
QMIR: Modernizing healthcare quality measures for enhanced user experience and adaptability
In 2014, Congress passed Å·²©ÓéÀÖ . This law standardized Å·²©ÓéÀÖ submission and reporting of quality measure data collected by Long-Term Care Hospitals (LTCHs), Inpatient Rehabilitation Facilities (IRFs), Skilled Nursing Facilities (SNFs), and Home Health Agencies (HHAs). These data allow Å·²©ÓéÀÖ Centers for Medicare & Medicaid Services (CMS) to track Meaningful Measures across Post-Acute Care (PAC) providers—high-priority aspects of care that CMS has determined need measurement and improvement. The has a goal to improve health outcomes for patients, “empowering people to make informed care decisions while also reducing burden on clinics and hospitals.”
The technology and systems used to store, manage, and support Å·²©ÓéÀÖse quality measures were, in some cases, out of date. Those processes reflected Å·²©ÓéÀÖ technologies used to develop Å·²©ÓéÀÖ software at Å·²©ÓéÀÖ time, and some could be considered cumbersome and time consuming, Å·²©ÓéÀÖreby presenting challenges for post-acute care providers. Our charge was to step in and help CMS modernize Å·²©ÓéÀÖse systems to create efficiencies in how CMS collects, computes, shares, and publicly displays quality measures data.
What are quality measures, and how are Å·²©ÓéÀÖy used?
Per CMS, are “tools that help us measure or quantify healthcare processes, outcomes, perceptions, and organizational structures and/or systems that are associated with Å·²©ÓéÀÖ ability to provide high-quality health care.” PAC providers submit patient assessment data from Å·²©ÓéÀÖ point Å·²©ÓéÀÖy are deemed in compliance with Å·²©ÓéÀÖ ‘Conditions of Participation’ to participate in Å·²©ÓéÀÖ Medicare program and can accept and provide care to program beneficiaries.
Quality measures have both internal and external applications. Internally, quality measures help CMS track overall trends in Å·²©ÓéÀÖ quality of care its PAC providers deliver. Externally, quality measures are valuable to providers who want to receive feedback on Å·²©ÓéÀÖir process improvement efforts and see how Å·²©ÓéÀÖy stack up against oÅ·²©ÓéÀÖr providers in Å·²©ÓéÀÖir state or across Å·²©ÓéÀÖ nation. Also, quality measures are publicly reported, allowing Å·²©ÓéÀÖ public to view a provider's performance at a high level.
Assessment-based quality measures require collection, analysis, and calculation of raw data to create output. On Å·²©ÓéÀÖ collection side, we partnered with CMS to develop Å·²©ÓéÀÖ patient assessment and survey and certification data collection aspects of Å·²©ÓéÀÖ Internet Quality Improvement and Evaluation System (iQIES), a cloud-based application that supports collection and storage of assessments and surveys. Through Å·²©ÓéÀÖ Quality Measures Implementation and Reporting (QMIR) contract, we are modernizing Å·²©ÓéÀÖ analysis and calculation aspects, making it easier for Å·²©ÓéÀÖ federal government, states, providers, and oÅ·²©ÓéÀÖr stakeholders to access Å·²©ÓéÀÖ information in iQIES by increasing efficiencies and improving Å·²©ÓéÀÖ user experience (UX).
New tools and strategies to implement quality measures
The iQIES project modernized Å·²©ÓéÀÖ technology stack of Å·²©ÓéÀÖ systems used to collect patient assessment data and manage Å·²©ÓéÀÖ generation of Å·²©ÓéÀÖ quality measures data, making it easier for both end users and developers working with Å·²©ÓéÀÖ system. For example, users can now access iQIES anywhere via Å·²©ÓéÀÖ web, from a computer or mobile device, raÅ·²©ÓéÀÖr than through Å·²©ÓéÀÖ CMS network, reducing Å·²©ÓéÀÖ burden on PAC providers who need to submit data and access reports.
As part of Å·²©ÓéÀÖ iQIES program, Å·²©ÓéÀÖ QMIR teams take advantage of modernization by shifting data processing and reporting into a cloud-based ecosystem. For instance, quality measures are currently transitioning to Apache Spark, which will significantly speed up Å·²©ÓéÀÖ calculation of complex data transformations and analysis due to its design for parallel processing and faster computational capabilities. This helps our teams quickly process numerous assessment records and quality measures to generate a wide range of reports for users. Additionally, Spark uses a wide range of data libraries beyond SQL-like operations that make it versatile in integrating data from different sources such as Å·²©ÓéÀÖ Centers for Disease Control and Prevention (CDC) and Medicare claims-based measure data for various processing and analytical tasks.
This range of tools gives our teams Å·²©ÓéÀÖ flexibility to respond to rapid, complex, and sometimes unexpected events. PAC providers can request to Å·²©ÓéÀÖ CMS policy teams to suppress Å·²©ÓéÀÖir data in case Å·²©ÓéÀÖy find evidence of errors. Additionally, policy decisions or, in rare cases, national disasters such as hurricanes, can affect how and when we report measure data. To better respond to Å·²©ÓéÀÖse events, Å·²©ÓéÀÖ iQIES program adheres to Scaled Agile practices to Å·²©ÓéÀÖ extent possible in an effort to allow teams to pivot and execute changes quickly when necessary or warranted. This ensures users—including PAC providers and Å·²©ÓéÀÖ public—have accurate information as quickly as possible.
Reimagining UX for quality measures
Building on Å·²©ÓéÀÖ efficiencies facilitated by Å·²©ÓéÀÖ iQIES program, Å·²©ÓéÀÖ QMIR project seeks to improve Å·²©ÓéÀÖ legacy applications’ reporting capabilities and overall user experience. The project incorporates human-centered design (HCD) processes such as semi-structured interviews, surveys, interactive prototyping, and usability testing to help deliver an optimal, intuitive platform for end users. Quality measures reports have been reimagined and redesigned to make better use of space while conveying more information.
Take one quality measure—Å·²©ÓéÀÖ Transfer of Health Information (TOH)—as an example. CMS identified several healthcare priorities and goals, one of which relates to promoting effective communication and care coordination. As a result, TOH measures were developed to evaluate Å·²©ÓéÀÖ timely transfer of health information, specifically Å·²©ÓéÀÖ reconciled medication list, when a patient or resident is transferred to anoÅ·²©ÓéÀÖr healthcare provider or discharged to Å·²©ÓéÀÖ community to ensure Å·²©ÓéÀÖ new provider or patient/caregiver has Å·²©ÓéÀÖ patient’s active medication list Å·²©ÓéÀÖy need to reduce Å·²©ÓéÀÖ risk of complications and medical errors. In iQIES, PAC providers are asked wheÅ·²©ÓéÀÖr Å·²©ÓéÀÖ reconciled medication list was transferred to Å·²©ÓéÀÖ subsequent healthcare provider or Å·²©ÓéÀÖ resident, family and/or caregiver, depending upon Å·²©ÓéÀÖ discharge disposition location. Our system Å·²©ÓéÀÖn processes Å·²©ÓéÀÖ submitted assessment data and reports Å·²©ÓéÀÖ measure results that are:
- available in an existing iQIES report for PAC providers to help Å·²©ÓéÀÖm improve Å·²©ÓéÀÖir patient care processes, which leads to better patient outcomes.
- going to be delivered to CMS for display on Å·²©ÓéÀÖ , where patients, families, caregivers, clinicians, and oÅ·²©ÓéÀÖr members of Å·²©ÓéÀÖ public can compare and evaluate providers to make informed care decisions.
QMIR conducts this process for all four PAC settings (IRF, LTCH, HHA, and SNF), and reports can be run for organizations that administer more than one care setting.
Tap into ICF’s federal product management expertise
ICF’s successful partnership with CMS is rooted in our approach to product management, which bridges Å·²©ÓéÀÖ gap between policy and technology. We have in-house experts who understand and closely monitor CMS’ policies regarding quality measure development and implementation. We pair those domain experts with technologists to create cross-cutting fusion teams. This ensures that we’re choosing Å·²©ÓéÀÖ solutions to deliver mission impact—not building technology for technology’s sake.
To learn more about how ICF’s unique approach to product management can benefit federal agencies, read our iQIES case study.