Web-based Risk Assessment Tool Research Articles

Community focus groups about a COVID-19 individual risk assessment tool: access, understanding and usefulness

To make informed COVID-19 related decisions, individuals need information about their personal risks and how those risks may vary with specific demographic and health characteristics. The Fight COVID Milwaukee web-based risk assessment tool allows for assessment of COVID-19 mortality risk as a function of personal and neighborhood characteristics. The purpose of this study is to explore public understanding of this risk assessment tool and risk perception through community focus groups. Individuals were recruited from the general adult population in Milwaukee County, Wisconsin, USA, to participate in nine online focus groups where the risk assessment tool was presented for feedback. Three main themes were identified in the focus groups regarding the web-based risk assessment tool: some challenges in accessibility, variable ease of understanding, and personal usefulness but uncertain value for others. This paper explores how members of the community interpret individual risk assessments and life expectancy estimations, and how these vary with age, gender, race/ethnicity, socioeconomic status, and pre-existing comorbidities.

Cancer risk assessment models versus National Comprehensive Cancer Network guidelines: What is the most comprehensive method to assess cancer risk and triage for genetic testing? (373)

Cancer risk assessment models versus National Comprehensive Cancer Network guidelines: What is the most comprehensive method to assess cancer risk and triage for genetic testing? (373)

Correction: PARS risk charts: A 10-year study of risk assessment for cardiovascular diseases in Eastern Mediterranean Region.

[This corrects the article DOI: 10.1371/journal.pone.0189389.].

PARS risk charts: A 10-year study of risk assessment for cardiovascular diseases in Eastern Mediterranean Region.

This study was designed to develop a risk assessment chart for the clinical management and prevention of the risk of cardiovascular disease (CVD) in Iranian population, which is vital for developing national prevention programs. The Isfahan Cohort Study (ICS) is a population-based prospective study of 6504 Iranian adults ≥35 years old, followed-up for ten years, from 2001 to 2010. Behavioral and cardiometabolic risk factors were examined every five years, while biennial follow-ups for the occurrence of the events was performed by phone calls or by verbal autopsy. Among these participants, 5432 (2784 women, 51.3%) were CVD free at baseline examination and had at least one follow-up. Cox proportional hazard regression was used to predict the risk of ischemic CVD events, including sudden cardiac death due to unstable angina, myocardial infarction, and stroke. The model fit statistics such as area under the receiver-operating characteristic (AUROC), calibration chi-square and the overall bias were used to assess the model performance. We also tested the Framingham model for comparison. Seven hundred and five CVD events occurred during 49452.8 person-years of follow-up. The event probabilities were calculated and presented color-coded on each gender-specific PARS chart. The AUROC and Harrell’s C indices were 0.74 (95% CI, 0.72–0.76) and 0.73, respectively. In the calibration, the Nam-D’Agostino χ2 was 10.82 (p = 0.29). The overall bias of the proposed model was 95.60%. PARS model was also internally validated using cross-validation. The Android app and the Web-based risk assessment tool were also developed as to have an impact on public health. In comparison, the refitted and recalibrated Framingham models, estimated the CVD incidence with the overall bias of 149.60% and 128.23% for men, and 222.70% and 176.07% for women, respectively. In conclusion, the PARS risk assessment chart is a simple, accurate, and well-calibrated tool for predicting a 10-year risk of CVD occurrence in Iranian population and can be used in an attempt to develop national guidelines for the CVD management.

Web-Based Risk Assessment Tool Using Integrated Duration–Cost Influence Network Model

AbstractThe major challenges of project risk assessment may be attributed to the knowledge requirements for determining the level of uncertainty and the development of complex models to predict project outcomes. The duration–cost influence network is an adequate model that can be used for activity-based risk modeling. In this study, a scenario analysis feature is added to this model and a Web-based tool is developed that can be used to calculate risk-adjusted duration and cost, considering the risks affecting cost and duration of individual activities. Monte Carlo simulation is used to create scenarios, and the output of these scenarios is calculated by using the cost–duration influence system that simulates the vulnerability of the project to the identified risk factors. The Web-based tool can be used by decision makers during the preplanning stage of construction projects to estimate the cost and duration implications of various risk occurrence scenarios, determine contingencies, and prepare risk-manage...

Electronic Patient Messages to Promote Colorectal Cancer Screening

Colorectal cancer is a leading cause of cancer mortality, yet effective screening tests are often underused. Electronic patient messages and personalized risk assessments delivered via an electronic personal health record could increase screening rates. We conducted a randomized controlled trial in 14 ambulatory health centers involving 1103 patients ranging in age from 50 to 75 years with an active electronic personal health record who were overdue for colorectal cancer screening. Patients were randomly assigned to receive a single electronic message highlighting overdue screening status with a link to a Web-based tool to assess their personal risk of colorectal cancer. The outcomes included colorectal cancer screening rates at 1 and 4 months. Screening rates were higher at 1 month for patients who received electronic messages than for those who did not (8.3% vs 0.2%, P < .001), but this difference was no longer significant at 4 months (15.8% vs 13.1%, P = .18). Of 552 patients randomized to receive the intervention, 296 (54%) viewed the message, and 47 (9%) used the Web-based risk assessment tool. Among 296 intervention patients who viewed the electronic message, risk tool users were more likely than nonusers to request screening examinations (17% vs 4%, P = .04) and to be screened (30% vs 15%, P = .06). One-fifth of patients (19%) using the risk assessment tool were estimated to have an above-average risk for colorectal cancer. Electronic messages to patients produce an initial increase in colorectal cancer screening rates, but this effect is not sustained over time. clinicaltrials.gov Identifier: NCT01032746.

A Comparison of Prediction Models for Fractures in Older Women

A Web-based risk assessment tool (FRAX) using clinical risk factors with and without femoral neck bone mineral density (BMD) has been incorporated into clinical guidelines regarding treatment to prevent fractures. However, it is uncertain whether prediction with FRAX models is superior to that based on parsimonious models. We conducted a prospective cohort study in 6252 women 65 years or older to compare the value of FRAX models that include BMD with that of parsimonious models based on age and BMD alone for prediction of fractures. We also compared FRAX models without BMD with simple models based on age and fracture history alone. Fractures (hip, major osteoporotic [hip, clinical vertebral, wrist, or humerus], and any clinical fracture) were ascertained during 10 years of follow-up. Area under the curve (AUC) statistics from receiver operating characteristic curve analysis were compared between FRAX models and simple models. The AUC comparisons showed no differences between FRAX models with BMD and simple models with age and BMD alone in discriminating hip (AUC, 0.75 for the FRAX model and 0.76 for the simple model; P = .26), major osteoporotic (AUC, 0.68 for the FRAX model and 0.69 for the simple model; P = .51), and clinical fracture (AUC, 0.64 for the FRAX model and 0.63 for the simple model; P = .16). Similarly, performance of parsimonious models containing age and fracture history alone was nearly identical to that of FRAX models without BMD. The proportion of women in each quartile of predicted risk who actually experienced a fracture outcome did not differ between FRAX and simple models (P > or = .16). Simple models based on age and BMD alone or age and fracture history alone predicted 10-year risk of hip, major osteoporotic, and clinical fracture as well as more complex FRAX models.