Flinders Digital Health Research Centre Collected Works

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Analysing homogenous patient journeys to assess quality of care for patients admitted outside of their ‘home-ward’
(Australian Computer Society, 2013) Perimal-Lewis, Lua; Qin, Shaowen; Thompson, Campbell Henry; Hakendorf, Paul Haylett
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.
Assessing Viewing Pattern Consistency in Mammogram Readers
(Australian Computer Society, 2009) Maeder, Anthony; Fookes, C
Breast cancer screening programs typically require very large volumes of x-ray images (mammograms) to be viewed by highly experienced human readers. The readers can recognise a wide range of different visible features indicative of clinically abnormal situations, which they use as a basis to generate a report on their findings. Errors in reporting can occur if the readers fail to identify a particular feature of interest for further visual inspection during the viewing process. This risk is typically reduced by training readers to follow a particular viewing path through an image, which they should be able to apply consistently. Knowledge of the extent of consistency in this viewing behaviour within and between viewers would inform the development of an automated checking approach, based on monitoring of viewer visual attention. This paper presents an analysis of some reader viewing pattern profiles obtained using eye tracking with an infra red computer vision system, as a basis for developing a suitable consistency assessment model. .
Characterizing Image Properties for Digital Mammograms
(Australian Computer Society, 2009) Nguyen, Anthony; Dowling, Jason A; Maeder, Anthony; Nguyen, Phuong; Brunton, Emma
Adoption of computed radiology (CR) and direct radiology (DR) imaging for screening mammograms in many countries alongside digitally scanned film mammograms has resulted in a wide range of different intrinsic (physical) characteristics of images becoming commonplace. It is sometimes conjectured that viewer performance could be adversely affected by this wider variability, as compared with the variability that was formerly experienced with film only. This paper identifies several aspects of the image characteristics relevant to viewer perception, including intensity properties (such as contrast), spatial properties (such as texture) and structure properties (such as breast density). We then provide quantitative descriptions of the variability of these properties over a test set of 12 screening mammograms drawn from three different modalities and containing a typical mix of screening cases..
Cloud-based Medical Image Collection Database with Automated Annotation
(IARIA, 2016) Maeder, Anthony; Planitz, B
Typical medical image annotation systems use manual annotation or complex proprietary software such as computer-assisted-diagnosis. A more objective approach is required to achieve generalised Content Based Image Retrieval (CBIR) functionality. The Automated Medical Image Collection Annotation (AMICA) toolkit described here addresses this need. A range of content analysis functions are provided to tag images and image regions. The user uploads a DICOM file to an online portal and the software finds and displays images that have similar characteristics. AMICA has been developed to run in the Microsoft cloud environment using the Windows Azure platform, to cater for the storage requirements of typical large medical image databases.
Clustering Multivariate Time Series Using Hidden Markov Models
(MDPI, 2014-03-06) Ghassem Pour, S; Girosi, F; Maeder, Anthony
In this paper we describe an algorithm for clustering multivariate time series with variables taking both categorical and continuous values. Time series of this type are frequent in health care, where they represent the health trajectories of individuals. The problem is challenging because categorical variables make it difficult to define a meaningful distance between trajectories. We propose an approach based on Hidden Markov Models (HMMs), where we first map each trajectory into an HMM, then define a suitable distance between HMMs and finally proceed to cluster the HMMs with a method based on a distance matrix. We test our approach on a simulated, but realistic, data set of 1,255 trajectories of individuals of age 45 and over, on a synthetic validation set with known clustering structure, and on a smaller set of 268 trajectories extracted from the longitudinal Health and Retirement Survey. The proposed method can be implemented quite simply using standard packages in R and Matlab and may be a good candidate for solving the difficult problem of clustering multivariate time series with categorical variables using tools that do not require advanced statistic knowledge, and therefore are accessible to a wide range of researchers.
Comparing Data Mining with Ensemble Classiﬁcation of Breast Cancer Masses in Digital Mammograms
(AIH, 2012) Ghassem Pour, S; McLeod, P; Verma, B; Maeder, Anthony
Medical diagnosis sometimes involves detecting subtle indi-cations of a disease or condition amongst a background of diverse healthy individuals. The amount of information that is available for discover-ing such indications for mammography is large and has been growing at an exponential rate, due to population wide screening programmes. In order to analyse this information data mining techniques have been utilised by various researchers. A question that arises is: do ﬂexible data mining techniques have comparable accuracy to dedicated classiﬁcation techniques for medical diagnostic processes? This research compares a model-based data mining technique with a neural network classiﬁcation technique and the improvements possible using an ensemble approach. A publicly available breast cancer benchmark database is used to determine the utility of the techniques and compare the accuracies obtained.
A Comparison Between Phone-Based Psychotherapy With and Without Text Messaging Support In Between Sessions for Crisis Patients
(Journal of Medical Internet Research, 2014-10) Furber, Gareth Vince; Jones, Gabby; Healey, David; Bidargaddi, Niranjan
Background Individually tailored text messaging interventions have the potential to improve the outcomes of traditional psychotherapy through improved symptom monitoring, prompts for between-session activities and psychoeducation. Objective To explore the use of individually tailored between-session Short Message Service (SMS) as an adjunct to telephone-based psychotherapy for consumers who present to the Emergency Department (ED) in situational and/or emotional crises. Method Over a 4-month period, two therapists offered 68 prospective consumers of a telephone-based psychotherapy service individually tailored between-session SMS alongside their telephone-based psychotherapy. Attendance and clinical outcomes (depression, anxiety, functional impairment) of those receiving messages were compared against a historical control group (n=157) who received telephone psychotherapy only. Results A total of 66% (n = 45) of the consumers offered SMS accepted the intervention. A total of 432 messages were sent over the course of the trial, the majority involving some kind of psychoeducation or reminders to engage in therapy goals. There were no significant differences in clinical outcomes between consumers who received the SMS and those in the control group. There was a trend for participants in the intervention group to attend fewer sessions than those in the control group (3.7 (SD = 1.9) versus 4.4 (SD = 2.3). Conclusions Both groups showed significant improvement over time. Individually tailored SMS were not found to improve clinical outcomes in consumers receiving telephone-based psychotherapy, but the study was underpowered, given the effect sizes noted and the significance level chosen. Given the ease of implementation and positive feedback from therapists and clients, individually tailored SMS should be explored further in future trials with a focus on enhancing the clinical impact of the tailored SMS, and utilising designs with additional power to test for between-group effects
A conceptual framework for secure mobile health
(International Society for Telemedicine and eHealth, 2013) William, P; Maeder, Anthony
Mobile health is characterised by its diversity of applicability, in a multifaceted and multidisciplinary healthcare delivery continuum. In an environment of rapid change with the increasing development of mobile health, issues related to security and privacy must be well thought out. The different competing tensions in the development of mobile health from the device technologies and associated regulation, to clinical workflow and patient acceptance, require a framework for security that reflects the complex structure of this emerging field. There are three distinct associated elements that require investigation: technology, clinical, and human factors. Each of these elements consists of multiple aspects and there are specific risk factors to be addressed successively and co-dependently in each case. The fundamental approach to defining a conceptual framework for secure use of mobile health requires systematic identification of properties for the tensions and critical factors which impact these elements. The resulting conceptual framework presented here can be used for new critique, augmentation or deployment of mobile health solutions from the perspective of data protection and security.
Constructing a Synthetic Longitudinal Health Dataset for Data Mining
(IARIA, 2012) Ghassem Pour, S; Maeder, Anthony; Jorm, L
The traditional approach to epidemiological research is to analyse data in an explicit statistical fashion, attempting to answer a question or test a hypothesis. However, increasing experience in the application of data mining and exploratory data analysis methods suggests that valuable information can be obtained from large datasets using these less constrained approaches. Available data mining techniques, such as clustering, have mainly been applied to cross-sectional point-in-time data. However, health datasets often include repeated observations for individuals and so researchers are interested in following their health trajectories. This requires methods for analysis of multiple-points-over-time or longitudinal data. Here, we describe an approach to construct a synthetic longitudinal version of a major population health dataset in which clusters merge and split over time, to investigate the utility of clustering for discovering time sequence based patterns.
Development of an Online Well-Being Intervention for Young People: An Evaluation Protocol
(JMIR Publications, 2015-04) Antezana, Gaston; Bidargaddi, Niranjan; Blake, Victoria; Schrader, Geoffrey; Kaambwa, Billingsley; Quinn, Stephen; Orlowski, Simone; Winsall, Megan; Battersby, Malcolm Wayne
Background: Research has shown that improving well-being using positive mental health interventions can be useful for predicting and preventing mental illness. Implementing online interventions may be an effective way to reach young people, given their familiarity with technology. Objective: This study will assess the effectiveness of a website called the “Online Wellbeing Centre (OWC),” designed for the support and improvement of mental health and well-being in young Australians aged between 16 and 25 years. As the active component of the study, the OWC will introduce a self-guided app recommendation service called “The Toolbox: The best apps for your brain and body” developed by ReachOut.com. The Toolbox is a responsive website that serves as a personalized, ongoing recommendation service for technology-based tools and apps to improve well-being. It allows users to personalize their experience according to their individual needs. Methods: This study will be a two-arm, randomized controlled trial following a wait-list control design. The primary outcome will be changes in psychological well-being measured by the Mental Health Continuum Short Form. The secondary outcomes will be drawn from a subsample of participants and will include depression scores measured by the Center for Epidemiologic Studies Depression Scale, and quality of life measured by the Assessment of Quality of Life-four dimensions (AQOL-4D) index. Cost-effectiveness analysis will be conducted based on a primary outcome of cost per unique visit to the OWC. Utility-based outcomes will also be incorporated into the analysis allowing a secondary outcome to be cost per quality-adjusted life year gained (based on the AQOL-4D values). Resource use associated with both the intervention and control groups will be collected using a customized questionnaire. Online- and community-based recruitment strategies will be implemented, and the effectiveness of each approach will be analyzed. Participants will be recruited from the general Australian population and randomized online. The trial will last for 4 weeks. Results: Small but clinically significant increases in well-being symptoms are expected to be detected in the intervention group compared with the control group.
Discovering itemset interactions
(Australian Computer Society, 2009) Liang, Ping; Roddick, John Francis; Ceglar, Aaron John; Shillabeer, Anna; de Vries, Denise Bernadette
Itemsets, which are treated as intermediate results in association mining, have attracted significant research due to the inherent complexity of their generation. However, there is currently little literature focusing upon the interactions between itemsets, the nature of which may potentially contain valuable information. This paper presents a novel tree-based approach to discovering item-set interactions, a task which cannot be undertaken by current association mining techniques.
e-Research Meets e-Health
(Australian Computer Society, 2008) Maeder, Anthony
This paper considers some key aspects of e-Research methodology and infrastructure which are relevant to e-Health, and identifies some promising areas in e-Health where these aspects could be used beneficially .
Effectiveness of a Web- and Mobile Phone-Based Intervention to Promote Physical Activity and Healthy Eating in Middle-Aged Males: Randomized Controlled Trial of the ManUp Study
(Journal of Medical Internet Research, 2014) Duncan, Mitch J; Vandelanotte, Corneel; Kolt, Gregory S; Rosenkranz, Richard R; Caperchione, Cristina M; George, Emma S; Ding, Hang; Hooker, Cindy; Karunanithi, Mohan; Maeder, Anthony; Noakes, Manny; Tague, Rhys; Taylor, Pennie; Viljoen, Pierre; Mummery, W Kerry
Background: The high number of adult males engaging in low levels of physical activity and poor dietary practices, and the health risks posed by these behaviors, necessitate broad-reaching intervention strategies. Information technology (IT)-based (Web and mobile phone) interventions can be accessed by large numbers of people, yet there are few reported IT-based interventions targeting males’ physical activity and dietary practices. Objective: This study examines the effectiveness of a 9-month IT-based intervention (ManUp) to improve the physical activity, dietary behaviors, and health literacy in middle-aged males compared to a print-based intervention. Methods: Participants, recruited offline (eg, newspaper ads), were randomized into either an IT-based or print-based intervention arm on a 2:1 basis in favor of the fully automated IT-based arm. Participants were adult males aged 35-54 years living in 2 regional cities in Queensland, Australia, who could access the Internet, owned a mobile phone, and were able to increase their activity level. The intervention, ManUp, was based on social cognitive and self-regulation theories and specifically designed to target males. Educational materials were provided and self-monitoring of physical activity and nutrition behaviors was promoted. Intervention content was the same in both intervention arms; only the delivery mode differed. Content could be accessed throughout the 9-month study period. Participants’ physical activity, dietary behaviors, and health literacy were measured using online surveys at baseline, 3 months, and 9 months. Results: A total of 301 participants completed baseline assessments, 205 in the IT-based arm and 96 in the print-based arm. A total of 124 participants completed all 3 assessments. There were no significant between-group differences in physical activity and dietary behaviors (P≥.05). Participants reported an increased number of minutes and sessions of physical activity at 3 months (exp(β)=1.45, 95% CI 1.09-1.95; exp(β)=1.61, 95% CI 1.17-2.22) and 9 months (exp(β)=1.55, 95% CI 1.14-2.10; exp(β)=1.51, 95% CI 1.15-2.00). Overall dietary behaviors improved at 3 months (exp(β)=1.07, 95% CI 1.03-1.11) and 9 months (exp(β)=1.10, 95% CI 1.05-1.13). The proportion of participants in both groups eating higher-fiber bread and low-fat milk increased at 3 months (exp(β)=2.25, 95% CI 1.29-3.92; exp(β)=1.65, 95% CI 1.07-2.55). Participants in the IT-based arm were less likely to report that 30 minutes of physical activity per day improves health (exp(β)=0.48, 95% CI 0.26-0.90) and more likely to report that vigorous intensity physical activity 3 times per week is essential (exp(β)=1.70, 95% CI 1.02-2.82). The average number of log-ins to the IT platform at 3 and 9 months was 6.99 (SE 0.86) and 9.22 (SE 1.47), respectively. The average number of self-monitoring entries at 3 and 9 months was 16.69 (SE 2.38) and 22.51 (SE 3.79), respectively. Conclusions: The ManUp intervention was effective in improving physical activity and dietary behaviors in middle-aged males with no significant differences between IT- and print-based delivery modes.
Effectiveness of a website and mobile phone based physical activity and nutrition intervention for middle-aged males: Trial protocol and baseline findings of the ManUp Study
(BioMed Central, 2012-08-15) Duncan, Mitch J; Vandelanotte, Corneel; Rosenkranz, Richard R; Caperchione, Cristina M; Ding, Hang; Ellison, Marcus; George, Emma S; Hooker, Cindy; Karunanithi, Mohan; Kolt, Gregory S; Maeder, Anthony; Noakes, Manny; Tague, Rhys; Taylor, Pennie; Viljoen, Pierre; Mummery, W Kerry
Background: Compared to females, males experience higher rates of chronic disease and mortality, yet few health promotion initiatives are specifically aimed at men. Therefore, the aim of the ManUp Study is to examine the effectiveness of an IT-based intervention to increase the physical activity and nutrition behaviour and literacy in middle-aged males (aged 35–54 years). Method/Design: The study design was a two-arm randomised controlled trial, having an IT-based (applying website and mobile phones) and a print-based intervention arm, to deliver intervention materials and to promote self-monitoring of physical activity and nutrition behaviours. Participants (n = 317) were randomised on a 2:1 ratio in favour of the IT-based intervention arm. Both intervention arms completed assessments at baseline, 3, and 9 months. All participants completed self-report assessments of physical activity, sitting time, nutrition behaviours, physical activity and nutrition literacy, perceived health status and socio-demographic characteristics. A randomly selected sub-sample in the IT-based (n = 61) and print-based (n = 30) intervention arms completed objective measures of height, weight, waist circumference, and physical activity as measured by accelerometer (Actigraph GT3X). The average age of participants in the IT-based and print-based intervention arm was 44.2 and 43.8 years respectively. The majority of participants were employed in professional occupations (IT-based 57.6%, Print-based 54.2%) and were overweight or obese (IT-based 90.8%, Print-based 87.3%). At baseline a lower proportion of participants in the IT-based (70.2%) group agreed that 30 minutes of physical activity each day is enough to improve health compared to the print-based (82.3%) group (p = .026). The IT-based group consumed a significantly lower number of serves of red meat in the previous week, compared to the print-based group (p = .017). No other significant between-group differences were observed at baseline. Discussion: The ManUp Study will examine the effectiveness of an IT-based approach to improve physical activity and nutrition behaviour and literacy. Study outcomes will provide much needed information on the efficacy of this approach in middle aged males, which is important due to the large proportions of males at risk, and the potential reach of IT-based interventions.
An eHealth Intervention for Patients in Rural Areas: Preliminary Findings From a Pilot Feasibility Study
(JMIR Publications, 2014-06) Schrader, Geoffrey; Bidargaddi, Niranjan; Harris, Melanie; Newman, Lareen Ann; Lynn, Sarah; Peterson, Leigh; Battersby, Malcolm Wayne
Background: eHealth facilitation of chronic disease management has potential to increase engagement and effectiveness and extend access to care in rural areas. Objective: The objective of this study was to demonstrate the feasibility and acceptability of an eHealth system for the management of chronic conditions in a rural setting. Methods: We developed an online management program which incorporated content from the Flinders Chronic Condition Management Program (Flinders Program) and used an existing software platform (goACT), which is accessible by patients and health care workers using either Web-enabled mobile phone or Internet, enabling communication between patients and clinicians. We analyzed the impact of this eHealth system using qualitative and simple quantitative methods. Results: The eHealth system was piloted with 8 recently hospitalized patients from rural areas, average age 63 (SD 9) years, each with an average of 5 chronic conditions and high level of psychological distress with an average K10 score of 32.20 (SD 5.81). Study participants interacted with the eHealth system. The average number of logins to the eHealth system by the study participants was 26.4 (SD 23.5) over 29 weeks. The login activity was higher early in the week. Conclusions: The pilot demonstrated the feasibility of implementing and delivering a chronic disease management program using a Web-based patient-clinician application. A qualitative analysis revealed burden of illness and low levels of information technology literacy as barriers to patient engagement.
Establishing a lineage for medical knowledge discovery
(Australian Computer Society, 2007) Roddick, John Francis; Shillabeer, Annette
Medical science has a long history characterised by incidents of extraordinary insights that have resulted in a paradigm shift in the methodologies and approaches used and have moved the discipline forward. While knowledge discovery has much to offer medicine, it cannot be done in ignorance of either this history or the norms of modern medical investigation. This paper explores the lineage of medical knowledge acquisition and discusses the adverse perceptions that data mining techniques will have to surmount to gain acceptance.
Evaluating success of mobile health projects in the developing world
(IOS Press, 2014) Ginige, J A; Maeder, Anthony; Long, V
Many mobile health (mHealth) projects, typically deploying pilot or small scale implementations, have been undertaken in developing world settings and reported with a widely varying range of claims being made on their effectiveness and benefits. As a result, there is little evidence for which aspects of such projects lead to successful outcomes. This paper describes a literature review of papers from PubMed undertaken to identify strong contributions to execution and evaluation of mHealth projects in developing world settings, and suggests a template for classifying the main success factors to assist with collating evidence in the future.
Evaluation Study of Australian Telehealth Projects
(Australian Computer Society, 2015-01-27) Poultney, N; Maeder, Anthony; Basilakis, J
This paper provides an overview of selected telehealth projects involving pilot or trial implementations, undertaken in Australia in the period since 2000, which have undergone substantial formal evaluations reported in the peer reviewed scientific literature. Barriers and enablers reported for these telehealth projects are identified and the evaluation aspects are presented using a recently proposed generalised evaluation framework.
Examining Participant Engagement in an Information Technology-Based Physical Activity and Nutrition Intervention for Men: The Manup Randomized Controlled Trial
(JMIR Publications, 2014-01-03) Short, Camille E; Vandelanotte, Corneel; Dixon, Marcus W; Rosenkranz, Richard R; Caperchione, Cristina M; Hooker, Cindy; Karunanithi, Mohan; Kolt, Gregory S; Maeder, Anthony; Ding, Hang; Taylor, Pennie; Duncan, Mitch J
Background:Males experience a shorter life expectancy and higher rates of chronic diseases compared to their female counterparts. To improve health outcomes among males, interventions specifically developed for males that target their health behaviors are needed. Information technology (IT)-based interventions may be a promising intervention approach in this population group, however, little is known about how to maximize engagement and retention in Web-based programs. Objective:The current study sought to explore attributes hypothesized to influence user engagement among a subsample of participants from the ManUp study, a randomized controlled trial testing the efficacy of an interactive Web-based intervention for promoting physical activity and nutrition among middle-aged males. Methods: Semistructured interviews were conducted and audiotaped with 20 of the ManUp participants. Interview questions were based on a conceptual model of engagement and centered on why participants took part in the study, what they liked and did not like about the intervention they received, and how they think the intervention could be improved. Interview recordings were transcribed and coded into themes. Results: There were five themes that were identified in the study. These themes were: (1) users’ motives, (2) users’ desired outcomes, (3) users’ positive experiences, (4) users’ negative emotions, and (5) attributes desired by user. Conclusions: There is little research in the field that has explored user experiences in human-computer interactions and how such experiences may relate to engagement, especially among males. Although not conclusive, the current study provides some insight into what personal attributes of middle-aged males (such as their key motives and goals for participating) and attributes of the intervention materials (such as usability, control, and interactivity) may impact on user engagement in this group. These findings will be helpful for informing the design and implementation of future health behavior interventions for males.
Gaining insight from patient journey data using process-oriented analysis approach
(Australian Computer Society, 2012) Perimal-Lewis, Lua; Qin, Shaowen; Thompson, Campbell Henry; Hakendorf, Paul Haylett
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.

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