ArticleMedicare & medicaid research review2012
The effects of premium changes on ALL Kids, Alabama's CHIP program.
Article in Medicare & medicaid research review, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed.
- Health Expenditure Concentration and Characteristics of High-Cost Enrollees in CHIP.Inquiry : a journal of medical care organization, provision and financing · 2016Article
- Estimating premium sensitivity for children's public health insurance coverage: selection but no death spiral.Health services research · 2015Article
- Can increases in CHIP copayments reduce program expenditures on prescription drugs?Medicare & medicaid research review · 2014Article
- The Great Recession of 2007-2009 and Public Insurance Coverage for Children in Alabama: Enrollment and Claims Data from 1999-2011.Public health reports (Washington, D.C. : 1974)Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveDescribe the trends in enrollment and renewal in the Alabama Children's Health Insurance Plan (CHIP), ALL Kids, since its creation in 1998, and to estimate the effect that an annual premium increase, along with coincident increases in service copays, had on the decision to renew participation.
backgroundUnlike many other CHIP programs, ALL Kids is a standalone program that provides year long enrollment and contracts with the state's Blue Cross and Blue Shield program for its network of providers and its provider fee structure. In October 2003 premiums for individual coverage were increased by $50 per year and copays by $1 to $3 per visit. POPULATION STUDIED: This study is based upon a sample of 569,650 person-year observations of 230,255 children enrolled in the ALL Kids program between 1999 and 2009. STUDY
designThe study models enrollment as a time series of cross section renewal decisions and specifies a series of linear probability regression models to estimate the effect of changes in the premium shift on the decision to renew. A second analysis includes interaction effects of the premiums shift with demographics, health status, income and previous enrollment to estimate differential response across subgroups. PRINCIPAL
findingsThe increases in premiums and copays are estimated to have reduced program renewals by 6.1 to 8.3 percent depending upon how much time one allows for families to renew. Families with a child who has a chronic condition were more likely to renew coverage. However, those with chronic conditions, African-Americans and those with lower family incomes were more price-sensitive.
conclusionsAn increase in annual premiums and visit copays had a modest impact on program reenrollment with effects comparable to those found in Florida, New Hampshire, Kansas and Arizona, but smaller than those in Kentucky and Georgia.
Indexed as
Identifiers
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.