Whether your organization provides healthcare directly, or supports patients and providers in the larger medical and insurance ecosystem, the rapid expansion of patient data and new technologies (including AI) that leverage it create an unprecedented opportunity to serve patients and optimize outcomes.
What makes data-driven healthcare journeys challenging and important
on one side: Discuss the challenging regulations related to the use of PHI and the need for BAA in the technology ecosystem.
on the other hand: Talk about the real-world implications of reaching the right members with the right messages at the right time.
- This isn’t just marketing to sell a product – it’s important communication that can change patients’ perspective on their health and wellness.
- You have the opportunity to engage more closely with patients to drive better outcomes while achieving key performance metrics like HEDIS and eCQMs.
Patient-centered care is the concept of meeting a person right there and taking appropriate activities to achieve the best possible outcome for that person. The ability to personalize care is supported by data-driven decisions – but these efforts often fall short due to some major challenges in health care.
The first is that although there is a lot of emphasis on interoperability on the CMS side (for example). CMS Health Tech Ecosystem And Interoperability and Patient Access Rules), systems of record do not include all patient-related information, creating a gap in data-informed decision making. Specific HIPAA rules around PHI and the need for BAA-regulated tools to collaborate are making interoperability more complex.
More nuanced than data interoperability are the practical challenges of reaching the right members with the right message at the right time. Unlike marketing in other industries, which may focus on selling specific products, health care outreach is about using information intelligently to directly address a member’s health and well-being. There is an opportunity to connect more deeply with patients and members and partner with them to live healthier lives. This engagement also helps health plans and providers improve key performance metrics such as HEDIS, STARS and eCQM.
Activating the right message at the right time presents another challenge. What means of communication should you use, and how should you measure response and effectiveness? For most health care organizations, a single platform does not solve every permutation of outreach, so non-technical teams often need to coordinate across multiple systems.
How composable CDPs work for health care
A composable CDP is a HIPAA Compliant Engagement layer based on your data.
- It allows you to create a complete patient profile in the data warehouse to empower your patient communications and interactions by separating data warehouse operations and outreach operations.
- Composable CDP 101: :
- Data lives in Databricks
- HiTouch provides modules for collecting data in Databricks; Integrate it into the overall member profile; Activate it on approved/compliant channels.
Data access and usage is excessive under in databricks
- Data resides in your cloud storage managed by Databricks
- PHI can be hidden and managed at a micro level by row, column or attribute tagging (see) attribute based access control)
- Controls ensure that only the right people access data
- Controls ensure that permitted data flows only to approved BAA-signed tools in your ecosystem
Patient and member service teams can self service Within your governed parameters at HiTouch
- Create segments and evergreen journeys based on specific signals from member journeys
- Analyze segment structure and adjust immediately
- Take action on those segments/visits/triggers
- Lifecycle Teams: Send emails, phone calls, text messages and more
- paid media teams: Start ad campaigns, stop ads to existing or recurring users
- digital teams: Personalize websites and mobile apps in real time, show relevant messages and offers
- the most important thing: You can create a single segment or journey that spans all of these teams and touchpoints. Make sure your members have a consistent experience across every channel.
- Use AI agents and AI decision making to automate and scale these interactions, becoming even more personalized for each user
- Analyze each campaign’s results, progress through visits, and more from that source of true data
Composable CDP (Customer Data Platform) is a common approach to data-driven decision making that empowers action. It is designed to solve the above challenges by leveraging your data as the primary driver and basis for insights and decision making, and operates upstream from the points of interaction and activation with customers. This allows organizations to take full advantage of the strength of their data foundation to power all their downstream customer interactions.
For many healthcare organizations, Databricks serves as the enterprise data platform of choice. Built on the Lakehouse architecture, it integrates the capabilities of a traditional data warehouse and business intelligence with the advanced AI, machine learning, and real-time processing of a data lake under a single platform. Data is stored within the organization’s cloud tenant, with governance enforced through enterprise security groups to support HIPAA compliance Secure, role-based access. Capabilities like dynamic row- and column-level masking enable teams to operate from a single source of truth while protecting sensitive PHI and PII.
With data secure and appropriate role-based access controls, composable CDPs like HighTouch run on Databricks to enable business users self service Through data access and use AI/BI Genie. These teams can create (and measure, and then adjust) group and evergreen journeys based on specific member journey signals. Then, they can trigger actual customer communications in downstream tools based on those customer signals. Lifecycle marketing teams can create key groups, such as “patients who are scheduled for an annual physical,” and initiate communications across channels such as email, phone, and SMS. Paid media teams can upload groups to advertising platforms to launch new advertising campaigns or push ads to existing members. Digital teams can use their composable CDPs to personalize websites and mobile apps in real-time, showing relevant offers or messages to each visitor. And, most importantly, these teams can create a single group or journey that spans all of these channels to ensure members have a consistent experience across every touchpoint.
And sure, AI can speed up all of these marketing workflows, but it’s extremely important that it’s properly controlled to prevent negative (or in the case of health misinformation, even dangerous) member experiences. high touch Agent Marketing Platform It starts with enabling marketers to analyze their data in Databricks, make suggestions, and create segments and journeys faster than ever with a simple workflow. This goes on to create content for advertising and lifecycle marketing campaigns that is driven with full reference to each brand’s style and needs, while ensuring that humans are the final approvers before anything reaches members. And AI decision making You can automatically choose which message, channel and time to deliver to each member to maximize business-defined results while working within your scope.
Example Use Cases for Data-Driven Customer Engagement
New Patient Acquisition (Payment Channel)
- Known target audience (e.g. people new to an area without PCP) and lookalike audiences
- efficiency lever
- Suppress audiences (stop advertising to existing customers)
- Conversion API to provide signals for ad effectiveness
- Measure incrementality of ad campaigns
Drive customer engagement at key moments in their lifecycle
- appointment reminder
- Referral for preventive screening (“You are scheduled to have a colonoscopy”)
- Reminders about taking and refilling medications
Evergreen/Active Member Health Management Trips
- Example: Customers are sent recommended readings based on their health history
- Examples: ongoing flow for managing a chronic condition such as diabetes, or for an ongoing program such as weight management while taking GLP-1
- Example: care sequence after surgery
- Example: maternity care order
Sync key patient and medication data across operational systems to determine cost savings
- For example: Identify drugs that may be excluded from the policy, and identify lower-cost alternatives
Your organization can start with simple, automated communications that have a positive impact on patients, like appointment reminders, medication pickup or refill notifications, and screening checkpoints. Use cases like this help lay the foundation for more complex workflows and potentially greater impact down the road.
Where a composable CDP clearly provides an advantageous approach is in more complex workflows for episodes of care such as pregnancy, and the management of chronic conditions such as diabetes and hypertension, as well as for programs such as behavioral health and weight management. These programs require a more sophisticated approach with a high level of individualization and flexibility that takes into account the nuances of each patient’s medical history and preferences. Special attention should be given to these programs because of the critical nature of the care needed and the limited resources available from health plans and providers to support them. Using your data and AI, and empowering outreach teams with self-service data access, helps them maximize impact.
conclusion
Many organizations are active in connecting with patients outside the clinical setting. A composable CDP extends these capabilities by giving organizations self-service capabilities to access and leverage their data across channels from their central source of truth—patient data in Databricks. This approach allows organizations to move faster, create communications more flexibly across multiple channels, and better engage patients and members based on their preferences and history. Explore more by getting in touch today.
