Penn Medicine
$16.1M
Annualized financial impact at a single site.
- 7,281
- Bed-days saved
Care that sees ahead.
HealthLeap is the AI platform that surfaces at-risk inpatients earlier — starting with malnutrition, the most under-captured condition in the hospital.
The current state is unacceptable.
- up to 50%
- of inpatients are at risk of malnutrition
- <9%
- are diagnosed
- ~5,500
- malnourished patients missed per year at a typical 1,000-bed hospital
- Cedars-Sinai
- Emory
- Houston Methodist
- Intermountain
- Northeast Georgia Health System
- Penn Medicine
- UMass Memorial
Screen all inpatients daily.
- Scans every chart
- Every adult, every day
- Scores each patient
- Risk score written into the EHR
- Improves CDI & CDS
- Upstream identification — at admission or during the stay
HealthLeap analyzes every adult inpatient's chart each day and writes a nutrition-risk score into the EHR flowsheet each morning. The registered dietitian's routine doesn't change — but instead of chasing false flags, the day starts with the highest-acuity patients already at the top of the list. HealthLeap sits upstream of CDI, closing the identification gap that comes before it.
Scored and sorted by severity of nutrition risk.
Each morning, every adult inpatient is scored and sorted by nutrition-risk severity, written straight into the dietitian's EHR flowsheet. The sickest patients sit at the top of the list, not buried in chart review.
Today's priority list
- 10.94
Bed 7B
64 F · 4 days LOS
- 20.89
Bed 3A
71 M · 2 days LOS
- 30.81
Bed 12C
58 F · 6 days LOS
- 40.76
Bed 9D
47 M · 1 day LOS
Upstream of CDI & CDS.
HealthLeap identifies at-risk patients on day one, before CDS and CDI workflows can engage. We don't replace them; we feed them a cleaner, earlier signal.
Patient admitted
Risk isn't continuously captured and surfaced.
HealthLeap identifies risk
Daily prioritization, written into the EHR.
CDI & CDS engage
Existing investment, fed an earlier signal.
Reimbursement & quality capture
Severity, LOS, and incremental revenue follow.
- 01
The only peer-reviewed
To our knowledge, HealthLeap offers the only commercially available, peer-reviewed AI malnutrition screening tool, validated against the clinical reference standard. 166k+ admissions over 3.75 years. Detects patients 88% more often than the modified MST, a median of 1.5 days before first dietitian documentation. Bernstein et al., Applied Clinical Informatics. AUROC 0.92 rising to 0.95.
- 02
A system, not just technology
We wrap our founder AI model in on-the-ground services that turn the signal into outcomes: implementation, change management, and outcomes accountability.
- 03
Malnutrition is the start
Malnutrition is the first condition, not the last. The same daily, EHR-native screening extends to the conditions hospitals struggle to capture in time — aspiration pneumonia, heart-failure readmissions, and more.
Validated against the clinical reference standard.
Co-authored research with leaders from Cedars-Sinai, Johns Hopkins, and Stanford, and published in Applied Clinical Informatics. To our knowledge, HealthLeap offers the only commercially available, peer-reviewed AI malnutrition screening tool.
- 88% higher sensitivity
- Than the nurse-administered malnutrition screening
- 4 days earlier identification
- Of patients with malnutrition
- 0.95 AUROC
- during stay; 0.92 on day one
Cedars-Sinai
$11M
Annual impact.
- 39%
- More diagnoses, same staffing
Every 1,000 additional reimbursable malnutrition cases captured is roughly $5M in incremental reimbursement.
Malnutrition is the first condition.
The same daily screening intelligence we use for malnutrition is already being extended to other conditions that hospitals consistently struggle to identify early and address in time.
Malnutrition
Daily, EHR-native risk identification, validated against the clinical reference standard.
Delirium & Toxic Metabolic Encephalopathy
Daily, EHR-native identification designed to surface patients who may otherwise be missed.
Aspiration pneumonia
Identifying patients at elevated aspiration risk before complications develop.
Congestive heart failure readmissions
Flagging the patients most likely to return before they leave.
Pressure injuries
Earlier identification of at-risk patients for prevention protocols.
Close gaps. Improve care. Strengthen margins.
- Measurable incremental reimbursement, contractual ROI floor.
- Measurable improvement in O:E ratios, length of stay, and severity capture.
- Prioritize the highest-risk patients, not false flags
“The AI in HealthLeap stands for actionable insights.”
See what you've been missing.
HealthLeap helps leading health systems find malnutrition-risk inpatients earlier than admission screening, using peer-reviewed daily EHR-based prioritization — with measurable impact on reimbursement, length of stay, and severity capture.