Owen Johnson

University of Leeds · Institute for Artificial Intelligence and Biological Systems (I-AIBS)

Oesophago-gastric cancer is difficult to diagnose in the early stages given its typical non-specific initial manifestation. We hypothesise that machine learning can improve upon the diagnostic performance of current primary care risk-assessment tools by using advanced analytical techniques to exploit the wealth of evidence available in the electron...

Objectives Reinforcement Learning is a branch of artificial intelligence (AI) which has the potential to support significant improvement in patient care. There is concern that such approaches may reinforce existing biases within patient groups. Understanding discrimination in AI models is important for building trust and ensuring fair and safe use....

The COVID-19 pandemic has highlighted some of the opportunities, problems and barriers facing the application of Artificial Intelligence to the medical domain. It is becoming increasingly important to determine how Artificial Intelligence will help healthcare providers understand and improve the daily practice of medicine. As a part of the Artifici...

Introduction Reviewing anticholinergic medicines is an important consideration in the safe care of frail older people. The cumulative effect of taking multiple anticholinergic medicines, known as anticholinergic burden (AB) (1), is associated with physical and cognitive decline, falls, and hospitalisation (2). There is a need to explore the develop...

Background and objectives Studies of Functional Neurological Disorders (FND) are usually outpatient-based. To inform service development, we aimed to describe patient pathways through healthcare events, and factors affecting risk of emergency department (ED) reattendance, for people presenting acutely with FND. Methods Acute neurology/stroke teams...

Introduction Medications with Anticholinergic (AC) properties, are prescribed to treat a range of conditions. Older people are increasingly likely to be prescribed multiple AC medications, but are also more likely to experience unwanted adverse effects, such as falls and delirium. The risks of adverse outcomes increase with the number and potency o...

Introduction This paper presents a mixed-methods study protocol that will be used to evaluate a recent implementation of a real-time, centralised hospital command centre in the UK. The command centre represents a complex intervention within a complex adaptive system. It could support better operational decision-making and facilitate identification...

The main challenge in the pathway analysis of cancer treatments is the complexity of the process. Process mining is one of the approaches that can be used to visualize and analyze these complex pathways. In this study, our purpose was to use process mining to explore variations in the treatment pathways of endometrial cancer. We extracted patient d...

In healthcare, process mining has been used in many case studies to discover and analyse process models of patient treatments. Process mining is generally applied to analyse the event log of patient treatments as extracted from the Electronic Health Record (EHR). In this study, we proposed an approach to combine the event log of patient treatments...

A temporal disease trajectory describes the sequence of diseases that a patient has experienced over time. Electronic health records (EHRs) that contain coded disease diagnoses can be mined to find common and unusual disease trajectories that have the potential to generate clinically valuable insights into the relationship between diseases. Disease...

UNSTRUCTURED The fourth industrial revolution is based on cyber-physical systems and the connectivity of devices. It is currently unclear what the consequences are for patient safety as existing digital health technologies become ubiquitous with increasing pace and interact in unforeseen ways. In this paper, we describe the output from a workshop f...

The fourth industrial revolution is based on cyber-physical systems and the connectivity of devices. It is currently unclear what the consequences are for patient safety as existing digital health technologies become ubiquitous with increasing pace and interact in unforeseen ways. In this paper, we describe the output from a workshop focused on ide...

PURPOSE Informatics solutions to early diagnosis of cancer in primary care are increasingly prevalent, but it is not clear whether existing and planned standards and regulations sufficiently address patients' safety nor whether these standards are fit for purpose. We use a patient safety perspective to reflect on the development of a computerized c...

Since medical processes are hard to be designed by consensus of experts, the use of data available for creating medical processes is a recurrent idea in literature [3, 7, 8]. Data-driven paradigms are named to be a feasible solution in this field that can support medical experts in their daily decisions [20]. Behind this paradigm, there are framewo...

The area of process change over time is a particular concern in healthcare, where patterns of care emerge and evolve in response to individual patient needs. We propose a structured approach to analyse process change over time that is suitable for the complex domain of healthcare. Our approach applies a qualitative process comparison at three level...

A temporal disease trajectory describes the sequence of diseases that a patient has experienced over time. Electronic health records (EHRs) that contain coded disease diagnoses can be mined to find common and unusual disease trajectories that have the potential to generate clinically valuable insights into the relationship between diseases. Disease...

Healthcare organizations are confronted with challenges including the contention between tightening budgets and increased care needs. In the light of these challenges, they are becoming increasingly aware of the need to improve their processes to ensure quality of care for patients. To identify process improvement opportunities, a thorough process...

Modelling patient disease trajectories from evidence in electronic health records could help clinicians and medical researchers develop a better understanding of the progression of diseases within target populations. Process mining provides a set of well-established tools and techniques that have been used to mine electronic health record data to u...

BACKGROUND Digital health is an important part of the future of health care, prevention and management of disease and innovative monitoring solutions. With an aging population and rising health related costs, digital health is an essential part of the solution, alongside the emerging big data and associated analytics. To varying extents, digital he...

Background: Global evidence suggests a range of benefits for introducing electronic health record (EHR) systems to improve patient care. However, implementing EHR within healthcare organisations is complex and, in the United Kingdom (UK), uptake has been slow. More research is needed to explore factors influencing successful implementation. This s...

Background: Significant amounts of health data are stored as free-text within clinical reports, letters, discharge summaries and notes. Busy clinicians have limited time to read such large amounts of free-text and are at risk of information overload and consequently missing information vital to patient care. Automatically identifying relevant info...

Background Global evidence suggests a range of benefits for introducing electronic health record (EHR) systems to improve patient care. However, implementing EHR within healthcare organisations is complex and in the United Kingdom (UK), uptake has been slow. More research is needed to explore factors influencing successful implementation. This stud...

Background Global evidence suggests benefits of introducing electronic health record (EHR) systems to improve patient care. However, implementing EHR into healthcare organisations is complex and in the United Kingdom (UK), uptake has been slow. More research is needed to explore factors influencing successful implementation. This study explored sta...

Objective To perform a systematic review examining the variation in methods, results, reporting and risk of bias in electronic health record (EHR)-based studies evaluating management of a common musculoskeletal disease, gout. Methods Two reviewers systematically searched MEDLINE, Scopus, Web of Science, CINAHL, PubMed, EMBASE and Google Scholar fo...

PURPOSE The use of health information technology (HIT) to support patient and health professional communication is emerging as a core component of modern cancer care. Approaches to HIT development for cancer care are often underreported, despite their implementation in complex, multidisciplinary environments, typically supporting patients with mult...

An understudied challenge within process mining is the area of process change over time. This is a particular concern in healthcare, where patterns of care emerge and evolve in response to individual patient needs and through complex interactions between people, process, technology and changing organisational structure. We propose a structured appr...

Process mining helps understand processes within healthcare. While often used in secondary care, there is little work using primary care data. Serious adverse events that result from hazardous prescribing are common and costly. For example, non-steroidal anti-inflammatory drugs (NSAIDs) and antiplatelets which can cause gastro-intestinal bleeds (Gi...

Process mining helps healthcare professionals understand processes within healthcare. While often used in secondary care, there is little work in process mining using primary care data. Serious adverse events that result from hazardous prescribing are common and costly. For example, non-steroidal anti-inflammatory drugs (NSAIDs) and antiplatelets c...

Background Global evidence suggests benefits of introducing electronic patient record (EPR) systems to improve patient care. However, implementing EPR into healthcare organisations is complex and in the United Kingdom (UK), uptake has been slow. More research is needed to explore factors influencing successful implementation. This study explored st...

General System Theory was proposed in the post-war period as a unifying framework for interdisciplinary science based on the idea that systems have a set of similar properties and characteristics regardless of discipline. General System Theory laid the foundations for talking about things in terms of systems, many of its terms are now embedded in e...

An understudied challenge within process mining is the area of process change over time. This is a particular concern in healthcare, where patterns of care emerge and evolve in response to individual patient needs and through complex interactions between people, process, technology and changing organisational structure. We propose a structured appr...

Introduction Learning health systems (LHS) are one of the major computing advances in health care. However, no prior research has systematically analysed barriers and facilitators for LHS. This paper presents an investigation into the barriers, benefits, and facilitating factors for LHS in order to create a basis for their successful implementation...

Process mining of routine electronic healthcare records can help inform the management of care pathways. Combining process mining with simulation creates a rich set of tools for care pathway improvement. Healthcare process mining creates insight into the reality of patients’ journeys through care pathways while healthcare process simulation can hel...

An understudied challenge within process mining is the area of process change over time. This is a particular concern in healthcare, where patterns of care emerge and evolve in response to individual patient needs and through complex interactions between people, process, technology and changing organisational structure. We propose a structured appr...

Process mining has proved to be a valuable technique for extracting process knowledge from data within information systems. Much work has been conducted in applying process mining to domains such as logistics, banking, transportation and many areas of the government, including healthcare. Frail elderly people who have an increased risk of adverse o...

There is a growing body of literature on process mining in healthcare. Process mining of electronic health record systems could give benefit into better understanding of the actual processes happened in the patient treatment, from the event log of the hospital information system. Researchers report issues of data access approval, anonymisation cons...

Process mining is a data analytics approach which has shown promising results in healthcare including the potential to improve the management of chronic diseases such as cardiovascular disease (CVD). CVD are one of the leading causes of premature death worldwide. Helping healthcare professionals develop a better understanding of how to improve CVD...

Objective: Learning Health Systems (LHS) are one of the major computing advances in healthcare. This paper presents an investigation into the barriers, benefits and facilitating factors for LHS in order to create a basis for successful implementation and adoption of LHS. Method: First, the ITPOSMO-BBF framework was developed based on the establishe...

Introduction Patients with Functional Neurological Symptoms (FNS) can present acutely, but many hospitals lack specific pathways or services for them. Outpatient FNS cohorts have been studied, but there is little data regarding acute FNS to inform service improvement. Method Over an 8 month period at Leeds Teaching Hospitals NHS Trust (UK), the on...

There is a growing body of literature on process mining in healthcare. Process mining of Electronic Health Record (EHR) systems could give benefit into better understanding of the actual processes happened in the patient treatment, from the event log of the hospital information system. Researchers report issues of data access approval, anonymisatio...

Process mining of routine electronic healthcare records can help inform the management of care pathways. Combining process mining with simulation creates a rich set of tools for care pathway improvement. Healthcare process mining creates insight into the reality of patients’ journeys through care pathways while healthcare process simulation can hel...

Background There are many proposed benefits of using learning health systems (LHS), including improved patient outcomes. There has been little adoption of LHS in practice due to challenges and barriers that limit adoption of new data-driven technologies in healthcare. We have identified a more fundamental explanation: the majority of developments i...

The learning health system (LHS) is one in which progress in science, informatics and care culture converges to continuously create new knowledge as a natural by-product of care processes. While LHS was first described over a decade ago, much of the recent published work that should fall within the domain of LHS fails to claim or be identified as s...

The learning health system (LHS) is one in which progress in science, informatics and care culture converges to continuously create new knowledge as a natural by-product of care processes. While LHS was first described over a decade ago, much of the recent published work that should fall within the domain of LHS fails to claim or be identified as s...

Process mining is a data analytics approach to discover and analyse process models based on the real activities captured in information systems. There is a growing body of literature on process mining in healthcare, including oncology, the study of cancer. In earlier work we found 37 peer-reviewed papers describing process mining research in oncolo...

Process mining is the discipline of discovering processes from event logs, checking the conformance of real world events to idealized processes, and ultimately finding ways to improve those processes. It was originally applied to business processes and has recently been applied to healthcare. It can reveal insights into clinical care pathways and i...

Process mining techniques can play a significant role in understanding healthcare processes by supporting analysis of patient records in electronic health record systems. Healthcare processes are complex and patterns of care may vary considerably within similar cohorts of patients. Process mining often creates "spaghetti" models and require signifi...

Process mining techniques can play a significant role in understanding healthcare processes by supporting the analysis of patient records in electronic health record systems. Healthcare processes are however complex and patterns of care may vary considerably within similar cohorts of patients. As a result process mining often creates “spaghetti” mo...

Process mining is a data analysis approach to discover and analyse process models based on the real activities captured in the event log. There is a growing body of literature on process mining in healthcare, including oncology, the study of cancer. In earlier work we found 37 peer-reviewed papers describing process mining research in oncology with...

Clinical pathways are highly variable and although many patients may follow similar pathway each individual will experience a unique set of events, for example with multiple repeated activities or varied sequences of activities. Process mining techniques are able to discover generalizable pathways based on data mining of event logs but using proces...

Background: Significant adverse events (AE) during cancer therapy disrupt treatment and escalate to emergency admissions. Approaches to improve the timeliness and accuracy of AE reporting may improve safety and reduce health service costs. Reporting AE via patient reported outcomes (PROs), can improve clinician-patient communication and making dat...

Clinical pathways are highly variable and although many patients may follow similar pathway each individual will experience a unique set of events, for example with multiple repeated activities or varied sequences of activities. Pro-cess mining techniques are able to discover generalizable pathways based on data mining of event logs but using proce...

Background: There is growing interest in the use of routinely collected electronic health records to enhance service delivery and facilitate clinical research. It should be possible to detect and measure patterns of care and use the data to monitor improvements but there are methodological and data quality challenges. Driven by the desire to model...

Process mining, an emerging data analytics method, has been used effectively in various healthcare contexts including oncology, the study of cancer. Cancer is a complex disease with many complicated care requirements and there is an urgent need to improve the cost and clinical effectiveness of cancer care pathways. Process mining of the e-health re...

Since Hippocrates, doctors have recognised the value of family history.1 It is less clear how GPs should use this information now that gene sequencing and electronic medical records are redefining what is possible. In rare genetic diseases, family history highlights important risks but shared ethnicity, culture, diet, and environment mean that fami...

The opportunities for data analytics to inform the science and practice of health care are growing. For example, in the UK, 65 million citizens have lifelong e-health records that can be used to examine patterns of disease, treatment and outcomes. Similarly the real-world impact of interventions such as new drugs can be evaluated in these records....

Many healthcare organizations are now making good use of electronic health record (EHR) systems to record clinical information about their patients and the details of their healthcare. Electronic data in EHRs is generated by people engaged in complex processes within complex environments, and their human input, albeit shaped by computer systems, is...

Introduction Point-of-care tests (POCTs) can eliminate the delay between being tested for chlamydia and receiving the result and treatment, potentially reducing loss to follow-up. However, the cost-effectiveness of POCT implementation depends on multiple factors, including cost-per-test, clinic time, sensitivity and specificity, and the epidemiolog...

Chlamydia trachomatis is the most commonly diagnosed bacterial sexually transmitted infection in Britain. Present standards specify treatment within 14 days of testing positive; point-of-care testing (POCT) can eliminate this delay and potentially reduce loss to follow-up; its greater convenience might increase testing. 90-min nucleic acid amplific...

Background Chlamydia trachomatis is the most commonly diagnosed bacterial sexually transmitted infection in Britain. Present standards specify treatment within 14 days of testing positive; point-of-care testing (POCT) can eliminate this delay and potentially reduce loss to follow-up; its greater convenience might increase testing. 90-min nucleic ac...

The nature of pathology services is changing under the combined pressures of increasing workloads, cost constraints and technological advancement. In the face of this, laboratory systems need to meet new demands for data exchange with clinical electronic record systems for test requesting and results reporting. As these needs develop, new challenge...

Introduction and AimProblem drinking is rarely identified unless health-care professionals are specifically instructed to assess alcohol consumption. Individualised web-based alcohol interventions provide opportunities to enhance screening and early identification. We aimed to create a web-based brief personalised feedback intervention to enable cl...

The Nursing Informatics International Research Network (NIIRN) is a group of experts who are collaborating on the development of internationally relevant research programs for nursing informatics. In this paper we outline key findings of a survey exploring international research priorities for nursing informatics. The survey was available online du...

We describe a study in the domain of health informatics which includes some novel requirements for patient confidentiality in the context of medical health research. We present a prototype which takes health records from a commercial data provider, anonymises them in an innovative way and makes them available within a secure cloud-based Virtual Res...

A Verbal Autopsy is the record of an interview about the circumstances of an uncertified death. In developing countries, if a death occurs away from health facilities, a field-worker interviews a relative of the deceased about the circumstances of the death; this Verbal Autopsy can be reviewed off-site. We report on a comparative study of the proce...

This paper presents a method employed in building a semantically annotated corpus of 11,741 Verbal Autopsy documents, each annotated with Cause of Death, based on verbal records of deaths of mothers, stillbirths, and infants up to 1 year of age, captured for analysis in Ghana between December 2000 and July 2010. Verbal Autopsy is a technique which...

Automatic Text Classification (ATC) is an emerging technology with economic importance given the unprecedented growth of text data. This paper reports on work in progress to develop methods for predicting Cause of Death from Verbal Autopsy (VA) documents recommended for use in low-income countries by the World Health Organisation. VA documents cont...