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BackgroundViolence against doctors in China is a serious problem that has attracted attention from both domestic and international media. ObjectiveThis study investigates readers’ responses to media reports on violence against doctors to identify attitudes toward perpetrators and physicians and examine if such trends are influenced by national policies. MethodsWe searched 17 Chinese violence against doctors reports in international media sources from 2011 to 2020. We then tracked back the original reports and web crawled the 19,220 comments in China. To ascertain the possible turning point of public opinion, we searched violence against doctors–related policies from Tsinghua University ipolicy database from 2011 to 2020, and found 19 policies enacted by the Chinese central government aimed at alleviating the intense patient–physician relationship. We then conducted a series of interrupted time series analyses to examine the influence of these policies on public sentiment toward violence against doctors over time. ResultsThe interrupted time series analysis (ITSA) showed that the change in public sentiment toward violence against doctors reports was temporally associated with government interventions. The declarations of 10 of the public policies were followed by increases in the proportion of online public opinion in support of doctors (average slope changes of 0.010, P

BackgroundChronic obstructive pulmonary disease (COPD) is the third leading cause of death by disease worldwide and has a 30-day readmission rate of 22.6%. In 2015, COPD was added to the Medicare Hospital Readmission Reductions Program. ObjectiveThe objective of this paper was to survey the current medical technologies for remote patient monitoring (RPM) tools that forecast COPD exacerbations in order to reduce COPD readmissions. MethodsWe searched literature and digital health news to find commercially available RPM devices focused on predicting COPD exacerbations. These technologies were reviewed and compared according to four criteria: forecasting ability, cost, ease of use, and appearance. A rating system was developed to facilitate the evaluation process. ResultsAs of June 2019, a list of handheld and hands-free devices was compiled. We compared features and found substantial variations. Devices that ranked higher on all criteria tended to have a high or unlisted price. Commonly mass-marketed devices like the pulse oximeter and spirometer surprisingly fulfilled the least criteria. ConclusionsThe COPD RPM technologies with most technological promise and compatibility with daily living appear to have high or unlisted prices. Consumers and providers need better access to product information to make informed decisions.

BackgroundPatient portals tethered to electronic health records can improve patient experience, activation, and outcomes. However, adoption of inpatient portals has been challenging. One way to potentially increase inpatient portal usage is to integrate it with a room control (RC) app on a common tablet computer. ObjectiveThe aim of this study was to perform a retrospective analysis of patient usage of an RC app provided on tablet computers in patient rooms of our new inpatient tower. MethodsWe identified all patients who were admitted for >24 hours to our new inpatient tower over a 90-day period from September 1 to November 30, 2017. After excluding newborn patients from our analysis, we then identified patients who used the RC app at least one time during their admission. We linked these data to patient demographics (including age, sex, and race) and admitting service. We then performed univariable and multivariable logistic regression to assess patterns of RC app usage. ResultsA total of 3411 patients were admitted over the course of the study period; 2242/3411 (65.73%) used the RC app during their hospitalization. Compared with white patients, other/mixed/unknown race and Asian, Hawaiian, Pacific Islander, American Indian race were significantly associated with increased use of the RC app in a multivariable analysis. Increasing age was significantly associated with increased usage of the RC app. Usage of the RC app also varied by admitting services. Compared with general medicine, bone marrow transplant and general surgery patients had increased usage of the RC app. Conversely, critical care, medical specialties, neurology, surgical subspecialties, and obstetrics/gynecology were all associated with decreased usage of the RC app. ConclusionsOur study shows that one-third of patients are not using the RC app for critical room functions. Future initiatives to increase RC usage should take these populations into consideration. Contrary to common belief, older patients may use tablet-enabled RCs just as often, if not more often, than younger patients. Certain admitting services, such as neurology and surgical subspecialties, may have had lower usage rates owing to accessibility issues. Our study allows hospitals to tailor support for specific patient populations to increase RC app usage.

Introduction: Vaccinations for COVID-19 are being distributed, yet vaccine hesitance is placing many people at risk for infection, negative outcomes, and compromising public health. Given primary care clinics are where people most often interact with health care providers, understanding factors associated with this hesitance may help providers in integrated primary care settings best address this hesitance. Method: Between September and November of 2020, a survey was sent to all primary care patients within a large southern California health system, with over 10,000 responding (22% response rate). Survey items included sociodemographic variables, level of vaccine hesitance, 'proximity to COVID' (e.g., direct exposure to COVID-19 and consequences), as well as a patient's primary source of health information (e.g., traditional news, social media, etc.). Responses assessed the strength of hesitance. Results: Results showed that while 78% of participants 'strongly' believed vaccines generally are a good way to protect from illness, only 51% reported strong willingness to get the COVID-19 vaccine. Consistent with previous surveys, younger patients were more hesitant to get vaccinated, as were people of color. Unique to this survey was the finding that those relying on social media, faith-based organizations, or family/friends for health information had the greatest vaccine hesitance. Discussion: While our patient sample was less hesitant than other U.S. adult samples previously reported in the literature, our data suggest that targeting those patients who report reliance on nontraditional health information sources should be approached by primary care teams, including behavioral health providers, to address vaccine hesitancy. Keywords: COVID-19, vaccination, vaccine hesitancy, social media, survey, The COVID-19 global pandemic propelled important public health efforts to broaden the utilization of masks, protective eyewear, hand washing, and physical distancing to reduce viral spread. Shortly after, a massive [...]

Introduction Methods Results Conclusion Addressing physician burnout is critical for healthcare systems. As electronic health record (EHR) workload and teamwork have been identified as major contributing factors to physician well‐being, we aimed to mitigate burnout through EHR‐based interventions and a compassion team practice (CTP), targeting EHR workload and team cohesion.A modified stepped wedge‐clustered randomized trial was conducted, involving specialties with heavy InBasket workloads. EHR interventions included quick‐action shortcuts and recommended practice for secure chats. The CTP comprised 30‐s practice between physicians and their dyad partners. Survey and EHR data were collected over four assessment periods. Linear and generalized mixed‐effects models assessed intervention effects, accounting for covariates.Forty‐four physicians participated (20% participation rate). While burnout prevalence decreased from 58.5% at baseline to 50.0% at the end of the study, burnout reduction was not statistically significant after EHR (OR 0.43, 95% CI 0.12 to 1.61, p = 0.21) or EHR + CTP (OR 0.60, 95% CI 0.17 to 2.10, p = 0.42) interventions. Statistically significant greater perceived ease of EHR work resulted from both the EHR intervention (coefficient 0.76, 95% CI 0.22 to 1.29, p = 0.01) and EHR + CTP intervention (coefficient 0.80, 95% CI 0.26 to 1.35, p < 0.01). EHR + CTP increased perceived workplace supportiveness (coefficient 0.61, 95% CI −0.04 to 1.26, p = 0.07). Total number of InBasket messages/week increased significantly after EHR interventions (coefficient = 27.4, 95% CI 6.69 to 48.1, p = 0.011) and increased after EHR + CTP (18.5, 95% CI −3.15 to 40.2, p = 0.097).While burnout reduction was not statistically significant, EHR interventions positively impacted workload perceptions. CTP showed potential for improving perceived workplace supportiveness. Further research is needed to explore the efficacy of CTP with more participants. The interventions gained interest beyond our institution and prompted consideration for broader implementation. [ABSTRACT FROM AUTHOR]

Background: Artificial intelligence (AI) is a rapidly advancing field that is beginning to enter the practice of medicine. Primary care is a cornerstone of medicine and deals with challenges such as physician shortage and burnout which impact patient care. AI and its application via digital health is increasingly presented as a possible solution. However, there is a scarcity of research focusing on primary care physician (PCP) attitudes toward AI. This study examines PCP views on AI in primary care. We explore its potential impact on topics pertinent to primary care such as the doctor-patient relationship and clinical workflow. By doing so, we aim to inform primary care stakeholders to encourage successful, equitable uptake of future AI tools. Our study is the first to our knowledge to explore PCP attitudes using specific primary care AI use cases rather than discussing AI in medicine in general terms. Methods: From June to August 2023, we conducted a survey among 47 primary care physicians affiliated with a large academic health system in Southern California. The survey quantified attitudes toward AI in general as well as concerning two specific AI use cases. Additionally, we conducted interviews with 15 survey respondents. Results: Our findings suggest that PCPs have largely positive views of AI. However, attitudes often hinged on the context of adoption. While some concerns reported by PCPs regarding AI in primary care focused on technology (accuracy, safety, bias), many focused on people-and-process factors (workflow, equity, reimbursement, doctor-patient relationship). Conclusion: Our study offers nuanced insights into PCP attitudes towards AI in primary care and highlights the need for primary care stakeholder alignment on key issues raised by PCPs. AI initiatives that fail to address both the technological and people-and-process concerns raised by PCPs may struggle to make an impact. [ABSTRACT FROM AUTHOR]

Evidence to date indicates that compassion and empathy are health-enhancing qualities. Research points to interventions and practices involving compassion and empathy being beneficial, as well as being salient outcomes of contemplative practices such as mindfulness. Advancing the science of compassion and empathy requires that we select measures best suited to evaluating effectiveness of training and answering research questions. The objective of this scoping review was to 1) determine what instruments are currently available for measuring empathy and compassion, 2) assess how and to what extent they have been validated, and 3) provide an online tool to assist researchers and program evaluators in selecting appropriate measures for their settings and populations. A scoping review and broad evidence map were employed to systematically search and present an overview of the large and diverse body of literature pertaining to measuring compassion and empathy. A search string yielded 19,446 articles, and screening resulted in 559 measure development or validation articles reporting on 503 measures focusing on or containing subscales designed to measure empathy and/or compassion. For each measure, we identified the type of measure, construct being measured, in what context or population it was validated, response set, sample items, and how many different types of psychometrics had been assessed for that measure. We provide tables summarizing these data, as well as an open-source online interactive data visualization allowing viewers to search for measures of empathy and compassion, review their basic qualities, and access original citations containing more detail. Finally, we provide a rubric to help readers determine which measure(s) might best fit their context. [ABSTRACT FROM AUTHOR]

Objective Physicians of all specialties experienced unprecedented stressors during the COVID-19 pandemic, exacerbating preexisting burnout. We examine burnout's association with perceived and actionable electronic health record (EHR) workload factors and personal, professional, and organizational characteristics with the goal of identifying levers that can be targeted to address burnout. Materials and Methods Survey of physicians of all specialties in an academic health center, using a standard measure of burnout, self-reported EHR work stress, and EHR-based work assessed by the number of messages regarding prescription reauthorization and use of a staff pool to triage messages. Descriptive and multivariable regression analyses examined the relationship among burnout, perceived EHR work stress, and actionable EHR work factors. Results Of 1038 eligible physicians, 627 responded (60% response rate), 49.8% reported burnout symptoms. Logistic regression analysis suggests that higher odds of burnout are associated with physicians feeling higher level of EHR stress (odds ratio [OR], 1.15; 95% confidence interval [CI], 1.07–1.25), having more prescription reauthorization messages (OR, 1.23; 95% CI, 1.04–1.47), not feeling valued (OR, 3.38; 95% CI, 1.69–7.22) or aligned in values with clinic leaders (OR, 2.81; 95% CI, 1.87–4.27), in medical practice for ≤15 years (OR, 2.57; 95% CI, 1.63–4.12), and sleeping for <6 h/night (OR, 1.73; 95% CI, 1.12–2.67). Discussion Perceived EHR stress and prescription reauthorization messages are significantly associated with burnout, as are non-EHR factors such as not feeling valued or aligned in values with clinic leaders. Younger physicians need more support. Conclusion A multipronged approach targeting actionable levers and supporting young physicians is needed to implement sustainable improvements in physician well-being. [ABSTRACT FROM AUTHOR]

Physician turnover is an important source of expense, burnout, and poor quality of care. Using a novel method with Centers for Medicare & Medicaid Services data, this study examined turnover rates by physician, practice, and patient characteristics. The findings shed new light on turnover trends over time and differences across specialty and gender and, collectively, have important policy and clinical implications. Visual Abstract. Physician Turnover in the United States: Physician turnover is an important source of expense, burnout, and poor quality of care. In this study, Bond and colleagues used a novel method with Centers for Medicare & Medicaid Services data to examine turnover rates by physician, practice, and patient characteristics. Their findings shed new light on turnover trends over time and differences across specialty and gender and, collectively, have important policy and clinical implications. Background: Medical groups, health systems, and professional associations are concerned about potential increases in physician turnover, which may affect patient access and quality of care. Objective: To examine whether turnover has changed over time and whether it is higher for certain types of physicians or practice settings. Design: The authors developed a novel method using 100% of traditional Medicare billing to create national estimates of turnover. Standardized turnover rates were compared by physician, practice, and patient characteristics. Setting: Traditional Medicare, 2010 to 2020. Participants: Physicians billing traditional Medicare. Measurements: Indicators of physician turnover—physicians who stopped practicing and those who moved from one practice to another—and their sum. Results: The annual rate of turnover increased from 5.3% to 7.2% between 2010 and 2014, was stable through 2017, and increased modestly in 2018 to 7.6%. Most of the increase from 2010 to 2014 came from physicians who stopped practicing increasing from 1.6% to 3.1%; physicians moving increased modestly from 3.7% to 4.2%. Modest but statistically significant (P  < 0.001) differences existed across rurality, physician sex, specialty, and patient characteristics. In the second and third quarters of 2020, quarterly turnover was slightly lower than in the corresponding quarters of 2019. Limitation: Measurement was based on traditional Medicare claims. Conclusion: Over the past decade, physician turnover rates have had periods of increase and stability. These early data, covering the first 3 quarters of 2020, give no indication yet of the COVID-19 pandemic increasing turnover, although continued tracking of turnover is warranted. This novel method will enable future monitoring and further investigations into turnover. Primary Funding Source: The Physicians Foundation Center for the Study of Physician Practice and Leadership. [ABSTRACT FROM AUTHOR]

Objectives Ambient clinical documentation technology uses automatic speech recognition (ASR) and natural language processing (NLP) to turn patient–clinician conversations into clinical documentation. It is a promising approach to reducing clinician burden and improving documentation quality. However, the performance of current-generation ASR remains inadequately validated. In this study, we investigated the impact of non-lexical conversational sounds (NLCS) on ASR performance. NLCS, such as Mm-hm and Uh-uh , are commonly used to convey important information in clinical conversations, for example, Mm-hm as a "yes" response from the patient to the clinician question "are you allergic to antibiotics?" Materials and Methods In this study, we evaluated 2 contemporary ASR engines, Google Speech-to-Text Clinical Conversation ("Google ASR"), and Amazon Transcribe Medical ("Amazon ASR"), both of which have their language models specifically tailored to clinical conversations. The empirical data used were from 36 primary care encounters. We conducted a series of quantitative and qualitative analyses to examine the word error rate (WER) and the potential impact of misrecognized NLCS on the quality of clinical documentation. Results Out of a total of 135 647 spoken words contained in the evaluation data, 3284 (2.4%) were NLCS. Among these NLCS, 76 (0.06% of total words, 2.3% of all NLCS) were used to convey clinically relevant information. The overall WER, of all spoken words, was 11.8% for Google ASR and 12.8% for Amazon ASR. However, both ASR engines demonstrated poor performance in recognizing NLCS: the WERs across frequently used NLCS were 40.8% (Google) and 57.2% (Amazon), respectively; and among the NLCS that conveyed clinically relevant information, 94.7% and 98.7%, respectively. Discussion and Conclusion Current ASR solutions are not capable of properly recognizing NLCS, particularly those that convey clinically relevant information. Although the volume of NLCS in our evaluation data was very small (2.4% of the total corpus; and for NLCS that conveyed clinically relevant information: 0.06%), incorrect recognition of them could result in inaccuracies in clinical documentation and introduce new patient safety risks. [ABSTRACT FROM AUTHOR]

The true incidence and comprehensive characteristics of Long Coronavirus Disease-19 (COVID-19) are currently unknown. This is the first population-based outreach study of Long COVID within an entire health system, conducted to determine operational needs to care for patients with Long COVID. [ABSTRACT FROM AUTHOR]

Introduction: Digital exposure notification (EN) approaches may offer considerable advantages over traditional contact tracing in speed, scale, efficacy, and confidentiality in pandemic control. We applied the science of learning health systems to test the effect of framing and digital means, email vs Short Message Service (SMS), on EN adoption among patients of an academic health center. Methods: We tested three communication approaches of the Apple and Google EN system in a rapid learning cycle involving 15 000 patients pseudorandomly assigned to three groups. The patients in the first group received a 284‐word email that presented EN as a tool that can help slow the spread. The patients in the second group received a 32‐word SMS that described EN as a new tool to help slow the spread (SlowTheSpreadSMS). Patients in the third group received a 47‐word SMS that depicted the system as a new digital tool that can empower them to protect their family and friends (EmpowerSMS). A brief four‐question anonymous survey of adoption was included in a reminder message sent 2 days after the initial outreach. Results: One hundred and sixty people responded to the survey within 1 week: 2.33% from EmpowerSMS, 0.97% from SlowTheSpreadSMS, and 0.53% from emails; 29 (41.43%), 24 (41.38%), and 11 (34.38%) reported having adopted EN from each group, respectively. Patient reported barriers to adoption included iOS version incompatibility, privacy concerns, and low trust of government agencies or companies like Apple and Google. Patients recommended that healthcare systems play an active role in disseminating information about this tool. Patients also recommended advertising on social media and providing reassurance about privacy. Conclusions: The EmpowerSMS resulted in relatively more survey responses. Both SMS groups had slightly higher, but not statistically significant EN adoption rates compared to email. Findings from the pilot not only informed operational decision‐making in our health system but also contributed to EN rollout planning in our State. [ABSTRACT FROM AUTHOR]

As an experiment, in employees who were provided with report cards in 1995-1996, it was found that subjective measures of quality and coverage influenced plan choices after controlling for plan premiums, out of their pocket expenses and service coverages. This effect was found stronger within smaller samples of new hires as compared to a larger sample of existing employees.

Background: In comparison with the general population, physicians, and physicians-in-training are at greater risk for suicide. Although key gender differences in suicide risk factors and behaviors have been identified in the general population, the extent to which these differences apply to physicians and physicians-in-training is unclear. Here, we aimed to identify gender differences in risk factors, clinical presentation, and help-seeking behaviors of medical students, house staff, and physician faculty at high risk for suicide.Methods: We explored gender differences among 450 physicians and trainees meeting criteria for high suicide risk on anonymous online questionnaires completed between 2009 and 2017.Results: High-risk female trainees and physicians had higher mean Patient Health Questionnaire-9 (PHQ-9) scores compared with the males (11.1, standard deviation [SD] 5.1 vs. 9.8, SD 4.7) and were more likely to endorse feeling worried (73.8% vs. 61.2%), irritable (60.4% vs. 49.4%), and stressed (79.6% vs. 70%). High-risk male trainees and physicians were more likely than females to endorse suicidal thoughts (31.2% vs. 22.1%), intense anger (24.3% vs. 16.1%), drinking too much (31.2% vs. 22.3%), and recreational drug or prescription medication use without clinically appropriate follow-up (9.4% vs. 4.3%). There were no gender differences in help-seeking behaviors.Conclusions: This is the first study to report gender differences among risk factors, presentation, and help-seeking behaviors of physicians, and trainees at high risk for suicide. Our findings are mostly consistent with those of the general population and show that only a minority of at-risk men and women in healthcare sought treatment, highlighting the importance of intervention and suicide prevention in this population. [ABSTRACT FROM AUTHOR]

As a major contributor to the burden of most chronic diseases, insufficient physical activity (PA) creates a significant financial burden on the health care system. Numerous interventions effectively increase PA, but few are integrated into primary care clinic workflows. Exercise Is Medicine (EIM) is a global health initiative committed to the belief that PA is integral to the prevention and treatment of diseases and should be routinely assessed as a vital sign and treated in the health care setting. This paper describes an in-progress embedded quality improvement (QI) project that integrates EIM into routine clinical practice. A combination of implementation science (IS) and QI models are used to adapt, implement, and evaluate the integration of EIM into six primary care clinics. The Practical, Robust Implementation and Sustainability Model (PRISM) guided preimplementation evaluation and adaptation of EIM protocol, materials, and delivery strategies. The learning evaluation QI model is used to design, test, refine, and implement EIM using rapid, 3 month Plan-Do-Study-Act microcycles. Learning meetings are used to obtain feedback and optimize workflow. The Stirman Framework is used to document adaptations to the program throughout implementation. Reach, adoption, implementation, effectiveness, and maintenance outcomes embedded within PRISM will guide the program evaluation to determine sustainability and scalability. Using an innovative approach of combining IS and QI methods to improve the identification of primary care patients with insufficient PA to increase their activity levels has great population health potential. Our work will inform the best approaches for EIM integration in primary care. [ABSTRACT FROM AUTHOR]

Background: Most persons with dementia have multiple chronic conditions; however, it is unclear whether co‐existing chronic conditions contribute to health‐care use and cost. Methods: Persons with dementia and ≥2 chronic conditions using the National Health and Aging Trends Study and Medicare claims data, 2011 to 2014. Results: Chronic kidney disease and ischemic heart disease were significantly associated with increased adjusted risk ratios of annual hospitalizations, hospitalization costs, and direct medical costs. Depression, hypertension, and stroke or transient ischemic attack were associated with direct medical and societal costs, while atrial fibrillation was associated with increased hospital and direct medical costs. No chronic condition was associated with informal care costs. Conclusions: Among older adults with dementia, proactive and ambulatory care that includes informal caregivers along with primary and specialty providers, may offer promise to decrease use and costs for chronic kidney disease, ischemic heart disease, atrial fibrillation, depression, and hypertension. [ABSTRACT FROM AUTHOR]

Objective: To describe the implementation of technological support important for optimizing clinical management of the COVID-19 pandemic.Materials and Methods: Our health system has confirmed prior and current cases of COVID-19. An Incident Command Center was established early in the crisis and helped identify electronic health record (EHR)-based tools to support clinical care.Results: We outline the design and implementation of EHR-based rapid screening processes, laboratory testing, clinical decision support, reporting tools, and patient-facing technology related to COVID-19.Discussion: The EHR is a useful tool to enable rapid deployment of standardized processes. UC San Diego Health built multiple COVID-19-specific tools to support outbreak management, including scripted triaging, electronic check-in, standard ordering and documentation, secure messaging, real-time data analytics, and telemedicine capabilities. Challenges included the need to frequently adjust build to meet rapidly evolving requirements, communication, and adoption, and to coordinate the needs of multiple stakeholders while maintaining high-quality, prepandemic medical care.Conclusion: The EHR is an essential tool in supporting the clinical needs of a health system managing the COVID-19 pandemic. [ABSTRACT FROM AUTHOR]

Electronic health record (EHR) log data have shown promise in measuring physician time spent on clinical activities, contributing to deeper understanding and further optimization of the clinical environment. In this article, we propose 7 core measures of EHR use that reflect multiple dimensions of practice efficiency: total EHR time, work outside of work, time on documentation, time on prescriptions, inbox time, teamwork for orders, and an aspirational measure for the amount of undivided attention patients receive from their physicians during an encounter, undivided attention. We also illustrate sample use cases for these measures for multiple stakeholders. Finally, standardization of EHR log data measure specifications, as outlined here, will foster cross-study synthesis and comparative research. [ABSTRACT FROM AUTHOR]