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Learn how AI can help you promote early diagnosis, slow CKD progression, and anticipate and avoid complications and adverse events. See how AI helps to identify people with undiagnosed CKD or at-risk of rapid progression, predict adverse events due to poor medication adherence, predict CKD-related complications (e.g., hyperkalemia), or identify patients who are likely to initiate dialysis in the next year.

Automatically ingest data from dozens of health data sources including...

Electronic Health Records

EHR data with comprehensive patient histories of vital signs and symptoms, problem lists and chief complaints, tests results, diagnoses and procedures, and prescriptions.

Remote Monitoring Data

Remote monitoring data capture key vital signs and health behaviors (e.g. blood pressure, heart rate, blood glucose, activity levels, etc.).

Social Determinants of Health (SDoH)

Geo-centric data with details about the social and environmental influences on people’s health and outcomes.

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ClosedLoop generates explainable predictions using

thousands of auto-generated, clinically relevant contributing factors

Douglas English
67-Year-Old Male
Risk of rapid CKD progression in the next 12 months
Risk Score Percentile
92
Impact on Risk  |  Contributing Factor
Value
+26% | Rise in Blood Pressure (mmHg)
130/85 to 150/100
+17% | Decline in eGFR (mL/min/1.73m2)
48 to 42
+12% | Low Adherence to HTN Medication
0.54
+8% | Pct With Limited Access to Healthy Foods
35%

What Is CKD?

Chronic Kidney Disease (CKD) is a complex condition in which patients experience excessive cardiovascular and other adverse events and carry a heavy burden of morbidity, mortality, and healthcare costs. An estimated 37 million people—15% of adults—have CKD and another 20–25 million are at risk for developing it.¹


And yet, CKD remains under-recognized by providers and patients, especially in its early stages when patients are largely asymptomatic. Nine in ten adults with CKD are not aware of their condition and one in two people with extremely low kidney function do not know they have CKD.¹ Healthcare costs increase dramatically as CKD progresses and in later stages, are five to ten times higher than for someone without CKD.² These costs are primarily due to hospitalizations resulting from severe complications that often accompany reduced kidney function.

Why It Matters

Effective interventions can improve outcomes and reduce healthcare costs. For example, an intervention among beneficiaries of a Maryland health plan reduced hospital admissions by 30 to 45% (depending on CKD stage), readmissions by more than 70%, and costs by 20%.³ To expand the use of value-based programs for CKD, CMS recently announced the Advancing American Kidney Health initiative designed to increase value-based models starting in 2020.⁴ AI-based models are ideally suited to help clinicians and care teams in value-based programs by identifying patients to help promote early diagnosis, slow CKD progression, and anticipate and avoid complications and adverse events.

Did You Know…

  • 660,000 people live with kidney failure⁵
  • 37 million adults in the U.S. have CKD, a number that has doubled each of the last two decades¹
  • 9 in 10 adults with mild-to-moderate CKD are not aware of their condition and 25% of them (who also have diabetes) will experience rapid progression within two years¹
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Citations & Footnotes

1. USRDS. “2016 USRDS Annual Data Report: Epidemiology of Kidney Disease in the United States.” National Institutes of Health, National Institute of Diabetes and Digestive and Kidney Diseases, 2016. United States Renal Data System. 2016 USRDS annual data report: Epidemiology of kidney disease in the United States. National Institutes of Health, National Institute of Diabetes and Digestive and Kidney Diseases, Bethesda, MD, 2016. 

2. Golestaneh, Alvarez L., et al. “All-Cause Costs Increase Exponentially With Increased Chronic Kidney Disease Stage.” The American Journal of Managed Care, vol. 23, no. 10 Suppl, 2017, pubmed.ncbi.nlm.nih.gov/28978205/. Accessed 5 June 2020. 

3. Vassalotti JA;DeVinney R;Lukasik S;McNaney S;Montgomery E;Voss C;Winn D. “CKD Quality Improvement Intervention With PCMH Integration: Health Plan Results.” The American Journal of Managed Care, vol. 25, no. 11, 2019, pubmed.ncbi.nlm.nih.gov/31747237/. Accessed 5 June 2020. 

4. “HHS To Transform Care Delivery for Patients with Chronic Kidney Disease | CMS.” Cms.Gov, Centers for Medicare & Medicaid Services, 10 July 2019, www.cms.gov/newsroom/press-releases/hhs- transform-care-delivery-patients-chronic-kidney- disease#:~:text=Today%2C%20delivering%20on%20President%20Trump’s,Medicare%20and%20M edicaid%20Innovation%20payment. Accessed 5 June 2020. 

5. National Institute of Diabetes and Digestive and Kidney Diseases. “Kidney Disease Statistics for the United States | NIDDK.” National Institute of Diabetes and Digestive and Kidney Diseases, 9 Mar. 2021, www.niddk.nih.gov/health-information/health-statistics/kidney-disease. Accessed 5 June 2020.

6. Go, Alan S., et al. “Contemporary Rates and Predictors of Fast Progression of Chronic Kidney Disease in Adults with and without Diabetes Mellitus.” BMC Nephrology, vol. 19, no. 1, 22 June 2018, bmcnephrol.biomedcentral.com/articles/10.1186/s12882-018-0942-1#ref-CR31, 10.1186/s12882- 018-0942-1. Accessed 30 Apr. 2020.

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
Cheryl

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 amount to the Johns Hopkins ACG predicted spend amount and found that 75% of the time ClosedLoop was closer, and in most cases significantly closer, to the actual spend amount.

Vickie Rice
Senior Vice President of Strategic Analytics, CareATC

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