A process measure tracks what a healthcare provider actually does when delivering care. It captures the specific actions, treatments, and services performed for patients, then expresses them as a rate or percentage. For example, “the percentage of people with diabetes who had their blood sugar tested and controlled” is a process measure. The majority of healthcare quality measures used for public reporting are process measures, making them one of the most common tools for evaluating how well a hospital or clinic performs.
Where Process Measures Fit: The Donabedian Model
Healthcare quality measurement follows a framework developed by physician and researcher Avedis Donabedian. His model divides quality measures into three categories: structure, process, and outcome. Understanding all three clarifies what makes process measures distinct.
Structure measures assess the resources and systems a provider has in place before care even begins. Think of them as the foundation: whether a hospital uses electronic medical records, the ratio of providers to patients, or the proportion of board-certified physicians on staff. These tell you about capacity, not performance.
Process measures capture what happens during care. They reflect whether providers followed evidence-based clinical recommendations. The percentage of patients receiving preventive services like mammograms or immunizations, or the percentage of stroke patients prescribed blood-thinning therapy at discharge, are both process measures. They answer a simple question: did the right thing get done?
Outcome measures look at results. Surgical mortality rates, hospital-acquired infection rates, and complication rates all fall here. Outcomes might seem like the gold standard for measuring quality, but they reflect many factors beyond a provider’s control, including a patient’s age, overall health, and social circumstances. That’s one reason process measures remain so widely used: they isolate what the provider did, rather than blending provider actions with everything else that affects a patient’s health.
Real-World Examples
Process measures show up across nearly every area of healthcare. In preventive care, they track how many eligible patients received screenings or vaccinations. In chronic disease management, they monitor whether patients with conditions like diabetes are getting the recommended lab tests and follow-up visits.
In hospital settings, process measures tend to be more specific and time-sensitive. The Centers for Medicare and Medicaid Services (CMS) requires hospitals to report on a range of process measures for quality scoring and reimbursement. For 2025, these include:
- Stroke care: Whether ischemic stroke patients with atrial fibrillation are prescribed anticoagulation therapy at discharge, and whether antithrombotic therapy is administered by the end of hospital day two.
- Blood clot prevention: Whether hospitalized patients (including ICU patients) receive preventive treatment for blood clots on the day of admission or the day after.
- Opioid safety: The proportion of patients discharged on two or more opioids at the same time, or an opioid combined with a sedative. A lower rate indicates safer prescribing.
Each of these is expressed as a percentage of eligible patients who received (or didn’t receive) a specific action. That percentage becomes the performance rate a hospital is scored on.
Why Process Measures Are So Widely Used
Process measures have a practical advantage: they point directly to what can be changed. If a hospital’s rate of blood clot prevention is low, the fix is clear. Improve the protocol for administering preventive treatment on admission. Outcome measures, by contrast, can flag a problem without revealing its cause. A high surgical complication rate could stem from poor technique, sicker patients, inadequate staffing, or a dozen other factors.
As researchers at Johns Hopkins have noted, validated process measures illuminate exactly which provider actions could be changed to improve patient outcomes. They turn quality improvement from a vague goal into a concrete checklist. They also provide faster feedback. Outcome data often takes months to accumulate in meaningful volumes, while process data can be reviewed in near real-time, especially when pulled automatically from electronic health records.
How Performance Is Scored
CMS uses benchmarks to compare a provider’s process measure performance against national data. Each measure has a set of deciles based on how other providers performed. If your rate falls in the sixth decile, for instance, you earn between 6 and 6.9 points for that measure. Higher deciles earn more points, and those points factor into reimbursement and public quality ratings.
Organizations also use control charts to track their own process measures over time. These charts plot performance data sequentially and flag meaningful patterns. Eight consecutive data points above or below the average line signals a genuine shift in performance, not random variation. Six consecutive points trending in one direction signals a trend. These rules help quality teams distinguish real improvement (or decline) from normal fluctuation.
Limitations and Unintended Consequences
Process measures have real blind spots. The most fundamental: completing a recommended action doesn’t guarantee a better outcome for the patient. A hospital can prescribe the right medication to every eligible patient and still see poor results if, say, patients can’t afford to fill their prescriptions after discharge.
There’s also the risk of distorted priorities. A qualitative study of British general practitioners identified four unintended consequences of quality measures: measure fixation, where providers overemphasize specific measured aspects of care at the expense of unmeasured ones; tunnel vision, where important context gets lost because attention narrows to the metric; misinterpretation of what the numbers actually mean; and gaming, where providers find ways to inflate their scores without genuinely improving care.
Measure fixation is particularly relevant to process measures. When a hospital is scored on whether stroke patients receive a specific medication by day two, the care team may focus intensely on that checklist item while spending less attention on other aspects of stroke recovery that aren’t being measured. The measure becomes the goal rather than a proxy for good care.
Process Measures vs. Outcome Measures
The choice between process and outcome measures isn’t either/or. They serve different purposes and work best together. Process measures are most useful when there’s strong evidence linking a clinical action to better outcomes, when you need fast feedback, and when you want to identify exactly where care breaks down. Outcome measures are more useful when you want to capture the overall effectiveness of care, including factors no single process measure covers.
For someone evaluating a hospital or clinic, process measures tell you whether the care team follows best practices consistently. Outcome measures tell you how patients actually fared. A hospital with strong process measure scores and weak outcomes may be dealing with a sicker population or gaps in care that current measures don’t capture. A hospital with weak process scores and decent outcomes may be getting lucky, or may serve a healthier population that does well despite inconsistent care. Neither type of measure tells the full story alone.