Innovaciones Tecnologías para la Salud y el Bienestar

MIlano, 26th August 2015

Diabetes care related process modelling using Process Mining techniques. Lessons learned in

the application of Interactive Pattern Recognition:

coping with the Spaghetti EffectCarlos Fernandez-Llatas, Antonio Martinez-Millana, Alvaro

Martinez-Romero, Jose Miguel Benedí and Vicente Traver

Where is the pain?

- The worldwide prevalence of Diabetes was estimated around 8.3% among adults between 20-80*

- Self management improves quality of life of patients

- Personalisation requires evidence (EBM)- Evidence needs to be extracted from available

data to suggest/define new care processes/Life Assistance Protocols for diabetes management

* L. Guariguata, D. R. Whiting, I. Hambleton, J. Beagley, U. Linnenkamp, and J. E. Shaw. Global estimates of diabetes prevalence for 2013 and projections for 2035. Diabetes Research and Clinical Practice, 103(2):137–149, February 2014

Need to design new care processes /Life Assistance Protocols

Process standardizationAutomation and traceabilityMeasure and optimization

Workflows as automation languageComplete, unambiguous formal processes Expressivity vs understandability

Difficulties in the process design using workflowsComplete and explicit definition neededDifferences between current and perceived processHigh time consumingDeep knowledge of representation language

Interactive Pattern Recognition

Process Mining

Process MiningObtain a model from the execution logsCorpus

Set of workflow execution logs used to train the modelOur Vision: Activity-Based Workflow Mining

Parallel Activity-based Log Inference Algorithm (PALIA)…27/05/2013 19:31:18.65 => i:9 Fin Accion: FirstTriageResult Res: ACUTE27/05/2013 19:31:18.68 => i:9d4fcabf Nodo: Get BP -> InicioAccion: getBloodPressure27/05/2013 19:31:18.69 => i:9d4fcabf Nodo: Get BP -> InicioReloj: clk427/05/2013 19:31:18.71 => i:9d4fcabf Nodo: Get Temp -> InicioAccion: getTemperature27/05/2013 19:31:18.72 => i:9d4fcabf Nodo: Get Temp -> InicioReloj: clk327/05/2013 19:31:18.83 => i:8229056d Fin Accion: FirstTriageResult Res: ACUTE27/05/2013 19:31:18.88 => i:8229056d Nodo: Get BP -> InicioAccion: getBloodPressure27/05/2013 19:31:18.90 => i:8229056d Nodo: Get BP -> InicioReloj: clk427/05/2013 19:31:18.91 => i:8229056d Nodo: Get Temp -> InicioAccion: getTemperature27/05/2013 19:31:18.93 => i:8229056d Nodo: Get Temp -> InicioReloj: clk327/05/2013 19:31:19.47 => i:1a5c92f6 Fin Accion: getTemperatureResult Res: FEVER27/05/2013 19:31:20.19 => i:aa3380da Fin Accion: getTemperatureResult Res: OK27/05/2013 19:31:20.27 => i:aa3380da Nodo: TEMP OK -> InicioAccion: 27/05/2013 19:31:20.38 => i:aa3380da Fin Accion: getBloodPressureResult Res: OK27/05/2013 19:31:20.40 => i:aa3380da Nodo: BP OK -> InicioAccion: 27/05/2013 19:31:20.41 => i:aa3380da Nodo: Quality Test -> InicioAccion: QualityTest…

Uses of Process Mining

Using workflows to describe Clinical Pathways/Care processesFacilitate the praxis of health professionalsImprovement of quality of careUnify criteriaHelp the administrative management of clinical processes

Process Mining can infer the real deployment of processesComputer Aided Design of Clinical PathwaysClinical Pathways tracing

Detect bottlenecksCost effectiveness study of care processesMeasure adherence of Clinical Pathways instances

Processes deployment supportIndividualized behavior modeling

Process Mining Lifecycle

Spaghetti Effect

This is not useful at all!

Spaghetti Effect

This is not useful at all!

Recommended practices: Using Space-Efficient Structures

Petri netDeterminate Finite Automation DFA

Recommended practices: Time Abstractions

Use of discrete time variables to reduce Spaghetti effect

Recommended practices: Rendering Algorithms

Based on different profiles/priorities

Recommended practices: Clustering

Showing the different paths and frequencies to know more about the problem and find a better solution

Recommended practices: Workflow layout and navigation

Discussion/Conclusions

Process Mining can be used to support clinical pathways design and traceabilityThe Spaguetti Effect is a well known problem that affects critically the application of process mining to healthThe use of such recommended practices allows a mitigation of the spaguetti effect making process mining techniques usable in clinical scenarios

The application of Interactive Pattern Recognition Technologies in the continuous following of patients with diabetes could be a very interesting alternative to manual creation of Clinical Pathways (or Life Assistance Protocols) offering not only a way to support the design of those protocols but also support the deployment of these protocols, offering a way to continuously improve them and tracking the patient throughout all the process.

Innovaciones Tecnologías para la Salud y el Bienestar

Vicente Traver @vtravervtraver@itaca.upv.es

MIlano, 26th August 2015

Diabetes care related process modelling using Process Mining techniques. Lessons learned in the application of

Interactive Pattern Recognition: coping with the Spaghetti Effect

Questions ?