We take a healthcare knowledge management approach to represent the Clinical Pathway (CP) as workflows. We have developed a semantic representation of CP in terms of a CP ontology that outlines the different clinical processes, their properties, constraints and relationships, and is able to computerize a range of CP. To model business workflows we use the graphical Business Process Modeling Notation (BPMN) modeling language that generates a BPMN ontology. To represent a CP as a BPMN workflow, we have developed a semantic interoperability (mapping ontology) framework between the CP ontology and the BPMN ontology. The mapping ontology allows the alignment of relations between two ontologies and ensures that a clinical process defined in the CP ontology is mapped to a standard BPMN workflow element. We execute our BPMN-based CP in the Lombardi workflow engine, whereby users can view the execution of the CP and make the necessary adjustments.

abstract: Background: Process mining (PM) using event log files is gaining popularity in healthcare to investigate clinical pathways. But it has many unique challenges. Clinical Pathways (CPs) are often complex and unstructured which results in spaghetti-like models. Moreover, the log files collected from the electronic health record (EHR) often contain noisy and incomplete data. Objective: Based on the traditional process mining technique of using event logs generated by an EHR, observational video data from rapid ethnography (RE) were combined to model, interpret, simplify and validate the perioperative (PeriOp) CPs. Method: The data collection and analysis pipeline consisted of the following steps: (1) Obtain RE data, (2) Obtain EHR event logs, (3) Generate CP from RE data, (4) Identify EHR interfaces and functionalities, (5) Analyze EHR functionalities to identify missing events, (6) Clean and preprocess event logs to remove noise, (7) Use PM to compute CP time metrics, (8) Further remove noise by removing outliers, (9) Mine CP from event logs and (10) Compare CPs resulting from RE and PM. Results: Four provider interviews and 1,917,059 event logs and 877 minutes of video ethnography recording EHRs interaction were collected. When mapping event logs to EHR functionalities, the intraoperative (IntraOp) event logs were more complete (45%) when compared with preoperative (35%) and postoperative (21.5%) event logs. After removing the noise (496 outliers) and calculating the duration of the PeriOp CP, the median was 189 minutes and the standard deviation was 291 minutes. Finally, RE data were analyzed to help identify most clinically relevant event logs and simplify spaghetti-like CPs resulting from PM. Conclusion: The study demonstrated the use of RE to help overcome challenges of automatic discovery of CPs. It also demonstrated that RE data could be used to identify relevant clinical tasks and incomplete data, remove noise (outliers), simplify CPs and validate mined CPs. / Dissertation/Thesis / Masters Thesis Computer Science 2020

The US spends more money on health care than other industrialized nations. Nevertheless, the US lags behind them in life expectancies, access to care, and other health indicators. This can be attributed to the numerous issues that afflict the US health care sector - the lack of a universal health coverage, increasing medical errors, over and under-treatment of patients, lack of standardization, and so on. It is believed that the structure of health care delivery as it exists in the US is broken, which consequently reduces the quality of provided care and increases costs. There is a growing consensus among the different players in the sector that a complete overhaul of the health care system is required. This study presents an approach to identify patient treatment over a cycle of care. Every medical condition has a care cycle over which treatment is provided. The complete cycle of care of most medical conditions comprise of both inpatient and ambulatory care and start from the onset of the disease to its resolution. There are established guidelines that state what care should be provided during various points of this cycle. It is important to identify and analyze the flow of patients through this cycle of care. Once the flow is identified, various analyses can then be conducted to identify bottlenecks, delays, redundancies and other issues that reduce efficiency and increase costs. Unfortunately, due to the fact that medical data is collected for either medical or billing purposes and not for an operational analysis, it is very difficult to analyze the flow of patients over this cycle of care. This study developed a framework to extract relevant patient medical information from existing administrative databases of health care organizations. This was used to create patient flow paths across a segment of the care cycle to enable the analysis of the care treatment. A case study was conducted at a federal health care provider to identify and map the flow over the care cycle of patients with lung cancer.

Introduction: Non-invasive ventilation (NIV) is an alternative method for providing safe mechanical ventilatory assistance to adult patients presenting with acute respiratory failure. Internationally the utilisation of NIV has increased by 400% during the past decade. The clinical pathway for NIV was collaboratively developed by the multidisciplinary team in the critical care unit in 2012, but implementation into practice did not realise as anticipated. As the burden of chronic disease rises in South Africa, the healthcare system is under pressure to provide evidence-based and costeffective care to more patients. Avoiding endotracheal intubation reduces the patient’s risk of complications which lengthens the hospitalisation period and the cost of hospitalisation. The utilisation of clinical pathways in the South African context is limited. Aim: The overall aim of the study was implementation and evaluation of the outcomes of a person-centred clinical pathway for non-invasive ventilation in the critical care unit. Research methodology: Mixed method design through a personcentred practice development approach utilising emancipatory action research. Several data collection methods are used throughout the phases of the study. A critical realist worldview was held which incorporated the principles of a person-centred approach through collaboration, inclusion and participation. The study was conducted in three interdependent and interrelated phases. During Phase 1, the culture of the critical care units was assessed using a validated 37-item questionnaire to establish the perceptions of the critical care nurses related to evidence implementation. A total of twenty-three registered nurses participated. Additionally, the content of the clinical pathway was adapted following a rigorous literature review in collaboration with the internal facilitators and validated via a Delphi with critical care experts. Phase 2 was dedicated to the collaborative development of an implementation strategy for the implementation of the clinical pathway in the critical care unit. During Phase 3, the outcomes of the implementation of the clinical pathway for NIV was evaluated. Findings: The collaborative utilisation of a person-centred practice development approach for the implementation and evaluation of the clinical pathway for NIV, aided the researcher in identifying moral injury amongst critical care nurses, which inhibits the implementation of research evidence into practice. / Thesis (PhD)--University of Pretoria, 2020. / Nursing Science / PhD / Unrestricted

No description available.

Objectives: To describe the use of standardized protocols (SPs) in emergency departments (EDs) across Ontario for childhood asthma and analyze the association of SPs with hospital admissions, 7-day ED re-visits, and outpatient follow-up visits. Methods: Population-based retrospective cohort study using health administrative data and survey data. EDs were categorized as having the optimal, other, or no SP for each outcome. Associations were tested with generalized estimating equations. Results: Between 2006/04/14-2009/02/28, 46,510 children with asthma were seen in 146 EDs, with 43 (29.5%) having SPs. Children treated in EDs with the optimal SP compared to no SP had no significant differences in hospital admissions (AOR 1.17; 95% CI 0.91, 1.49) or ED re-visits (AOR 1.09; 95% CI 0.85, 1.40) but were more likely to have follow-up visits (AOR 1.27; 95% CI 1.02, 1.59). Conclusions: SPs for childhood asthma are not common in Ontario EDs and had little impact on outcomes measured.

Objectives: To describe the use of standardized protocols (SPs) in emergency departments (EDs) across Ontario for childhood asthma and analyze the association of SPs with hospital admissions, 7-day ED re-visits, and outpatient follow-up visits. Methods: Population-based retrospective cohort study using health administrative data and survey data. EDs were categorized as having the optimal, other, or no SP for each outcome. Associations were tested with generalized estimating equations. Results: Between 2006/04/14-2009/02/28, 46,510 children with asthma were seen in 146 EDs, with 43 (29.5%) having SPs. Children treated in EDs with the optimal SP compared to no SP had no significant differences in hospital admissions (AOR 1.17; 95% CI 0.91, 1.49) or ED re-visits (AOR 1.09; 95% CI 0.85, 1.40) but were more likely to have follow-up visits (AOR 1.27; 95% CI 1.02, 1.59). Conclusions: SPs for childhood asthma are not common in Ontario EDs and had little impact on outcomes measured.

[pt] Sepse é considerada uma carga na saúde e na economia global. No Brasil, a sepse é a principal causa de morte em Unidades de Terapia Intensiva, bem como uma das principais causas de mortalidade hospitalar tardia. Nesta tese, inicialmente apresenta-se um relatório epidemiológico brasileiro de sepse contemplando 10 anos utilizando dados do Sistema Único de Saúde (SUS). Em seguida, mostra-se um estudo que apoia os estabelecimentos de saúde na avaliação e otimização de seus protocolos clínicos de sepse usando técnicas de mineração de processos. Um protocolo clínico consiste em um plano de cuidados bem definido, que inclui uma ordem clara e tempo para a execução de intervenções com resultados esperados. Durante a execução deste estudo, identificou-se a falta de técnicas de mineração de processos para a otimização de protocolos clínicos. Assim, neste trabalho foi proposta, implementada e testada uma nova técnica de mineração de processos que auxilia usuários na otimização de seus processos. Esta técnica foi aplicada para a melhoria de protocolos clínicos. A técnica desenvolvida (Multi-CAT) identifica e destaca um conjunto de atividades e subsequências que promovem resultados positivos ou negativos, considerando múltiplos critérios simultâneos. A técnica foi aplicada com sucesso em um protocolo clínico de sepse, na qual foram adquiridas mais recomendações de otimização do que foi previamente obtido em análise manual. Conclui-se que a técnica desenvolvida apresenta grande potencial para auxiliar na otimização de processos com bom desempenho. No cenário de testes mais complexo, com 58 atividades, 50.000 casos e 14.451 variantes, Multi-CAT utilizou 2,04 minutos para executar a análise. Para finalizar, a ferramenta foi validada em dois processos distintos, indicando potencial para ser aplicada em outras áreas de negócio. / [en] Sepsis is considered a worldwide health and economic burden. In Brazil, sepsis is the major cause of death in Intensive Care Units, as well as, one of the main causes of late hospital mortality. In this thesis, we first provide a 10 years population-level epidemiology report of sepsis in Brazil, using data from the Brazilian Unified Health System. Secondly, we present a research study that supports health care facilities in the evaluation and optimization of their sepsis clinical pathways (CP) using process mining techniques. A CP consists of a well-defined care plan, which includes a clear order and time for the execution of interventions with expected outcomes. During the execution of this study, it became clear for us the lack of existing process mining techniques for the optimization of CPs. Thus, we proposed, implemented and tested a novel process mining technique that supports users to improve their processes and we applied it for CP improvement. Our developed technique (Multi-CAT) identifies and highlights a set of activities and sub-sequences that provide positive or negative outcomes considering multiple simultaneous criteria. We successfully applied our technique in a real sepsis CP, and we acquired more optimization insights that we got in our previous manual analysis. We conclude that Multi-CAT has high potential to help in the optimization of processes with a good performance. In the most complex test scenario, with 58 activities, 50,000 cases and 14,451 variants, Multi-CAT took 2.04 minutes to execute the analysis. Finally, the tool was validated in two different processes, indicating potential capability to be applicable to other business areas.

Projektet genomfördes i samarbete med Siemens Healthineers i syfte att utreda möjligheter till att prognostisera vårdflöden. Det genom att undersöka hur big data tillsammans med maskininlärning kan utnyttjas för prediktiv analys. Projektet utgjordes av två fallstudier med mål att, baserat på data från tidigare MRT-undersökningar, förutspå undersökningstider för kommande undersökningar respektive identifiera patienter som riskerar att missa inbokad undersökning. Fallstudierna utfördes med hjälp av programmeringsspråket R och tre olika inbyggda funktioner för maskininlärning användes för att ta fram prediktiva modeller för respektive fallstudie. Resultaten från fallstudierna gav en indikation på att det med en större datamängd av bättre kvalitet skulle vara möjligt att förutspå undersökningstider och vilka patienter som riskerar att missa sin inbokade undersökning. Det talar för att den här typen av prediktiva analyser kan användas för att prognostisera vårdflöden, något som skulle kunna bidra till ökad effektivitet och kortare väntetider i vården. / This project was performed in cooperation with Siemens Healthineers. The project aimed to investigate possibilities to forecast healthcare processes by investigating how big data and machine learning can be used for predictive analytics. The project consisted of two separate case studies. Based on data from previous MRI examinations the aim was to investigate if it is possible to predict duration of MRI examinations and identify potential no show patients. The case studies were performed with the programming language R and three machine learning methods were used to develop predictive models for each case study. The results from the case studies indicate that with a greater amount of data of better quality it would be possible to predict duration of MRI examinations and potential no show patients. The conclusion is that these types of predictive models can be used to forecast healthcare processes. This could contribute to increased effectivity and reduced waiting time in healthcare.

Standardisation of professional work is a major policy concern to ensure quality and efficiency of services and a number of hospitals are now focusing on the use of clinical pathways as an important tool to standardise their work. This study sheds light on the processes set in motion when notions of standardisation meet local practice. In order to gain insight into what clinical pathways mean for professional work in mental health care, the focus of the study was to explore the contexts in which standardisation by “rule production” takes place. Two empirical cases from Norwegian mental health care show how dedicated professionals are in charge of carrying out the standardisation work, strongly influenced by a steering framework of defined governmental policies where employee involvement and responsibility ensured loyalty to the idea.  Along with a “package” of ideas, new bodies and techniques, clinical pathways contribute to the institutionalisation of prima facie knowledge in demonstrating that evidence basing is linked to steering and control of employees. Thus, professional autonomy is threatened in an insidious way: through the institutionalisation of evidence-based knowledge as ‘prima facie’ knowledge in combination with professionals who standardise and control their own work. The thesis therefore concludes that the control of professional work has now become a complex and sophisticated process where professional work is “controlled by knowledge”.