Sunday, August 24, 2014

Recommendations for New Legislation & Regulations Supporting the Use of 'Big Data' in Healthcare


By Marc Wine & Peter Groen

Our nation’s healthcare system is in transformation from consumers paying a fee-for-service to paying for value-based outcomes of quality services. The collection, storage, analysis, and use of 'Big Data' are key to bringing about this transformation. 

The aim of this article is to provide a high level overview and recommendations to leaders in the healthcare industry, health information technology (IT) companies, and healthcare consumers about needed changes in legislation and regulations that will help facilitate the transformation of the healthcare sector, safely and securely.

This article focuses on selected high priority areas of healthcare delivery and health information technology (IT) that require a new framework and legislation to further encourage 'open access' and use of 'Big Data' to facilitate more effective direction and decision-making.

Background

The healthcare industry is still largely unprepared to deal with the flood of 'Big Data' being generated by Electronic Health Record (EHR) and Personal Health Records (PHR) systems that now include medical images, genomic data, and even biometric data generated by smart devices - all interconnected by Health Information Exchange (HIE) networks. There is a need for new legislation, regulations, and guidelines to help more effectively collect, store, analyze, and use 'Big Data' to improve healthcare for all.

Motivated by a desire to raise awareness and initiate a more detailed discussion about the topic of 'Big Data' in healthcare by lawmakers, consumers, healthcare organizations and the health IT industry, a detailed draft report was produced entitled, “A Congressional Analysis and Recommendations for Enhancing the Use of Big Data in Healthcare.” It was hoped the report could be used to help decision-making by key organizations like the Health Information Systems Society (HIMSS), eHealth Initiative (eHi), and the 'open source' EHR development community to encourage further collaboration in developing new and innovative 'open' solutions related to 'Big Data' in healthcare. This article contains highlights from that report.


Selected 'Big Data' Projects in Healthcare
Million Veteran Program (MVP) - This is an initiative supported by the Department of Veterans Affairs (VA) to enroll one million Veterans who are active users of the VA healthcare system into a genetic epidemiology cohort. Participants give informed consent and HIPAA authorization for unrestricted use of their electronic medical record (EMR) data and completed case report form (CRF) data for IRB approved research purposes. Additionally, they agree to future re-contact for the purpose of additional data collection and donate a sample of blood for storage and testing. To date approximately 250,000 subjects have been enrolled in MVP from 50 VA Medical Centers participating in the enrollment phase of the study. The intention is to create a platform that allows researchers to use the MVP data to better understand the genetic relationships to veterans suicidal conditions, PTSD/TBI, substance abuse and Alzheimer’s Disease. (SOURCE: Massachusetts Veterans Epidemiology Research and Information Center and Million Veteran Program)
Center for Medicare and Medicaid Services (CMS) - CMS has put together a centralized approach to using Big Data and predictive analytics. As part of their Fraud Prevention System and Medicare’s anti-fraud program, assembled a repository of algorithms to target specific claim and provider types. The goal of the program is to keep individuals and companies that intend to defraud out of the system. It also equips CMS with the tools to recognize fraudulent claims and eliminate payment errors. For example Big Data tools can be used to review large healthcare claims and billing information to target payment risk associated with each provider; over-utilization of services in very short-time windows; and patients simultaneously enrolled in multiple states. (SOURCE: Government Health IT, Top 9 Fraud and Abuse Areas for Big Data, May 2012)


Key Issues & Challenges

The President's priority for the public and private sector to harness the power of 'Big Data' for boosting productivity, generating innovation and improving citizen’s health through the power of collaboration and open solutions is commendable. Continued discussions about 'Big Data' and associated federal laws and regulations will help lead to a better understanding about what next steps to take in the healthcare arena.
 
The following are some of the key issues or challenges faced with regards to the use of 'Big Data' by the healthcare industry, especially as health IT systems see more widespread use and continue to evolve - adding genomic data, medical images, and biometric data collected by a wide range of smart devices.


  • Concerns about privacy and security should receive the highest priority when crafting and issuing new law and regulations related to 'Big Data.’
  • Manipulation of information about price, quality and access to care are often kept secret by healthcare providers to maintain a competitive edge and hide many shortcomings.
  • Physician documentation styles vary substantially, making errors and omissions in data collection difficult to identify.
  • The use of health information entered by consumers and aggregated into 'Big Data' systems can intentionally and unintentionally introduce systematic errors.
  • There is a need to rationalize complex, often conflicting legal frameworks as the stakes rise and 'Big Data' becomes one of the keys to the future of healthcare.
  • Much clinical data is still stored in 'unstructured' form within EHR systems, making it difficult to access for effective use when analyzing 'Big Data'.
  • The difference between 'Open Data' and 'Big Data' needs to be clarified and understood when crafting new policies and legislation.

Without consensus on clearly defined, concrete standards and a new healthcare roadmap for use of 'Big Data' for analytical and decision-making purposes, healthcare organizations and providers are likely to generate data that is not trusted and useful.


Major Findings & Observations


Empowering people with 'Big Data' for use in generating both quality and cost efficiency  will require all special interests coming to grips with information systems and new business processes that will help move the nation’s health providers and consumers towards a continuously Learning Health System, while also expanding the adoption of better interoperable technologies.

The following are some key observations and findings related to the current state of affairs concerning the use of 'Big Data' in healthcare:

  • A look ahead promises sweeping change in healthcare as a result of the new Affordable Care Act (ACA). Healthcare reforms need to address the topic of 'Big Data'.
  • Standardization of healthcare data is still a ways off. Health IT systems and the data they contain often are comprised of incompatible formats and definitions for similar data elements.
  • 'Big Data' is also still often kept in hard-to-penetrate silos owned by companies that are less than willing to share the data collected by their proprietary systems.
  • The quality of 'Big Data' is still an issue. To derive from insights from data collected by healthcare systems, it is critical that they be accurate, complete, and semantically harmonized.
  • Lawmakers and regulators, health providers and vendors plus the consuming public have yet to fully understand the relationship between 'Open Data' and 'Big Data' in healthcare.
  • Increasingly, healthcare institutions have access to digitized patient medical records containing massive amounts of raw data.
  • Much of the available health data are in textual form. While textual data are convenient for tasks such as review by clinicians, they present significant obstacles for graphic presentation, searching, summarization, and statistical analysis.
  • An interoperable and 'open' data architecture and infrastructure are key to enabling the collection, storage, and analysis of 'Big Data' in healthcare.
  • 'Big Data' technologies have emerged that have the capability to better data mine and analyze data now accessible via emerging health information exchange (HIE) networks.
To summarize, there is a need for Congress and regulating agencies to carefully craft new legislation and regulations further enabling ways to better leverage 'Big Data' in healthcare.

Conclusions & Recommendations

The key challenge now is whether we will limit the capacities of Big Data to outmoded legal and regulatory processes of enforcement or broaden them to affirmatively improve public health and reduce costs by creating Open Big Data.

The following are some key recommendations that Congress, regulatory agencies, industry leaders, and consumer groups might want to consider related to 'Big Data' and the healthcare sector.


  • Congress and regulators should encourage increased collaboration between the public and private sector entities so new and innovative technologies, business processes and solutions related to 'Big Data' can be unleashed
  • Congress should ensure that large-hospital provider networks will take no steps to inhibit the openness of the 'Big Data' marketplace that might be harmful to consumers’ interests.
  • Congress should encourage research, analysis and meaningful use of 'Big Data' now being captured by EHR systems
  • Congress and HHS should revise HIPAA to allow and encourage further sharing of personal health data between healthcare organizations.
  • Congress should establish additional HIPAA privacy guidelines for setting up and deleting all personally identifiable data after a designated timeframe and allow consumers to opt-in as anonymous data donors to support healthcare research.
  • CMS should determine and publish national criteria and standards for the enhanced use of 'Big Data' when measuring improvements in quality of care by Medicare and Medicaid programs.
  • For healthcare consumers, Congress should continue to help create a more trusted view of pricing for common procedures across the U.S. healthcare system.
  • Congress, HHS, FDA, and other regulatory agencies strive to establish laws, regulations and guidance with regards to data being generated by the growing number of smart healthcare devices that are part of the Internet of Things (IoT).
  • Especially with regards to Public Health, CDC should issue regulations requiring more collaboration and sharing of data between public and private sector healthcare providers.
  • Congress should legislate that all data and studies generated by government funded healthcare research ought to be shared and published in 'open access' journals.
  • Congress should develop legislation that provides investments for creative partnerships between universities and health IT vendor in order to better educate healthcare professionals and administrators in the analysis and meaningful use of 'Big Data'.
Again, our nation’s healthcare system is undergoing a major transformation and the collection, storage, analysis, and use of 'Big Data' are key to bringing about this transformation. Whenever and wherever possible, 'Big Data' in healthcare must be made more transparent and 'open'. This will facilitate the need for increased collaboration and data sharing across the healthcare sector leading to the development of many new and innovative solutions that may result in improving health and healthcare for everyone.


Other selected articles on the use of 'Big Data' in healthcare include:

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