While preventing all medication complications is impossible, health care providers strive to identify the risks of complications for their patients.  Complications can increase a patient’s length of stay, consume limited staff resources, increase the need for higher levels of care, and even lead to the patient’s death.

When a patient unexpectedly deteriorates from a complication, the poor outcome is often referred to as a failure to rescue or FTR case. The term can be used as a diagnosis or as a safety and quality measure. Hospital records use a coding system that can identify the diagnosis for a patient, and FTR has such a code. Since 2003, many healthcare organizations review their records to identify the underlying causes of their FTR cases to improve patient care and outcomes. In 2010, the Centers for Medicare and Medicaid Services began to monitor FTR rates using an algorithm called Patient Safety Indicators 04 (PSI 04).

With the advancement of the electronic medical record, data collection and analysis in the field of FTR has exploded. A few of the key studies and findings are highlighted below:

• Approximately 10% of general ward patients experience unexpected decompensation, with half transferred to an intensive care unit (ICU).¹
• Over 85% of cardiac arrests demonstrate a clinical warning signal up to 8 hours before the event.²
• Between 8% to 16% of hospital admissions develop in-house acute kidney injuries.³
• The majority of surgical ICU transfers happen within the first 48 hours of general ward patient transfers.⁴
• Patients who develop postoperative complications within 48 hours of general ward admission have a 44% increased mortality rate.⁴
• One in 10 postoperative Medicare patients dies after developing either a pulmonary embolism/deep-vein thrombosis, pneumonia, sepsis, shock/cardiac arrest, or a gastrointestinal hemorrhage.⁵
• By the time a rapid response team is informed, the patient may have been showing subtle signs of deterioration anywhere from 1 to 24 hours.⁶

Without question, we must work together to reduce the number of cases of FTR; thus, innovative solutions are needed to meet the challenge. As the studies above point out, warning signs are often seen before the devastating outcome. However, monitoring of patients is always a challenge. A nurse may be monitoring a large number of patients and miss key warning signs. This is an area where software can be used to automate data collection and improve the ability of team members to surveil patients. The InsightIQ software integrates on-time vital signs along with early warning system scores and other electronic data capture. A single screen at the patient’s bedside can vividly display the individual’s data in an integrated setting. Meanwhile the InsightIQ software can organize data from patients on an entire floor. Thus, the treating team has a report on how each patient is doing and which patients may need closer monitoring. 

Automation is not the only solution for reducing FTR. Multiple strategies are needed. However, implantation of smart software can help your team and your outcomes.

DECISIO is a Texas-based company with deep expertise in the healthcare industry and information technology. Our software experts work alongside clinicians and administrators to provide a framework for developing unique programs to address specific FTR situations. 

Learn more about InsightIQ and DECISIO’s suite of products at: https://www.decisiohealth.com/ 

References

1. Jones D et al. Challenges for recognising and responding to patient deterioration [Conference Presentation]. Singapore: International Society of Rapid Response Systems;  2019.
2. American Heart Association. Advanced Cardiovascluar Life Support: Provider Manual. Dallas (TX): American Heart Association; 2015.
3. Dasta JF, Kane-Gill S. Review of the Literature on the Costs Associated with Acute Kidney Injury. J Pharm Pract. 2019; 32(3):292-302. doi: 10.1177/0897190019852556
4. Liu V, Kipnis P, Rizk NW, et al. Adverse Outcomes Associated with Delayed Intensive Care Unit Transfers in an Integrated Healthcare System. J Hosp Med. 2012;7(3):224-30. doi: 10.1002/jhm.964
5. Read K, May R. HealthGrades Patient Safety in American Hospitals Study. Denver (CO): HealthGrades Inc; 2011. Available from: https://patientsafetymovement.org/wp-content/uploads/2016/02/Resources_Reports_Patient_Safety_in_American_Hospitals_Study.pdf
6. Churpek MM, Yuen KC, Huber MT, et al. Predicting Cardiac Arrest on the Wards – a Nested Case-Control Study. Chest. 2012; 141(5): 1170-6. doi: 10.1378/chest.11-1301