Drowning in Data, but Starving for Knowledge?




Thomas R. Ortiz, MD, FAAFP, is the Chief Medical Officer at Reliance Medical Group, LLC, operating the Primary Care Medical Practices in five counties in New Jersey; he is responsible for clinical oversight, integration and health information technology. In this interview, Tom says his business could do with better, organized data streams that would improve outcomes and costs.

Big Data IQ: There is a common perception that the healthcare industry is "drowning in data, but starving for knowledge." Part of the reason is that much of the aggregated data is never analyzed, or hidden information in the data is passed on as inconsequential. Has your organization been able to remedy this situation? If so, how?

No, not completely. Only about 20% of the big data that I need as a family physician is available to me, at the point of service, to make important decisions about someone’s health and wellness. We do a great job with the data we do have access to but with better, organized data streams outcomes and cost would improve. For years we have had to come up with a variety of manual solutions using our limited EMR for both clinical and practice management purposes.

It is as you state, we are drowning in data elements that are not yet interoperable onto one platform that is collecting all the data from all of its sources within the medical system, available on a real

time basis, to really have any impact on utilization, outcomes or cost. We have been working with our REC and HIE in their developmental stages, locally, helping them to appreciate the need for interfacing all of the potential data sources and understand what data is needed and how it needs to be presented to the clinicians in an organized, meaningfully useful way.

Big Data IQ: How can hospitals capitalize on government incentives by parsing through the requirements and focusing on the practical aspects that can benefit insurance payers and healthcare providers?

This is a really good question with no simple answer. In my region the hospitals are the biggest cost driver in the system. As I understand them, there is no rhyme or reason to the economic models; that they employ to charge and bill and right off, while functioning at a deficit and providing very poor quality care with no ability to measure the outcomes of their methods. The hospitals are capitalizing on meaningful use incentives, unaccountable use of GME money to train the most costly specialist doing the most expensive procedures with minimal emphasis on the outcomes of their interventions and PCMH and ACO projects.

Big Data IQ: How has the use and analysis of Big Data transformed the way your organization does business?

I don’t know, I will let you know once the Big Data is available. I have a vision of how this would work. First we all have to agree to the objective, high patient satisfaction and access, improving clinical outcomes especially in the vulnerable populations, reduction in overall cost of care while reforming the payment paradigm for primary care services and beyond. Then we have to agree on the discreet data elements that need to be collected from a variety of data sources into meaningful informatics for PCPs on specific high impact patients, their diseases, care coordination and population care management, utilization of services and patient satisfaction. This needs to all stream onto a PCP Dashboard where a PCP can make informed decisions on the daily activities and focus of the health care delivery team.

Big Data IQ: Despite the hype around big data, the exact meaning of how it applies to healthcare remains vaguely defined. How would you answer this question?

You are absolutely correct. There is no definition or standardization/agreement on what data needs to be collected and how it is presented. This to me is the crux of the issue. Health Information Technology, which is behind most other industries in this country by about 20 years, has not sat down with the busy, boots-on-the-ground clinicians, to come together on the understanding of definitions and standards necessary.

First the data exchange and interoperability between EMRs, HIEs, Hospitals, Nursing Homes, Home care, ERs, portals, etc., must be addressed and industry standards need to emerge on the technology, but also the costs need to be defined. Who is going to pay for what and when? It seems like the deepest pockets in the industry – pharmaceuticals and insurance – have put a dime into technology solutions or Big Data. Yet they have the most to gain. This is a huge disconnect because physicians and hospitals cannot afford to capitalize this start up by ourselves. I believe that they will need to be influenced to contribute to this effort, in kind or with cash, for this system to be made whole and meaningful. HIT industry leaders need to sit down with busy clinicians to create a work flow of automated Big Data in a way that provides all the stakeholders with the data to improve all levels of efficiencies and outcomes.

Big Data IQ: Can you discuss a project that you’ve implemented within your organization that you’re particularly proud of?

I am proud of many projects that our organization has implemented during the past 10 years from EMR to programs that serve the poor and uninsured. My most important project has been our transformation into a NCQA recognized PCMH which has allowed me an opportunity to negotiate several insurance, blended rate contracts and our ultimate selection to participate in the CMS CPC initiative. This will provide me with additional revenues to continue to develop the HIT infrastructure so that the practice is ready to plug into the rest of the world, once we have accomplished all that we have discussed above. It defines the clinical data matrix and benchmarks to target, allows for use of clinicians and informatics technologists to develop a local methodology of empanelment, risk stratification, focused clinical services and gaps in care analysis and a system of patient engagement and electronic online communications.

Interview by Hannah Hager