Basic and applied decision making in cancer control.

2005 ◽  
Vol 24 (4, Suppl) ◽  
pp. S3-S8 ◽  
Author(s):  
Wendy Nelson ◽  
Michael Stefanek ◽  
Ellen Peters ◽  
Kevin D. McCaul
Keyword(s):  
Decision Making ◽  
Cancer Control

Ethics and the idea of cancer control

2013 ◽  
Author(s):  
Lisa Schwartz
Keyword(s):  
Decision Making ◽  
Cancer Control ◽  
Ethical Values ◽  
Control Programmes ◽  
Decision Making Processes

Chapter 20 examines how proposed cancer control programmes can include ethical procedures and explore the value in their so doing and at the kinds of decisions that need to be made and at the ethical values and principles that can be applied to the decision-making processes.

Educating African American men on prostate health and informed decision making: Initial report from a peer-education program in Louisiana.

2011 ◽  
Vol 29 (7_suppl) ◽  
pp. 211-211
Author(s):  
M. M. Robinson ◽  
A. O. Sartor ◽  
L. Jack
Keyword(s):  
Prostate Cancer ◽  
Health Care ◽  
Decision Making ◽  
African American ◽  
African American Men ◽  
Peer Education ◽  
Cancer Control ◽  
Informed Decision ◽  
Informed Decision Making

211 Background: Informed decision making for prostate cancer health is widely endorsed but systematic programs to address this need are sparse. Herein we report initial progress in a statewide effort targeting African American men. Methods: The Louisiana Cancer and Lung Trust Fund Board (LCLTFB) Prostate Cancer Program is funded via a “check box” on the state income tax form, in which a portion of refunds could be allocated for prostate cancer efforts. The LCLTFB partnered with the statewide comprehensive cancer control program to develop a pilot lay program to educate men on prostate informed decision. The program was developed and modeled after “My Brother's Keeper,” a CDC funded program and implemented in five regions of the state. African American men active in the cancer community and regional cancer coalitions were identified as possible trainers for the program. Staff members from “My Brother's Keeper” trained the Cancer Control regional staff, as well as the community trainers in a two day session. Upon completion, the community trainers were charged to go into their community and convene three education sessions. Educational sessions were conducted in local churches, head start centers, men social club meeting, Greek organizational meetings, and labor union meetings. Men attending the session received a short pre- and post-test assessing whether or not they had discussed prostate informed decision making with a health care provider, if they had made an appointment with a health care provider, or was any follow up from the educational session initiated. Results: A total of 250 African American men in Louisiana were educated by the program. Upon followup phone calls, 172 men self-reported that they had initiated some form of follow up as a consequence of the participation. 35 men were unable to be contacted for follow up (number no longer in service or no phone number listed) 43 men (messages left but no returned call). Conclusions: Peer education can engage African American men regarding informed decision making on prostate cancer health issues. More data are needed to verify and determine the type of followup that was initiated after the educational sessions. [Table: see text]

Cancer patient experience: A pilot survey in Japan.

2014 ◽  
Vol 32 (30_suppl) ◽  
pp. 260-260
Author(s):  
Izumi Kamiya ◽  
Ayako Okuyama ◽  
Kayoko Katayama ◽  
Natsumi Yamashita ◽  
Keizo Akuta ◽  
...  
Keyword(s):  
Decision Making ◽  
Patient Experience ◽  
Emotional Support ◽  
Cancer Care ◽  
Medical Staff ◽  
Pain Control ◽  
Cancer Control ◽  
Treatment Preferences ◽  
Inpatient Setting ◽  
Patient Reported

260 Background: Patient-reported experiences of cancer care are an important outcome of cancer control programs. To establish a nation-wide system to monitor progress in cancer control policies, we piloted a patient experience survey to six hospitals in Japan. Methods: We conducted a self-administered questionnaire survey to a total of 1,804 adult cancer patients receiving cancer treatment in six hospitals (three cancer centers, two general hospitals, and one academic institution) from July 2013 to Mar 2014. Patients were asked to answer 94 questions covering eight dimensions of cancer experience: 1) decision-making, 2) care coordination, 3) patient education, 4) pain control, 5) emotional support, 6) family support, 7) access to care, and 8) care continuity. Results: Eighty percent of the patients reported that their treatment preferences were respected in the decision-making process, but a large proportion of patients (60%) also noted that they preferred to have their treatment decisions made for them by their physicians. Many (32%) expressed difficulty in communicating their questions and concerns to their physicians at the time of diagnosis. Only one fifth of patients were informed at the time of diagnosis that they can seek for a second opinion from other providers. Average patient-reported wait time to surgery was 30 days, which was considered to be long by a third of the patients. Eighty percent of patients felt that their care was well-coordinated by a multidisciplinary team, while % also felt that they received adequate emotional support from their medical staff. Relatively small proportion of outpatients (77%) felt that they had access to medical staff when they had medical questions, compared to nearly all patients in an inpatient setting. Only 65% of inpatients and 40% of outpatients felt that they had received best available pain control during their care. Less than half of the patients were able to communicate their preferred place of care after discharge with their healthcare provider. Conclusions: Patient-reported experiences of cancer care are an important outcome measure of cancer policy performance. This pilot study served to reveal some of the important on in future nationwide surveys.

scholarly journals The OncoSim model: development and use for better decision-making in Canadian cancer control

2017 ◽  
Vol 24 (6) ◽  
pp. 401 ◽  
Author(s):  
C.L. Gauvreau ◽  
N.R. Fitzgerald ◽  
S. Memon ◽  
W.M. Flanagan ◽  
C. Nadeau ◽  
...  
Keyword(s):  
Decision Making ◽  
Demographic History ◽  
Model Development ◽  
Internal Validity ◽  
Cancer Control ◽  
Control Policy ◽  
Population Level ◽  
Population Heterogeneity ◽  
Face Validity ◽  
Cancer Models

The Canadian Partnership Against Cancer was created in 2007 by the federal government to accelerate cancer control across Canada. Its OncoSim microsimulation model platform, which consists of a suite of specific cancer models, was conceived as a tool to augment conventional resources for population-level policy- and decision-making. The Canadian Partnership Against Cancer manages the OncoSim program, with funding from Health Canada and model development by Statistics Canada.Microsimulation modelling allows for the detailed capture of population heterogeneity and health and demographic history over time. Extensive data from multiple Canadian sources were used as inputs or to validate the model. OncoSim has been validated through expert consultation; assessments of face validity, internal validity, and external validity; and model fit against observed data. The platform comprises three in-depth cancer models (lung, colorectal, cervical), with another in-depth model (breast) and a generalized model (25 cancers) being in development. Unique among models of its class, OncoSim is available online for public sector use free of charge. Users can customize input values and output display, and extensive user support is provided.OncoSim has been used to support decision-making at the national and jurisdictional levels. Although simulation studies are generally not included in hierarchies of evidence, they are integral to informing cancer control policy when clinical studies are not feasible. OncoSim can evaluate complex intervention scenarios for multiple cancers.Canadian decision-makers thus have a powerful tool to assess the costs, benefits, cost-effectiveness, and budgetary effects of cancer control interventions when faced with difficult choices for improvements in population health and resource allocation.

scholarly journals The OncoSim Cancer Simulation Platform: A Tool to Project the Population Effects of Cancer Control Interventions in Canada

2018 ◽  
Vol 4 (Supplement 2) ◽  
pp. 77s-77s
Author(s):  
N. Fitzgerald ◽  
C. Gauvreau ◽  
S. Memon ◽  
S. Hussain ◽  
A. Coldman ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Decision Making ◽  
Cancer Screening ◽  
Control Strategies ◽  
Cancer Control ◽  
Lung Cancer Screening ◽  
Long Term Effects ◽  
National Guidelines ◽  
Incidence And Mortality ◽  
Statistics Canada

Background: Cancer control interventions exert their effects over multiple decades. To evaluate diverse and competing opportunities to reduce future cancer burden it is desirable to understand long-term effects prior to any new program implementation or significant change. Internationally, modeling is becoming an accepted source of planning information for decision-makers. Aim: We will describe the construction and use of the OncoSim microsimulation model, which was developed to evaluate cancer control strategies in Canada. Methods: OncoSim is a suite of models (cancers of the lung, colorectum, cervix and breast, plus a composite 32-cancer model) used to address key policy questions and support decision-making. It is led by the Canadian Partnership Against Cancer with model development by Statistics Canada. OncoSim incorporates risk factors, cancer natural history, screening, treatment, survival and end-of-life care. Wherever possible it is informed by Canadian data sources. Models are calibrated to reproduce a range of cancer-specific statistics, e.g., current and historical Canadian cancer-specific incidence and mortality, smoking patterns, and results of screening. The site-specific models have undergone further validation by replicating reported short-term effects of cancer prevention and screening interventions. Users may customize interventions through modifying input parameters. Outputs include incidence, mortality, costs, cost-effectiveness, and resource utilization. Users from the public sector have access at no cost to OncoSim and receive extensive support from a multidisciplinary technical team. The model is continually updated to incorporate emerging knowledge. Results: OncoSim has been used to support cancer control decision-making at the national and provincial/territorial levels. Applications include: national guidelines recommendations for colorectal and lung cancer screening; comparison of cytology vs. HPV based cervical cancer screening; and integration of smoking cessation into low-dose CT lung cancer screening. Conclusion: Validated simulation models such as OncoSim can be a versatile and efficient tool for cancer control planners to evaluate and prioritize cancer control strategies.

scholarly journals Opportunities for theory-informed decision science in cancer control

2021 ◽  
Vol 11 (11) ◽  
pp. 2055-2064
Author(s):  
Arielle S Gillman ◽  
Rebecca A Ferrer
Keyword(s):  
Decision Making ◽  
Shared Decision Making ◽  
Cognitive Processes ◽  
Cancer Control ◽  
Decision Science ◽  
Shared Decision ◽  
Interpersonal Dynamics ◽  
Cancer Care Continuum ◽  
And Control

Abstract Cancer prevention and control involves navigation of complex clinical decisions, often laden with uncertainty and/or intricate interpersonal dynamics, which have implications for both physical health and quality of life. Cancer decision-making research in recent decades has primarily focused on working to improve the quality of decisions by providing patients with detailed information about their choices and through an increased emphasis in medicine on the importance of shared decision making. This emphasis is reflective of a model of decision making that emphasizes knowledge, options, and deliberative synthesis of information as primary to decision making; yet, decades of research in psychology, decision science, and behavioral economics have taught us that our decisions are not influenced only by our objective knowledge of facts, but by our emotions, by the influence of others, and by biased cognitive processes. We present a conceptual framework for a future of research in decision science and cancer that is informed by decision science theories. Our framework incorporates greater recognition of the interpersonal dynamics of shared decision making, including the biases (including cognitive heuristics and race-based bias) that may affect multiple actors in the decision-making process, and emphasizes study of the interaction between deliberative and affective psychological processes as they relate to decision making. This work should be conducted with an eye toward informing efforts to improve decision making across the cancer care continuum, through interventions that are also informed by theory.

scholarly journals Selecting Active Surveillance: Decision Making Factors for Men with a Low-Risk Prostate Cancer

2019 ◽  
Vol 39 (8) ◽  
pp. 962-974
Author(s):  
Richard M. Hoffman ◽  
Tania Lobo ◽  
Stephen K. Van Den Eeden ◽  
Kimberly M. Davis ◽  
George Luta ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Decision Making ◽  
Active Surveillance ◽  
Clinical Stage ◽  
Cancer Control ◽  
Treatment Selection ◽  
Low Risk ◽  
Decision Making Factors ◽  
Risk Prostate Cancer ◽  
Low Risk Prostate Cancer

Background. Men with a low-risk prostate cancer (PCa) should consider observation, particularly active surveillance (AS), a monitoring strategy that avoids active treatment (AT) in the absence of disease progression. Objective. To determine clinical and decision-making factors predicting treatment selection. Design. Prospective cohort study. Setting. Kaiser Permanente Northern California (KPNC). Patients. Men newly diagnosed with low-risk PCa between 2012 and 2014 who remained enrolled in KPNC for 12 months following diagnosis. Measurements. We used surveys and medical record abstractions to measure sociodemographic and clinical characteristics and psychological and decision-making factors. Men were classified as being on observation if they did not undergo AT within 12 months of diagnosis. We performed multivariable logistic regression analyses. Results. The average age of the 1171 subjects was 61.5 years ( s = 7.2 years), and 81% were white. Overall, 639 (57%) were managed with observation; in adjusted analyses, significant predictors of observation included awareness of low-risk status (odds ratio 1.75; 95% confidence interval 1.04–2.94), knowing that observation was an option (3.62; 1.62–8.09), having concerns about treatment-related quality of life (1.21, 1.09–1.34), reporting a urologist recommendation for observation (8.20; 4.68–14.4), and having a lower clinical stage (T1c v. T2a, 2.11; 1.16–3.84). Conversely, valuing cancer control (1.54; 1.37–1.72) and greater decisional certainty (1.66; 1.18–2.35) were predictive of AT. Limitations. Results may be less generalizable to other types of health care systems and to more diverse populations. Conclusions. Many participants selected observation, and this was associated with tumor characteristics. However, nonclinical decisional factors also independently predicted treatment selection. Efforts to provide early decision support, particularly targeting knowledge deficits, and reassurance to men with low-risk cancers may facilitate better decision making and increase uptake of observation, particularly AS.

scholarly journals Klasifikasi Pasien Kanker Payudara Menggunakan Metode Rough Set

2020 ◽  
Vol 16 (2) ◽  
pp. 207-220
Author(s):  
M Rifai ◽  
S Musdalifah ◽  
D Lusiyanti
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Decision Support System ◽  
Rough Set ◽  
Support System ◽  
System Application ◽  
Cancer Control ◽  
Distant Metastases ◽  
Data Set ◽  
Java Language

ABSTRACTBreast cancer is a condition where the cell has lost control and its normal mechanism, so that abnormal growthoccurs quickly and uncontrollably that occurs in breast tissue. The basic thing that needs to be known about thecancer is the stage, so that the handling of the patient can be done correctly. In determining the cancer stage Union for International Cancer Control (UICC) uses several indicators, namely, the primary tumor which describes the size of the tumor and the expansion of the tumor to the chest wall, involvement of lymph nodes around the breast and distant metastases to other organs. Therefore, it is necessary to have a decision support system application that aims to classify cancer patient data based on the Stadium. One classification method that looks for the Decision Rule is the Rough Set. Basically this Rough set method is a decision-making method that is used to find a pattern from the data set that is processed. So that a pattern / rule can be obtained that can be used as a reference in decision making. In this study the pattern obtained as many as 16 will be entered into the Net-Bean software with java language so that it becomes a decision support system, then the system will be tested using 135 test data From these tests, namely by comparing the actual data with the results obtained from the decision support system application. So, the accuracy is 100%.Keywords : Classification, Breast Cancer Stadium, Rough Set.

Understanding the non-curative potential of palliative chemotherapy: Do patients hear what they want to hear?

2017 ◽  
Vol 35 (15_suppl) ◽  
pp. 6575-6575
Author(s):  
Andrea Catherine Enzinger ◽  
Jen Wind ◽  
Elizabeth Frank ◽  
Nadine Jackson McCleary ◽  
Christine Cronin ◽  
...  
Keyword(s):  
Decision Making ◽  
Cancer Control ◽  
Patient Characteristics ◽  
Cancer Type ◽  
Prognostic Information ◽  
Chi Square ◽  
Future Studies ◽  
Information Preferences ◽  
Logistic Regressions ◽  
Length Of Life

6575 Background: Misconceptions about the curative potential of PC are common, and may arise from gaps in informed consent. Another contributing factor could be patients’ desire, or lack of desire, for information about prognosis and PC outcomes. Methods: We surveyed 137 patients with advanced colorectal (N = 102) or pancreatic cancer (N = 35) within 2 weeks of consultation about 1st or 2ndline PC, as part of randomized trial of a PC education intervention at 6 US sites. Patients rated how much information they wanted about PC risks/benefits, including impact on prognosis. Responses ranged from no information to as much as possible on a 5-point Likert scale. They reported decision-making preferences; whether a doctor discussed curability, and how likely they thought PC was to cure their cancer. Chi square and Wilcoxon tests examined whether information and decision-making preferences, or curability discussions were associated with expectations of cure. Multivariable logistic regressions evaluated whether associations were modified by age, race, gender, marital status, or cancer type. Results: Only 44.5% of patients accurately reported that their cancer was not at all likely to be cured by PC. Most patients wanted a lot, or as much information as possible about PC risks/benefits, including likelihood of cure (81.7%), cancer control (84.7%), and impact on length of life (80.3%). Most patients preferred shared (70.8%) versus active or passive decision-making. Neither decision-making nor prognostic information preferences were associated with expectations of cure. Patients (13.9%) who did not recall curability discussions were less likely to have accurate expectations (21% v 48%; OR, 0.29; 95% CI, 0.07-.97). Patient characteristics did not significantly confound this association. Conclusions: Most patients value shared decision-making and want maximal information about PC risks/benefits, including impact on prognosis. Despite wanting prognostic information and reporting curability discussions, many patients report inaccurate expectations about cure from PC. Future studies should examine whether these assertions reflect misunderstandings, differences in belief, or expressions of hope.

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