The prevailing quality paradigm starts with the simple observation that we can observe gaps in care when we create an evidence based guideline and assess observed care against expected. One study says that we meet these expectations about 56% of the time.[1]
This observation leads to the seemingly logical conclusion that we can aggregate gaps in care as strong indicator of quality. This is important as we assume that more of this quality will lead to improved outcomes. We know from other studies that quality and cost are out of whack in the U.S. and health care costs are sucking the life blood out of employers, further exacerbating dismal job growth.Because we desperately want improved quality, we must have more of this gap closing work.
The prevailing quality paradigm has a number of flaws. It is expensive, overly focused on process measures, and may not predict the outcomes we want and need.
Expensive
Delivering evidence based care is a good thing, but the burden of managing the vast array of discrete data elements is beyond the capabilities of the vast majority of EMR vendors in spite of their claims to the contrary. Data entry is laborious and back end analytics infuriatingly complex, weak, or non-existent. Vendors have jumped into the breach to extract information from electronic records and even dictations but these solutions add significant cost that might not be recuperated in outcomes.
Overly focused on process
With years and years of disease management experience we know that process improvement does not always result in outcomes improvement. In a time of limited resource we should avoid the added cost and work burden of meaningless measurement.
Weakly predictive of outcomes
Making the case is a recent article from Duke. Boulding and colleagues used Hospital Compare data to analyze thousands of hospitals, looking at predictors of re-admission. They found evidence-based gap analysis a weak predictor of outcomes (re-admission in this case). The strongest predictor was the patients report of good communication.[2]
This study adds to the growing literature that is trying to tell us something: Patients perception and report of their care is tapping very important attributes of quality. These attributes appear to have strong correlation with important outcomes.
Good patient experience data can inform hospitals about structural weakness in communication that increases readmission risk. Patient report on primary care key performance indicators (access, person focused care over time, comprehensiveness, care coordination) can identify structural weakness far upstream. When we address these structural elements we improve population health in meaningful ways.
This is a measurement burden we can bear. This information is a powerful addition to our understanding of quality and outcomes. The health care industry tends to disparage or only provide lip service to patient-reported outcome measures. We continue to do so at our and our patients' peril.
