Patient identification is a key part of both the old and new IAPT datasets. Patients need to be matched in successive months’ submissions so that the care pathways can be tracked for their full duration. Most patients are identified using their NHS number but where this is missing other demographic information is used to try and match a patient across different submissions. This is where the methodology change to patient identification occurs as the new process in v2.0 (called the Master Patient Service or MPS) involves using more demographic data than the method in v1.5 (called SLAB)
To see the impact of the different patient identification methods on the dataset, we need to look at how much the two methods have changed the proportion of referrals that are linked from one month to the next. The referral data between two months is linked by the pathway identifier for both methods. The pathway id itself is made up of the service request id from the provider’s system and the patient id from the SLAB or MPS algorithm. As the service request id must match between months for the same patient referral, a difference in the linkage between the two methods in the same month can only come about because the patient identification methods have differed.
Table 1. Percentage of open referrals at the end of the previous month linked by pathways in next month. Linked pathways include referrals where the patient has moved between providers. England level data, July to November 2020.
|Open referrals at end of previous month
|Linked pathways using SLAB
|Linked pathways using MPS
Table 1 shows the impact of using the two different methods on linking pathways between successive months from July to November 2020. Up to the implementation of the v2.0 of the dataset on 1st September, the SLAB methodology was used to link referral data across months. From September, the MPS algorithm has been used. However, the MPS algorithm has also been applied to patient data from before September. This allows us to compare the linkage of patient data between the two identification methods for submissions in July and August 2020.
The July and August 2020 columns in Table 1 show that the SLAB and MPS algorithms link data from the previous month’s open referrals at very similar rates with slightly more pathways linked using MPS in both months (189 more in July and 150 in August). This shows the impact of the different patient identification methodology in v2.0 is small, i.e. on the order of 100 to 200 referrals in a month. As the impact on linking data across months is so small, it follows that the impact on activity and outcomes, which involve tens of thousands of referrals every month, is also small.
Table 1 also shows the sharp drop in the proportion of linked pathways with the implementation of v2.0. September 2020 shows a drop to 95.6% as over 15,000 referrals from August were not linked. This is the impact of data quality issues in the submissions to the new dataset. It will include those referrals that weren’t submitted in September at all and those that did not pass the validation procedures during submission. Also, the open referrals from August that weren’t linked in September will include referrals where the demographic data submitted in September meant that the new MPS algorithm couldn’t match the patient details with the same service request id in August