Kevin Davies of Bio-IT World wrote the article “Running tranSMART for the Drug Development Marathon”, an overview of a translational medicine data warehouse project at Johnson & Johnson, led by Eric Perakslis, VP of R&D informatics, managed by Sándor Szalma, senior research fellow, and delivered by Recombinant during an 18-month implementation.

Davies wrote: “TranSMART helps investigators mine drug target, gene and clinical trial data to aid in predictive biomarker discovery, chiefly in immunology and oncology. Perakslis says it is an ‘amazingly advanced’ data warehouse that compares favorably with many such efforts he’s seen in the Pharma world.”

Davies highlighted the open platform approach by Recombinant: “Perakslis is currently having discussions [with Recombinant] about a Red Hat approach where a lot of the advanced analytics is made open source. ‘I’m not running a commercial software company,’ he says. He’s already offered the software to Guna Rajagopal, a colleague at the Cancer Institute of New Jersey. In addition, St Jude Children’s Research Hospital, UCSF and other centers are all considering the adoption of the i2b2-based platform.”

Labels: Data Warehousing, i2b2, Open Source, Translational Research

Recombinant is based on the east coast, which is unfortunate for us as the folks in Hawaii never called us about their new statewide data warehouse. Nonetheless, they are deploying a system that is focused on both population health and management of infectious diseases. Let it be known that Recombinant is always available with useful expertise and technology for statewide implementations--especially when it involves on-site work in Maui or any other decent surfing spot!

The interesting part of the Hawaii warehouse project is the alert and monitoring system that manages the spread of infectious diseases. This is a major problem in areas with high volumes of tourism, and a great example of why a government needs to review the unique economic and social structure of their state when building a centralized healthcare data warehouse.

Hopefully other states and large metropolitan areas that are timid about the notion of a statewide initiative will consider Hawaii as a successful reference point. Progress can be made on the political, competitive, and technical fronts that ultimately produce collaborations that are in the best interest of every patient's health and safety.

Dan Housman
Managing Director, Analytical Applications

Labels: Data Warehousing, Patient Safety

The Business Times recently published the article “Technology and the fight against epidemics” by Suganthi Shivkumar. It is quite topical about the use of data warehousing and real-time messaging to monitor pandemics. An example in the article mentions the use of Informatica in Hong Kong to track the SARS epidemic.

With the upcoming H1N1 season fast approaching, it would be helpful if tools such as BioSense from the Centers for Disease Control and Prevention (CDC) had greater adoption. It would also help if local areas effectively leveraged EMRs and related infrastructure to help monitor and contain major pandemic risks.

It is possible that some organizations will launch new data warehouses specifically to fight pandemics; however it is more likely to be an offshoot from existing HIT investments. The financial model is complicated in a world where healthcare networks are independent of each other. That challenge is in the hands of the CDC to figure out.

Dan Housman
Managing Director, Analytical Applications

Labels: Data Warehousing

Steve Beller wrote the blog post “A Novel Way to Exchange Patient Health Information”, an interesting take on the NHIN, HIE, and research data warehousing world. It is further evidence of the coming convergence between HIE functions and healthcare data warehousing.

I prefer the decentralized peer-to-peer (P2P) thinking of the proposed solution as well as the simplicity of using Microsoft Office as a platform to share continuity of care document (CCD) messages between physicians. P2P is now infamous from Napster, and is an ideal way to exchange content without central hubs or repositories because it scales quickly and quietly by participants. The general idea of an HIE system involves P2P data exchange, but most architectures of today utilize big hubs.

The Microsoft Office-style exchange may work best for small practices, but not for large integrated health networks. EMR implementations such as EPIC and heterogeneous application systems across hospitals and outpatient facilities require centralized interface engines and CCD factories to consolidate interoperability.

A new twist in the development of a national patient identifier is the use of biometrics. This would avoid reliance on patient reported information which is often inconsistent and the cause of privacy issues. Although I personally like the idea, patient privacy folks may not be pleased with the notion of each office keeping a biometric imprint of their patients with the intention of sharing data.

The thought of universal biometrics reminds me of the movie Gattaca. I find it difficult to imagine every hospital and clinic registration system adding a fingerprint swipe or retinal scan to their hardware and software infrastructure. However, it is a clever idea to address the daunting challenge of uniquely identifying patients amongst a few hundred million people before providing medical facts.

I like the idea of adding de-identified feeds at a patient-level into the mix of the NHIN/HIE/RHIO frameworks for the purpose of public health and research. This is the first time I’ve heard of that idea and it might work for some applications. It may only scale for certain applications, because a warehouse is needed to query complex questions such as cohort size estimations. That being said, ePCRN doesn’t differ much from this approach.

Thanks for the thoughtful posting!

Dan Housman
Managing Director, Analytical Applications

Labels: Biometrics, Data Warehousing, Privacy

I had the pleasure to attend the PHIN conference in Atlanta last month. PHIN refers to the Public Health Informatics Network, a Centers for Disease Control and Prevention (CDC) initiative to improve the exchange of health data.

Recombinant was somewhat of a duck out of water in regards to public health because our focus revolves around clinical research and quality reporting through data warehousing. However, there were quite a few conversations where public health considered themselves uninvited to the table where data was being served.

Our knowledge about i2b2 and the capabilities of clinical systems for data management at hospitals led to some lively discussions and a handful of new opportunities. For example, the CDC has struggled to connect with chronic diseases and i2b2 would be an ideal way to connect to healthcare delivery networks with data management strategies around conditions such as coronary artery disease (CAD), hypertension, diabetes, and chronic obstructive pulmonary disease (COPD).

I met some vendors of interest that intersect with the clinical data warehousing world. A company in the Boston area called Diagnosis One has invested in developing a service including thousands of validated clinical decision support rules. We discussed combining their rule sets with the content that gets extracted and loaded into the Recombinant Data Trust. If anyone is interested in combining both a data warehouse and a privately maintained decision support rule library that is curated by physicians, give me a holler and we will pull together a collaboration with the folks at Diagnosis One!

Another vendor, Trizano, developed an open source public health application that could be a powerful tool linked with a data repository to handle the workflows for public health issues. Given that they focus on the beekeeper model like Pentaho, their licensing model should be compatible with research frameworks such as i2b2. Trizano’s tools might be another key application to drive value out of existing data sets.

The drive for meaningful use has also pushed a lot of interest in HIEs, thus these sorts of tools were well-represented at the conference. I was pleased to encounter the booths focused on IHE-HIE systems. The exhibitors clearly conveyed the message that an HIE doesn't ensure the sort of interoperability that is typically suggested. To ensure one will scale to a national level like an NHIN, the HIE must be implemented to satisfy IHE standards. Among the frustrating and somewhat odd outcomes from the rushed drive toward meaningful use by healthcare systems, is that many HIEs may never be interoperable because even the integration systems have put barriers in front of interoperability.

Based on the PHIN tour of HIE technology, it is now my preference to see more IHE-based HIEs. The Europeans and Canadians are rapidly adopting IHE, but in the United States we haven't wholeheartedly engaged in the standards and efforts at the healthcare-network level. Perhaps it isn't too late for national legislation or state initiatives to include requirements that satisfy international standards.

Dan Housman
Managing Director, Analytical Applications

Labels: Data Warehousing, i2b2

Health Insight Technologies recently announced that it has rebranded as Humedica, Inc., a venture-backed firm in Boston that plans to offer a software-as-a-service approach to clinical intelligence. Their model intends to reduce the burden of BI implementations by eliminating local infrastructure. Using ETL services, Humedica will store healthcare data at a national-level using a centralized clinical data warehouse; then offer access to the data for quality reporting and research, presumably for a fee. The article “Humedica Wants to Dose U.S. Healthcare Crisis with Clinical Analytics” by Ryan McBride offers a great overview of Humedica’s impressive endeavor.

Dan Housman
Managing Director, Analytical Applications

Labels: Clinical Intelligence, Data Warehousing, SaaS, Translational Research

Recombinant is scheduled to co-present with Amazon Web Services at the upcoming Oracle OpenWorld conference on October 14th in San Francisco, CA. Joseph Adler, Solutions Architect will explore the cost, performance, and operational advantages of healthcare and life sciences data warehousing in the cloud. For more information about the conference, visit the OpenWorld website.

Labels: Cloud Computing, Data Warehousing

There is an interesting blog post about healthcare data warehousing titled “What do copy editors and data miners have in common?” by Blake Zenger. His comparison of data miners and warehouse developers to the relationship between editors and authors can help folks improve their understanding of the roles on a clinical data warehouse team.

Dan Housman
Managing Director, Analytical Applications

Labels: Data Warehousing

Dr. Charles M. Watts, senior vice president of medical affairs at Northwestern Memorial Foundation, presented an overview of Karl Weick’s high-reliability organization principles in relation to healthcare. Among his key points was an importance to focus on failure in order to ensure safety. He stated that "Chronic wariness is the tone in a safe environment...hubris is the enemy."

Dr. Watts simplified data warehouse quality as "data quality equals completeness multiplied by validity." He provided an example of an average newborn baby weighing 32 kilograms or about 71 lbs in a healthcare system. The occurrence was attributed to inconsistent data entry with staff using kilograms and grams interchangeably. The solution was to transform the data into one unit of measurement and to ultimately correct the consistency in data entry.

Dr. Watts also demonstrated two cases of applying improvement to increase safety and reliability. The first case involved shoulder dystocia, a tremendous liability risk that occurs when a newborn is stuck in the birth canal. By instituting a simulator, a standard protocol, and a training program, the existing $20 million annual liability was successfully eliminated. The second case involved a decrease in severe adverse events even though the total number of reported adverse events actually increased. This was attributed to improvements in both safety and visibility. Dr. Watts stated "I don't think mistakes went up--reporting of mistakes became more acceptable and we should celebrate that."

Deb Batson, clinical research data warehouse architect at Children’s Hospital Denver, mentioned an example of finding married 6-year-olds. This mistake was attributed to a registration system that was prone to data entry error during hospital admissions.

The reports from Memorial Sloan-Kettering, National Institutes of Mental Health, Duke, and Ottawa differed tremendously. It would be helpful to find a better way to execute technology transfer of reports between organizations.

The folks at Intermountain built an amazing tool for improving labor costs using Cognos as well as a meta-report search engine. The engine allowed users to browse and launch reports from multiple BI tools using just one portal. It appeared to be a good solution for groups with more than one reporting tool.

Dan Housman
Managing Director, Analytical Applications

Labels: Data Warehousing

There were a handful of interesting presentations from Northwestern Medical Faculty Foundation (NMFF), Ottawa Hospital, Duke, and MD Anderson on the first day of the HDWA conference.

NMFF presented an open source SQL server integration services extension for regular expression extractions from free text, a de-identification utility, and TaskMaster, a system for processing ad-hoc data requests. One of the clever features in their workflow management approach was an integration that pulls data from the eIRB into the data warehouse to display the details of the eIRB process. It also had the capability to link out from the tool to execute tasks such as creating a report from a SQL query. Another interesting component of their model was the use of distributed analysts to query the database. The analysts operated within their own groups, but this required segmented hospital data to prevent inappropriate queries.

The Ottawa Hospital presented a dashboard view of their hospital-acquired infections graphically overlaid onto the hospital floor plan to identify infection hotspots.

Duke presented a poster on an open source framework that supports patient recruitment for clinical trials using Mirth.

MD Anderson created a new group called the Office of Performance Improvement. The organization utilized Minitab, QI Analyst, and ultimately Statit to effectively generate control charts in order to rectify challenges found among common BI tools such as Cognos and Business Objects. One of the challenges was an inflated length of stay measurement from last year. This was due to Hurricane Ike, as it was inappropriate to discharge patients in the midst of 110 MPH winds.

One of the common trends among the HDWA presentations was an initial model for data warehouses and delivery systems that provided free access in order to drive adoption, but eventually transitioned to a fee-for-service model for sustainability. Only a few of the organizations were successful thus far in making that transition.

Dan Housman
Managing Director, Analytical Applications

Labels: Data Warehousing

After being trapped in an Atlanta airport for 24 hours I purchased and read Ben Mezrich's new book, The Accidental Billionaires, about the Facebook start-up story.

I have become a fan of Facebook and must commend Zuckerman for having built a great application and network.

There have been medical applications that play off of the social networking theme. PatientsLikeMe allows patients with similar medical conditions to share information with each other about treatments.

Within the CTSA there is a grant opportunity to establish tools for researchers to network with each other. At the moment it appears that the CTSA initiative will either focus on a network already established by Collexis, a private company, or to take the open source route of hardening tools used at UCSF and within Harvard's CTSA in their catalyst site.

We also have seen many physician networks try to establish a social network among their physicians to encourage increased intranetwork referrals.

There will surely be social networking extensions built upon PHRs like Google Health and Microsoft HealthVault.

At Recombinant we are likely to intersect with social networking in all three areas. Each network is dependent on rich reference and clinical data sets that must be powered by data warehouse strategies. For example - knowing a physician's specialties is a secondary use of credentialing data normally found in tools like ECHO or Cactus. Knowing their practice patterns is a matter of analyzing their medical claims. Microsoft is already linking their data management engine, Amalga, with their PHR. We have even discussed using the data warehouse to help physicians socially understand best practice care patterns from their peers.

The holy grail that may never come to be would be an integration of the networks of patients, researchers, and providers. I think Jim Clark had some vision of this when he started Healthscape as his follow-up to Netscape before it became WebMD.

Given the projects we are working on today we can see many exciting opportunities and challenges in the intersection of data warehousing and social networking. It's a hot space that may take ten years to settle before the dominant Facebook-like platforms emerge. After all, Facebook followed the work of SixDegrees (too early), Friendster (too date focused), and MySpace (too ego driven).

There may be some smart kid at Harvard or MIT with a better model for social networking in healthcare and a drive like Zuckerman. Maybe we already know them? But if you are out there.... give us a call when you are ready!

Dan Housman
Managing Director, Analytical Applications
Recombinant Data Corp.

Labels: Data Warehousing, PHR, Social Networking

Recombinant provides leading-edge data warehousing and clinical intelligence solutions to healthcare providers, academic medical centers, and life sciences researchers to deliver higher quality outcomes, accelerate personalized medicine, and lower costs. Our team of industry veterans is focused on improving the flow of reliable data to power clinical and research applications in a secure, compliant environment. For more information about Recombinant’s products and services, visit www.recomdata.com.

Labels: Clinical Intelligence, Data Warehousing