{'fraction_non_alphanumeric': 0.020813623462630087, 'fraction_numerical': 0.007568590350047304, 'mean_word_length': 5.370481927710843, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
PS1-16: Effect of Insurance Plan Choice on Utilization in Kaiser Permanente Colorado

Background/Aims There has been a shift in recent years from traditional HMO-type insurance products to high deductible or co-insurance plans. Kaiser Permanente Colorado (KPCO) has also added new service areas to the region that include Southern and Northern Colorado. In addition, the impending Affordable Care Act will be implemented in 2014 which may bring new and different members to KPCO. There is a need to describe socio-demographic and clinical characteristics by plan type in order to understand how members within these different plan types utilize KPCO resources and what data are available and identifiable within our source data systems. These answers will enable us to establish appropriate inclusion and exclusion criteria for future research studies. Methods All members with at least 1 day of membership from January, 2000 through July 2013 were identified. Membership within product lines and all associated utilization was based on calendar year. Patient characteristics, ambulatory visits, inpatient admissions, emergency department admissions, lab tests, tumors, pharmacy utilization and variations in therapy for certain diagnoses were obtained from the Virtual Data Warehouse (VDW). Socio-demographic characteristics, including gender, race, and age, were described by percentages. Clinical characteristics and variation in utilization were calculated on a per-person per-month measure and were compared for each region/insurance product/year combination. Results Demographics and utilization varied across all product lines and years. An increase in the number of different products offered was observed over time. Members in the HMO plan type were more likely to be younger, less educated and use more resources than members in other products. Some data were not easily identifiable in certain plan types. Conclusions These results indicate that demographic and clinical patterns do vary between plan types. These patterns need to be taken into account when creating cohorts in future research projects.