Quality Measurement - Could we have gone too far?

The complex, at times confusing landscape of quality measurement programs in which practices and providers are required to participate, are the culmination of over a century of evolving quality measurement and improvement efforts in the American health care system.¹ The Institute of Medicine (IOM) defined quality as "the degree to which health services for individuals and populations increase the likelihood of desired health outcomes and are consistent with current professional knowledge".²

Contemporary quality measures fall under four broad categories:³

Structure

Process

Outcome

Patient experience measures

Structure measures assesses the characteristics of a care setting, including facilities, personnel, and/or policies related to care delivery. An example of a structure measure in the primary care setting would be the requirement to show the consistent availability of same day appointments in the setting of a Patient Centered Medical Home.

Many of the current measures that practices are reporting on are process measures which determine whether recommended evidence-based care/procedures were provided to the patient. Typical examples of process measures would be whether patients 50 years or older had a recommended colonoscopy, or a diabetic patient had a foot or eye exam at a recommended interval.

Outcome measures assess the resultant health outcomes of care, or a given intervention. An example of such a measure would be the reduction in dialysis rates in well controlled diabetics, or the rates of skin breakdown in nursing home patients. Understandably, these are the most complex measures to report. The outcomes are impacted by many confounding factors and some outcomes unfold over many years making measurement very difficult.

Finally, patient experience measures solicit patient feedback on the care they received whether it be the provider, the facility or services rendered. A typical example would be the question whether the patient felt the provider spent enough time with them at their appointment or explained matters clearly. These measures are often impacted by recall bias, and selection bias in the patients who choose to respond to these types of questionnaires.

There are many challenges presented by each of these measure categories, the quality of data available frequently does not support all types of measures, great ambiguity exists regarding the denominator and numerator participation criteria and in many practice settings current workflows do not support the availability of the structured data needed for calculation of accurate performance rates. Practices frequently develop a "study for the test" mentality which supports an enhanced performance rate but does little to address systemic deficiencies in the overall quality of care provided.

My personal experience participating in multiple quality and quality reporting programs leads me to fully agree with Dr. Don Berwick the former head of the Centers for Medicare & Medicaid Services and senior fellow with the Institute of Healthcare Improvement who is a vocal advocate for the reduction in required measurement in our health care system. Dr. Berwick has gone as far as suggesting a 50% reduction in current measurement requirements as part of an overall simplification of the existing incentive programs that physicians are required to participate in.⁴

Until the measurement requirements are indeed simplified, focused and streamlined, the NextGen Population Health and Analytics tools is available to help practice seamlessly integrate EMR workflows with mandated measurement requirements to lessen the burden of participation in programs such as UDS, MIPS or local and regional payer programs.