Extending computer guideline system with advanced AI and DB facilities Alessio Bottrighi

Alessio Bottrighi 's Ph.d. Dissertation A clinical guidelines is sistematically developments statemnts to assist pratictioners and patient decision about appropriate health care for specific clinical circumstance Alessio Bottrighi 's Ph.d. Dissertation

Alessio Bottrighi 's Ph.d. Dissertation Our work Decision theory support Model checking in clinical guidelines Cooperative update Alessio Bottrighi 's Ph.d. Dissertation

Decision System Support decision making is a central issue in clinical practice. it is frequent that it is not possible define if an alternative is really “better” than other, for a clinical point of view Alessio Bottrighi 's Ph.d. Dissertation

Decision System Support: our work We made a systematic analysis of main clinical guidelines representation primitives We made the mapping of representation primitives into Markov Decision Process. We studied how algorithms for evaluating utility and for evaluating the optimal policy can be exploited in clinical guidelines context As case of study, we have applied our general approach to the GLARE system Alessio Bottrighi 's Ph.d. Dissertation

Decision System Support: publication S. Montani, P. Terenziani, A. Bottrighi, Exploiting decision theory for supporting therapy selection in computerized clinical guidelines, Proc. European Conference on Artificial Intelligence in Medicine (AIME) 2005, July 2005 P. Terenziani, S. Montani, A. Bottrighi, M. Torchio, G. Molino, G. Correndo, Managing clinical guidelines contextualization in the GLARE system, Proc. Congresso Nazionale dell'Associazione Italiana per l'Intelligenza Artificiale (AI*IA) 2005, September 2005 Alessio Bottrighi 's Ph.d. Dissertation

Model checking in clinical guidelines improving the quality of clinical guideline the capabilities verification available in the guideline systems is usually rather limited defining a general mechanism to evaluate the quality of clinical guideline Alessio Bottrighi 's Ph.d. Dissertation

Model checking in clinical guidelines: our work We had mapped the behaviour of a clinical guideline into a formalism accepted by the model checker (the SPIN model checker) We have defined a comprehensive framework in which a computer-based approach to clinical guidelines is developed using an agent-based technology We have identified the types of properties that are useful to verify about a clinical guideline As case of study, we have applied our general approach to the GLARE system Alessio Bottrighi 's Ph.d. Dissertation

Model checking in clinical guidelines: publication P. Terenziani, L. Giordano, A. Bottrighi, S. Montani, L.Donzella, Spin Model Ckecking for the verification of Clinical Guidelines, Workshop on AI techniques in healthcare: evidence-based guidelines and protocols, ECAI 2006, August 2006 L. Giordano, P. Terenziani, A. Bottrighi, S. Montani, L. Donzella, Model checking for clinical guidelines: an agent-based approach, American Medical Informatics Association (AMIA), November 2006 Alessio Bottrighi 's Ph.d. Dissertation

Cooperative Update: introduction (1) Important, e.g. software development Multiple alternative proposals Selection Software engineering tools Analogous problems using Database to model complex domains Alessio Bottrighi 's Ph.d. Dissertation

Cooperative Update: introduction (2) The case of clinical guidelines: General guideline proposed by a standardization committee Proposals of update Local contextualization New therapies Evaluation of proposals Guideline to be stored in a DB Alessio Bottrighi 's Ph.d. Dissertation

Cooperative Update: introduction (3) Augmenting DB approaches to support cooperative work, i.e.: distinction between two phases: proposals and acceptance/rejection history of the evolution of the proposals alternative proposals Alessio Bottrighi 's Ph.d. Dissertation

Cooperative Update: introduction (4) Both validity time and transaction time should be supported “Consensus” approach (TSQL2) with a high-level semantics (BCDM) BCDM supports several Temporal Database implementations (not only TSQL2) Alessio Bottrighi 's Ph.d. Dissertation

Cooperative Update: goal Extending BCDM to support cooperative updates Propose vs accept/reject Alternative proposals of updates Alessio Bottrighi 's Ph.d. Dissertation

Cooperative Update: criteria (1) Under-constrained policy: Super user vs user Super user operations: standard + accept/reject proposals User operations: delete (not proposals) insert update (chains allowed) Alessio Bottrighi 's Ph.d. Dissertation

Cooperative Update: criteria (2) “Minimal” extension of BCDM: Upward compatibility (manipulation operations) Reducibility (algebra) Alessio Bottrighi 's Ph.d. Dissertation

Cooperative Update: our work Data model Manipulation operations Algebra Alessio Bottrighi 's Ph.d. Dissertation

Cooperative Update: data model (1) Two data levels needed: Super users (accepted) data User proposals Observe that proposals need to be maintained and affect super-user data only if/when accepted Alessio Bottrighi 's Ph.d. Dissertation

Cooperative Update: data model (2) Authoring: author as a data attribute Basically a “standard” data attribute (however, author cannot be modified) Alessio Bottrighi 's Ph.d. Dissertation

Cooperative Update: data model (3) Super user data: Standard BCDM semantics User proposals data: For each super-user relation r: insert(r) delete(r) update(r) Alessio Bottrighi 's Ph.d. Dissertation

Cooperative Update: data model (4) insert(r) is a set of standard BCDM tuples delete(r) is a set of standard transaction-time tuples Alessio Bottrighi 's Ph.d. Dissertation

Cooperative Update: data model (5) Update involves: An origin tuple to be updated (time not needed) A new temporal tuple (standard BCDM tuple) Alessio Bottrighi 's Ph.d. Dissertation

Cooperative Update: data model (6) Semantic interpretation: disjunctive set of alternative proposals (each one is a BCDM tuple) Alessio Bottrighi 's Ph.d. Dissertation

Cooperative Update: data model (7) Definition: proposal tuple pt = <o, Alt{alt1,alt2,..,altk}> an origin o a non empty set Alt{alt1,alt2,..,altk} of (bi)temporal tuples Observe that Alt{alt1,alt2,..,altk} is a disjunctive set of mutually exclusive tuples referring to the origin o, representing the different proposals of update concerning o. Alessio Bottrighi 's Ph.d. Dissertation

Cooperative Update: data model (8) proposal(r) is a set of Proposal-tuples Alessio Bottrighi 's Ph.d. Dissertation

Cooperative Update: manipulation operation (1) User: propose_update propose_insert propose_delete Alessio Bottrighi 's Ph.d. Dissertation

Cooperative Update: manipulation operation (2) Super-user: accept_update, accept_insert, accept_delete reject_update, reject_insert, reject_delete confirm Alessio Bottrighi 's Ph.d. Dissertation

Cooperative Update: manipulation operation (3) E.g.: propose_update(r,origin,old,new,VT) Alessio Bottrighi 's Ph.d. Dissertation

Cooperative Update: manipulation operation (4) E.g.: propose_update(r,origin,old,new,VT) IF admissible IF  ptproposal(r) with origin(pt)=origin THEN add <origin, <new,user,UCVT>> in proposal(r) insert a new propoasal tuple IF  ptproposal (r) with origin(pt)=origin  ( a1  alternatives(pt)\ a1 value equivalent to ‘new’ OR  a1  alternatives(pt)\ a1 value equivalent to ‘new’  user(a) user) THEN add ‘new’ to alternatives(pt) insert a new proposal into an existing proposal-tuple user(a) = user THEN add (UCVT) to the bitemporal of a1 update previous proposal Alessio Bottrighi 's Ph.d. Dissertation

Cooperative Update: manipulation operation (5) Admissibility of propose_uptade operation origin: in r or in insert(r)  current old: old (old=origin OR old origin)  current new: ( tuple t r  current  t value equivalent to ‘new’  t value equivalent to origin)   proposal value equivalent to t with same VT Alessio Bottrighi 's Ph.d. Dissertation

Cooperative Update: manipulation operation (6) Condition on ‘new’: example r: {<a,u,Ta>,<b,u,Tb>,…..} (r is a super-user relation) Admissible update: a,u  <a,u’,T’> NOT admissible: b,u  <a,u,T’>

Cooperative Update: manipulation operation (7) E.g.: accept update proposal IF admissible IF  tr \ t value equivalent to origin  current(t) THEN DELETE(t); INSERT(new); close UC to all alternative proposals concerning origin IF  tr \ t value equivalent to origin  current(t)   tinsert(r) \ t value equivalent to origin  current(t) THEN INSERT(new); close UC to all alternative proposals concerning origin admissible:  ptproposal(r) with origin(pt)=origin  newalternatives(pt)  current(new)  [( tr \ t value equivalent to new  current(t))  t value equivalent to origin] Alessio Bottrighi 's Ph.d. Dissertation

Cooperative Update: algebra(1) Standard BCDM algebraic operations for super-user and for insert(r), delete(r) New algebraic operations on Proposal-relations Alessio Bottrighi 's Ph.d. Dissertation

Cooperative Update: algebra(2) E.g.: natural join: r⋈A s = { z=<origin(z),alternatives(z)> \ IF $pt1Îr , $pt2Îs \ origin(pt1)[A]= origin(pt2) [A] $a1Îalternatives(pt1), $a2Îalternatives(pt2) \ a1[A]=a2[A] Ù a1[T]a2[T]  THEN origin(z)[A]=origin(pt1)[A] Ù z[B]=origin(pt1)[B] Ù z[C]=origin(pt2)[C] Ù altÎalternatives(z), where alt[A]=a1[A]=a2[A] Ù alt[B]=a1[B] Ù alt[C]=a2[C] Ù alt[T]=a1[T]a2[T] } Alessio Bottrighi 's Ph.d. Dissertation

Cooperative Update: algebra(3) Definition: convert convert(proposal(r))={(a1,..,a1,u, a’1,…,a’n,u',T)\ ptproposal(r) \(a1,…,an,u)=origin(pt) (a’1,…,a’n,u’)=alternatives(pt) } Alessio Bottrighi 's Ph.d. Dissertation

Alessio Bottrighi 's Ph.d. Dissertation End Thanks!! Alessio Bottrighi 's Ph.d. Dissertation