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Why an adjustable EPR is the best defense against sepsis

  • Steven Shaha, Ph.D., DBA
  • 04/22/2014

Sepsis exacts a devastating toll on human life, and the estimated costs for this disease are about US$17 billion in the United States alone.  But evidence suggests optimized electronic patient records (EPRs)* can make a real difference in the battle against sepsis and other hospital-acquired infections.

My personal prediction is that, because of our ability to detect patient deterioration, sepsis will eventually become another never event.

Fighting sepsis with computer power

Sepsis is a deadly and costly disease that arises when the body’s response to an infection damages its own tissue. Treatments are not benign and are astronomically expensive, hence clinicians are appropriately conservative in initiating treatment.

Sepsis is insidious. Clinicians know it might happen, but it’s hard to see all the factors contributing to it. In the past, we had to rely on smart clinicians, watching carefully to discern when a patient was about to “go septic.” Then they had to order the right labs to confirm their diagnosis and initiate immediate, aggressive treatment.

In our modern day and age we have another way. We can use computers for computing sepsis risk. We can detect patient deterioration using locally specific factors and avert, in many or most cases, sepsis. Worst case, we can detect sepsis early on, and initiate treatment early to minimize impact and cost.

The EPR can monitor patients in real time and assess important changes, and notify key clinicians to act quickly. This concept of alert-based monitoring of patient status is not new. We’ve had things like Early warning systems (EWS) and Medical Early Warnings (MEWs) for years.  However, the ability to achieve this early detection and alerting, leveraging locally relevant criteria that are programmed and refined locally IS new.

So now we have the option to program and customize EPRs by location. Our Sunrise platform has this capability, which is imperative for many reasons, including:

  • Targeting alerts to the right people. Who is the best clinician to respond to an alert? It’s different for different organizations. For some it’s the nurse, and for others it’s the attending physician. Still others prefer the rapid response team, or maybe all of the above. Providing locally relevant notifications reduces “alert fatigue” and improves clinician response.
  • Fine-tuning alerts for each population. In all fairness, no two acute care facilities have identical patient populations or community bugs. Some patient populations may be more susceptible to sepsis than others and some community bugs more virulent than others. Clinicians can modify alerts to suit these particular needs and optimal treatment alternatives, for example matching initial antibiotics to local microbes.
  • Keeping up with latest treatment regimens. Nobody knows what the best care model will be two years from now, or 10 years from now. So we need to be able to adjust our EPRs and treatment recommendations for clinicians.

How one organization reduced sepsis rates by 66%

By programming their EPRs to monitor each patient for changes in critical physiological factors, clinicians can now perceive deteriorating patients before they “go septic.” We can alert key clinicians so they can act efficaciously and avert disasters.

One specific organization I work with was able to reduce its sepsis rate by 66% over two years. The average cost per case for sepsis is open to debate. Estimates vary between US$7,000 and US$75,000 per case, reflecting the wide range of severity and comorbidities. But if we use a moderate estimate, that organization avoided more than $10 million in costs of sepsis care over two years.

Surely, we would like to eliminate all avoidable sepsis cases. Ideally clinicians can program, fine-tune and automate their EPRs for fast response. They should be able to readily adjust EPRs for new treatment approaches and protocols. Any organization that has to rely on the EPR vendor to provide this cannot effectively innovate or react to improvements in care models in time to avert disasters at the patient level.

Leveraging computing power inherent within advanced EPRs leads to better patient care, reduced costs, higher efficiencies and optimal clinical outcomes.

*Editor’s Note: Electronic Patient Record (EPR) is another term for Electronic Medical Record (EMR) or Electronic Health Record (EHR).

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About the author

Steven H. Shaha, Ph.D., DBA, is a Professor at the Center for Policy & Public Administration, and the Principal Outcomes Consultant for Allscripts. Dr. Shaha received his first doctorate in Research Methods and Applied Statistics from UCLA and has taught and lectured at universities including Harvard, University of Utah, UCLA, Princeton, Cambridge and others. An internationally recognized thought leader, lecturer, consultant and outcomes researcher, Dr. Shaha has provided advisory and consulting work to healthcare organizations including the National Institutes for Health (NIH), and to over 50 non-healthcare corporations including RAND Corp, AT&T, Coca-Cola, Disney, IBM, Johnson & Johnson, Kodak, and Time Warner. Dr. Shaha has presented over 200 professional papers, has over 100 peer-reviewed publications in print, over 35 technical notes and two books. He served on the 15-member team that authored and piloted the Malcolm Baldrige National Quality Award for Health Care, and he contributed to the Baldrige for Education.

3 COMMENTS on Why an adjustable EPR is the best defense against sepsis

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Sal Sabeela Ali says:

09/11/2014 at 5:58 am

Is it possible to share the cds used to capture sepsis?

Steve Shaha says:

09/12/2014 at 9:44 am

Thank you very much for your superb question. The regression analyses of the 12-months of retrospective data revealed six predictors of patient deterioration leading to all sepsis cases from the prior year. The underlying EMR/EPR was programmed to score every patient 24/7 on the six criteria and alert the key clinicians whenever any patient came at risk, or began to deteriorate, so that appropriate interventions could begin, as determined on personal observation to be needed or not.

Two of those predictors were comparatively static or unchanging, including BMI and Age – no surprise that patients with either of those clinical characteristics in any extreme would be at risk of deteriorating and becoming septic. Four of the six were more dynamic and reflected the ongoing changes in patient status or wellness, or deterioration and risk for sepsis. The more dynamic predictors included temperature, heart rate, respiratory rate and systolic blood pressure. It is important that none of the predictors depended on a lab value, thus making the ongoing monitoring and consideration possible for every patient, not only those for whom key labs had been taken. Scoring was bidirectional on a 0-3 scale for each of the six factors, meaning points were assigned whether the value for any factor went up or down, all as determined form the retrospective data analysis.

Once a patient was determined to be at risk by score, notifications went to key clinicians who acted. Actions could range from no action to launching of the Order Set programmed for requesting appropriate and pre-determined medications and labs, and the authorized clinician could also order different drugs or labs as exceptions, or images or any other exception as appropriate.

Thanks again for the inquiry, and let us know if more specificity would be helpful.

Steve himself says:

06/25/2015 at 9:20 am

Wow, this is so incredibly powerful and impactful.

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