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The use of advanced electronic health record (EHR) systems has grown rapidly in the United States. This has created an abundance of data previously unavailable for analysis. Many Health
organizations have advanced and now have reporting systems for operational key performance indicators (KPIs), regulatory metrics and data warehouse systems for analytics. However, using this
information as meaningful knowledge to increase and target those areas of concerns regarding quality of care still remains a challenge.
In this use case, we explain how Fusion Consulting helped Loma Linda University Health Systems successfully turn data analytics for Clinical Quality – Blood Utilization into a strategic asset through the identification of targeted clinical programs and clinical events that affect quality care delivery. We demonstrated our expertise by utilizing an enterprise data warehouse and business intelligence tools to improve clinical outcomes for those most vulnerable patients who are at high risk of developing an infection due to blood transfusions.
• Chief Medical Officer (CMO)
• Chief Nursing Officer
• VP of Patient Care
• Director of Clinical Quality
• Inpatient Clinical Services Director
Loma Linda University Health System maintains all medical records using their EHR system. Fusion implemented the EHR’s data warehouse solution and extended it to become a true enterprise data warehouse including detailed clinical and operational information for each hospital visit.
Blood utilization is only used to monitor potential ordering abuse and wastage. It provides an organization with the information to make corrective clinical decision to help reduce unnecessary administrations of blood products. It is up to each organization to establish clinical guidelines for blood unit ordering and administration.
This use case explores our process for defining, and creating KPIs and business intelligence tools to analyze clinical outcomes. The goal was to use this analysis to identify Loma Linda’s clinical areas with the greatest opportunity for improvement and risk reduction specifically around blood utilization.
Together we developed work groups where quality clinicians worked with the business intelligence team to develop analytics for each targeted clinical program.
For blood utilization analysis, we limited the scope to red blood cells and addressed blood transfusions by analyzing the clinical events preceding the order to determine the necessity of the transfusion. Blood transfusions negatively affect the patient’s immune system and increase the risk of acquiring an infection. We evaluated each blood transfusion as clinically appropriate or not based on blood utilization categories. The key metrics to categorize clinical necessity are hemoglobin, systolic blood pressure, blood loss, lactate, base deficit, venous oxygen saturation, and the presence of acute myocardial infarction. There were five blood utilization categories applied to each unit of blood administered. Categories 1 through 4 represent a unit of blood that deemed clinically appropriate. If the blood unit administered is a Category 5 then the it is seen as having no applicable reason for administration.
Next, we built custom reporting tables or views for each of our programs. This enabled simpler reporting and better performance. We faced several challenges in this.
For blood utilization we needed to determine the exact number of units administered. Several of our early attempts, including looking at clinical documentation and order status, failed to give us
an accurate account due to workflow and documentation inconsistencies. Each unit of blood requires a label. We were finally able to get accurate information by directly mining the label
printing actions. Discarded units were being properly documented and were rare so we were able to take that into account. Another challenge with blood utilization is that we need to not just look
at lab results but look at the delta in lab results over specific periods of time. We built an auxiliary table which monitored delta ranges for lab results. This allowed this information to be updated
with standard incremental load and easily accessed.
Our self-reporting initiative has had significant early success. Users have created their own reports and developed programs not mentioned here, including cirrhosis, childhood immunizations, and critical care daily goals. These were developed not by the IT analytics team but by the business users and quality department.
We have evaluated progress of the analytics in improving clinician behavior and patient outcomes with the following results vs patient encounters prior to the analytics rollout:
Blood Utilization:
• 21% reduction in total blood units administered monthly
• 34% reduction in blood units administered without clinical necessity
• 7.4% reduction in the percentage of units which are not clinically justified
Total reduction of 5000 red blood cell units administered over 7 months.
CHF analytics can be reused in all inpatient hospital settings. CHF is a common chronic medical condition that is associated with complications and high mortality rates. Improving the quality of timely medical interventions associated with CHF exacerbation can improve patient outcomes. This CHF analytic clinical program will provide the necessary data elements clinically recommended to treat CHF exacerbation. The program tracks the times of which medical interventions are performed. This data will help to identify potential barriers and trends in treatment plans once CHF exacerbation treatment begins. The improvement of CHF exacerbation treatment workflows impacts notable hospital KPI’s such as length of stay, readmissions, and mortality rates.
Blood Product Administration Categories (Customer Specific)
Blood utilization is only used to monitor potential ordering abuse and wastage. It provides an organization with the information to make corrective clinical decision to help reduce unnecessary
administrations of blood products. It is up to each organization to establish clinical guidelines for blood unit ordering and administration. These established clinical guidelines will be represented as blood utilization categories in future use cases.
“Improving Patient Care Through Analytics” – Paper Publication Conference Paper· September 2016
DOI: 10.1109/ISCBI.2016.7743265
Conference: 2016 4th International Symposium on Computational and Business Intelligence (ISCBI)
https://www.researchgate.net/publication/310500110_Improving_patient_care_throug
h_analytics
https://www.researchgate.net/profile/James_Mcglothlin/publications?sorting=recently
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