Newborn Screening Long Term Follow-Up in the Medical Home

This demonstration project explored the feasibility of utilizing data from pediatric primary care providers to evaluate the long-term outcomes of children with disorders identified by newborn screening (NBS). Compliance with national guidelines for care and the morbidity for this population was also examined. Primary care practices were recruited and patients with sickle cell disease or who were deaf/hard of hearing were given the opportunity to enroll in the study. Data were collected on the quality of the medical home with practice data compared to family responses. Clinical outcomes for each patient were assessed by review of medical records and patient surveys. These data sources were compared to determine accuracy of primary care data, morbidity, and receipt of preventive care. Electronic data sharing was explored through transmission of Clinical Document Architecture (CDA) files. Care coordination was a challenge, even in highly accredited medical homes. Providers did not have complete information regarding clinical outcomes and children were not consistently receiving recommended preventive care. Electronic data sharing with public health departments encountered interface challenges. Primary care providers in the USA should not currently be used as a sole source to evaluate long-term outcomes of children with disorders identified by NBS

Sequence-matched probes produce increased cross-platform consistency and more reproducible biological results in microarray-based gene expression measurements

Cancer derived microarray data sets are routinely produced by various platforms that are either commercially available or manufactured by academic groups. The fundamental difference in their probe selection strategies holds the promise that identical observations produced by more than one platform prove to be more robust when validated by biology. However, cross-platform comparison requires matching corresponding probe sets. We are introducing here sequence-based matching of probes instead of gene identifier-based matching. We analyzed breast cancer cell line derived RNA aliquots using Agilent cDNA and Affymetrix oligonucleotide microarray platforms to assess the advantage of this method. We show, that at different levels of the analysis, including gene expression ratios and difference calls, cross-platform consistency is significantly improved by sequence- based matching. We also present evidence that sequence-based probe matching produces more consistent results when comparing similar biological data sets obtained by different microarray platforms. This strategy allowed a more efficient transfer of classification of breast cancer samples between data sets produced by cDNA microarray and Affymetrix gene-chip platforms