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The International Meeting for Simulation in Healthcare
2015-01-10 - 2015-01-14    
All Day
Registration is Open! Please join us on January 10-14, 2015 for our fifteenth annual IMSH at the Ernest N. Morial Convention Center in New Orleans, Louisiana. Over [...]
Finding Time for HIPAA Amid Deafening Administrative Noise
2015-01-14    
1:00 pm - 3:00 pm
January 14, 2015, Web Conference 12pm CST | 1pm EST | 11am MT | 10am PST | 9am AKST | 8am HAST Main points covered: [...]
Meaningful Use  Attestation, Audits and Appeals - A Legal Perspective
2015-01-15    
2:00 pm - 3:30 pm
Join Jim Tate, HITECH Answers  and attorney Matt R. Fisher for our first webinar event in the New Year.   Target audience for this webinar: [...]
iHT2 Health IT Summit
2015-01-20 - 2015-01-21    
All Day
iHT2 [eye-h-tee-squared]: 1. an awe-inspiring summit featuring some of the world.s best and brightest. 2. great food for thought that will leave you begging for more. 3. [...]
Chronic Care Management: How to Get Paid
2015-01-22    
1:00 pm - 2:00 pm
Under a new chronic care management program authorized by CMS and taking effect in 2015, you can bill for care that you are probably already [...]
Proper Management of Medicare/Medicaid Overpayments to Limit Risk of False Claims
2015-01-28    
1:00 pm - 3:00 pm
January 28, 2015 Web Conference 12pm CST | 1pm EST | 11am MT | 10am PST | 9AM AKST | 8AM HAST Topics Covered: Identify [...]
Events on 2015-01-10
Events on 2015-01-20
iHT2 Health IT Summit
20 Jan 15
San Diego
Events on 2015-01-22
Articles

Nov 18: EHR useful for pediatric health insurance surveillance

pediatric health insurance surveillance

EHR useful for pediatric health insurance surveillance

1. Electronic health records databases can be used by providers to track insurance coverage of their patients.

2. In this study, 30% of children who were uninsured on their first clinic visit remained uninsured at subsequent visits, suggesting the need for insurance surveillance and intervention.

Evidence Rating Level: 2 (Good)

Study Rundown: Insurance coverage options are changing rapidly following the 2012 passage of the Affordable Care Act. Although pediatric patients previously had access to public insurance programs under the Children’s Health Insurance Program, many experienced gaps in coverage or had difficulty accessing the program. In order to best assist primary care providers in tracking patient’s insurance coverage status and to identify families requiring additional support to obtain and maintain coverage, this study used electronic health records (EHR) to characterize uninsured patients in a member-based, nonprofit community health clinic provider network. Patients who visited the primary care network between 2010 and 2011, were included in the study and, of these, 21% were uninsured at their first visit and 30% remained uninsured during subsequent visits. Within this cohort, children between 15-18 were more likely to be uninsured, and, differing from previous reports, racial and ethnic minorities were less likely to be uninsured. This study demonstrates that information collected via EHR may be useful when assessing health insurance status among discrete clinic patients to identify those in need of  coverage support. Despite the short, 1-year study period, EHR tracking provides a simple means of identifying vulnerable populations and may assist policy makers in understanding patterns of insurance access.

Click to read the study published today in Pediatrics

Relevant Reading: Disruptions in insurance coverage: patterns and relationship to health care access, unmet need, and utilization before enrollment in the State Children’s Health Insurance Program

In-Depth [retrospective cohort study]: This study analyzed EHR data collected through the Oregon Community Health Information Network (OCHIN), a collaborative of community health centers employing a common EHR, to evaluate health insurance coverage among pediatric patients within the network. A total of 185 989 children visited OCHIN sites during the January 2010 through December 2011 study period. Information collected included patients’ health insurance status, age, gender, household income, race, ethnicity and preferred language. Multiple regression analysis was completed to assess the potential relationship between insurance status and other variables. Of the patients identified, 21% were uninsured at their first clinic visit. The uninsured included 19% of children 0-14 years of age, and 29% of children 15-18 years of age. A total of 18% of nonwhite or Hispanic children were uninsured, compared with 24% of white, non-Hispanic children. Although nonwhite and/or Hispanic children had a lower odds of being uninsured than having Medicaid/Medicare (aOR, 0.73, 95% CI:  0.71-0.75), they had higher odds of being uninsured rather than having commercial insurance (aOR 1.50, 95% CI: 1.44-1.56). In addition, children from rural areas had lower odds of being uninsured than having Medicaid/Medicare coverage when compared to urban children (aOR, 0.89, 95% CI: 0.87-0.92). Of those identified without coverage, 30% were uninsured at all subsequent clinic visits, and 47% had no additional visits. Source