Types Of Clinical Questions Research Articles

Common Ground: Primary Care and Specialty Clinicians' Perceptions of E-Consults in the Veterans Health Administration.

The US Department of Veterans Affairs (VA) introduced electronic consultation (e-consult) to increase access to specialty care. The objective of this study was to understand perceptions of e-consults that may be relevant to increasing adoption in the VA. Deductive and inductive content analysis of semistructured qualitative telephone interviews with VA primary care practitioners (PCPs), specialists, and specialty division chiefs was performed. Participants were identified based on rates of e-consult in 2016 at the individual and facility level within primary care, hematology, cardiology, gastroenterology, and endocrinology. Interview guide development was informed by the Practical, Robust, Implementation, and Sustainability (PRISM) framework. We interviewed 35 PCPs and 25 specialists working in 36 facilities. Four themes emerged across both PCPs and specialists: (1) e-consults are best suited for certain types of clinical questions; (2) high-quality e-consults include complete background information from the requesting clinician and clear diagnostic or treatment recommendations from the responding clinician; (3) PCPs and specialists perceive e-consults as a novel opportunity to provide efficient, transparent care; and (4) lack of awareness of e-consults hinders adoption despite obvious benefits. We identified themes that are informative for further adoption of high-quality e-consults in the VA. Educating PCPs and specialty practitioners about the benefits of e-consults, and providing support, such as lists of specialties available for e-consults at the facility are 2 such practices.

Semantic Deep Learning: Prior Knowledge and a Type of Four-Term Embedding Analogy to Acquire Treatments for Well-Known Diseases.

BackgroundHow to treat a disease remains to be the most common type of clinical question. Obtaining evidence-based answers from biomedical literature is difficult. Analogical reasoning with embeddings from deep learning (embedding analogies) may extract such biomedical facts, although the state-of-the-art focuses on pair-based proportional (pairwise) analogies such as man:woman::king:queen (“queen = −man +king +woman”).ObjectiveThis study aimed to systematically extract disease treatment statements with a Semantic Deep Learning (SemDeep) approach underpinned by prior knowledge and another type of 4-term analogy (other than pairwise).MethodsAs preliminaries, we investigated Continuous Bag-of-Words (CBOW) embedding analogies in a common-English corpus with five lines of text and observed a type of 4-term analogy (not pairwise) applying the 3CosAdd formula and relating the semantic fields person and death: “dagger = −Romeo +die +died” (search query: −Romeo +die +died). Our SemDeep approach worked with pre-existing items of knowledge (what is known) to make inferences sanctioned by a 4-term analogy (search query −x +z1 +z2) from CBOW and Skip-gram embeddings created with a PubMed systematic reviews subset (PMSB dataset). Stage1: Knowledge acquisition. Obtaining a set of terms, candidate y, from embeddings using vector arithmetic. Some n-gram pairs from the cosine and validated with evidence (prior knowledge) are the input for the 3cosAdd, seeking a type of 4-term analogy relating the semantic fields disease and treatment. Stage 2: Knowledge organization. Identification of candidates sanctioned by the analogy belonging to the semantic field treatment and mapping these candidates to unified medical language system Metathesaurus concepts with MetaMap. A concept pair is a brief disease treatment statement (biomedical fact). Stage 3: Knowledge validation. An evidence-based evaluation followed by human validation of biomedical facts potentially useful for clinicians.ResultsWe obtained 5352 n-gram pairs from 446 search queries by applying the 3CosAdd. The microaveraging performance of MetaMap for candidate y belonging to the semantic field treatment was F-measure=80.00% (precision=77.00%, recall=83.25%). We developed an empirical heuristic with some predictive power for clinical winners, that is, search queries bringing candidate y with evidence of a therapeutic intent for target disease x. The search queries -asthma +inhaled_corticosteroids +inhaled_corticosteroid and -epilepsy +valproate +antiepileptic_drug were clinical winners, finding eight evidence-based beneficial treatments.ConclusionsExtracting treatments with therapeutic intent by analogical reasoning from embeddings (423K n-grams from the PMSB dataset) is an ambitious goal. Our SemDeep approach is knowledge-based, underpinned by embedding analogies that exploit prior knowledge. Biomedical facts from embedding analogies (4-term type, not pairwise) are potentially useful for clinicians. The heuristic offers a practical way to discover beneficial treatments for well-known diseases. Learning from deep learning models does not require a massive amount of data. Embedding analogies are not limited to pairwise analogies; hence, analogical reasoning with embeddings is underexploited.

Clinical Screening Interview Using a Social Robot for Geriatric Care

Social robots are coming to our homes and have already been used to help humans in a number of ways in geriatric care. This article aims to develop a framework that enables social robots to conduct regular clinical screening interviews in geriatric care, such as cognitive evaluation, falls’ risk evaluation, and pain rating. We develop a social robot with essential features to enable clinical screening interviews, including a conversational interface, face tracking, an interaction handler, attention management, robot skills, and cloud service management. Besides, a general clinical screening interview management (GCSIM) model is proposed and implemented. The GCSIM enables social robots to handle various types of clinical questions and answers, evaluate and score responses, engage interviewees during conversations, and generate reports on their well-being. These reports can be used to evaluate the progression of cognitive impairment, risk of falls, pain level, and so on by caregivers or physicians. Such a clinical screening capability allows for early detection and treatment planning in geriatric care. The framework was developed and implemented on our 3-D-printed social robot. It was tested on 30 older adults with different ages, achieved satisfying results, and received their high confidence and trust in the use of this robot for human well-being assessment. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —This article is motivated by the goal of using a social robot to perform geriatric well-being assessment through clinical screening interviews. In order to conduct clinical screening interviews, the social robot needs the following essential features: having a verbal conversational interface, adapting to different types of clinical screening interviews, scoring and evaluating answers, having nondirective listening responses, and enabling directive listening responses. The proposed general clinical screening interview management (GCSIM) model demonstrates these capabilities on the social robot. The robot can give structured clinical screening interviews with different question–answer sheets. This will help advance assistive technologies for use by geriatric physicians, nurses, and social service professionals to keep older adults healthy, safe, and independent at home. Robots will become more and more essential in working alongside geriatric practitioners to help monitor older adults at home and to provide early detection and warning of cognitive/mental health problems, falls’ risk, and so on. This early detection property can improve quality-of-care and help older adults remain living at home.

Electronic Consultation Systems: Impact on Pediatric Orthopaedic Care

The demand for pediatric orthopaedic surgery consultation has grown rapidly, leading to longer wait times for elective consultation in some regions. Some specialties are addressing this increased demand through electronic consultation services. We wanted to examine the impact of pediatric orthopaedic e-consultations in Canada's Eastern Ontario region. We developed a cross-sectional study of all the cases directed to a pediatric orthopaedic surgery specialist using the Champlain Building Access to Specialists through eConsultation (BASE) eConsult service over a 2-year period and examined their impact on in-person referrals, time of e-consultation and primary care satisfaction as well as types of clinical questions that were asked. Electronic consultations avoided in-person appointments in 68% of the submitted cases. The median response by specialists received by the primary care providers (PCPs) was <20 hours. A total of 69% of consultations involve >1 type of clinical questions, most commonly about basic trauma/fracture care and management recommendations. Ninety-seven percent of the PCPs found the overall value for the care of the patients to be good or excellent. This cross-sectional study demonstrates the effective and timely use of eConsult in pediatric orthopaedic surgery. It also shows a significant reduction in the number of in-person consultations required and demonstrates a high satisfaction rate by PCPs using the service. In addition to the efficacy and time-sensitive care provided to the patients, the study shows that, professionally, 89% of PCPs found this service to be excellent or good. The broader implications of electronic consultation on overall quality of care, population health, and patient satisfaction requires further investigation.

Classifying Electronic Consults for Triage Status and Question Type.

Electronic consult (eConsult) systems allow specialists more flexibility to respond to referrals more efficiently, thereby increasing access in under-resourced healthcare settings like safety net systems. Understanding the usage patterns of eConsult system is an important part of improving specialist efficiency. In this work, we develop and apply classifiers to a dataset of eConsult questions from primary care providers to specialists, classifying the messages for how they were triaged by the specialist office, and the underlying type of clinical question posed by the primary care provider. We show that pre-trained transformer models are strong baselines, with improving performance from domain-specific training and shared representations.

Assessing Abnormal Uterine Bleeding: Are Physicians Taking a Meaningful Clinical History?

Women with abnormal uterine bleeding (AUB) report significant reductions in quality of life (QOL), which can be attributed in many cases to the fear of embarrassing episodes of bleeding. We performed this study to determine whether or not during clinical encounters physicians addressed the impact of AUB on patient-reported QOL. Between October 2008 and May 2009, we conducted a cross-sectional study of members of the American College of Obstetricians and Gynecologists. Surveys were distributed using a mixed method (web- and mail-based) and included questions about physician characteristics and types of questions used when obtaining a clinical history from a patient with AUB. We calculated the proportion of physicians who endorsed asking each type of clinical question with 95% confidence intervals (CIs). Four hundred seventeen questionnaires were returned (52%). Ninety-nine percent (95% CI 98.4%-99.9%) reported always asking a bleeding heaviness question, 87.2% (95% CI 83.2%-90.5%) reported always asking a QOL question, and 17.5% (95% CI 13.6%-21.9%) reported always asking a mood associated with bleeding question. Seventy-eight percent specifically asked patients about bleeding through their clothes, and 55% asked about changing social plans because of bleeding. Only 18% endorsed that asking about QOL was most essential for the evaluation of women with AUB. No physician characteristics such as years since completing residency, geography, or gender were associated with how commonly providers reported asking questions regarding impact of bleeding on QOL. Physicians may not be optimizing patient-provider interactions during menstrual history taking with patients with AUB by failing to assess impact of AUB on QOL in a way that is meaningful to patients.

Searching CINAHL did not add value to clinical questions posed in NICE guidelines

ObjectivesThis study aims to quantify the unique useful yield from the Cumulative Index to Nursing and Allied Health Literature (CINAHL) database to National Institute for Health and Clinical Excellence (NICE) clinical guidelines. A secondary objective is to investigate the relationship between this yield and different clinical question types. It is hypothesized that the unique useful yield from CINAHL is low, and this database can therefore be relegated to selective rather than routine searching. Study Design and SettingA retrospective sample of 15 NICE guidelines published between 2005 and 2009 was taken. Information on clinical review question type, number of references, and reference source was extracted. ResultsOnly 0.33% (95% confidence interval: 0.01–0.64%) of references per guideline were unique to CINAHL. Nursing- or allied health (AH)–related questions were nearly three times as likely to have references unique to CINAHL as non–nursing- or AH-related questions (14.89% vs. 5.11%), and this relationship was found to be significant (P<0.05). No significant relationship was found between question type and unique CINAHL yield for drug-related questions. ConclusionsThe very low proportion of references unique to CINAHL strongly suggests that this database can be safely relegated to selective rather than routine searching. Nursing- and AH-related questions would benefit from selective searching of CINAHL.

Evidence level of individual studies

Evidence level of individual studies

Impact of Patient Selection in Various Study Designs

Many different study designs are used to address different types of clinical questions. The two broad categories are the experimental study, which is the randomized controlled trial, and observational studies, which includes all of the other basic study designs (cohort [prospective and retrospective] studies, case-control [etiologic] studies, cross-sectional [prevalence] studies, case series, and case reports). These study designs address basic categories of clinical questions: treatment, diagnosis, prognosis, and harm. This article focuses on some of these study designs, highlighting the impact of patient selection, inclusion, and exclusion criteria on results and outcomes through the use of specific examples.

Comparative evaluation of web search engines in health information retrieval

PurposeThe intent of this work is to evaluate several generalist and health‐specific search engines for retrieval of health information by consumers: to compare the retrieval effectiveness of these engines for different types of clinical queries, medical specialties and condition severity; and to compare the use of evaluation metrics for binary relevance scales and for graded ones.Design/methodology/approachThe authors conducted a study in which users evaluated the relevance of documents retrieved by four search engines for two different health information needs. Users could choose between generalist (Bing, Google, Sapo and Yahoo!) and health‐specific (MedlinePlus, SapoSaúde and WebMD) search engines. The authors then analysed the differences between search engines and groups of information needs with six different measures: graded average precision (gap), average precision (ap), gap@5, gap@10, ap@5 and ap@10.FindingsThe results show that generalist web search engines surpass the precision of health‐specific engines. Google has the best performance, mainly in the top ten results. It was found that information needs associated with severe conditions are associated with higher precision, as are overview and psychiatry questions.Originality/valueThe study is one of the first to use a recently proposed measure to evaluate the effectiveness of retrieval systems with graded relevance scales. It includes tasks from several medical specialties, types of clinical questions and different levels of severity which, to the best of the authors' knowledge, has not been done before. Moreover, users have considerable involvement in the experiment. The results help in understanding how search engines differ in their responses to health information needs, what types of online health information are more common on the web and how to improve this type of search.

Extending an evidence hierarchy to include topics other than treatment: revising the Australian 'levels of evidence'

BackgroundIn 1999 a four-level hierarchy of evidence was promoted by the National Health and Medical Research Council in Australia. The primary purpose of this hierarchy was to assist with clinical practice guideline development, although it was co-opted for use in systematic literature reviews and health technology assessments. In this hierarchy interventional study designs were ranked according to the likelihood that bias had been eliminated and thus it was not ideal to assess studies that addressed other types of clinical questions. This paper reports on the revision and extension of this evidence hierarchy to enable broader use within existing evidence assessment systems.MethodsA working party identified and assessed empirical evidence, and used a commissioned review of existing evidence assessment schema, to support decision-making regarding revision of the hierarchy. The aim was to retain the existing evidence levels I-IV but increase their relevance for assessing the quality of individual diagnostic accuracy, prognostic, aetiologic and screening studies. Comprehensive public consultation was undertaken and the revised hierarchy was piloted by individual health technology assessment agencies and clinical practice guideline developers. After two and a half years, the hierarchy was again revised and commenced a further 18 month pilot period.ResultsA suitable framework was identified upon which to model the revision. Consistency was maintained in the hierarchy of "levels of evidence" across all types of clinical questions; empirical evidence was used to support the relationship between study design and ranking in the hierarchy wherever possible; and systematic reviews of lower level studies were themselves ascribed a ranking. The impact of ethics on the hierarchy of study designs was acknowledged in the framework, along with a consideration of how harms should be assessed.ConclusionThe revised evidence hierarchy is now widely used and provides a common standard against which to initially judge the likelihood of bias in individual studies evaluating interventional, diagnostic accuracy, prognostic, aetiologic or screening topics. Detailed quality appraisal of these individual studies, as well as grading of the body of evidence to answer each clinical, research or policy question, can then be undertaken as required.

Numerical modelling of the shoulder for clinical applications

Research activity involving numerical models of the shoulder is dramatically increasing, driven by growing rates of injury and the need to better understand shoulder joint pathologies to develop therapeutic strategies. Based on the type of clinical question they can address, existing models can be broadly categorized into three groups: (i) rigid body models that can simulate kinematics, collisions between entities or wrapping of the muscles over the bones, and which have been used to investigate joint kinematics and ergonomics, and are often coupled with (ii) muscle force estimation techniques, consisting mainly of optimization methods and electromyography-driven models, to simulate muscular action and joint reaction forces to address issues in joint stability, muscular rehabilitation or muscle transfer, and (iii) deformable models that account for stress-strain distributions in the component structures to study articular degeneration, implant failure or muscle/tendon/bone integrity. The state of the art in numerical modelling of the shoulder is reviewed, and the advantages, limitations and potential clinical applications of these modelling approaches are critically discussed. This review concentrates primarily on muscle force estimation modelling, with emphasis on a novel muscle recruitment paradigm, compared with traditionally applied optimization methods. Finally, the necessary benchmarks for validating shoulder models, the emerging technologies that will enable further advances and the future challenges in the field are described.

Factors Associated With the Full Publication of Studies Presented in Abstract Form at the Annual Meeting of the American Urological Association

Many abstracts presented at scientific meetings never come to full text publication, which is a prerequisite for the critical appraisal of a given study for its validity, impact and generalizability. We determined factors associated with the publication of abstracts presented at the American Urological Association national meeting. All abstracts addressing clinical research accepted for presentation at the 2002 and 2003 meetings of the American Urological Association were reviewed. A comprehensive MEDLINE search was performed for evidence of publication in full manuscript form. Data abstraction and literature searches were done between June 15 and August 30, 2005. Univariate and multivariate analyses were performed to determine the association between abstract characteristics and time to publication. Of the 1,683 abstracts reviewed 740 (44.0%) were published within a median followup of 27.8 months (range 25.9 to 39.7). Time to publication was associated with abstract origin in the United States and the reporting of statistical testing (HR 1.2, 95% CI 1.0-1.4, p=0.040 and HR 1.2, 95% CI 1.1-1.4, p=0.010, respectively). Other variables, such as presentation type, study design, clinical question type and negative outcome, were not predictive. Nonpublication of research findings is a problematic issue that affects more than half of studies 2 years after presentation at the American Urological Association national meeting. Abstracts from the United States and those providing statistical testing were more likely to be published in full text form. Further efforts are warranted to identify and eliminate factors that hinder publication of research to bring it to the scrutiny of a broad audience of urologists.

Good Research Ideas for Clinicians

While the conduct of nursing research is an important professional value, it is an activity rarely performed by nurses employed in the service setting. Whether the reason is a lack of commitment to a scientific basis for nursing practice or an inability to operationalize the research process in the clinical setting, the outcome is a dearth of clinically relevant studies to guide patient care. Clinicians must be involved in asking and answering clinically relevant questions to maximize patient outcomes. This article provides suggestions to assist clinicians to identify the types of clinical questions that are most likely to result in successful completion of research projects by busy, service-setting clinicians. Strategies are described that will assist clinicians to identify research questions of relevance to their practice areas.