New life for old cellular pathology: a transformational approach to the upcycling of historic e-pathology records for contemporary clinical uses.

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.

Validation of the liver traffic light test as a predictive model for survival and development of liver-related events.

BACKGROUND AND AIM: Liver disease mortality rates continue to rise due to late diagnosis. We need noninvasive tests to be made available in the community that can identify patients at risk from a serious liver-related event (SLE). We examine the performance of a blood test, the liver traffic light test (LTLT), with regard to its ability to predict survival and SLEs. METHODS: Using routinely gathered clinical data, sequential LTLT test results from 4854 individuals with suspected liver disease were prospectively analyzed (median follow-up 41 months). An SLE was defined as the development of cirrhosis, liver failure, ascites, or varices. Patients were graded as follows: red (high risk), amber (intermediate risk), and green (low risk). RESULTS: Overall, 565 individuals experienced an SLE (11.6%). The area under the curve (AUC) for the continuous LTLT variable was 0.87 (95% confidence interval 0.85-0.89) for prediction of an SLE and 0.81 (0.78-0.84) for mortality. When categorized into red/amber/green grades, a red LTLT result predicted an SLE with negative and positive predictive values of 0.97 and 0.29, respectively. A red LTLT score predicted mortality with negative and positive predictive values of 0.98 and 0.18, respectively. Kaplan-Meier plots demonstrated increased mortality and SLEs in the red group versus the green and amber groups (P < 0.001) and an increase in SLEs in the amber versus green group (P < 0.001). CONCLUSION: Here, the LTLT is further validated for the prediction of survival and SLE development. The LTLT could aid primary care risk management and referral pathways with the aim of detecting and treating liver disease earlier in the general population.

Can routine blood tests be modelled to detect advanced liver disease in the community: model derivation and validation using UK primary and secondary care data.

OBJECTIVES: Most 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 PARTICIPANTS: Logistic 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 MEASURES: Model creation dataset: cirrhosis or portal hypertension. Validation datasets: SLE (gastro-oesophageal varices, liver-related ascites or cirrhosis). RESULTS: In 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. CONCLUSION: Identification 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.

Design and implementation of the stacked, synchronised and iconographic timeline-structured electronic patient record in a UK NHS Global Digital Exemplar hospital.

BACKGROUND: Conventional 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. METHODS: Since 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. OUTCOMES: UHSL went live in 2017 for all authorised staff at the hospital. It displays all e-records for 2.5 million 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. CONCLUSIONS: UHSL 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.