Case for a Collaborative Health-Support Model System
Posted Mar 06 2009 2:39pm
In our current economy, improving healthcare value is absolutely essential. High-value comes from consistently delivering top quality care at a good price. In other words, we have to focus on making healthcare much more cost-effective.
Part of the solution is reforming healthcare economic models, changing how care is paid, and redirecting the way healthcare providers compete because current methods fail to offer high value products and services to consumers. Arguably more important, however, is the need for healthcare professionals and consumers to:
Know the most efficient and effective ways to prevent, treat and manage health problems
Use this knowledge competently and consistently.
Sadly, while drowning in oceans of information, the healthcare industry lacks the knowledge and motivation needed to deliver high-value care. Proof includes:
The disconnection between quality and cost; research has proven that more expensive care rarely results in better care
The fact that healthcare providers often don't know what treatments work best for a particular patient
The unaided human mind, no matter how competent, simply cannot focus on all the necessary details nor possess all the knowledge needed for continually making the best clinical decisions
Our country hasn't focused enough on making existing healthcare knowledge useful and applicable to clinical practice
Obtaining the knowledge to improve decision-making requires a commitment to ongoing clinical outcomes research and a focus on continuous quality improvement, things that the healthcare industry has largely avoided
Knowledge about prescription medication safety and effectiveness can be greatly enhanced.
How can this troubling situation be improved? By using and evolving collaborative health-support models.
Health-Support Models Described
Let's begin by describing what health-support models are, what they do, and how using them in collaborative networks is an essential ingredient for increasing healthcare value.
What Health-Support Models Are and What They Do
A health-support model is anything tool that helps a person make a health-related decision or take specific action to deal with a (potential) health problem. The model may be built into a software program, be described in a book or pamphlet, be shown in a video, or be presented any other way.
A good health-support model (a) increases awareness and understanding about people's health status, threats, problems, and care options and (b) guides subsequent action to avoid the threats and deal with the problems. The model accomplishes these objectives by offering personalized recommendations, instructions, feedback, and alerts based on mathematical and logical analyses of comprehensive personal health information.
To be truly useful, this information should include data about a person's:
Physical and psychological (body & mind, whole-person) health and susceptibility, past and present
History of treatments, the clinical outcomes (the results of care), and the costs
Influences of one's environment and culture
The model's recommendations, instructions, feedback, and alerts—which should be supported by evidence-based guidelines and sound theory—ought to focus on helping people:
Assess (diagnose) and define health risks and conditions
Prevent risks from becoming serious health problems
Treat and cure existing problems
Manage chronic conditions (such as diabetes, obesity, and heart disease), so debilitating complications do not happen.
It's important to note that models differ in many ways; for example, different models:
Take into account different health data
Employ different math and logic to analyze the data
Make different assumptions
Base their recommendations, instructions, feedback, and alerts on different information resources (such as evidence-based guidelines)
Present their recommendations and instructions in different ways (including computer software, written manual, video, etc.).
This means that certain models are more useful than others depending on the people utilizing them and the particular circumstances in which they are used. Yet despite these differences, the goal of decision-models used in healthcare should be to increase care cost-effectiveness. And achieving this goal requires collaboration.
Models and Collaboration
Collaboration is essential for bringing ever-greater value to the healthcare consumer by fostering model evolution, and by utilizing models in loosely-coupled collectives. These networks of people collaborate by working together to support shared decision-making and facilitate care coordination, which are two of the most important model-driven processes for high-value healthcare. That's why collaborative health-support models are so important.
A "loosely-coupled collective" is a dispersed group of people from multiple locations and with different roles, responsibilities, experiences, and awareness. These people collaborate to make more valid decisions and competent actions by taking advantage of their collective wisdom. When such collaboration is among people with wide diversities of knowledge, ideas and points of view, the collective provides a greater assortment of intellectual resource, and offers access to a wider variety of non-redundant information and understandings  on which to base decisions and guide actions. This is unlike a tightly-coupled network that limits participation to people within the same discipline, department, region, etc. who have access to the same information sources and who share similar experiences. Loosely-coupled collectives provide the greatest opportunities for stimulating multifaceted discussions and creative solutions.
Model Evolution through Collaboration in Loosely-Coupled Collectives
Collaborating around models helps evolve (improve) the models by making them more effective in:
Increasing people's awareness and understanding of health risks, problems, and remedies Providing useful recommendations, guidance, feedback, and instruction.
Evolving health-support models in this manner is accomplished by sharing and "playing with" the models. When people share and play with these models, they:
Compare and test the models for their ability to reflect reality accurately
Manipulate the models to represent different scenarios, such as "what if" scenarios about the probability of future occurrences
Discuss the assumptions and results the models produce.
When they find models that disagree or generate invalid results, they:
Examine the fundamental assumptions built into the models
Look for logical flaws and inconsistencies in the model
Question the model's authors' perception of reality
Debate about the assumptions and practical value of the model.
By challenging the model's assumptions in these ways:
Useful counterintuitive insights often emerge
Innovative thought is sparked
New questions arise
Relationships between collaborators are developed
The influence of an organization's culture and politics are revealed
Compelling and unexpected management issues are discovered.
This all means that sharing and playing with models is an effective way to evolve health-support models to increase their validity and usefulness.
Failure to evolve models in this manner can be disastrous! Take, for example, the famous mathematical model that brought Wall Street to its knees. The model was used for the past five years to justify risky mortgage-based investments, even though few understood it and even fewer questioned its assumptions. Invented by a mathematician, the model was based on the faulty assumption that home prices would continue to rise and few homeowners would be unable to pay back their mortgages. While some financial experts realized this was a seriously flawed model, it brought great wealth to many for years, so there was little incentive to criticize it. This very model is a root cause of the world's current financial meltdown.
The healthcare industry ought to learn a valuable lesson from that fiasco!
Enabling Loosely-Coupled Collectives with Decentralized Communication Architectures
To streamline communications in these loosely-coupled collectives, it's best to deploy a low-cost decentralized (peer-to-peer) architecture. One example is the "mesh" network architecture, which grew out of the need for a distribution network in telephone, power, and water, and oil pipeline businesses. It enables anyone to communicate directly with anyone else at any time, from anywhere. It's like using the telephone to communicate with a single person, or to set up a conference call where each person can communicate to many other people. The mesh network architecture, therefore, provides a simple, flexible, low-cost way to exchange models.
In my next post, I'll discuss how to use health decision-models in loosely-coupled collectives to provide high-value care by promoting coordinated care, delivering consumer-centered cognitive support, and fostering shared decision-making.