National Institute for Health Research Health Informatics Collaborative: development of a pipeline to collate electronic clinical data for viral hepatitis research

Phenogrouping heart failure with preserved or mildly reduced ejection fraction using electronic health record data

BACKGROUND

Heart failure (HF) with preserved or mildly reduced ejection fraction includes a heterogenous group of patients. Reclassification into distinct phenogroups to enable targeted interventions is a priority. This study aimed to identify distinct phenogroups, and compare phenogroup characteristics and outcomes, from electronic health record data.

METHODS

2,187 patients admitted to five UK hospitals with a diagnosis of HF and a left ventricular ejection fraction ≥ 40% were identified from the NIHR Health Informatics Collaborative database. Partition-based, model-based, and density-based machine learning clustering techniques were applied. Cox Proportional Hazards and Fine-Gray competing risks models were used to compare outcomes (all-cause mortality and hospitalisation for HF) across phenogroups.

RESULTS

Three phenogroups were identified: (1) Younger, predominantly female patients with high prevalence of cardiometabolic and coronary disease; (2) More frail patients, with higher rates of lung disease and atrial fibrillation; (3) Patients characterised by systemic inflammation and high rates of diabetes and renal dysfunction. Survival profiles were distinct, with an increasing risk of all-cause mortality from phenogroups 1 to 3 (p < 0.001). Phenogroup membership significantly improved survival prediction compared to conventional factors. Phenogroups were not predictive of hospitalisation for HF.

CONCLUSIONS

Applying unsupervised machine learning to routinely collected electronic health record data identified phenogroups with distinct clinical characteristics and unique survival profiles.

Patient Biochemistry and Treatment Need in Chronic Hepatitis B Virus Infection Across Three Continents: Retrospective Cross-Sectional Cohort Studies

INTRODUCTION

Chronic hepatitis B virus (HBV) infection is associated with significant global morbidity and mortality. Low treatment rates are observed in patients living with HBV; the reasons for this are unclear. This study sought to describe patients' demographic, clinical and biochemical characteristics across three continents and their associated treatment need.

METHODS

This retrospective cross-sectional post hoc analysis of real-world data used four large electronic databases from the United States, United Kingdom and China (specifically Hong Kong and Fuzhou). Patients were identified by first evidence of chronic HBV infection in a given year (their index date) and characterized. An algorithm was designed and applied, wherein patients were categorized as treated, untreated but indicated for treatment and untreated and not indicated for treatment based on treatment status and demographic, clinical, biochemical and virological characteristics (age; evidence of fibrosis/cirrhosis; alanine aminotransferase [ALT] levels, HCV/HIV coinfection and HBV virology markers).

RESULTS

In total, 12,614 US patients, 503 UK patients, 34,135 patients from Hong Kong and 21,614 from Fuzhou were included. Adults (99.4%) and males (59.0%) predominated. Overall, 34.5% of patients were treated at index (range 15.9-49.6%), with nucleos(t)ide analogue monotherapy most commonly prescribed. The proportion of untreated-but-indicated patients ranged from 12.9% in Hong Kong to 18.2% in the UK; almost two-thirds of these patients (range 61.3-66.7%) had evidence of fibrosis/cirrhosis. A quarter (25.3%) of untreated-but-indicated patients were aged ≥ 65 years.

CONCLUSION

This large real-world dataset demonstrates that chronic hepatitis B infection remains a global health concern; despite the availability of effective suppressive therapy, a considerable proportion of predominantly adult patients apparently indicated for treatment are currently untreated, including many patients with fibrosis/cirrhosis. Causes of disparity in treatment status warrant further investigation.

Mapping and evaluating national data flows: transparency, privacy, and guiding infrastructural transformation

The importance of big health data is recognised worldwide. Most UK National Health Service (NHS) care interactions are recorded in electronic health records, resulting in an unmatched potential for population-level datasets. However, policy reviews have highlighted challenges from a complex data-sharing landscape relating to transparency, privacy, and analysis capabilities. In response, we used public information sources to map all electronic patient data flows across England, from providers to more than 460 subsequent academic, commercial, and public data consumers. Although NHS data support a global research ecosystem, we found that multistage data flow chains limit transparency and risk public trust, most data interactions do not fulfil recommended best practices for safe data access, and existing infrastructure produces aggregation of duplicate data assets, thus limiting diversity of data and added value to end users. We provide recommendations to support data infrastructure transformation and have produced a website (https://DataInsights.uk) to promote transparency and showcase NHS data assets.

Establishing a colorectal cancer research database from routinely collected health data: the process and potential from a pilot study

Objective

Colorectal cancer is a common cause of death and morbidity. A significant amount of data are routinely collected during patient treatment, but they are not generally available for research. The National Institute for Health Research Health Informatics Collaborative in the UK is developing infrastructure to enable routinely collected data to be used for collaborative, cross-centre research. This paper presents an overview of the process for collating colorectal cancer data and explores the potential of using this data source.

Methods

Clinical data were collected from three pilot Trusts, standardised and collated. Not all data were collected in a readily extractable format for research. Natural language processing (NLP) was used to extract relevant information from pseudonymised imaging and histopathology reports. Combining data from many sources allowed reconstruction of longitudinal histories for each patient that could be presented graphically.

Results

Three pilot Trusts submitted data, covering 12 903 patients with a diagnosis of colorectal cancer since 2012, with NLP implemented for 4150 patients. Timelines showing individual patient longitudinal history can be grouped into common treatment patterns, visually presenting clusters and outliers for analysis. Difficulties and gaps in data sources have been identified and addressed.

Discussion

Algorithms for analysing routinely collected data from a wide range of sites and sources have been developed and refined to provide a rich data set that will be used to better understand the natural history, treatment variation and optimal management of colorectal cancer.

Conclusion

The data set has great potential to facilitate research into colorectal cancer.

What makes administrative data "research-ready"? A systematic review and thematic analysis of published literature

Introduction

Administrative data are a valuable research resource, but are under-utilised in the UK due to governance, technical and other barriers (e.g., the time and effort taken to gain secure data access). In recent years, there has been considerable government investment in making administrative data "research-ready", but there is no definition of what this term means. A common understanding of what constitutes research-ready administrative data is needed to establish clear principles and frameworks for their development and the realisation of their full research potential.

Objective

To define the characteristics of research-ready administrative data based on a systematic review and synthesis of existing literature.

Methods

On 29th June 2021, we systematically searched seven electronic databases for (1) peer-reviewed literature (2) related to research-ready administrative data (3) written in the English language. Following supplementary searches and snowball screening, we conducted a thematic analysis of the identified relevant literature.

Results

Overall, we screened 2,375 records and identified 38 relevant studies published between 2012 and 2021. Most related to administrative data from the UK and US and particularly to health data. The term research-ready was used inconsistently in the literature and there was some conflation with the concept of data being ready for statistical analysis. From the thematic analysis, we identified five defining characteristics of research-ready administrative data: (a) accessible, (b) broad, (c) curated, (d) documented and (e) enhanced for research purposes.

Conclusions

Our proposed characteristics of research-ready administrative data could act as a starting point to help data owners and researchers develop common principles and standards. In the more immediate term, the proposed characteristics are a useful framework for cataloguing existing research-ready administrative databases and relevant resources that can support their development.

Impact of the COVID-19 pandemic on routine surveillance for adults with chronic hepatitis B virus (HBV) infection in the UK

Background: To determine the impact of the COVID-19 pandemic on the population with chronic Hepatitis B virus (HBV) infection under hospital follow-up in the UK, we quantified the coverage and frequency of measurements of biomarkers used for routine surveillance (alanine transferase [ALT] and HBV viral load). Methods: We used anonymized electronic health record data from the National Institute for Health Research (NIHR) Health Informatics Collaborative (HIC) pipeline representing five UK National Health Service (NHS) Trusts. Results: We report significant reductions in surveillance of both biomarkers during the pandemic compared to pre-COVID-19 years, both in terms of the proportion of patients who had ≥1 measurement annually, and the mean number of measurements per patient. Conclusions: These results demonstrate the real-time utility of HIC data in monitoring health-care provision, and support interventions to provide catch-up services to minimise the impact of the pandemic. Further investigation is required to determine whether these disruptions will be associated with increased rates of adverse chronic HBV outcomes.

Longitudinal Analysis of the Utility of Liver Biochemistry as Prognostic Markers in Hospitalized Patients With Corona Virus Disease 2019

The association of liver biochemistry with clinical outcomes of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is currently unclear, and the utility of longitudinally measured liver biochemistry as prognostic markers for mortality is unknown. We aimed to determine whether abnormal liver biochemistry, assessed at baseline and at repeat measures over time, was associated with death in hospitalized patients with COVID-19 compared to those without COVID-19, in a United Kingdom population. We extracted routinely collected clinical data from a large teaching hospital in the United Kingdom, matching 585 hospitalized patients who were SARS-CoV-2 real-time reverse transcription-polymerase chain reaction (RT-PCR) positive to 1,165 hospitalized patients who were RT-PCR negative for age, sex, ethnicity, and preexisting comorbidities. A total of 26.8% (157/585) of patients with COVID-19 died compared to 11.9% (139/1,165) in the group without COVID-19 (P < 0.001). At presentation, a significantly higher proportion of the group with COVID-19 had elevated alanine aminotransferase (20.7% vs. 14.6%, P = 0.004) and hypoalbuminemia (58.7% vs. 35.0%, P < 0.001) compared to the group without COVID-19. Within the group with COVID-19, those with hypoalbuminemia at presentation had 1.83-fold increased hazards of death compared to those with normal albumin (adjusted hazard ratio [HR], 1.83; 95% confidence interval [CI], 1.25-2.67), while the hazard of death was ~4-fold higher in those aged ≥75 years (adjusted HR, 3.96; 95% CI, 2.59-6.04) and ~3-fold higher in those with preexisting liver disease (adjusted HR, 3.37; 95% CI, 1.58-7.16). In the group with COVID-19, alkaline phosphatase (ALP) increased (R = 0.192, P < 0.0001) and albumin declined (R = -0.123, P = 0.0004) over time in patients who died. Conclusion: In this United Kingdom population, liver biochemistry is commonly deranged in patients with COVID-19. Baseline hypoalbuminemia and rising ALP over time could be prognostic markers for death, but investigation of larger cohorts is required to develop a better understanding of the relationship between liver biochemistry and disease outcome.

Hepatitis B virus (HBV) viral load, liver and renal function in adults treated with tenofovir disoproxil fumarate (TDF) vs. untreated: a retrospective longitudinal UK cohort study

BACKGROUND

Current clinical guidelines recommend treating chronic hepatitis B virus (HBV) infection in a minority of cases, but there are relatively scarce data on evolution or progression of liver inflammation and fibrosis in cases of chronic HBV (CHB) that do not meet treatment criteria. We aimed to assess the impact of TDF on liver disease, and the risk of renal impairment in treated CHB patients in comparison to untreated patients.

METHODS

We studied a longitudinal ethnically diverse CHB cohort in the UK attending out-patient clinics between 2005 and 2018. We examined TDF treatment (vs. untreated) as the main exposure, with HBV DNA viral load (VL), ALT, elastography scores and eGFR as the main outcomes, using paired tests and mixed effects model for longitudinal measurements. Additionally, decline of eGFR during follow-up was quantified within individuals by thresholds based on clinical guidelines. Baseline was defined as treatment initiation for TDF group and the beginning of clinical follow-up for untreated group respectively.

RESULTS

We included 206 adults (60 on TDF, 146 untreated), with a median ± IQR follow-up duration of 3.3 ± 2.8 years. The TDF group was significantly older (median age 39 vs. 35 years, p = 0.004) and more likely to be male (63% vs. 47%, p = 0.04) compared to the untreated group. Baseline difference between TDF and untreated groups reflected treatment eligibility criteria. As expected, VL and ALT declined significantly over time in TDF-treated patients. Elastography scores normalised during treatment in the TDF group reflecting regression of inflammation and/or fibrosis. However, 6/81 (7.4%) of untreated patients had a progression of fibrosis stage from F0-F1 to F2 or F3. There was no evidence of difference in rates or incidence of renal impairment during follow-up in the TDF vs. untreated group.

CONCLUSIONS

Risk of liver inflammation and fibrosis may be raised in untreated patients compared to those receiving TDF, and TDF may benefit a larger percentage of the CHB population.

Creation of the first national linked colorectal cancer dataset in Scotland: prospects for future research and a reflection on lessons learned

INTRODUCTION

Current understanding of cancer patients, their treatment pathways and outcomes relies mainly on information from clinical trials and prospective research studies representing a selected sub-set of the patient population. Whole-population analysis is necessary if we are to assess the true impact of new interventions or policy in a real-world setting. Accurate measurement of geographic variation in healthcare use and outcomes also relies on population-level data. Routine access to such data offers efficiency in research resource allocation and a basis for policy that addresses inequalities in care provision.

OBJECTIVE

Acknowledging these benefits, the objective of this project was to create a population level dataset in Scotland of patients with a diagnosis of colorectal cancer (CRC).

METHODS

This paper describes the process of creating a novel, national dataset in Scotland.

RESULTS

In total, thirty two separate healthcare administrative datasets have been linked to provide a comprehensive resource to investigate the management pathways and outcomes for patients with CRC in Scotland, as well as the costs of providing CRC treatment. This is the first time that chemotherapy prescribing and national audit datasets have been linked with the Scottish Cancer Registry on a national scale.

CONCLUSIONS

We describe how the acquired dataset can be used as a research resource and reflect on the data access challenges relating to its creation. Lessons learned from this process and the policy implications for future studies using administrative cancer data are highlighted.