Quality Measures and Clinical Decision Support within Electronic Health Record systems. As a quick refresher on the two types of healthcare reports:
Clinical Quality Measurement (CQM)
- Typically post-event reporting on treatment, usually via a quarterly or annual basis
- Longer term impact on healthcare quality of a population of patients
Clinical Decision Support (CDS)
- Guide clinical choices during treatment now
- More direct and immediate impact on the quality of care being provided to a patient
CQMs and CDS are clearly very closely related disciplines. In fact, they are two sides of the same coin. They both consider what actions providers take with the "hand they are dealt" with their patients. For both types of reports, data in input via electronic clinical data, and both are implemented within EHR systems. Additionally, the logic of a CDS rule and a CQM report are indeed very similar.
With CQMs, you are reviewing actions taken in the past to help educate and influence decisions in the future.
With CDS, you are working in real-time... in the present.
To put this in another context, with CQMs you may be viewing data that may have led to the death of a patient. The goodness or badness has been performed by the provider or healthcare team. With CDS, you have the potential to actually kill a patient by taking the wrong action.
This is the part of the CDS space that I personally find troubling to work with, since there is a much more real risk to harming a patient with either a bug in CDS logic or with ambiguity in standards that could be used to express CDS
Consider a Warfarin CQM that measures “Did you perform appropriate warfarin dosing?” You could apply this CQM to a population of cardiac patients and consider the results in aggregate to see if over the course of a year. Now consider a CDS that determines "What is the lethal dose of warfarin dosing that I am providing this patient... right now?!?”
For me, addressing the second scenario become really serious very quickly. For healthcare providers, I do not think that they are phased with either domain, since they deal with life and death scenarios all the time.
But again, for me, these are the scenarios and domains where I lose sleep after work.
Several considerations have been discussed to expand the Health Quality Measures Format (HQMF) XML standard that is used for expressing the CQM logic for the Meaningful Use program. The HQMF is an HL7 standard for representing a Clinical Quality Measure (CQMs) in XML. The HQMF standard is a declarative approach to defining procedural CQM reporting logic. What the HQMF standard has going for it, is (regrettably) being named the authoritative source for expressing the logic for the Meaningful Use Stage 2 CQMs.
The HQMF implementation of CQMs defines the data elements referenced by the logic, and associates them to value sets using object identifiers (OIDs). These OIDs can then be used with the National Library of Medicine's (NLM's) Value Set Authority Center (VSAC) to translate clinical concepts into various operational clinical codes.
For those really interested in using the HQMF, you can download the HQMF files for all the Meaningful Use Stage 2 Clinical Quality Measures from the CMS site here.
Having worked with the HQMF XML standard indirectly for the past 2 years on both the popHealth project, and for the past year the Cypress project, my team has repeatedly expressed concern over the standard due to ambiguity and difficulty in ensuring that the HQMF standard is properly implemented in an EHR. For our team, our challenge was consuming HQMF XML and turning it into procedural logic for Cypress and popHealth.
Based on the challenges my team has faced, I am very cautious about any considerations to re-use the HQMF standard for CDS support, since I feel it does a poor job expressing even the CQM logic. My primary concern with the plans on converging CQMs and CDSs logic is the current declarative approach used for CQMs which is the HQMF XML standard.
What I feel is needed is a procedural definition of both CQM and CDS logic. The reason for this need for procedural expression of the logic is that it allows for more rigorous testing, and also reduces the ambiguity associated with EHR systems have to implement their own parser to convert the declarative HQMF definition of either a CQM or CDS into their own procedural set of software instructions.
Consider the following procedural JavaScript logic built into popHealth v1.4 for the Meaningful Use Stage 1 CQM, NQF 0421 Adult Weight Screening:
function() {
var patient = this;
var measure = patient.measures["0421"];
if (measure == null)
measure={};
var day = 24 * 60 * 60;
var year = 365 * day;
var effective_date = <%= effective_date %>;
var measurement_period_start = effective_date - (1 * year);
var latest_birthdate = latestBirthdayForThisAge(65, measurement_period_start);
var earliest_encounter = measurement_period_start - year;
var population = function() {
var correct_age = patient.birthdate <= latest_birthdate;
return (correct_age);
}
var denominator = function() {
return inRange(measure.encounter_outpatient_encounter,
earliest_encounter, effective_date);
}
var numerator = function() {
return weight_numerator(measure, 22, 30);
}
var exclusion = function() {
return weight_exclusion(measure, earliest_encounter, effective_date);
}
map(patient, population, denominator, numerator, exclusion);
};
By having a single procedural definition for both CQMs and CDS, we should be able to have a higher level of confidence in the performance of the EHR systems that have to implement either a CQM or CDS. What could then be done, is test and certify EHR systems ability to process the procedural definition of the standard, and then have a higher level of confidence that the any new CQM expressed in procedural logic... as long as it were syntactically well formed... would work with an EHR system.
The benefit to this type of approach is accelerated velocity in development, testing, and deployment of new CQMs and new CDS reports/rules.
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported License. © Rob McCready, 2013.
