SNOMED CT Data, Business Intelligence Tools. Tom Seabury NHS Connecting for Health Crown copyright 2013

Transcription

1 SNOMED CT Data, Business Intelligence Tools Tom Seabury NHS Connecting for Health Crown copyright 2013

2 Business Intelligence NHS Information Analysis and Reporting professionals - anecdotally (synopsis from just one discussion thread) A selection of BI Tools in secondary care SQL 2008 R1 complete stack Dynistics' Service Line Management Module graphical representation of its key financial performance measures SharePoint to deliver static reporting services reports IBM Cognos version 8 and10 the usual stack of SSAS, SSRS and recently Performance Point and PowerPivots to complement the reporting Tableau and Qlikview Strategy Companion's Analyzer etc. etc. Many other products and services are available None of the above is an endorsement

3 Business Intelligence NHS Information Analysis and Reporting professionals - Finance, operations anecdotally (synopsis from just one discussion thread) ICT A selection of BI Tools in secondary care SQL 2008 R1 complete stack Enterprise statistics Dynistics' Service Line Management Module graphical representation of its key financial performance measures SharePoint to deliver static reporting services reports IBM Cognos version 8 and10 the usual stack of SSAS, SSRS and recently Performance Point and PowerPivots to complement the reporting Tableau and Qlikview Strategy Companion's Analyzer etc. etc. Many other products and services are available None of the above is an endorsement Clinical process ICT Clinical outcomes?

4 Rudiments of Business Intelligence - OLAP tools On Line Analytic Processing [OLAP] Data is held for analysis by its Dimensions & Measures Presentation & interaction via Data Cube an array of numerous dimensions Dimensions are mostly (not always?) divided between exclusive classes Measures are mostly (not always?) aggregatable values

5 Measures Compare measures from banking, retail, manufacturing, sales data Measures: cash, unit volumes, mass, waste%, % of target, market share. Compare to clinical data Referral to treatment dwell time, clinical outcomes, Qualies added, wait list size, average bed occupancy, costs, weighted mortality rates and so many many more! Qualitative clinical outcomes banded into classes/ranges? Severity, likelihood & other contexts as measures or dimensions? Mild - Moderate Severe Deadly?

6 Dimensions Compare dimensions from banking, retail, manufacturing, sales data Enterprise unit, geography, time interval Compare to clinical data Stratified risk group, demographics, disease register status, comorbidities Drugs data are clearer cut * smaller information model

7 So (1 of 2) Exclusive categories are the norm for Business Intelligence tools, you must feed these in Exclusive categories are gained by some classification of data (by any of the methods mentioned elsewhere today) Data mapped to classifications 1:1 Classified based on knowledge content within SNOMED CT itself Tested against indicators : classified between in/out Too many categories inherent in your data? Roll up your data some SNOMED CT way?

8 So (2 of 2) Aggregatable measures are the norm for Business Intelligence tools, you must feed these in Measures associated with clinical data will often be Count of, time intervals, proportions, costs Beware any non-aggregatable measures e.g. probabilities, non linear measures

9 Summary (1 of 2) Generally: Data fed into Business Intelligence tools should be aggregatable should be from exclusive classes Normally

10 Keep in mind Confused semantics of data entry > predictable consequences Poor data (despite all best efforts etc. etc.) > predictable consequences

11 Summary (2 of 2) Specifically: Uncategorised data from any extensive terminology is not well suited to direct use in Business Intelligence tools Forcing exclusive categories (alone) onto the clinician at time of data entry is {? } SNOMED CT can be mapped to a good range of existing categorical schemes SNOMED CT can be rolled-up in a variety of ways