Your browser doesn't support javascript.
loading
Show: 20 | 50 | 100
Results 1 - 2 de 2
Filter
Add more filters










Database
Language
Publication year range
1.
Learn Health Syst ; 8(3): e10415, 2024 Jul.
Article in English | MEDLINE | ID: mdl-39036533

ABSTRACT

In 2006 following several years of preliminary study, the American Society of Clinical Oncology (ASCO) launched the Quality Oncology Practice Initiative (QOPI). This cancer-focused quality initiative evolved considerably over the next decade-and-a-half and is expanding globally. QOPI is undoubtedly the leading standard-bearer for quality cancer care and contemporary medical oncology practice. The program garners attention and respect among federal programs, private insurers, and medical oncology practices across the nation. The MaineHealth Cancer Care Network (MHCCN) has undergone expansive growth since 2017. The network provides cancer care to more than 70% of the cases in Maine in a largely rural health system in Northern New England. In fall 2020, the MHCCN QOPI project leadership, following collaborative discussions with the ASCO-QOPI team, elected to proceed with a health system-cancer network-wide QOPI certification. Key themes emerged over the course of our two-year journey including: (1) Developing a highly interprofessional team committed to the project; (2) Capitalizing on a single electronic medical record for data transmission to CancerLinQ; (3) Prior experience, especially policy development, in other cancer-focused accreditation programs across the network; and (4) Building consensus through quarterly stakeholder meetings and awarding Continuing Medical Education (CME) and American Board of Medical Specialists (ABMS) Maintenance of Certification (MOC) credits to oncologists. All participants demonstrated a genuine spirit to work together to achieve certification. We report our successful journey seeking ASCO-QOPI certification across our network, which to our knowledge is the first-of-its-kind endeavor.

2.
J Microbiol Methods ; 130: 95-99, 2016 11.
Article in English | MEDLINE | ID: mdl-27609714

ABSTRACT

BACKGROUND: Cystic fibrosis (CF) is an autosomal recessive disease characterized by recurrent lung infections. Studies of the lung microbiome have shown an association between decreasing diversity and progressive disease. 454 pyrosequencing has frequently been used to study the lung microbiome in CF, but will no longer be supported. We sought to identify the benefits and drawbacks of using two state-of-the-art next generation sequencing (NGS) platforms, MiSeq and PacBio RSII, to characterize the CF lung microbiome. Each has its advantages and limitations. METHODS: Twelve samples of extracted bacterial DNA were sequenced on both MiSeq and PacBio NGS platforms. DNA was amplified for the V4 region of the 16S rRNA gene and libraries were sequenced on the MiSeq sequencing platform, while the full 16S rRNA gene was sequenced on the PacBio RSII sequencing platform. Raw FASTQ files generated by the MiSeq and PacBio platforms were processed in mothur v1.35.1. RESULTS: There was extreme discordance in alpha-diversity of the CF lung microbiome when using the two platforms. Because of its depth of coverage, sequencing of the 16S rRNA V4 gene region using MiSeq allowed for the observation of many more operational taxonomic units (OTUs) and higher Chao1 and Shannon indices than the PacBio RSII. Interestingly, several patients in our cohort had Escherichia, an unusual pathogen in CF. Also, likely because of its coverage of the complete 16S rRNA gene, only PacBio RSII was able to identify Burkholderia, an important CF pathogen. CONCLUSION: When comparing microbiome diversity in clinical samples from CF patients using 16S sequences, MiSeq and PacBio NGS platforms may generate different results in microbial community composition and structure. It may be necessary to use different platforms when trying to correctly identify dominant pathogens versus measuring alpha-diversity estimates, and it would be important to use the same platform for comparisons to minimize errors in interpretation.


Subject(s)
Bacteria/classification , Bacteria/genetics , Cystic Fibrosis/microbiology , High-Throughput Nucleotide Sequencing/methods , Lung/microbiology , Microbiota/genetics , Sputum/microbiology , Bacteria/pathogenicity , Base Sequence , Biodiversity , Classification , Computational Biology/methods , DNA, Bacterial/genetics , Humans , Metagenome , Phylogeny , RNA, Ribosomal, 16S/genetics
SELECTION OF CITATIONS
SEARCH DETAIL
...