Healthcare Analytics: Integrating content into business processes

Last week I was just thinking back to some interesting scenarios I have worked on over the years where content analytics was the key to both solving a critical business problem, but more importantly in generating real business transformation which is critical to success of any analytics project. These scenarios are not new or surprising, but I thought it might be helpful to intersperse my usually conceptually dense blogs with some light reading :-) So today lets look at a healthcare scenario for content analytics.

For most hospitals, the knowledge that resides within their unstructured text (referral or discharge letters, clinical notes, etc.) is largely ignored by their operational processes. Today when someone enters the Emergency Room it can take hours for their entire patient record to be retrieved from archives. Even for hospitals which have full digital records, there are frequently digital gaps (such as medical correspondence). In addition, even if all the information is complete, it can constitute hours of light reading and not something which is rapidly consumable for an emergency situation. This is clearly unacceptable. It was the opinion of the medical consultants that if they had quick & easy access to the key information encoded in the most recent outpatient and discharge letters (consolidated & prioritized), then that would significantly mitigate risk of mis- diagnosis & treatment in an emergency setting.

This approach to solving what could have been perceived as a simple search problem, proved to demonstrate a number of additional benefits above and beyond digitizing, searching, and retrieving clinical correspondence.

  • Firstly, through integrating the clinical documents directly into a PIMS system and converting them into a richly described XML format, you can convert these letters into HL7 records which means that instead of physically posting letters to General Practitioners you are now able to electronically transfer everything and have proper workflow and audit trails around the information.
     
  • Secondly, this new richly annotated content repository, which is linked to the structured PIMS data, provides a hugely valuable set of clinical data that could be used by consultants for research, reporting, tracking, evaluation, etc.
     
  • Thirdly, through integrating content analytics into the content creation process itself, writing of patient letters by the medical staff, you can introduce quality control and auditing at a very low cost to the clinicians creating the content. In fact, the additional time that may be involved in quality control is mitigated by other efficiencies introduced by the system.
     
  • Finally, today most hospitals have Electronic Medical Record (EMR) initiatives which are frequently unpopular, inefficient, and, in many cases, unsuccessful. One issue is that most these programs solve the “unstructured / structured” problem by simply throwing a myriad of huge, complex, and restrictive forms-based processes at clinicians. These forms not only cause huge amounts of frustration but their rigidity frequently means key information may be lost or misrepresented. Text fields are frequently used to workaround this data entry problem, however since the text fields are “black boxes” from an application integration perspective, we are back to square one – information silos. Real-time content analytics allows clinicians to describe patient symptoms, diagnosis, and prognosis in a natural way, while at the same time allowing the key concepts and facts to be captured normalized across different patient groups and medical vocabularies.
     

4 Comments to “Healthcare Analytics: Integrating content into business processes”

  1. FYI: Report Calls for Building #Biomedical #KnowledgeNetwork to Drive Precision Medicine | http://www.ucsf.edu http://bit.ly/tR4EyF

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    • Fantastic article & vision! Thanks for sharing.

      My early analytics work was in healthcare and I have to confess a soft spot for the space. It’s one off those few areas where you feel you are making a positive impact on society.

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  2. Marie,
    As always, your posts are both revealing and insightful. With respect to healthcare analytics, it seems to me that the problem is systemic and behavioral. If we remove the complexities of a) most healthcare facilities/practices are neither adept nor fond of EMR and b) data from facilities don’t necessarily integrate or compliment the data which comes from practices, I think we find ourselves with an enormous information and capabilities gap. There are certainly software vendors which are chomping at the bit to solve the mechanical problems of data integration but it seems to me that one of the biggest challenges in this whole equation is behavior and incentive. Based on my own recent experience with a visit to the ER, I was amazed at the inefficiencies, redundancies, and enormous cost violations which occur that are both systemic and technological. My ER discharge report said it all. At least in the U.S., it really is a complete mess. I was amazed at the degree of error and redundancy in the discharge report, the lack of information integration contributed by all the attending physicians, and the complete lack of communication to the primary care physician about the net results. At the risk of being insulting, a first year college student could map this process out more efficiently.

    I don’t know if this is more of a question, piece of commentary, or fodder for future discussion but it appears to me that the root cause that plagues the current healthcare system is complex mix of behavior, incentive, technology, and lack of education.

    Just my own personal ramblings :-) (but please keep yours coming!)

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    • Thanks for the great commentary and I really couldn’t agree with you more!

      The non-IT aspects (behavior, incentive, and education) are the key factors in realization of a successful analytics project. When I try to explain to a client that software isn’t the solution to their problem they look at me as though I have three heads [ I am supposed to be convincing them to buy software :-) ] But truth be told, trying to implement an analytics project without introducing process transformation is like trying to make an omelette without breaking an egg :)

      However these issues are not limited to the healthcare sector and are familiar characteristic of many analytics projects. The business process not only consumes the results of the analytics and hence needs to be maximized to effectively leverage insights (at the right time, in the right place, to the right person), it also generates (or should generate) the data that is needed for the analytics to be successful.

      I can’t count the number of times I have completed the business mapping process to uncover huge gaps in the data. Sometimes the gaps are due to a process break (as per your commentary). but other times they are due to data, perceived as irrelevant in a non-analytics context, being just thrown away. That’s the most frustrating aspect.

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