Facilitating Data Sharing
This text emphasizes the importance of facilitating data sharing in the field of Computer Science. It touches on the significance of collaboration and open access to data for research and innovation. The author, James Geller, provides insights into how sharing data can benefit the scientific community and drive progress in the field. The content discusses strategies and methods that can enhance data sharing practices to further advance research and knowledge in Computer Science.
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Presentation Transcript
Facilitating Data Sharing James Geller Computer Science NJIT
Overview 0: What I am not going to talk about (1 page) 1: Ontologies 101 (or really: Ontologies 099). 2: Not sharing has recently been recognized as a new problem, to the point of getting its own name: Information Blocking 3: The agreed-upon questions 2
What I am not Going to Talk about i2b2, SHRINE PCORnet, CDM (Common Data Model) HL7, FHIR (Fast Healthcare Interoperability Resources), CDA (Clinical Document Architecture) Blue Button, CommonWell Health Alliance, Microsoft Health Vault, ONC s S&I Framework caBIG OHDSI, OMOP (Observational Medical Outcomes Partnership) CARPEM, EFPIA and other European projects 3
Disease IS-A IS-A Stroke Cancer Organ IS-A Located in IS-A IS-A IS-A Lung Cancer Lung Located in Liver Liver Cancer IS-A IS-A IS-A Hepatoblastoma Cholangiocarcinoma Angiosarcoma 4
With Apologies to Winston Churchill Ontology is the worst mechanism for data sharing except for all the others. Democracy is the worst form of government, except for all the others. Winston Churchill, House of Commons, 11 November 1947. From: Churchill by Himself: The Definitive Collection of Quotations Hardcover October 27, 2008 by Winston Churchill (Author), Richard Langworth (Editor) https://www.amazon.com/dp/1586486381/?tag=richmlang-20 5
What is Information Blocking? Information blocking occurs when persons or entities knowingly and unreasonably interfere with the exchange or use of electronic health information This report focuses on potential information blocking by health care providers and health IT developers, including vendors of EHR technology. 6
Q1 How is data sharing different for (encounter) patient care data vs. epidemiological study data based on long term patient care vs. (genomic/phenotype etc.) research study data? 7
Q2 What technologies are useful to provide a simple and efficient mechanism to streamline data sharing? (e.g. what research projects shall NIH/NSF fund?) e.g. meta-data management, data integration, data/result reproduction/annotation/provenance, workflow for data sharing, anonymization, search/query the data, version control, access control 8
Q3 - Main What are the policies that can facilitate data sharing (e.g. what policies that the government could establish would be helpful)? 9
Q3 a) Is HIPAA/HITEC too burdensome for data sharing and should it be possible/easier for patients to opt out of HIPAA protection, e.g., from the privacy of their own cell phone as opposed to being under emotional pressure in a doctor's office or in a hospital to opt out? 10
Q3 b) Should America slaughter some sacred cows and introduce a single payer system for the whole country or at least for groups of states, such as "the north east" and eliminate all barriers to data sharing inside of those regional payer systems? 11
Q3 c) Is it technically and legally possible to create one main repository for every patient at one specific healthcare provider of her choice (her "health home base"), and force all other healthcare providers serving her to automatically share/upload any encounter data from her visits to this health home base? 12
Q4 What actions should be taken to facilitate data sharing, again for the three categories mentioned in question 1? 13
Results of Discussion Create a Data Home Base for every patient. All data used in research should be submitted to an agency like the National Library in Washington. The NLM (National Library of Medicine) could fill the bill. How to motivate people to SHARE and to USE what is shared: Use a data citation system. Compute an S-Index
Sharing platform Provenance Metadata Workflow Data discovery Privacy Usability
Need a business model to pay for this Value driven data sharing What benefits do participants get? Individual health records analysis and compare with others patients feel the value of sharing the data
