Move the Quality Focus to Patient Outcomes

I had the privilege to attend the Microsoft Connected Health Conference in Bellevue, Washington on May 19-20.  Microsoft changed the format of their education sessions this year to a panel discussion including short presentations.  This new format included a moderator and several views of the topic from industry experts and key people from healthcare organizations.  One of my favorite sessions was titled “Capturing Value Across the Continuum: Healthcare Quality and Outcomes.”  If you have been following the Edgewater blogs on improving Core Measures then you understand my interest.

The real take-away on this topic was the understanding that the focus on quality in healthcare has been centered more on improving business processes than improving patient outcomes.  The panel consisted of Kim Jackson, Director of Data Warehousing, St. Joseph Health System, Kevin Fahsholtz, Senior Director with Premier, Dr. Floyd Eisenberg, Senior Vice President for Health Information Technology at the National Quality Forum and Dr. Richard Chung of the Hawaii Medical Services Association.  The panel represented a Hospital Provider (Kim), an Analytics and Benchmarking company (Kevin), a healthcare standards organization (Dr. Eisenberg) and a Payer organization (Dr. Chung),all of the key aspects of the Healthcare Quality continuum and was focused on the real world challenges of improving the quality of healthcare.

The key idea of improving patient outcomes dominated the hour long discussion.  Kim White noted that “the burden (of collecting data) for a hospital is overwhelming, and measuring is overtaking the work.”  Dr. Eisenberg agreed that there was a need to move the focus of the quality measures to outcomes and away from the small process details.  He went on to say that the real issue is the definitions of the data and that the definitions need to be standardized.  In his role, Dr. Eisenberg is working to create a standard data model for quality measures and key definitions to the standards for care.  Dr. Chung pointed out that we need to change our “culture of care delivery” along with the awareness of the data.  Dr. Chung believes that providing visibility of the quality data helps set up a culture of change.  His experience shows that separating the data from the application software allows new understanding.
All of the panelists agreed that a key issue is developing the “single version of the truth” and eliminating conflicting information.  Kim White presented that using Microsoft’s Amalga UIS product allowed St. Joseph Health System to unite their data, reorganize their data and prioritize it.  She pointed out that consolidating data sources from eight locations created this “single version of the truth” and reduced the administrative burden for tracking core measures.

Our experience in improving core measures parallels this panel discussion.  Success in improving healthcare quality and outcomes involves plain old hard work – collecting the right data, with the right definition, at the right time in the process and providing it to the right people.  The need to extend the data collection to tracking outcomes beyond reporting requirements is the right idea at a right time in healthcare.  Let’s not settle for the minimal reporting requirements, but truly track outcomes and develop the feedback loops necessary to keep them successful and improving.  It is, after all, about the patient and not mere statistics.

From Free Text Clinical Documentation to Data-rich Actionable Information

Hey healthcare providers! Yeah you the “little guy”, the rural community hospital; or you the “average Joe”, the few-hundred bed hub hospital with outpatient clinics, an ED, and some sub-paper-pilespecialties; or you the “behemoth”, the one with the health plan, physician group, outpatient, inpatient, and multi-discipline, multi-care setting institution. Is your EMR really just an electronic filing cabinet? Do nursing and physician notes, standard lab and imaging orders, registration and other critical documents just get scanned into a central system that can’t be referenced later on to meet your analytic needs? Don’t worry, you’re not alone…

Recently, I blogged about some of the advantages of Microsoft’s new Amalga platform; I want to emphasize a capability of Amalga Life Sciences that I hope finds its way into the range of healthcare provider organizations mentioned above, and quick! That is, the ability to create adoctor microscope standard ontology for displaying and navigating the unstructured information collected by providers across care settings and patient visits (see my response to a comment about Amalga Life Science utilization of UMLS for a model of standardized terminology). I don’t have to make this case to the huge group of clinicians already too familiar with this process in hospitals across the country; but the argument (and likely ROI) clearly needs to be articulated for those individuals responsible for transitioning from paper to digital records at the organizations who are dragging their feet (>90%). The question I have for these individuals is, “why is this taking so long? Why haven’t you been able to identify the clear cut benefits from moving from paper-laden manual processes to automated, digital interfaces and streamlined workflows?” These folks should ask the Corporate Executives at hospitals in New Orleans after Hurricane Katrina whether they had hoped to have this debate long before their entire patient population medical records’ drowned; just one reason why “all paper” is a strategy of the past.   

Let’s take one example most provider organizations can conceptualize: a pneumonia patient flow through the Emergency Department. There are numerous points throughout this process that could be considered “data collection points”. These, collectively and over time, paint a vivid picture of the patient experience from registration to triage to physical exam and diagnostic testing to possible admission or discharge. With this data you can do things like real or near-real time clinical alerting that would improve patient outcomes and compliance with regulations like CMS Core Measures; you can identify weak points or bottlenecks in the process to allocate additional resources; you can model best practices identified over time to improve clinical and operational efficiencies. Individually, though, with this data written on a piece of paper (and remember 1 piece of paper for registration, a separate piece for the “Core Measure Checklist”, another for the physician exam, another for the lab/X-ray report, etc.) and maybe scanned into a central system, this information tells you very little. You are also, then, at the mercy of the ability to actually read a physicians handwriting and analyze scanned documents of information vs. delineated data fields that can be trended over time, summarized, visualized, drilled down to, and so on.11-3 hc analytics

Vulnerabilities and Liabilities from Poor Documentation

Relying on poor documentation like illegible penmanship, incomplete charting and unapproved abbreviations burdens nurses and creates a huge liability. With all of the requirements and suggestions for the proper way to document, it’s no wonder why this area is so prone to errors. There are a variety of consequences from performing patient care based on “best guesses” when reading clinical documentation. Fortunately, improving documentation directly correlates with reduced medical errors. The value proposition for improved data collection and standardized terminology for that data makes sense operationally, financially, and clinically.   

So Let’s Get On With It, Shall We?

Advancing clinical care through the use of technology is seemingly one component of the larger healthcare debate in this country centered on “how do we improve the system?” Unfortunately, too many providers want to sprint before they can crawl. Moving off of paper helps you crawl first; it is a valuable, achievable goal across that the majority of organizations burdened with manual processes and their costs and if done properly, the ROI can be realized in a short amount of time with manageable effort. Having said this, the question quickly then becomes, “are we prepared to do what it takes to actually make the system improve?” Are you?