Health care quality process measures

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Health care quality process measures are often used to recommend guidelines for clinical practice based on consensus or scientific evidence [1]. Quality measures are defined by the Pennsylvania Health Care Quality Alliance as metrics, indicators, or ratings which provide information in regards to the quality of care that patients are receiving in a particular setting . [1] A process measure is a type of quality assessment. The data acquired from process measures can be incorporated into clinical information systems via the electronic health record. It is a useful tool to enhance clinical decision support [1] [2].

Standardization of Process Measures

Evidence based research is used to create guidelines for healthcare. Once guidelines are developed, standardization of process measures can be achieved. The following formula is one way to explain this [2]:

     Number of Patients Who Receive Care/Number of Patients Eligible 
     to Receive Care=Y
     Y multiplied by 100=Percentage of Patients Who are in
     Accordance with the Guideline 

This would allow a quality assessment comparison of what was actually done to what should have been done. Once the results of process measures have been determined, the reasons why that measure was performed or not performed can be evaluated further. [3] Process measures can be tracked as part of the electronic health record [3]. Thus making results and alerts easily accessible to providers.

An applicable example would be an emergency room guideline that requires a tetanus vaccine for patients seen that have been injured by a nail or screw. If in the month of June, 10 patients visited the emergency room after being hurt by a nail and 7 received the vaccine, then the percentage of patients in accordance with the guideline would be 70%. This information should be kept in the electronic health record (EHR). If the patient is seen again within 10 years, he/she should not be given the vaccine. However, if the patient is seen again after 10 years, regardless of the reason, an alert in the EHR should prompt the provider to administer the vaccine.

Possible reasons why the Accordance of guideline was not 100% in the above example include: tetanus vaccination within 10 years, allergy to vaccination, or patient refusal.


  1. Can be used to provide feedback for quality improvement initiatives [3] [4]. It also provides information that is actionable, what is being done well or what needs improvement according to Rubin et al [3]. It gives the ability to accurately reflect the care that clinicians are providing.
  2. Minimal risk adjustment for patient illnesses [3]. A process measure requires defining a population that is eligible to receive the intervention [3] [5]. For example, patient population to receive antihistamine upon admittance to the emergency room for allergic reaction.
  3. Data collection can be done when clinical process is occurring [3]. This eliminates the need for additional tracking of patients for data collection.


  1. May be difficult to specify population eligible for a process [3]. There may be many exclusions, such as diabetic patients with congestive heart disease and poor renal function would potentially not be allowed a specific drug to treat an infection due to contraindications.
  2. Not as valued to patients and non-clinicians [3]. Patients believe it is the providers responsibility to perform appropriate care and are only concerned about outcome as stated by Rubin et al [3]. Patients may not be aware of what processes are chosen or why.

Relationship between Process Measures and Outcome Measures

There is a strong relationship between outcome and process measures. An outcome measure is the patient's health status as a result of receiving medical care. The outcome measure is important to determine how the health care treatment received influenced the result [3] [4] [5]. Mortality rate is an outcome measure. The reason for mortality in a patient usually relies on complex risk adjustment. Outcome measures are often more difficult than process measures to quantify the quality of care due to the amount of multiple factors that may be involved. Outcome measure calculations are usually based on specific groups or populations.

For example, if a process measure answers the question of did the patient receive the right care [2], an outcome measure answers the question of did the patient respond favorably to the treatment [2]. Therefore, the information obtained from both process measures and outcome measures collectively gives a comprehensive assessment of healthcare quality.

This can be summarized below from the Pennsylvania Health Care Quality Alliance:

  1. Process measures assess whether specific health care services are provided to an individual who needs them based on their conditions and place of treatment [1].
  2. Outcome measures assess how patients actually respond during and after their treatment [1].
  3. Outcome measures attempt to gauge the comprehensive result of multiple health care services (or processes) provided to an individual [1].


The Donabedian model, which was originally developed by Avedis Donabedian [6], proposed that structures, processes and outcomes should be measured in order to ascertain the quality of health care [5]. The Institute of Medicine's framework for healthcare quality utilizes the process and outcome measures of the Donabedian model [3]. The IOM's principles for healthcare quality include:

  1. the ability to determine the effect of health care on desired outcomes [3]
  2. the ablility to use processes that are evidence based or have a professional concensus [3]

Together, the foundational Donabedian model and the current principles of the Institute of Medicine supply growth and opportunity for health care quality process measures to become instrumental for improvement to patient care.


  1. 1.0 1.1 1.2 1.3 1.4 1.5 Pennsylvania Health Care Quality Alliance. Quality measures.
  2. 2.0 2.1 2.2 2.3 Behavioral and Social Sciences Research. Evaluating the quality of health care.
  3. 3.00 3.01 3.02 3.03 3.04 3.05 3.06 3.07 3.08 3.09 3.10 3.11 3.12 3.13 Rubin HR, Pronovost P, Diette G. The advantages and disadvantages of process-based measures of health care quality.
  4. 4.0 4.1 Harris AH, Kivlahan DR, Bowe T, Finney JW, Humphreys K. Developing and validating process measures of health care quality: an application to alcohol use and disorder treatment.
  5. 5.0 5.1 5.2 Mant J. Process versus outcome indicators in the assessment of quality of health care.
  6. Sunol R. Avedis Donabedian. International Journal for Quality in Health Care. 2000;12(6):451-454.