Are we ready for conformance checking in healthcare? Measuring adherence to clinical guidelines: A scoping systematic literature review.

Clinical guidelines are recommendations of how to diagnose, treat, and manage a patient's medical condition. Health organizations must measure adherence to clinical guidelines to enhance the quality of service, but due to the complexity of the medical environment, there is no simple way of measuring adherence to clinical guidelines. This scoping review will systematically assess the criteria used to measure adherence to clinical guidelines in the past 20 years and explore the suitability of using process mining techniques. We will use a workflow protocol based on declarative and temporal constraints to translate the narrative text rules in the publications into a high-level process model. This approach will enable us to explore the main patterns and gaps identified when measuring adherence to clinical guidelines and how they affect the adoption of process mining techniques. The main contributions of this paper are a) a comprehensive analysis of the criteria used for measuring adherence, considering a diverse set of medical conditions b) a framework that will classify the level of complexity of the rules used to measure adherence based on declarative and temporal constraints c) list of key trends and gaps identified in the literature and how they relate to the use of process mining techniques in healthcare.

Process mining for healthcare: Characteristics and challenges.

Process mining techniques can be used to analyse business processes using the data logged during their execution. These techniques are leveraged in a wide range of domains, including healthcare, where it focuses mainly on the analysis of diagnostic, treatment, and organisational processes. Despite the huge amount of data generated in hospitals by staff and machinery involved in healthcare processes, there is no evidence of a systematic uptake of process mining beyond targeted case studies in a research context. When developing and using process mining in healthcare, distinguishing characteristics of healthcare processes such as their variability and patient-centred focus require targeted attention. Against this background, the Process-Oriented Data Science in Healthcare Alliance has been established to propagate the research and application of techniques targeting the data-driven improvement of healthcare processes. This paper, an initiative of the alliance, presents the distinguishing characteristics of the healthcare domain that need to be considered to successfully use process mining, as well as open challenges that need to be addressed by the community in the future.

[An appraisal of healthcare mobile applications]. / Apps y Medicina: una visión global y la situación chilena.

Mobile applications (Apps) may become effective aids in health care. Health Apps could reduce barriers such as access and costs and could be used to monitor symptoms, behaviors and even treatments. There is more evidence of their usefulness in nutrition, cardiovascular and mental health. Despite this, its current use is predominantly for information purposes. Healthcare App quality evaluation should consider both clinical and technological aspects since the evidence on its clinical effectiveness is still incipient and they have associated risks. In Chile, the use of mobile technology and Apps is increasing, but there are no regulations for their use. There are few national institutions oriented to the creation and development of Apps for healthcare, highlighting the Digital Transformation Committee, part of the Corporation for the Promotion of Production (CORFO) and the National Center for Health Information Systems (CENS). General recommendations for healthcare App development and use have been established. In this process, it would be beneficial to include actors involved in care. Given the progress of healthcare Apps worldwide and nationally, it is important that health professionals develop digital skills to maximize the potential benefit of these technologies.

[Anticoagulant efficacy of different pharmacological presentations of vitamin K antagonists]. / Eficacia en el control de la anticoagulación de los diferentes fármacos antagonistas de la vitamina K disponibles en Chile.

BACKGROUND: Vitamin K antagonist medications (VKA) are essential for the prevention of thromboembolic events, but their effectiveness is influenced by multiple factors, such as the type of medication chosen. AIM: To evaluate the efficacy in anticoagulant control of the bioequivalent and non-bioequivalent drugs of acenocoumarol compared to the reference drug. To evaluate the efficacy of warfarin bioequivalents available in Chile. To contrast the overall anticoagulant control efficacy between acenocoumarol and warfarin. MATERIAL AND METHODS: The results of 69333 outpatient oral anticoagulation controls were analyzed. Patient were separated in groups according to the drug that they used. Subsequently, the proportions of controls outside the range for each of acenocoumarol and warfarin bioequivalent drugs were compared. Acenocoumarol non-bioequivalent drugs were also compared with the reference drug. Acenocoumarol was compared with warfarin. RESULTS: Acenocoumarol bioequivalent drugs and the reference drug had a similar proportion of controls outside the range (Odds ratios (OR) 0.812; 0.969; 0.974 and 0.963). Non-bioequivalent drugs had a higher proportion than the reference drug (OR 1.561 and 2.037). Both warfarin brands have a similar proportion of controls outside of the range (OR 1.050). Acenocoumarol compared to warfarin had a significant higher proportion of controls outside the range (OR 1.191). CONCLUSIONS: The pharmacological presentation of vitamin K antagonists could influence anticoagulant control. Therefore, it is not prudent to switch these presentations frequently.

Discovering role interaction models in the Emergency Room using Process Mining.

OBJECTIVES: A coordinated collaboration among different healthcare professionals in Emergency Room (ER) processes is critical to promptly care for patients who arrive at the hospital in a delicate health condition, claiming for an immediate attention. The aims of this study are (i) to discover role interaction models in (ER) processes using process mining techniques; (ii) to understand how healthcare professionals are currently collaborating; and (iii) to provide useful knowledge that can help to improve ER processes. METHODS: A four step method based on process mining techniques is proposed. An ER process of a university hospital was considered as a case study, using 7160 episodes that contains specific ER episode attributes. RESULTS: Insights about how healthcare professionals collaborate in the ER was discovered, including the identification of a prevalent role interaction model along the major triage categories and specific role interaction models for different diagnoses. Also, common and exceptional professional interaction models were discovered at the role level. CONCLUSIONS: This study allows the discovery of role interaction models through the use of real-life clinical data and process mining techniques. Results show a useful way of providing relevant insights about how healthcare professionals collaborate, uncovering opportunities for process improvement.

Process mining in healthcare: A literature review.

Process Mining focuses on extracting knowledge from data generated and stored in corporate information systems in order to analyze executed processes. In the healthcare domain, process mining has been used in different case studies, with promising results. Accordingly, we have conducted a literature review of the usage of process mining in healthcare. The scope of this review covers 74 papers with associated case studies, all of which were analyzed according to eleven main aspects, including: process and data types; frequently posed questions; process mining techniques, perspectives and tools; methodologies; implementation and analysis strategies; geographical analysis; and medical fields. The most commonly used categories and emerging topics have been identified, as well as future trends, such as enhancing Hospital Information Systems to become process-aware. This review can: (i) provide a useful overview of the current work being undertaken in this field; (ii) help researchers to choose process mining algorithms, techniques, tools, methodologies and approaches for their own applications; and (iii) highlight the use of process mining to improve healthcare processes.

Endothelial Dysfunction and Cardiovascular Risk in Obstructive Sleep Apnea: A Review Article.

Obstructive sleep apnea (OSA) is a respiratory condition during sleep caused by repeated pauses in breathing due to upper airway obstruction. It is estimated that OSA affects 30% of the population, but only 10% are well diagnosed due to the absence of a well-defined symptomatology and poor screening tools for early diagnosis. OSA is associated to an endothelial dysfunction inducing several biological responses such as hypoxia, hypercapnia and oxidative stress, among others. OSA also triggers respiratory, nervous, metabolic, humoral and immunity system activations that increase the possibility of suffering a cardiovascular (CV) disease. In this review, we expose different studies that show the relationship between OSA and endothelial dysfunction and its association with CV pathologies like hypertension, and we define the most well-known treatments and their limitations. Additionally, we describe the potential future directions in OSA research, and we report clinical features such as endothelial progenitor cell alterations that could act as biomarkers for the development of new diagnostic tools and target therapies.

Process Mining to Explore Variations in Endometrial Cancer Pathways from GP Referral to First Treatment.

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 data from a hospital information system, created the process model, and analyzed the variations of the 62-day pathway from a General Practitioner referral to the first treatment in the hospital. We also analyzed the variations based on three different criteria: the type of the first treatment, the age at diagnosis, and the year of diagnosis. This approach should be of interest to others dealing with complex medical and healthcare processes.

Association between serum sphingolipids and eudaimonic well-being in white U.S. adults.

Emerging research has linked psychological well-being with many physiological markers as well as morbidity and mortality. In this analysis, the relationship between components of eudaimonic well-being and serum sphingolipids levels was investigated using data from a large national survey of middle-aged American adults (Midlife in the United States). Health behaviors (i.e., diet, exercise, and sleep) were also examined as potential mediators of these relationships. Serum levels of total ceramides-the main molecular class of sphingolipids previously associated with several disease conditions-were inversely linked with environmental mastery. In addition, significant correlations were found between specific ceramide, dihydroceramide, and hexosylceramides species with environmental mastery, purpose in life, and self-acceptance. Using hierarchical regression and mediation analyses, health behaviors appeared to mediate these associations. However, the link between ceramides and environmental mastery was partially independent of health behaviors, suggesting the role of additional mediating factors. These findings point to sphingolipid metabolism as a novel pathway of health benefits associated with psychological well-being. In particular, having a sense of environmental mastery may promote restorative behaviors and benefit health via improved blood sphingolipid profiles.

Process Mining of Disease Trajectories: A Literature Review.

Disease trajectories model patterns of disease over time and can be mined by extracting diagnosis codes from electronic health records (EHR). Process mining provides a mature set of methods and tools that has been used to mine care pathways using event data from EHRs and could be applied to disease trajectories. This paper presents a literature review on process mining related to mining disease trajectories using EHRs. Our review identified 156 papers of potential interest but only four papers which directly applied process mining to disease trajectory modelling. These four papers are presented in detail covering data source, size, selection criteria, selections of the process mining algorithms, trajectory definition strategies, model visualisations, and the methods of evaluation. The literature review lays the foundations for further research leveraging the established benefits of process mining for the emerging data mining of disease trajectories.

Mapping the Patient's Journey in Healthcare through Process Mining.

Nowadays, assessing and improving customer experience has become a priority, and has emerged as a key differentiator for business and organizations worldwide. A customer journey (CJ) is a strategic tool, a map of the steps customers follow when engaging with a company or organization to obtain a product or service. The increase of the need to obtain knowledge about customers' perceptions and feelings when interacting with participants, touchpoints, and channels through different stages of the customer life cycle. This study aims to describe the application of process mining techniques in healthcare as a tool to asses customer journeys. The appropriateness of the approach presented is illustrated through a case study of a key healthcare process. Results depict how a healthcare process can be mapped through the CJ components, and its analysis can serve to understand and improve the patient's experience.

The assessment of data quality issues for process mining in healthcare using Medical Information Mart for Intensive Care III, a freely available e-health record database.

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 constraints, and data quality. One solution to progress methodology development is to use a high-quality, freely available research dataset such as Medical Information Mart for Intensive Care III, a critical care database which contains the records of 46,520 intensive care unit patients over 12 years. Our article aims to (1) explore data quality issues for healthcare process mining using Medical Information Mart for Intensive Care III, (2) provide a structured assessment of Medical Information Mart for Intensive Care III data quality and challenge for process mining, and (3) provide a worked example of cancer treatment as a case study of process mining using Medical Information Mart for Intensive Care III to illustrate an approach and solution to data quality challenges. The electronic health record software was upgraded partway through the period over which data was collected and we use this event to explore the link between electronic health record system design and resulting process models.

Performance Analysis of Emergency Room Episodes Through Process Mining.

The performance analysis of Emergency Room episodes is aimed at providing decision makers with knowledge that allows them to decrease waiting times, reduce patient congestion, and improve the quality of care provided. In this case study, Process Mining is used to determine which activities, sub-processes, interactions, and characteristics of episodes explain why some episodes have a longer duration. The employed method and the results obtained are described in detail to serve as a guide for future performance analysis in this domain. It was discovered that the main cause of the increment in the episode duration is the occurrence of a loop between the Examination and Treatment sub-processes. It was also found out that as the episode severity increases, the number of repetitions of the Examination-Treatment loop increases as well. Moreover, the episodes in which this loop is more common are those that lead to Hospitalization as discharge destination. These findings might help to reduce the occurrence of this loop, in turn lowering the episode duration and, consequently, providing faster attention to more patients.

Process Mining in Primary Care: Avoiding Adverse Events Due to Hazardous Prescribing.

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 can cause gastro-intestinal bleeds (GiBs). Prescribing typically occurs during primary care; therefore we used this setting to attempt process mining. We extracted events (drug started, drug stopped, GiB) for understanding three prescribing pathways, and applied process mining. We found NSAIDs are often short-term prescriptions whereas antiplatelets are often long-term. This perhaps explains our finding that co-prescription of gastro-protection is more prevalent for antiplatelets than NSAIDs. We identified reasons why primary care data is harder to process mine and proposed solutions. Process mining primary care data is possible and likely useful for improving patient safety and reducing costs.

Toward Value-Based Healthcare through Interactive Process Mining in Emergency Rooms: The Stroke Case.

The application of Value-based Healthcare requires not only the identification of key processes in the clinical domain but also an adequate analysis of the value chain delivered to the patient. Data Science and Big Data approaches are technologies that enable the creation of accurate systems that model reality. However, classical Data Mining techniques are presented by professionals as black boxes. This evokes a lack of trust in those techniques in the medical domain. Process Mining technologies are human-understandable Data Science tools that can fill this gap to support the application of Value-Based Healthcare in real domains. The aim of this paper is to perform an analysis of the ways in which Process Mining techniques can support health professionals in the application of Value-Based Technologies. For this purpose, we explored these techniques by analyzing emergency processes and applying the critical timing of Stroke treatment and a Question-Driven methodology. To demonstrate the possibilities of Process Mining in the characterization of the emergency process, we used a real log with 9046 emergency episodes from 2145 stroke patients that occurred from January 2010 to June 2017. Our results demonstrate how Process Mining technology can highlight the differences between the flow of stroke patients compared with that of other patients in an emergency. Further, we show that support for health professionals can be provided by improving their understanding of these techniques and enhancing the quality of care.

Process Mining in Primary Care: A Literature Review.

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 inform the redesign of healthcare services. We reviewed the literature on process mining, to investigate the extent to which process mining has been applied to primary care, and to identify specific challenges that may arise in this setting. We identified 143 relevant papers, of which only a small minority (n=7) focused on primary care settings. Reported challenges included data quality (consistency and completeness of routinely collected data); selection of appropriate algorithms and tools; presentation of results; and utilization of results in real-world applications.

Apps y Medicina: una visión global y la situación chilena / An appraisal of healthcare mobile applications

Mobile applications (Apps) may become effective aids in health care. Health Apps could reduce barriers such as access and costs and could be used to monitor symptoms, behaviors and even treatments. There is more evidence of their usefulness in nutrition, cardiovascular and mental health. Despite this, its current use is predominantly for information purposes. Healthcare App quality evaluation should consider both clinical and technological aspects since the evidence on its clinical effectiveness is still incipient and they have associated risks. In Chile, the use of mobile technology and Apps is increasing, but there are no regulations for their use. There are few national institutions oriented to the creation and development of Apps for healthcare, highlighting the Digital Transformation Committee, part of the Corporation for the Promotion of Production (CORFO) and the National Center for Health Information Systems (CENS). General recommendations for healthcare App development and use have been established. In this process, it would be beneficial to include actors involved in care. Given the progress of healthcare Apps worldwide and nationally, it is important that health professionals develop digital skills to maximize the potential benefit of these technologies.

Eficacia en el control de la anticoagulación de los diferentes fármacos antagonistas de la vitamina K disponibles en Chile

Background: Vitamin K antagonist medications (VKA) are essential for the prevention of thromboembolic events, but their effectiveness is influenced by multiple factors, such as the type of medication chosen. Aim: To evaluate the efficacy in anticoagulant control of the bioequivalent and non-bioequivalent drugs of acenocoumarol compared to the reference drug. To evaluate the efficacy of warfarin bioequivalents available in Chile. To contrast the overall anticoagulant control efficacy between acenocoumarol and warfarin. Material and Methods: The results of 69333 outpatient oral anticoagulation controls were analyzed. Patient were separated in groups according to the drug that they used. Subsequently, the proportions of controls outside the range for each of acenocoumarol and warfarin bioequivalent drugs were compared. Acenocoumarol non-bioequivalent drugs were also compared with the reference drug. Acenocoumarol was compared with warfarin. Results: Acenocoumarol bioequivalent drugs and the reference drug had a similar proportion of controls outside the range (Odds ratios (OR) 0.812; 0.969; 0.974 and 0.963). Non-bioequivalent drugs had a higher proportion than the reference drug (OR 1.561 and 2.037). Both warfarin brands have a similar proportion of controls outside of the range (OR 1.050). Acenocoumarol compared to warfarin had a significant higher proportion of controls outside the range (OR 1.191). Conclusions: The pharmacological presentation of vitamin K antagonists could influence anticoagulant control. Therefore, it is not prudent to switch these presentations frequently.