From the onset, we knew we would not be able to measure quality of care in its entirety and that we would need to take some difficult decisions and make some compromise.
Figure 2. Development process of QOMS

1. Which subspecialties or areas of OMFS practice should be included?
The main considerations for a subspecialty to be considered for inclusion in QOMS were that:
- It should not be an obscure or minor area of practice
- No other dedicated audit or registry was already in place (e.g. the cleft audit, the BATS TMJ Replacement audit)
- Variations in care is present
- Standards already exists or not
2. Which procedure(s) and conditions to be considered?
The volume and risk associated to a condition or a procedure are important factors that dictate the type of quality-of-care indicators that are relevant:
- Low-volume and low-risk procedures (e.g. Sistrunk procedure): no SMART indicators
- Low-volume and high-risk procedures (e.g. craniosynostosis surgery): Structural measures*
- High-volume and low-risk procedures (e.g. orthognathic surgery): Structural or process measures*
- High-volume and high-risk procedures (e.g.: major head and neck cancer resection with flap repair): process or outcomes measures*
Table 1. Types and definitions of quality-of-care measures
Figure 3. Volume and risks of procedures and conditions

3. Which quality of care indicators to be included?
SMART is an acronym that describes the criteria quality-of care indicators should fulfill:
- Specific to OMFS
- Measurable and readily accessible (this means it must rely on collecting information regularly documented in clinical care)
- Actionable by the surgical team
- Relevant to the surgical team, patients and/or the commissioners.
- Timely as the value of data decreases with time.
Figure 4. Characteristics of quality-of-care indicators

What does QOMS want to achieve and how?
- Produce information on the quality of care received by patients undergoing oral and maxillofacial surgery in NHS hospitals.
QOMS plans to identify best performers against any given metric across the NHS, quality assure that data and then generalise the care practices that underpin it by case studies, newsletters, presentations at conference, as well as BAOMS website content. Where performance falls significantly below the average, and data checking confirms that to be the case, BAOMS intends to provide mentorship for change.
- Ensure that any change or improvements to OMFS services benefit patients.
- Learn about the best ways in which surgical teams can use patient information to improve quality of care.
- Understand better what happens to patients after they leave hospital following surgery, and whether the surgery has had a beneficial effect on their longer-term health and wellbeing.
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