journal
MENU ▼
Read by QxMD icon Read
search

Medical Decision Making: An International Journal of the Society for Medical Decision Making | Page 2

journal
https://read.qxmd.com/read/30759064/medical-decision-making-and-mdm-policy-practice-reviewers-2018
#21
(no author information available yet)
No abstract text is available yet for this article.
February 2019: Medical Decision Making: An International Journal of the Society for Medical Decision Making
https://read.qxmd.com/read/30654704/development-and-validation-of-the-real-world-progression-in-diabetes-rapids-model
#22
Anirban Basu, Min-Woong Sohn, Brian Bartle, Kwun Chuen Gary Chan, Jennifer M Cooper, Elbert Huang
INTRODUCTION: To develop and validate the first real-world data-based type 2 diabetes progression model (RAPIDS) employing econometric techniques that can study the comparative effects of complex dynamic patterns of glucose-lowering drug use. METHODS: The US Department of Veterans Affairs (VA) electronic medical record and claims databases were used to identify over 500,000 diabetes patients in 2003 with up to 9-year follow-up. The RAPIDS model contains interdependent first-order Markov processes over quarters for each of the micro- and macrovascular events, hypoglycemia, and death, as well as predictive models for 8 biomarker levels...
February 2019: Medical Decision Making: An International Journal of the Society for Medical Decision Making
https://read.qxmd.com/read/30678607/physician-and-nonphysician-estimates-of-positive-predictive-value-in-diagnostic-v-mass-screening-mammography-an-examination-of-bayesian-reasoning
#23
Laurel C Austin
BACKGROUND: The same test with the same result has different positive predictive values (PPVs) for people with different pretest probability of disease. Representative thinking theory suggests people are unlikely to realize this because they ignore or underweight prior beliefs when given new information (e.g., test results) or due to confusing test sensitivity (probability of positive test given disease) with PPV (probability of disease given positive test). This research examines whether physicians and MBAs intuitively know that PPV following positive mammography for an asymptomatic woman is less than PPV for a symptomatic woman and, if so, whether they correctly perceive the difference...
January 24, 2019: Medical Decision Making: An International Journal of the Society for Medical Decision Making
https://read.qxmd.com/read/30678537/leveraging-cumulative-network-meta-analysis-and-value-of-information-analysis-to-understand-the-evolving-value-of-medical-research
#24
David D Kim, Thomas A Trikalinos, John B Wong
BACKGROUND: Leveraging cumulative network meta-analysis (NMA) and value of information (VOI) analysis, this article aims to understand the evolving value of medical research and to identify gaps in the evidence for future research. METHODS: As an illustration, we identified 31 randomized controlled trials (RCT) from 1980 to 2013 that examined a network of 3 interventions for coronary artery disease: medical therapy (MED), percutaneous coronary intervention (PCI), and coronary artery bypass graft (CABG) surgery...
January 24, 2019: Medical Decision Making: An International Journal of the Society for Medical Decision Making
https://read.qxmd.com/read/30678526/reducing-uncertainty-in-eq-5d-value-sets-the-role-of-spatial-correlation
#25
Shahriar Shams, Eleanor Pullenayegum
OBJECTIVE: Scoring algorithms for the EQ-5D-3L are constructed subject to a large degree of uncertainty (a credible interval width of 0.152, which is significant in comparison to the reported minimal important differences). The purpose of this work is to explore modeling techniques that will reduce the extent of this uncertainty. METHODS: We used the US valuation study data. A Bayesian approach was used to calculate predicted utilities and credible intervals. A spatial Gaussian correlation structure was used to model correlation among health states (HS), thus allowing directly valued HS to contribute to the predicted utility of nearby unvalued HS...
January 24, 2019: Medical Decision Making: An International Journal of the Society for Medical Decision Making
https://read.qxmd.com/read/30678520/development-and-validation-of-the-evaluation-platform-in-copd-epic-a-population-based-outcomes-model-of-copd-for-canada
#26
Mohsen Sadatsafavi, Shahzad Ghanbarian, Amin Adibi, Kate Johnson, J Mark FitzGerald, William Flanagan, Stirling Bryan, Don Sin
BACKGROUND: We report the development, validation, and implementation of an open-source population-based outcomes model of chronic obstructive pulmonary disease (COPD) for Canada. METHODS: Evaluation Platform in COPD (EPIC) is a discrete-event simulation model of Canadians 40 years of age or older. Three core features of EPIC are its open-population design (incorporating projections of future population growth, aging, and smoking trends), its incorporation of heterogeneity in lung function decline and burden of exacerbations, and its modeling of the natural history of COPD from inception...
January 24, 2019: Medical Decision Making: An International Journal of the Society for Medical Decision Making
https://read.qxmd.com/read/30658540/cancer-screening-markers-a-simple-strategy-to-substantially-reduce-the-sample-size-for-validation
#27
Stuart G Baker
BACKGROUND: Studies to validate a cancer prediction model based on cancer screening markers collected in stored specimens from asymptomatic persons typically require large specimen collection sample sizes. A standard sample size calculation targets a true-positive rate (TPR) of 0.8 with a 2.5% lower bound of 0.7 at a false-positive rate (FPR) of 0.01 with a 5% upper bound of 0.03. If the probability of developing cancer during the study is P = 0.01, the specimen collection sample size based on the standard calculation is 7600...
January 18, 2019: Medical Decision Making: An International Journal of the Society for Medical Decision Making
https://read.qxmd.com/read/30649998/assessing-the-clinical-impact-of-risk-models-for-opting-out-of-treatment
#28
Kathleen F Kerr, Marshall D Brown, Tracey L Marsh, Holly Janes
Decision curves are a tool for evaluating the population impact of using a risk model for deciding whether to undergo some intervention, which might be a treatment to help prevent an unwanted clinical event or invasive diagnostic testing such as biopsy. The common formulation of decision curves is based on an opt-in framework. That is, a risk model is evaluated based on the population impact of using the model to opt high-risk patients into treatment in a setting where the standard of care is not to treat. Opt-in decision curves display the population net benefit of the risk model in comparison to the reference policy of treating no patients...
January 16, 2019: Medical Decision Making: An International Journal of the Society for Medical Decision Making
https://read.qxmd.com/read/30632890/visual-representations-of-risk-enhance-long-term-retention-of-risk-information-a-randomized-trial
#29
Bradley A Arrick, Katarzyna J Bloch, Laura Stein Colello, Steven Woloshin, Lisa M Schwartz
BACKGROUND: People often overestimate their risk of developing cancer, which can cause undue worry and unwarranted risk-reducing actions. Standard counseling has a limited and short-lived effect on correcting these misperceptions. We conducted a randomized study to evaluate whether incorporation of visual depictions of risk improves the efficacy and durability of cancer risk counseling. METHODS: Sixty-six individuals seen in the Familial Cancer Program were randomized to receive standard counseling or counseling supplemented with 2 interactive visual representations of their 10-year risk of developing the cancer type of greatest concern (enhanced counseling)...
January 11, 2019: Medical Decision Making: An International Journal of the Society for Medical Decision Making
https://read.qxmd.com/read/30799693/comparing-strategies-for-modeling-competing-risks-in-discrete-event-simulations-a-simulation-study-and-illustration-in-colorectal-cancer
#30
Koen Degeling, Hendrik Koffijberg, Mira D Franken, Miriam Koopman, Maarten J IJzerman
BACKGROUND: Different strategies toward implementing competing risks in discrete-event simulation (DES) models are available. This study aims to provide recommendations regarding modeling approaches that can be defined based on these strategies by performing a quantitative comparison of alternative modeling approaches. METHODS: Four modeling approaches were defined: 1) event-specific distribution (ESD), 2) event-specific probability and distribution (ESPD), 3) unimodal joint distribution and regression model (UDR), and 4) multimodal joint distribution and regression model (MDR)...
January 2019: Medical Decision Making: An International Journal of the Society for Medical Decision Making
https://read.qxmd.com/read/30799692/feasibility-and-efficacy-of-decision-aids-to-improve-decision-making-for-postmastectomy-breast-reconstruction-a-systematic-review-and-meta-analysis
#31
Nicholas L Berlin, Vickram J Tandon, Sarah T Hawley, Jennifer B Hamill, Mark P MacEachern, Clara N Lee, Edwin G Wilkins
BACKGROUND: The decision-making process for women considering breast reconstruction following mastectomy is complex. Research suggests that fewer than half of women undergoing mastectomy have adequate knowledge and make treatment decisions that are concordant with their underlying values. This systematic review assesses the feasibility and efficacy of preoperative decision aids (DAs) to improve the patient decision-making process for breast reconstruction. METHODS: A systematic review was performed using PubMed, Ovid MEDLINE, EMBASE, CINAHL, and Cochrane Databases published prior to January 4, 2018...
January 2019: Medical Decision Making: An International Journal of the Society for Medical Decision Making
https://read.qxmd.com/read/30799691/effect-of-tabular-and-icon-fact-box-formats-on-comprehension-of-benefits-and-harms-of-prostate-cancer-screening-a-randomized-trial
#32
Michelle McDowell, Gerd Gigerenzer, Odette Wegwarth, Felix G Rebitschek
BACKGROUND: Fact boxes employ evidence-based guidelines on risk communication to present benefits and harms of health interventions in a balanced and transparent format. However, little is known about their short- and long-term efficacy and whether designing fact boxes to present multiple outcomes with icon arrays would increase their efficacy. METHOD: In study 1, 120 men (30-75 y) completed a lab study. Participants were randomly assigned to 1 of 3 fact box formats on prostate cancer screening: a tabular fact box with numbers, a fact box with numbers and icon array, and a fact box with numbers, separate icon arrays, and text to describe each benefit and harm...
January 2019: Medical Decision Making: An International Journal of the Society for Medical Decision Making
https://read.qxmd.com/read/30799690/referral-decision-making-of-general-practitioners-a-signal-detection-study
#33
Olga Kostopoulou, Martine Nurek, Simona Cantarella, Grace Okoli, Francesca Fiorentino, Brendan C Delaney
BACKGROUND: Signal detection theory (SDT) describes how respondents categorize ambiguous stimuli over repeated trials. It measures separately "discrimination" (ability to recognize a signal amid noise) and "criterion" (inclination to respond "signal" v. "noise"). This is important because respondents may produce the same accuracy rate for different reasons. We employed SDT to measure the referral decision making of general practitioners (GPs) in cases of possible lung cancer...
January 2019: Medical Decision Making: An International Journal of the Society for Medical Decision Making
https://read.qxmd.com/read/30799689/ratio-format-shapes-health-decisions-the-practical-significance-of-the-1-in-x-effect
#34
Miroslav Sirota, Marie Juanchich
Prior research found that "1-in-X" ratios led to higher and less accurate subjective probability than "N-in-X*N" ratios or other formats, even though they featured the same mathematical information. It is unclear, however, whether the effect transfers into health decisions, and the practical significance of the effect is undetermined. Based on previous findings and risk communication theories, we hypothesized that the 1-in-X effect would occur and transfer into relevant decisions. We also tested whether age, gender, and education differences would moderate the 1-in-X effect on decision making...
January 2019: Medical Decision Making: An International Journal of the Society for Medical Decision Making
https://read.qxmd.com/read/30799687/cost-effectiveness-analysis-and-geographic-variation-in-health-care-costs-in-the-united-states
#35
Zachary Predmore
No abstract text is available yet for this article.
January 2019: Medical Decision Making: An International Journal of the Society for Medical Decision Making
https://read.qxmd.com/read/30517823/harnessing-expert-judgment-to-support-clinical-decisions-when-the-evidence-base-is-weak
#36
James G Dolan, Peter J Veazie
PURPOSE: In the process of developing an evidence-based decision dashboard to support treatment decisions for patients with newly diagnosed prostate cancer, we found that the clinical evidence base is insufficient to provide high-quality comparative outcome data. We therefore sought to determine if clinically acceptable outcome estimates could be created using a modified version of the Sheffield Elicitation Framework (SHELF), a formal method for eliciting judgments regarding probability distributions of expected decision outcomes...
December 5, 2018: Medical Decision Making: An International Journal of the Society for Medical Decision Making
https://read.qxmd.com/read/30403581/early-development-of-value-of-information-methods
#37
Stuart G Baker
No abstract text is available yet for this article.
November 2018: Medical Decision Making: An International Journal of the Society for Medical Decision Making
https://read.qxmd.com/read/30403580/comparing-the-performance-of-2-health-utility-measures-in-the-medicare-health-outcome-survey-hos
#38
Haomiao Jia, Erica I Lubetkin, Kimberly DeMichele, Debra S Stark, Matthew M Zack, William W Thompson
BACKGROUND: The Medicare Health Outcomes Survey (HOS), a nationwide annual survey of Medicare beneficiaries, includes the Centers for Disease Control and Prevention's HRQOL-4 questionnaire and Veterans RAND 12-item Health Survey (VR-12). This study compared EQ-5D scores derived from the HRQOL-4 (dEQ-5D) to SF-6D scores derived from VR-12. METHODS: Data were from Medicare HOS Cohort 15 (2012 baseline; 2014 follow-up). We included participants aged 65+ ( n = 105,473)...
November 2018: Medical Decision Making: An International Journal of the Society for Medical Decision Making
https://read.qxmd.com/read/30403579/low-health-literacy-and-health-information-avoidance-but-not-satisficing-help-explain-don-t-know-responses-to-questions-assessing-perceived-risk
#39
Heather Orom, Elizabeth Schofield, Marc T Kiviniemi, Erika A Waters, Caitlin Biddle, Xuewei Chen, Yuelin Li, Kimberly A Kaphingst, Jennifer L Hay
BACKGROUND: People who say they don't know (DK) their disease risk are less likely to engage in protective behavior. PURPOSE: This study examined possible mechanisms underlying not knowing one's risk for common diseases. METHODS: Participants were a nationally representative sample of 1005 members of a standing probability-based survey panel who answered questions about their comparative and absolute perceived risk for diabetes and colon cancer, health literacy, risk factor knowledge and health information avoidance, and beliefs about illness unpredictability...
November 2018: Medical Decision Making: An International Journal of the Society for Medical Decision Making
https://read.qxmd.com/read/30403578/simple-inclusion-of-complex-diagnostic-algorithms-in-infectious-disease-models-for-economic-evaluation
#40
Peter J Dodd, Jeff J Pennington, Liza Bronner Murrison, David W Dowdy
INTRODUCTION: Cost-effectiveness models for infectious disease interventions often require transmission models that capture the indirect benefits from averted subsequent infections. Compartmental models based on ordinary differential equations are commonly used in this context. Decision trees are frequently used in cost-effectiveness modeling and are well suited to describing diagnostic algorithms. However, complex decision trees are laborious to specify as compartmental models and cumbersome to adapt, limiting the detail of algorithms typically included in transmission models...
November 2018: Medical Decision Making: An International Journal of the Society for Medical Decision Making
journal
journal
28204
2
3
Fetch more papers »
Fetching more papers... Fetching...
Read by QxMD. Sign in or create an account to discover new knowledge that matter to you.
Remove bar
Read by QxMD icon Read
×

Search Tips

Use Boolean operators: AND/OR

diabetic AND foot
diabetes OR diabetic

Exclude a word using the 'minus' sign

Virchow -triad

Use Parentheses

water AND (cup OR glass)

Add an asterisk (*) at end of a word to include word stems

Neuro* will search for Neurology, Neuroscientist, Neurological, and so on

Use quotes to search for an exact phrase

"primary prevention of cancer"
(heart or cardiac or cardio*) AND arrest -"American Heart Association"