In this section, you will find a broad range of resources and information on the quality agenda, split into 4 sections:

Quality Standards Data Collection

MSKPN continue to work with our members’ patient management software providers to ensure each of the recommended quality standards can be easily collected and consistently analysed. Templates are being developed to capture the recommended quality standards across the following providers.

A consistent set of patient and service level data is also required to enable meaningful analysis of MSKPN’s recommended quality outcomes. Each patient management software template in development is being developed to capture this data in a consistent format.

Consistently coding clinical condition/presentation codes to individual patient outcome data is fundamental to meaningful analysis. This will enable conclusions to be drawn to the level of clinical care required to achieve meaningful outcomes across the wide range of MSK conditions.

Clinical experience tells us that achieving a clinically important improvement following an ACL reconstruction requires more care than following a mild ankle sprain, but this level of consistent reporting will enable our industry to quantify this. As such, all templates are being constructed to ensure clinicians capture either ICD codes – International Classification of Disease ( or OSIICS codes – Orchard Sports Injury and Illness Classification System ( for each patient record. These codes can be matched using a resource available to members
(Orchard_ICD-Sports-Injury-and-Illness-Classification-System-v13.4) and as such members are advised to use whichever approach is preferred by your team.

OSIICS / ICD Coding Example:

An easy-to-use reporting function is also being developed with each patient management software provider to ensure each individual member organisations can monitor their clinical outcomes on a regular basis. MSKPN recommend monthly reporting, identifying all patients who have a completed data set of outcome data in the previous month. This approach will ensure each member clinic can build a clear picture of achieved clinical outcomes and understand variation across results.

A future ambition is the creation of a central data warehouse where consenting members can share anonymised data to create an industry dataset. This will allow all members to understand the industry average for each measure and their variance to this. Robust data sharing agreements will need to be established for this to ensure confidence in all supporting contributing members.