Enabling More Accurate and Timely Meaningful Use Reporting
Meaningful use is the set of standards defined by the Centers for Medicare and Medicaid Services (CMS) that govern the use of electronic health records (EHRs) and allows for eligible providers and hospitals to earn incentive payments based on meeting specific criteria.
Achieving meaningful use of EHRs is of utmost importance for hospitals and providers looking to improve the quality of care they deliver, satisfy federal mandates, and qualify for financial incentives.
The end goal is to improve the quality of care provided throughout the United States, but it’s clear that the path is by no means easily attainable. The fact that many hospitals, providers, and IT solutions struggle to comply with and adapt to these standards has certainly played a large role in the CMS decision to push back Meaningful Use Stages 2 and 3 by over a year.
IMAT aggregates, normalizes, indexes, and codifies all patient data from across the continuum of care
Challenges of Meaningful Use Attestation
Need to Capture all Patient Data – To support MU cohort building and measure reporting, all relevant patient data needs to be made electronically available. For most EHR users, MU reporting has been limited to only the data captured in the EHR, during templated, structured data entry. While there are advantages to this type of approach, an organization needs access to diagnosis or treatment insights captured in the unstructured data, which includes visit notes, transcriptions, discharge summaries, radiology notes, and referral physician letters. Unfortunately most data management systems weren’t designed to convert and utilize unstructured data when reporting on MU measures, excluding this source of patient information from MU analysis.
Lack of Cooperation – In an ideal healthcare world, there would be well followed standards for the comprehensive exchange of information among health service organizations, such as imaging centers, labs referring physicians, hospitals and any other healthcare provider involved in the continuum of care of an individual patient. That just isn’t the case in today’s environment. Many EHR vendors, for example, struggle or simply fail when it comes to ingesting data generated outside their system. Regardless of their reasons, it’s clear that until vendors are more willing to own the responsibility of working toward industry standards, the road to capturing a 360º view of the patient, across the continuum of care will likely progress slowly.
Scaleand Complexity –As these stores of patient data balloon to millions or billions of records, the time it takes to run complex cohort and quality measure reports balloons as well. Many data management systems were not designed for this level of scale and complexity, thus the time it takes to get results back from these big data stores may be measured in hours or days.
IMAT Solutions Solves the Meaningful Use Reporting Challenges
The IMAT platform was designed from the ground up for today’s big data challenges in medical reporting. IMAT has the capacity, speed and flexibility to bridge the gaps introduced by the data capture vendors currently in use by medical organizations.
Through the six-step IMAT data ingestion process: Connect – Collect – Validate – Normalize – Index – Codify, all data, no matter the source, the format or data type can be aggregated into one common data store. This includes narrative information captured as unstructured data. The IMAT platform can capture, standardize and make available both structured and unstructured data for real-time search and reporting.
Processing times for complex queries across millions or billions of records has been compressed for IMAT users. In performance and accuracy benchmarking, the IMAT system identified complex cohort sets in 2 to 20 seconds, across 2 billion records, representing 19 million patients from 20 data sources. Competing systems took 20 hours to execute the same queries. Imagine running and reviewing your MU cohort and quality measure reports during your lunch hour, with time to spare.
Other benefits include:
Accurate Data – The IMAT platform ensures that ALL data is indexed at its most granular level. Working with our clients, they pre-define a set of concept recognition, validation and code mapping rules, which are run against the data during the ETL(extract, transform, load) process to ensure a high degree of data accuracy. During a monitored ETL process, the IMAT system was able to take in 2,000 records per second, which included running 15 validation rules against each record, while running on a single server. Accurate data leads to accurate MU 2 reporting results.
Affordable Scalability – IMAT’s unique architecture enables literally billions of records to be stored and processed on a single server. IMAT is designed to scale, cost effectively.
The true value of data management systems in healthcare lies in leveraging the data to create actionable insights. By leveraging IMAT’s disruptive technology, healthcare systems are discovering that true data aggregation, normalization, analysis and reporting is not only possible, but can be practical, in terms of cost and time.