Physician Oversight Research Articles

Perceptions of Multimorbid Patients When Health Care Staff Accompany Family Physicians In Primary Care Settings

Background: Multimorbidity, the presence of two or more chronic conditions in an individual, presents significant challenges in primary care, including fragmented care, higher healthcare costs, and difficulty in care coordination. Integrating nursing professionals into primary care teams has been proposed as a strategy to enhance access, improve care quality, and address these challenges. However, limited attention has been given to understanding patients’ perspectives, particularly those with multimorbidity, regarding the inclusion of health care staff in primary care practices. Methods: This qualitative descriptive study utilized semi-structured interviews to explore the perceptions of patients with multimorbidity toward the integration of health care staff in primary care settings. Participants were recruited from diverse healthcare environments, ensuring varied experiences with collaborative care models. Patients with five or more chronic illnesses were purposefully sampled, with interviews focusing on their experiences and expectations of health care staff involvement in primary care. Thematic analysis of interview transcripts was conducted using NVivo software, employing both inductive and deductive coding methods. Results: 28 participants with diverse chronic conditions were interviewed, with most expressing openness to health care staff involvement in primary care. Three central themes emerged: Expectations of Enhanced Care: Participants anticipated improved accessibility and continuity of care through health care staff integration but highlighted concerns about reduced access to physicians. Perception of the Health care staff ’s Role: While many viewed health care staff in supportive roles, others recognized their broader responsibilities in patient education, chronic disease management, and medication monitoring. Trust in health care staff ’ competence varied, with participants favoring physician oversight for complex tasks. Conditions for Effective Integration: Patients emphasized the need for clear role definitions, robust communication between health care staff and doctors, adherence to protocols, and continuity of care with the same health care staff to build trust. Conclusion: Patients with multimorbidity generally support the integration of health care staff into primary care teams, recognizing potential benefits in accessibility and care coordination. However, successful implementation requires clear delineation of roles, effective communication, and strategies to build trust. These findings highlight the importance of incorporating patient perspectives into healthcare system reforms to ensure collaborative care models meet their needs effectively.

Impersonating Expertise: The Ethics of Misleading Dermatology Advertising

The proliferation of medical spas has led to an increase in misleading advertising practices, particularly relating to the qualifications of practitioners and the risks of cosmetic procedures. Aestheticians manage many spas without having the extensive and rigorous training that board-certified dermatologists undergo. By advertising physician oversight when there is none and promoting procedures as minimally invasive, these facilities create a false sense of security for patients. Procedures such as laser therapies and injectables require specialized expertise to avoid and, if necessary, treat potentially dangerous complications. The ethics of misleading advertising in dermatology must be considered due to its impact on patient decision-making (autonomy), safety (beneficence), and confidence regarding the medical profession.

Ethical Application of Generative Artificial Intelligence in Medicine.

Generative artificial intelligence(AI) may revolutionize healthcare, providing solutions that range from enhancing diagnostic accuracy to personalizing treatment plans. However, its rapid and largely unregulated integration into medicine raises ethical concerns related to data integrity, patient safety, and appropriate oversight. One of the primary ethical challenges lies in generative AI's potential to produce misleading or fabricated information, posing risks of misdiagnosis or inappropriate treatment recommendations, which underscore the necessity for robust physician oversight. Transparency also remains a critical concern as the closed-source nature of many large-language models(LLMs) prevents both patients and healthcare providers from understanding the reasoning behind AI-generated outputs, potentially eroding trust. The lack of regulatory approval for AI as a medical device, combined with concerns around the security of patient-derived data and AI-generated synthetic data, further complicates its safe integration into clinical workflows. Furthermore, synthetic datasets generated by AI, while valuable for augmenting research in areas with scarce data, complicate questions of data ownership, patient consent, and scientific validity. Additionally, generative AI's ability to streamline administrative tasks risks depersonalizing care, further distancing providers from patients. These challenges compound the deeper issues plaguing the healthcare system, including the emphasis of volume and speed - over value and expertise. The utilization of generative AI in medicine brings about mass scaling of synthetic information, thereby necessitating careful adoption to protect patient care and medical advancement. Given these considerations, generative AI applications warrant regulatory and critical scrutiny . Key starting points include establishing strict standards for data security and transparency, implementing oversight akin to Institutional Review Boards(IRBs) to govern data usage, and developing interdisciplinary guidelines that involve developers, clinicians, and ethicists. By addressing these concerns, we can better align generative AI adoption with the core foundations of humanistic healthcare - preserving patient safety, autonomy, and trust while harnessing AI's transformative potential. LEVEL OF EVIDENCE: Level V: Expert Opinion.

Establishing a Gynecology Student-Run Free Clinic: A Joint Medical Student and Resident Physician Initiative

Dedicated women’s health services are rarely mentioned in the student-run free clinic literature. As society grappled with repeated waves of coronavirus-2019, the number of healthcare professionals decreased across the country and impacted all healthcare settings, including student-run free clinics. In response, a collaboration between medical students and Obstetrics & Gynecology resident physicians at Oakland University William Beaumont School of Medicine and the Gary Burnstein Community Health Clinic established a new gynecology free clinic. This program, under the joint oversight of medical students and resident physicians in addition to attending physician support, provided uninsured women across Southeast Michigan with critical access to healthcare services at a time demand for services was similarly rising. Our clinic emphasized excellence in screening, contraception, and vaccination and, in doing so, provided our patients with evidence-based care and a medical home. Our experience demonstrates student-run free clinics are uniquely positioned to critically expand access to women’s health services. Additionally, the establishment of a joint medical student and resident physician endeavor can further enrich both the educational and patient-care experience.

Nurse practitioner oversight ratios and labor market outcomes

AbstractNurse practitioners are important to the US healthcare system; however, many states impose physician oversight ratios, which limit the number of NPs a physician may supervise. In this study, we evaluate the effect of eliminating physician oversight ratios on the supply of NPs by conducting case studies of three states—New York, Nevada, and Pennsylvania—using synthetic control and related approaches. Surprisingly, we find that eliminating oversight ratios had little effect on the labor supply of NPs. For New York, we also analyze the effects of eliminating oversight ratios on wages and hours worked and again find null results.

Comparing ChatGPT and a Single Anesthesiologist's Responses to Common Patient Questions: An Exploratory Cross-Sectional Survey of a Panel of Anesthesiologists.

Increased patient access to electronic medical records and resources has resulted in higher volumes of health-related questions posed to clinical staff, while physicians' rising clinical workloads have resulted in less time for comprehensive, thoughtful responses to patient questions. Artificial intelligence chatbots powered by large language models (LLMs) such as ChatGPT could help anesthesiologists efficiently respond to electronic patient inquiries, but their ability to do so is unclear. A cross-sectional exploratory survey-based study comprised of 100 anesthesia-related patient question/response sets based on two fictitious simple clinical scenarios was performed. Each question was answered by an independent board-certified anesthesiologist and ChatGPT (GPT-3.5 model, August 3, 2023 version). The responses were randomized and evaluated via survey by three blinded board-certified anesthesiologists for various quality and empathy measures. On a 5-point Likert scale, ChatGPT received similar overall quality ratings (4.2 vs. 4.1, p = .81) and significantly higher overall empathy ratings (3.7 vs. 3.4, p < .01) compared to the anesthesiologist. ChatGPT underperformed the anesthesiologist regarding rate of responses in agreement with scientific consensus (96.6% vs. 99.3%, p = .02) and possibility of harm (4.7% vs. 1.7%, p = .04), but performed similarly in other measures (percentage of responses with inappropriate/incorrect information (5.7% vs. 2.7%, p = .07) and missing information (10.0% vs. 7.0%, p = .19)). In conclusion,LLMs show great potential in healthcare, but additional improvement is needed to decrease the risk of patient harm and reduce the need for close physician oversight. Further research with more complex clinical scenarios, clinicians, and live patients is necessary to validate their role in healthcare.

The Economic Impact of Community Paramedics Within Emergency Medical Services: A Systematic Review.

Globally, emergency medical services (EMSs) report that their demand is dominated by non-emergency (such as urgent and primary care) requests. Appropriately managing these is a major challenge for EMSs, with one mechanism employed being specialist community paramedics. This review guides policy by evaluating the economic impact of specialist community paramedic models from a healthcare system perspective. A multidisciplinary team (health economics, emergency care, paramedicine, nursing) was formed, and a protocol registered on PROSPERO (CRD42023397840) and published open access. Eligible studies included experimental and analytical observational study designs of economic evaluation outcomes of patients requesting EMSs via an emergency telephone line ('000', '111', '999', '911' or equivalent) responded to by specialist community paramedics, compared to patients attended by usual care (i.e. standard paramedics). A three-stage systematic search was performed, including Peer Review of Electronic Search Strategies (PRESS) and Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA). Two independent reviewers extracted and verified 51 unique characteristics from 11 studies, costs were inflated and converted, and outcomes were synthesised with comparisons by model, population, education and reliability of findings. Eleven studies (n = 7136 intervention group) met thecriteria. These included one cost-utility analysis (measuring both costs and consequences), four costing studies (measuring cost only) and six cohort studies (measuring consequences only). Quality was measured using Joanna Briggs Institute tools, and was moderate for ten studies, and low for one. Models included autonomous paramedics (six studies, n = 4132 intervention), physician oversight (three studies, n = 932 intervention) and/or special populations (five studies, n = 3004 intervention). Twenty-one outcomes were reported. Models unanimously reduced emergency department (ED) transportation by 14-78% (higher quality studies reduced emergency department transportation by 50-54%, n = 2639 intervention, p < 0.001), and costs were reduced by AU$338-1227 per attendance in four studies (n = 2962). One study performed an economic evaluation (n = 1549), finding both that the costs were reduced by AU$454 per attendance (although not statistically significant), and consequently that the intervention dominated with a > 95% chance of the model being cost effective at the UK incremental cost-effectiveness ratio threshold. Community paramedic roles within EMSs reduced ED transportation by approximately half. However, the rate was highly variable owing to structural (such as local policies) and stochastic (such as the patient's medical condition) factors. As models unanimously reduced ED transportation-a major contributor to costs-they in turn lead to net healthcare system savings, provided there is sufficient demand to outweigh model costs and generate net savings. However, all models shift costs from EDs to EMSs, and therefore appropriate redistribution of benefits may be necessary to incentivise EMS investment. Policymakers for EMSs could consider negotiating with their health department, local ED or insurers to introduce a rebate for successful community paramedic non-ED-transportations. Following this, geographical areas with suitable non-emergency demand could be identified, and community paramedic models introduced and tested with a prospective economic evaluation or, where this is not feasible, with sufficient data collection to enable a post hoc analysis.

Position Statement:UHMS Position Statement + Physician’s Duties in Hyperbaric Medicine - 99183

ABSTRACT Hyperbaric oxygen treatment demands a meticu- lous approach to patient management. As the com- plexity of hyperbaric patients continues to evolve, the direct oversight of qualified physicians becomes paramount to ensuring optimal patient outcomes and safeguarding against potential risks. In this statement, we outline the key reasons physician involvement is essential in every facet of HBO2, ad- dressing the technical intricacies of the treatment and the broader spectrum of patient care.

Operational Impact of Neurology Rural Access Model: Reflections on the Importance of Demand-Shaping.

Demand for specialty neurologic care has been steadily increasing over the past several decades, and health systems are needing to meet the demands of their patients while managing a dwindling workforce. This retrospective study investigates the operational impact of a regional neurology clinic staffed by advanced practice providers with remote physician oversight in a "hub and spoke" delivery model to serve lower complexity patients. A retrospective, cross-sectional study was conducted to evaluate outcomes. Descriptive analysis of referral volumes, cancellation/no-show rates, and patient complexity as determined by the reason for referral were used to evaluate patients who received referrals from rural counties north of the primary neurology practice before and after the opening of the regional clinic. These metrics were evaluated longitudinally from counties of interest and for differences in patients seen at the regional clinic vs primary neurology practice. Referral volumes from the northern counties increased at significantly higher rates after the opening of the regional clinic than other counties in the serviced area. This resulted in an increase in patients seen in the hub clinics and spoke clinic. The regional clinic did see patients who were less complex than the primary practice; however, the total volume of low-complexity patients scheduled at the primary practice did not decrease. Cancellation and no-show rates did not seem to be affected in either clinic. The opening of a regional "spoke" clinic resulted in the generation of greater referral volumes that exceeded the capacity created by the clinic. Owing to this, there was an increase in the number of patients seen from the regional counties in the hub clinics, negating the potential benefit of improving access for high-complexity patients. Importance of demand-shaping and appropriate utilization as part of the value equation are discussed, followed by discussion of mitigation strategies.

Using ChatGPT-4 to Analyze 24-Hour Urine Results and Generate Custom Dietary Recommendations for Nephrolithiasis.

Purpose: The increasing incidence of nephrolithiasis underscores the need for effective, accessible tools to aid urologists in preventing recurrence. Despite dietary modification's crucial role in prevention, targeted dietary counseling using 24-hour urine collections is underutilized. This study evaluates ChatGPT-4, a multimodal large language model, in analyzing urine collection results and providing custom dietary advice, exploring the potential for artificial intelligence-assisted analysis and counseling. Materials and Methods: Eleven unique prompts with synthesized 24-hour urine collection results were submitted to ChatGPT-4. The model was instructed to provide five dietary recommendations in response to the results. One prompt contained all "normal" values, with subsequent prompts introducing one abnormality each. Generated responses were assessed for accuracy, completeness, and appropriateness by two urologists, a nephrologist, and a clinical dietitian. Results: ChatGPT-4 achieved average scores of 5.2/6 for accuracy, 2.4/3 for completeness, and 2.6/3 for appropriateness. It correctly identified all "normal" values but had difficulty consistently detecting abnormalities and formulating appropriate recommendations. The model performed particularly poorly in response to calcium and citrate abnormalities and failed to address 3/10 abnormalities entirely. Conclusions: ChatGPT-4 exhibits potential in the dietary management of nephrolithiasis but requires further refinement for dependable performance. The model demonstrated the ability to generate personalized recommendations that were often accurate and complete but displayed inconsistencies in identifying and addressing urine abnormalities. Despite these limitations, with precise prompt design, physician oversight, and continued training, ChatGPT-4 can serve as a foundation for personalized medicine while also reducing administrative burden, indicating its promising role in improving the management of conditions such as nephrolithiasis.

Performance of a Large Language Model on Japanese Emergency Medicine Board Certification Examinations.

Emergency physicians need a broad range of knowledge and skills to address critical medical, traumatic, and environmental conditions. Artificial intelligence (AI), including large language models (LLMs), has potential applications in healthcare settings; however, the performance of LLMs in emergency medicine remains unclear. To evaluate the reliability of information provided by ChatGPT, an LLM was given the questions set by the Japanese Association of Acute Medicine in its board certification examinations over a period of 5 years (2018-2022) and programmed to answer them twice. Statistical analysis was used to assess agreement of the two responses. The LLM successfully answered 465 of the 475 text-based questions, achieving an overall correct response rate of 62.3%. For questions without images, the rate of correct answers was 65.9%. For questions with images that were not explained to the LLM, the rate of correct answers was only 52.0%. The annual rates of correct answers to questions without images ranged from 56.3% to 78.8%. Accuracy was better for scenario-based questions (69.1%) than for stand-alone questions (62.1%). Agreement between the two responses was substantial (kappa = 0.70). Factual error accounted for 82% of the incorrectly answered questions. An LLM performed satisfactorily on an emergency medicine board certification examination in Japanese and without images. However, factual errors in the responses highlight the need for physician oversight when using LLMs.

Evaluating the Use of ChatGPT to Accurately Simplify Patient-centered Information about Breast Cancer Prevention and Screening.

Purpose To evaluate the use of ChatGPT as a tool to simplify answers to common questions about breast cancer prevention and screening. Materials and Methods In this retrospective, exploratory study, ChatGPT was requested to simplify responses to 25 questions about breast cancer to a sixth-grade reading level in March and August 2023. Simplified responses were evaluated for clinical appropriateness. All original and simplified responses were assessed for reading ease on the Flesch Reading Ease Index and for readability on five scales: Flesch-Kincaid Grade Level, Gunning Fog Index, Coleman-Liau Index, Automated Readability Index, and the Simple Measure of Gobbledygook (ie, SMOG) Index. Mean reading ease, readability, and word count were compared between original and simplified responses using paired t tests. McNemar test was used to compare the proportion of responses with adequate reading ease (score of 60 or greater) and readability (sixth-grade level). Results ChatGPT improved mean reading ease (original responses, 46 vs simplified responses, 70; P < .001) and readability (original, grade 13 vs simplified, grade 8.9; P < .001) and decreased word count (original, 193 vs simplified, 173; P < .001). Ninety-two percent (23 of 25) of simplified responses were considered clinically appropriate. All 25 (100%) simplified responses met criteria for adequate reading ease, compared with only two of 25 original responses (P < .001). Two of the 25 simplified responses (8%) met criteria for adequate readability. Conclusion ChatGPT simplified answers to common breast cancer screening and prevention questions by improving the readability by four grade levels, though the potential to produce incorrect information necessitates physician oversight when using this tool. Keywords: Mammography, Screening, Informatics, Breast, Education, Health Policy and Practice, Oncology, Technology Assessment Supplemental material is available for this article. © RSNA, 2023.

A faculty-led resident strike team as a force expander during disaster.

The emergence of the coronavirus disease 2019 (COVID-19) pandemic produced an unprecedented strain on the United States medical system. Prior to the pandemic, there was an estimated 20,000 physician shortage. This has been further stressed by physicians falling ill and the increased acuity of the COVID-19 patients. Federal medical team availability was stretched to its capabilities with the large numbers of deployments. With such severe staffing shortages, creative ways of force expansion were undertaken. New Orleans, Louisiana, was one of the hardest hit areas early in the pandemic. As the case counts built, a call was put out for help. The Louisiana State University (LSU) system responded with a faculty-led resident strike team out of the LSU Health Shreveport Academic Medical Center. Residents and faculty alike volunteered, forming a multispecialty, attending-led medical strike team of approximately 10 physicians. Administrative aspects such as institution-specific credentialing, malpractice coverage, resident distribution, attending physician oversight, among other aspects were addressed, managed, and agreed upon between the LSU Health Shreveport and the New Orleans hospital institutions and leadership prior to deployment in April 2020. In New Orleans, the residents managed patients within the departments of emergency medicine, medical floor, and intensive care unit (ICU). The residents assigned to the medical floor became a new hospitalist service team. The diversity of specialties allowed the team to address patient care in a multidisciplinary manner, leading to comprehensive patient care plans and unhindered team dynamic and workflow. During the first week alone, the team admitted and cared for over 100 patients combined from the medical floor and ICU. In a disaster situation compounded by staff shortages, a resident strike team is a beneficial solution for force expansion. This article qualitatively reviews the first published incidence of a faculty-led multispecialty resident strike team being used as a force expander in a disaster.

Evaluating the Accuracy of ChatGPT and Google BARD in Fielding Oculoplastic Patient Queries: A Comparative Study on Artificial versus Human Intelligence.

This study evaluates and compares the accuracy of responses from 2 artificial intelligence platforms to patients' oculoplastics-related questions. Questions directed toward oculoplastic surgeons were collected, rephrased, and input independently into ChatGPT-3.5 and BARD chatbots, using the prompt: "As an oculoplastic surgeon, how can I respond to my patient's question?." Responses were independently evaluated by 4 experienced oculoplastic specialists as comprehensive, correct but inadequate, mixed correct and incorrect/outdated data, and completely incorrect. Additionally, the empathy level, length, and automated readability index of the responses were assessed. A total of 112 patient questions underwent evaluation. The rates of comprehensive, correct but inadequate, mixed, and completely incorrect answers for ChatGPT were 71.4%, 12.9%, 10.5%, and 5.1%, respectively, compared with 53.1%, 18.3%, 18.1%, and 10.5%, respectively, for BARD. ChatGPT showed more empathy (48.9%) than BARD (13.2%). All graders found that ChatGPT outperformed BARD in question categories of postoperative healing, medical eye conditions, and medications. Categorizing questions by anatomy, ChatGPT excelled in answering lacrimal questions (83.8%), while BARD performed best in the eyelid group (60.4%). ChatGPT's answers were longer and potentially more challenging to comprehend than BARD's. This study emphasizes the promising role of artificial intelligence-powered chatbots in oculoplastic patient education and support. With continued development, these chatbots may potentially assist physicians and offer patients accurate information, ultimately contributing to improved patient care while alleviating surgeon burnout. However, it is crucial to highlight that artificial intelligence may be good at answering questions, but physician oversight remains essential to ensure the highest standard of care and address complex medical cases.

Health outcomes and provider choice under full practice authority for certified nurse-midwives

Full practice authority grants non-physician providers the ability to manage patient care without physician oversight or direct collaboration. In this study, we consider whether full practice authority for certified nurse-midwives (CNMs/CMs) leads to changes in health outcomes or CNM/CM use. Using U.S. birth certificate and death certificate records over 2008–2019, we show that CNM/CM full practice authority led to little change in obstetric outcomes, maternal mortality, or neonatal mortality. Instead, full practice authority increases (reported) CNM/CM-attended deliveries by one percentage point while decreasing (reported) physician-attended births. We then explore the mechanisms behind the increase in CNM/CM-attended deliveries, demonstrating that the rise in CNM/CM-attended deliveries represents higher use of existing CNM/CMs and is not fully explainable by improved reporting of CNM/CM deliveries or changes in CNM/CM labor supply.

Most Patients With Bone Sarcomas Seek Emotional Support and Information About Other Patients' Experiences: A Thematic Analysis.

Online discussion forums allow individuals who otherwise may be strangers to create a community where they can seek and share information. Patients with bone sarcomas and their support networks use discussion forums dedicated to cancer support. There is a paucity of published reports regarding the care experience of patients with bone sarcomas because studies on online discussion groups have primarily focused on some of the more common cancers, including breast and prostate cancer. Understanding commonly discussed themes among patients with bone sarcomas would allow treating physicians to have a better understanding of patient concerns when providing patient education and counseling. We performed this study to review posts from bone sarcoma internet discussion boards to establish common themes related to the care experience of patients with sarcomas. Online discussion forums were identified using the search term "sarcoma discussion forum." After identifying 12 websites, we excluded closed forum groups, websites with missing or invalid links to forums, and nonpublic forums, such as groups on Facebook. These websites include profiles and photos that are personal, and sufficient author anonymity could not be achieved for this study. Posts written between January 1, 2012, and May 1, 2022, posted on five discussion boards were reviewed and collected until we reached a point of data saturation in which we agreed that the collection of additional posts would not reveal new themes. Discussion threads were filtered to identify posts pertaining to the most common bone sarcomas: chondrosarcoma, Ewing sarcoma, and osteosarcoma. Grounded theory-the methodology of repeated analyses of qualitative data to identify recurring themes or concepts-was used to analyze posts. Caregiver posts were delineated from patient posts and categorized separately for subgroup analysis. Grounded theory, although a qualitative method, endeavors to integrate the strengths inherent in quantitative methods with qualitative approaches. Grounded theory categorizes words, language, and the meanings these imply and seeks to organize and reduce the data gathered into themes or essences, which, in turn, can be fed into descriptions, models, or theories. Our analysis used three reviews of text to assign and group codes based on repeating ideas or concepts. The first review (open coding) aims to assign codes based on the verbatim text included by the author to capture the specific thoughts and ideas of the post. The second review (axial coding) aims to consolidate the ideas of posts by applying broader concepts to each post. The third and final review (selective coding) aims to further consolidate the themes of each post by trying to embody the main message contained in a post. A total of 570 posts from 139 threads were collected and analyzed using grounded theory. Twenty-five axial codes and four selective codes were created. We defined data saturation by the absence of a new open code in the analysis of a block of 50 posts to ensure that signals of saturation were not accepted too early in the analysis. The four selective codes included emotional aspects or connecting with others, information support: diagnosis, information support: treatment, and information support: recovery. Of these four codes, emotional aspects and connecting with others was the most prevalent theme (78% [445 of 570] of posts) followed by information support: treatment (49% [282 of 570] of posts). Information support: diagnosis and information support: recovery were each captured in 15% of posts. Analysis of posts reveals that the two most common themes involve seeking out emotional support and information about the experiences of others with various treatment modalities. Although most of the posts we assessed contained experiential information and emotional support rather than directed medical advice, future studies should assess the accuracy of information shared among online sarcoma forums. Physicians caring for patients with sarcomas should not only address patient concerns related to medical care, but also provide emotional support directly and assist patients by providing resources to peer support outlets, including online discussion forums. Although we cannot ascertain the proportion of patients who use online sites given the anonymity of posts included, these findings suggest common experiential themes across patients with sarcomas outside their doctors' offices. It is important that providers be aware of reputable forums to provide as resources for their patients. The Musculoskeletal Tumor Society may further benefit from endorsing one or more of these forums and providing physician oversight to monitor misinformation.

Penicillin de-labelling in vancouver, British Columbia, Canada: comparison of approaches, outcomes and future directions

BackgroundInaccurate penicillin allergy labels lead to inappropriate antibiotic prescriptions and harmful patient consequences. System-wide efforts are needed to remove incorrect penicillin allergy labels, but more health services research is required on how to best deliver these services.MethodsData was extracted from five hospitals in Vancouver, British Columbia, Canada from October 2018-May 2022. The primary outcomes of this study were to outline de-labelling protocol designs, identify the roles of various healthcare professionals in de-labelling protocols and identify rates of de-labelling penicillin allergies and associated adverse events at various institutions. Our secondary outcome was to describe de-labelling rates for special populations, including pediatric, obstetric and immunocompromised subpopulations. To achieve these outcomes, participating institutions provided their de-labelling protocol designs and data on program participants. Protocols were then compared to find common themes and differences. Furthermore, adverse events were reviewed and percentages of patients de-labelled at each institution and in total were calculated.ResultsProtocols demonstrated a high level of variability, including different methods of participant identification, risk-stratification and roles of providers. All protocols used oral and direct oral challenges, heavily involved pharmacists and had physician oversight. Despite the differences, of the 711 patients enrolled in all programs, 697 (98.0%) were de-labelled. There were 9 adverse events (1.3%) with oral challenges with mainly minor symptoms.ConclusionsOur data demonstrates that de-labelling programs effectively and safely remove penicillin allergy labels, including pediatric, obstetric and immunocompromised patients. Consistent with current literature, most patients with a penicillin allergy label are not allergic. De-labelling programs could benefit from increasing clinician engagement by increasing accessibility of resources to providers, including guidance for de-labelling of special populations.

Physician-patient boundaries in palliative care

BackgroundNurturing effective physician-patient relationships is essential to the provision of patient-centred care. Palliative care physicians may apply boundary-crossings or breaches in professional standards to nurture effective physician-patient relationships. Being highly individualized and shaped by the physician’s narratives, clinical experience, and contextual considerations, boundary-crossings are susceptible to ethical and professional violations. To better appreciate this concept, we employ the Ring Theory of Personhood (RToP) to map the effects of boundary-crossings on the physician’s belief systems.MethodsAs part of the Tool Design SEBA methodology, a Systematic Evidence-Based Approach (SEBA) guided systematic scoping review was employed to guide the design of a semi-structured interview questionnaire with palliative care physicians. The transcripts were simultaneously content and thematically analysed. The themes and categories identified were combined using the Jigsaw Perspective and the resulting domains formed the basis for the discussion.ResultsThe domains identified from the 12 semi-structured interviews were catalysts and boundary-crossings. Boundary-crossings attempt to address threats to a physician’s belief systems (catalysts) and are highly individualized. Employ of boundary-crossings depend on the physician’s sensitivity to these ‘catalysts’, their judgement and willingness to act, and their ability to balance various considerations and reflect on their actions and their ramifications. These experiences reshape belief systems, understandings of boundary-crossings and may influence decision-making and practice, underscoring the potential for greater professional breaches when unchecked.ConclusionUnderlining its longitudinal effects, the Krishna Model underscores the importance of longitudinal support, assessment and oversight of palliative care physicians, and lays the foundation for a RToP-based tool to be employed within portfolios.

Mobile Integrated Health Interventions for Older Adults: A Systematic Review.

Mobile integrated health (MIH) interventions have not been well described in older adult populations. The objective of this systematic review was to evaluate the characteristics and effectiveness of MIH programs on health-related outcomes among older adults. We searched Ovid MEDLINE, Ovid EMBASE, CINAHL, AgeLine, Social Work Abstracts, and The Cochrane Library through June 2021 for randomized controlled trials or cohort studies evaluating MIH among adults aged 65 and older in the general community. Studies were screened for eligibility against predefined inclusion/exclusion criteria. Using at least 2 independent reviewers, quality was appraised using the Downs and Black checklist and study characteristics and findings were synthesized and evaluated for potential bias. Screening of 2,160 records identified 15 studies. The mean age of participants was 67 years. The MIH interventions varied in their focus, community paramedic training, types of assessments and interventions delivered, physician oversight, use of telemedicine, and post-visit follow-up. Studies reported significant reductions in emergency call volume (5 studies) and immediate emergency department (ED) transports (3 studies). The 3 studies examining subsequent ED visits and 4 studies examining readmission rates reported mixed results. Studies reported low adverse event rates (5 studies), high patient and provider satisfaction (5 studies), and costs equivalent to or less than usual paramedic care (3 studies). There is wide variability in MIH provider training, program coordination, and quality-based metrics, creating heterogeneity that make definitive conclusions challenging. Nonetheless, studies suggest MIH reduces emergency call volume and ED transport rates while improving patient experience and reducing overall health care costs.

Delegation and oversight of non-physician practitioners in dermatology.

A rising demand for dermatologic procedures has led to a recent increase in the number of non-physician operators (NPOs) in the dermatology workforce. Nurse practitioners, physician assistants, and aestheticians commonly perform procedures in both physician-based practices and medical spas with varying degrees of dermatology-specific training and physician oversight. Although the lack of regulations can negatively impact patient outcomes and adverse events, the role of NPOs in dermatology continues to grow. Among Medicare beneficiaries, nurse practitioners and physician assistants are independently billing for a growing number of dermatologic procedures, whereas the number performed by dermatologists remains relatively stable. Medical spas are an increasingly popular destination for aesthetic consumers, and the majority employ only NPOs as primary providers. Recent data suggest that compared to dermatologists, NPOs have a higher rate of adverse events. As attempts are made to standardize and improve the training requirements for dermatologic procedures, a concerted effort should be made to prioritize patient outcomes and safety.