Predictive Prevention is designed to work with longitudinal health information from multiple available sources. Depending on an organization’s infrastructure and program, these may include EHR data, claims, clinical registries, medication information, patient-reported information, remote patient monitoring, connected devices, wearables, behavioral data, and social determinants of health.

Bringing relevant information together can provide a more complete view of the patient and help organizations identify meaningful changes that may warrant additional attention, engagement, or clinical review.

No. Predictive Prevention is designed to complement the healthcare technology infrastructure organizations already depend on. Rather than replacing the EHR or other core systems,

Calcium can provide a prevention layer that connects available patient information with predictive intelligence, prioritized workflows, and ongoing digital engagement. This helps extend the value of existing data and systems beyond documentation and risk identification, creating a more direct connection between what an organization knows about a patient and what happens next.

Healthcare organizations often manage populations too large for every patient to receive the same level of manual attention. Predictive Prevention helps translate available risk intelligence into actionable priorities. Patient populations can be segmented according to defined risk, urgency, clinical criteria, or program requirements, helping create more focused care-management workflows.

Intelligent work queues, alerts, and escalation processes can then help care teams identify where human attention may be appropriate and concentrate resources on patients with emerging or higher-priority needs.

The framework is designed to use automation for routine activities while directing clinical resources toward interactions where human expertise matters most. Personalized Digital Pathways can support education, reminders, assessments, monitoring, behavioral guidance, and routine patient engagement without requiring manual outreach at every step.

At the same time, prioritization and escalation workflows can help teams focus attention on patients requiring additional support. This creates an opportunity to scale proactive care without relying solely on proportional increases in clinical staffing.

Identification is intended to trigger an appropriate next step rather than simply generate another score or dashboard notification. Depending on the organization’s configured workflows, a patient may receive a personalized Digital Pathway, assessment, reminder, educational content, monitoring request, or other guided intervention.

Higher-priority signals can also support escalation to care teams for review and follow-up. The objective is to create a structured connection between emerging risk, patient engagement, and appropriate human intervention when it is needed.

Digital Pathways provide the patient engagement and intervention layer of the Predictive Prevention Framework. They can guide patients through personalized sequences of education, assessments, reminders, health tracking, behavioral support, and other program-specific activities between traditional encounters.

Pathways also create opportunities to capture new patient-generated information throughout the journey. This helps transform prediction into an ongoing process in which patients remain engaged while care teams gain additional visibility into changing needs, behaviors, symptoms, and potential risk signals.

The framework operates as a repeating cycle rather than a one-time risk assessment. Calcium helps organizations Assess available health information, Predict emerging risk, Prioritize patients who may need attention, and Prevent through guided digital or care-team interventions.

As patients engage, new information can become available for subsequent assessment, allowing the cycle to begin again. This feedback loop helps organizations maintain a more current understanding of patient needs instead of relying exclusively on episodic encounters or static risk snapshots.

Yes. The framework is designed as a flexible operating model rather than a single-condition solution. Organizations can apply its assess-predict-prioritize-prevent approach across programs such as chronic disease management, population health, perioperative care, post-acute care, behavioral health, and other preventive initiatives.

Digital Pathways can be configured around specific populations, conditions, and care journeys, enabling health systems to establish a common prevention infrastructure while adapting patient engagement and clinical workflows to different program requirements and organizational priorities.

Value-based care increases the importance of understanding patient risk and acting before avoidable deterioration becomes more difficult or costly to address. Predictive Prevention can help organizations connect population-level risk intelligence with prioritized outreach, ongoing patient engagement, and structured interventions.

This approach can support capabilities important to accountable care, including chronic disease management, transitions of care, rising-risk management, preventive engagement, and longitudinal population management—helping organizations build infrastructure aligned with greater accountability for patient outcomes, utilization, quality, and total cost of care.

Calcium extends engagement into the periods when patients are managing their health outside hospitals and clinics. Through the Calcium Super App and personalized Digital Pathways, organizations can deliver education, reminders, assessments, health tracking, symptom questions, behavioral guidance, and other targeted activities.

Patients can receive support throughout their care journey while generating information that may provide additional insight into changing needs. This creates a more continuous connection between the patient and healthcare organization than encounter-based care alone can provide.

AI can support several elements of the framework, including risk intelligence and the efficient creation of personalized Digital Pathways. Calcium AI Studio helps healthcare organizations develop and manage pathway content, assessments, education, monitoring activities, reminders, and guided engagement experiences.

AI is intended to support scalable healthcare workflows rather than replace professional clinical judgment. Organizations can establish appropriate clinical, operational, and governance processes around how predictive insights, pathway content, escalation criteria, and patient interventions are implemented within their specific care environments.

Implementation can be designed around the workflows, populations, and priorities of each healthcare organization. Rather than requiring every patient interaction to become a new manual task, the framework combines automated digital engagement with risk-informed prioritization and defined escalation processes.

Care teams can focus on patients requiring their expertise while lower-intensity activities can be supported digitally. This approach allows organizations to incorporate proactive prevention into existing care-management models while configuring workflows around their staffing structures, clinical protocols, and operational requirements.

A practical starting point is a clearly defined population and use case where earlier intervention has meaningful clinical or operational value. The organization can identify relevant data sources, risk signals, target workflows, patient engagement requirements, escalation criteria, and measurable objectives.

Calcium can then support the connection of data, prioritization workflows, and Digital Pathways around that program. Starting with a focused implementation also gives organizations an opportunity to evaluate performance, refine workflows, demonstrate value, and expand to additional populations over time.

Measurement should begin with objectives established for the specific population and use case. Organizations may evaluate operational measures such as engagement, pathway participation, outreach efficiency, escalations, and care-team workload alongside appropriate clinical, quality, utilization, and financial measures.

The relevant indicators will vary by program and population. Establishing baseline performance and clearly defined success measures before deployment can help organizations determine whether Predictive Prevention is improving workflows, influencing patient engagement, and contributing to the outcomes their programs are designed to achieve.