Using Markov Models to Characterize and Predict Process Target Compliance

Processes are everywhere, covering disparate fields such as business, industry, telecommunications, and healthcare. They have previously been analyzed and modelled with the aim of improving understanding and efficiency as well as predicting future events and outcomes. In recent years, process mining has appeared with the aim of uncovering, observing, and improving processes, often based on data obtained from logs. This typically requires task identification, predicting future pathways, or identifying anomalies. We here concentrate on using Markov processes to assess compliance with completion targets or, inversely, we can determine appropriate targets for satisfactory performance. Previous work is extended to processes where there are a number of possible exit options, with potentially different target completion times. In particular, we look at distributions of the number of patients failing to meet targets, through time. The formulae are illustrated using data from a stroke patient unit, where there are multiple discharge destinations for patients, namely death, private nursing home, or the patient’s own home, where different discharge destinations may require disparate targets. Key performance indicators (KPIs) of this sort are commonplace in healthcare, business, and industrial processes. Markov models, or their extensions, have an important role to play in this work where the approach can be extended to include more expressive assumptions, with the aim of assessing compliance in complex scenarios

Clinical foundations and information architecture for the implementation of a federated health record service

Clinical care increasingly requires healthcare professionals to access patient record information that may be distributed across multiple sites, held in a variety of paper and electronic formats, and represented as mixtures of narrative, structured, coded and multi-media entries. A longitudinal person-centred electronic health record (EHR) is a much-anticipated solution to this problem, but its realisation is proving to be a long and complex journey. This Thesis explores the history and evolution of clinical information systems, and establishes a set of clinical and ethico-legal requirements for a generic EHR server. A federation approach (FHR) to harmonising distributed heterogeneous electronic clinical databases is advocated as the basis for meeting these requirements. A set of information models and middleware services, needed to implement a Federated Health Record server, are then described, thereby supporting access by clinical applications to a distributed set of feeder systems holding patient record information. The overall information architecture thus defined provides a generic means of combining such feeder system data to create a virtual electronic health record. Active collaboration in a wide range of clinical contexts, across the whole of Europe, has been central to the evolution of the approach taken. A federated health record server based on this architecture has been implemented by the author and colleagues and deployed in a live clinical environment in the Department of Cardiovascular Medicine at the Whittington Hospital in North London. This implementation experience has fed back into the conceptual development of the approach and has provided "proof-of-concept" verification of its completeness and practical utility. This research has benefited from collaboration with a wide range of healthcare sites, informatics organisations and industry across Europe though several EU Health Telematics projects: GEHR, Synapses, EHCR-SupA, SynEx, Medicate and 6WINIT. The information models published here have been placed in the public domain and have substantially contributed to two generations of CEN health informatics standards, including CEN TC/251 ENV 13606

Direct Oral Anticoagulants (DOACs) Use in Patients with Renal Insufficiency and Obesity

The popularity of Direct Oral AntiCoagulants (DOACs) for approved indications has risen dramatically following their introduction to the UK’s National Health Service (NHS) due to their convenience of dosing surpassing warfarin. However, prescribing these medications to high-risk patients has been challenging since mainly due to uncertainties around limited clinical trial data. Patients with chronic kidney disease and obesity pose a risk in particular as DOAC dosing was significantly affected by the variables such as, body weight and renal function. Due to the increased prevalence of CKD and obesity among the NHS patient population, the cost savings of preferring DOACs over warfarin was no longerbeneficial due to higher costs of mortalities and consequential morbidities (e.g., strokes and bleeding events). There are very limited interventional studies to rationalise the sample sizes to generalise findings. Therefore, a retrospective real-world data-driven approach was used in this thesis in an attempt to optimise the DOACs dosing regimen for patients with renal impairment and obesity.The main data-driven techniques used in the thesis employed machine learning and multivariate logistic regression (The systematic review in Chapter 6 describes the potential of in-silico modelling). These were applied to a pre-processed dataset, carefully collected from Calderdale and Huddersfield NHS Foundation Trust Hospitals, and profiled accordingly. The methodology was executed in three phases: overall analysis of the full dataset, comprising different BMI categories (Chapter 3), the data analyses comprising patients with morbid obesity only (Chapter 4), and the analyses of the overall dataset comprising patients with different categories of renal impairment (Chapter 5).The factors that influenced the clinical outcomes (such as mortality, ischaemic stroke, clinically relevant non-major bleeding (CRNMB), thromboembolism, length of stay, and emergency visits) in renal impairment and obesity were then determined following data analysis. Some of these factors, which included the individual DOACs administered, exerted a protective effect, while others worsened the safety and, or efficacy indicators. Also, it was found that some of the machine learning models employed in the thesis predicted the target (i.e., DOAC dose regimen) more accurately than others. Chapter 7 provides a discussion of the findings and makes reference and comparison with the existing evidence in the literature. More importantly, the results from patients with renal impairment and obesity were compared. Overall, the aim of generating real-world evidence for optimising DOACs safety and effectiveness in obesity and renal impairment was achieved. Our findings would support clinicians’ decision-making by reducing the uncertainty in DOACs prescribing.There is a need to validate the thesis findings with well-designed prospective studies. There is also a need to explore pharmacometrics analyses and advanced data-driven techniques such as reinforcement learning to arrive at more precise DOAC dosing estimates for patients with renal impairment and obesity

Front-Line Physicians' Satisfaction with Information Systems in Hospitals

Day-to-day operations management in hospital units is difficult due to continuously varying situations, several actors involved and a vast number of information systems in use. The aim of this study was to describe front-line physicians' satisfaction with existing information systems needed to support the day-to-day operations management in hospitals. A cross-sectional survey was used and data chosen with stratified random sampling were collected in nine hospitals. Data were analyzed with descriptive and inferential statistical methods. The response rate was 65 % (n = 111). The physicians reported that information systems support their decision making to some extent, but they do not improve access to information nor are they tailored for physicians. The respondents also reported that they need to use several information systems to support decision making and that they would prefer one information system to access important information. Improved information access would better support physicians' decision making and has the potential to improve the quality of decisions and speed up the decision making process.Peer reviewe

Telemedicine

Telemedicine is a rapidly evolving field as new technologies are implemented for example for the development of wireless sensors, quality data transmission. Using the Internet applications such as counseling, clinical consultation support and home care monitoring and management are more and more realized, which improves access to high level medical care in underserved areas. The 23 chapters of this book present manifold examples of telemedicine treating both theoretical and practical foundations and application scenarios

Task Shifting and Health System Design: Report of the Expert Panel on effective ways of investing in Health (EXPH)

Imagine a health professional in any European country who fell asleep in 1960 and awoke in a health facility in 2019. Much of what the observer saw would be quite different. There would be many more patients who were surviving into old age thanks to advances in therapy. Many of the treatments that they were receiving would be much more complex, involving radically new techniques such as laparoscopic or even robotic surgery, and they would be amazed by the advances in diagnostic capacity. Yet, in many health systems, some things would have changed very little. Among them would be the traditional roles of different types of health worker, with responsibility for certain task being reserved for those with particular qualifications based on custom and practice rather than on evidence. This opinion argues that this situation must change. There is now an impressive body of evidence that things can often be done differently. This does not mean that they should be. Change is only appropriate where it helps to achieve the goals of the health system and allows it to provide better care in ways that are more responsive to the needs of users. Tasks can be shifted from health workers to patients and their carers, to machines, and to other health workers. Where these shifts have been evaluated, they often, but not always, are associated with outcomes that are as good or even better than with the status quo. However, the results are often context dependent, and it cannot be assumed that what works in one situation will apply equally to another. What matters is the evidence, rather than traditional, but often obsolete rules. If a health system can ensure that tasks are being undertaken by those most appropriate to do them, it will enhance patient care. However, change is often difficult. Those involved must be convinced of the rationale for change and must be supported in implementing it. This should recognise that any change in roles will have implication for their status and thus existing hierarchies. It may also be necessary to challenge outdated legislative or regulatory barriers. Finally, it is essential the changes are evaluated, results are documented, and lessons are learned, both in relation to what works and in what circumstances. Task shifting, where it is based on robust evidence and implemented effectively, can make a major contribution to health outcomes and to the sustainability of health systems. It is not, however, a panacea for all of the challenges health systems face.Představte si zdravotnického odborníka v kterékoli evropské zemi, který usnul v roce 1960 a probudil se ve zdravotnickém zařízení v roce 2019. Hodně z toho, co by pozorovatel viděl, by bylo úplně jiné. Bylo by mnohem více pacientů, kteří přežili do stáří díky pokrokům v terapii. Mnoho z ošetření, které dostávali, by bylo mnohem složitější, zahrnovalo radikálně nové techniky, jako je laparoskopická nebo dokonce robotická chirurgie, a byl by ohromen pokrokem v diagnostickém rozsahu. Přesto by se v mnoha zdravotnických systémech některé věci změnily jen velmi málo. Mezi nimi by byly tradiční role různých typů zdravotnických pracovníků, přičemž odpovědnost za určitý úkol by byla vyhrazena těm, kteří mají zvláštní kvalifikaci založenou spíše na zvyklostech a praxi než na důkazech. Toto stanovisko tvrdí, že se tato situace musí změnit. Nyní existuje impozantní soubor důkazů, že věci lze často dělat jinak. To neznamená, že by měli být jinak dělány. Změna je vhodná pouze tam, kde pomáhá dosahovat cílů zdravotnického systému a umožňuje jí poskytovat lepší péči způsoby, které lépe reagují na potřeby uživatelů. Úkoly lze převádět ze zdravotnických pracovníků na pacienty a jejich pečovatele, na stroje a další zdravotnické pracovníky. Tam, kde byly tyto posuny vyhodnoceny, jsou často, ale ne vždy, spojeny s výsledky, které jsou stejně dobré nebo dokonce lepší než za současného stavu. Výsledky jsou však často závislé na kontextu a nelze předpokládat, že to, co funguje v jedné situaci, se bude vztahovat stejně na jiné. Důležitý je důkaz spíše než tradiční, ale často zastaralá pravidla. Pokud zdravotní systém může zajistit, že osoby, které jsou pro ně nejvhodnější, plní správně alokované úkoly, zlepší se péče o pacienty. Změna je však často obtížná. Zúčastněné strany musí být přesvědčeny o důvodech změny a musí být podporovány při jejich provádění. Musí uznat, že každá změna rolí bude mít dopad na jejich stav, a tedy na existující hierarchie. Může být také třeba změnit zastaralé legislativní nebo regulační překážky. Nakonec je nezbytné, aby byly změny vyhodnoceny, výsledky zdokumentovány a vedly k ponaučení, co funguje a za jakých okolností. Posun úkolů, činností a kompetencí, pokud je založen na spolehlivých důkazech a je účinně prováděn, může významně přispět k lepším výsledkům v oblasti zdraví a k udržitelnosti zdravotních systémů. Nejedná se však o všelék na všechny výzvy, kterým zdravotnické systémy čelí.Imagine a health professional in any European country who fell asleep in 1960 and awoke in a health facility in 2019. Much of what the observer saw would be quite different. There would be many more patients who were surviving into old age thanks to advances in therapy. Many of the treatments that they were receiving would be much more complex, involving radically new techniques such as laparoscopic or even robotic surgery, and they would be amazed by the advances in diagnostic capacity. Yet, in many health systems, some things would have changed very little. Among them would be the traditional roles of different types of health worker, with responsibility for certain task being reserved for those with particular qualifications based on custom and practice rather than on evidence. This opinion argues that this situation must change. There is now an impressive body of evidence that things can often be done differently. This does not mean that they should be. Change is only appropriate where it helps to achieve the goals of the health system and allows it to provide better care in ways that are more responsive to the needs of users. Tasks can be shifted from health workers to patients and their carers, to machines, and to other health workers. Where these shifts have been evaluated, they often, but not always, are associated with outcomes that are as good or even better than with the status quo. However, the results are often context dependent, and it cannot be assumed that what works in one situation will apply equally to another. What matters is the evidence, rather than traditional, but often obsolete rules. If a health system can ensure that tasks are being undertaken by those most appropriate to do them, it will enhance patient care. However, change is often difficult. Those involved must be convinced of the rationale for change and must be supported in implementing it. This should recognise that any change in roles will have implication for their status and thus existing hierarchies. It may also be necessary to challenge outdated legislative or regulatory barriers. Finally, it is essential the changes are evaluated, results are documented, and lessons are learned, both in relation to what works and in what circumstances. Task shifting, where it is based on robust evidence and implemented effectively, can make a major contribution to health outcomes and to the sustainability of health systems. It is not, however, a panacea for all of the challenges health systems face

Facilitating implementation of research evidence (FIRE): A randomised controlled trial and process evaluation of two models of facilitation informed by the promoting action on research implementation in health services (PARIHS) framework

Background: The PARIHS framework proposes that successful implementation of research evidence results from the complex interplay between the evidence to be implemented, the context of implementation and the facilitation processes employed. Facilitation is defined as a role (the facilitator) and a process (facilitation strategies/methods). Empirical evidence comparing different facilitation approaches is limited; this paper reports a trial of two different types of facilitation represented in the PARIHS framework. Methods: A pragmatic cluster randomised controlled trial with embedded process evaluation was undertaken in 24 long-term nursing care settings in four European countries. In each country, sites were randomly allocated to standard dissemination of urinary incontinence guideline recommendations and one of two types of external-internal facilitation, labelled Type A and B. Type A facilitation was a less resource intensive approach, underpinned by improvement methodology; Type B was a more intensive, emancipatory model of facilitation, informed by critical social science. The primary outcome was percentage documented compliance with guideline recommendations. Process evaluation was framed by realist methodology and involved quantitative and qualitative data collection from multiple sources. Findings: Quantitative data were obtained from reviews of 2313 records. Qualitative data included over 332 hours of observations of care; 39 hours observation of facilitation activity; 471 staff interviews; 174 resident interviews; 120 next of kin/carer interviews; and 125 stakeholder interviews. There were no significant differences in the primary outcome between study arms and all study arms improved over time. Process data revealed three core mechanisms that influenced the trajectory of the facilitation intervention: alignment of the facilitation approach to the needs and expectations of the internal facilitator and colleagues; engagement of internal facilitators and staff in attitude and action; and learning over time. Data from external facilitators demonstrated that the facilitation interventions did not work as planned, issues were cumulative and maintenance of fidelity was problematic. Implications for D&I Research: Evaluating an intervention - in this case facilitation - that is fluid and dynamic within the methodology of a randomised controlled trial is complex and challenging. For future studies, we suggest a theoretical approach to fidelity, with a focus on mechanisms, as opposed to dose and intensity of the intervention