close

Вход

Забыли?

вход по аккаунту

?

Drowning in Data, but Starving for Knowledge? How to Define Big

код для вставки
Drowning in Data, but Starving for Knowledge?
How to Define Big Data for Healthcare
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.
Interview by Hannah Hager
Big Data IQ: There is a common perception that the
healthcare industry is “drowning in data, but starving
Tom Ortiz, Chief Medical Officer
for knowledge.” Part of the reason is that much of the
Reliance Medical Group, LLC
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
unaccountable care with unknown outcomes. The hospitals are capitalizing on meaningful use
incentives, unaccountable use of GME money to train the most costly specialists who are conducting
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.
www.bigdatahealthcaresummit.com • 1-800-882-8684 • info@iqpc.com
Документ
Категория
Без категории
Просмотров
9
Размер файла
556 Кб
Теги
1/--страниц
Пожаловаться на содержимое документа