A fundamental part of developing capitation rates for risk-based managed care programs is the selection and usage of historical data to be used as the base data.1 Relative to other sources of data that may be used in developing capitation rates—summarized managed care entity (MCE) utilization and cost experience, fee-for-service data, statutory financial statements, etc.—encounter data provides the most transparent view of an MCE's provision of healthcare services. Encounter data is also the basis for many other required activities resulting from managed care programs, including risk adjustment, quality measurement, value-based purchasing, program integrity, and policy development.
However, encounter data that is incomplete, missing information, or reported incorrectly can render the data of limited use in evaluating an MCE’s financial experience and delivery system performance. Recognizing that quality encounter data is imperative in creating greater transparency in Medicaid managed care programs, the Centers for Medicare and Medicaid Services (CMS) has made ensuring encounter data quality a high priority for states and MCEs. Guidance prior to the release of the final managed care rule (final rule) required an actuary certifying managed care rates to document how base experience used in the rate development process was validated for completeness, accuracy, and consistency across data sources.2 The final rule provides a comprehensive modernization of Medicaid managed care rules and regulations, including addressing encounter data quality and submission requirements in detail.3 Additionally, the final rule permits financial penalties for poor encounter data quality, in the form of withholding federal financial participation (FFP) from states that do not comply with new standards.
In this article, we summarize new regulatory requirements for Medicaid encounter data from the final rule, identify best practices for state Medicaid agencies and MCEs in the development and submission of encounter data, and envision how improvements to Medicaid managed care encounter data quality may change the industry.
Summary of regulatory requirements
The table in Figure 1 summarizes key new standards for encounter data from the final rule. We focus on five issues: provider entities required to submit encounter data, encounter data submission elements, quality control, noncompliance penalties, and the applicability period.4
|Figure 1: Summary of Regulations on Encounter Data|
|Provider entities required to submit encounter data||
|Encounter data submission elements||
The final rule addresses several encounter data issues that we observe frequently in our work with state Medicaid agencies and MCEs:
- Sub-capitated providers and alternative payment arrangements. Encounter data for sub-capitated providers, particularly for ancillary services such as nonemergency transportation, are more likely to be incomplete or inaccurate in submissions to state Medicaid agencies. The final rule makes no exceptions for encounter data associated with sub-capitated providers, which will require MCEs to work with sub-capitated entities to ensure compliance with the new requirements. Similarly, managed care systems using alternative payment arrangements, such as bundled payments or episode-based payments, are not exempt from encounter data submission requirements. While MCEs may be moving away from fee-for-service provider reimbursement, this does not negate the need for complete and accurate encounter data reporting.
- Variance in state encounter data quality processes. The current capabilities of state Medicaid programs in evaluating encounter data quality vary significantly, with some states having already established processes and internal expertise to monitor and assess encounter data quality, while other states are just now developing encounter data quality protocols (many of these differences may be a result of when risk-based managed care was implemented in the state). CMS requirements in the final rule will incentivize, through noncompliance penalties, all state Medicaid managed care programs to submit data in a standardized format, which should aid CMS in evaluating the efficiency and operation of managed care delivery systems across the country. Likewise, MCEs should anticipate additional oversight, monitoring, and noncompliance penalties associated with their collection and submission of encounter data to state Medicaid agencies.
- State innovation in encounter data quality improvement. While CMS will require data encounter data submitted in a standardized format, it does not define how states will validate if encounter data is complete and accurate prior to submission. In the comment section of the final rule, it states: “Many states have been developing procedures and protocols to ensure that their data is complete and accurate, including evaluating the value of submitted claims against the managed care plan’s general ledger, random sampling of claims within managed care plans’ systems, and other types of reconciliation. States have found that performing validation activity on a monthly or quarterly basis has improved the data collection efforts. We support and encourage states’ efforts to improve encounter data. CMS anticipates continuing to work with states and to publish guidance and best practices based on states’ experiences.” We believe the final rule provides states with the flexibility to develop customized solutions that fit the unique characteristics of their managed care programs for monitoring encounter data quality.
- Standardized data elements. The completeness or inclusion of data fields contained historically in Medicaid encounter data may vary by state, managed care program, MCE, and service type. For example, the completion of the paid amount field within an encounter data set may be limited for sub-capitated services. By mandating specified data fields for each encounter data submission, CMS will further facilitate data analytics between MCEs within a managed care program, as well as the evaluation of overall delivery system performance across states and populations.
With encounter data submission requirements becoming effective July 1, 2017, states, MCEs, and their business partners will need to increase focus and rigor in managing encounter data processes to avoid penalties or sanctions in the near future.
Administrative best practices for encounter data management and submission
With CMS’s increased focus on encounter data accuracy and completeness, adopting sound administrative management practices will undoubtedly assume greater prominence for both states and MCEs. States in particular are becoming both receivers and submitters of encounter data and will need to ensure that “downstream” entities are prepared to support this highly visible CMS requirement and that their internal processes result in compliant encounter data submissions to CMS. In our consulting work with states and MCEs nationally, we have identified a set of administrative “best practices” for encounter data management and submission. They are outlined below.
State Medicaid agencies
Best practice state Medicaid agencies work to develop clear and consistent guidelines for encounter data reporting and monitoring, including the following:
- Documentation. Provide detailed, up-to-date encounter submission guides and companion documents as the foundation of a successful submission process.
- Contract. Incorporate clear reconciliation processes, remediation timelines, penalties, and remedies in MCE contracts. As the final rule establishes a mechanism to withhold FFP from states with encounter data quality issues, making sure MCEs have a vested financial interest in complying with encounter data submission requirements becomes even more imperative.
- Communication. Establish clear routine and nonroutine communication protocols, including meetings of both a technical and business owner nature.
- Time frames. Develop clear parameters and timelines for processing encounter data submissions, reporting errors or failures, and processes for correction.
- Validation. Although CMS and state validation methods are not yet clearly defined, states can begin to develop practices that will enable them to conduct file validation on multiple dimensions and adapt their practices as guidance evolves. For example, technical validation can ensure that headers and trailers are accurate, and logical validation may include checking that the claim does not include improper data, such as a paid date before the service date, and a procedural validation processes check for issues such as non-covered procedures.
- Reconciliation with audited financial reports. The final rule requires that audited financial reports be submitted by managed care entities specific to the Medicaid contract on an annual basis. Expenditures reported in the encounter data should be reconciled with each MCE’s financial report to identify potential gaps in encounter data reporting.
- Testing. Develop and implement testing and quality acceptance protocols for all new plan data submissions and for all plans when the state or CMS changes a submission rule or when technical submission requirements are modified.
- Data integrity. Maintain original data elements and a comprehensive data architecture and dictionary throughout each stage of the validation process to allow the state and MCEs to reconcile all interim data sets, if needed; and routinely provide the finalized encounter data to MCEs for agreement on a “source of truth” for contractual measurement purposes.
- Monitoring. Produce internal dashboard reports for state management, and potentially external dashboards for MCE review. Dashboards may track encounter volumes and error volumes, and trend data elements month-to-month and year-to-year.
- Web-based reporting tools. With the availability of web-based reporting tools with drill-down capabilities, state Medicaid agencies and their MCE vendors can drill down into specific issues that are identified through dashboard reporting.
Medicaid managed care entities
Best practice MCEs strive to create quality encounter data as early in the data collection process as possible. Factors that may drive improvements in the data collection process include:
- Ownership. Establish ownership and accountability in a formal manner. Best practice organizations establish strong cross-functional teams to support the encounter data process.
- Financial reconciliation. Conduct routine financial reconciliation of encounter data submissions to the plan’s general ledger because of the impact of encounter data on risk adjustment and premium revenue. If submitted encounter data does not include dollar amounts (e.g., in capitated arrangements), establish protocols to assign prices based on Medicaid fee schedules or other standardized pricing.
- Collaboration. Work collaboratively with state officials to influence encounter submission specifications. Partner with other MCEs to ensure that specifications make sense.
- Provider and vendor data. Ensure that provider and vendor contracts require timely and high-quality submission of claims and encounters. Provide problem resolution and feedback on encounter submission issues to providers and vendors. As CMS has increased focus on data quality concurrent with an expansion of new provider types who must submit data (e.g., MLTSS providers), managing vendors and delegates has taken on new importance for MCEs.
- Information systems architecture. Incorporate encounter data collection, management, and submission requirements into overarching system architecture and design. Invest in technology enhancements to support new and emerging requirements.
- Technical processes. Create a technical infrastructure to support encounter submission processing and quality review. Audit encounter submissions before submission, to identify issues up-front.
- Quality improvement. Put a data quality improvement process in place to continually improve all data within the organization. Ensure that encounter submission errors are tracked and aggregated and that patterns are reviewed as sources for potential data quality improvements.
- Documentation. Ensure that processes are well documented and teams fully staffed, and that cross-training has occurred so processes are not reliant on a small number of staff.
- Monitoring. Ensure that encounter submission processes are tracked and metrics are available throughout the organization, that completeness is reviewed by comparing encounters with financial reports, that timeliness and error rates are tracked, and that risk adjustment results are constantly monitored to ensure that encounters reflect accurate health risk (as applicable).
While many state agencies and MCEs have adopted some, or even many, of these practices, in our experience even large sophisticated organizations are still evolving and refining their operations to optimally support encounter data processing requirements.
The impact of enhanced encounter data on Medicaid managed care
The final rule addresses a number of topics, including: transparency in the MCE rate development process, quality measurement and improvement, and delivery system reform. At the center of these issues is the ability for stakeholders to have a clear picture of the services, costs, and quality associated with providing healthcare to Medicaid beneficiaries. This can only be done with complete and accurate encounter data. We believe the encounter data requirements in the final rule will lead to a more data-driven environment in Medicaid managed care, with the following key outcomes:
- Rate development process. Encounter data will serve as the base experience in the rate development process for established managed care programs. State Medicaid agencies will have greater insight into MCE performance through evaluating encounter data with managed care efficiency and quality measures. Improvements to encounter data reporting for services associated with sub-capitated and alternative payment arrangements will facilitate greater visibility into clinical and financial outcomes associated with such arrangements.
- CMS comparison of state managed care programs. With the establishment of standardized encounter data sets across the country, CMS will be able to better evaluate the performance of Medicaid managed care programs across states. This will aid CMS in ranking state performance based on standardized quality and managed care efficiency measures. In particular, it will assist in measuring the impact of Section 1115 demonstrations and other innovative health policies. It may be possible that CMS will employ more technical measures in measuring the cost-effectiveness of managed care programs across states.
Encounter data requirements in the final rule reflect significant changes with important ramifications for states, MCEs, and business partners. Prudent organizations should examine their current capabilities in relation to the new CMS requirements and take action to identify and remediate issues that might impact their ability to meet the new requirements.
Encounter data standards: Implications for state Medicaid agencies and managed care entities from final Medicaid managed care rule
Encounter data provides the most transparent view of a managed care entity's delivery of healthcare services, but encounter data that is incomplete, missing information, or reported incorrectly can severely limit its effectiveness.