Dr. John Svirbely's blog post - Going from Zero to Success using BPM+ for Healthcare. 
                Part I: Learning Modeling and Notation Tools
Dr. John Svirbely, MD

Going from Zero to Success using BPM+ for Healthcare.

Part I:
Learning Modeling and Notation Tools

By Dr. John Svirbely, MD

Read Time: 3 Minutes

Welcome to the first installment of this informative three-part series providing an overview of the resources and the success factors required to develop innovative, interoperable healthcare workflow and decision applications using the BPM+ family of open standards. This series will unravel the complexities and necessities for achieving success with your first clinical guideline automation project. Part I focuses on how long it will take you to reach cruising speed for creating BPM+ visual models.

When starting something new, people often ask some common questions. One is how long will it take to learn the new skills required. This impacts how long it will take to complete a project and therefore costs. Learning something new can also be somewhat painful when we are set in our old ways.

Asking such questions is important, since there is often a disconnect between what is promoted online and the reality. I can give my perspective based on using the Trisotech tools for several years, starting essentially from scratch.

How long does it take to learn?

The simple answer – it depends. A small project can be tackled by a single person quite rapidly. That is how I got started. Major projects using these tools should be approached as team projects rather than something an individual can do. Sure, there are people who can master a wide range of skills, but in general most people are better at some things than others. Focusing on a few things is more productive than trying to do everything. A person can become familiar with the range of tools, but they need to realize that they may only be able to unlock a part of what is needed to automate a clinical guideline.

The roles that need to be filled to automate a clinical guideline with BPM+ include:

1 subject matter expert (SME)

2 medical informaticist

3 visual model builder

4 hospital programmer/system integrator

5 project manager

6 and of course, tester

A team may need to be composed of various people who bring a range of skills and fill various roles. A larger project may need more than one person in some of these roles.

The amount of time needed to bring a subject matter expert (SME) up to speed is relatively short. Most modeling diagrams can be understood and followed after a few days. I personally use a tool called the Knowledge Entity Modeler (KEM) to document domain knowledge; this allows specification of term definitions, clinical coding, concepts maps and rule definitions. The KEM is based on the SVBR standard, but its visual interface makes everything simple to grasp. Other comparable visual tools are available. The time spent is quickly compensated for by greater efficiency in knowledge transfer.

The medical informaticist has a number of essential tasks such as controlling terminology, standardizing data, and assigning code terms. The person must understand the nuances of how clinical data is acquired including FHIR. These services cannot be underestimated since failures here can cause many problems later as the number of models increase or as models from different sources are installed.

The model builder uses the various visual modelling languages (DMN, BPMN, CMMN) according to the processes and decisions specified by the SME. These tools can be learned quickly to some extent, but there are nuances that may take years to master. While some people can teach themselves from books or videos, the benefits of taking a formal course vastly outweigh the cost and time spent. Trsiotech offers eLearning modules that you can learn from at your own pace.

When building models, there is a world of difference between a notional model and one that is automatable. Notional models are good for knowledge capture and transfer. A notional model may look good on paper only to fail when one tries to automate it. The reasons for this will be discussed in Part 3 of this blog series.

The hospital programmer or system integrator is the person who connects the models with the local EHR or FHIR server so that the necessary data is available. Tools based on CDS Hooks or SMART on FHIR can integrate the models into the clinical workflow so that they can be used by clinicians. This person may not need to learn the modeling tools to perform these tasks.

The job of the project manager is primarily standard project management. Some knowledge of the technologies is helpful for understanding the problems that arise. This person’s main task is to orchestrate the entire project so that it keeps focused and on schedule. In addition, the person keeps chief administrators up to date and tries to get adequate resources.

The final player is the tester. Testing prior to release is best done independently of other team members to maintain objectivity. There is potential for liability with any medical software, and these tools are no exception. This person also oversees other quality measures such as bug reports and complaints. Knowing the modeling languages is helpful but understanding how to test software is more important.

My journey

I am a retired pathologist and not a programmer. While having used computers for many years, my career was spent working in community hospitals. When I first encountered the BPM+ standards, it took several months and a lot of prodding before I was convinced to take formal training. I have never regretted that decision and wish that I had taken training sooner.

I started with DMN. On-line training takes about a month. After an additional month I had enough familiarity to become productive. In the following 12 months I was able to generate over 1,000 DMN models while doing many other things. It was not uncommon to generate 4 models in one day.

I learned BPMN next. Training online again took a month. This takes a bit longer to learn because it requires an appreciation of how to design a process so that it executes optimally. Initially a model would take me 2-3 days to complete, but later this dropped to less than a day. Complex models can take longer, especially when multiple people need to be orchestrated and exception handling is introduced.

CMMN, although offering great promise for healthcare, is a tough nut to crack. Training is harder to arrange, and few vendors offer automatable versions. This standard is better saved until the other standards have been mastered.

What are the barriers?

Most of the difficulties that I have encountered have not been related to using the standards. They usually arise from organizational or operational issues. Some common barriers that I have encountered include:

1 lack of clear objectives, or objectives that constantly change.

2 lack of commitment from management, with insufficient resources.

3 unrealistic expectations.

4 rushing into models before adequate preparations are made.

If these can be avoided, then most projects can be completed in a satisfactory manner. How long it takes to implement a clinical guideline will be discussed in the next blog.

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What is FEEL?

FEEL (Friendly Enough Expression Language) is a powerful and flexible standard expression language developed by the OMG® (Object Management Group) as part of the Decision Model and Notation (DMN™) international standard.

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It is a valuable tool for modeling and managing decision logic in many domains, including healthcare, finance, insurance, and supply chain management. FEEL is designed specifically for decision modeling and execution and to be human-readable to business users, while still maintaining the expressive power needed for complex decision-making. Its simplicity, expressiveness, domain-agnostic functionality, strong typing, extensibility, and standardization make FEEL a valuable tool for representing and executing complex decision logic in a clear and efficient manner. Organizations using FEEL enjoy better collaboration, increased productivity, and more accurate decision-making.

What Are Expression Languages?

FEEL is a low-code expression language, but what is the difference between Expression Languages, Scripting Languages, and Programming Languages. They are all different types of languages used to write code, but they have distinct characteristics and uses.

Expression Languages

Expression languages are primarily designed for data manipulation and configuration purposes. They are focused on evaluating expressions rather than providing full-fledged programming capabilities. Expression languages are normally functional in nature, meaning that at execution the expression will be replaced by the resulting value. What makes them attractive to both citizen developers and professional developers is that they are usually simpler and have a more limited syntax compared to general-purpose programming languages and/or scripting languages. Due to their simplicity, expression languages are often more readable and easier to use for non-programmers or users who don’t have an extensive coding background. FEEL is a standard expression language.

Scripting Languages

Scripting languages provide abstractions and higher-level constructs that make programming using them easier and more concise than programming languages. They are usually interpreted rather than compiled, meaning that the code is executed line-by-line by an interpreter rather than being transformed into machine code before execution. Popular examples of scripting languages are Python, JavaScript, and Ruby.

Programming Languages

Programming languages are general-purpose computer languages designed to express algorithms and instructions to perform a wide range of tasks and create applications. They offer extensive features and capabilities for developing complex algorithms, data structures, and user interfaces. They offer better performance compared to scripting languages due to the possibility of compiling code directly into machine code. Examples of programming languages include C++, Java, and C#.

Is FEEL Like Microsoft Power FX (Excel Formula Language)?

FEEL and Power FX are both expression languages used for data, business rules, and expressions, but in different contexts. Power FX is a low-code programming language based on Excel Formula Language, tailored for Microsoft Power Platform, with some limitations in handling complex decision logic. As soon as the business logic gets a bit tricky, Power FX expressions tend to become highly complex to read and maintain. On the other hand, FEEL is a human-readable decision modeling language, designed for business analysts and domain experts, offering a rich set of features for defining decision logic, including support for data transformations, nested decision structures, and iteration. FEEL provides clear logic and data separation, making it easier to understand and maintain complex decision models.

While Power FX has a visual development environment in the Microsoft Power Platform, FEEL is primarily used within business rules and decision management systems supporting DMN and process orchestration platforms. FEEL is a language standard across multiple BPM and decision management platforms, providing interoperability, while Power FX is tightly integrated with Microsoft Power Platform services. For further comparison, Bruce Silver’s articles FEEL versus Excel Formulas and Translating Excel Examples into DMN Logic.

FEEL Benefits for Technical people and for Business people.

Technical Benefits of FEEL

Decision focus language

FEEL is designed specifically for decision modeling and business rules. It provides a rich set of built-in functions and operators that are tailored for common decision-making tasks. This decision focus nature makes FEEL highly expressive and efficient for modeling complex business logic.


FEEL supports common mathematical operations, string manipulation, date and time functions, temporal logic and more. This expressiveness enables the representation of complex decision rules in a concise and intuitive manner.

Decision Table Support

FEEL has native support for decision tables, which are a popular technique for representing decision logic. Decision tables provide a tabular representation of rules and outcomes, making it easy to understand and maintain complex decision logic.

Strong typing and type inference

FEEL is a strongly typed language, which means it enforces strict type checking. This feature helps prevent common programming errors by ensuring that values and operations are compatible.

Boxed Expression Support for FEEL

Boxed expressions allow FEEL expressions and statements to be structured visually including:

  • If, then, else statements
  • For, in, return statements
  • List membership statements
  • … and more.

These visual constructs, along with autocomplete make creating, reading, and understanding complex expressions easy to model and debug.

Flexibility and modularity

FEEL supports modular rule definitions and reusable expressions, promoting code reuse and maintainability. It allows the creation of decision models and rule sets that can be easily extended, modified, and updated as business requirements change. This flexibility ensures agility in decision-making processes.

Testing and Debugging

FEEL expressions can be tested and debugged independently of the larger application or system. This enables users to validate and verify decision logic before deployment, ensuring accuracy and reliability. FEEL also provides error handling and exception mechanisms that help identify and resolve issues in decision models.

Execution efficiency

FEEL expressions are designed to be executed efficiently, providing fast and scalable performance. FEEL engines often use optimized evaluation algorithms and data structures to ensure high-speed execution of decision logic, even for complex rule sets.

Integration FEEL

can be easily integrated with other programming languages and platforms. Many decision management systems and business rules engines provide support for executing FEEL expressions alongside other code or as part of a larger application. This enables seamless integration of decision logic via services into existing IT architectures and workflows.


FEEL can be extended with domain-specific functions and operators to cater to specific industries or business domains. These extensions can be defined to encapsulate common calculations, business rules, or industry-specific logic, enabling greater reusability and modularity.


FEEL also enables the sharing and reuse of decision models across different organizations and applications.

Business Benefits of FEEL

Standardization and Vendor-neutrality

FEEL is a standardized language within the OMG DMN standard, which means it has a well-defined specification and is supported by various software tools and platforms. Standardization ensures interoperability, as FEEL expressions can be used across different DMN-compliant systems without compatibility issues. FEEL is designed to be portable across different platforms and implementations.


FEEL focuses on capturing business rules and decision logic in a way that is intuitive and natural for business users. This allows subject matter experts and domain specialists to directly participate in the decision modeling process, reducing the dependency on IT teams and accelerating the development cycle.

Simplicity and Readability

FEEL has a syntax that is easy to read and understand – even for non-technical users like subject matter experts and citizen developers. It uses natural language constructs including spaces in names and common mathematical notation. This simplicity enhances collaboration between technical and non-technical stakeholders, facilitating the development of effective decision models.

Ease of Use

FEEL is supported by various decision management tools and platforms. These tools provide visual modeling capabilities, debugging, testing, and other features that enhance productivity and ease of use. The availability of modeling and automation tooling support simplifies the adoption and usage of FEEL.

Decision Traceability

FEEL expressions support the capture of decision traceability, allowing users to track and document the underlying logic behind decision-making processes. This traceability enhances transparency and auditability, making it easier to understand and justify the decisions made within an organization.

Decision Automation

FEEL has well-defined semantics that support the execution of decision models. It allows the evaluation of expressions and decision tables, enabling the automated execution of decision logic. This executable semantics ensures that the decision models defined in FEEL can be deployed and executed in a runtime environment with other programs and systems.

Compliance and Governance

FEEL supports the definition of decision logic in a structured and auditable manner. This helps businesses ensure compliance with regulatory requirements and internal policies. FEEL’s ability to express decision rules transparently allows organizations to track and document decision-making processes, facilitating regulatory audits and internal governance practices. FEEL includes several features specifically tailored for decision modeling and rule evaluation. It supports concepts like ranges, intervals, and temporal reasoning, allowing for precise specification of conditions and constraints. These domain-specific features make FEEL particularly suitable for industries where decision-making based on rules and constraints is critical, such as healthcare, finance, insurance, and compliance.

Decision Analytics

FEEL provides the foundation for decision analytics and reporting. By expressing decision logic in FEEL, organizations can capture data and insights related to decision-making processes. This data can be leveraged for analysis, optimization, and continuous improvement of decision models. FEEL’s expressive capabilities allow for the integration of decision analytics tools and techniques, enabling businesses to gain deeper insights into their decision-making processes.

Trisotech FEEL Support

Most comprehensive FEEL implementation

Trisotech provides the industry’s most comprehensive modeling and automation tools for DMN including support for the full syntax, grammar, and functions of the FEEL expression language. To learn more about basic types, logical operators, arithmetic operators, intervals, statements, extraction and filters supported by Trisotech see the FEEL Poster.

FEEL Boxed Expressions

Boxed Expressions are visual depictions of the decisions’ logic. Trisotech’s visual editor makes the creation of Boxed Expressions and FEEL expressions easy and accessible to non-programmers and professional programmers alike.

FEEL Functions

FEEL’s entire set of built-in functions are documented and menu selectable in the editor. The visual editor also offers supports for the Trisotech-provided custom FEEL functions including functions for Automation, Finance, Healthcare, and other categories.


The Trisotech FEEL autocompletion feature proposes variable and function names including qualified names as you type when editing expressions thus saving time and improving accuracy.

FEEL as a Universal Expression Language

Trisotech has also expanded the availability of the international standard FEEL expression language to its Workflow (BPMN) and Case Management (CMMN) visual modelers. For example, FEEL expressions can be used for providing Gateway logic in BPMN and If Part Condition expressions on sentries in CMMN.

FEEL Validation and Debugging

Trisotech provides validation for FEEL and real-time full-featured debugging capabilities. To learn more about testing and debugging read the blog Trisotech Debuggers.

Additional Presentations and Blogs

You can also watch a presentation by Denis Gagne on using FEEL as a standards-based low-code development tool and read a blog by Bruce Silver about how using FEEL in DMN along with BPMN™ is the key to standards-based Low-Code Business Automation.

OMG®, BPMN™ (Business Process Model and Notation™), DMN™ (Decision Model and Notation™), CMMN™, (Case Management Model and Notation™), FIBO®, and BPM+ Health™ are either registered trademarks or trademarks of Object Management Group, Inc. in the United States and/or other countries.



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