Estimates of the number of uninsured may differ for a number of reasons, such as which data are used for the estimate, how the data are interpreted, and the time-period over which the uninsured are defined. Monheit (1994) reviewed how estimates of the uninsured population are obtained and reached four general conclusions. First, a consistent, long-term series of estimates is not available. For example, the CPS, the most commonly used source for health insurance coverage, changed the content of its health insurance questions at various times, which has resulted in artificial changes in the number who are uninsured from one year to the next. Second, analysts using the same data may obtain varying estimates for the same time periods because the data can be interpreted in different ways. For example, estimates of the uninsured done by The Urban Institute using CPS data are lower than estimates by other groups using the same data because The Urban Institute adjusts their estimates for the known underreporting of Medicaid in the CPS. Third, as mentioned above, estimates across alternative data vary. And fourth, estimates vary depending upon the time-frame around which the estimate is made. For example, the number of persons uninsured throughout a given year will be less than the number of uninsured at a point in time which, in turn, will be less than the number of uninsured at any time during a given year.