Healthcare and ECM – What’s Next Doc? (part 2 of 2)
Updated: Feb 19
In my last blog post, Healthcare and ECM – What’s Up Doc?, I wrote about using ECM-based content analytics technology to help accelerate decision-making in an industry in transition.
But why stop there … how powerful would it be to turn those new insights (from unstructured information) into action by combining content analytics with predictive analytics or other business analytics?
This is transformational … by unlocking the 80% of information not currently being leveraged (explained in part 1) we unlock new ways to use information. More compellingly, we unlock never seen before trends and patterns in both clinical and operational data.
Think about it … do we know everything we need to know about healthcare and how to identify and treat diseases? Or can we benefit from new insights? The answer is obvious.
Combining content and predictive analytics enables:
Accurate extraction of medical facts and relationships from unstructured data in clinical and operational sources – not easy, cost-effective, or even possible in the past.
Never seen before trends, patterns and anomalies are revealed – connections or relationships between diseases, patients and outcomes (and even costs) are now able to be surfaced and acted upon. Think of the medical research possibilities!
The ability to predict future outcomes based on past and present scenarios – optimizing resource allocation and patient outcomes. One organization reduced cardiac surgery patient morbidity from 2.9% to 1.3% by doing this.
New insights can be surfaced to any clinical or operational knowledge based on their respective role – this could be through dashboards, case management/care coordination system, EMR, claims processing or any number of other ways – enabling better decision making and action across the organization.
The ability to leverage these new insights with other systems such as data warehouses, master patient data – maximizing and befitting from the use of other systems.
In my last post, I commented that it was now imperative to leverage clinical information and operational data in new ways … and there are obvious things to do to improve quality of care, patient satisfaction and business efficiency.
There are at least nine areas where this opportunity exists. The clinical scenarios are:
Diagnostic Assistance: Highly correlated symptom to health/disease analysis issues visualized with predictive guidance on diagnosis to improve treatment and outcomes … with predicted or forecasted costs.
Clinical Treatment Effectiveness: Examine patient-specific factors against the effectiveness of a healthcare organization's specific treatment options and protocols … including comparisons to industry-wide outcomes and best practices.
Critical Care Intervention: Early detection of unmanageable or high-risk cases in the hospital that leads to interventions to reduce costs and maintain or improve clinical conditions … including case-based interventions.
Research for Improved Disease Management: Perform analysis and predict outcomes by extracting discreet facts from text, such as: patient smoking status, patient diet and patient exercise regime to find new and better treatment options … use a mechanism for differentiation or to secure research grants.
Claims Management: All claims involve unstructured data and manually intensive analysis. Analyze claims information documented in cases, forms and web content to understand new trends and patterns to identify areas … perfect for process improvement, cost reduction and optimal service delivery.
Fraud Detection and Prevention: Uncover eligibility, false assertions and fraud patterns trapped in the unstructured data to reduce risk before payments are made … usually represented by a word or combination of words in text that can’t be detected with just structured data.
Voice of the Patient: Include unstructured data and sentiment analysis from surveys and web forms in an analysis of patient and member satisfaction … this will be key as the industry moves to a value-based model.
Prevention of Readmissions: Discover key indicators which are indicative of readmission to alert healthcare organizations to these so that protocols can be altered to avoid readmission … this is key as new Medicare payment penalties go into effect in 2012.
Patient Discharge and Follow-up Care: Understand and monitor patient behavior to proactively inform preventative and follow-up care coordinators before situations get worse.
According to the New England Journal of Medicine, one in five patients suffers from preventable readmissions. This represents $17.4 billion of the current $102.6 billion Medicare budget. Beginning in 2012, hospitals will be penalized for high readmission rates with reductions in Medicare discharge payments.
Seton Healthcare Family
Seton Healthcare Family is already ahead of the game. "IBM Content and Predictive Analytics for Healthcare uses the same type of natural language processing as IBM Watson, enabling us to leverage our unstructured information in new ways not possible before,” said Charles J. Barnett, FACHE, President/Chief Executive Officer, Seton Healthcare Family.
“With this solution, we can access an integrated view of relevant clinical and operational information to drive more informed decision making. For example, by predicting readmission candidates, we can reduce costly and preventable readmissions, decrease mortality rates, and ultimately improve the quality of life for our patients.”
This week at IOD … IBM is launching a new solution specifically designed to reveal clinical and operational insights in the high impact overlap between clinical and operational use cases – enabling low-cost accountable care.
IBM Content and Predictive Analytics for Healthcare
IBM Content and Predictive Analytics for Healthcare, a synergistic solution to IBM Watson, helps transform healthcare clinical and operational decision making for improved outcomes by uniquely applying multiple analytics services to derive and act on new insights in ways not previously possible … which is exactly what Seton Healthcare Family is doing.
IBM Content and Predictive Analytics for Healthcare (ICPA) is Watson Ready and is designed to complement and leverage IBM Watson for Healthcare through the ability to analyze and visualize the past, understand the present, and predict future outcomes.
ICPA, as the first Watson Ready offering, not only provides assurance of Watson solution interoperability but extends the value ultimately delivered to clients. For example, using input from ICPA outcomes, IBM Watson will be able to provide better diagnostic recommendations and treatment protocols as well as learn from the confidence-based responses.
But it’s not just healthcare … every industry is impacted by the explosion of information and has the same opportunity to leverage the 80+ percent that is unstructured to turn insights into action.
As always, leave me your thoughts and comments here.
#NLP #textanalytics #ECM #IBMInfoGov #AIIM #contentanalytics #enterprisesearch #IBMWatson #cloud #seton #analytics #classification #categorization #Watson #ibm #ACM #infogov #healthcare #QA #Jeopardy #IBMECM #DeepQA #search