Aims: To highlight the limitations and challenges of combining primary and secondary care medicines datasets to understand medicines use across an Integrated Care System (ICS) footprint1
Background: To optimise the use of medicines within an ICS, analysis of multiple datasets is required. In primary care, medicines data is available through ePACT2 as dispensed data (NHS BSA), with data fields that include the number of patients and basic demographics. However, secondary care medicines data (SCMD) (excluding outpatient prescriptions) is only available as a national dataset in the form of stock control medicines data, either through the Secondary Care Medicines Dataset or Define/Refine (Rx-info)2. Stock control datasets do not contain the diversity of data fields available for primary care medicines.
Patients access hospital treatment beyond their ICS of residence, this cross border activity will be captured through contractual reporting, however it is not reflected in secondary care medicines usage data, so it cannot be assumed that this relates to the ICS population for which the secondary care provider is located.
Methodology: The proportions of cross ICS border hospital admissions & attendances, including treatment speciality, have been analysed for the North of England (NoE) ICSs. The preferred dataset for SCMD use would be ‘Electronic Prescribing and Medicines Administration’ data, but this is not available nationally. Data (FY 2021/22) obtained from the Hospital Episode Statistics (HES) data warehouse held by NHS Digital3 was obtained and amalgamated to present the residence of the patient, the place and speciality of hospital admission or attendance. Analysis of the patterns of hospital attendance in relation to the geographical residence of the patient, informed the limitations of combined medicines usage. This was extended to an analysis of carbon foot printing of anaesthetic gases across primary and secondary care in North-East North Cumbria (NENC) ICS.
Results: Of the total number of attendances and admissions in South Yorkshire ICS, 12.3% and 12.5% respectively are resident outside the ICS, the highest proportion across the NoE. In contrast, the NENC ICS has minimal out of area activity; 2.8% of attendances and 3.2% of admissions. Humber and North Yorkshire (HNY) ICS has the greatest disparity between the proportion of attendances and admissions (6.6% and 9.1%). Conclusions: The lower the cross-border activity, the more accurate the SCMD will be e.g. utilising the specialities information for NENC ICS, the percentage of out of area admissions and attendances that were either surgical or obstetrics (where anaesthetic gases are likely to be used), was 1.3% and 1.2% respectively. It is therefore a reasonable assumption that the corresponding stock utilisation in secondary care is nearly entirely due to the NENC population