ABSTRACT
Background/Aims The COVID-19 pandemic has placed unprecedented pressures on NHS departments, with demand rapidly outstripping capacity. The British Society for Rheumatology 'Rheumatology Workforce: a crisis in numbers (2021)' highlighted the need to provide innovative ways of delivering rheumatology specialist care. At University College London Hospitals (UCLH) we created a rheumatology multidisciplinary team (MDT) clinic to meet rising demands on our service. The aims of the Rheumatology MDT clinic were to: reduce new appointment/follow-up waiting times, increase clinic capacity, incorporate musculoskeletal (MSK) point of care ultrasound, reduce number of hospital visits and add value to each clinic encounter. Methods We ran a 6-month pilot, supported by our outpatient transformation team, incorporating a Rheumatology Advanced Practice Physiotherapist (APP), Clinical Nurse Specialist (CNS) and MSK ultrasound within a Consultant clinic. The success of the pilot helped secure funding for a further 12 months. Over 18 months we have implemented: APP/Consultant enhanced triage - up to 40% of referrals were appropriate for APP assessment, including regional MSK problems and back pain. This increased capacity for consultant-led appointments. Standardisation of time-lapse between CNS and consultant follow-up appointments to ensure appropriate spacing between patient encounters. Facilitated overbooking of urgent cases afforded by additional capacity provided by the APP. MSK ultrasound embedded in the clinic template. 'Zoom' patient education webinars facilitated by MDT members and wider disciplines e.g. dietetics, to empower self-management and reduce the administrative burden of patient emails/phone calls occurring outside the clinic. Patient participation sessions and feedback to help shape the service. Results During the 6-month pilot we reduced our waiting time for follow-up appointments from 9 months to 2. We now have capacity to book 1-2 urgent cases each week. Pre-MDT the average wait from consultant referral to physiotherapist appointment was 55 days. The MDT allows for same day assessment (reducing 2-3 patient journeys a clinic) and where suitable, facilitates discharge or onwards referral to the appropriate service. A dedicated MDT CNS has shortened treatment times, reduced email traffic between CNS and consultant and allows for same day, joint decision-making resulting in fewer appointments. Zoom webinar feedback has been positive. Patients value the broad expertise of allied health professionals which supports self-management. Embedding ultrasound allows for same day diagnostics, decreased referrals to radiology and reduced hospital visits. Conclusion Our MDT model has reduced waiting lists, decreased treatment delays and cut hospital attendances. Point of care ultrasound allows for same day decision making and abolishes the cost and diagnostic delay associated with referrals to radiology or outsourced providers. Shared decision-making adds value to outpatient attendances, which is reflected in patients' positive feedback. The MDT model maximises the existing workforce skill set by enhancing the APP and CNS role, allowing patients immediate access to their expertise.
ABSTRACT
Background: BHIVA's 'Don't Forget the Children' and Standards of Care (SoC) documents highlight the importance of routine HIV testing for children of people living with HIV (PLWH). Our HIV service audited child testing in 2008, 2009 and 2010 with 46%, 78% and 82% respectively of children requiring testing having a documented result. Having evolved a child testing pathway and MDT, with dedicated Health Advisor and Paediatric nurse support, we wanted to re-evaluate our child testing performance during the COVID-19 pandemic. Method(s): Newly diagnosed PLWH, 01/08/2020 - 31/12/2021, were identified via our HARS dataset. All 32 identified individuals case notes were reviewed and the relevant auditable outcomes from BHIVA's SoC document used. Result(s): 32/32 (100%) had documented evidence that child testing had been considered within 4 weeks of diagnosis (BHIVA target 95%). 13/32 had a total of 35 children, 29 of whom did not require testing. 20/29 had documented evidence their mother was not living with HIV post childbirth, 9/29 were >18 years and all but 1, not living in the UK, had either tested in sexual health or antenatal settings. 6/35 (17%) children required testing. 6/6 (100%) had a documented test result within 6 months of their parent's diagnosis, 1 of whom tested negative prior to parental diagnosis (BHIVA target 90%). 5/6 tested aged >18 months. 1 child <18 months, whose parent was diagnosed antenatally, awaits final 4th generation testing at 18 months. Conclusion(s): Our service has a robust mechanism in place for asking all newly diagnosed individuals, and those new to our service, about children during their first consultation. Where children without documented evidence of HIV testing are identified our child testing pathway ensures timely investigation and documentation - all child testing was completed within one month of parental diagnosis in this audit sample. Our service surpassed the BHIVA standards for child testing for all new diagnoses during the COVID-19 pandemic. Future planned work includes a re-audit of child testing for those already known to our HIV service. As neither parental status nor child location is static regular enquiry in relation to children needs embedding into routine HIV care. (Table Presented).
ABSTRACT
BACKGROUND: The International Classification of Diseases (ICD) codes represent the global standard for reporting disease conditions. The current ICD codes connote direct human-defined relationships among diseases in a hierarchical tree structure. Representing the ICD codes as mathematical vectors helps to capture nonlinear relationships in medical ontologies across diseases. METHODS: We propose a universally applicable framework called "ICD2Vec" designed to provide mathematical representations of diseases by encoding corresponding information. First, we present the arithmetical and semantic relationships between diseases by mapping composite vectors for symptoms or diseases to the most similar ICD codes. Second, we investigated the validity of ICD2Vec by comparing the biological relationships and cosine similarities among the vectorized ICD codes. Third, we propose a new risk score called IRIS, derived from ICD2Vec, and demonstrate its clinical utility with large cohorts from the UK and South Korea. RESULTS: Semantic compositionality was qualitatively confirmed between descriptions of symptoms and ICD2Vec. For example, the diseases most similar to COVID-19 were found to be the common cold (ICD-10: J00), unspecified viral hemorrhagic fever (ICD-10: A99), and smallpox (ICD-10: B03). We show the significant associations between the cosine similarities derived from ICD2Vec and the biological relationships using disease-to-disease pairs. Furthermore, we observed significant adjusted hazard ratios (HR) and area under the receiver operating characteristics (AUROC) between IRIS and risks for eight diseases. For instance, the higher IRIS for coronary artery disease (CAD) can be the higher probability for the incidence of CAD (HR: 2.15 [95% CI 2.02-2.28] and AUROC: 0.587 [95% CI 0.583-0.591]). We identified individuals at substantially increased risk of CAD using IRIS and 10-year atherosclerotic cardiovascular disease risk (adjusted HR: 4.26 [95% CI 3.59-5.05]). CONCLUSIONS: ICD2Vec, a proposed universal framework for converting qualitatively measured ICD codes into quantitative vectors containing semantic relationships between diseases, exhibited a significant correlation with actual biological significance. In addition, the IRIS was a significant predictor of major diseases in a prospective study using two large-scale datasets. Based on this clinical validity and utility evidence, we suggest that publicly available ICD2Vec can be used in diverse research and clinical practices and has important clinical implications.