Predictive Intelligence for the Inpatient Setting
With hundreds of outcome-specific predictive models embedded directly into the EHR, HealthVision™ helps care teams identify risk earlier, find missed diagnoses that need attention, reduce readmissions and mortality rates, support seamless transitions, and connect more patients to goal-concordant care. All this while ensuring optimized impact from your busy internal and contracted staff and resources.
Early Results from Health System Implementations
Turning Buried Data into Action
A small percentage of patients account for a disproportionate share of adverse events, readmissions, and cost, but they're not always the ones who appear highest risk in the ED or at bedside. Nationally, even top-performing academic medical centers follow up with fewer than half of their highest-risk patients after discharge. HealthVision surfaces the patients who need attention now, ranked by outcome-specific risk, directly inside your existing EHR, leveraging existing clinical resources into measurably better quality and revenue outcomes.
Need
Prevent avoidable readmissions
Readmissions are lower in high-risk patients seen within 14 days of discharge. But, strapped for time, care teams frequently rely on clinical judgment alone to assess who to prioritize for the available specialist and PCP appointments. Each preventable return takes up a bed that someone else might need and may incur a CMS penalty risk.
Solution
In real-time, prioritize appointments for impactable patients
Risk-sorted lists of patients, viewable within the chart, enables schedulers, case managers, hospitalists to assess post-discharge care needs—before they transition to next site of care.
Solution
In real-time, prioritize appointments for impactable patients
Risk-sorted lists of patients, viewable within the chart, enables schedulers, case managers, hospitalists to assess post-discharge care needs—before they transition to next site of care.
Need
Optimize existing clinical resources to match patient needs
Your care teams are making critical decisions with limited real-time visibility leading to preventable readmissions, longer lengths of stay, and avoidable costs. The information exists in the EHR. It’s just not delivered where and when it’s needed.
Solution
Real-time Risk Rosters and Patient Summaries
Rank-ordered patient lists, driven by condition-specific models and customized for specific users and specialties, uncover the highest risk patients, along with the key contributing factors so clinicians can address the need rather than digging through the chart to figure out why the patient is on the list.
Solution
Real-time Risk Rosters and Patient Summaries
Rank-ordered patient lists, driven by condition-specific models and customized for specific users and specialties, uncover the highest risk patients, along with the key contributing factors so clinicians can address the need rather than digging through the chart to figure out why the patient is on the list.
Need
Proactive discharge planning to reduce LOS and readmissions
Decisions around follow-up care, discharge destination, and post-acute support are often made without a complete picture of patient risk. That fragmentation can lead to last-minute scrambles that delay transitions and increase cost.
Solution
Predict discharge destination and resource needs
Highly specific risk thresholds guide enrollment of eligible patients into programs like TCM, CCM, and RPM to support continuity after discharge.
Solution
Predict discharge destination and resource needs
Highly specific risk thresholds guide enrollment of eligible patients into programs like TCM, CCM, and RPM to support continuity after discharge.
Need
Earlier care planning for patients with advanced illness to reduce inpatient mortality
Many patients are first identified for advance care planning during a crisis, when families are overwhelmed, patient goals of care are buried in the chart, and treatment options have narrowed.
Solution
Predict risks and summarize goals of care
90-day hospice and mortality risk models identify patients with serious illness before a crisis forces the conversation. AI-generated summaries surface each patient’s expressed wishes, fears, and understanding of their prognosis, so care teams can engage earlier with a personalized plan, at measurably lower inpatient costs.
Solution
Predict risks and summarize goals of care
90-day hospice and mortality risk models identify patients with serious illness before a crisis forces the conversation. AI-generated summaries surface each patient’s expressed wishes, fears, and understanding of their prognosis, so care teams can engage earlier with a personalized plan, at measurably lower inpatient costs.
Areas of Impact
Readmission Prevention
Identify patients at the highest risk of 30-day readmission at the point of discharge. Condition-specific models for cardiac, pulmonary, and surgical populations surface the interventions most likely to keep patients safely at home.
- Condition-specific readmission risk at the point of discharge
- 7-day and 30-day follow-up scheduling prioritized by risk level
- Top contributing factors surfaced for each patient
- Service line targeting across medical and surgical populations
- Post-discharge mortality risk for highest-acuity patients
- Embedded directly within the EHR
“Teams became much more engaged because they felt like they could make an impact. We were getting the patients who needed clinic time scheduled earlier post discharge and focusing our resources where they mattered most.”
Brenda Campbell
Senior Consultant, Health Systems Innovations
Houston Methodist
Who We Help
Multi-Hospital Health Systems
Medium to Large (>500 bed) Hospitals
Academic Medical Centers
Community Hospitals
Accountable Care Organizations
Deliver Better Outcomes with Earlier Insight
See how real-time risk intelligence can reduce readmissions, improve transitions, and support better clinical decisions.