1. Extending Temporal Databases to Deal with Telic/Atelic Medical Data Paolo Terenziani 1, Richard T. Snodgrass 2, Alessio Bottrighi 1, Mauro Torchio 3, Gianpaolo Molino 3 1 DI, Univ. Piemonte Orientale A. Avogadro, Alessandria, Italy 2 Department of Computer Science, University of Arizona, Tucson, AZ, USA 3 Lab. Informatica Clinica, Az. Ospedaliera S. G. Battista, Torino, Italy - The problem: an example - The problem: a general perspective - Need for a general (not ad-hoc) solution - The solution (sketch) (see AIME and IEEE TKDE papers) - Conclusions

2. Introduction - Temporal information plays a basic role in Medical data - Need for suitable data models and query languages - Many approaches (mostly extensions/modifications of relational model) - Lack of specific supports makes the task of managing medical temporal data quite complex - All approaches share the same limitation: the underlying semantics is point-based, so that telic (medical) data connot be properly dealt with

3. The problem: an example John had two i.v. infusions of the drug Y, one starting at 10:00 and ending at 10:50, and the other from 10:51 to 11:30 (all extremes included) ; John had an i.v. of drug Z from 17:05 to 17:34, Mary had two i.v. infusions of Z, one from 10:40 to 10:55 and the other from 10:56 to 11:34, Ann had an i.v. from 10:53 to 11:32. Point-based semantics 10:00 10:01 ……

4. The problem: an example NOTICE (1): All approaches in the literature adopt point- based semantics, even if they adopt different representations Point-based semantics 10:00 10:01 …… 10:50, 10:51, e.g., TSQL2

5. The problem: an example Point-based semantics 10:00 10:01 …… 10:50, 10:51, Answers must be based on the semantics of data (and not on the representation!) Some pieces of information cannot be captured in any approach based on point based semantics!

6. The problem: an example UPWARD INHERITANCE (Q1)Who had one i.v. of Y lasting more than 1 hour? Answer: { } COUNTABILITY (Q3)How many i.v. did John have? Answer: 2

7. The problem: a general perspective Not only a problem in case of consecutive time intervals! PROJECTION e.g., Select Drug, VT from PHLEBO GRANULARITY CHANGES e.g., Scale up to hours

8. The problem: a general perspective Telic vs atelic facts Aristotle: Telic facts (countable, no upward inheritance, ……) (e.g., i.v. infusion) Atelic facts (not-countable, upward inheritance, …..) (e.g., patient X having a temperature > 38) Cognitive Science (e.g., [Bloom et al., 80]) … and, more recently, in AI Linguistics (e.g., [Bennet & Partee, 78]) NOTICE: Classical TDB approaches (and point-based semantics) perfectly cope with atelic facts!

9. Need for a general (not ad-hoc) solution Analogous to the question: why not just adding an additional attribute to relational tables to deal with validity times? … about 15 years of DBT reasearch responding to the second question! Basically: -time is a special status, and deeply impacts the semantics of the other attributes -thus, it needs a specialised treatment (e.g, definition of the temporal algebraic operators) - ad-hoc solutions are: difficult, likely to be erroneous, not economical, not compatible e.g., Why not just adding an additional (surrogate) attribute to keep all occurrences of telic tables separate?

10. Need for a general (not ad-hoc) solution A further problem: aktionsart coercions E.g., progressive forms coerce telic statements into atelic ones John had an i.v. infusions starting at 10:00 and ending at 10:50 John was having an i.v. infusions at 10:30 What is the impact on TDBs? In short: general problems need to be solved once-and-forall in a general (not ad-hoc) way Ex.1Who was having an i.v. while John was having an i.v.? Ex.2Who had a (complete) i.v. while having an i.v.?

11. Our solution: Point-based + Interval-based Semantics Interval-based semantics for telic facts (e.g., i.v. infusion) Coercion functions to switch from a interval to point semantics, and viceversa [10:00 – 10:50] [10:40 – 10:55] [10:51 – 11:30] …… Point-based semantics for atelic facts (e.g., temperature > 38) 10:00 10:01 10:02, ……

12. Our solution: Data model: telic + atelic tables Telic tables for telic facts (e.g., i.v. infusion) Atelic tables for atelic facts (e.g., temperature > 38) Also non-temporal (snapshot) tables

13. Our solution: Three-sorted algebra Telic algebraic operators Atelic algebraic operators Non-temporal (snapshot) operators Coercion functions [Terenziani & Snodgrass, 04] IEEE Transactions on Knowledge and Data Engineering, 16(4), 540-551, April 2004.

14. Our solution: Query language Extension to TSQL2: AIME05 paper Limited extensions to the language are sufficient (substantial extensions in the semantics) TELIC SELECT P2.P_CODE FROM T_PHLEBO (ATELIC PERIOD) AS P, T_PHLEBO (PERIOD) AS P2 WHERE P.P_CODE='John' AND P.Drug=' Y ' AND P CONTAINS P2 Ex. Who had one (complete) i.v., while John was having an Y i.v.?

15. Our solution: Query language Principled and general solution, and increased expressiveness without much user effort (only limited extensions to the query language)! TELIC SELECT P2.P_CODE FROM T_PHLEBO (ATELIC PERIOD) AS P, T_PHLEBO (PERIOD) AS P2 WHERE P.P_CODE='John' AND P.Drug=' Y ' AND P CONTAINS P2 T_PHLEBO ATELIC(T_PHLEBO) P P.P_CODE=John, … P CONTAINS R1 TELIC P2