Archive for Healthcare Data Mining

ONC drops pursuit of NwHIN governance

September 15, 2012 admin No comments

The Office of the National Coordinator for Health IT has dropped pursuit of a regulation for establishing “rules of the road” for the nationwide health information network (NwHIN) based on feedback it has received.

Commenters from industry and the public made it clear that federal regulation could slow development of health information exchange just as those activities are starting to emerge and pick up steam, “perhaps more than is widely appreciated,” according to Dr. Farzad Mostashari, national coordinator for health IT.

ONC issued a request for information (RFI) in May to collect public comment on a possible approach for rulemaking to spell out “conditions of trusted exchange,” including safeguards and technical and business practices. ONC wanted to receive broad input before issuing a proposed rule, he said.

ONC also considered establishing a voluntary accreditation and certification process through which to approve organizations as being legitimate participants in NwHIN, somewhat similar to the procedures for certifying electronic health records for meaningful use functions.

“Based on what we heard and our analysis of alternatives, we’ve decided not to continue with the formal rulemaking process at this time, and instead implement an approach that provides a means for defining and implementing nationwide trusted exchange with higher agility, and lower likelihood of regret,” he wrote in a Sept. 7 blog.

NwHIN is a set of comprehensive standards, services and policies that enable healthcare organizations to share information securely through the Internet.

ONC’s goal is that information follows the patient where and when it is needed, across organizational, vendor, and geographic boundaries.

But the current state of information exchange and care coordination is far from this ideal. In addition to technical challenges with interoperability, “the absence of common ‘rules of the road’ may be hindering the development of a trusted marketplace for information exchange services,” Mostashari said.

However, voluntary governance bodies are now forming both for directed and query-based exchange. ONC wants to encourage the exchange activities that are gaining steam, “and not to hobble them,” he said, especially with the expectations for standards-based exchange in stage 2 of meaningful use.

“And let me assure you that if systemic problems or market break-downs emerge that might require regulatory action, we will again seek input from the public and our stakeholders, including the Health IT Policy and Standards committees,” Mostashari warned.

Participation in the NwHIN Exchange previously was limited to federal health agencies and primarily large healthcare organizations that contract with them or are federal grantees. Agreement on how to assure conditions for trusted exchange will enable many more organizations to participate.

Among the actions that ONC will press for to promote trusted exchange are:

• Identify and shine a light on good practices that support secure and interoperable exchange and provide a guide for evolving governance models

• Learn from and engage with groups in governance and oversight roles for exchange partners in order to foster models within and across communities

• Continue to use existing authorities and convening powers to create consensus and provide guidance and tools around specific barriers to interoperability and exchange

• Evaluate how and what consumer protections can be appropriately applied to health information exchange through existing regulations

• Monitor and learn from the wide range of activities that are occurring.

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What the platforms tell us about parties’ stance on health IT

September 13, 2012 admin No comments

It’s a joke without a punch line: Both Republican and Democratic national party platforms make sparse mention of health IT.

To be certain, there’s plenty of focus on the broader healthcare issues. The GOP platform, in fact, dedicates its first two sections to ‘Saving Medicare for future generations’ and ‘Strengthening Medicaid in the states’, while the Democrats also address the issue early on with a section about healthcare as part of ‘The middle class bargain’ and another on ‘Social Security and Medicaid.’

[Survey analysis: Romneycare vs. Obamacare, do Americans care?]

As for any particulars of health IT, well, that’s another matter. Quite literally, each party offers up a single sentence on its intentions for health IT.

From page 33 of the 2012 Republican Platform PDF:
We support technology enhancements for health records and data systems while affirming patient privacy and ownership of health information.

Now, should that strike you as oddly vague, just wait.

“If anyone was disappointed in the scant attention given to health IT in the Republican Party Platform, then the Democratic Party Platform should give them pause,” said Brian Ahier, health IT evangelist at Mid-Columbia Medical Center, author of the Healthcare, Technology, and Government 2.0 blog, and city councilor in The Dalles, Ore. “Health IT is barely mentioned at all, and only in the context of broader technology initiatives.”

Indeed, in the 2012 Democratic National Party Platform health IT is on page 41 of the PDF:
We will ensure that America has a 21st century digital infrastructure – robust wired and wireless broadband capability, a smarter electrical grid, and upgraded information technology infrastructure in key sectors such as health care and education.

Reactions to the perhaps pithy stances of both parties stance have been mixed.

“I regret that the platforms are largely silent on HIT,” former four-term Vermont Governor Jim Douglas wrote in an email exchange with Government Health IT. Douglas is now a member of the Bipartisan Policy Center’s Governor’s Council and executive-in-residence at Middlebury College. “Perhaps it’s not a sexy topic, but it’s essential to our efforts to improve the quality of care and contain costs.”

So, why such vague references to health IT? Shouldn’t the national party platforms include a greater vision of and intent for the technologies forging the underpinnings of next-gen healthcare in America? Or is what the parties outlined enough for the majority of American voters?

“At this point in time I think maybe it is enough,” said Iowa State Representative Linda Upmeyer (R), a career nurse practitioner who has proposed health IT legislation since being elected 10 years ago. “I hope what it means is that this is really in an early state, but there’s a commitment to move health IT forward, that they’re listening and trying to continually improve so that the government doesn’t get this wrong.”

While some will argue that the November elections might test the bipartisan nature of health IT, at least for now Ahier, Douglas and Upmeyer view the party platforms as evidence that bipartisanship remains intact.

“It would seem that both parties agree that when health IT is used effectively it can help address the challenges confronting our healthcare system,” Ahier said. Douglas added that “the current administration continues to move the ball down the field through grants to the states, incentives to providers and implementation of the meaningful use standards,” he said. “I’m confident that the bipartisan support will continue because both parties understand the value of HIT.”

Which leads back to the beginning, where both parties support health IT, but are short on detail about exactly how – which may be because neither party can say for sure precisely what committing to health IT will really mean for the future.

[See also: Political strategists on how candidates should shape healthcare messages in election.]

“It’s always important to have something that keeps policymakers pushing health IT to the forefront, but we policymakers, be it inside the beltway or inside the golden dome in Iowa, don’t have the solutions or all the answers. So we can commit to investing in health IT and rely on the people really doing it to help determine what the next steps are,” Upmeyer, the Iowa rep said. “I don’t really want congressmen or senators or legislators deciding for them.”

Neither does Steven Waldren, MD, director of the Center for Health IT at the American Academy of Family Physicians.

“I’d much rather health IT not be a political football and remain behind the scenes a little because there’s no political urgency such that either side is going to try to politicize it and move forward. Instead, they recognize it’s an important issue,” Waldren said. “The two platforms have different philosophies but at least it’s not being debated at the level of lies, made up truths, or spinning things out of context.”

Although, there might be a solid punch line or two to emerge from that manner of rhetoric.

For more of our politics coverage, visit Political Malpractice: Healthcare in the 2012 Election.

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HealthCare Data Mining and Natural Language Processing

November 17, 2011 admin No comments
HealthCare Data Mining and Natural Language Processing
View more presentations from Neil Shah

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Healthcare Data Mining, Structured Data and Natural Language Processing

November 7, 2011 admin No comments

EZDI Healthcare Data Mining, Structured Data and Natural Language ProcessingMedicine and healthcare have been one of the most researched and studied branches of Science for centuries.  There are records of use of medicines as early as 500 B.C.  Research and development over millions of years has led to the establishment of the current structured healthcare system.  Documentation of patient records is an integral component of healthcare and mandatory in many countries which rely on insurance-based healthcare systems.

Early forms of healthcare documentation involved physicians keeping hand-written records of patient visits and filing this information for future reference.  Managing records of thousands of patients in paper became impossible, not to mention that paper-based records were vulnerable to loss in natural calamities.

This led to the birth of electronic healthcare data capture and documentation.  Patient records were then managed in the form of electronic documents and systems like EMRs, EHRs, and other forms of electronic healthcare data management systems provided secure patient information and easily available to the physicians whenever required.

Hospitals and healthcare practices across the US spend thousands of dollars every year in documenting and managing patient care details to meet statutory requirements of the healthcare industry.  Most of this data is recorded and stored in EMRs and EHRs and used generally for insurance purposes or for reference.

An innovative and visionary line of thought is the use of concrete data and evidence to support medical decisions.  This is called EBM or evidence-based medicine.  Evidence of this is available from as early as 1854 when John Snow (considered the father of epidemiology) used maps with bar graphs to discover the source of a cholera outbreak and trace it to the water supply system in London.  He counted the number of deaths and plotted the victims’ addresses on a map and saw that all the deaths occurred around a common water body.  This was one of the earliest applications of data mining.

The modern EMR of a hospital or healthcare facility is a rich treasure-house of information of thousands of patients with a wide facet of illnesses, containing thousands of medicines, history etc.  Each and every bit of information stored in this system could be a part of a pattern of events which if studied could give valuable insights into the pattern of diseases and the techniques of treatment and if researched lead to predictions about disease outbreaks.

The question however is how do we tap into this vast pool of data and extract the information we need!!!

This could be available either by:

  1. Manually searching through thousands of documents.
  2. Creating an electronic tool to search for data and analyze patterns.

Manual searching of such huge volumes of data is not a practical solution.  An electronic tool to do that would have to be an intelligent system which should know exactly what to search for, where to search it, and how to present it in the most useful way.  Different physicians have different styles of dictation and formats of reports, the search tool will have to separate out the required information and present the most valuable information.

For example:

Heart disease is one of the most common causes of death in the United States.

Identification of early signs of heart disease can save thousands of lives.  Analyzing a database of thousands of patients with heart disease can give valuable information about the probable causes, nature of progression, etc., of heart disease and help in developing systems that could identify heart disease at the earliest signs of occurrence leading to timely treatment and preventive techniques can save many lives.

Natural Language Processing or NLP is a field of computer science and linguistics concerned with the interactions between computers and human (natural) languages.  It began as a branch of artificial intelligence.  In theory, natural language processing is a very attractive method of human–computer interaction.  Natural language understanding is sometimes referred to as an AI-complete problem because it seems to require extensive knowledge about the outside world and the ability to manipulate it.

Combining NLP and data mining provides the solution to tap into the huge resource of health-care data and provide tangible solutions to queries and problems.

EZDI is a clinical Natural Language Processing Engine that identifies and converts relevant text into codes and numbers using patented technology.

EZDI combines data mining and NLP to extract clinical information from an EMR, or any healthcare documentation system, and provides structured information on diseases, findings, procedures, microorganisms, pharmaceuticals, etc., arranged systematically with computer processable collection of medical terminology SNOMED-CT (Systematized Nomenclature of Medicine – Clinical Terms).

Key Areas of Application Include:

  • Improving the Quality of Patient Care

Identifying high-risk patient groups with combinations of symptoms and/or risks.

Identifying the need for prophylactic measures to prevent outbreak of disease.

Improve patient care through efficient prescribing of drugs by identifying duplication or over-prescribing of drugs, and also identifying potential drug interactions in contraindicated drugs

Search for statistical data regarding patient-disease patterns, classifying them based on age, gender, geographical locations, food groups, etc., by identifying common factors among patients with similar diseases.

Identifying the need for diagnostic tests in specific patients, leading to effective dispensing of health care measures.

  • Ensure Compliance of Health Care Documentation

EZDI’s search engine makes auditing and reporting of “medical records compliance” an automated process.

  • Revenue Generation and Saving

Lowering the cost and effort involved in clinical Research and Development through automated chart review.

Identifying the need for specific diagnostic tests in specific patients, leading to effective dispensing of health care measures and eliminating unnecessary tests.

EZDI is the perfect tool for evidence-based medicine and treatment and is the future of healthcare in general.  With accuracy up to 98% and immediate availability of query results, EZDI is the future of clinical data analytics this product will ensure more effective and efficient healthcare delivery.

About ezDI

The Company is one of the leaders in business intelligence and healthcare analytics that aim at improving the quality of services in health care and reducing costs. The company offers integrated solutions with a single data feed, and increases the industry’s speed, accuracy, flexibility and value overtime.

For additional information, please visit http://www.ezdi.us .

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