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Learn how AI can help to reduce the prevalence of UTIs among at-risk patients and anticipate adverse events. Discover how AI can help to proactively predict individuals at high risk for UTIs, identify increased risk for avoidable catheter-associated UTIs, and predict and address complications due to overutilization of antibiotics (e.g. C. difficile infection).

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Medical Claims

Data extracted from health insurance medical claims with details about dates and place of service, diagnosis codes, key procedures, use of medical equipment, and provider specialties.

Lab Test Results

Data about important risk markers from tests used for diagnosis, monitoring therapy, or screening, with details about specific results and abnormal indicators.

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thousands of auto-generated, clinically relevant contributing factors

Karen Galen
65-Year-Old Female
Risk of admission due to UTI in the next 12 months
Risk Score Percentile
Impact on Risk  |  Contributing Factor
+21% | Diagnosis of Diabetes (12M)
+14% | Urine Culture for Bacteriuria
+12% | # of ER Visits (6M)
+5% | Uninsured Children %age Measure

What Are Urinary Tract Infections?

Urinary tract infections (UTIs) are the most common infections treated in outpatient settings in the United States.¹ UTIs are also the fifth most common type of hospital-acquired infection, with an estimated 62,000 infections occurring annually in acute care hospitals.² Each year, UTIs are responsible for approximately 400,000 hospitalizations, an estimated seven million office visits, and one million ED visits, resulting in roughly $10 billion in expenditures related to UTI care.³ 

Why It Matters

UTIs can lead to serious complications, especially for older adults, and may also be difficult to distinguish from asymptomatic bacteriuria (ASB). Catheter-associated urinary tract infections (CAUTIs) can lead to prolonged length of stay, sepsis, and increased costs and mortality. Annually, more than 13,000 deaths are associated with healthcare-acquired UTIs.² Differentiating UTIs from ASB in older adults is challenging, as ASB is estimated to be found in up to 16% of women older than 65.⁴ In long-term care facilities (LTCs), ASB prevalence may be as high as 50%.⁴ ASB also remains a common reason antibiotics are prescribed, but studies have indicated that up to 75% of antimicrobial use is inappropriate.⁴ This potential overutilization of antibiotics can lead to serious complications (e.g. C. difficile infection).

AI Presents an Opportunity

UTIs impose significant health and financial burdens, but providers can employ predictive analytics to proactively identify individual patients at high risk for UTIs and intervene accordingly. These interventions may be especially important for older adults who are at increased risk for complications due to overuse of antibiotics. UTI interventions may include encouraging sufficient fluid intake, promoting genital and urinary hygiene, and the use of low-dose vaginal estrogen cream.⁵ Removal of indwelling catheters without clear urological need can also prevent CAUTIs. 69% of CAUTIs are considered avoidable, and interventions based on decreasing utilization have been proven to reduce CAUTI incidence by 50% in acute care settings.⁶

Did You Know…

  • $10 billion is the estimated cost associated with UTI care in the U.S. annually³
  • 13,000 deaths are associated with healthcare-acquired UTIs each year²
  • 69% of CAUTIs are considered to be avoidable⁶
Citations & Footnotes

1. Medina, Martha, and Edgardo Castillo-Pino. “An Introduction to the Epidemiology and Burden of Urinary Tract Infections.” Therapeutic Advances in Urology, vol. 11, 1 Jan. 2019, DOI: 10.1177/1756287219832172. Accessed 5 Mar. 2021.

2. Centers for Disease Control and Prevention. “Urinary Tract Infection (Catheter-Associated Urinary Tract Infection [CAUTI] and Non-Catheter-Associated Urinary Tract Infection [UTI] Events.” National Healthcare Safety Network, Jan. 2021, https://www.cdc.gov/nhsn/pdfs/pscmanual/7psccauticurrent.pdf. Accessed 5 Mar. 2021.

3. Simmering, Jacob E., et al. “The Increase in Hospitalizations for Urinary Tract Infections and the Associated Costs in the United States, 1998–2011.” Open Forum Infectious Diseases, vol. 4, no. 1, 1 Jan. 2017, DOI: 10.1093/ofid/ofw281. Accessed 8 Mar. 2021.

4. Rowe, Theresa A, and Manisha Juthani-Mehta. “Urinary Tract Infection in Older Adults.” Aging Health, vol. 9, no. 5, Oct. 2013, pp. 519–528, 10.2217/ahe.13.38.

5. Family Health Team. “6 Things You Should Know about UTIs in Older Adults.” Health Essentials from Cleveland Clinic, Health Essentials from Cleveland Clinic, 4 May 2018, health.clevelandclinic.org/6-things-you-should-know-about-utis-in-older-adults/. Accessed 23 Feb. 2021.

6. Meddings, Jennifer, et al. “Systematic Review of Interventions to Reduce Urinary Tract Infection in Nursing Home Residents.” Journal of Hospital Medicine, vol. 12, no. 5, 1 May 2017, pp. 356–368, doi: 10.12788/jhm.2724. Accessed 8 Mar. 2021.

ClosedLoop is an exciting and important partner in our strategy to develop timely predictive insights through operationalized AI solutions that will drive member engagement and better health outcomes.

Pat Wang
President & CEO, Healthfirst

Our partnership with ClosedLoop adds the depth of AI to more accurately identify those patients who are most likely to benefit from our primary care interventions as well to evaluate these interventions and make more relevant and timely modifications to improve their effectiveness.

David Klebonis
Chief Operating Officer, PBACO

We are extremely impressed with the predictive modeling capabilities the ClosedLoop platform has delivered. The ClosedLoop team has exceeded all defined goals and benchmarks set to date and we anticipate a substantial return on our investment as these predictions are operationally deployed.

Cheryl Lulias
President & Executive Director, MHN

We’re able to store and operationalize analytics directly from ClosedLoop. That’s driving real value—it’s accelerated the implementation of key insights into clinical workflows and it allows us to more easily account for all of the different factors that influence intervention decisions.

Christer Johnson
Chief Analytics Officer, Healthfirst

At SWHR, our patient-centered network is committed to innovative care models that are value-based, high-quality, and data-driven. Because of our partnership with ClosedLoop, we’re better able to identify and act on the most impactful opportunities for our physician partners to improve patient results and reduce unnecessary costs.

Dr. Jason Fish
Chief Medical Officer & SVP, Southwestern Health Resources

We compared the ClosedLoop predicted spend to the spend predicted by a leading rules-based risk prediction engine and found that 75% of the time ClosedLoop was closer, and in most cases significantly closer, to the actual spend.

Phillip Bruns
Chief Technology Officer, CareATC

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