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Objective To evaluate the validity of the Utah statewide All‐Payer Claims Database (APCD), we compared breast cancer‐specific treatments and dosages with gold‐standard ion of medical records. Study Design In this pilot study, breast cancer treatments were ed by a certified tumor registrar at the Utah Cancer Registry (UCR) for patients diagnosed in 2013 with breast cancer. The ion of medical records was the gold standard for comparison with treatments identified in the APCD. The reliability and agreement between the treatment identified in the APCD and ion data were measured with sensitivity and specificity. Dose consistency was measured with the intraclass correlation coefficients (ICC). Results Compared with the 186 ions, the sensitivity of the APCD to identify chemotherapy agents was high: 89% for any agent, 91% for carboplatin, 83% for docetaxel, 82% for doxorubicin, or 94.7% for biologic therapy. The consistency between the chemotherapy dosage identified in the claims and the ion varied from 63% to 76%. For radiotherapy, the sensitivity of the claims to identify the completed radiotherapy regimen was 66%. The ICC between radiotherapy doses identified in the claims and the ion was 54% (95% confidence interval [CI], 48%, 67%). Conclusions Employing these novel methods, the claims were highly reliable in identifying cancer treatment agents overall, namely carboplatin, docetaxel, and trastuzumab. The claims were of moderate utility in capturing the treatment dose information. In addition to the APCD, the use of multiple data sources improved the completeness of cancer treatment information.

Abstract Background and Objectives Older adult multimorbidity trajectories are helpful for understanding the current and future health patterns of aging populations. The construction of multimorbidity trajectories from comorbidity index scores will help inform public health and clinical interventions targeting those individuals that are on unhealthy trajectories. Investigators have used many different techniques when creating multimorbidity trajectories in prior literature, and no standard way has emerged. This study compares and contrasts multimorbidity trajectories constructed from various methods. Research Design and Methods We describe the difference between aging trajectories constructed with the Charlson Comorbidity Index (CCI) and Elixhauser Comorbidity Index (ECI). We also explore the differences between acute (single-year) and chronic (cumulative) derivations of CCI and ECI scores. Social determinants of health can affect disease burden over time; thus, our models include income, race/ethnicity, and sex differences. Results We use group-based trajectory modeling (GBTM) to estimate multimorbidity trajectories for 86,909 individuals aged 66–75 in 1992 using Medicare claims data collected over the following 21 years. We identify low-chronic disease and high-chronic disease trajectories in all 8 generated trajectory models. Additionally, all 8 models satisfied prior established statistical diagnostic criteria for well-performing GBTM models. Discussion and Implications Clinicians may use these trajectories to identify patients on an unhealthy path and prompt a possible intervention that may shift the patient to a healthier trajectory.