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Learn how AI can help HCOs to promote early identification of patients at-risk for readmission, improve care transition planning, and avoid post-discharge complications and adverse events. Discover how AI can help predict which patients are at the highest risk, ensure medication reconciliation to prevent adverse drug events, and identify patient care and PCP follow-up needs at discharge.

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

ADT Records

Data from Admit, Discharge, and Transfer feeds and patient data notification services that synchronize patient demographic, diagnostic, and visit information across healthcare systems.

Rx Claims

Data extracted from health insurance pharmacy claims with details about each medication and its type, fill dates, days supply, pharmacy location, and prescribing clinician.

Social Needs Assessments

Self-reported data that identify an individual's specific needs and the acute social and economic challenges they are experiencing.

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ClosedLoop generates explainable predictions using

thousands of auto-generated, clinically relevant contributing factors

David Hunt
71-Year-Old Male
Risk of being readmitted to the hospital in the next 30 days
Risk Score Percentile
Impact on Risk  |  Contributing Factor
+26% | Admissions for CHF (1M)
+18% | Decrease in Medication Adherence (12M)
75% to 50%
+14% | # of Changes in Medication Regimen @ Discharge
+10% | Levels of Caregiver Support

What Are Readmissions?

According to CMS, a readmission occurs when a patient is readmitted to the same or another acute care facility within 30 days of an initial hospital stay.  Annually, adult patients experience 4.2 million hospital readmissions in the U.S., and among Medicare beneficiaries, one in six are readmitted within 30 days of discharge.¹𝄒²  For older adults with functional impairments, the risk of readmission rises substantially and is 40% higher than the risk for a Medicare patient with no functional impairments.³

Why It Matters

Readmissions are expensive. Hospital readmissions cost Medicare $26 billion annually with costs for readmissions of commercial payers and Medicaid beneficiaries amounting to $8.1 billion and $7.6 billion, respectively.⁴ They are also expensive for hospitals.  CMS imposes a penalty on hospitals with excessive Medicare readmissions as part of the Hospital Readmissions Reduction Program (HRRP) and in 2019, penalized 2,583 hospitals $564 million for excessive 30-day hospital readmission rates.⁵ 

The conditions that contribute most to readmissions differ for Medicare, commercial payers, and Medicaid, and the first step to managing them is identifying patients with these conditions who are the most likely to be readmitted.⁶  This also involves pinpointing any other reasons that patients might return to the hospital, which can include inadequate caregiver support, housing instability, food insecurity, or other social determinants of health. Using these insights to proactively work with patients, care teams can better plan transitions from hospital to home.  When successful, such programs have been able to reduce readmissions by 34%.⁷

AI Presents an Opportunity

Predictive analytics and AI can help healthcare organizations (HCOs) conduct successful care transitions, improve patient outcomes, and achieve their readmission reduction goals.  AI-based models can help care teams identify high-risk patients, establish post-discharge PCP visits, ensure medication reconciliation to prevent adverse drug events, and provide appropriate support for patients with functional limitations. Bolstered by AI, such efforts can profoundly improve patient health outcomes and lower costs.

Did You Know…

  • $14,400 is the average cost of a readmission¹
  • 83% of general hospitals evaluated in the HRRP (Hospital Readmissions Reduction Program) during financial year 2020 were penalized by CMS for higher than expected readmission rates⁵
  • 40% of patients are discharged with pending test results⁸

Citations & Footnotes

1.  Bailey, Molly K., et al. “Characteristics of 30-Day Readmissions, 2010-2016. Healthcare Cost and Utilization Project—Statistical Brief #248.” Agency for Healthcare Research and Quality, Feb. 2019. Accessed 13 Dec. 2020. 

2. “All-Cause Admissions and Readmissions 2017 Technical Report.” Department of Health and Human Services National Quality Forum, Sep. 2017. Accessed 14 Dec. 2020. 

3. Greysen, S. Ryan, et al. “Functional Impairment and Hospital Readmission in Medicare Seniors.” JAMA Internal Medicine, vol. 175, no. 4, 1 Apr. 2015, pp. 559–565, doi:10.1001/jamainternmed.2014.7756. Accessed 12 Mar. 2021.

4. LaPointe J. 3 Strategies to Reduce Hospital Readmission Rates, Costs. RevCycleIntelligence. https://revcycleintelligence.com/news/3-strategies-to-reduce-hospital-readmission-rates-costs. Published January 8, 2018. Accessed March 23, 2021.

5. Rau, Jordan. “New Round of Medicare Readmission Penalties Hits 2,583 Hospitals.” Kaiser Health Network, Oct. 2019. https://khn.org/news/hospital-readmission-penalties-medicare-2583-hospitals/. Accessed 14 Dec. 2020. 

6. Hines, Anika L., et al. “Conditions with the Largest Number of Adult Hospital Readmissions by Payer, 2011. HealthCare Cost and Utilization Project—Statistical Brief #172.” Agency for Healthcare Research and Quality, Apr. 2014. Accessed 13 Dec. 2020.

7. Kemp KA, Quan H, Santana MJ. Lack of Patient Involvement in Care Decisions and Not Receiving Written Discharge Instructions Are Associated with Unplanned Readmissions up to One Year. Patient Experience Journal. 2017;4(2). Accessed March 23, 2021. https://pxjournal.org/journal/vol4/iss2/4/

8. Roy, Christopher L., et al. “Patient safety concerns arising from test results that return after hospital discharge.” Annals of internal medicine vol. 143, no. 2, Jul. 2005, pp: 121-128. DOI:10.7326/0003-4819-143-2-200507190-00011.

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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