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PurposeTo ascertain resource use, costs and risk of workforce absence in non‐infectious uveitis cases versus matched controls.MethodsIn a retrospective claims analysis of employees in the United States, prevalent (N = 705) and incident (N = 776) cases 18–64 years old with ≥2 diagnoses of non‐infectious intermediate, posterior or panuveitis were matched 1:1 to controls without uveitis. Persistent prevalent cases (treated for ≥90 days, N = 112) also were analysed. Outcomes were annual direct resource use and costs associated with inpatient stays; emergency department, outpatient and ophthalmologist/optometrist visits; and prescription drugs. Indirect resource use and costs associated with work loss from disability and medically related absenteeism also were compared. Multivariate regression assessed cost differences between cases and controls.ResultsCases had significantly (p < 0.05) more medical resource use versus controls including 0.4 versus 0.2 emergency visits and 16.5 versus 7.6 outpatient/other visits. Cases used more prescription drugs (7.8 versus 4.1) and had more disability days (10.3 versus 4.6), medically related absenteeism days (8.5 versus 3.8), and work loss days (18.7 versus 8.4) than controls (all p < 0.05). Total direct ($12 940 versus $3730) and indirect ($3144 versus $1378) costs were higher in cases than controls (all p < 0.05). Results for persistent cases suggested greater utilization and associated cost and work loss burden. Compared with controls, cases had significantly greater risks of workforce absence, leave of absence and long‐term disability (all p < 0.05).ConclusionNon‐infectious intermediate, posterior or panuveitis, particularly persistent disease, is associated with substantial medical and work loss costs suggesting an unmet need for more effective treatments.
228 Background: Use of anti-cancer therapies in the last 14-30 days of life may worsen patient outcomes and increase cost; accordingly, rate of chemotherapy use near EOL is an important quality measure. Contemporary benchmarks are needed, with transparent methods describing the cohort in which the measure is assessed, and criteria for calculation. Methods: Data on chemotherapy use, mortality, and cancer diagnosis was sourced from electronic health records (EHRs) of >8,000 patients seen between 2014-2016 at two large US academic centers, for whom dates of death were available. Death dates were sourced from the EHR and public records (e.g., obituaries). Patients were grouped by diagnosis using ICD-10 codes. Rates of infusional chemotherapy receipt within 14 or 30 days of death were calculated. Results: Across 10 tumor types, 3-7% of patients received chemotherapy within 14d of death, and 6-16% received it within 30d. Rates were stable from 2014-2016 and did not differ by cancer center. Rates were highest in diseases where patients may experience rapid clinical decline near EOL: in pancreatic and rectal cancer, 30d rates were 16% and 13%. The 30d rate was lowest (6%) in kidney cancer. When the cohort was restricted to only treated patients (who received >=5 chemotherapy administrations at the center), rates of chemotherapy use at EOL increased to 6-12% (14d) and 17-28% (30d). Conclusions: This study provides baseline estimates of current rates of EOL chemotherapy use at academic centers. Transparency in methodology is critical; for example, when the whole population of cancer patients seen at a center is considered, rates are low, but when the analysis is limited to patients who received chemotherapy there, rates nearly double. Further studies should focus on whether this quality measure is a meaningful driver of patient and health system outcomes. This work also demonstrates that it is possible to assess this metric across multiple centers; this approach could be easily scaled to all oncology practices integrated in a data sharing network. [Table: see text]
212 Background: Timely and appropriate biomarker testing guides evidence-based treatment decision-making in advanced non-small cell lung cancer (aNSCLC). American Society of Clinical Oncology (ASCO) and National Comprehensive Cancer Network (NCCN) guidelines recommend that all treatment-eligible patients with non-squamous, or squamous histology in non-smokers undergo EGFR and ALK biomarker testing prior to initiating first line therapy. Genentech’s Learning and Clinical Integration team and Flatiron Health explored the frequency of EGFR/ALK testing and overall time between advanced disease diagnosis, results receipt and treatment initiation in clinical oncology practices. Methods: Structured and unstructured data were obtained from Flatiron’s electronic health record database. 6,991 patients from 166 clinics diagnosed after 1/1/14 with at least 2 visits before 8/31/15 were randomly selected from the Flatiron aNSCLC national cohort of > 25,000 patients. Dates of specimen collection, results receipt and treatment start were collected. Results: EGFR/ALK testing was conducted in 75% of non-squamous patients with wide variation across practices (< 20% to 100%). For squamous patients, 15% were tested overall, but with dramatic variation across practices (0% to 100%). For patients with a positive test result available prior to initiation of first line treatment, 79% of EGFR+ and 94% of ALK+ patients received the appropriate targeted therapy. However, for those patients tested after initiation of first line therapy, only 41% of EGFR+ and 65% of ALK+ patients received appropriate targeted first line therapy. EGFR/ALK tests results were received > 4 weeks from aNSCLC diagnosis in 32% and 34% of patients, respectively. Validation testing indicated that delays were attributed to non-lab factors, as test results were returned in < 2 weeks in 95% of cases. Conclusions: Wide variation in real-world practice illustrates the need to improve adherence to ASCO and NCCN biomarker testing guidelines. Educational intervention to improve quality of care in aNSCLC should focus on ensuring testing of almost all non-squamous patients, limiting testing to the non-smoking squamous cell population, and ensuring timely ordering of testing by clinicians.
B, and stand-alone Part D plan coverage in the 12-months pre-and post-index date and have > 1 claim for psoriasis (ICD-9CM code 696.1) in the 12-month preindex period. Exclusion criteria included presence of other conditions for which these biologics are indicated, or receipt of any biologic in the 12-months preindex. Adherence to index biologic was defined as patients with proportion of days covered (PDC) > 0.80 during the 12-months post-index. Logistic regression analyses were conducted to determine the factors associated with being adherent. RESULTS: Our sample included 2,707 patients newly initiating biologics. Overall, mean PDC for any index biologic was 0.61 and only 38% were adherent to their index biologic in the 12 months following initiation. Mean PDC and adherence rates were similar between physician-administered and self-administered agents, but there were several differences by index biologic. Mean PDCs were 0.66 for infliximab (N= 318), 0.70 for ustekinumab (N= 280), 0.63 for adalimumab (N= 1084), and 0.56 for etanercept (N= 1025). Adherence rates were 49%, 43%, 41%, and 29%, respectively. Logistic regression indicated that older age, and female gender were associated with poor adherence. Index biologic was also a significant factor associated with being adherent. CONCLUSIONS: Adherence with biologic treatment for psoriasis is poor in the Medicare population with rates < 50% across all biologics. Urinary/Kidney disorders -Clinical outcomes studies PUK2
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