ArticleCancer2008
A multidisciplinary approach to honest broker services for tissue banks and clinical data: a pragmatic and practical model.
Article in Cancer, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 43 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
43 citing papers in PubMed, 1 synthesis or guideline pooled it, 75 citations in OpenAlex.
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- An Interdisciplinary Approach to Reducing Errors in Extracted Electronic Health Record Data for Research.Perspectives in health information managemen · 2021Article
- Development and maintenance of a medical education research registry.BMC medical education · 2020Article
- DASH, the data and specimen hub of the National Institute of Child Health and Human Development.Scientific data · 2018Article
- Embracing an integromic approach to tissue biomarker research in cancer: Perspectives and lessons learned.Briefings in bioinformatics · 2017Article
- Consent2Share: an integrated broad consenting process for re-contacting potential study subjects.Journal of clinical and translational research · 2017Article
- Article
- The biorepository portal toolkit: an honest brokered, modular service oriented software tool set for biospecimen-driven translational research.BMC genomics · 2016Article
- Secondary consent to biospecimen use in a prostate cancer biorepository.BMC research notes · 2016Article
- A Federated Network for Translational Cancer Research Using Clinical Data and Biospecimens.Cancer research · 2015Review
- Big Data: the challenge for small research groups in the era of cancer genomics.British journal of cancer · 2015Review
- Enabling a Learning Health System through a Unified Enterprise Data Warehouse: The Experience of the Northwestern University Clinical and Translational Sciences (NUCATS) Institute.Clinical and translational science · 2015Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 3 institutions in 1 country.
Funding
Abstract
backgroundHonest broker services are essential for tissue- and data-based research. The honest broker provides a firewall between clinical and research activities. Clinical information is stripped of Health Insurance Portability and Accountability Act-denoted personal health identifiers. Research material may have linkage codes, precluding the identification of patients to researchers. The honest broker provides data derived from clinical and research sources. These data are for research use only, and there are rules in place that prohibit reidentification. Very rarely, the institutional review board (IRB) may allow recontact and develop a recontact plan with the honest broker. Certain databases are structured to serve a clinical and research function and incorporate 'real-time' updating of information. This complex process needs resolution of a variety of issues regarding the precise role of the HB and their interaction with data. There also is an obvious need for software solutions to make the task of deidentification easier.
methodsThe University of Pittsburgh has implemented a novel, IRB-approved mechanism to address honest broker functions to meet the specimen and data needs of researchers. The Tissue Bank stores biologic specimens. The Cancer Registry culls data and annotating information as part of state- and federal-mandated functions and collects data on the clinical progression, treatment, and outcomes of cancer patients. The Cancer Registry also has additional IRB approval to collect data elements only for research purposes. The Clinical Outcomes Group is involved in patient safety and health services research. Radiation Oncology and Medical Oncology provide critical treatment related information. Pathology and Oncology Informatics have designed software tools for querying availability of specimens, extracting data, and deidentifying specimens and annotating data for clinical and translational research. These entities partnered and submitted a joint IRB proposal to create an institutional honest broker facility. The employees of this conglomerate have honest broker agreements with the University of Pittsburgh and the Medical Center. This provides a large group of honest brokers, ensuring availability for projects without any conflict of interest.
resultsThe honest broker system has been an IRB-approved institutional entity at the University of Pittsburgh since 2003. The honest broker system currently includes 33 certified honest brokers encompassing the multiple partners of this system. The honest broker system has handled >1600 requests over the past 4 years with a 25% increase in volume each year.
conclusionsThe current results indicate that the collaborative honest broker model described herein is robust and provides a highly functional solution to the specimen and data needs for critical clinical and translational research activities.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.