Redpoint for providers
Get Every Patient on the Right Care Path
Run more, better, faster patient acquisition and engagement campaigns with Redpoint.
Data-Driven Healthcare Organizations Trust Redpoint
The Redpoint Difference
Improve patient health – and operating margins – by addressing the root challenges of data accuracy and accessibility. Quickly and easily create effective omnichannel campaigns that keep patients engaged with their health and your system.
Truly Understand Your Patients
Seamlessly bring clinical and consumer data together from disparate sources to create a unified patient profile that supports patient outreach beyond the EHR.
Improve the Health of Patients and Communities
Easily and autonomously segment patient cohorts for targeted value-based programs or specialty procedures that improve health outcomes, patient satisfaction and revenue growth.
Execute Frictionless Patient Journeys
Effortlessly orchestrate and optimize personalized omnichannel campaigns. Engage patients at every stage of their journey to enable better care management and optimize costs.
Provider Use Cases
Expand your patient population, guide individuals to care solutions that best address their needs and keep them engaged to improve health outcomes and increase ROI.
New Patient Acquisition
Prevention & Wellness
Care Gap Closure
Health Equity
Appointment Optimization & Adherence
Patient Retention & Leakage Prevention
Chronic Care Management
Patient Portal/App Adoption
Care Transition & Follow-Up
NPS & Satisfaction Surveys
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In our transformation of marketing, we moved lower down the funnel of finding people that are in need of care now, that have symptoms or concerns, that we can talk to which makes marketing spend more efficient.
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Multi-Billion Dollar Health System
Patient Engagement Resources
Frequently Asked Questions
What is Data Readiness for Providers?
Patient data readiness is a process and methodology for ensuring patient data is right and and fit for purpose across clinical, operational, and engagement use cases. Extending beyond basic data quality, data readiness is a framework for building and activating a unified, longitudinal view of the patient. To do so, it integrates clinical, claims, demographic, social determinants of health, behavioral, and engagement data to support marketing, patient experience, and AI use cases.
For healthcare providers, data readiness enables a deeper understanding of patients and populations, supporting proactive outreach acquisition and retention campaigns, through data that’s contextualized and fit for purpose,. The practice of data readiness extracts maximum value from patient data by ensuring it is complete, accurate, timely, actionable, trusted, secure, and compliant, all within a unified patient profile for healthcare enterprise use.
Why is Data Readiness valuable for healthcare organizations?
Data readiness is valuable because traditional clinical and claims data alone do not provide a complete picture of patients’ status, needs, behaviors, or engagement preferences. By unifying clinical, behavioral, and interaction data into a single, trusted patient view, healthcare organizations gain the context needed to anticipate needs, personalize outreach, and engage patients beyond the exam room. This unified understanding supports stronger patient-provider relationships, builds patient trust, and improves satisfaction and retention. Data readiness also prepares patient information for the healthcare organization’s effective use of AI tools. Only data readiness can turn fragmented patient data into actionable insight that drives hyper personalization and sustainable growth.
I have an Electronic Health Record (EHR or EMR). Why do I need data readiness?
EMR/EHR data quality focuses on whether clinical data is accurate and usable within a specific system, primarily to support documentation, billing, and point-of-care decisions. The practice of data readiness goes further by ensuring all patient, demographic, social determinants of health, and engagement data is complete, accurate, timely, actionable, trusted, secure, and compliant. This contextualized insight then becomes actionable across systems and use cases; it links clinical records with claims, engagement, behavioral, and operational data to create a unified patient view.
While the EHR warehouses data, data readiness determines whether data can be activated to drive patient retention and acquisition campaigns through hyper-personalized engagement, or used to fuel analytics, and AI at scale. The EHR records medical insight; data readiness turns data into strategy.
Do healthcare providers need a Customer Data Platform (CDP) for data readiness?
While many CDPs focus on aggregating data for engagement, data readiness ensures that data is accurate, connected, timely, and fit for use across clinical, operational, analytics, and AI initiatives. Implementing a CDP does not make data ready; without strong data quality, identity resolution, and governance, CDPs can amplify flawed inputs. A strong data readiness foundation can strengthen CDP outcomes by enabling a trusted, unified patient view that can be activated across systems and use cases.
Why is data readiness critical for AI-driven patient engagement?
While AI, machine learning, and predictive analytics can make hyper-personalized patient engagement possible at scale, the data that is fed into AI must be accurate, complete, and fit for purpose. Clean, contextualized data ensures that each touchpoint feels relevant, timely, and human. When data is inconsistent or incomplete, it can quickly derail the experience.
As healthcare organizations adopt AI, data readiness becomes essential. Preparing data for AI requires more than collecting and storing information, it requires a foundation that continuously ensures data is clean, connected, and fit for purpose. This starts with automated data quality processes that cleanse and normalize records as they enter the system. Advanced identity resolution then links patient data across fragmented sources such as EHRs, claims, call centers, and digital interactions.
Once unified, these signals form contextualized patient profiles that integrate clinical, behavioral, demographic, and engagement data, giving AI a complete and trustworthy view of each individual. When activated in real time, these robust patient profiles enable meaningful predictions, autonomous engagement, and smarter decisionmaking across the entire care journey.
