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The Impact of the Obama Healthcare Agenda on Business Intelligence

Originally published February 24, 2009

Every four or eight years, a new administration enters the White House with new promises for its healthcare agenda. The Obama administration has made some of the most specific statements about its intent to reform healthcare, but has offered few details of how it intends to complete this transformation. Prior to his inauguration, Obama listed healthcare IT as a priority for reducing healthcare costs. To back this up, Obama and the House Democrats drafted the American Recovery and Reinvestment Act (now known as the stimulus package), which initially allotted $30 billion for Healthcare IT. After recent modifications by Congress, it is now $19 billion. With the new President’s focus on the mechanisms that improve access to data, such as healthcare IT, opportunities will arise to improve business intelligence programs in healthcare.

There are several areas of the Obama-Biden plan that could have a significant impact on business intelligence if they come to fruition. The first is the intent to “invest in proven strategies to reduce preventable medical errors.” First and foremost is wider adoption of electronic medical records (EMR). Research has shown that without access to continuity of care that an EMR provides, medical errors will continue to occur often. According to an article in the Washington Post, 49% of patients suffered at least one medical error in the two months after leaving the hospital. This is often attributed to physicians responsible for follow-up care in the clinics not knowing what was done in the hospital or what still needs to be done (“VA Takes Lead in Paperless Care.” Brown, David. April 10, 2007). Furthermore, EMRs are particularly good at managing the dispensing of prescription drugs, the primary source of medical errors.

However, the barriers to EMR adoption are significant. First of all, estimates of costs for adopting EMR range from a few million to $60 million per hospital system. While the savings may be significant over time, it is still difficult for hospital systems, clinics or physicians to make the case for a capital investment during depressed economic times. The overall cost to implement EMR nationwide could easily dwarf the $19 billion earmark.

The second barrier to adoption, and perhaps the most impactful, is standardization. The many EMR products available currently vary greatly in their approach. Some fields require “yes” or “no” answers that limit the doctor-patient interaction to a simple question-and-answer session. The benefit is that it produces quantifiable data for analysis, but the disadvantage is that doctors may miss something they would have caught through a traditional conversation with the patient. The other side of this coin is that EMRs are transcription-based. They function in a way that physicians are familiar with, utilizing software that creates transcripts from their dictation. Physicians are comfortable with this functionality, but the disadvantage is that much of the data is textual and therefore more difficult to analyze, and there is often a minor delay in access due to transcription.

With these very significant barriers to adoption, many groups have argued against the feasibility and value of making a sweeping requirement. But, if the administration makes good on its promise, the size of data warehouses around the country will grow radically. The value of this data is hard to predict since much of the information in a medical record comes from the physician’s notes, which is not “quantifiable” in the traditional sense. Taking full advantage of the analytic capabilities of this data would require an investment in qualitative data analysis. And this is exactly what the Department of Veterans Affairs has done. “Searchable computerized databases allow physicians to examine information collected across time and space.” In addition, “They may also prove to be essential tools of research, allowing scientists to examine patterns of medical practice, drug use, complication rates and health outcomes." In reality, very few healthcare companies are using the EMR for analytic purposes, but the possibilities are endless. What if we could do analysis on weight changes over time? As a tool in the battle against epidemic obesity, a BI program backed with EMR data could track changes in weight over time and perhaps even find predictive indicators of weight changes (besides the obvious ones like pregnancy and seasonality). Speaking of seasonality, imagine the analyses you could do on appointment cancellations by seasons. You could make staffing modifications if you knew that more patients cancel their appointments on particular days of the year. It is possible to create a return on your data storage investment if business intelligence and analytics are the focus.

The increase in volume and type of data may certainly strain the data warehousing applications, but perhaps a bigger consideration is that more data isn’t always better. First, we have to address the quality of the data. Healthcare data is notoriously quality challenged, and it’s unlikely that the EMR will be any different. And since no standard version of an EMR system has been mandated, we can assume that our biggest data quality challenge will be comparing data between many types of systems. This would be particularly true if a single hospital or clinic had more than one system, which would slow adoption and diminish the value of EMR.

Assuming we address the quality issue, how will we use this data to the benefit of the patient? Will the data simply reside in a database and be used only during clinical visits or hospital stays? Additional value will be discovered if patients have access to this data as part of a personal health record (PHR). The adoption of an EMR will challenge the current analytic capabilities, not just technologically, but from a personnel standpoint due to the lack of analysts who could turn this data into valuable information.

The need for change in healthcare is no longer debatable, but what remains debatable is the role that business intelligence and analytics will play in this reform. I believe that the biggest challenge facing healthcare business intelligence is using the data effectively and getting tangible benefits that outweigh the costs. The high-side potential is huge, with improvements possible in everything from scheduling, to hospital operations, to benefit structures of insurance companies. With Obama’s funding coming soon, it will be up to BI professionals to meet the challenge and help improve the state of American healthcare.

  • Laura MadsenLaura Madsen
    Laura leads the healthcare practice for Lancet, where she brings more than a decade of experience in business intelligence (BI) and data warehousing for healthcare, and a passion for engaging and educating the BI community. At Lancet, she spearheads strategy and product development for the healthcare sector. She also works with key accounts across the country in the provider, payer, and healthcare manufacturing markets. Laura is the founder of the Healthcare Business Intelligence Summit, an annual event that brings together top hospitals, insurers, and suppliers in the healthcare business intelligence space. Laura is also the author of the popular book, Healthcare Business Intelligence: A Guide to Empowering Successful Data Reporting and Analytics (Wiley, 2012). You may reach her at lmadsen@lancetsoftware.com.

    Editor's note: More healthcare articles, resources, news and events are available in the BeyeNETWORK's Healthcare Channel featuring Laura Madsen and Scott Wanless. Be sure to visit today!

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Posted February 25, 2009 by Nick van Terheyden

Interesting article - the soltuion is out there to help solve this problem:


You can read more details here

Nick van Terheyden, MD

Chief Medical Officer





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