Managing relationships & affiliations
As we noted, understanding affiliations and relationships of clinicians and other healthcare professionals with other providers and provider organizations is important. Modern data management platforms leverage graph technology to help with discovering and presenting the provider’s relationships with other data entities such as healthcare organizations, plans, specialties, and patients and provides the foundation with reliable data and relationships that can be used for analytics or visualized in the form of various data-driven applications.
Quick business value with data driven applications
Once a reliable data foundation is established with continuous data quality management, it can be visualized in consumer grade applications. Business teams can confidently use data driven applications to segment providers based not only on location and specialty but any attribute available. Analytics and visualizations are built into data driven applications, delivering relevant insights that align with the objectives of the business user, reducing the “hunt and peck” required by standalone do-it-yourself business intelligence and analytical-only tools. Leveraging predictive analytics and machine learning, data-driven applications provide intelligent recommended actions guiding users to make informed decisions.
Approach to improving provider data quality
Proper data management will continually review data for creeping loss of integrity, and provide data-driven applications that recognize the context of the inquirer to respond with the most appropriate data values. Customer satisfaction depends on this information being accurate, available, and relevant.
Managing provider data in all its forms is a discipline in itself requiring a blend of people, process, and technology. A payer desiring to improve the quality and relevancy of its provider data should actively engage in the following steps:
1. Improve data intake:
a. Ensure your organization is capturing information from all input channels: master data, reference data, transaction, interaction and social data in a single unified view.
b. Reduce data latency and improve integrity.
2. Ensure a single source of the truth and contextualization to ensure downstream systems and applications are fed reliable and relevant data.
3. Appropriate platform design to ensure quick connectivity with other applications in the eco-system, easy onboarding of internal and third-party data, and agility, scalability, and elasticity to grow with user needs.
4. Engage MDM methods and best practices for end-to-end management and governance of the provider data lifecycle, including related reference data.
5. Automate business rules and workflow processes to manage data change requests and approvals.
6. Analyze for insight such as practice patterns, utilization, costs, outcomes, network capacity, capability, and fitness to the membership base.
A technology platform that accurately and efficiently collects, consolidates, masters, and shares provider data from all contributing sources is critical to ensuring this process is consistently being executed, managed, and measured – at enterprise scale. A modern provider data management platform ensures that standards for data governance and stewardship are being applied uniformly and in a sustainable manner.
A best-in-class modern provider data management platform should meet the following minimum criteria:
- Cloud-based PaaS - Offers lower total cost of ownership, quicker time to value, and operational flexibility. Supports both structured and unstructured data at any volume and scale. Blends and relates multi-domain master data, reference data, transactions, omnichannel interactions and social data into a single unified view.
- Strong master data management - Collects, consolidates, enriches, and manages provider data from multiple internal and external sources.
- Managing relationships - Data architecture should handle complex connections, hierarchies and relationships between multiple domains to understand affiliations among providers, plans, and HCOs.
- Data stewardship, transparency, and lineage - Complete data lineage, granular audit trails and structured workflows with reviews and approvals for data change requests ensures required transparency and compliance.
- Collaborative curation - Business users, data owners, and data stewards should be able to easily collaborate and contribute towards data quality. Capabilities like discussion threads and voting available within data-driven applications allow the teams to continuously improve the data quality.
- Search - Quick searches across all domains and across all profile attributes allow users to easily find the right profiles.
- Flexibility and scalability - To easily incorporate new information sources, expanded data sets, or support additional use cases to provide a full 360º provider view.
- Interoperability - With existing enterprise systems.
- Advance analytics - To improve data quality as well as derive relevant business insights and recommend intelligent actions.
- Information security - As evidenced by certifications like HITRUST CSF.
Adoption, deployment and sustainment
Many traditional data management initiatives have failed to deliver the promised results. A modern approach offers the opportunity to apply best practices and key learnings to adoption,deployment, and sustainment to ensure value is achieved and enhanced over time:
- Align investment with business value - Avoid large up-front capital investments. Cloud-based Software-as-a-Service based approaches offer maximum flexibility to achieve results cost-effectively. Cloud-based solutions allow for innovation while avoiding internal resource and infrastructure investments and constraints.
- Be agile - Focus on delivered business value, deliver in small increments, get feedback, and iterate. Time to initial delivered value should be measured in weeks, not months.
- Define, measure, and monitor throughout - Evolve from simple to sophisticated.
- Business participation and business/IT collaboration is crucial. Ownership must be shared and the business must be empowered.
- Leverage external skills and expertise to avoid pitfalls but make self-sufficiency a goal!
A comprehensive overview of best practices is outside the scope of this paper but the authors and their respective organizations can review these with organizations considering this type of program.
A robust provider MDM program supported by a modern provider data management platform allows healthcare enterprises to reap multiple organizational benefits:
- Improved operational performance: Efficiency, effectiveness, consistency, and lower costs
- Improved provider directory accuracy
- Improved quality of care
- Enhanced business agility
- Compliance and regulation