OBJECTIVE: To assess the quality of hydroxychloroquine (HCQ)-induced retinopathy screening at a Canadian tertiary center, we concentrate on risk factor documentation within the electronic health record, in accordance with the 2016 AAO guidelines.
METHODS: We performed a retrospective quality assessment study based on chart review of patients who underwent screening for HCQ-induced retinopathy at the Centre Hospitalier de l\'Université de Montréal (CHUM) from 2016 to 2019. We evaluated four key risk factors for HCQ-induced retinopathy: daily dose, duration of use, renal disease, and tamoxifen use, using a three-tier grading system (ideal, adequate, inadequate) for documentation assessment. Pareto and root cause analyses were conducted to identify potential improvement solutions.
RESULTS: Documentation quality varied in our study: daily dosage was 33% ideal, 31% appropriate, and 36% inappropriate. Duration of use documentation was 75% ideal, 2% adequate, and 24% inadequate. Renal disease documentation was only 6% ideal, with 62% adequate and 32% of charts lacking any past medical history. Among women\'s charts, tamoxifen use wasn\'t documented at all, with 65% adequately documenting medication lists. Pareto analysis indicated that improving renal disease and tamoxifen documentation could reduce 64% of non-ideal records, and enhancing daily dose documentation could decrease this by up to 90%.
CONCLUSIONS: Accurate documentation of key risk factors is critical for HCQ-induced retinopathy screening, impacting both exam initiation and frequency. Our study identifies potential improvements in the screening process at the hospital, referring physician, and ophthalmologist levels. Implementing integrated pathways could enhance patient experience and screening effectiveness.

BACKGROUND: Children with developmental coordination disorder (DCD) show deviations in motor development and motor skills in early childhood where the learning and execution of coordinated motor skills are below the level expected for their age. Early detection of DCD is critical to provide an opportunity for intervention and support, yet many cases remain undetected until school age. The study described aims to determine the warranty, feasibility and validity of a mobility screening in Tyrolean kindergartens and evaluate its potential benefit to enhance the motor development prospects of affected children.
METHODS: This research employs a two-stage cross-sectional approach with 6 months of follow-up assessments. The initial stage involves a playful mobility screening for all participating kindergarten children, followed by individual assessments for those displaying conspicuous motor skills. Motor skills will be evaluated using MobiScreen 4-6 and the Movement Assessment Battery for Children-2. Prior to the screening, informed consent is obtained from kindergarten bodies and authorities, parents and the children themselves. Parents are provided with information sheets and questionnaires to assess their attitudes and their child\'s eligibility. The study described aims to form a representative sample of kindergarten children, aged 4-6, in Tyrol. To target approximately 20-40 children with DCD for follow-up, the goal is to include 650 children, assuming an incidence of 3%-6%. For the follow-up, matching control groups will be formed and information about how identified motor deficits were addressed, including therapies or sports, will be gathered. Quantitative data will mainly be analysed descriptively, while feedback from kindergarten teachers regarding the practical implementation will be analysed using qualitative content analyses, according to Mayring.
BACKGROUND: The study has been approved by the Research Committee for Scientific Ethical Questions (RCSEQ 3369/24). Findings will be disseminated through contributions, peer-reviewed journals, and conferences.

BACKGROUND: Most Japanese medical schools likely continue to rely on peer physical examination (PPE) as a tool to for teaching physical examination skills to students. However, the attitudes of medical students in Japan toward PPEs have not be identified. Therefore, we evaluated students\' attitudes toward PPE in a Japanese medical school as a preparation for developing a PPE policy tailored to the context of Japanese culture.
METHODS: We conducted a mixed-methods study with an explanatory sequential approach, in which qualitative data were used to interpret the quantitative findings. Surveys and interviews were conducted with medical students and junior residents at a Japanese university. A total of 63 medical students and 50 junior residents responded to the questionnaire. We interviewed 16 participants to reach theoretical saturation and investigated the attitudes of medical students toward PPE and the themes emerging from the interview data, providing detailed descriptions of the quantitative findings.
RESULTS: Female participants were significantly more likely than male participants to report varying degrees of resistance to being a model patient during PPE (male: 59.7%, female: 87%, p < 0.001). Most of the participants who took on the role of patients that involved undressing were males. The participants expected improvements in issues related to the guarantee of freedom to refuse to be a model patient and measures to protect confidentiality. Approximately 22% of the participants reported that they witnessed incidental findings (including variations within the normal range) in front of other students during PPE.
CONCLUSIONS: The findings imply that medical students expect high levels of autonomy and confidentiality when volunteering as model patients during PPE. Thus, developing a PPE policy suitable for Japanese culture may be effective in establishing a student-centered PPE environment.

BACKGROUND: UK general practice surgeries collect data regarding patient ethnicities, typically at registration. These data are subsequently used in both clinical care and research, for example, when embedded in risk modelling tools. The published standard list of ethnic categories exists, but little is known about what happens in frontline practice.
OBJECTIVE: To document the variation in ethnic categories available on online patient registration forms across GP surgeries in Oxfordshire.
METHODS: Of all 67 GP surgeries in Oxfordshire, 56 had online registration forms that included an option list for ethnicity reporting. The authors compared these against the 2001, 2011, and 2021 UK census ethnic group categorisation.
RESULTS: Significant heterogeneity was identified across practices. The number of options for ethnicity group ranged from 5 to 84, with a median of 14, compared to the census lists that comprise of 19 (2021), 18 (2011), and 16 (2001) groups. Of the 56 practices, six used the 2001 census list, five used the 2011 census list, and none used the 2021 census list. Overall, 45 practices used lists that differed from any census list, including categories not typically considered to be ethnic, for example \'Muslim\' or \'Buddhist\', meaning individuals could potentially identify with multiple options.
CONCLUSIONS: High-quality research and healthcare data that includes patient ethnicity is essential to understand, document, and mitigate against health inequalities. However, this may be compromised by poorly conceived ethnic categorisations and a lack of standardisation. This pilot/exploratory study suggests that the ethnicity records in primary health care may be neither standardised nor meaningful.

BACKGROUND: Perinatal anxiety (PNA) occurs throughout the antenatal period or up to 1 year after childbirth, with a prevalence of 21%.
OBJECTIVE: To investigate if primary care records could be used to identify women at \'higher risk\' of PNA.
METHODS: Mixed-methods approach using quantitative and qualitative methods. Quantitative data analysis used Clinical Practice Research Datalink and IQVIA Medical Research Data to identify risk factors for PNA. Interviews explored the lived experiences of women with PNA about predisposing factors for PNA and acceptability of being informed of risk; and perspectives of primary healthcare professionals and Voluntary, Community, and Social Enterprise practitioners about risk communication. Interviews were conducted online, digitally recorded with consent, transcribed, and anonymised prior to analysis. Data were thematically analysed. Patient and clinical advisory groups informed each stage of the research.
RESULTS: Women reflected on both positive and negative impacts of being identified at higher risk of PNA, a lack of understanding of how primary care records are used, and who has access to them. All interview participants suggested predisposing factors that would not be coded in primary care records. Quantitative analysis demonstrated that some predisposing factors for PNA can be identified in a woman\'s primary care records. Initial analysis suggests associations between PNA and infant health and healthcare use.
CONCLUSIONS: While identification of higher risk of PNA may be acceptable, some factors that may contribute to PNA are not coded in primary care records. Identifying and managing PNA is needed to improve infant health.

BACKGROUND: Referring providers are often critiqued for writing poor-quality referrals. This study characterised clinical referral guidelines and forms to understand which data consultant providers require. These data were then used to codesign an evidence-based, high-quality referral form.
METHODS: This study used both observational and quality improvement approaches. Canadian referral guidelines were reviewed and summarised. Referral data fields from 150 randomly selected Ontario referral forms were categorised and counted. The referral guideline summary and referral data were then used by referring providers, consultant providers and administrators to codesign a referral form.
RESULTS: Referral guidelines recommended 42 types of referral data be included in referrals. Referral data were categorised as patient demographics, provider demographics, reason for referral, clinical information and administrative information. The percentage of referral guidelines recommending inclusion of each type of referral data varied from 8% to 77%. Ontario referral forms requested 264 different types of referral data. Digital referral forms requested more referral data types than paper-based referral forms (55.0±10.6 vs 30.5±8.1; 95% CI p<0.01). A codesigned referral form was created across two sessions with 29 and 21 participants in each.
CONCLUSIONS: Referral guidelines lack consistency and specificity, which makes writing high-quality referrals challenging. Digital referral forms tend to request more referral data than paper-based referrals, which creates administrative burdens for referring and consultant providers. We created the first codesigned referral form with referring providers, consultant providers and administrators. We recommend clinical adoption of this form to improve referral quality and minimise administrative burdens.

UNASSIGNED: Recent AUA guidelines for the management of benign prostatic hyperplasia (BPH) recommend routine collection of the International Prostate Symptom Score (IPSS) data, but routine collection can be challenging to fully implement. We investigated the impact of distributing the IPSS by electronic patient portal (EPP) on IPSS completion and its impact on BPH management.
UNASSIGNED: We performed a retrospective, longitudinal study of men undergoing a new patient visit (NPV) for BPH at our academic medical center. From September 2019 to November 2022, we identified patients undergoing an NPV for BPH. Prior to January 2021, the IPSS was collected in person at NPVs via paper forms; afterwards, the IPSS was distributed before the NPV using the EPP. Our primary outcome was IPSS completion; secondary outcomes were new BPH medications and BPH surgery ordered within 6 months.
UNASSIGNED: We identified 485 patients who underwent an NPV for BPH. EPP implementation significantly increased IPSS questionnaire completion (36.5% vs 56.9%, P < .0001). Following EPP implementation, we found that new BPH medications ordered at time of NPV decreased (10.4% vs 4.7%, P = .02). Although BPH surgery ordered within 6 months was similar, patients following EPP implementation had shorter time to BPH surgery compared to prior.
UNASSIGNED: Our study revealed that EPP distribution of the IPSS improves IPSS collection compliance, aligning our practice closer with AUA guidelines. Routine collection of the IPSS may impact clinical practice through the detection of more severe BPH, which reduces medical BPH management and time to definitive BPH therapy. Further work is needed to confirm findings.

OBJECTIVE: Develop a novel technique to identify an optimal number of regression units corresponding to a single risk point, while creating risk scoring systems from logistic regression-based disease predictive models. The optimal value of this hyperparameter balances simplicity and accuracy, yielding risk scores of small scale and high accuracy for patient risk stratification.
METHODS: The proposed technique applies an adapted line search across all potential hyperparameter values. Additionally, DeLong test is integrated to ensure the selected value produces an accuracy insignificantly different from the best achievable risk score accuracy. We assessed the approach through two case studies predicting diabetic retinopathy (DR) within six months and hip fracture readmissions (HFR) within 30 days, involving cohorts of 90 400 diabetic patients and 18 065 hip fracture patients.
RESULTS: Our scores achieve accuracies insignificantly different from those obtained by existing approaches, reaching AUROCs of 0.803 and 0.645 for DR and HFR predictions, respectively. Regarding the scale, our scores ranged 0-53 for DR and 0-15 for HFR, while scores produced by existing methods frequently spanned hundreds or thousands.
CONCLUSIONS: According to the assessment, our risk scores offer simple and accurate predictions for diseases. Furthermore, our new DR score provides a competitive alternative to state-of-the-art risk scores for DR, while our HFR case study presents the first risk score for this condition.
CONCLUSIONS: Our technique offers a generalizable framework for crafting precise risk scores of compact scales, addressing the demand for user-friendly and effective risk stratification tool in healthcare.

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BACKGROUND: Diagnostic errors pose significant health risks and contribute to patient mortality. With the growing accessibility of electronic health records, machine learning models offer a promising avenue for enhancing diagnosis quality. Current research has primarily focused on a limited set of diseases with ample training data, neglecting diagnostic scenarios with limited data availability.
OBJECTIVE: This study aims to develop an information retrieval (IR)-based framework that accommodates data sparsity to facilitate broader diagnostic decision support.
METHODS: We introduced an IR-based diagnostic decision support framework called CliniqIR. It uses clinical text records, the Unified Medical Language System Metathesaurus, and 33 million PubMed abstracts to classify a broad spectrum of diagnoses independent of training data availability. CliniqIR is designed to be compatible with any IR framework. Therefore, we implemented it using both dense and sparse retrieval approaches. We compared CliniqIR\'s performance to that of pretrained clinical transformer models such as Clinical Bidirectional Encoder Representations from Transformers (ClinicalBERT) in supervised and zero-shot settings. Subsequently, we combined the strength of supervised fine-tuned ClinicalBERT and CliniqIR to build an ensemble framework that delivers state-of-the-art diagnostic predictions.
RESULTS: On a complex diagnosis data set (DC3) without any training data, CliniqIR models returned the correct diagnosis within their top 3 predictions. On the Medical Information Mart for Intensive Care III data set, CliniqIR models surpassed ClinicalBERT in predicting diagnoses with <5 training samples by an average difference in mean reciprocal rank of 0.10. In a zero-shot setting where models received no disease-specific training, CliniqIR still outperformed the pretrained transformer models with a greater mean reciprocal rank of at least 0.10. Furthermore, in most conditions, our ensemble framework surpassed the performance of its individual components, demonstrating its enhanced ability to make precise diagnostic predictions.
CONCLUSIONS: Our experiments highlight the importance of IR in leveraging unstructured knowledge resources to identify infrequently encountered diagnoses. In addition, our ensemble framework benefits from combining the complementary strengths of the supervised and retrieval-based models to diagnose a broad spectrum of diseases.