Family Well-being in MA
Definition of terms
Bivariate Analysis: An analysis of the relationship between two variables.
CSHCN: Children with special health care needs as defined by the U.S. Maternal and Child Health Bureau: “children who have or are at risk for chronic physical, developmental, behavioral or emotional conditions and who also require health and related services of a type or amount beyond that required by children generally.”
CSHCN Screener: A 5-item parent survey-based tool developed to identify CSHCN based on the U.S. Maternal and Child Health Bureau’s definition. A well-tested survey, developed by a national group of state leaders, families, experts and policymakers, it identifies a broad group of children based on consequences of their condition, as opposed to their specific diagnosis. It includes children with a wide array of conditions, levels of severity and service use need. The survey consists of 5 multi-part questions that each ask about a consequence the child might experience because of a physical or mental health condition. Those 5 health consequences are 1) use or need of prescription medication; 2) above average use or need of medical, mental health or educational services; 3) limited or prevented in ability to do things compared with others of same age; 4) use or need of specialized therapies (OT, PT, speech, etc.); and 5) treatment or counseling for emotional or developmental problems. In order to be identified as a child with special health care needs, the parent must report at least one of the above consequences and that the health consequence is due to a health condition that has lasted or is expected to last at least 12 months. For a copy of the CSHCN Screener click here.
Medical Home: A medical home is not a building, house, or hospital, but rather an approach to providing comprehensive primary care. A medical home is defined as primary care that is accessible, continuous, comprehensive, family centered, coordinated, compassionate, and culturally effective. A medical home addresses how a primary health care professional works in partnership with the family/patient to assure that all of the medical and non-medical needs of the patient are met. For more information on medical homes visit the National Center of Medical Homes Initiatives for Children with Special Needs.
Multivariate Analysis: An analysis of the relationship between a dependent variable (e.g. unmet need) and several independent variables (e.g. age, race, etc) simultaneously.
Odds Ratio (OR): The odds ratio is a way of comparing whether the probability of a certain event is the same for two groups. For example, suppose that seven out of 10 males are admitted to an engineering school while four of 10 females are admitted. The probability for admitting a male is p = 7/10 = .7. The probability for admitting a female is p = 4/10 = .4. Now we can use the probabilities to compute the admission odds for both males and females: odds(male) = .7/.4 = 1.75 and odds(female) = .4/.7 = .571. Next, we compute the odds ratio for admission: OR = 1.75/.571 = 3.06. Thus, the odds of a male being admitted are 3.06 times greater than for a female. Conversely, we can say that the odds of a female being admitted is one-third that of a male (.571/1.75 = .326 = approximately 1/3). (Adapted from http://www.ats.ucla.edu/stat/SAS/faq/oratio.htm).
Statistical significance, Confidence Interval (CI) and p-value: The statistical significance of a result tells us something about the degree to which the difference found between groups is “true” or if the result could have occurred by chance alone (that is, the data accurately represents the true population). Conventionally, the difference is statistically significant if the difference between groups could have occurred by chance alone in less than 1 time in 20. This is expressed as a p value < 0.05. The p-value represents the probability of error that is involved in accepting our observed result as valid. For example, a p-value of 0.05 indicates that there is a 5% probability that the relation between the variables found in our sample is just by chance and that we are 95% confident that estimates derived from the sample data accurately represent the true population value. Thus, the 95% confidence interval is the range of values within which we can be 95% sure that the true value lies for the whole population from whom the study population was selected.
More Statistics Help: For more help interpreting survey data, visit the BRFSS Data Systems Course, an excellent interactive teaching resource. Examples are from the Behavioral Risk Factor Surveillance System (BRFSS) survey; however, the concepts apply to National Survey of CSHCN and similar data.
