Root cause analysis and health informatics

Root Cause Analysis (RCA) is the most widely used system analysis tool for investigating safety related incidents in healthcare. This contribution reviews RCA techniques, using a Health Informatics example, and discusses barriers to their successful uptake by healthcare organisations. It is concluded that a critical assessment to examine the uptake and evaluate the success of RCA, and other safety related techniques, within healthcare is long overdue

The use of computer-interpretable clinical guidelines to manage care complexities of patients with multimorbid conditions : a review

Clinical practice guidelines (CPGs) document evidence-based information and recommendations on treatment and management of conditions. CPGs usually focus on management of a single condition; however, in many cases a patient will be at the centre of multiple health conditions (multimorbidity). Multiple CPGs need to be followed in parallel, each managing a separate condition, which often results in instructions that may interact with each other, such as conflicts in medication. Furthermore, the impetus to deliver customised care based on patient-specific information, results in the need to be able to offer guidelines in an integrated manner, identifying and managing their interactions. In recent years, CPGs have been formatted as computer-interpretable guidelines (CIGs). This enables developing CIG-driven clinical decision support systems (CDSSs), which allow the development of IT applications that contribute to the systematic and reliable management of multiple guidelines. This study focuses on understanding the use of CIG-based CDSSs, in order to manage care complexities of patients with multimorbidity. The literature between 2011 and 2017 is reviewed, which covers: (a) the challenges and barriers in the care of multimorbid patients, (b) the role of CIGs in CDSS augmented delivery of care, and (c) the approaches to alleviating care complexities of multimorbid patients. Generating integrated care plans, detecting and resolving adverse interactions between treatments and medications, dealing with temporal constraints in care steps, supporting patient-caregiver shared decision making and maintaining the continuity of care are some of the approaches that are enabled using a CIG-based CDSS

Totally connected healthcare with TV white spaces

Recent technological advances in electronics, wireless communications and low cost medical sensors generated a plethora of Wearable Medical Devices (WMDs), which are capable of generating considerably large amounts of new, unstructured real-time data. This contribution outlines how this data can be propagated to a healthcare system through the internet, using long distance Radio Access Networks (RANs) and proposes a novel communication system architecture employing White Space Devices (WSD) to provide seamless connectivity to its users. Initial findings indicate that the proposed communication system can facilitate broadband services over a large geographical area taking advantage of the freely available TV White Spaces (TVWS)

Converting text to structured models of healthcare services

The paper presents a concise method for transforming textual representations of healthcare services, to a structured, semantically unambiguous modelling language. Employing the method can create structured models of the services that can then be analysed either manually or automatically

Evaluation of patient perception towards dynamic health data sharing using blockchain based digital consent with the Dovetail digital consent application : a cross sectional exploratory study

Background New patient-centric integrated care models are enabled by the capability to exchange the patient’s data amongst stakeholders, who each specialise in different aspects of the patient’s care. This requires a robust, trusted and flexible mechanism for patients to offer consent to share their data. Furthermore, new IT technologies make it easier to give patients more control over their data, including the right to revoke consent. These characteristics challenge the traditional paper-based, single-organisation-led consent process. The Dovetail digital consent application uses a mobile application and blockchain based infrastructure to offer this capability, as part of a pilot allowing patients to have their data shared amongst digital tools, empowering patients to manage their condition within an integrated care setting. Objective To evaluate patient perceptions towards existing consent processes, and the Dovetail blockchain based digital consent application as a means to manage data sharing in the context of diabetes care. Method Patients with diabetes at a General Practitioner practice were recruited. Data were collected using focus groups and questionnaires. Thematic analysis of the focus group transcripts and descriptive statistics of the questionnaires was performed. Results There was a lack of understanding of existing consent processes in place, and many patients did not have any recollection of having previously given consent. The digital consent application received favourable feedback, with patients recognising the value of the capability offered by the application. Patients overwhelmingly favoured the digital consent application over existing practice. Conclusions Digital consent was received favourably, with patients recognising that it addresses the main limitations of the current process. Feedback on potential improvements was received. Future work includes confirmation of results in a broader demographic sample and across multiple conditions

Understanding and de-risking the dependencies between operator and manufacturer of clinical IT

Health IT, in addition to benefits can also have unintended consequences both in terms of operational and business risks. Understanding the dependencies between operator and manufacturer as well as issues that need to be addressed during procurement is essential to increase confidence in the operation of health IT. The paper provides the context, and a number of issues health IT operators such as clinical organisations, need to investigate during acquisition of health IT

A method of justifying confidence in the safety of digital health interventions

Digital health interventions (DHIs) enable improvements in health strategy and address health system challenges. The World Health Organization provides a formal classification for DHIs. However, safety claims, about such interventions, vary in quality and are often vague as to how they are communicated between technical, clinical experts and stakeholders. By combining the classifications with a method of safety analysis and justification, we postulate confidence in the safety of digital technology. Confidence is resulting from the application of the framework to the DHI, using defined health system challenges. The framework and derived safety justifications can be applied to any DHI. It can serve as guideline for health strategy, regulatory and standards based compliance

Using event trees to inform quantitative analysis of healthcare services

The paper illustrates how event tree diagrams, used in safety engineering, can be applied to test the design of a healthcare service. Event tree diagrams can be employed to inform quantitative approaches to quality, by providing justification with respect to safety, of operational aspects to be monitored and measured

Generation of realistic synthetic validation healthcare datasets using generative adversarial networks

Background: Assurance of digital health interventions involves, amongst others, clinical validation, which requires large datasets to test the application in realistic clinical scenarios. Development of such datasets is time consuming and challenging in terms of maintaining patient anonymity and consent. Objective: The development of synthetic datasets that maintain the statistical properties of the real datasets. Method: An artificial neural network based, generative adversarial network was implemented and trained, using numerical and categorical variables, including ICD-9 codes from the MIMIC III dataset, to produce a synthetic dataset. Results: The synthetic dataset, exhibits a correlation matrix highly similar to the real dataset, good Jaccard similarity and passing the KS test. Conclusions: The proof of concept was successful with the approach being promising for further work

The challenges of balancing safety and security in implantable medical devices

Modern Implantable Medical Devices (IMDs), implement capabilities that have contributed significantly to patient outcomes, as well as quality of life. The ever increasing connectivity of IMD's does raise security concerns though there are instances where implemented security measures might impact on patient safety. The paper discusses challenges of addressing both of these attributes in parallel