122125 O3 Attachment 4 - Data Integration Guidelines.docx.pdf
PDF 430 KB Posted
- Attached to
- Program Integrity Case Management (PICM) and Fraud Abuse Detection (FAD) Analytics Solution
- Solicitation number
- 122125 O3
- Issued by
- Blaine County, Nebraska
About this file
This document is a Data Integration Guidelines document for PICM (Provider and Individual Case Management) within the Department of Health and Human Services (DHHS). The guidelines outline the current and target data system landscapes, focusing on integrating various data sources including claims, encounter, provider, member, reference, and Electronic Visit Verification (EVV) data. The integration approach aims to minimize work on existing systems and HIA operations, with data to be routed through an integration hub that will act as a pass-through from source systems to PICM and the Enterprise Data Warehouse.
The document specifies technical standards for data integration, including batch processing with nightly or weekly ETL jobs, potential real-time integration using protocols like Webhooks, Kafka, or MQTT, and acceptance of data formats such as JSON, XML, CSV, and X12. Security and privacy measures include TLS encryption for data in transit, AES-256 for data at rest, role-based access control, HIPAA compliance, and anonymization of personally identifiable information. Monitoring and maintenance provisions include tools for error reporting, backup and disaster recovery procedures, alerts for system issues, and a maintenance schedule to ensure ongoing compatibility and performance.
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Text version
Data Integra�on Guidelines for PICM
Table of Content
Table of Content ________________________________________________________________________ 2
1. Introduction___________________________________________________________________________________ 3
2. Objectives ____________________________________________________________________________________ 3
3. Integration Scope ______________________________________________________________________________ 4
3.1 Current Data Warehouse System Landscape __________________________________________________ 4
3.1.1 Key Highlights _____________________________________________________________________________ 4
3.2 Data System Landscape for MLTC Post PICM Implementation ___________________________________ 5
3.2.1 Key Highlights _____________________________________________________________________________ 5
3.3 Target Data System Landscape for MLTC ______________________________________________________ 6
3.3.1 Key Highlights _____________________________________________________________________________ 6
3.4 Data Sources Landscape ____________________________________________________________________ 7
3.5 Initial Data Mapping for PICM _________________________________________________________________ 7
4. Standards (Integration Methods and Data Standards) ____________________________________________ 8
5. Security and Privacy __________________________________________________________________________ 8
6. Monitoring and Maintenance __________________________________________________________________ 8
1. Introduction
The purpose of this document is to provide an overview of the current and target data and system environment to ensure that the PICM system can optimally operate in the overall data landscape of DHHS. These guidelines are designed to ensure consistency, security, and reliability in the data integration process, enabling stakeholders to make data-driven decisions effectively.
2. Objectives
Identify the different data sources and promote an optimal approach for integrating data sources into PICM.
Ensure alignment with applicable data governance, security, and privacy policies.
Promote interoperability among different systems.
Minimize integration risks while maximizing data quality and consistency.
3. Integration Scope
3.1 Current Data Warehouse System Landscape
3.1.1 Key Highlights
- The MMIS provides all the data for the current Data Warehouse system including fetching data from N-FOCUS and PDMS system.
- There is currently no EVV data in the Data Warehouse system.
3.2 Data System Landscape for MLTC Post PICM Implementation
3.2.1 Key Highlights
- The case management system will be retired with the implementation of the PICM system. This will involve the conversion and migration of case data in the PICM system.
- The existing warehouse operations will continue to operate with its existing data feeds from the MMIS system.
- PICM will get data through the Integration Hub. The integration hub will be a pass-through model and not manipulate the data from the underlying source systems.
- The encounter data and the claims data will use the existing claims format to feed PICM data.
- PICM system will publish its data and metadata in a standard format for downstream systems.
3.3 Target Data System Landscape for MLTC
3.3.1 Key Highlights
- Data to both the new Data Warehouse and PICM will come through the integration hub.
- The integration hub will act as a pass through of data from source systems.
- PICM and the Enterprise Data Warehouse system will publish its data and metadata in a standard format for downstream systems.
3.4 Data Sources Landscape
S No. Type of Data Source(s) of Data 1 Claims Data MMIS, N-FOCUS, THERAP
2 Encounter Data HIA- Encounter Processing System
3 Provider Data MMIS, PDMS, N-FOCUS
4 Member Data N-FOCUS, MMIS
5 Reference Data MMIS
6 EVV Data EVV System
7 Authoriza�ons Data N-FOCUS, MMIS
3.5 Initial Data Mapping for PICM
This is the planned approach for data sources feeding data into PICM. This will be refined as we collaborate with the PICM vendor. The guiding principle is going to minimize work on existing systems and HIA operations.
S No. Type of Data Source of Data Data Type
1. FFS Claims Data MMIS Internal Claims
Format or Post Adjudicated HIPAA format*. CSV file
2. Encounter Data HIA Internal Claims Format
3. Waiver Claims Data N-FOCUS Internal Claims Format
4. Provider Data PDMS CSV File/ API
5. Provider Ownership Data PDMS CSV File/ API
6. Member Data N-FOCUS CSV File/ API
7. EVV Data THERAP TBD
8. Waiver Authorizations and Claims
THERAP TBD
4. Standards (Integration Methods and Data Standards)
4.1 Batch Processing
Schedule: Nightly or weekly jobs.
Tools: ETL (Extract, Transform, Load).
4.2 Real-Time Integration
Protocols: Webhooks, Kafka, or MQTT.
Use Case- TBD
4.3 Data Formats
Accepted Formats: JSON, XML, CSV, X12 Character Encoding: UTF-8 encoding is mandatory.
5. Security and Privacy
Encryption: Use TLS for data in transit and AES-256 for data at rest.
Access Control: Implement role-based access control (RBAC).
Compliance: Adhere to HIPAA, and other applicable regulations.
Anonymization: Mask personally identifiable information (PII) and PHI when necessary.
6. Monitoring and Maintenance
Monitoring Tools: Tools and processes in place for handling schedules, exceptions and error reporting.
Backup and Disaster Recovery- RTO and RPO in alignment with the business expectations and there are appropriate procedures to support disaster situations.
Alerts: For errors, delays, or failures.
Maintenance Schedule: Regular updates to maintain compatibility and performance.
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