I started this topic with the statement that our healthcare system needs radical transformation since:
- All patients "…are at risk for receiving poor health care, no matter where they live; why, where and from whom they seek care; or what their race, gender, or financial status is"
- Healthcare is increasingly more expensive and less accessible, with more than 46 million uninsured in the U.S. from every age group and at every income level, 8 out of 10 being in working families
- There is a "knowledge gap"-the healthcare community is drowning in oceans of information, yet doesn't know the best ways to prevent health problems and treat them cost-effectively.
- Know the best ways to prevent illness, avoid complications of chronic diseases, and treat health problems (i.e., in the most effective and efficient manner)
- Use this knowledge to promote wellness, self-management, and recovery
- Participate in evolving this knowledge to make it ever-more useful and effective.
I concluded with a review of how a secure, economical, node-to-node architecture-with universal translation, composite reporting, and application integration-are essential components to the successful implementation of an intelligent and efficient quality improvement system.
I will now tie this all together as I present what might be considered the "holy grail" health-knowledge system.
Imagine patients and other healthcare consumers, along with clinicians and researchers, who collaborate to build an evergreen (i.e., continually growing and evolving) knowledge base of comprehensive information. This information comes from data obtained, which protect patients' privacy, via controlled clinical studies and real world outcomes research. These data are received around the globe every day and are analyzed on a regular basis in order to find associations between biological and psychological signs & symptoms, lab studies, diagnoses, genetic data, demographics, wellness interventions, sick care treatments, patient preferences, care costs, and clinical outcomes. The knowledge emerging from all this information is then used to create and validate evidence-based guidelines promoting high-value (i.e., safe & cost-effective) care alternatives that are matched to the particular needs of different consumers and providers. Understanding the relationships between health problems, care interventions and results enables both professionals and consumers to make wiser decisions that improve outcomes and control costs.
Underlying this information, knowledge and understanding are the data obtained from patients/consumers' PHAs (personal health applications) and providers' EHRs (electronic health records).
Clinicians and hospitals who collaborate in a patient's care, then share and view the patient data via next-generation CCRs (continuity of care records) tailored to each practitioner's particular needs. These CCRs go well beyond the ones being developed today by adding:
- Sophisticated clinical decision support capabilities that present warnings and alerts, as well as clinical guidelines (and pathways)
- Patient self-care information (i.e., "information therapy")
- Tools that track compliance to the guidelines, reasons for non-compliance (i.e., "variance"), and clinical & financial outcomes.
The data and guidelines are transmitted through networks of networks using a simple, secure, low-cost node-based architecture and e-mail that require no build out of existing IT infrastructures. The nodes' "universal translation" function accommodates all data standards, as well as any non-standardized data sets and terminologies. Furthermore, since the nodes communicate asynchronously via publisher-subscriber process, and since they can present interactive reports through "desktop/standalone" applications (i.e., they are not limited to Internet browsers), critical information can therefore be accessed offline using rich, powerful tools. This means:
- There is no loss of data when a network connection drops out (i.e., unexpected disconnection), and there is no single point of failure to disrupt and entire network when a central server develops problems
- All the information can be accessed anywhere/anytime, even if there is no Internet or other network connections
- A great deal of data can be exchanged even when bandwidth is low and connectivity is intermittent (e.g., using dial-up)
- Each person controls their own data since they are stored locally (in their own computers) in encrypted files
- Total cost of ownership is minimized since there is no need to rely on expensive central servers and server administrators
- Performance is greatly increased when performing complex, intensive computations since all data processing is done quickly and easily using local computer resources, rather than waiting for a strained central server, or being restricted by the limitations of a browser
- You can integrate multiple desktop applications, which cannot be done securely using a browser.  
- What data to collect and exchange
- How to analyze, interpret and validate the data to generate useful information
- How to organize, access, share and discuss the information to emerge useful knowledge
- How to use the knowledge to improve care quality and control costs.
- " Comprehensive dik is required for understanding the "big picture" clearly. This big picture reflects a person's physical and psychological risks, strengths, problems and preferences, as well as the evidence-based well care and sick care intervention options best suited to that individual.
- Complex dik provides crucial insights into care that are not possible using today's "minimum data set" standards. This higher level understanding comes from analyzing data that reveal such complexities as:
- Medication-related interactions (e.g., drug-drug, drug-supplement, drug-metabolism and drug-lab results interactions, as well as allergic reactions)
- Mind-body and mind-body-environment interactions (e.g., the adverse affect of psychological stress and emotions on one's immune system, the affect of one's belief systems on one's health, etc.)
- Medication side-effects and biomedical conditions that present as psychological symptoms
- Trends, including changes in lab test results, functionality and signs & symptoms over a person's lifetime
- The correlation of treatments and outcomes for different patient populations and providers
- The reasons for not following particular recommended treatment processes and the results of such variance.
- Comprehendible dik:
- Are readily understandable (e.g., unambiguous, valid, reliable, relevant and useful)
- Maintain important nuances of meaning (e.g., uses the correct terminology standards)
- Do not overload people with irrelevancies or redundancies.
- How can we know if the data being collected are complete, appropriately complex, comprehendible, relevant and useful?
- What has to happen for good data to become useful knowledge that leads to ever-better and more affordable care?
 The First National Report Card on Quality of Health Care in America by RAND Corp (2006)
 Health Care Coverage in America: Understanding the Issues and Proposed Solutions by The Alliance for Health Reform (March 2007)
 The Current Situation - WellnessWiki
 The Knowledge Gap - WellnessWiki
 Linking Providers Via Health Information Networks. Alliance for Health Reform. (Dec 2006).
 Is the Browser Singularly Capable of Everything? Software Development Times (June 15, 2007)
 New Google Tool Gets Offline Access in Gear. Eweek (June 11, 2007)
 Biopsychosocial Healthcare - WellnessWiki