Contemporary technologies, innovative solutions, and expert support services enabling reliable, secure, and high-quality data resources for our clients.
At the core of our enterprise integration solution is formidable software designed for efficient information processing. This platform, which serves as the engine behind our market-leading solution, Onpoint CDM, provides tools for secure submission, cleanses and standardizes incoming data, performs rigorous quality assurance procedures, and integrates and consolidates disparate data sets. The end goal: downstream data enrichment and follow-on analytics.
Data Collection: Our systems have been handling secure submissions of healthcare data – commercial, Medicaid, and Medicare alike – for nearly 15 years across multiple states and more than 250 carriers. With tested and trusted systems, our data collection solution sets the foundation for the delivery of a reliable resource in support of advanced analytics with its superior data processing and performance capabilities.
Data Submission Portal: Onpoint supports each of our clients’ submitters through a customized, secure online interface from implementation through production. Onpoint CDM offers credentialed users a wide range of tools to help keep them informed – from helpful links and collection rules and regulation documentation, to data submission guides, FAQs, and announcements.
Data Quality Validations: Active data quality validation occurs across every stage of the data integration process, from verifying the integrity and validity of the submitted data, to reviewing consistency and completeness across data types and time. With thousands of checks stored in our data quality library, Onpoint CDM features complex and customizable programming that ensures our clients’ data will meet their end users’ analytic needs. Refreshed on demand and in real time, Onpoint CDM delivers the results of these processes to credentialed users through a variety of parameter-driven status reports.
Public/Private Payer Integration: Our staff have deep expertise in the integration of public and private payer data, expertly mapping and merging Medicaid and Medicare data with commercial streams, applying customized field-level validations, adjustment algorithms, and flag assignments to support analytics.
Non-Claims Data Linkage: We regularly integrate non-claims data sources with our clients’ claims-based data collections, including hospital discharge data, public health/birth/death registries, cancer surveillance data, EHRs, chronic disease program registry data sets, clinical registries, and survey data. This expertise enables the reporting of a broader set of claims-and-clinical-fused measures at the regional and state levels, including ACO, AHRQ, HEDIS, IHA, and TCOC metrics among others.
Data Warehousing: Onpoint’s operational data store uses a highly normalized, relational database design to enable efficient processing of data transactions. The format of the Onpoint CDM standard extract (the data model used for data dissemination and analytics) has been optimized for downstream analytics and reporting. With the recipients and uses of this standard extract varying greatly, the structure has been designed with the versatility to meet changing needs.
Data Security: We take data security as seriously as our clients. Operating from a SSAE 16 / SOC II hardened data center, we remain in full security compliance with HIPAA and HITECH and feature certification from the CMS Qualified Entity Certification Program (QECP). Onpoint is currently undergoing certification with HITRUST, with an estimated finish date in late 2016.
Onpoint’s integration tools are optimized to provide superior data processing and performance, enabling the creation of a robust set of value-add services, including attribution, group assignment, identity resolution, performance measurement, risk scoring, and use-flag assignment.
Attribution: Member-to-provider, provider-to-practice, and practice-to-organization attribution algorithms are interconnected processes that together enable researchers to evaluate the delivery and quality of care at each level of treatment.
Group Assignment: Onpoint has extensive experience using more than a dozen systems of groupers – from CRGs and DRGs to ERGs and PFEs, from BETOS to Red Book®. This work helps support a wide array of advanced analyses for employers and provider organizations based on these groupers, including provider profiling, the examination of preference-sensitive conditions to reduce unnecessary care and associated cost, the assessment of cost and quality at episode and specialty levels, and the bundling of provider-based payments to focus on event-based episodes.
Identity Resolution: The tracking of individual patients and providers across time and health plans is critical to accurate analysis. Onpoint performs this service through the construction of advanced master patient and provider indices. This construction spans a complex series of algorithms and automated linkage steps that rely, first and foremost, on the quality of the underlying data, which is safeguarded by our library of robust data quality validations.
Performance Measurement: Onpoint has programmed and run a wide array of claims-based cost, utilization, and quality measures, including measures developed and supported by HEDIS, NQF, IHA, AHRQ, and HealthPartners. We currently have more than 100 claims- and clinical-based measures in our Measures Engine library, which are refreshed regularly for multiple clients. Where national standards don’t yet exist, Onpoint has developed measures and their respective methodologies to address our clients’ interests and varying needs.
Risk Scoring: Depending on the type of reporting needed, Onpoint generates risk scores using a wide range of attributes, including age, gender, and health status. For clients that are combining commercial, Medicaid, and Medicare data streams into single reporting measures, a variety of payer-specific adjustments are implemented to ensure the most accurate adjustment of risk.
Use-Flag Assignment: Analytic flags assist researchers and analysts in identifying only a subset of records of particular interest. Standard use flags include inpatient discharge, claim type, aggregated age groupings, and chronic condition flags. Our inpatient discharge flag, for example, uses a sophisticated algorithm to cluster multi-claim inpatient stays into a single institutional stay for more accurate results.
To ensure that end users both understand and trust the validity and reliability of the data we deliver, our dedicated end-user support involves an array of steady communications, technical assistance, and tools to effectively support our clients’ initiatives and their key stakeholders. Standard tools include online collaboration sites, helpdesk support, tailored training, and supporting documentation.
End-User Documentation: To develop a cohesive end-user community, we help build a transparent knowledge base by producing a wide array of documentation, including data dictionaries, user guides, technical backgrounders, and data FAQs.
Online Collaboration: Onpoint’s interactive Collaboration Zone, powered by Microsoft’s SharePoint, is a secure online hub tailored to the specific needs of clients and their end users, enabling stakeholders to share documentation, access key communications, exchange questions and ideas, and stay up to date through an intuitive user-friendly environment.
Submitter Outreach: Every data collection implementation involves extensive work with submitters, new and experienced alike — not just to initiate data intake but also to resolve data quality and completeness issues identified throughout the process. Rapid resolution of such issues with submitters is essential to generating the foundational data to support downstream analytic goals. Factors critical to this process include proactive communication with submitters, online updates and reports through the Onpoint CDM portal, robust and regularly updated documentation, and ongoing training and support.
Tailored Training Programs: Online webinar trainings for clients and their stakeholders support knowledge transfer and cross-training needs on the data and its analytic use. Standard sessions include review of data and schema processes, end-user documentation, quality assurance processes, and standard and client-specific value-add services.