Physician Workforce Disparities and Patient Care: A Narrative Review.

Background: Ensuring the strength of the physician workforce is essential to optimizing patient care. Challenges that undermine the profession include inequities in advancement, high levels of burnout, reduced career duration, and elevated risk for mental health problems, including suicide. This narrative review explores whether physicians within four subpopulations represented in the workforce at levels lower than predicted from their numbers in the general population-women, racial and ethnic minorities in medicine, sexual and gender minorities, and people with disabilities-are at elevated risk for these problems, and if present, how these problems might be addressed to support patient care. In essence, the underlying question this narrative review explores is as follows: Do physician workforce disparities affect patient care? While numerous articles and high-profile reports have examined the relationship between workforce diversity and patient care, to our knowledge, this is the first review to examine the important relationship between diversity-related workforce disparities and patient care. Methods: Five databases (PubMed, the Cochrane Library of Systematic Reviews, EMBASE, Web of Knowledge, and EBSCO Discovery Service) were searched by a librarian. Additional resources were included by authors, as deemed relevant to the investigation. Results: The initial database searches identified 440 potentially relevant articles. Articles were categorized according to subtopics, including (1) underrepresented physicians and support for vulnerable patient populations; (2) factors that could exacerbate the projected physician deficit; (3) methods of addressing disparities among underrepresented physicians to support patient care; or (4) excluded (n=155). The authors identified another 220 potentially relevant articles. Of 505 potentially relevant articles, 199 (39.4%) were included in this review. Conclusions: This report demonstrates an important gap in the literature regarding the impact of physician workforce disparities and their effect on patient care. This is a critical public health issue and should be urgently addressed in future research and considered in clinical practice and policy decision-making.

Fast Healthcare Interoperability Resources, Clinical Quality Language, and Systematized Nomenclature of Medicine-Clinical Terms in Representing Clinical Evidence Logic Statements for the Use of Imaging Procedures: Descriptive Study.

BACKGROUND: Evidence-based guidelines and recommendations can be transformed into "If-Then" Clinical Evidence Logic Statements (CELS). Imaging-related CELS were represented in standardized formats in the Harvard Medical School Library of Evidence (HLE). OBJECTIVE: We aimed to (1) describe the representation of CELS using established Systematized Nomenclature of Medicine-Clinical Terms (SNOMED CT), Clinical Quality Language (CQL), and Fast Healthcare Interoperability Resources (FHIR) standards and (2) assess the limitations of using these standards to represent imaging-related CELS. METHODS: This study was exempt from review by the Institutional Review Board as it involved no human subjects. Imaging-related clinical recommendations were extracted from evidence sources and translated into CELS. The clinical terminologies of CELS were represented using SNOMED CT and the condition-action logic was represented in CQL and FHIR. Numbers of fully and partially represented CELS were tallied. RESULTS: A total of 765 CELS were represented in the HLE as of December 2018. We were able to fully represent 137 of 765 (17.9%) CELS using SNOMED CT, CQL, and FHIR. We were able to represent terms using SNOMED CT in the temporal component for action ("Then") statements in CQL and FHIR in 755 of 765 (98.7%) CELS. CONCLUSIONS: CELS were represented as shareable clinical decision support (CDS) knowledge artifacts using existing standards-SNOMED CT, FHIR, and CQL-to promote and accelerate adoption of evidence-based practice. Limitations to standardization persist, which could be minimized with an add-on set of standard terms and value sets and by adding time frames to the CQL framework.

Comorbidity of dementia and age-related macular degeneration calls for clinical awareness: a meta-analysis.

AIM: To determine the association between dementia and age-related macular degeneration (AMD) using meta-analysis. METHODS: We searched in the MEDLINE, EMBASE, Web of Knowledge, PsycInfo and Cochrane database of systematic reviews for studies published from March 1959 to March 2018. We included cross-sectional, case-control and cohort studies that evaluated the association of dementia/Alzheimer's disease (AD) with AMD (as outcome) and the association of AMD with dementia/AD (as outcome). Studies that compared cognitive functions between AMD and controls were also included. The summary outcomes, namely odds ratio (OR), relative risk, mean differences and corresponding 95% CIs, were estimated using random effects models. We performed sensitivity analysis based on study quality and individual study effect to control for potential biases. RESULTS: Among 2159 citation records, we identified 21 studies consisting of 7 876 499 study subjects for meta-analysis. Patients with dementia (padjusted≤0.017, OR≥1.24, I2≤9%) or AD (p=0.001, ORunadjusted=2.22, I2=50%) were at risk for AMD, particularly for late AMD (padjusted<0.001, OR=1.37, I2=0). AMD was also significantly associated with increased risk of AD/cognitive impairment (padjusted=0.037, OR=2.42, I2=38%). Moreover, patients with AMD had poorer cognitive functions when compared with controls, including Mini-Mental State Examination (p<0.001, I2≤79%) and Trail Making Test A (p<0.001, I2=0). Sensitivity analysis and Egger's test indicated our results were less likely biased. CONCLUSIONS: A significant association between dementia/AD and AMD calls for greater clinical awareness. The cost-effectiveness of routine screening for the other condition in patients with primary diagnosis of dementia/AD or AMD requires further study.

Characteristics of knowledge content in a curated online evidence library.

Objective: To describe types of recommendations represented in a curated online evidence library, report on the quality of evidence-based recommendations pertaining to diagnostic imaging exams, and assess underlying knowledge representation. Materials and Methods: The evidence library is populated with clinical decision rules, professional society guidelines, and locally developed best practice guidelines. Individual recommendations were graded based on a standard methodology and compared using chi-square test. Strength of evidence ranged from grade 1 (systematic review) through grade 5 (recommendations based on expert opinion). Finally, variations in the underlying representation of these recommendations were identified. Results: The library contains 546 individual imaging-related recommendations. Only 15% (16/106) of recommendations from clinical decision rules were grade 5 vs 83% (526/636) from professional society practice guidelines and local best practice guidelines that cited grade 5 studies (P < .0001). Minor head trauma, pulmonary embolism, and appendicitis were topic areas supported by the highest quality of evidence. Three main variations in underlying representations of recommendations were "single-decision," "branching," and "score-based." Discussion: Most recommendations were grade 5, largely because studies to test and validate many recommendations were absent. Recommendation types vary in amount and complexity and, accordingly, the structure and syntax of statements they generate. However, they can be represented in single-decision, branching, and score-based representations. Conclusion: In a curated evidence library with graded imaging-based recommendations, evidence quality varied widely, with decision rules providing the highest-quality recommendations. The library may be helpful in highlighting evidence gaps, comparing recommendations from varied sources on similar clinical topics, and prioritizing imaging recommendations to inform clinical decision support implementation.

Assessing Strength of Evidence of Appropriate Use Criteria for Diagnostic Imaging Examinations.

OBJECTIVE: For health information technology tools to fully inform evidence-based decisions, recommendations must be reliably assessed for quality and strength of evidence. We aimed to create an annotation framework for grading recommendations regarding appropriate use of diagnostic imaging examinations. METHODS: The annotation framework was created by an expert panel (clinicians in three medical specialties, medical librarians, and biomedical scientists) who developed a process for achieving consensus in assessing recommendations, and evaluated by measuring agreement in grading the strength of evidence for 120 empirically selected recommendations using the Oxford Levels of Evidence. RESULTS: Eighty-two percent of recommendations were assigned to Level 5 (expert opinion). Inter-annotator agreement was 0.70 on initial grading (κ = 0.35, 95% CI, 0.23-0.48). After systematic discussion utilizing the annotation framework, agreement increased significantly to 0.97 (κ = 0.88, 95% CI, 0.77-0.99). CONCLUSIONS: A novel annotation framework was effective for grading the strength of evidence supporting appropriate use criteria for diagnostic imaging exams.

Evaluating Terminologies to Enable Imaging-Related Decision Rule Sharing.

Purpose: Clinical decision support tools provide recommendations based on decision rules. A fundamental challenge regarding decision rule-sharing involves inadequate expression using standard terminology. We aimed to evaluate the coverage of three standard terminologies for mapping imaging-related decision rules. Methods: 50 decision rules, randomly selected from an existing library, were mapped to Systemized Nomenclature of Medicine (SNOMED CT), Radiology Lexicon (RadLex) and International Classification of Disease (ICD-10-CM). Decision rule attributes and values were mapped to unique concepts, obtaining the best possible coverage with the fewest concepts. Manual and automated mapping using Clinical Text Analysis and Knowledge Extraction System (cTAKES) were performed. Results: Using manual mapping, SNOMED CT provided the greatest concept coverage (83%), compared to RadLex (36%) and ICD-10-CM (8%) (p<0.0001). Combined mapping had 86% concept coverage. Automated mapping achieved 85% mapping coverage vs. 94% with manual mapping (p<0.001). Conclusion: Although some gaps remain, standard terminologies provide ample coverage for mapping imaging- related evidence.

Vignettes: Diverse library staff offering diverse bioinformatics services.

OBJECTIVES: The paper gives examples of the bioinformatics services provided in a variety of different libraries by librarians with a broad range of educational background and training. METHODS: Two investigators sent an email inquiry to attendees of the "National Center for Biotechnology Information's (NCBI) Introduction to Molecular Biology Information Resources" or "NCBI Advanced Workshop for Bioinformatics Information Specialists (NAWBIS)" courses. The thirty-five-item questionnaire addressed areas such as educational background, library setting, types and numbers of users served, and bioinformatics training and support services provided. Answers were compiled into program vignettes. DISCUSSION: The bioinformatics support services addressed in the paper are based in libraries with academic and clinical settings. Services have been established through different means: in collaboration with biology faculty as part of formal courses, through teaching workshops in the library, through one-on-one consultations, and by other methods. Librarians with backgrounds from art history to doctoral degrees in genetics have worked to establish these programs. CONCLUSION: Successful bioinformatics support programs can be established in libraries in a variety of different settings and by staff with a variety of different backgrounds and approaches.

Carving a niche: establishing bioinformatics collaborations.

OBJECTIVES: The paper describes collaborations and partnerships developed between library bioinformatics programs and other bioinformatics-related units at four academic institutions. METHODS: A call for information on bioinformatics partnerships was made via email to librarians who have participated in the National Center for Biotechnology Information's Advanced Workshop for Bioinformatics Information Specialists. Librarians from Harvard University, the University of Florida, the University of Minnesota, and Vanderbilt University responded and expressed willingness to contribute information on their institutions, programs, services, and collaborating partners. Similarities and differences in programs and collaborations were identified. RESULTS: The four librarians have developed partnerships with other units on their campuses that can be categorized into the following areas: knowledge management, instruction, and electronic resource support. All primarily support freely accessible electronic resources, while other campus units deal with fee-based ones. These demarcations are apparent in resource provision as well as in subsequent support and instruction. CONCLUSIONS AND RECOMMENDATIONS: Through environmental scanning and networking with colleagues, librarians who provide bioinformatics support can develop fruitful collaborations. Visibility is key to building collaborations, as is broad-based thinking in terms of potential partners.