Agreement between self-reported morbidity and pharmacy claims data for prescribed medications in an older community based population.

BACKGROUND: Studies have indicated variability around prevalence estimates of multimorbidity due to poor consensus regarding its definition and measurement. Medication-based measures of morbidity may be valuable resources in the primary-care setting where access to medical data can be limited. We compare the agreement between patient self-reported and medication-based morbidity; and examine potential patient-level predictors of discordance between these two measures of morbidity in an older (≥ 50 years) community-based population. METHODS: A retrospective cohort study was performed using national pharmacy claims data linked to The Irish LongituDinal study on Ageing (TILDA). Morbidity was measured by patient self-report (TILDA) and two medication-based measures, the Rx-Risk (< 65 years) and Rx-Risk-V (≥65 years), which classify drug claims into chronic disease classes. The kappa statistic measured agreement between self-reported and medication-based morbidity at the individual patient-level. Multivariate logistic regression was used to examine patient-level characteristics associated with discordance between measures of morbidity. RESULTS: Two thousand nine hundred twenty-five patients were included (< 65 years: N = 1095, 37.44%; and ≥ 65 years: N = 1830 62.56%). Hypertension and high cholesterol were the most prevalent self-reported morbidities in both age cohorts. Agreement was good or very good (κ = 0.61-0.81) for diabetes, osteoporosis and glaucoma; and moderate for high cholesterol, asthma, Parkinson's and angina (κ = 0.44-0.56). All other conditions had fair or poor agreement. Age, gender, marital status, education, poor-delayed recall, depression and polypharmacy were significantly associated with discordance between morbidity measures. CONCLUSIONS: Most conditions achieved only moderate or fair agreement between self-reported and medication-based morbidity. In order to improve the accuracy in prevalence estimates of multimorbidity, multiple measures of multimorbidity may be necessary. Future research should update the current Rx-Risk algorithms in-line with current treatment guidelines, and re-assess the feasibility of using these indices alone, or in combination with other methods, to yield more accurate estimates of multimorbidity.

Patterns of comorbidities in women with breast cancer: a Canadian population-based study.

PURPOSE: Improving the understanding of co-existing chronic diseases prior to and after the diagnosis of cancer may help to facilitate therapeutic decision making in clinical practice. This study aims to examine patterns of comorbidities in Canadian women with breast cancer. METHODS: We conducted a retrospective cohort study using provincial linked administrative health datasets from British Columbia, Canada, between 2000 and 2013. Women diagnosed with breast cancer between 2005 and 2009 were identified. The index date was defined as the date of diagnosis of breast cancer. Subsets of the breast cancer cohort were identified based on the absence of individual type of comorbidity of interest within 5 years prior to breast cancer diagnosis. For each subset, cases were then individually matched by year of birth at 1:2 ratios with controls without a history of cancer and the individual type of comorbidity of interest within 5 years prior to the assigned index year, matching with the year of breast cancer diagnosis of the corresponding case. Baseline comorbidities were measured over a 1-year period prior to the index date using two comorbidity indices, Rx-Risk-V and Aggregated Diagnosis Groups (ADG). Cox regression model was used to assess the development of seven specific comorbidities after the index date between women with breast cancer and non-cancer women. RESULTS: The most prevalent baseline comorbidity in the breast cancer cohort measured using the Rx-Risk-V model was cardiovascular conditions (39.0%), followed by pain/pain-inflammation (34.8%). The most prevalent category measured using the ADG model was major signs or symptoms (71.8%), followed by stable chronic medical conditions (52.2%). The risks of developing ischemic heart disease, heart failure, depression, diabetes, osteoporosis, and hypothyroidism were higher in women with breast cancer compared to women without cancer, with the hazard ratios ranging from 1.09 (95 CI% 1.03-1.16) for ischemic heart disease to 2.10 (95% CI 1.99-2.21) for osteoporosis in the model adjusted for baseline comorbidity measured using Rx-Risk-V score. CONCLUSION: Women with breast cancer had a higher risk of developing new comorbidities than women without cancer. Development of coordinated care models to manage multiple chronic diseases among breast cancer patients is warranted.