The Four Different Types of Clinical Quality Measures

Clinical Quality Measures (CQMs) have been a significant part of my work for the past 3 years.  My first foray into the CQM space was with the popHealth project, which is a reference implementation of the CQM logic that a provider or EHR vendor could use or incorporate into a software project.  popHealth was entirely focused on a family of CQMs called "proportion-based".

While the "proportion-based" CQMs get the majority of the attention with the healthcare community, it was not until a year working on popHealth that I discovered that there are a total of four different types of CQMs that affect how the CQM logic is implemented and reported.

The four different classifications of CQM logic are:

Proportion

• This is the type of CQM that most individuals are familiar with when referring to the Meaningful Use program.  
• These types of CQMs are routinely referred to as the "Numerator/Denominator" CQMs.  I recently wrote about the exception and exclusion logic, but it is worth noting that those CQM reporting characteristics are only applied to proportion-based CQMs.
• Usually, the proportion-based CQMs are a positive measurement of quality, meaning that usually, the higher the value of the Numerator/Denominator proportion, the better you are doing as a healthcare provider
• Example: "What percentage of women over the age of 45 and under the age of 65, who have had an outpatient encounter in the past 2 years, have had a mammography screening?"

Continuous Variable

• These CQMs are usually applied in the hospital CQM domain.  
• These types of CQMs measure the average time 
• Example: "What is the average time for Emergency Department (ED) admission until either Discharge or Admission to Inpatient Hospitalization?"

Episode of Care 

• These CQMs assess each distinct ‘encounter’ between a patient and a provider, during a a measurement period.
• A single patient can contribute to numerous considerations of the CQM result if they had numerous encounters
• Examples: "Did the provider measure the patient’s blood pressure during a particular episode?" or "Were heart attack patients discharged with an Rx for Aspirin during a particular episode?"

Longitudinal

• These CQMs take into account complete patient record with focus on a ‘measurement period’
• Examples: "Have patients who turned 2 years old during the measurement period received all required vaccinations on schedule?" or "Have diabetic patients received 2 foot exams during the measurement period?"

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported License. © Rob McCready, 2013.

Complexity and Certification of MU Stage 1 Eligible Professional Clinical Quality Measures

While working in the Clinical Quality Measure space on the two open source projects popHealth and Cypress, I have observed trends in the adoption of EHR vendors of various Clinical Quality Measures (CQMs).  For a little background on the role of CQMs in the Meaningful Use program, read the beginning of the entry that I wrote about Applying Kiviat Visualization to Meaningful Use Clinical Quality Measures. 

For Meaningful Use Stage 1, there are minimal requirements by EHR vendors to support the 6 Core and Core Alternate CQMs, and any 3 of the remaining 38 Meaningful Use Stage 1 CMS.  This allows for some malleability by the commercial EHR vendors to select CQMs based on either their ability to implement CQM logic in their product or based on customer demand for specific CQMs.

The Office of the National Coordinator for Health Information Technology (ONC) hosts the Certified HealthIT Product List (CHPL pronounced "CHaPeL") service.  You can view the list of certified products through the CHPL web interface.  Compiling the results for the EHR products against various Meaningful Use Stage 1 CQMs, there are some interesting results:

Meaningful Use Stage 1 Ambulatory Clinical Quality Measures:
Adoption by EHR vendors from data collected via the CHPL service

In addition to the work I am leading via Cypress, I am also leading a research project to assess the quality of Clinical Quality Measures called "Kamira".  The Kamira project can provide metrics on the quality of CQMs.  For early 2013, this has included automated Cyclomatic Complexity calculation of the CQM algorithmic logic based off of the JavaScript code that the Cypress and popHealth projects use to calculate the CQM results.

If you then compare the results of the CQMs that were tested and certified by EHR vendors against the complexity score of the CQMs, you can see a weak correlation between the two.  You can download the full file with the results here.

Meaningful Use Stage 1 Ambulatory Clinical Quality Measures:
Adoption by EHR vendors from data collected via the CHPL service
compared against Cyclomatic Complexity Analysis of the CMQ logic

It's worth noting that the correlation here is weak, but there does appear to be a trend toward vendors opting to implement the less complex CQMs in their products when they have some latitude to choose.

FYI, the ranges for the CQM complexity (the colored diamonds) are:

• 1-10 Very Simple/Low Risk (green)
• 11-20 Nominal/Moderate Risk (yellow)
• 21-50 Complex/High Risk (orange)
• >50 Untestable/Extreme Risk (red)

These metrics are somewhat arbitrary, but I picked ranges for CQM complexity from a Carnegie Mellon paper that had a good number of citations, so I think that the values and thresholds are fairly defensible.

Where this work might have a few vulnerabilities is that I am 100% certain that EHR vendors do not use complexity as their only consideration when selecting CQMs to implement in their products.  For instance some of the red, highly complex CQMs which were in the middle when it came to adoption by EHR vendors are cardiac CQMs.  From my perspective, it's a safe assumption that some of these EHR vendors were going to bite bullet and implement the cardiac CQMs regardless of the complexity associated with them because there is more demand in the marketplace from providers that need the cardiac CQM results, vs. say the behavioral health CQMs.  However, I think that CQM developers need to start tracking complexity of CQMs as they are developed for MU Stage 3 or beyond.

Lastly, the Kamira project just launched last week.  I plan on posting the MU Stage 2 complexity results for the Eligible Professional CQMs in the coming weeks.

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported License. © Rob McCready, 2013.