We have many source systemsWe have users using applicationsOne way is to have web services that hit the source systems in real time, collecting necessary data, combine, then give back to application/user. (SOA architecture). Pros:Always up to date informationNo ETLCons:Hitting a live clinical system. Depending on the query this can have unpredictable effect on the performance of such clinical systems.More points of failure – if any one of the systems is offline for maintenance, user has to wait.The other way is to integrate data into a data warehouse.Pros:Centralized data managementNot impacting clinical systemProdictible data availability Better performanceCons:Need expertise on data ETLData Delays – depending on update frequency.
IT Tools Supporting P4 Medicine
IT Support Tools and Personalized Medicine<br />Phyllis Teater, Chief Information Officer<br />The Ohio State University Medical Center<br />
Fundamental Objective of Informatics and Healthcare IT<br />Delivering timely and contextually appropriate data, information, and knowledge in support of basic science, clinical and translational research, clinical care, and public health.<br />
Computers are incredibly fast, accurate and stupid.Human beings are incredibly slow, inaccurate and brilliant.Together they are powerful beyond imagination. -Albert Einstein<br />
Goal = Move Expert Knowledge and new Discoveries to the Point of Care <br />
Eligible Hospital Status Must Meet 5<br />Meet 4<br />Meet 1<br />
MU: Quality Measures<br />The Final Rule identifies quality measures that eligible providers and hospitals will be required to report on as evidence of Meaningful Use. <br /><ul><li>For eligible providers, 44 measures are identified.
All EPs must report on the three measures in the core measure group or, if they see no patients for which the core measures apply, on three alternative measures.
All EPs must also choose an additional 3 measures to report on from the remaining list.
For hospitals, 15 measures are identified. Each hospital must report on all 15 measures. </li></li></ul><li>Meaningful Use at OSUMC<br />
The Need for Structured Data: Beyond Meaningful Use<br />
Historical trends in storage prices vs DNA sequencing costs<br />“Next generation” sequencing technologies in the mid-2000s changed the trends and now threatens the conventional genome informatics ecosystem<br />Notice: this is a logarithmic plot – exponential curves appear as straight lines.<br />Lincoln D Stein Genome Biology 2010, 11:207<br />
The Need for Data Integration and Analytics<br />Data integration is a pervasive challenge faced in applications that <br />need to query across multiple autonomous and heterogeneous data sources. Data integration is crucial in large enterprises that own a multitude of data sources, for progress in large-scale scientifc projects, where data sets are being produced independently by multiple researchers, … …<br /> Halevy A, Rajaraman A, Ordille J; “Data Integration: The Teenage Years. VLDB `06, September 1215, 2006, Seoul, Korea.<br />Radiology<br />Appl<br />Icat<br />ions<br />Web Services<br />Lab<br />EMR<br />Pathology<br />IW<br />
Constant Evolution in Technologies for Patients, Clinicians and Researchers<br />1950-60’s: Specialized computing facilities, programming languages, decision support, bibliographic databases, basic clinical documentation systems, first training programs<br />Today: Tele-health, mobile computing, widespread EHR adoption, service-oriented architectures, genomic and personalized medicine applications, translational research<br />