Lead Bus Solutions Analyst, Mercy
SuperNova Award Category:
Mercy, the seventh largest Catholic health care system in the U.S., serves four states and millions of patients annually. Mercy includes 34 acute care hospitals, four heart hospitals, two children’s hospitals, three rehab hospitals and two orthopedic hospitals, nearly 700 clinic and outpatient facilities, 40,000 co-workers and more than 2,000 Mercy Clinic physicians in Arkansas, Kansas, Missouri and Oklahoma. Mercy also has outreach ministries in Louisiana, Mississippi and Texas. For the 12th time in 17 years, Mercy has been placed on the American Hospital Association’s (AHA) Most Wired list for 2015, alongside Kaiser Permanente, Mayo Clinic and others.
Providers treating patients in a hospital setting stay focused on the primary reason for admission and often miss the documentation of disease conditions that are secondary diagnoses. At best, the clinical indicators may be mentioned in the physician’s notes or captured in discrete measures, but the lack of documentation does not accurately portray the complete care provided to a coding specialist. As an example, if a physician is treating a patient with a Urinary Tract Infection (UTI) who also has Sepsis (a severe life threatening condition), it may lead to the documentation of ‘Urosepsis’ which codes to a simple UTI and thereby inaccurately reflects the patient care provided. Medical Documentation Specialists (MDS) spend hours manually sifting through patients’ charts searching for specific clinical indicators that would help identify possible documentation omissions.
In May of 2014, Mercy began using industry-leading analytics utilizing a combination of data warehouse tables, ETL logic, Business Objects reporting universe, Epic’s (Electronic Medical Record) reporting interface as well as a strong partnership with Medical Documentation Specialists (MDS). This led to a transformation of a manual, time consuming medical documentation workflow to an automated instantaneous detection of diagnosis opportunities targeted to improve the accuracy of provider documentation.
Our unprecedented, innovative solution integrates business intelligence into clinical workflows in ways that transform and simplify a complex, labor intensive, manual process to an automated solution. This enables frontline caregivers to turn insight from the report into immediate action. We have been able to convert a 20-40 minute MDS chart review process to an instantaneous detection of an opportunity, not to mention the greater accuracy it delivers. MDS users now have the ability to click on hyperlinks within the report that will take them to specific areas in the Epic chart for a more detailed review, as well as to submit a query to the physician about the possibility of a missed documentation of a diagnosis. In tandem with this, the method of communication between MDS and physicians has transformed, encouraging more face-to-face communication. Sometimes little changes have big effects; in our case, the effect of implementing this novel approach across the multiple acute care hospitals spanning four states had an exponential downstream benefit towards accuracy of documentation and increased reimbursement.
An analytical application was created that measures the impact of this automation report on key metrics such as Case Mix Index (CMI), Severity of Illness (SOI), Risk of Mortality (ROM), Diagnosis Related Group (DRG), and Length of Stay (LOS). This monitoring enables continuous workflow improvement and targeted educational opportunities. The process efficiency gains of 20-40 minutes per chart review resulted in our solution being utilized more than 150 times per week by Mercy’s MDS team since its introduction. It has contributed to an improved, more accurate reflection of the clinical picture with an increase in CC (Complication and Co-morbidity)/ MCC (Major Complication and Co-morbidity) rates by at least 36%. Our physician response times to queries have also interestingly improved by roughly 40%. Additionally, it has led to a significant increase in reimbursement, per initial evaluation, possibly more than a million dollars per year.
Mercy used a combination of data warehouse tables, ETL logic, Business Objects tools and Epic’s reporting interface to deliver the secondary diagnosis automation report. We were able to embed this new solution within the end users existing workflow. In addition, we utilized Smart Data Elements (custom data attributes created within the Epic system) to track the adoption of the new innovative process versus a manual, labor intensive chart review.
Typically, any operational change is hard. However, in this case the ease of use, automated detection of secondary diagnosis opportunities embedded in the workflow with the resultant time savings in process efficiency were so significant that it became more of a pull by the end user than a push. This led to more requests to add additional disease conditions to the list purely because of the peer to peer advocacy of the value realized.
There have been quite a few process changes. Here is how it’s different now:
We now leverage discrete data elements to automate identification of high-value secondary diagnoses.We have integrated business intelligence tools and electronic patient health records to expedite the chart review process.We successfully transformed communication methodology between MDS and physicians to encourage face to face non-leading dialogue instead of traditional queries.We utilized Smart Data Elements to monitor, manage and track the success of the secondary diagnosis automation report.
Our solution has dramatically simplified the process of identifying and addressing clinical documentation deficiencies. This improvement more accurately reflects the patient care provided and dramatically increased the revenue opportunity for Mercy. Our goal is to continuously integrate analytics into patient care workflows, enabling the insight gained to drive a smarter platform that raises the bar towards improved, higher impact and compassionate patient care.