Simplifying Quality Measurement to Help Patients Select Payers and Providers

Published 2020.8.4

There are several heuristics for how patients might make decisions about choosing a healthcare payer or provider. One approach assumes that all providers and payers only do the minimum work necessary to meet external mandates and one should choose the least expensive option available. Another approach believes some actors consistently outperform their peers on overall quality and deserve a premium for their performance. A third approach suggests there are centers of excellence that have mastered one or more clinical pathways and should be recognized for that specific work. Yet another approach suggests patients select providers who maximize quality-adjusted-life years. Regardless of the approach, purchasers or patients rely on some measurements to determine if the healthcare entity is delivering some minimum level of quality.

Today’s leading ambulatory healthcare quality measurement tool is the Healthcare Effectiveness Data and Information Set (HEDIS). The tool includes over 90 measures across six domains (effectiveness of care, access/availability of care, experience of care, utilization and risk-adjusted utilization, health plan descriptive information and measures collected using electronic clinical data systems). Within the risk-adjusted utilization group, HEDIS measures plan all-cause readmissions, acute hospital utilization, emergency department utilization and hospitalization for potentially preventable complications. The last measure measures several conditions, including bacterial pneumonia, cellulitis, urinary tract infection, pressure ulcer, diabetes, COPD, asthma, hypertension and heart failure. The Core Quality Measures Collaborative have identified a separate series of metrics for accountable care organizations, patient-centered medical homes and primary care (last updated in early 2016) that are heavily weighted toward cardiovascular disease management and cancer screening.

Medicare’s Hospital Compare website uses over 100 quality measures within seven categories (Mortality [22%], Safety of Care [22%], Readmission [22%], Patient Experience [22%], Effectiveness of Care [4%], Timeliness of Care [4%], and Efficient Use of Medical Imaging [4%]). The agency has additional measures of cost and value for specific care episodes (i.e., heart attack, heart failure, pneumonia and hip and/or knee replacement). The website does not define what high or low value might be, but it does list if the inpatient facility charges significantly more or less than the national average for a type of hospitalization.

For episodes of care (e.g., a heart attack, a hip replacement), there might be three types of metrics:

  • What, if any, is the right level of intervention?
  • If an intervention is warranted, was it performed in the most effective way (safety, cost, quality)?
  • What is the risk of the patient developing short- or long-term sequelae from the condition being inadequately treated, overtreated or incorrectly treated?

For chronic conditions (e.g., hypertension, heart failure diabetes), quality metrics might focus on:

  • Managing symptoms or risk factors with the most cost-effective medication regimen or behavioral recommendations to prevent undesirable outcomes
  • Detecting complications early enough to reduce the incidence of emergency room visits or hospitalizations
  • Maximizing patient-oriented outcomes like functional status or days without contacting a healthcare provider

In my own experience, the quality measurement community has focused their episodic metics on safety and quality (complications, readmission rates) without considering if a procedure needed to be done or if the patient’s quality-of-life improved after the intervention. Metrics for chronic conditions prioritize risk factor management, providing advice to change behaviors and avoiding emergency room visits and hospitalizations.

Back in 2016, two employees from the Hospital for Special Surgery (one of three percent of hospitals with a 5-star rating from Hospital Compare based on 64 measures that year) suggested Medicare’s quality reporting methodology was flawed for several reasons, including:

  • Roll-up scores across conditions/procedures obfuscate quality at the level of the condition or procedure where gains in quality could happen,
  • Grading on a curve fails to identify whether quality is good or bad, and
  • Measurement is incomplete and/or imbalanced both in terms of application of existing measures across hospitals and the absence of important measures in the set.

Based on a 2018 Lancet publication, American health care workers should focus on the following risk factors to minimize avoidable disability: high body mass-index, smoking, high fasting plasma glucose, drugs and high systolic blood pressure. Unfortunately, many Americans who have these risk factors may not:

  • See the value in addressing these risk factors or
  • Be willing to make (and sustain) the behavioral changes to address these risk factors. One research group estimated that less than one percent of patients counseled to lose weight are successful long-term whereas 3-17% of patients advised to quit smoking successfully do so.

What an employer or government payer may value (smoking cessation, weight loss, medication adherence) may not always be valued by the patient. One could argue that the medical community has not fulfilled its role as educators to help patients see the value of changing these behaviors, but holding providers accountable for patient behavior has led to providers discharging “noncompliant” patients from their practice.

Even without considering the challenges of polychronic disease, the current approach to generating more quality metrics may actually distract payers, providers and patients from what everyone wants: high-quality, high-value care. Understanding what matters to payers and patients might help providers reorient their care delivery patterns in the ambulatory, urgent care and inpatient arenas. I would advocate for the following sets of measures:

  1. Global metrics
    • Mortality
    • Quality-of-life (physical, psychological, level of independence, social relations, environment)
    • Total cost of care
  2. Interventions to maximize quality and quality of life
    • Tobacco use
    • Body-mass index
    • Non-prescription drug use with some exemptions (e.g.,moderate alcohol and marijuana use)
    • Firearm safety
  3. Disease-specific metrics by expected duration
    • Chronic
      • Risk factor control
      • Medication burden (number of pills, cost)
      • Risk of intensive procedures compared to others at the same point in the disease course
    • Acute
      • Likelihood to recover from the acute event
      • Total cost of care for a given episode
      • Residual change in quality of life 90 days after the episode
      • Readmissions or recurrent healthcare utilization after the acute episode but before 90 days

Rather than rolling up metrics into a global score, payers, patients and caregivers might review each of these measures separately and weight them based on their own priorities. The reduction in number of metrics tracked along with a greater focus on disease-specific progression should help providers focus on those interventions that make a difference rather than trying to perform well on dozens of metrics that may not have any impact on the patient’s quality or quantity of life.

Using this limited set of metrics could also help payers make more informed decisions about what physician groups or medical systems to contract with for specific clinical conditions. Practice A may be great for hypertension and thryoid disease, but not so good with gastric cancer follow-up. Health system 2 might manage congestive heart failure well, but struggle with back surgery. Obtaining greater clarity around provider performance might also help providers see their own performance improves over time.