Evaluating the impact of genetic counseling and testing with signal detection methods

Protocol for the "Implementation, adoption, and utility of family history in diverse care settings" study

Background

Risk assessment with a thorough family health history is recommended by numerous organizations and is now a required component of the annual physical for Medicare beneficiaries under the Affordable Care Act. However, there are several barriers to incorporating robust risk assessments into routine care. MeTree, a web-based patient-facing health risk assessment tool, was developed with the aim of overcoming these barriers. In order to better understand what factors will be instrumental for broader adoption of risk assessment programs like MeTree in clinical settings, we obtained funding to perform a type III hybrid implementation-effectiveness study in primary care clinics at five diverse healthcare systems. Here, we describe the study’s protocol.

Methods/design

MeTree collects personal medical information and a three-generation family health history from patients on 98 conditions. Using algorithms built entirely from current clinical guidelines, it provides clinical decision support to providers and patients on 30 conditions. All adult patients with an upcoming well-visit appointment at one of the 20 intervention clinics are eligible to participate. Patient-oriented risk reports are provided in real time. Provider-oriented risk reports are uploaded to the electronic medical record for review at the time of the appointment. Implementation outcomes are enrollment rate of clinics, providers, and patients (enrolled vs approached) and their representativeness compared to the underlying population. Primary effectiveness outcomes are the percent of participants newly identified as being at increased risk for one of the clinical decision support conditions and the percent with appropriate risk-based screening. Secondary outcomes include percent change in those meeting goals for a healthy lifestyle (diet, exercise, and smoking). Outcomes are measured through electronic medical record data abstraction, patient surveys, and surveys/qualitative interviews of clinical staff.

Discussion

This study evaluates factors that are critical to successful implementation of a web-based risk assessment tool into routine clinical care in a variety of healthcare settings. The result will identify resource needs and potential barriers and solutions to implementation in each setting as well as an understanding potential effectiveness.

Trial registration

NCT01956773

From ideas to efficacy: The ORBIT model for developing behavioral treatments for chronic diseases

OBJECTIVE

Given the critical role of behavior in preventing and treating chronic diseases, it is important to accelerate the development of behavioral treatments that can improve chronic disease prevention and outcomes. Findings from basic behavioral and social sciences research hold great promise for addressing behaviorally based clinical health problems, yet there is currently no established pathway for translating fundamental behavioral science discoveries into health-related treatments ready for Phase III efficacy testing. This article provides a systematic framework for developing behavioral treatments for preventing and treating chronic diseases.

METHOD

The Obesity-Related Behavioral Intervention Trials (ORBIT) model for behavioral treatment development features a flexible and progressive process, prespecified clinically significant milestones for forward movement, and return to earlier stages for refinement and optimization.

RESULTS

This article presents the background and rationale for the ORBIT model, a summary of key questions for each phase, a selection of study designs and methodologies well-suited to answering these questions, and prespecified milestones for forward or backward movement across phases.

CONCLUSIONS

The ORBIT model provides a progressive, clinically relevant approach to increasing the number of evidence-based behavioral treatments available to prevent and treat chronic diseases. (PsycINFO Database Record

Assessing the Predictive Accuracy of hMLH1 and hMSH2 Mutation Probability Models

Hereditary nonpolyposis colorectal cancer (HNPCC) is characterized by a susceptibility to colorectal and extra-colonic cancers. Several guidelines exist for the identification of families suspected of having HNPCC, however these guidelines lack adequate sensitivity and specificity. In an attempt to improve accuracy for the detection of individuals with HNPCC, the Wijnen pre-test probability model (1998) and Myriad Genetics Laboratory prevalence table (2004) were developed. Here we evaluate the Wijnen model and Myriad table at predicting the presence of a mutation in individuals undergoing genetic testing for HNPCC. Forty-nine patients who had undergone genetic testing for germline mutations in hMLH1 and/or hMSH2 were part of our analysis. Our results revealed that the revised Bethesda guidelines performed with the highest sensitivity for germline mutations (94.4%), however the specificity was low (12.9%). Using a 10.0% mutation probability threshold, the Wijnen model and Myriad table had sensitivities of 55.6 and 60.0%, respectively and specificities of 54.8 and 23.8%, respectively. The Wijnen model and Myriad table were poor predictors of mutation prevalence, which is shown by the areas underneath their corresponding receiver operator characteristic curves (0.616 and 0.400, respectively). The results of this study demonsrate that neither the Wijnen model nor the Myriad table are sensitive or specific enough to be used as the only indication when to offer genetic testing for HNPCC.