Quality & Process Improvement

What is your general approach to interventions?

Response: Using the Anatomy of Healthcare as a foundation and the lean methodology as a guide, Health Catalyst supports clients in the creation of a governance and work team structure with provider and nursing leadership to ensure clinical and operational oversight. Health Catalyst encourages supporting roles such as subject matter experts and knowledge managers to bring expertise from the floor into the improvement process. AIM statements, which define outcomes or process goals, are created based on data-driven analysis of key processes that need improvement. Interventions and action plans are based on evidence-based best practices. Process improvements and workflow redesigns are monitored using Health Catalyst’s analytic tools.

How do you match or correlate patient data from different source systems?

Response: The Catalyst common bus architecture allows patients from disparate sources to be uniquely identified across multiple systems.

Describe your solution to meet pay-for-performance measurements?

Response: A key component in all pay-for-performance initiatives is a measurement. Various government programs and payers have started to measure and pay for quality and improvement. For example, the CMS (Centers for Medicare & Medicaid) value-based purchasing program pays for achievement (compare to benchmark) and improvement (compare to your performance in previous period). With Health Catalyst Regulatory Explorer, hospitals can compare various quality metrics over time. This product is a framework for metrics.

To monitor outpatient performance, Health Catalyst created a Community Care application that tracks physician performance to metrics developed by various payers to improve quality.

Health Catalyst Readmission Explorer allows users to see trends and drill into the drivers of readmissions. Readmissions are important to hospitals as CMS is in the second year of the Readmission Reduction Program that includes penalties of 2% for 2014. Patient Satisfaction Explorer shows users the specific measures by location.

How do you measure compliance with evidence-based guidelines in primary care?

Response: We help clients establish a primary care dashboard that provides rates and analysis indicating provider compliance to diabetes monitoring, cardiology monitoring, and prevention screening. This capability could easily be expanded to any chronic disease or procedure measured in an EMR, and it allows clinicians to monitor compliance and identify patients that need additional care.

In progress — expected benefits are better compliance, improved patient compliance tracking, improved clinician compliance management tracking, etc.

How do you use patient registries to track specific diseases and diagnoses and ensure appropriate care?

Response: Health Catalyst provides a rich set of services based on a proven methodology for clinical improvement. One of the key initial steps in the Health Catalyst methodology is the definition of an accurate representation of patients impacted by the clinical process that is being optimized. Once that patient cohort is defined, the registry (or module) is built into the Health Catalyst architecture. The architecture provides data structures to hold detailed cohort definitions. It also provides data structures and technology to hold metrics related to that cohort. The metrics are customizable by a data architect and can be sourced from clinical guidelines, institutional best practices, regulatory bodies, and other sources. The metrics are displayed in a visualization layer, usually alongside a target value. The module architecture holds granular data in a way that metrics surfaced in the visualization layer always allow drill down, often to the order level. The drill-down functionality can often point to the “why” behind a piece of data, which allows physicians and other clinicians to implement appropriate interventions to improve the metric.

What is your episode treatment grouping (ETG) methodology?

Response: ETGs (or Episode Treatment Groups) are a way to better understand which healthcare services, typically provided within a defined window of time, can be logically grouped together into a condition-related Episode. The Health Catalyst data warehouse platform can integrate with popular third-party treatment grouper products, such as those from OptumInsight and 3M. Alternatively, customized grouping rules and logic can be developed to effectively tag ambulatory and acute services as belonging to the same episode. Those tags can then be surfaced through Health Catalyst’s applications.

How do you group patients into disease profiles for analysis and planning?

Response: Health Catalyst feels that the implementation of disease registries is critical to empowering clinical improvement in populations of patients with chronic disease. Health Catalyst delivers applications and services that accelerate the discovery, exploration, and operationalization of disease registries, typically in three phases.

First, Care Improvement Teams are empowered with a tool called Cohort Finder. Cohort Finder is an ad hoc querying application that allows non-technical users to rapidly filter and profile patient populations using clinical, financial, and administrative data.

Next, Health Catalyst’s data architects configure specific analytic applications using the population definitions developed with Cohort Finder.

Finally, Population Explorer provides an easy-to use interface that lets users explore a wide variety of metrics across a growing list of clinically validated cohort definitions. Users can view metrics about individual patient populations, including case counts, readmission rates, charges, revenue, and length of stay, among many other metrics. Each of these metrics can be stratified by demographic information and other clinical and financial information. The tool makes it very easy to switch between different populations and provides comparative views between multiple populations.

How do you identify gaps in care?

Response: The Population Health advanced module was built to support the shifting payment models that place a larger emphasis around primary care. This module helps providers and healthcare systems that are taking on risk either through formal payment channels such as VBP, accountable care, capitation, etc. or informally through internal quality initiatives. Built at the core is a care coordinator workflow that identifies high utilization, ability for outreach, and risk stratification among chronically ill patients. Leveraging knowledge assets from content providers, the Population Health module identifies patients that are out of compliance with the standard of care for a given condition. Identifying those patients lets the provider intervene to fill gaps in care.

How do you stratify patient populations and identify opportunities for intervention?

Response: Health Catalyst’s Population Explorer not only focuses on identifying chronically ill populations, but it also focuses on prevention strategies around each chronic condition and in general. For example, the Population Health advanced module focuses on primary care around the following common ACO, PQRS, and Meaningful Use prevention measures:

  • Medication Monitoring (ACE/ARB/diuretic)
  • Breast Cancer Screening
  • Colorectal Cancer Screening
  • Chlamydia Screening
  • Evidence-Based Cervical Cancer Screening
  • Annual Flu Vaccine
  • Pneumonia Vaccine

How do your products help improve clinical outcomes?

Response: Population Modules from Health Catalyst go beyond basic indicators of health outcomes like readmissions and length of stay to focus attention on specific clinical measures needed to measure baseline care processes and outcomes, but more importantly, to actively measure the effectiveness and outcome of care improvement interventions for specific patient populations.

How do you address utilization (lab, radiology, surgery)?

Response: The Departmental Explorer Suite provides a collection of basic dashboarding tools to help foundational hospital departments, such as Lab, Radiology, Surgery, and more, gain a baseline understanding of basic operational efficiency and volume metrics specific to their areas.