Development and validation of a 5-year mortality prediction model using regularized regression and Medicare data.

PURPOSE: De-implementation of low-value services among patients with limited life expectancy is challenging. Robust mortality prediction models using routinely collected health care data can enhance health care stakeholders' ability to identify populations with limited life expectancy. We developed and validated a claims-based prediction model for 5-year mortality using regularized regression methods. METHODS: Medicare beneficiaries age 66 or older with an office visit and at least 12 months of pre-visit continuous Medicare A/B enrollment were identified in 2008. Five-year mortality was assessed through 2013. Secondary outcomes included 30-, 90-, and 180-day and 1-year mortality. Claims-based predictors, including comorbidities and indicators of disability, frailty, and functional impairment, were selected using regularized logistic regression, applying the least absolute shrinkage and selection operator (LASSO) in a random 80% training sample. Model performance was assessed and compared with the Gagne comorbidity score in the 20% validation sample. RESULTS: Overall, 183 204 (24%) individuals died. In addition to demographics, 161 indicators of comorbidity and function were included in the final model. In the validation sample, the c-statistic was 0.825 (0.823-0.828). Median-predicted probability of 5-year mortality was 14%; almost 4% of the cohort had a predicted probability greater than 80%. Compared with the Gagne score, the LASSO model led to improved 5-year mortality classification (net reclassification index = 9.9%; integrated discrimination index = 5.2%). CONCLUSIONS: Our claims-based model predicting 5-year mortality showed excellent discrimination and calibration, similar to the Gagne score model, but resulted in improved mortality classification. Regularized regression is a feasible approach for developing prediction tools that could enhance health care research and evaluation of care quality.

Developing a Quality Measurement Strategy in an Academic Primary Care Setting: An Environmental Scan.

PURPOSE: The purpose of this project was to: (1) develop a strategy for primary care quality measurement using an environmental scan and interviews to identify best practices and candidate measures; (2) present recommendations to facilitate successful measurement. METHODS: Following stakeholder interviews and review of existing measures, we created a three-tiered recommendation system for selecting and implementing measures. We also developed a framework for reviewing and prioritizing measures and prepared a detailed project report. RESULTS: Interviews provided a broader perspective on measuring quality, including implementing measures, measuring value, and identifying measurement gaps. Our recommendations fall into three tiers: Tier 1 measures can be implemented quickly and include clinical processes and outcomes for preventive care and disease states. Tier 2 measures require modifications to electronic health record, workflows, and/or staff preparation. Tier 3 (Strategic Vision) addresses topics that should be incorporated in the future to ensure high-quality primary care (adherence, patient activation, patient experience, teamness, staff satisfaction, and value), and infrastructure development to support ongoing quality measurement. CONCLUSIONS: Implementing a quality measurement strategy is challenging and labor-intensive but is necessary to improve healthcare quality. Our work demonstrates the effort and investment required to progress quality measurement and offers recommendations for successfully undertaking this type of endeavor.

Design of a randomized clinical trial of a colorectal cancer screening decision aid to promote appropriate screening in community-dwelling older adults.

BACKGROUND: Appropriate colorectal cancer screening in older adults should be aligned with the likelihood of net benefit. In general, patient decision aids improve knowledge and values clarity, but in older adults, they may also help patients identify their individual likelihood of benefit and foster individualized decision-making. We report on the design of a randomized clinical trial to understand the effects of a patient decision aid on appropriate colorectal cancer screening. This report includes a description of the baseline characteristics of participants. METHODS: English-speaking primary care patients aged 70-84 years who were not currently up to date with screening were recruited into a randomized clinical trial comparing a tailored colorectal cancer screening decision aid with an attention control. The intervention group received a decision aid that included a values clarification exercise and individualized decision-making worksheet, while the control group received an educational pamphlet on safe driving behaviors. The primary outcome was appropriate screening at 6 months based on chart review. We used a composite measure to define appropriate screening as screening for participants in good health, a discussion about screening for patients in intermediate health, and no screening for patients in poor health. Health state was objectively determined using patients' Charlson Comorbidity Index score and age. RESULTS: A total of 14 practices in central North Carolina participated as part of a practice-based research network. In total, 424 patients were recruited to participate and completed a baseline visit. Overall, 79% of participants were White and 58% female, with a mean age of 76.8 years. Patient characteristics between groups were similar by age, gender, race, education, insurance coverage, or work status. Overall, 70% had some college education or more, 57% were married, and virtually all had Medicare insurance (90%). The three primary medical conditions among the cohort were a history of diabetes, pneumonia, and cancer (28%, 26%, and 21%, respectively). CONCLUSION: We designed a randomized clinical trial to test a novel use of a patient decision aid to promote appropriate colorectal cancer screening and have recruited a diverse study population that seems similar between the intervention and control groups. The study should be able to determine the ability of a patient decision aid to increase individualized and appropriate colorectal cancer screening.