Odd Erik Gundersen

Computer-Based Symptom Assessment Is Feasible in Patients With Advanced Cancer: Results From an International Multicenter Study, the EPCRC-CSA

CONTEXT Symptom assessment by computers is only effective if it provides valid results and is perceived as useful for clinical use by the end users: patients and health care providers. OBJECTIVES To identify factors associated with discontinuation, time expenditure, and patient preferences of the computerized symptom assessment used in an international multicenter data collection project: the European Palliative Care Research Collaborative-Computerized Symptom Assessment. METHODS Cancer patients with incurable metastatic or locally advanced disease were recruited from 17 centers in eight countries, providing 1017 records for analyses. Observer-based registrations and patient-reported measures on pain, depression, and physical function were entered on touch screen laptop computers. RESULTS The entire assessment was completed by 94.9% (n = 965), with median age 63 years (range 18-91 years) and median Karnofsky Performance Status (KPS) score of 70 (range 20-100). Predictive factors for noncompletion were higher age, lower KPS, and more pain (P ≤ 0.012). Time expenditure among completers increased with higher age, male gender, Norwegian nationality, number of comorbidities, and lower physical functioning (P ≤ 0.007) but was inversely related to pain levels and tiredness (P ≤ 0.03). Need for assistance was predicted by higher age, nationality other than Norwegian, lower KPS, and lower educational level (P < 0.001). More than 50% of patients preferred computerized assessment to a paper and pencil version. CONCLUSION The high completion rate shows that symptom assessment by computers is feasible in patients with advanced cancer. However, reduced performance status reduces compliance and increases the need for assistance. Future work should aim at identifying the minimum set of valid screening questions and refine the software to optimize symptom assessment and reduce respondent burden in frail patients.

A Real-Time Decision Support System for High Cost Oil-Well Drilling Operations

In this paper we present DrillEdge - a commercial and award winning software system that monitors oil-well drilling operations in order to reduce nonproductive time (NPT). DrillEdge utilizes case-based reasoning with temporal representations on streaming real-time data, pattern matching and agent systems to predict problems and give advice on how to mitigate the problems. The methods utilized, the architecture, the GUI and development cost in addition to two case studies are documented.

Toward Measuring the Similarity of Complex Event Sequences in Real-Time

Traditional sequence similarity measures have a high time complexity and are therefore not suitable for real-time systems. In this paper, we analyze and discuss properties of sequences as a step toward developing more efficient similarity measures that can approximate the similarity of traditional sequence similarity measures. To explore our findings, we propose a method for encoding sequence information as a vector in order to exploit the advantageous performance of vector similarity measures. This method is based on the assumption that events closer to a point of interest, like the current time, are more important than those further away. Four experiments are performed on both synthetic and real-time data that show both disadvantages and advantages of the method.

Characteristics of breakthrough cancer pain and its influence on quality of life in an international cohort of patients with cancer.

Objectives Breakthrough cancer pain (BTP) represents a treatment challenge. Objectives were to examine the prevalence and characteristics of BTP in an international sample of patients with cancer, and to investigate the relationship between BTP and quality of life (QoL). Methods This was an observational cross-sectional multicentre study. Participating patients completed self-report questionnaires on a touch-screen laptop computer, including the Brief Pain Inventory, Alberta Breakthrough Pain Assessment Tool (ABPAT) and European Organisation for Research and Treatment of Cancer 30-item Core Quality of Life Questionnaire (EORTC QLQ-C30). The study was performed in 17 centres in 8 countries and involved 4 languages (Norwegian, Italian, German and English). Results Records from a convenience sample of 978 patients with advanced cancer were analysed; mean age was 62.2 years, 48.3% were women and 84.4% had metastatic disease. A total of 296 patients (30%) had no pain, defined as worst pain in the past 24 hours <1 on a 0–10 scale. Of the 682 patients with a pain score ≥1, 393 (58%) reported no BTP on the screening item, while 289 (30%) confirmed flare ups of BTP. Patients with BTP reported significantly higher pain intensity scores (<0.001) than patients without BTP; 57.1% of patients rated BTP at its worst as being severe: ≥7 on a 0–10 scale. Time from onset to peak intensity was <10 min for 42.9%, and average time to pain relief was 27.1 min. BTP was commonly triggered by medication wearing off (28%). Patients with BTP had significantly worse mean outcomes on 10 of 15 functional and symptom scales of the EORTC QLQ-C30 (<0.001). Severe pain intensity in the last week was a powerful predictor of BTP (OR 4.1) and poor QoL (OR 1.9). Conclusions BTP is highly prevalent with prolonged episodes despite analgaesics, and has a pervasive impact on QoL. Patients reporting high pain intensity should be carefully evaluated for BTP and efficacy of analgaesic treatment, to provide optimal pain management and improve QoL. Trial registration number NCT00972634; Results.

Case-based reasoning for assessment and diagnosis of depression in palliative care

The goal of the research presented is to create a computational framework and system architecture for clinical decision support in palliative care. The application focused is the classification of depression. The method under investigation is case-based reasoning, motivated by the complexity of the domain and a lack of generalized principles of sufficient coverage and strength for diagnosis and treatment. A system architecture is described and exemplified through an implemented prototype. The outcome of the research so far is a system that captures the properties intended, and for which a clinical test set-up has been defined.

Case Representation and Similarity Assessment in the selfBACK Decision Support System

In this paper we will introduce the selfBACK decision support system that facilitates, improves and reinforces self-management of non-specific low back pain. The selfBACK system is a predictive case-based reasoning system for personalizing recommendations in order to provide relief for patients with non-specific low back pain and increase their physical functionality over time. We present how case-based reasoning is used for capturing experiences from temporal patient data, and evaluate how to carry out a similarity-based retrieval in order to find the best advice for patients. Specifically, we will show how heterogeneous data received at various frequencies can be captured in cases and used for personalized advice.

Detection of Symptoms for Revealing Causes Leading to Drilling Failures

When a diagnosis of a problem is known, the problem can usually be solved efficiently. This paper presents a method that helps reveal the most probable cause of a drilling-process failure immediately after occurrence. Normally, it takes some time to investigate and evaluate all available information before the correct cause can be determined. The method presented is targeted at reducing this time and at the same time improving the quality of the interpretation. The method relies on input parameters from the ongoing drilling process, parameters that behave irregularly and are referred to as symptoms or errors when the irregularity is severe. Recognized symptoms are used as input parameters in a knowledge-modeling method that relates symptoms to failures. The method was verified on the basis of historical drilling data, and its ability to point out the correct causes with high probability was demonstrated. Field testing the method is yet to be performed.

Animating physically based explosions in real-time

We present a framework for real-time animation of explosions that runs completely on the GPU. The simulation allows for arbitrary internal boundaries and is governed by a combustion process, a Stable Fluid solver, which includes thermal expansion, and turbulence modeling. The simulation results are visualised by two particle systems rendered using animated textures. The results are physically based, non-repeating, and dynamic real-time explosions with high visual quality.

The Role of Context and its Elements in Situation Assessment

This chapter presents an analysis of the concept of context in situation assessment. Situation assessment is the process that develops a situation awareness, which is the basis for deciding which action to perform in a given situation. The contributions of the research documented here include a knowledge level model of situation assessment, a context element ontology and an analysis of the role of context in situation assessment, which are based on models of situation awareness and context found in the literature. The knowledge level model includes a task decomposition, a task description, and a goal analysis. Finally, this view is illustrated in a short example.

Situational Awareness in Context

In this paper we analyze the relationship between context and situational awareness with the aim to get a better understanding of how context information influences situation assessment. The analysis is based on previous research on situational awareness, context and situations. We show how situation assessment could be specified more detailed with regards to sub-processes through investigating the components of a situation. Events are introduced as situational elements in themselves. The role of context in situation assessment is also analyzed and so is the information that can be treated as contextual. A case study is presented that relates the findings to the monitoring of oil well drilling. Our main contribution is an analysis of the situation assessment process and how it operates on and manipulates the components of the situation. Another contribution is the case study of how the findings apply in monitoring of the oil well drilling situation.