A Decision Technology System To Advance the Diagnosis and Treatment of Breast Cancer

Geographical variations in cancer rates have been observed for decades. Described spatial patterns and trends have provided clues for generating hypotheses about the etiology of cancer. For breast cancer, investigators have demonstrated that some variation can be explained by differences in the population distribution of known breast cancer risk factors such as menstrual and reproductive variables (Laden, Spiegelman, and Neas, 1997; Robbins, Bescianini, and Kelsey, 1997; Sturgeon, Schairer, and Gail, 1995). However, regional patterns also may reflect the effects of Workshop on Hormones, Hormone Metabolism, Environment, and Breast Cancer (1995): (a) environmental hazards (such as air and water pollution), (b) demographics and the lifestyle of a mobile population, (c) subgroup susceptibility, (d) changes and advances in medical practice and healthcare management, and (e) other factors. To accurately measure breast cancer risk in individuals and population groups, it is necessary to singly and jointly assess the association between such risk and the hypothesized factors. Various statistical models will be needed to determine the potential relationships between breast cancer development and estimated exposures to environmental contamination. To apply the models, data must be assembled from a variety of sources, converted into the statistical models’ parameters, and delivered effectively to researchers and policy makers. A Web-enabled decision technology system can be developed to provide the needed functionality. This chapter will present a conceptual architecture for such a decision technology system. First, there will be a brief overview of a typical geographical analysis. Next, the chapter will present the conceptual Web-based decision technology system and illustrate how the system can assist users in diagnosing and treating breast cancer. The chapter will conclude with an examination of the potential benefits from system use and the implications for breast cancer research and practice

BCAS: A Web-enabled and GIS-based Decision Support System for the Diagnosis and Treatment of Breast Cancer

For decades, geographical variations in cancer rates have been observed but the precise determinants of such geographic differences in breast cancer development are unclear. Various statistical models have been proposed. Applications of these models, however, require that the data be assembled from a variety of sources, converted into the statistical models’ parameters and delivered effectively to researchers and policy makers. A web-enabled and GIS-based system can be developed to provide the needed functionality. This article overviews the conceptual web-enabled and GIS-based system (BCAS), illustrates the system’s use in diagnosing and treating breast cancer and examines the potential benefits and implications for breast cancer research and practice

Cancer Surveillance using Data Warehousing, Data Mining, and Decision Support Systems

This article discusses how data warehousing, data mining, and decision support systems can reduce the national cancer burden or the oral complications of cancer therapies, especially as related to oral and pharyngeal cancers. An information system is presented that will deliver the necessary information technology to clinical, administrative, and policy researchers and analysts in an effective and efficient manner. The system will deliver the technology and knowledge that users need to readily: (1) organize relevant claims data, (2) detect cancer patterns in general and special populations, (3) formulate models that explain the patterns, and (4) evaluate the efficacy of specified treatments and interventions with the formulations. Such a system can be developed through a proven adaptive design strategy, and the implemented system can be tested on State of Maryland Medicaid data (which includes women, minorities, and children)

Exploring colorectal cancer patients' perceptions of the quality of their care

This report discusses the local situation in Halton with regard to colorectal cancer care by exploring how patients perceived the quality of their care.Widnes Primary Care Grou

Patient and public attitudes to and awareness of clinical practice guidelines : a systematic review with thematic and narrative syntheses

Article Accepted Date: 15 July 2014 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. Acknowledgements The research leading to these results has received funding from the European Community’s Seventh Framework Programme (FP7/2007-2013) under grant agreement n° 258583 (DECIDE project). The Health Services Research Unit, Aberdeen University, is funded by the Chief Scientist Office of the Scottish Government Health Directorates. The authors accept full responsibility for this paper and the views expressed in it are those of the authors and do not necessarily reflect those of the Chief Scientist Office. NS receives funding through a Knowledge Translation Fellowship from the Canadian Institutes of Health Research. No funding bodies had a role in the manuscript. We would like to thank Healthcare Improvement Scotland and the University of Dundee for support, including access to literature. We would also like to thank Lorna Thompson (Healthcare Improvement Scotland), for her help with the protocol for this review.Peer reviewedPublisher PD

Designing the customer journey in a service delivery network: evidence from cancer patient treatments

Customer experiences - not in the least for customers with chronic diseases - depend on a series of exchanges over a considerable amount of time with a variety of service providers and thus a service delivery network (SDN). The impact of SDNs on the customer experience, however, is unclear. This research provides insight into (1) the service delivery system characteristics in SDNs, and (2) their impact on the relationship between customer journey duration and value for time as an important customer experience indicator. The service delivery system characteristics were explored by process travel sheets of patients undergoing cancer treatment in a hospital (n=412). These data were linked to time measurement data (n=262) and survey data (n=312) to explain customer journey duration and value for time, thereby showing the importance of the number of service events and the type of service providers. Theoretical and managerial implications are discussed

Supporting people with active and advanced disease: a rapid review of the evidence

1.1 Background: the NCSI AAD group The National Cancer Survivorship Initiative (NCSI, 2010) was set up in response to the NHS Cancer Reform Strategy (Department of Health, 2007) as a collaboration between Macmillan Cancer Support, the Department of Health and NHS Improvement, with the goal to achieve a better understanding of the experiences of cancer survivors and to advocate for the provision of services to support them. Within this broad remit, it was recognised that there was a particular group of patients whose needs were commonly neglected; people who were experiencing the ongoing effects of cancer beyond first-line treatment but who were not at end of life. The Active and Advanced Disease (AAD) working group was created to consider issues of relevance to such people. 1.2 Aims of this review This project set out to meet the following aim: To review the literature on selected cancers in order to identify implications for the development of services to support patients experiencing difficulties associated with active and advanced disease

Improving quality of life in cancer patients through higher participation and health literacy: study protocol for evaluating the oncological social care project (OSCAR)

BACKGROUND: Cancer patients experience psychological and social distress due to their medical treatment and social issues. However, continuous and specialized social support is still lacking. In Germany, a group of company health insurance funds has developed an approach to support cancer patients with monthly structured interviews conducted by specially trained Social Care Nurses. The nurses will identify patient needs in order to provide help with medical, personal, and social matters. One aim of the scientific evaluation is to analyze the effect of the consultations on various patient-reported outcomes, especially quality of life. The evaluation concept will be described in this study protocol. METHODS/DESIGN: The evaluation is a non-randomized, controlled, multi-center intervention study with a mixed-method design. It consists of three research modules which include primary data from questionnaires, and claims data from the health insurance funds. In Module 1, cancer patients will be recruited to form an intervention group (OSCAR, n = 150) and a control group (n = 200) in four study centers for a period of 1 year. One baseline and three follow-up questionnaires will be conducted to survey the patient-reported outcomes. Relevant secondary outcomes are health literacy, participation, and physician-patient communication. In Module 2, claims data will be used to analyze cost effects and thereby assess effectivity and hospitalization. Module 3 will involve a qualitative analysis of project diaries kept by the Social Care Nurses. The diaries will record the nurses' practical experiences and the benefits of deploying OSCAR across the German healthcare system. DISCUSSION: OSCAR is an innovative way of providing cancer patients with continuous support to improve their quality of life. The evaluation concept aims to assess the effects of the monthly consultations by the Social Care Nurses on the patients, and will use a mixed-method design. The results are important for assessing the transferability of OSCAR to the healthcare system as a whole. TRIAL REGISTRATION: German Clinical Trials Register (DRKS-ID: DRKS00013640 ). Registered 29 December 2017