Reliability of coded data to identify earliest indications of cognitive decline, cognitive evaluation and Alzheimer's disease diagnosis: a pilot study in England.

OBJECTIVES: Evaluate the reliability of using diagnosis codes and prescription data to identify the timing of symptomatic onset, cognitive assessment and diagnosis of Alzheimer's disease (AD) among patients diagnosed with AD. METHODS: This was a retrospective cohort study using the UK Clinical Practice Research Datalink (CPRD). The study cohort consisted of a random sample of 50 patients with first AD diagnosis in 2010-2013. Additionally, patients were required to have a valid text-field code and a hospital episode or a referral in the 3 years before the first AD diagnosis. The earliest indications of cognitive impairment, cognitive assessment and AD diagnosis were identified using two approaches: (1) using an algorithm based on diagnostic codes and prescription drug information and (2) using information compiled from manual review of both text-based and coded data. The reliability of the code-based algorithm for identifying the earliest dates of the three measures described earlier was evaluated relative to the comprehensive second approach. Additionally, common cognitive assessments (with and without results) were described for both approaches. RESULTS: The two approaches identified the same first dates of cognitive symptoms in 33 (66%) of the 50 patients, first cognitive assessment in 29 (58%) patients and first AD diagnosis in 43 (86%) patients. Allowing for the dates from the two approaches to be within 30 days, the code-based algorithm's success rates increased to 74%, 70% and 94%, respectively. Mini-Mental State Examination was the most commonly observed cognitive assessment in both approaches; however, of the 53 tests performed, only 19 results were observed in the coded data. CONCLUSIONS: The code-based algorithm shows promise for identifying the first AD diagnosis. However, the reliability of using coded data to identify earliest indications of cognitive impairment and cognitive assessments is questionable. Additionally, CPRD is not a recommended data source to identify results of cognitive assessments.

The GERAS Study: a prospective observational study of costs and resource use in community dwellers with Alzheimer's disease in three European countries--study design and baseline findings.

To address socioeconomic challenges associated with its increasing prevalence, data are needed on country-level resource use and costs associated with Alzheimer's disease (AD). GERAS is an 18-month observational study being conducted in France, Germany, and the U.K. (with an 18-month extension in France and Germany), aimed at determining resource use and total costs associated with AD, stratified by AD severity at baseline. Resource use information and time spent on informal care by non-professional caregivers was obtained using the Resource Utilization in Dementia instrument. Total baseline societal costs were based on four cost components: patient health care costs, patient social care costs, caregiver health care costs, and caregiver informal care costs. Overall, 1,497 community-dwelling patients with AD were analyzed at baseline. Estimated mean monthly total societal costs per patient at baseline differed significantly between groups with mild, moderate, and moderately severe/severe AD (p < 0.001 in each country): euro $1,418, euro 1,737, and euro 2,453 in France; euro 1,312, euro $2,412, and euro 3,722 in Germany; and euro 1,621, euro 1,836, andeuro 2,784 in the U.K., respectively. All cost components except caregiver health care costs increased with AD severity. Informal caregiver costs were the largest cost component accounting for about half to just over 60% of total societal costs, depending on country and AD severity group. In conclusion, GERAS study baseline results showed that country-specific costs increase with AD severity. Informal care costs formed the greatest proportion of total societal costs, increasing with AD severity independent of costing method. Longitudinal data will provide information on cost trends with disease progression.