Unified Data Management Platform

In a major study, 40% of participants cited the ability to get relevant data as the biggest stumbling block in adoption of Analytics for business decision support in healthcare. Healthcare Organizations need key competencies in extracting, integrating, and standardizing the right data from multiple disparate sources to ensure they are able to attain and maintain the practice of “right care to the right patient at the right time by the right caregiver.” This is the foundation for Population Health Intelligence.

Our CareQuotient™ Data Platform enables healthcare organizations to move towards unified platforms with “trusted data quality” for use in clinical, claims, operational and financial performance improvement. The solution is built on a modular, scalable, and flexible architecture that allows healthcare organizations to scale their Data Platform assets according to their needs – whether one starts with Clinical or Claims or Financial or Operational data or a combination. Combined with PluralSoft’s Agile Analytics Adoption Implementation Methodology, healthcare organizations often take an iterative approach to build out their Unified Data Platform – reliably and cost-effectively to ensure reduced Time-To-Value.

Approach: Our multi-step approach to creating a Unified Data Platform is pictorially represented and briefly described below.


unified

Data Extraction

The goal of a Unified Data Platform is to deliver consistent data seamlessly regardless of – (a) the content and format of data captured in a healthcare organization’s source data application(s), and (b) the organization’s driving clinical, administrative, operational or financial business process workflow variations. Using our proven data management tools combined with our domain expertise, we work with identified customer subject-matter experts, to provide flexible data extract strategies in order to successfully meet this goal.

CareQuotient™ platform provides many mechanisms to selectively and comprehensively extract data from disparate sources of healthcare data – whether the sources of data are EHRs, HISs, Practice Management / Billing Systems, Laboratory, Diagnostic Imaging, Pharmacy, Claims processing, Public Health Registries, Drug databases, or other external sources. These mechanisms are available as pre-built Source Data Extraction Adaptors supporting data extraction from:

  • Healthcare interoperability standards based message streams in various formats (such as HL7, CCD, CCR, QRDA, X12, NCPDP, to name a few)
  • Popular EHR/HIS relational databases (such as NextGen, GE Centricity, eClinicalWorks, AllScripts, EPIC, to name a few)
  • Custom XML or Flat File formats from less popular EHR and HIS databases

Extracted Data is secured in transport using HIPAA HITECH prescribed security standards.

Data Quality Validation

Just mere information on the patient does not empower the caregiver to deliver quality care at the lowest possible cost. For value-driven care, providers need actionable insights from patient clinical data as well as associated demographic and financial data. For such data to become fully actionable, it should satisfy the dimensions of Quality, Context and Accessibility. We understand and demonstrate the data life cycle and supporting process life cycle around clinical, claims, administrative, financial and operational data; and hence expect data quality variations.

CareQuotient™ platform comes pre-built with hundreds of Data Quality Validation rules and checks on a number of clinical, claims, administrative, operational and financial healthcare data sets. These Data Quality Validation rules are configurable and customizable. They are not only relevant to individual elements but also across other data elements which combine to reflect a healthcare fact or event or relationships among them. Further, thresholds can be established with levers to promote or demote data with unsatisfactory quality into the Unified Data Platform for use in Analytics and decision support.

Data Normalization

Data Normalization is essential to ensure semantic integration and sharing of healthcare data leading up to trusted and accurate analyses, performance measurement and standardized benchmarking to promote increased use of evidence-based care practices and reduction of practice variation – all necessary building blocks to attain Meaningful Use objectives, and implement various value-based reimbursement models are available.

To bolster a healthcare organization’s Data Governance policies, procedures and standards, PluralSoft provides pre-built Master Data Management capabilities as well as pre-built interfaces to integrate third party products in two key areas:

  • Vocabulary Normalization and Standardization
  • Entity Normalization and Attribution
 Vocabulary Normalization and Standardization

Healthcare has many vocabulary standards and derivative variants implemented in a multitude of health information system applications. When a Unified Data Platform needs to deliver an accurate and consistent insight from its data; normalizing data contextually when captured in varying vocabulary or terminology standards across disparate data sources is an essential refinement step.

CareQuotient™ platform has pre-built capabilities for Vocabulary Normalization and Standardization to one or more industry terminologies (such as HL7, ANSI X12, ICD-9, ICD-10, CPT, CDT, RxNorm, SNOMED-CT, NDC, and CVX to name a few). This is powered by the National Library of Medicine’s Unified Meta Language System (UMLS™).

To further expand the breadth of Vocabulary Normalization and Standardization capabilities such as: support for a larger set of Ontologies, or automated terminology normalization using a suite of probabilistic and contextual mapping rules, or an expanded set of Data Governance workflow tools for use by Data Stewards, PluralSoft offers integration with third party Terminology Management applications.

 Entity Normalization and Attribution

CareQuotient™ integrates with third party EMPI products such as IBM Initiate, NextGate MatchMetrix, and VisionWare MultiVue.

In reality, patients receive care delivered by different providers or care givers in many care settings and locations over time. Further, patients could have had different health plans from one or more insurance carriers over that same time frame. When a Unified Data Platform needs to deliver an accurate and consistent insight from its data;it is imperative to create a trusted, accurate, yet longitudinal patient-centric view containing clinical, operational and financial perspectives. Such a picture needs to reflect a single patient who is identified using different identifiers and possibly variants of the patient’s given name, yet maintain a time-sensitive relationship with the various entities involved in that patient/member’s care.

Such a capability is popularly known by the acronym EMPI (or MPI) that can stand for one or more of – Enterprise Master Patient Index, Enterprise Master Person Index, Enterprise Master Provider Index, Enterprise Master Payer Index, and many others. At PluralSoft we call this EMEI (Enterprise Master Entity Index). An Entity is any place or thing that is of significance.

CareQuotient™ platform has the capability to represent a unique identification of an Entity – patient (a.k.a member, covered life, person, etc.), Provider, Physician, Caregiver, Healthcare Organization or its facilities or care settings, Health Plan, Insurance Company, Employer, Healthcare Collaborative (ACO, Clinically Integrated Network, etc.) and many more. Not only does the capability uniquely identify the Entity but captures a time-variant association among these Entities. This is the only way to derive a time-specific perspective of information across various Entity perspectives – By Patient, By Provider, By Payer, By Healthcare organization, By Program.

Data Integration

Once data extracted from source systems are validated, normalized and standardized, data is integrated into specific information domains with relationships that reflect the real world for trusted sharing, access, analyses, and aggregation. Such an integration approach ensures that data provenance or source data lineage is maintained to build auditability of data back to its source system. This allows users of the Unified Data Platform to also inquire and report on data as it is known to them in the original source, not only to build confidence, but to aid transitioning to a more standardized organization of their data.

CareQuotient™ Care Data Repository (CDR) is the trusted data integration layer that models all real-world data – covering clinical, claims, administrative, operational and financial realms as well as Industry Reference Data and Analytics Metadata. Such data is organized for storage in a third normal form as well as in purpose-driven multi-dimensional forms to aid quick aggregation, analyses and retrieval through CareQuotient™ provided data visualization tools, or through third party business intelligence and reporting tools. Data in CareQuotient™ CDR can be encrypted, if data-at-rest security is a requirement.

Pre-built CareQuotient™ functionality such as Performance Management Analytics for clinical quality, operational and financial performance measurement, Care registries, Care Management, Virtual Health Record, Dashboards, Ad-hoc Query, and many more are built on top of CareQuotient™ CDR.

Besides sharing data from CareQuotient™ CDR across healthcare organizations using CareQuotient™ provided Data Visualization tools, any HIE technology platform or HIT application can call a robust set of Web Services that deliver data either as raw data in information domain specific objects or as pre-packaged HL7 and CCD documents. This is one way to push insights gained from the Unified Data Platform back into point-of-care workflow at a healthcare organization.