Aims Cellular pathology ('e-pathology') record sets are a rich data resource with which to populate the electronic patient record (EPR). Accessible reports, even decades old, can be of great value in contemporary clinical decision making and as a resource for longitudinal clinical research. The aim of this short paper is to describe a solution in a major UK University Hospital which gives immediate visibility and clinical utility to 30 years of e-pathology records Methods Over the past decade, we have created a timeline structured and iconographic data framework for the 'whole-of-life' visualisation of the entirety of an EPR. We have enhanced this interface with the sequential extraction of 373 342 e-pathology reports from legacy Ferranti (1990-1997) and Masterlab (1997-2004) files. They have been uploaded into our SQL file servers, following appropriate data quality and patient identity reconciliation checks. Results We have restored a large repository of previously inaccessible e-pathology records to clinical use and to immediacy of access as a foundation element of our timeline structured EPR. This process has also allowed us to populate and validate an EPR-integral breast cancer data system of 20 000 cases with e-pathology records dating back to 1990. Conclusions The revitalisation of old e-pathology reports into a timeline structured EPR creates preserves and upcycles the investment in pathology reporting which is otherwise progressively lost to clinical use. E-pathology records provide reliable, life-long evidence of critical transition points in individual lives and disease progression for clinical and research use, when they can be instantly accessed.

Abstract Aims Surgical and Cellular pathology (‘e-pathology’) record sets are a valuable data resource with which to populate the Electronic Patient Record (EPR). Accessible reports, even decades old, can be of great value in contemporary clinical decision making and as a resource for longitudinal clinical research. They commonly identify the operation, the location and the pathology, even if not to modern reporting standards. Methods Since 2010, we have built and implemented a timeline structured EPR for the ‘whole-of-life’ visualisation of the electronic documents (e-Docs) of 2.5M+ patients on our Master Index. Prior to this project, our earliest e-Docs dated to 1995. We tracked down 373,342 inert e-pathology reports from our legacy Ferranti (1990-1997) and Masterlab (1997-2004) systems. These were uploaded into our active file servers, following appropriate data quality and patient identity reconciliation checks. Results We have progressively restored 373,342 previously inaccessible e-pathology records to clinical use and to immediacy of access, and in the process extending our “addressable EPR” back to 1990 for living and deceased patients. This process has also allowed us to populate and validate an EPR-integral breast cancer data system of 20,000 cases with e-pathology records dating back to 1990. Conclusions The sustainable revitalisation of old e-pathology reports into a timeline structured EPR creates preserves and upcycles the investment in pathology reporting which is otherwise progressively lost to clinical use. E-pathology records provide reliable, life-long evidence of critical transition points in individual lives and disease progression for clinical and research use, when they can be instantly accessed.

Abstract Introduction The digitisation of the electronic patient record (EPR) provides transformative opportunities for data visualisation. The synchronised timeline and iconographic interface permits the whole-of-life display, navigation and interpretation of all documents and reports of each and every EPR on a single screen, thus substantially facilitating clinical research. Methods Since 2010, we have conceived, programmed and iterated a radical interface, UHS Lifelines, within our Trust EPR using agile methodology. It is live for >2.5M record sets, and enriched with cellular pathology records back to 1990. We have integrated this interface into a unique, HTML-enabled, dynamic and continually updated database for the recording of treatments and pathologies of all cases of breast neoplasia from our current and historic record sets. Results As of January 2021, our data system contains ∼20,000 sequential whole of life records of patients with breast neoplasia, including ∼15,000 locally diagnosed and ∼ 5,000 externally referred cases. The unique Cancer Lifetrack timelines displays the disease course of every case from primary diagnosis, through loco-regional recurrence, to distant metastasis, other morbid cancers and cause of death, where relevant. An integral data mining system permits a wide range of analyses. Conclusions We believe our Breast Cancer Data System to be the first-in-class exemplar of a new and proven approach to clinical data visualisation. It permits near-instantaneous oversight and real time updating of every patient record in the system. We recognise its potential application for the whole-of-life study of all chronic diseases of childhood and adulthood as the model is more widely adopted.

Abstract Background Many surgeons work within multidisciplinary cancer teams. The Somerset Cancer Register (SCR) is a national reporting system for service performance which is in use in more than 100 NHS Trusts. However, the core system has not yet been optimised for MDT users or for the surfacing of clinical data for research and other uses. Methods SCR replaced our legacy cancer reporting system in 2014. Working with the SCR developers, we integrated our cellular pathology and imaging records with the SCR MDT outputs. We subsequently developed SCR+ to optimise workflows for MDT coordinators and information presentation to clinical users. Results Our HTML-enabled SCR+ software application displays all cancer patients by pathological type and year of presentation on dynamic histograms, for ease of visualisation and interaction. Every selected case is displayed in list order for each and every MDT meeting, with a fast hyperlink to our integral Lifelines EPR interface, to electronic pathology records back to 1990, and to our Breast Cancer Data System for relevant patients. Conclusions The SCR+ module transforms the access and visualisation of cancer workload across our Trust for all authorised MDT users, with appropriate data security. The agile programming methodology allowed us to build a sustainable cancer data system with further development potential. The product substantially enhances user experience, data recall and productivity over legacy systems. Close cooperation between clinically proficient IT teams and clinicians as the end consumers of digital health data systems yields significant operational benefits at pace and with very modest costs.

Aims Colonoscopy electronic patient record (EPR) reporting systems are generally reliant on endoscopist self-report to accurately determine procedure withdrawal time – a key metric of high-quality colonoscopy. As the accuracy of self-report vs image-linked timestamping is presently unknown our aim was to investigate this.

ObjectivesMost patients are unaware they have liver cirrhosis until they present with a decompensating event. We therefore aimed to develop and validate an algorithm to predict advanced liver disease (AdvLD) using data widely available in primary care.Design, setting and participantsLogistic regression was performed on routinely collected blood result data from the University Hospital Southampton (UHS) information systems for 16 967 individuals who underwent an upper gastrointestinal endoscopy (2005–2016). Data were used to create a model aimed at detecting AdvLD: ‘CIRRhosis Using Standard tests’ (CIRRUS). Prediction of a first serious liver event (SLE) was then validated in two cohorts of 394 253 (UHS: primary and secondary care) and 183 045 individuals (Care and Health Information Exchange (CHIE): primary care).Primary outcome measuresModel creation dataset: cirrhosis or portal hypertension. Validation datasets: SLE (gastro-oesophageal varices, liver-related ascites or cirrhosis).ResultsIn the model creation dataset, 931 SLEs were recorded (5.5%). CIRRUS detected cirrhosis or portal hypertension with an area under the curve (AUC) of 0.90 (95% CI 0.88 to 0.92). Overall, 3044 (0.8%) and 1170 (0.6%) SLEs were recorded in the UHS and CHIE validation cohorts, respectively. In the UHS cohort, CIRRUS predicted a first SLE within 5 years with an AUC of 0.90 (0.89 to 0.91) continuous, 0.88 (0.87 to 0.89) categorised (crimson, red, amber, green grades); and AUC 0.84 (0.82 to 0.86) and 0.83 (0.81 to 0.85) for the CHIE cohort. In patients with a specified liver risk factor (alcohol, diabetes, viral hepatitis), a crimson/red cut-off predicted a first SLE with a sensitivity of 72%/59%, specificity 87%/93%, positive predictive value 26%/18% and negative predictive value 98%/99% for the UHS/CHIE validation cohorts, respectively.ConclusionIdentification of individuals at risk of AdvLD within primary care using routinely available data may provide an opportunity for earlier intervention and prevention of liver-related morbidity and mortality.

'Big data' in healthcare encompass measurements collated from multiple sources with various degrees of data quality. These data require quality control assessment to optimise quality for clinical management and for robust large-scale data analysis in healthcare research. Height and weight data represent one of the most abundantly recorded health statistics. The shift to electronic recording of anthropometric measurements in electronic healthcare records, has rapidly inflated the number of measurements. WHO guidelines inform removal of population-based extreme outliers but an absence of tools limits cleaning of longitudinal anthropometric measurements. We developed and optimised a protocol for cleaning paediatric height and weight data that incorporates outlier detection using robust linear regression methodology using a manually curated set of 6,279 patients' longitudinal measurements. The protocol was then applied to a cohort of 200,000 patient records collected from 60,000 paediatric patients attending a regional teaching hospital in South England. WHO guidelines detected biologically implausible data in <1% of records. Additional error rates of 3% and 0.2% for height and weight respectively were detected using the protocol. Inflated error rates for height measurements were largely due to small but physiologically implausible decreases in height. Lowest error rates were observed when data was measured and digitally recorded by staff routinely required to do so. The protocol successfully automates the parsing of implausible and poor quality height and weight data from a voluminous longitudinal dataset and standardises the quality assessment of data for clinical and research applications.

BackgroundConventional electronic screen visualisation formats, which use tabs, dropdown menus, lists and multiple windows, present huge navigation challenges to health professionals. A unifying and intuitive interface for the electronic patient record (EPR) has been an elusive goal for software developers for decades.MethodsSince 2009, by working in an agile way, we have built and implemented a fully operational and dynamic system, the University Hospital Southampton Lifelines (UHSL), within our clinical data estate, in a UK university hospital. UHSL permits the continuously updated display of the EPR on a single desktop computer screen in an intuitive format. During this iterative evolution, we have resolved a number of practical challenges in data display, while maintaining our core aims of end-user optimisation and radical simplification of the interface. Concurrently, we have upcycled a significant volume of clinical e-content, some from as far back as 1991, into UHSL, and at a marginal cost.OutcomesUHSL went live in 2017 for all authorised staff at the hospital. It displays all e-records for 2.5million patients and for more than 100 million documents and reports. It significantly reduces the screen time to navigate the individual EPR, and it offers substantial productivity gains in designated clinical services.ConclusionsUHSL has considerable further development potential as a National Health Service EPR interface, for the integration, display and ease of understanding of medical records across primary, secondary and community care.

Embedding electronic growth charts (EGCs) into clinical practice in a children’s hospital. We employed initial implementation in the outpatient setting and subsequently extended this across inpatients with the growth chart following the child’s records through both settings and significantly increasing growth data documentation.

Searchable abstracts of presentations at key conferences in endocrinology ISSN 1470-3947 (print) | ISSN 1479-6848 (online)

Introduction: The NCIN has recently recognised the importance of understanding the interactions between complex multidisciplinary treatments and therapeutic outcomes in terms of local recurrence and metastasis in breast and other cancers.

Introduction: The development of a temporally structured data system to provide “whole of life” oversight of breast cancer treatment inputs, pathological parameters, clinical episodes and final outcomes is a significant conceptual, design and technical challenge. There are no commercial systems yet available which fulfil the requirement.

Introduction: Clinical and MDT decision making for patients with breast cancer and other chronic diseases is handicapped by the lack of reliable long term follow up; of robust measures of final outcome, including accurate death certification; and of tools for the ready visualisation and radical simplification of complex data sets.