and professional lives. Swift action and advocacy by academic institutions is needed to support the lives and careers of our colleagues now and in the future.

IntroductionClinicians that care for hospitalised patients face unprecedented work conditions with exposure to highly infectious disease, exceedingly high patient numbers, and unpredictable work demands, all of which have resulted in increases in stress and burnout. Preliminary studies suggest that increasing workloads negatively affect inpatient clinician well-being and may negatively affect job performance; yet high workloads may be prioritised secondary to financial drivers or from workforce shortages. Despite this, the correlation between workload and these negative outcomes has not been fully quantified. Additionally, there are no clear measures for inpatient clinician workload and no standards to define ideal workloads. Using the protocol described here, we will perform a scoping review of the literature to generate a comprehensive understanding of how clinician workload of medical patients is currently defined, measured in clinical settings and its impact on the workforce, patients and institutional outcomes.Methods and analysisWe will follow the methodology outlined by Joanna Briggs Institute and Arksey and O’Malley to conduct a comprehensive search of major electronic databases including Ovid Medline (PubMed), Embase (Embase.com), PsycINFO, ProQuest Dissertations and Google Scholar. All relevant published peer-reviewed and dissertaion grey literature will be included. Data will be extracted using a standardised form to capture key article information. Results will be presented in a descriptive narrative format.Ethics and disseminationThis review does not require ethics approval though all included studies will be screened to ensure appropriate approval. The synthesis of this literature will provide a better understanding of the current state of work for inpatient clinicians, associated outcomes, and will identify gaps in the literature. These findings will be used in conjunction with an expert Delphi panel to identify measures of inpatient clinician workload to then guide the development of a novel workforce mobile application to actively track clinician work. We aim to lay the groundwork for future workforce studies to understand the optimal workloads that drive key outcomes for clinicians, patients and institutions.

Background Hospital systems have rapidly adapted to manage the influx of patients with COVID-19 and hospitalists, specialists in inpatient care, have been at the forefront of this response, rapidly adapting to serve the ever-changing needs of the community and hospital system. Institutional leaders, including clinical care team members and administrators, deployed many different strategies (i.e. adaptations) to manage the influx of patients. While many different strategies were utilized in hospitals across the United States, it is unclear how frontline care teams experienced these strategies and multifaceted changes. As these surge adaptations likely directly impact clinical care teams, we aimed to understand the perceptions and impact of these clinical care and staffing adaptations on hospitalists and care team members in order to optimize future surge plans. Methods Qualitative, semi-structured interviews and focus groups with hospitalist physicians, advanced practice providers (APPs), and hospital nursing and care management staff at a quaternary academic medical center. Interviews focused on the impact of COVID-19 surge practices on the following areas: (1) the experience of clinical care teams with the adaptations used to manage the surge (2) the perception and experience with the communication strategies utilized (3) the personal experience with the adaptations (i.e. how they impacted the individual) and (4) if participants had recommendations on strategies for future surges. We utilized rapid qualitative analysis methods to explore themes and subthemes. Results We conducted five focus groups and 21 interviews. Three themes emerged from the work including (1) dynamic clinical experience with a lot of uncertainty, (2) the importance of visible leadership with a focus on sense-making, and (3) the significant emotional toll on care team members. Subthemes included sufficient workforce, role delineation and training, information sharing, the unique dichotomy between the need for flexibility and the need for structure, the importance of communication, and the emotional toll not only on the provider but their families. Several recommendations came from this work. Conclusions COVID-19 surge practices have had direct impact on hospitalists and care team members. Several tactics were identified to help mitigate the many negative effects of COVID-19 on frontline hospitalist providers and care teams.

IntroductionThere is growing emphasis on the importance of both the cognitive and behavioural phenomenon of attention for clinicians engaged in patient care. Aspects of attention such as cognitive load, distraction and task switching have been studied in various settings with different methodologies. Using the protocol described here, we aim to systematically review the medical literature in order to map the concept of attention and to synthesise diverse concepts and methods under the broader category of research focused on ‘attention’.Methods and analysisFollowing the methodology described by the Joanna Briggs Institute and Arksey and O’Malley, our scoping review conducts an iterative search of Cumulative Index of Nursing and Allied Health Literature (CINAHL), Medline (PubMed) and EMBASE (Ovid). An initial limited search based on key concepts and terminology will generate relevant articles which in turn will be mined for additional keywords and index terms to guide a formal literature search. Our multidisciplinary team will extract data into a matrix, including a small random sample of the same studies (to ensure concordance), and present the results in a descriptive narrative format.Ethics and disseminationAs a secondary analysis, our study does not require ethics approval, and we will ensure that included studies have appropriate approval. We anticipate results will identify diverse ways of conceptualising clinician attention and will provide a foundation for developing additional metrics and study methods to optimise attention in the clinical environment. We will disseminate results through journals and conferences and coordinate with colleagues doing work in adjacent fields.

Objective Our objective was to determine the impact of the Health Literacy Universal Precautions Toolkit, adapted for rheumatology, on medication adherence, patient satisfaction, and feasibility in all patients; its effect on the clinical disease activity index (CDAI) was studied in a rheumatoid arthritis (RA) subpopulation. Methods Data collected during a 6‐month prospective quality assurance intervention was compared with data from a prior 6‐month period. Interventions included 1) encouraging questions, 2) teach‐back communication, and 3) brown‐bag medication review. Analysis was performed using linear regression or generalized estimating equation (GEE) regression. Results During the intervention period, 46 physicians completed 1737 patient visits. Questions were encouraged, and teach‐back communication was performed in more than 90% of visits. Brown‐bag medication reviews were performed in 47% of visits overall and 69% of visits in a subgroup that received additional reminder calls. Visit duration and patient satisfaction were not significantly increased. Adherence for rheumatology‐related medications that were prescribed both before and during the intervention increased by 22% (P ≤ 0.001; by GEE). Teach‐back communication predicted a statistically significant improvement in medication adherence in this subpopulation (by linear regression). The mean CDAI did not improve; however, African American race and Hispanic ethnicity were associated with a decreased CDAI (by GEE). Conclusion Implementation of the Health Literacy Universal Precautions Toolkit, adapted for rheumatology, improved medication adherence in our safety‐net clinic, with particularly strong effects seen with teach‐back communication. In certain populations, use of the toolkit may also improve RA disease activity. This is the first study to document improved medication adherence with this intervention in a real‐world setting.