• CraigRhinehart

Healthcare and ECM – What’s Up Doc? (part 1 of 2)

Updated: Feb 20


healthcare data

This is one of those industry-centric topics everyone can relate to … we all need healthcare and we’ll all use it at some point in our lives. I plan to write a couple of posts on Healthcare and ECM … here is the first.


The healthcare industry is undergoing a major transformation. 


We have a legacy health system that is fee-for-service based resulting in a care system that is high cost with inconsistent quality.  Healthcare provider consolidation is accelerating; competitors, as well as payers/providers, are merging. Clinical transformation is already occurring … disease management, health and wellness management, and behavioral health are integrating. The industry is moving to a more patient-centric, evidence-based and competitive care system where the players are held accountable and will have to compete on the value they deliver and not rely solely on quantity-based reimbursements.


This transformation is driving new thinking, new business models, and restructuring of clinical and operational care models.  The expectation of value is changing and healthcare organizations have to adjust their business models to deliver value, not just volume. This type of transformation requires innovation … the kind of innovation that improves productivity and competitive advantage … and not just advancing medical technology for technology's sake. The main consideration must be for total well-being and cost, and not one for the sake of the other.


As the backbone for a transformed healthcare system, leveraging clinical information and operational data in new ways are obvious things to do to improve quality of care, patient satisfaction and business efficiency. This places a premium on making this information accessible and actionable to optimize outcomes! … and where ECM comes in!


Enterprise Content Management (ECM)


There are many ways ECM technologies are being applied to solve problems in healthcare. The obvious ones are document capture conversion of paper-based patient records and advanced case management for care coordination. I am going to focus on content analytics and leveraging unstructured information to reveal insights currently trapped in documents, records and other content.  I believe this has significant transformative potential as ECM-based information technology.


Studies show that healthcare information is growing at 35% per year and that over 80% of information is unstructured data (or content).  The explosion of information makes accessing and leveraging it a harder task, but this is now an imperative.


Unstructured Data


Unstructured data resides in many sources:  physician notes, registration forms, discharge summaries, text messages, documents and more. Because this content lacks structure, it is arduous for healthcare enterprises to include it in business analysis and therefore it is routinely left out.


The impact of this is staggering.  If you had a choice – would you choose to leverage all of your available information or just the 20% that is structured data and found in databases?  This is exactly the type of thing that can accelerate transformation.  We need to leverage the remaining 80% of available information.  After all … would you want your Doctor making decisions about your health on 1/5th of the available information?


It’s such a simple premise but the reality is that until recently, the technology wasn’t available to easily and accurately analyze and unlock insights contained in the unstructured information. This is where natural language processing (NLP) and breakthrough technologies like IBM Watson and IBM Content Analytics come in. So let’s apply this to the real world.


Smoking has long been known as a habit that contributes to poor health and diseases like Congestive Heart Failure (CHF) but how accurately do the healthcare systems of today reflect the patient’s current smoking status? To understand a patient’s smoking status … it cannot only be a yes/no checklist question found in structured data. How can a check box know you if you quit 3 years ago … or started again last year and just recently quit again … or that you recently took up casual cigar-smoking … or that you cut down from 2 packs to 1 pack a day? 


Structured Data


A structured data field can’t understand these nuances. This is natural language based information found only in text.  These text-based descriptions are often captured in registration forms, history and physical reports, progress reports and other update reports.  Most systems have not factored in this kind of information due to the cost and time taken to manually extract it. It’s often too costly and too late. Yet it is exactly this kind of information that could be most critical in improving care.


In a recent private IBM customer data study, we found 40% of the total population of smoking patients were identified in the text of unstructured physician notes, and not the structured data. This is huge! Can you imagine doing research on smoking without including this kind of information? … or not including 40% of the total smoking population?


BJC Healthcare has figured out the value of leveraging unstructured data. They found that structured data alone was not enough when doing research often resulting in the reading of documents … many many documents … one by one. You can imagine how fun and helpful that was. They are now using IBM Content Analytics to extract key medical facts and relationships from more than 50 million documents in medical records, speeding up research to ultimately provide better care for patients worldwide… See the recent case study.


I feel strongly that ECM technologies, and especially Content Analytics, can make a huge impact in both the clinical and operational healthcare transformation underway.


As always, leave me your thoughts and comments here.


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