Data sources for UK Pharma Sales Analysts - Overview
1. Data sources for the Sales Analyst What’s out there and how to use it. Andrew Finnegan BHBIA Sales Analyst Foundation Training Sept 2011
2. This session 28/09/2011 Some background Which data sources are available to analysts Which sources are most commonly used - detail The rational use of these sources Reactive number cruncher v Valuable contributor to the business ? ?
6. Data sources 28/09/2011 Sales/Usage BPI/RSA/RxI HPA SCM Ex-factory DTP Homecare reports Etc… Patient/Rx Xponent CSD Longitudinal databases GPRD Etc… NHS/Gov’t QoF HES/SUS PROMS Census NHS IC FoI Etc… Not an exhaustive list!
7. Retail sales – Sourced from wholesalers 28/09/2011 BPI British Pharmaceutical Index National, monthly, all products and packs Projection to account for missing data Volume cashed up to NHS price Watch out for inclusion/exclusions Brand teams’ national monitoring of market Comparison of growth of different packs
8. Retail sales – Sourced from wholesalers 28/09/2011 RSA/RxI Same source as BPI, though different inclusion rules Regional, granular, monthly Projection/redistribution/chain estimation Volume cashed up to NHS price Watch out for inclusion/exclusions Sales team measurement (eg bonus schemes) Can vary geographical presentation level (down to surgery)
9. Retail sales – Sourced from wholesalers or internal 28/09/2011 SCM Same source as BPI, though different inclusion rules Outlet level, including hospitals No projection – ‘reality’ Volume cashed up to NHS price Commercial teams – eg chemist quotas Investigations of buying patterns DTP Only if you have a ‘direct to pharmacy scheme’ Outlet level, including hospitals, homecare etc No projection – ‘reality’ Volume and real prices Commercial teams – eg chemist quotas Investigations of buying patterns
10. Hospital Usage – Sourced from individual hospitals 28/09/2011 HPA From pharmacy stock control – usage by ward All products/packs monthly National – projected Regional – unprojected 90+% coverage in UK Own product at hospital level Competitor at ‘hospital brick’ Reputation as a ‘tricky’ dataset…. Hospital specialist team measurement Brand teams’ national monitoring of market
11. NHS sources 28/09/2011 HES/SUS Mandatory for English hospitals (PbR) Clinical coding of I/P, O/P and A&E Diagnosis, Procedures, Demographics High-cost drugs HES on-line Understanding incidence/opportunity Targeting of hospital resources Referral mapping
12. When to use which data source? 28/09/2011 Pay/Reward/Incentive Targeting Ops planning Local Business planning Corporate reporting Your thoughts Which sources to avoid
13. Sales Analyst as expert 28/09/2011 Understand the data sources – don’t just rely on vendors Get involved in the vendor management Understand and engage with your internal customers Never just deliver numbers – give your view Present your own work where you can
14. Data sources and the supply chain 28/09/2011 The following slides identify the main data sources available in pharma and their place within the product and data supply chain. Note these slides are about the source of the data, not its use (e.g. even though RSA is used as a analogue for GP prescribing demand, it is sourced from wholesale to chemists) As the pharma supply chain is complex and varies between products, each slide covers only that part of the chain that is relevant to the data product. We have widened out only where necessary for comparison.
15. Data sources and the supply chain BPI, RSA (RxI) and SCM 28/09/2011 Product Ex-factory Data source RSABPI RSABPI SCM SCM SCM
16. Data sources and the supply chain DTP (Direct To Pharmacy) 28/09/2011 Product Data source DTP DTP DTP
17. Data sources and the supply chain HPA 28/09/2011 Product SCM DTP Data source HPA HPA HPA HPA
18. Data sources and the supply chainPrimary care patient and Rx 28/09/2011 Xponent QoF GPRD, CSD… Patient + FP10 Patient + Product Patient
19. Data sources and the supply chainSecondary care 28/09/2011 SUS/HES Clinical Coding
Notes de l'éditeur
Pharma manufacturers (and other entities such as parallel importers) sell pharmaceutical product to wholesalers. It is the sum of these transactions that give the companies their ex-factory numbers. The raw figures will be volume and cash (net of discounts). Companies may also apply the full NHS price to the volume to get a full-price version of ex-factory that may allow for more accurate comparisons across regions. Ex-factory figures will only be available for a company’s own products (UK pack).Pharma wholesalers (e.g. Alliance Boots, AAH, Phoenix) then sell the product on to retail dispensers, delivering the product and offering discounts based on volume ordering. The pharma wholesalers sell the data (volume sales into dispensing outlets) to IMS and it is the sum of these datasets (after data cleaning and application of business rules) that produce BPI, RSA, RxI and SCM. These data products are then sold to pharma companies and others in various formats.
In the DTP distribution model, the pharma company does not sell its product to wholesalers, rather it sells directly to dispensing outlets and pays a logistics provider a fee for ‘carrying’ product to outlet. The key difference between this and the wholesaler model is that the product remains the property of the pharma company until it is delivered to the outlet. Because this model includes a financial relationship between manufacturer and outlet, the data available as a result should be much more detailed (daily sales etc). DTP figures will only be available for a company’s own products (UK pack).This dataset is particularly useful for commercial teams who may wish to impose quotas on pharmacy (which helps overall stock and demand management).
HPA (Hospital Pharmacy Audit) is the only UK national hospital data available that contains information on all products. Rather than recording the sales into hospitals, HPA records the usage in those hospitals by tracking the movement of pharmaceutical product out of hospital pharmacy to hospital ‘wards’ (these may be actual wards, outpatient departments or virtual wards that are set up to track usage in e.g. satellite hospitals or homecare). Over half of such product dispensing is to named patient (with the remainder being replenishment of ward stock), so it is a good approximation to real usage.Recording usage rather than sales has the advantage of not being vulnerable to buying peaks and troughs so, in theory, HPA should be a better indicator of demand that SCM or DTP hospital data. HPA uses the ward element of the information captured to split usage by specialty. Whilst HPA is generally robust and a very useful measurement tool for hospital products, the many data collection points and complex product and ward coding make it vulnerable to reporting errors and misinterpretation. You will need to keep an eye out for these.NB Hospitals must record homecare transactions somewhere (as, even though the product does not go via the hospital, the patient is still officially under the care of the hospital). If the hospital uses its pharmacy stock control system to record this channel, homecare will be included in the HPA numbers (though not differentiated as homecare); if the hospital uses a separate system, there will be no homecare recorded.HPA is available as a national or regional dataset. In the regional dataset, companies are allowed to see data on their own products at hospital level, with competitors shown at a hospital brick level.
Quality outcomes framework data is available from an online database. The data measures at a surgery level and provides patient numbers and other useful metrics based on the current performance measures in the GP contract. The data is sourced from the computer systems within GP surgeries.There are also several databases that use patient records sourced from GP systems to create longitudinal databases of patient treatment. Though tightly regulated, these databases (eg GPRD) can provide valuable information on the way diseases are treated and the associated outcomes.When patients leave the GP and have Rx dispensed at retail chemists, lots of information is recorded in the pharmacy computer system. Xponent from IMS and the equivalent CSD product taps into this data source to give a genuine record of Rx demand by geography.
In order to be paid for services they have provided, English hospitals must submit very detailed information on each patient intervention (system known as PbR – payment by results). All this information is pooled in the SUS (Secondary Uses Service) database and used to produce HES (Hospital Episode Statistics). This is a very rich data source that gives details on patient demographics, diagnoses, procedures and payment flows through secondary care. It can be accessed directly via HESOnline or via the many agencies that will package and interpret the data for companies.
