うつ病と不安に関するジャーナル
オープンアクセス
ISSN: 2167-0420
ISSN: 2167-0420
Maria Lopes
In the USA, about 12.8% of babies (more than half a million a year) are born prematurely. The rate of premature birth has increased by 36% since the early 1980’s, [1] and is now responsible for an estimated $26 billion in costs to the American healthcare system annually [2]. Unfortunately, little progress has been made to decrease prevalence in so serious condition. From a managed care perspective, a premature birth constitutes a potential high cost episode of care and high-risk pregnancies constitute a major category of high-cost for payers. In Medicaid, 27% of all inpatient charges and 60% of all hospital procedures covered by Medicaid [3] are related to pregnancy and although only 10% of pregnancies are considered high risk, they account for 57% of total newborn costs [4]. A recent analysis found that overall, 4% of the Medicaid population was responsible for 48% of program spending in 2001 [5]. These high-cost members translate into highly concentrated spending on only a small fraction of the entire population. In this paper we will identify ways in which new technology can improve the diagnostic accuracy of pregnancy-related disorders and assist in managing the costs of high risk obstetrics.