The Health Sciences Blog covers the latest trends and advances in life sciences and healthcare.

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How FDA’s Guidance on RWE Impacts the Life Sciences and Influences Oracle Health Sciences

If you haven’t yet, please navigate to this link to read this exciting new guidance on Real World Evidence (RWE) released by the FDA in early December 2018!  The guidance document is riveting to read, and it is an exciting element of Oracle Health Sciences’ current strategy to disrupt clinical research with our new Oracle Health Sciences Clinical One platform, Oracle Health Sciences Data Management Workbench (DMW), and Oracle Health Sciences mHealth Cloud Connector Service.  Read on to find out how! First, in the guidance document, the FDA makes clear that coupled with the 21st Century Cures Act, RWE is a critical pillar in the ongoing quest to get the approvals of new drugs and biologics to patients faster and at a lower cost.  This guidance is underscored by FDA Commissioner Scott Gottlieb’s quote, “As the breadth and reliability of RWE increases, so do the opportunities for FDA to make use of this information.” Additional critical points: The FDA’s RWE journey started years ago in the safety arena.  One manifestation that has been very successful is the Sentinel System. This system assesses EHRs and claims-real world data (RWD) sources to generate RWE for drug safety.  The Oracle Empirica Signal Suite is also a byproduct of the FDA’s safety journey. Years ago, the FDA served as an Oracle development partner to create the solution, and the agency continues to use the Empirica Signal Suite in its drug safety program today. Examples of RWE sources include data derived from: EHRs, medical claims and billing, product and disease registries, and patient generated data (including in-home settings) from mobile devices and sensors.  The good news for our customers is that Oracle Helath Sciences knows a lot about RWD sources.  With its healthcare business, Oracle has been successfully integrating EHR data for healthcare provider and government organizations for over 20 years.  Also, because Oracle’s mHealth Connector product supports patient generated data from mobile devices and sensors, electronic clinical outcome assessment (eCOA) and electronic patient reported outcomes (ePRO) data sources can be easily integrated with both Oracle Health Science InForm and Oracle DMW. In addition to using the above-mentioned real world data (RWD) sources to generate RWE, RWD can also be used to improve trial efficiency.  This means that a biopharmaceutical company’s clinical research budget can support exploring more potential targets, not only reducing time to market, but also increasing the number of therapies it can pursue simultaneously.  Examples include:     Generating hypotheses for testing in randomized controlled trials (RCTs) Identifying drug development tools, including biomarker identifiers Assessing trial feasibility by examining the impact of planned inclusion/exclusion criteria in a relevant population Informing prior probability distributions in Bayesian statistical models Identifying patient baseline characteristics for enrichment and/or stratification Assembling geographically distributed research cohorts (particularly for rare diseases and targeted therapeutics) Single-arm trials are a reality!  This development is extremely exciting.  It speaks to manyof the good things they enable, such as: Reducing the number of patients needed for a trial.  Since there isn’t a need to conduct a dual arm trial, a single-arm trial can reduce the number of patients needed by up to 50 percent (50%).  Patient enrollment is the Number One problem with running clinical trials, as only three percent (3%) of patients volunteer to participate.  In addition, the overhead of finding the best sites that can help a sponsor get to the right level of patient enrollment, including getting all the patient data and paperwork required for the regulatory process, adds tremendous time to a successful study startup. (See how our recent goBalto acquisition streamlines this!) Alleviating ethical dilemmas.  For deadly diseases, it’s very difficult, ethically, to have a control group who does not receive the prescribed trial treatment.  In a single-arm trial, the sponsor can mine RWD sources for patients with that disease who have not taken the therapy in past and compare those historic patients to the current studied patient group.​ Speeding the Drug Approval Process. Using RWE, Blincyto, a treatment for acute lymphoblastic leukemia, was approved under the FDA’s accelerated approval process.  The response rate in a clinical trial for Blincyto was compared to historical data from 694 patients. The historical data was extracted from over 2,000 patient records at US and EU clinical study and treatment sites.  Enabling an adaptable learning health system. A dose-response-aspirin-trial compared two common doses (81mg and 325mg) across 20,000 randomized patients who had a history of myocardial infarction (aka heart attack).  This was a long-running trial integrated into regular patient care with minimal inclusion/exclusion criteria and no additional treatment protocol beyond the aspirin regimen.  Primary trial end points such as death, another heart attack, stroke, etc. and secondary endpoints, such as coronary procedures, hospitalization, etc. were captured from electronic health records (EHRs) and claims-data sources.  Arguably, this trial was an example of integrating trials/research directly into patient care processes and/or an instance of the learning health system. Of course, there are many, many more important elements of the FDA’s RWE framework strategy in the document, so please read it! From all of this, it’s easy to see how Oracle Health Sciences’ fundamental Clinical One strategy is really going to advance and re-envision clinical trials. Most critically, the next module for Clinical One is not called EDC (for electronic data capture).   It’s named Data Capture.  Why? Because the game is different now.  Our new data capture capacity isn’t just to get data from one site.  It’s performed to enable data to be captured from all required data sources -- including RWD sources -- in real-time for the trial.  Clinical One allows users to make this fundamental, streamlining, yet disruptive, change to the clinical research process easily. Are you re-thinking your RWE strategy? Take a look at the progress of our Clinical One vision and contact us for a conversation!  

If you haven’t yet, please navigate to this link to read this exciting new guidance on Real World Evidence (RWE) released by the FDA in early December 2018!  The guidance document is riveting to read,...

Health Sciences

Galen to Prix Galien -- from Rome to New York in Two Millennia

Next week, the Galien Foundation hosts the Prix Galien awards at The American Museum of Natural History in Manhattan. The gala event  --  including the ceremony, cocktail party, and dinner  --  recognizes outstanding achievements in pharmaceuticals, biotechnology, and medical technology that improve the human condition. The award is considered the equivalent of the Nobel Prize in life sciences research. Ever wonder how Prix Galien got its name? The award honors Claudius Galenus, an anatomist, physiologist, clinician and researcher. He has been called the father of medical science and modern pharmacology. His work has been considered a reference for over two millenniums. Born in Pergamos in 131 A.D., Galen studied in Smyrna, Corinth and Alexandria, the three centers of medical excellence of the ancient world. According to a legend, Galen dreamt of Aesclapius, the god of medicine in ancient Greek mythology, and this dream inspired the rest of his life.  When he turned 17, Galen worked as a physician at a gladiators’ training center. Marcus Aurelius requested Galen to come to Rome when he was 37. There, he grew in reputation and stature as a healer, teacher, researcher and writer. His ideas on the functioning of the human body were so well received that he became the personal doctor of young Commodus, the Emperor’s heir. During his long, eminent life, Galen completed over 500 works on anatomy, physiology, pathology, medical theory/practice, and forms of therapy. His work formed the basis of Galenism, a medical philosophy that dominated medical thinking until the Renaissance. He also  travelled throughout the world, studying local plants and remedies. He described 473 original drugs and many mineral and plant based substances. He was the first scientist to codify the art of preparing active drugs. His observations, logic, and deduction made him the true successor to Hippocrates and his view that the prime aim of medicine is patient care has formed the very cornerstone of modern pharmacy.  Galen died in 201 AD. Oracle is honored to sponsor an award dedicated to such a remarkable medical pioneer and very proud to celebrate, this year’s Prix Galien nominees for their innovation in science and medicine. Join us in New York on October 26 for the Galien Forum, a day-long event where Nobel laureates and scientists discuss pressing health issues and scientific breakthroughs. And, in the evening, honor the life science innovators of today at Prix Galien.

Next week, the Galien Foundation hosts the Prix Galien awards at The American Museum of Natural History in Manhattan. The gala event  --  including the ceremony, cocktail party, and dinner  -- ...

Health Sciences

Data Models & Their Importance for Clinical Data Management

A data model is quite simply a 'description of the structure' of stored data.  For example, a clinical trial in Oracle Health Sciences InForm is described by an InForm Clinical Trial Data Model.  Data models are created by applications to store data and accessed by end users to manipulate data.   Data models are important because they help end users to access data that is easily understandable, meaningful, and useable.  For example, an Oracle Health Sciences InForm Clinical Trial Data Model is easily understandable to a study manager.  But, it is not immediately useable for submission to the FDA because it is not in a submission ready structure.  The FDA requires clinical data to be provided as a "Study Data Tabulation Model” (SDTM) dataset. So the business need is for end users to easily create data models that can be used: To capture data (ELECTRONIC DATA CAPTURE data models) To review data (REVIEW data models) To submit data to regulatory authorities (SDTMs) To visualize data (ANALYTICS data models) For any other purpose Rather like the alchemists of old who were trying to convert lead into gold, Clinical R&D is currently challenged with slow, complex, manual processes that must transform raw clinical data sets into high value clinical data models and datasets. What This Means for Sponsors and CROs: Sponsors and CROs need to take raw clinical data and provide it to their internal stakeholders in real time to: Fix data collection and quality issues Identify clinical safety issues Monitor trial progress Support interim analysis However, many data managers work with multiple systems, with many CROs, and many internal clinical groups.  Often they use processes that are disconnected, fragmented, expensive, and complicated to manage. How Oracle Health Sciences Data Management Workbench (DMW) Can Help Oracle DMW is the only industry solution that provides a unified platform in which data models can easily be created, stored, re-used, and transformed from one model to another. The value in this is that end users can easily connect to a data model to access and use clinical data in real time. This month at the Society of Clinical Data Management Annual Conference (SCDM), sponsors and CROs will be looking for ways to enable the transparency and analytic capabilities of the data within the clinical R&D process.  They can meet Oracle there (Booth #310) to discuss: The ease of creating clinical data models  The ease of transforming clinical data models from one to another The ease of connecting to a data model to visualize data The ease of automating clinical data flow to provide end users access to more accurate, higher quality data faster, and at lower cost Oracle Health Sciences breaks down barriers and opens new pathways to unify people and processes to help bring new drugs to market faster. Join us at SCDM, Booth #310, for a demonstration of Oracle Health Sciences Data Management Warehouse to add value to your patient-centric trials. ### Srinivas Karri is Director of Life Sciences Product Strategy for Oracle Health Sciences.

A data model is quite simply a 'description of the structure' of stored data.  For example, a clinical trial in Oracle Health Sciences InForm is described by an InForm Clinical Trial Data Model.  Data...

Health Sciences

Realizing Clinical Trial Value and Business Efficiency in the Cloud

One of the most interesting aspects of organizations moving to the cloud has been increased scrutiny around Value.   Increasingly, many of our customer interactions feature one or more conversations around business value and operational efficiencies.   Value is important because it allows organizations to focus on what is important with a new IT project. It helps manage and maintain scope, cost and risk.   Value  can be quantified  at any stage using business objectives during and post implementation to ensure continued, focused delivery through organizational alignment. This article discusses value in relation to multiproduct platform solutions in the Oracle cloud.   Value Assuming that a customer is considering deploying one or more Oracle products and associated services, it becomes necessary to quantify the opportunity cost for the change and balance the potential derived ROI benefits. The following describes the value associated with Oracle Health Sciences Data Management Workbench (DMW). Additionally, there are significant operational benefits associated with moving to the cloud that also should be considered and quantified. Figure 1.  One definition of value can be represented as the freeing up of cash flow as a result of decreasing direct and indirect costs, increasing revenue, or decreasing investment in fixed assets.   By increasing incremental free cash flow, value is generated within the enterprise. Business value is at the heart of any business case and is, in essence, the key driver for any new implementation.  It is evident that the business case at the very least requires three components: Understanding what product capabilities are provided by the solution and the business benefits:  For example, Oracle DMW helps organizations automatically aggregate, clean and transform data, which they may currently perform manually.  The business benefit is automation and making data more available to a larger number of downstream consumers.  Understanding how the business benefits translate to operational improvements, which are characterized by operational metrics.   For the example, using Oracle DMW, an organization can expect a decrease in the operational costs associated with study setup, data cleaning, and data transformation. Examples of operational metrics that capture these improvements are: Cost per change order, $ Cost per data load per study, $ Cycle time from raw to review model, days Number of man hours spent on validation and testing for new study build, man hours For example, a study build in Oracle DMW can be performed in less than an hour. Some organizations take over eight weeks to perform the same! Understanding how operational metrics translate into financial metrics.  Operational metrics, such as the cost of operations, translate directly into financial metrics, such as direct and indirect operations costs.   However, the link between operational metrics and financial metrics is not always clear and may even overlap between different operational metrics.  Usually the activity to translate operational metrics into financial metrics is performed by the customer using proprietary data.      Figure 2.  Operational metrics are intimately tied to financial metrics that appear on financial statements. In addition to these elements, the business case should also describe how the benefits would be realized through the implementation and subsequent go-live timeline.  Value may continue to be derived well after go live and may even increase through greater organizational adoption of the solution. Measuring Value by Implementing Oracle DMW So, given this approach to quantifying value, how can this be applied to implementing DMW?     Figure 3.  Value categories impacted by implementing Oracle DMW. To help our customers navigate the value realization roadmap, Oracle Health Sciences (OHS) has developed a comprehensive tool that describes product features, business benefits, operational metrics, and  mapping to quantifiable value categories.  With this tool, OHS customers can create a pragmatic, focused approach to a successful DMW implementation that can form the foundation of their clinical data collection and management strategy. If you would like to know more about this approach and would like to use the tool with your customers, please don’t hesitate to get in touch. If you have any questions or suggestions based on what you’ve just read or what you would like to read about, I’d love to hear from you. Contact me at: srinivas.karri@oracle.com

One of the most interesting aspects of organizations moving to the cloud has been increased scrutiny around Value.   Increasingly, many of our customer interactions feature one or more conversations...

Life Sciences

The FHIR RESTful Services Standard

Real world data generates real world evidence.  Many use cases drive the biopharma organization’s needs to do this.  These use cases can aid many areas within the biopharma organization including: the commercial, health economics and outcomes research (HE&OR), early development, translational research, corporate strategy, safety, and clinical R&D groups.  Therefore, real world evidence substantially enhances the effectiveness of the overall biopharma organization.  This post discusses how a biopharma organization’s clinical R&D team can populate case report forms (CRFs) in an electronic data collection (EDC) application from electronic health record (EHR) systems using in Oracle Health Sciences InForm and the emerging HL7 standard, known as Fast Healthcare Interoperability Resources (FHIR). The FHIR standard is a specification for implementation of RESTful Services* (a technology approach to building APIs). It enables access to patient data in EHR systems in support of system to system communication (e.g. interoperability).  The FHIR standard is actively under development by the HL7 standards organization and is maturing rapidly from investment over the past 5+ years. Some of its specifications are implemented in several EHR vendors’ systems.  So, code can be written once to the interface standard; and data can be accessed from supporting electronic health record (EHR) systems.  While it is not a fully mature standard, yet, it certainly has substantial momentum in the patient care technology arena.  Over the last couple of years, there has been a focus on using FHIR RESTful Services to integrate patient care data into the clinical research process.  A key use case has been populating electronic data collection (EDC) system case report forms (CRFs) from EHR systems.  This use case can help the biopharma company and its sites participating in a clinical trial to: 1.       Reduce overall data entry volume for each clinical trial 2.       Improve quality of entered data for each clinical trial 3.       Reduce clinical trial costs as data populating the CRF from the EHR system does not have to be    source data verified.  Source data verification is typically done at each site participating in the clinical trial by biopharma-retained employees known as contract research associates (CRAs). Exploring FHIR right now, there is clear evidence that biopharma companies are experimenting with EHR to EDC integration.  Recent discussions with several top biopharma organizations indicate interest as companies look to exploit the benefits of this approach.  HL7 Connectathon Connectathons support quick and easy experimental approaches to developing the various standards the HL7 organization produces.  HL7 continues to use this technique, now over 20 years old, as it develops the FHIR RESTful Service Standard.  A connectathon is a weekend “hacking” session. It   includes members of healthcare organizations who attend and work to “prove” the standard.  They hack together “quick and dirty” working code (a FHIR RESTful Services working prototype) demonstrating that the standard actually will work in the real world. These events occur two to three times per year as the standard is developed.  Oracle Health Sciences (OHS) is participating in the 2017 FHIR Hackathon this autumn.  Currently OHS is building an integration using the HL7 FHIR RESTful Services with InForm. The integration enables mapping patient data from an EHR system into the appropriate trial visit CRF schedule. It can include information such as demography, vital signs, and more.  The integration initiative will help OHS participate in the upcoming HL7 FHIR Connectathon this fall.    The InForm Portal is a key component enabling a user to configure basic mapping metadata required for the integration of: 1.      Which fields in each CRF form map to which fields in the source EHR system 2.      Code list mapping for CRF filed referenced in #1, above 3.       Which patient care visit data ranges (aka Encounter) map to which visits in the visit schedule 4.       The initiation of the data movement from the source EHR to the targeted InForm system This is all accomplished by using FHIR RESTful Services in the standard as they interact with InForm’s Clinical APIs. Customer Focus This summer, OHS is running the first meeting of a newly formed patient EHR data driven Clinical R&D Customer Focus Group and plans to showcase the FHIR RESTful Services to InForm integration.   We’d like to gather customer feedback for this as a very powerful, high value-add, real world data/ evidence use case.  In addition, we will share these advances with our customers as we continue to help them understand what is possible with the HL7 FHIR Standard and InForm’s robust clinical API capability.  OHS is at the beginning of its FHIR RESTful Services journey with biopharma customers.  The early steps include working with customer partners running initial pilots with participating clinical trial sites.  In 2016, OHS worked with a large healthcare organization and a big pharma company on developing pilots in this area. Additionally, two other large biopharmas are considering running FHIR RESTful Services pilots on Phase 1 oncology sites and a  COPD observational study.  Stay tuned for progress updates in this exciting, new innovation area. Greg Jones is responsible for Enterprise Architecture Strategy for Oracle's Health Sciences business.    *Representational state transfer (REST) or RESTful Web services are one way of providing interoperability between computer systems on the Internet.

Real world data generates real world evidence.  Many use cases drive the biopharma organization’s needs to do this.  These use cases can aid many areas within the biopharma organization including: the...

Life Sciences

Oh No! Johnny's Getting Hypertension Again

Imagine if we could remotely connect to subjects in clinical trials and measure their vitals. Imagine if we could take those measurements, in real time, and deliver them to an investigator’s Oracle Health Sciences InForm desktop solution for his/her review. Imagine if a subject felt less burdened by staying home and having his six weekly Investigator Meetings from the comfort of his home, instead of making a two hour commute to the clinic.  Imagine when the subject arrives at the clinic, he can’t find a car parking space. So by the time he reaches the clinic, he is really frustrated and fuming mad that he has to be on this “damn clinical trial in the first place.”         “Sit down Johnny.  Let me take your blood pressure. It seems a little high.  I think you have hypertension…”           “NO! I DO NOT!!! I tell you what I do have.  It’s A PARKING TICKET!  I am quitting this clinical trial right now. GOODBYE!” Imagine keeping Johnny as a subject on the trial because he used a remote wearable sensor device. Imagine his data flowing seamlessly into Oracle InForm for site review, and simultaneously, into Oracle Health Sciences Data Management Workbench (DMW). Imagine the data instantly transformed into SDTM data formats and made immediately available to data managers for downstream, actionable, medical reviews and clinical monitors. Well, the good news is, you don’t need to imagine these things for much longer. The Oracle Health Sciences (OHS) team has just released its first, initial component for its mHealth stack. This library allows app developers to create  IOS/Android mHealth mobile apps that connect to the Oracle Cloud. The OHS team welcomes the opportunity to leverage this exciting new offering to enable connected scenarios.                   For more info please watch this video. Jonathan Palmer is Oracle Health Sciences Senior Director, Product Strategy.

Imagine if we could remotely connect to subjects in clinical trials and measure their vitals. Imagine if we could take those measurements, in real time, and deliver them to an investigator’s Oracle...

Life Sciences

EMR to EDC for RWE

A new real world data/real world evidence (RWD/RWE) industry trend is emerging.  That is, electronic medical records (EMRs) to electronic data collection (EDC) integration.   Here, instead of trial research staffers entering patient history data information, the sponsor implements the “wiring” to take the data directly from the site’s EMR system. Several members of the Oracle HSGBU team have been working on this with our biopharma and our healthcare provider customers including myself, Paul Boyd, Kim Rejndrup, and Chris Huang.  Here’re a few of the things we’ve learned: -In the summer of 2016 the FDA published guidance around considerations for biopharma organizations as they consider moving their EMR to EDC integration. -Every EMR system out there will have only a subset of the information necessary for a particular clinical trial and that subset will vary by clinical trial and therapeutic area.  It’s too early to know precisely what percentage of coverage will be available.  So right now, the expectancy is 40-70 percent (40-70%) on average, per trial.  Again, this is an evolving learning experience in relation to our work and our partnerships with our customers. -Here are some powerful numbers Paul Boyd put together. 1) There are 745,000 data points in a production trial. 2) Approximately 300,000 data entry strokes could be saved, if 40 percent (40%) of the data from EMR could be mapped.  There can be substantial savings of time and energy with EMR to EDC integration!  These numbers also produce savings on the monitoring side of the equation.  Data fields in the InForm customer report forms (CRFs) sourced from the EMR system don’t have to be source data verified (SDV’d) by sponsor employees monitoring the clinical trial at each site (usually known as contract research associates).  Therefore, there will be substantial savings as a major benefit, as well. -Academic Medical Centers (AMCs) that participate in clinical trials as sponsors, have their research staff perform the dual data entry as explained above.  In recent discussions with AMCs, they’ve also indicated that sometimes they’ll set up a “shadow” EDC system for what they own and run for a particular trial, and input the data, yet again (in triplicate!).  They want to capture the data they are providing to the sponsor in their own, internal, research database to advance their various research programs. -Our customers are interested in the APIs and various technology interfaces Oracle Health Sciences supports on the InForm platform.  These interfaces are key to allowing them to bring data from sites’ EMR systems into their InForm clinical trial instances to capture the above stated benefits. -Our customers are interested in Oracle Healthcare Foundation (OHF).   Imagine this scenario. A large biopharmaceutical organization is running 100 plus clinical trials.  It has piloted EMR to EDC integration in several trials over a couple of years.  Now the organization is ready to ramp up this capability as a standard element for many of the clinical trials in its portfolio.  Each trial on average has about 65 sites (that number comes from our experience with production trials run in our Health Sciences Cloud over the years).  Plus a number of sites the biopharma deals with will likely participate in multiple trials with it – not just the one trial.  Some percentages of the sites in the trial (an educated guess is 50-80 percent (50-80%) of them) have the ability to provide EMR data to the biopharma’s EDC system for that clinical trial.           Here’s the challenge. Does the biopharma “wire” each individual InForm instance for each trial to every site?  That’s definitely doable from a brute force perspective. But probably not idea, as it will be very expensive.  Or does the org use a technology like OHF as a platform to integrate receiving data from sites and doing all the wiring and plumbing to those sites with the platform.  Then as new trials start up, they “wire” InForm to the OHF platform, which serves as a “hub”; and go live costs likely are substantially smaller. -An exciting HL7 standard known as FHIR (Fast Healthcare Interoperability Resources) appears to have a decent amount of traction in the industry.  Organizations such as Cerner, Epic, Meditech, and GE Healthcare have implemented this RESTful* Service based API on top of their recent EMR application releases.  Organizations are starting to use these APIs to build and deliver new applications and mobile apps to improve patient and staff healthcare activities.  In addition, the FHIR APIs allow support for interoperability among systems.   With this insight into one of the more exciting use cases for Real World Data & Real World Evidence.  EMR to EDC integration will continue to be explored with our customers.  The Oracle Health Sciences team plans to be there and working closely with them as the technology, policy, and business process challenges are resolved.  Ultimately this will become a mainstream approach increasing clinical research efficiency to deliver new therapies to patients more rapidly.   *Representational state transfer (REST) or RESTful Web services are one way of providing interoperability between computer systems on the Internet.   Greg Jones is responsible for Enterprise Architecture Strategy for Oracle's Health Sciences business. 

A new real world data/real world evidence (RWD/RWE) industry trend is emerging.  That is, electronic medical records (EMRs) to electronic data collection (EDC) integration.   Here, instead of trial...


Metadata Management in Clinical Trials

Metadata management in clinical R&D is centered on the concept that each piece of data collected for a clinical trial, as defined by that trial’s protocol, can be managed independently.  Each piece of metadata and logical groupings of many metadata items together can be governed and managed in the organization. This includes version control, data edit rules for that data item, and transformation rules for that data item as it changes to support the analysis process.  In addition, it also supports the ability to trace that data element through the entire clinical trial lifecycle. This trace-ability extends from the time it’s initially captured during the clinical trial through to that data element’s submission to regulators.  This trace covers all information on how that data element contributes to proving the efficacy and safety of a new therapy for regulatory approval.   As a quick example, blood pressure can be a metadata item for a clinical trial.  One can attach edit rules to that blood pressure item to insure accuracy. When the user inputs the data, the rules assure that it is edit-checked properly and that transformation logic is defined to change the representation of the blood pressure data element during data entry to a completely different representation for an analysis dataset that will be written in SAS code to prove efficacy and safety of the therapy.   I can do all that and maintain version control of that blood pressure data element as I change its representation over time.  Here’s another example. If I use that blood pressure data element consistently across all my clinical trials, then when I change that data element and produce a new version; I can query my metadata system on which clinical trials in my portfolio will be impacted by changing that blood pressure data element.   If I am running multiple clinical trials in which each has potentially hundreds of data items to be collected, then metadata management can help me manage those clinical trials operationally.  Metadata management also helps me to insure that I maintain full regulatory compliance and trace-ability as data goes through its lifecycle from capture to submission.  As mentioned at the beginning, this industry trend has been a long time coming.  The industry move over the last 10 years away from paper based clinical trials to electronic data capture based trials set the stage for this type of capability and for the operational savings from a successful metadata management solution deployment.  Unfortunately,expanding from the basic functionality described and scaling it up across a large scale clinical trial operation has proven to be very elusive to date for many organizations.  The metadata management highway is littered with several organizations that have failed to y deploy it successfully in their complex clinical trial environments.  The reasons for failure are complex, including the challenge of the activity and the resulting impact on the business processes of these large, complex, early- pioneering organizations.  Recently, there’s been a new wave of momentum!  Oracle Health Sciences’ (OHS) powerful partner ecosystem around its clinical R&D applications is kicking in to drive the next set of attempts at metadata management.  Specifically, OHS partner Accenture is leading the charge in close collaboration with two OHS top customers - GlaxoSmithKline (GSK) and Eli Lilly & Company – to tackle, once again, this very complex problem space.   Accenture is working to build a module called Metadata Registry (MDR).  The Accenture, GSK, and Lilly team is working to build this module with the above mentioned capabilities.  Progress is very promising to date!  They do have a large number of the above mentioned capabilities implemented successfully and are going through testing with GSK and Lilly.   In addition, the team will ultimately integrate the MDR with OHS Central Designer and Data Management Workbench applications.  This integration fulfills the promise of the enormous value of the MDR module.  Clinical trial metadata can be managed, version controlled, and more, within the module. Then, those same metadata data can be pushed into our Central Designer and Data Management Workbench applications at study startup and for the management of changes to study(s) in progress.   This will reduce the amount of time it takes to manage clinical trials operationally in each, respective, company’s portfolio and will increase the trace-ability and audit-ability quality each company needs for regulatory compliance.     Greg Jones is an Enterprise Strategy Architect with Oracle Health Sciences.

Metadata management in clinical R&D is centered on the concept that each piece of data collected for a clinical trial, as defined by that trial’s protocol, can be managed independently.  Each piece of...


Population Health and Oracle Healthcare Foundation’s Partner Ecosystem

As the Population Health Strategist for Oracle Health Science (OHS), I enjoy the ability to continue my educational quest for healthcare knowledge.  Between reading the Federal Register and House bills, catching up with CSPAN, and keeping upwith my friends from industry, I am amazed at the number and variety of population health applications currently available.   When I first started 20 years ago, the concept of “population health “ was something closer to evidence based medicine. Today, population health is synonymous with a range of US healthcare market subjects including: patient identification, cost analysis, clinical care gaps, precision medicine and early identification,outcomes measures,and EHR Implementations. We, who are on the OHS team, look at the idea of population health from the ground up. We aggregate a healthcare organization’s data and use it multiple times for any question posed, today, tomorrow, a year from now, or five years from now.   Our OHS team has invested in Oracle Healthcare Foundation (OHF) as the data aggregation and normalization engine that can fulfil population health discovery and care transformation, both clinically and financially. OHF offers a fit-for-purpose, analytics platform that provides a data acquisition, data integration, data warehousing, and data analytics solution.   The solution meets and exceeds current market conditions for organizations evaluating Value Based Care, Quality Measurement Performance, and Internal Cost and Care Team Effectiveness. It evaluates an organization’s information, turning data-driven insight into action.  In addition, OHS is active in recruiting top-quality population health partners to build out our partner ecosystem. These efforts leverage and extend OHF in the vast population health analytics space. OHS also invites its partners to join the Oracle Validated Integration Program. Prior to the invitation, the OHS strategy team takes into account several, fluid factors including: · The organization’s ranking according to IDC, KLAS, Gartner, Forrester, and other analyst organizations · A review of how the partner organization addresses the healthcare market’s business needs · A review of the landscape for emerging healthcare trends and initiatives at federal, state, and local levels  Oracle Validated Integration, available through the Oracle PartnerNetwork (OPN), gives customers confidence that the integration of a complementary partner software product with an Oracle application has been validated, and that the products work together as designed. This can help customers reduce risk, improve system implementation cycles, provide for smoother upgrades and ensure simpler maintenance. Oracle Validated Integration applies a rigorous technical process to review partner integrations. Partner companies that successfully complete the program are authorized to use the “Oracle Validated Integration” logo.  At this year’s HIMSS17 in Orlando, FL, OHS (Booth #3349) is pleased to join the population health conversation with our newest Oracle Validated Integration partners: ENLI Health Intelligence, SpectraMedix, and SCIO Health Analytics . These partners have developed and tested pre-built integrations between Oracle Healthcare Foundation and their population health analytics applications.   About Enli Health Intelligence Enli Health Intelligence™ is the market leader in population health management technology. Enli enables care teams to perform to their full potential by integrating healthcare data with evidence-based guidelines embedded in provider workflows across the population and at the point of care. @enlihealthintel,HIMSS17 Booth #2723 About SpectraMedix SpectraMedix empowers health systems, hospitals and other provider organizations to transition to fee-for-value and shared-risk programs using advanced quality measure, performance reporting and predictive modeling solutions in support of DSRIP, PRIME and operational activities.@SpectraMedix,HIMSS17 Booth #1889 About SCIO Health Analytics   SCIO identifies, risk stratifies and leverages predictive modeling (claims based) on patient populations based on actionable care gaps in order to design effective programs and meet value-based care delivery initiatives. @SCIOAnalytics Lesli Adams, MPA, is Director, Population Health Strategy for Oracle Health Sciences. Visit us in the Oracle Booth #3349 at HIMSS17 in Orlando, Feb 19 - Feb 23, 2017.

As the Population Health Strategist for Oracle Health Science (OHS), I enjoy the ability to continue my educational quest for healthcare knowledge.  Between reading the Federal Register and House...