Deconfusing Healthcare through Taxonomy Inquiry

This winter,  I had an opportunity to participate in an information research team that had a chance to interview top executives in health care in Massachusetts.  This included the CEOs of insurance companies,  regulators from the Attorney General’s office, and medical directors of major medical networks and hospitals.   The goal of this project was to understand one term  “Cost Containment”   — what are the drivers for rising health care costs and what can be done to slow the rate of growth.

When someone with taxonomy skills participates in these types of investigations, it is hard not to put those taxonomy skills to work. What did I learn from this process that might be applicable to best practice and to understanding health care cost containment?

1) Start with a  simple but important question  as a guide for developing deeper knowledge

This group started with the question  “What is cost containment?”   It is a fairly fundamental question since we in Massachusetts are fortunate to have universal coverage (about 97%)  but there is a need to control costs.  By asking this fundamental question. the group could  collect basic facts from each key player on the same topic   to understand how proposed strategies are defined from the point of view of key players who are shaping policy.

2) Get to know the cast of characters

Remember the adage that the key to a baseball game is to know the players and the same applies to understanding a complex issue. We need to  who the users are, what brought them to these meetings,  It is critical to  identify the constituencies in healthcare, all of whom have different goals in any situation.   The key actors we indentified were:

  • Insurers (also known as Payers)
  • Providers (Hospitals, Doctors, Specialists)
  • Regulators (government, legislature, attorney general)
  • Consumers (includes business owners, patients, local government)
  • Purchasing agents (people who buy insurance for large groups — government, business, insurance agents)
The above list is a top level of the Actors/Player facet which further breakdowns.  Insurers for example is further categorized into companies, corporate structure (profit/non-profit), market share.    Not all the groups under these broad headings share characteristics.  For examples, we rarely saw a “specialist” at  a meeting on cost containment, but other types of medical personnel including primary care, psychiatrists, behavior medicine, were well represented because they, as a group, lower reimbursement and higher volume than specialists.  Grouping does not mean all values are inherited  — thus the need for understanding power relationships and attributes.

3) Understand the power relationships

Some actors have more power and are core to the discussion.  Insurers and providers have a closer affinity for example, while consumers, including employees,  business and local government entities tend to have less to no power in these relationships.  Hospitals and specialists have more power than primary care and behavioral medicine.  Understanding these internecine wars within health care is a key analysis for understanding core relationships and who is outlying.  The health care debate is in part about how to give outliers more power and equity in the health care process. The most outlying of all voices is patients and consumers.  Theoretically,  in new models of health care, their voice is supposed to be represented by larger purchasing pools who can negotiate for better service at less cost.

4) Identify  the key cost drivers —  Isolate the attributes 

The hardest part of this work is to isolate the variables/attributes  or cost drivers, and understand how each group contributes to improving these practices.  These are topics that should be of mutual concern but that are  not universally understood and standardized.  Examples of cost drivers included:

  • Use of and dissemination of best practices (end-of-life care, chronic diseases)
  • Use of Technology
  • Number  and Variety of Insurance Plans
  • Cost of drugs
  • Reimbursement rates
  • Risk Management (use of defensive medicine, malpractice, high-risk pools)

Each of these attributes needed to be further understood from perspective of the key players to understand how it contributes to cost.  For example, Massachusetts has an excellent universal health care law, where consumers can choose from about 18 different plans over the Connector, but in addition, there are additional public, private and individual plans resulting in over 16,000 different plans.   Some cost containment could be achieved by having a “shared minimal contract” that is at a high standard of care, and captures essence of basic wellness.  To do this, the players and consumers need to find the common language for describing conditions and coverage.

5) Capture the AS IS Definitions.

Since these conditions and coverage are not standardized,  it is useful to understand what the current status is.   Understanding AS IS definitions help to capture the many disconnects between group. For example, while consumers argue about cost of deductibles, insurance companies might spend more money in order to reduce high cost of hospitalization.  Result is like a balloon filled with water — one end gets leaner, while more pressure is put on another end of the balloon — the consumer.    Capturing the cacophony, instead of the symphony, turned out to be the most valuable part of the work. We discovered we did not have to reach common understanding, which meant trying to capture the current status and its impacts.

6) Read background content

In addition to understand the “cast and drivers”  it is also important to read studies and literature to keep a broad and balance perspective. Being in rooms with charming and knowledgeable power players can be quite intoxicating, but to keep it honest, we needed to keep reading and we needed to ask honest questions about what was the advantage for each player in their advocacy for a certain program.   Spending a few hours each week on literature reviews, books, articles, podcasts on general health care was very important to building our group and individual knowledge base and developing our facility in the terminology of health care economics.  We used reading to define comparative health care models in other countries (Taiwan, Switzerland, Japan, Canada, Germany, UK, France, and US) and to understand multiple models of healthcare delivery.

7) Capture concepts in simple diagrams

Even within our small, random  data collection group, there were divisions in understanding can be quite diverse.  Using simple diagrams to capture concepts  turned out to be powerful shared way to come to common understanding.  Bubble mapping, graphing, hierarchical diagrams, any visual graph was useful to clarify information.

8)  If any term is hard to explain with a simple sentence, it probably deserves a taxonomy

“Cost containment”  is not trivial,  but it is also important to understand. And it is almost  impossible to explain without learning something about healthcare system.   It is worthy of the time and effort to create a taxonomy to define the information space or information void, and a void is filled by misunderstanding or misinformation.

Developing a consumer-focussed taxonomy for navigating health care  turns out to be valuable work, but it is hard to sustain without a dedicated team with and sustained funding.  A consumer-focused taxonomy would help  navigate the health care debate, can be used across all actors, including   insurers, providers, governmental entities  and consumers who want to share information with a confused but curious public.

~ Marlene Rockmore

Skills of a Classy Taxonomist

At SemTech in June 2010,  several speakers including Professor Deb McGuiness drew a very clear line was drawn between what a taxonomist does and what an ontologist does.  Taxonomists build hierarchies, and ontologists determine classes or categories.   In other words, ontologies are neat and unambiguous, and taxonomies are a bit messy.

Defining classes or ontology work  typically precedes building the taxonomy.  Defining the classes is like writing a specification for the taxonomy; in fact defining classes is the same as defining facets.   The goal of a taxonomist and ontologies should be to define a specific, unambiguous description of a term that helps manage how we find and organize content so the pathways are clear and specific; adding an ontology ensures that the term is placed in the most specific categories to help ensure clarity and lack of ambiguity. I would argue that no taxonomy is useful unless it is faceted – that is, has been divided into classes. Taxonomies work best when they share homogenous properties, and when they are smaller and focused.

By using class analysis, or facet analysis,  several problems are solved:

1)       Clarify specific terms by situation or functions: If I am interested in Java as a programming language, I want to see material related to Java as software, not as slang for coffee or  an island in the South Pacific.  If I am looking for “drill bits,”  it might be important to understand if the drill bits are for my home electric screwdriver  or for an oil rig.   Classes capture these distinctions, and help to create precise specific tagging and information retrieval.

2)       Ease longterm  maintenance issues: Christine Connors points to a simple but common example where taxonomies are built where people’s names are included as narrow terms under the role such as “Hillary Clinton” is “Secretary of State”  or “Charles Windsor” is the “Prince of Wales.” The problem is that when people filling these roles change, there is a maintenance headache.   A classy taxonomy recognizes that there is a separate class for <people> as an entity, as distinguished from <role>.  <People> and <Role>  can be connected by a predicate such as <isA>.  These distinctions are necessary for fast-changing information (such as who is dating whom in an entertainment application) or (who owns whom in a business application).

Abstraction <person> <has> <role>

Instance: Hillary Clinton <is>  Secretary of State

3)    Facilitate sharing  and importing taxonomies: Having taxonomies that are specified by a class description means the taxonomy will be more homogenous, have shared properties, and be more focused.  This will make it easier to import with less cleanup and review.  It will facilitate the use of SKOS for example. Messy taxonomies are harder to merge.

Anyone working with semantic technologies will tell you that most problems in inference happen when hierarchies in source taxonomies create odd associations by inserting a narrow or broad term. A taxonomist needs to be attentive to inferences in order to prevent false statements.   Professor Deb McGuiness calls this issue “truth maintenance.”

To keep these categories clear and distinct, ontologists rely on building a conceptual model or a picture of the domain (see earlier post on Taxonomies and modeling.)   Modeling strategies involve skills of most taxonomists.  Most taxonomists have been taught how to capture vocabulary and how to identify facets.  Check out the blog post Taxonomies and Modelling for more information.

Elaine Kendall  of Sandpiper Software, which is a concept-modelling tool.  suggested that “one could build an ontology in 2 hours.”   With new generation of tools that can create RDF/OWL from data and content,  this statement might be true.

    With good modelling tools that automatically generate RDF/OWL,such as TopQuadrant,  taxonomists might  be able to slide into the needed role as ontologists.  Taxonomists need to understand  some basic concepts in RDF/OWL to extend their skills such as what is a class, what is a property and what is a slot facet, what is class inheritance, what is meant by reciprocation and inverse properties and how to write a SPARQL query.  But more importantly,  a classy taxonomist can help become a facilitator to help build bridges between user and development communities and  to help diagnose and prevent technical problems.

    A taxonomist who is trained in ontologies  should bring the following skills:

    • Ability to create processes to identify the requirements for each class,
    • Develop  metrics to assess good results
    • Identify what vocabularies are needed and use skills to evaluate existing vocabularies, import and adapt these vocabularies to the current needs
    • Ensure the integrity and focus of vocabularies particularly when sourced from an outside vendor,
    • Develop processes to keep vocabularies current, and understand how to use metrics to “measure and improve” any vocabularies.
    • To be part of the development team to help identify if a source vocabulary might be part of false inference.

    The taxonomist works with different user communities as well as developers and helps bridge the gap between what users and experts know and what is needed to build a useful application.   A classy taxonomist has a well-rounded set of skills that can work with development teams and user organizations to build intelligent systems.

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    Book Review: Organising Knowledge by Patrick Lambe

    Although the interest in and applications of taxonomies has grown in recent years, there are still not many books on the subject. Most of the information on taxonomies currently resides in online discussion group archives, blogs, wikis, conference presentations, white papers and reports (the latter at quite a premium price), but not much yet in easily accessible books. A search on Amazon.com on “taxonomies” yields numerous books of specific taxonomies, but very few on the art of creating taxonomies in general. Even the “books” page on the Taxonomy Community of Practice Wikispace lists mostly books on information architecture, a classic book on classification theory, chapters of books on broader topics, and high-priced research reports. There is just one book listed with a focus on taxonomies: Organising Knowledge: Taxonomies, Knowledge and Organisational Effectiveness by Patrick Lambe (Oxford, England: Chandos Publishing, 2007)

    Indeed, as its title and subtitle suggest, taxonomies are presented within a broader view of how knowledge is organized. The book is neither a simple “how to” book, nor a scholarly treatment of the subject, but in fact combines both: practical advice on how to create taxonomies along with thoroughness in covering the field of knowledge organization and analysis of various ideas and previous literature on the subject, with many footnotes and a lengthy bibliography.

    The author, Patrick Lambe, is a Singapore-based consultant in the field of knowledge management who can base his ideas on his own business experience. Yet Lambe also has the academic credentials of an information scientist, a Master’s degree in Information Studies and Librarianship and experience teaching as an adjunct professor. Thus, he aptly bridges both sides of taxonomies, the traditional library science side and the newer corporate knowledge management side, although it is the latter that is the subject of this book. What I appreciate in this book is that Lambe writes based on both his research and his experience, and based on these he has developed a number of his own ideas.

    While common definitions of taxonomies often limit them to hierarchies, Lambe prefers a broader definition. The forms of taxonomies that Lambe presents, along with a detailed explanation for each, are: lists, trees, hierarchies, polyhierarchies, matrices, facets, and system maps. Stretching the definition and boundaries of what taxonomies are and can do is a central theme of Organising Knowledge. Lambe states: “Taken together, it becomes clear that taxonomy work holds a wider range of application and use than simply as a tool of information retrieval.” (p. 95) .

    Organising Knowledge presents a number of real world examples, scenarios, and case studies of the application of taxonomies in their broadest sense. These include implementations by the U.S. Department of Homeland Security, Unilever, and Club Med. These examples illustrate the wide range of uses for taxonomies. Among business activities, Lambe says that taxonomies can support the areas of risk recognition and response, cost control, customer and market management, and innovation.

    Lambe does not simply describe taxonomies and their use. In this in-depth book he discusses their varied roles, how they are understood, and trends in their implementation. He describes how different kinds of taxonomies can either (1) structure and organize (both things and processes), (2) establish common ground, (3) span boundaries between groups, (4) help in sense-making, or (5) aid in the discovery of risk and opportunity.

    Several later chapters turn to the practical steps of preparing, designing, and implementing a taxonomy project. Lambe breaks out the process into ten steps, the first six of which are all still part of the preparation stage. Among the topics presented in the preparation phase are taking technology into consideration and communicating well with the taxonomy sponsor and stakeholders. While it is appreciated that technology/computer systems are mentioned, I would have liked to learn more about this. It becomes quite evident that different situations require different approaches and different kinds of taxonomies, the different kinds of taxonomies that Lambe describes earlier in the book. My only point of disagreement here is the continual distinction between tree taxonomies and faceted taxonomies, since taxonomies often exhibit both characteristics at the same time.

    The book is well written and relatively easy to follow, but it is not a “light” read. It has a number of helpful tables and diagrams. Particularly useful is the table (two and half pages long) comparing the uses and issues for each of the seven forms of taxonomies: lists, trees, hierarchies, polyhierarchies, matrices, facets, and system maps.

    I highly recommend this book of great breadth and depth to anyone who works on taxonomies or is interested in working on taxonomies. The intended audience of the book is indeed limited to knowledge management and taxonomy professionals. Even those with considerable experience working in taxonomies will find this book informative and enlightening.

    – Heather Hedden

    This review is based on a longer book review written by Heather Hedden and published in Key Words, the Bulletin of the American Society for Indexing, Vol. 15, No. 4, October-December 2007, pp. 130-132.

    A Well-Planned Taxonomy

    Recently, I ran into a neighbor who is a VP at a high-tech firm working on speech recognition, so I asked if she was using taxonomies. “To me, Tom Brady is a topic and that’s enough. It’s too much work to build hierarchies.” But for me, there is way too much information about Tom Brady. I’d like to be able to find information based Tom Brady’s statistics, or how he is managed, or maybe, something about his social life.

    Taxonomies are not just about hierarchies or long lists of terms. Taxonomies exist to capture how users look for information. For example, if I am interested in “Food Policy”, I might want to know where food is produced, what is added to food (food additives), how food is distributed, and where food is needed to prevent hunger, including local food banks.

    A taxonomy term has to be categorized to have any meaning.  The process of categorization is called facet analysis, and here’s why it’s necessary:

    • Reduces the complexity of thousands of terms into smaller, manageable categories
    • Provides semantic, contextual meaning for a term including the power to disambiguate terms
    • Allows connections to be made between categories that can be inherited (but carefully)
    • Provides ability to recognize gaps in information
    • Provides ability to reuse concepts for multiple applications, or to identify local variations of a vocabulary
    • Provides ability to focus on important topics

    For example, in one project, I was handed a taxonomy that had 4,000 terms that we reduced to 9 top nodes. In addition to improving search, we noticed another effect. Our computer products facet included attributes such as supercomputers, minicomputers and personal computers. As our application was tied to a search interface, we began to notice the uptick in searches on laptops and personal computers, which became indicative of changing demand in a changing market,    Similarly,  on another project,  we noticed emerging concepts around “Green Business” “Social Responsibility” and “Business Ethics.” One of the goals of that implementation project was to make it easy for the  taxonomy editor  to add these concepts and realign content to meet these new demands.

    That’s why it’s important to integrate social networking with taxonomy tools. Terminology, whether suggested through social networks or  formally produced, increase their value  when they are linked through categorization. Be sure to evaluate your taxonomy to make sure it is categorized. I’ve heard horror stories recently of organizations with thousands of terms that were not defined or categorized.

    A well-managed taxonomy can be a strategic tool to like the “canary in the mine” to help identify emerging concepts.

    canary on a branch

    canary on a branch


    So take the planning or revisionof the taxonomy seriously. It is an opportunity to find out what the organization knows, how different groups inside and outside the organization express what they know, what an organization wants to know, and what gaps are in their content and knowledge.

    Here’s a five point plan.

    1. Understand the expectations and information needs of stakeholders, endusers, technical staff and production work including information flows, and bottlenecks. Gather information. Listen to what different levels perceive as existing problems and compare to what exists. Learn how indexing is currently done and what the issues are with search and terminology management. Acknowledge what works well, and discover what problems exist. Pay attention to how terminology is used in different context.

    2. Develop a clear set of requirements based on needs of the organization. Determine project goals. For some organizations, the ability to tie vocabulary to search will be imperative, while other organizations need to find ways to come to common agreements about standard terminology across diverse entities. Is the taxonomy to being used to manage metadata or is it being used to search and index full-text? Is the application managing non-digital assets like people, services, and projects? How immediate are the information needs? Does a vast amount of content need to be indexed quickly which might lead to an auto-categorization solution? What statistics will demonstrate the value of the taxonomy? Are similar terms used in different context? Take, for example, a company name — a company can be simultaneously a product supplier, competitor, customer, and strategic partner. Is there a need to represent multiple views of the same term?

    3. Create a deeper understanding of user needs by building a model of the domain. Without categorization, taxonomy can become a long, unwieldy list of terms that lack meaning and context. By placing a term in a category can add meaning. Use the techniques of ontological type analysis to abstract categories and create information models that link concepts (in semantic modeling, this would be creating RDF schema).  Visio or Topic Mapping can help capture these connections visually.

    4. Obtain a strong set of detailed test terms by collecting terms from a variety of activities including card sorts, search analytics, content analysis, deeper text analytics, and entity extraction that represent both user need and content. Users can be involved in this process. Automated tools can help here if your content is accessible. Entity Extraction and Automated Concept Generation can help, but someone will still need to sift and winnow the output – that’s why it’s so important to have a prior understanding of what users want and need to know.

    5. Define the core areas of knowledge that need more depth in the taxonomy. As part of the evaluation process, you would need to define how deep and broad the taxonomy needs to be. If you have done a facet analysis, some of those questions will be answered. As a rule of thumb, core areas of knowledge need to have depth and structure.

    6. Prepare for change. In fact, having a taxonomy that quickly recognizes new concepts might be a competitive advantage.  Test your taxonomy, and be prepared for change.  It means that taxonomy is open to new ideas from the people who are on the front lines of the market – customers, sales and marketing, customer service staff, librarians, the customer service department. It means new terminology can bubble from the bottom up! A taxonomy tool needs to allow for dynamic and flexible editing of terms to grow with changing enterprises and information needs in a global economy.