How does IMAT handle unstructured content and retrieve clinical concepts?
IMAT transforms and annotates unstructured medical narratives, such as those found in medical records or dictated clinical summaries, using best-of-breed Natural Language Processing (NLP) technologies. The records are converted into easily retrievable, accurate data that supports interoperability, disability screening, medical necessity, decision support, patient safety, billing and coding and case management. IMAT also indexes structured data from ODBC compliant solutions, HL7 messages, Radiology reports, etc.
What medical code sets does IMAT support (e.g. SNOMED, ICD-9, etc.)?
IMAT leverages best-of-breed Natural Language Processing (NLP) technologies to transform unstructured data into formally represented data (annotation/classification) according to semantic interoperability standards. IMAT currently has the ability to code information in UMLS (SNOMED CT, and RXNorm) and, by leveraging cross mapping, to represent and code information in ICD-9, ICD-10, CPT, LOINC, ICF, HCPCS and other standard terminologies.
What document formats can IMAT handle (e.g. doc, pdf, txt, rtf, xml)?
IMAT can extract information from any unstructured text document including Word, PDF, Open Office, Corel, WordPerfect, etc. Additionally, IMAT processes and indexes structured content from EHR systems, labs, claims data, ADTs, MPI, and more.
What is the format of your output file?
IMAT uses industry standard XML encoded file as its native output. In addition to discrete data within the XML document, encoded data is available for distribution via the IMAT web service with the use of APIs. IMAT is also able to extract user-defined fields in CSV, XML, and HL7.
How does IMAT handle big data?
The IMAT platform can process millions of records per day by taking advantage of proprietary distributed processing and can invoke multiple IMAT instances to manage increased volume requirements, in terms of both indexing and complex reports generation.
What type of interfaces does IMAT support?
IMAT includes a browser-based user interface that supports the latest versions of Edge, Chrome, Firefox and Internet Explorer 11. IMAT also has API calls that allow programmatic access.
Does IMAT provide a workflow management solution for the review of records?
Yes, IMAT includes a configurable document and data workflow. A series of configurable rules allow the system to select where the data is sourced from, determine the path that the document or data will take through the system, and choose what cross referencing and NLP technologies to apply.
How are medical record codes updated and what type of rules are pre-populated?
Basic rules and workflow paths are pre-configured and kept up to date using best practices for content, structure, metadata identification, medical concept and encoding, error management and document review. After basic configuration, IMAT’s rules engines and workflow are configured for each client’s needs, based on the applicable medical codes received from the various code standards organizations.
Will IMAT support an onsite solution?
Yes, IMAT can be deployed on-site using customer-furnished hardware that meets the minimum specifications. IMAT is also offered as a hosted solution for customers seeking to minimize their on-site computing requirements.
Can the solution be hosted in my data center?
Yes, the IMAT platform could be hosted within the client’s environment, provided the data center has the infrastructure to support the required performance.
Does IMAT support service-oriented architecture?
Yes, the IMAT platform is provided as a cloud-based solution or SAAS.
Is IMAT compliant with the Health Insurance Portability and Accountability Act of 1996 (HIPAA) requirements?
Yes, the IMAT platform and related tools are HIPAA compliant. These compliancy standards are laid out by each governing body. Access to documents and related data is controlled at the document level for each document. This ensures that access to patient information is maintained at the lowest level.
Does IMAT capture auditable history? At what level and for what duration of time?
Yes, the solution provides a full audit history from various levels of the application, including data processing, user access to information, queries and reports created and run by users, and user administration. By default the logs are stored for 30 days, but this duration is configurable.
Does IMAT include any base or ad hoc reporting capabilities?
IMAT is a configurable solution with several modules. Even the most basic IMAT installation provides the most comprehensive ad hoc reporting and cohort identification available. Optional modules add or improve data access, charting, and analysis functionality.
Does IMAT provide any user interface or administrative tool?
Yes, IMAT includes a web application interface that provides customers with complete access to the administration, configuration, and maintenance of the various components. The solution provides role-based data access controls for monitoring, settings, rules, and data.
Does IMAT support RAC audits?
Yes, the RAC audit process is fundamentally simple in terms of the process. There are two types of audits—the first is automated and involves the identification of items that are not covered by Medicare policies or guidance using billing information. The second is a more in-depth or complex review where human intervention and review of supporting medical records is required. The second type of audit is typically performed when there is a high probability of a non-covered service or when there is no definitive Medicare policy in place. Both can be facilitated using IMAT’s medical query builder.
Does IMAT support meaningful use?
Yes, IMAT supports 100 percent of meaningful use reporting by automating the process of capturing medical information, encoding and indexing the data or notes, aggregating the data into the IMAT Medical Data Warehouse, and distributing the relevant portions of the data for use by industry standard reporting tools or EHR solutions. IMAT’s platform is able to identify information such as patient demographics, diagnosis, medications, allergies, lab results and treatment plans from narrative text and convert this information into structured data for reporting purposes. The process is automated and the data can be derived from any industry standard text-based report or form.