Incidence and Survival for Patients Diagnosed With Breast, Colorectal, and Lung Cancer in an Integrated System.

INTRODUCTION: Documenting trends in cancer incidence and survival is a national priority. This study estimated age- and sex-adjusted incidence and 5-year relative survival among patients with cancer diagnosed within Kaiser Permanente compared to Surveillance, Epidemiology, and End Results (SEER) estimates. METHODS: The cohort included Kaiser Permanente health plan members diagnosed with breast (BC), colorectal (CRC), or lung cancer (LC) between January 1, 1999 and December 31, 2018. Incidence was computed as age-adjusted rates per 100,000 member-years. SEER*Stat was used to compute 5-year relative survival. RESULTS: Kaiser Permanente BC incidence rates were persistently higher than SEER from 2004 (126.5 [95% confidence interval (CI) = 123.2-129.9] vs 122.6 [95% CI = 121.3-123.2]) through 2013 (132.06 [95% CI = 129.5-135.7] vs 126.7 [95% CI = 125.9-127.5]). Kaiser Permanente CRC and LC incidence rates were lower than SEER for all years except 2008, showing a spike in CRC incidence (51.5 [95% CI = 49.9-53.0] vs 46.1 [95% CI = 45.7-46.4]). Kaiser Permanente BC, CRC, and LC survival estimates for all stages were higher than SEER. CONCLUSIONS: Incidence rates for all-stage and localized-stage BC were consistently higher for Kaiser Permanente than for SEER. CRC and LC rates were lower. Kaiser Permanente survival rates were consistently higher than for SEER. The strengths of these findings are associated with the ability to capture "gold-standard" cancer registry data on defined Kaiser Permanente populations. However, findings should be interpreted cautiously given differences in the underlying populations and secular and regional differences between Kaiser Permanente and SEER. The Kaiser Permanente population is younger and more racially diverse than SEER aggregate populations, and Kaiser Permanente members are insured with access to preventive care (eg, smoking cessation programs, cancer screening).

A standardized relative resource cost model for medical care: application to cancer control programs.

Medicare data represent 75% of aged and permanently disabled Medicare beneficiaries enrolled in the fee-for-service (FFS) indemnity option, but the data omit 25% of beneficiaries enrolled in Medicare Advantage health maintenance organizations (HMOs). Little research has examined how longitudinal patterns of utilization differ between HMOs and FFS. The Burden of Cancer Study developed and implemented an algorithm to assign standardized relative costs to HMO and Medicare FFS data consistently across time and place. Medicare uses 15 payment systems to reimburse FFS providers for covered services. The standardized relative resource cost algorithm (SRRCA) adapts these various payment systems to utilization data. We describe the rationale for modifications to the Medicare payment systems and discuss the implications of these modifications. We applied the SRRCA to data from four HMO sites and the linked Surveillance, Epidemiology, and End Results-Medicare data. Some modifications to Medicare payment systems were required, because data elements needed to categorize utilization were missing from both data sources. For example, data were not available to create episodes for home health services received, so we assigned costs per visit based on visit type (nurse, therapist, and aide). For inpatient utilization, we modified Medicare's payment algorithm by changing it from a flat payment per diagnosis-related group to daily rates for diagnosis-related groups to differentiate shorter versus longer stays. The SRRCA can be used in multiple managed care plans and across multiple FFS delivery systems within the United States to create consistent relative cost data for economic analyses. Prior to international use of the SRRCA, data need to be standardized.