Health intelligence: Discovering the process model using process mining by constructing Start-to-End patient journeys

Archived with the publisher's permission. Copyright © 2014, Australian Computer Society, Inc. This paper appeared at the Australasian Workshop on Health Informatics and Knowledge Management (HIKM 2014), Auckland, New Zealand. Conferences in Research and Practice in Information Technology (CRPIT), Vol. 153. J. Warren and K. Gray, Eds. Reproduction for academic, not-for profit purposes permitted provided this text is included.Australian Public Hospitals are continually engaged in various process improvement activities to improve patient care and to improve hospital efficiency as the demand for service intensifies. As a consequence there are many initiatives within the health sector focusing on gaining insight into the underlying health processes which are assessed for compliance with specified Key Performance Indicators (KPIs). Process Mining is classified as a Business Intelligence (BI) tool. The aim of process mining activities is to gain insight into the underlying process or processes. The fundamental element needed for process mining is a historical event log of a process. Generally, these event logs are easily sourced from Process Aware Information Systems (PAIS). Simulation is widely used by hospitals as a tool to study the complex hospital setting and for prediction. Generally, simulation models are constructed by ‘hand’. This paper presents a novel way of deriving event logs for health data in the absence of PAIS. The constructed event log is then used as an input for process mining activities taking advantage of existing process mining algorithms aiding the discovery of knowledge of the underlying processes which leads to Health Intelligence (HI). One such output of process mining activity, presented in this paper, is the discovery of process model for simulation using the derived event log as an input for process mining by constructing start-to-end patient journey. The study was undertaken using data from Flinders Medical Centre to gain insight into patient journeys from the point of admission to the Emergency Department (ED) until the patient is discharged from the hospital.

Gaining insight from patient journey data using process-oriented analysis approach

Hospitals are continually struggling to cater for the increasing demand for inpatient services. This is due to increased population, aging, and the rising incidence of chronic diseases associated with modern life. The high demand for hospital services leads to unpredictable bed availability, longer waiting period for acute admission, difficulties in keeping planned admission, stressed hospital staff, undesirable patient and family experience, as well as unclear long term impact on health care capacity. This study aims to derive some correlation between various factors contributing to ward occupancy rate and operation efficiency. The aim is also to discover the inpatient flow process model proposing to use process mining techniques combined with data analysis to depict the relationships among inpatients, wards and Length of Stay (LOS) in an effort to gain insight into factors that could be focused to relieve access block. Open source process mining software - ProM is used for this study. The study is done in collaboration with Flinders Medical Centre (FMC) using data from their Patient Journey Database as case study

Analysing homogenous patient journeys to assess quality of care for patients admitted outside of their ‘home-ward’

This study is the first to explore the quality of care based on the outlier or the inlier status of patients for a large heterogeneous General Medicine (GM) service at a busy public hospital. The study compared the quality of care between ward outliers and ward inliers based on a homogenous group of patients using Two-step clustering method. Contrary to common perception, ward outliers had overall shorter Length of Stay (LOS) than ward inliers. The study also was unable to support the perception of shorter LOS in the outlier group being associated with higher in-hospital mortality. The study confirmed that overall the outliers received inferior quality of care as discharge summaries for the outliers were delayed and more outliers were re-admitted within 7 days of discharge in comparison to the inliers

A tablet-based memory enhancement application for older users: design approach

This paper provides a case study of the design process undertaken in producing a mobile tablet memory assistant solution which was intended for older adults (\u3e65yo) living with early stage memory loss. We adopted an overall design framework consistent with “living laboratory” methodology, for which the associated design principles are: co-creation, multi-stakeholder participation, active user involvement, real-life setting, and multi-method approach. We describe here the detailed steps and provide examples of the application design decisions and outcomes, through successive stages of its evolution. Results of the various user engagements which informed our design choices and for validation of the artefact are presented

Addressing Pain Points: Thinking Outside the Telehealth Box

In this chapter, we present the synthesis of six pain points relating to Australia’s hospital congestion which is under crisis. The COVID-19 pandemic forced health services to respond rapidly to maintain continuity of care through telehealth. Some of these strategies were anticipated to be short-term arrangements, implemented quickly, and haphazardly deployed. While the health emergency accelerated the adoption of telehealth and models of remote care, this implementation was reactive. It is evident that our hospital systems continue to grapple with the issues of an aging population, expanding demand for mental health services, and escalating costs and too few resources. A shift in philosophy to address these and other recurring pain points presents opportunities to embrace virtual care beyond current implementations of telehealth

Protocol of a parallel group Randomized Control Trial (RCT) for Mobile-assisted Medication Adherence Support (Ma-MAS) intervention among Tuberculosis patients.

BackgroundNon-adherence to Tuberculosis (TB) medication is a serious threat to TB prevention and control programs, especially in resource-limited settings. The growth of the popularity of mobile phones provides opportunities to address non-adherence, by facilitating direct communication more frequently between healthcare providers and patients through SMS texts and voice phone calls. However, the existing evidence is inconsistent about the effect of SMS interventions on TB treatment adherence. Such interventions are also seldom developed based on appropriate theoretical foundations. Therefore, there is a reason to approach this problem more rigorously, by developing the intervention systematically with evidence-based theory and conducting the trial with strong measurement methods.MethodsThis study is a single-blind parallel-group design individual randomized control trial. A total of 186 participants (93 per group) will be individually randomized into one of the two groups with a 1:1 allocation ratio by a computer-generated algorithm. Group one (intervention) participants will receive daily SMS texts and weekly phone calls concerning their daily medication intake and medication refill clinic visit reminder and group two (control) participants will receive the same routine standard treatment care as the intervention group, but no SMS text and phone calls. All participants will be followed for two months of home-based self-administered medication during the continuation phases of the standard treatment period. Urine test for the presence of isoniazid (INH) drug metabolites in urine will be undertaken at the random point at the fourth and eighth weeks of intervention to measure medication adherence. Medication adherence will also be assessed by self-report measurements using the AIDS Clinical Trial Group adherence (ACTG) and Visual Analogue Scales (VAS) questionnaires, and clinic appointment attendance registration. Multivariable regression model analysis will be employed to assess the effect of the Ma-MAS intervention at a significance level of P-value DiscussionFor this trial, a mobile-assisted medication adherence intervention will first be developed systematically based on the Medical Research Council framework using appropriate behavioural theory and evidence. The trial will then evaluate the effect of SMS texts and phone calls on TB medication adherence. Evidence generated from this trial will be highly valuable for policymakers, program managers, and healthcare providers working in Ethiopia and beyond.Trial registrationThe trial is registered in the Pan-Africa Clinical Trials Registry with trial number PACTR202002831201865

Effect of zerumbone on scopolamine-induced memory impairment and anxiety-like behaviours in rats

Introduction: We investigated the effects of zerumbone (1 and 10 mg/kg) against hyperactivity, anxiety and memory impairment in scopolamine-induced dementia in Sprague-Dawley rats. Methods: Open field tests, elevated plus maze and Morris water maze were performed to assess general locomotor activity, anxiety-like behaviours and learning and memory processes respectively in rats pre treated with scopolamine. Results: Scopolamine-treated rats showed high total activity, stereotype, and total distance travelled in the open field arena, reduced number of entries to open arms, decreased the percentage of time spent in open arms and higher escape latency time in the Morris water maze test. Interestingly, single administration of zerumbone (1 and 10 mg/kg) reversed the hyperactivity, anxiety-like behaviours, and learning impairment effects of scopolamine in the three experimental model studied respectively. Discussion: Our findings demonstrated that the scopolamine-induced impairment of learning and memory was reversed by the administration of zerumbone. As a conclusion, our findings presented the positive effects of zerumbone on dementia-like behaviours in the animal model used and could possibly contribute for future research to manage hyperactivity, anxiety, and learning disabilities