Monday, June 29, 2009

Deploying a Patient-Centered Medical Home Cyberinfrastructure

Following is a scenario describes how multidisciplinary teams of healthcare professionals collaborating in a patient-centered medical home (PCMH), using an innovative cyberinfrastructure, can improve care outcomes and bring greater value to patients. This cyberinfrastructure has two software programs:

  1. A computerized health agent (CHA) that enables patients and clinicians to connect to the PCMH network via the Internet
  2. A next-generation electronic health record (EHR) designed for each clinician's specific role and special, as well as a next-generation personal health record (PHR), such as the PHPro™.

In this scenario John, a 40 year old high school teacher with type II diabetes, has been having trouble managing his blood glucose, blood pressure, and cholesterol levels, despite taking medication. He recently changed to a different primary care physician (PCP) who is involved in a PCMH network that uses the innovative cyberinfrastructure to help support and coordinate collaboration among a multidisciplinary team of clinicians.

Day 1: John calls his PCP to schedule the first office visit for the following week. After scheduling his appointment, the receptionist sends him instructions for accessing a comprehensive whole-person (mind-body) health assessment and joining the PCMH network. She also asks John to allow the results of the assessment to be sent automatically to the PCP; he agrees.

John then goes to his computer and opens his browser. He navigates to the PCMH web site and registers. After supplying the requested information and selecting a user name and password, he is automatically enrolled as a patient in the PCMH network. The CHA and PHR are then automatically downloaded and installed in his computer. The PHR then begins displaying a series of holistic health assessment questions on his screen.

After completing the detailed assessment, John's PHR automatically:

  1. Analyses the data using its mind-body health logic engine
  2. Stores the resulting biopsychosocial (biomedical and psychosocial) health information about securely in his computer in an encrypted data file
  3. Generates a personal profile report providing him an integrated "big picture" view of his physical and mental health—past, present, and probably future—as well as evidence-based guidelines that enables him to understand his problems, risks, prognosis, and the relative pros and cons of different preventive and treatment options.

John starts interacting with biopsychosocial profile report offline. The report, which is comprehensive and easy to understand, includes:

  • A description his medical and emotional problems and risks based on the information he input into the PHR
  • A warning that he was under a great deal of stress due to problems at work and in his personal life
  • An alert that his high blood pressure may be exacerbated by a side-effect of a supplement he is taking
  • An easy to understand visual depiction of his health status, treatments, and significant life events on a timeline spanning many year
  • A prognosis that give him realistic expectations by predicting how his health will likely be in the future if things continue the way they are going, and how likely his health will improve if he takes effective steps to control his current problems and prevent his risks from becoming problems
  • Information therapy containing explanations and evidence-based recommendations about his health and what to do, including how his mental stress may be raising blood glucose and blood pressure levels, as well as targeted actionable recommendations that anticipates his needs
  • A list of questions to ask his doctor to assist in shared decision-making.

John's CHA also sends a predefined subset of data from John's data file to his PCP's CHA via an encrypted data file. The PCP's CHA stores the file in his computer in a folder (directory) containing the data files of other patients currently in treatment; the files of inactive patients are in another folder. Whenever the PCP accesses his EHR and selects to view John's health information, his data file is retrieved and the information it contains is presented in an interactive report.

Day 12: John meets his PCP for the first time and the two of them discuss the results of the initial biopsychosocial assessment. The doctor then gives John his annual physical and tells John that the results of the blood tests will be sent automatically to his PHR once the doctor receives them. In the mean time, the PCP refers him to see a cognitive-behavioral psychotherapist, who is also in the PCMC network, to help him to handle his stress. After the office visit, John calls the therapist and makes an appointment for later that week.

Day 15: During his initial session with the psychotherapist, John authorizes an automatic electronic transmission of specific whole-person information from his PHR database to the therapist's EHR.

After the session, John returns home and clicks a few buttons on his PHR, which automatically sends the authorized health information to the therapist's database. At the same time, certain data from the therapist's database are sent to the PCP's database to help the PCP track and coordinate John's care. In addition, the PCP is alerted that his database is updated.

The therapist requires different health information than the PCP. Since the cyberinfrastructure is configured to distribute the appropriate data sets based on each clinician's specialty, the data received by the therapist includes detailed information about John's mental health that the PCP did not receive. This information includes analyses of the connections between John's thoughts, attitudes, emotions and behaviors; the nature of his current stressors and life problems; his coping skills and tendencies; certain observations of daily living (ODL) data; as well as his psychosocial history and significant past experiences. The therapist views this information through his EHR. He then adds his professional observations and psychological test results into EHR, as well as information that is sent from his EHR to the PCPs.

Day 19: After the PCP receives John's blood test results from the lab, those data are automatically sent to John's data file. An alert appears on John's as in icon on John's computer notifying him that new information is available for viewing via his PHR. Later that day John accesses his PHR and views his lab test results in language, graphs, and picture he can understand. As suspected, his A1c glucose levels are too high and his cholesterol levels are borderline. He clicks a link next to the abnormal levels and receives additional information therapy explaining the likely causes for his condition and suggesting steps for him to take. In addition, he receives an alert that sent to him automatically by his PCP's CHA; it instructs him to contact his PCP to schedule a follow-up visit ASAP, which he does online via the PHR.

Day 22: John goes to his PCP's office for the follow-up. He is prescribed new medications as recommended by the clinical guidelines displayed on the PCP's EHR. If his EHR implements the patient-centered cognitive support (PCCS) process, a virtual human model would be used to assist with guideline selection and generations of a holistic plan of care. A wellness coach working in the PCP's office, who uses a different version of the EHR, then sits with John, explains his self-management plan of care, and answers John's questions.

Day 23: John goes to his psychotherapist for his second session during which he and the therapist reviews his mental health report generated by the therapist's EHR. The report contains useful information that helps them determine treatment goals and methods for achieving those goals. This information also suggests a diagnosis and assists the therapist in establishing a treatment plan. The therapist then gives John a homework assignment. He is asked to use the self-help problem management guide on his PHR to assist him in managing stress, improving his coping skills, and developing more effective ways dealing with his personal problems. This assistance augments and supports the care rendered by his therapist.

Ongoing for the next 8 weeks: John continues meeting with his psychotherapist weekly and uses his PHR as a self-help tool. He also uses the PHR to collect observations of daily living (ODL) data on a regular basis. These data include his levels of stress, the situations in which the stress is high, his mood and thought processes when under stress, his behavioral reactions to the stress, medication use, physical activity levels, diet, as well as his blood glucose and blood pressure levels using home monitoring tools. The PHR analyzes these data automatically and displays a report explaining how John's mind and body are interacting, the changes taking place in his physical and mental health, trends, projections, and warnings. Similar data are sent automatically in encrypted data files by John's CHA to his therapist and PCP's CHA. Their CHAs then automatically update the versions of John's data file stored in their computers, thereby ensuring the most recent data available for viewing via their EHRs. In addition, the wellness coach receives a subset of the data, which updates John's data file stored in her computer. Each of these collaborating healthcare professionals are alerted whenever information on a patient is updated. When they view their EHR reports, the new data are automatically processed and warnings are displayed if newly discovered problems with John's health appear.

End of episode of care: Upon completion of his mental health treatment, John is alerted to use his PHR to do an outcome assessment in which a portion of the initial assessment is repeated. The results are calculated automatically revealing positive changes in his level of stress, mood, key cognitions (attitudes and beliefs), coping skills, as well as in his glucose and blood pressure levels; his cholesterol remains at a borderline level, however. The results are sent via his CHA to the PCP, psychotherapist, and wellness coach. In addition, the initial and outcomes data are de-identified and sent in a data file to a CHA connected to a research database, which imports the data. The data are then immediately available to collaborating networks of researchers and clinicians studying care outcomes and evolving the clinical guidelines for ever-better results.

Bottom line: This scenario exemplifies the benefit of delivering whole-person care in a coordinated and integrated manner supported by and innovative cyberinfrastructure consisting of (a) a CHA that connect clinicians and patients to a PCMH network via the Internet and (b) next-generation EHRs and PHR. The result is a happier and healthier person, who is a more productive employee, and who self-manages one's health more effectively. This benefits many by reducing utilization of healthcare services to lower employer overhead, insurer payouts, and the person's out of pocket expenses. In addition, healthcare professionals benefit from better outcomes, fewer errors, and more satisfied patients. And everyone benefits from greater peace of mind knowing that care is well-coordinated and delivered competently.

Related links:

Tuesday, June 23, 2009

A Debate on Gradual versus Radical Change

Following is a discussion I'm having on a LinkedIn forum about adopting a very gradual approach to HIT evolution versus implementing a strategy promoting evolutionary leaps coming from disruptive innovation and a focus on radical change.

Someone wrote: I have proposed in the past and believe you might agree that a better approach would be to create a model of data sets that could be sent and received by providers in order to "qualify" their systems. This does still require a data standard but it allows the vendors to create their own tools and for innovation to thrive. Without a well defined data structure, we…will never be in a position to leverage those innovative tools such as cognitive support.

And I replied: While I agree that a model data set would be useful for qualification purposes, I've learned from experience that they tend to be "minimum data sets" with minimal usefulness, instead of being comprehensive/complete multidisciplinary data sets that approach "maximum usefulness." The problem with such minimal data standards is that it sets the bar way too low because vendors typically make that minimum their ultimate goal, rather than developing tools that can handle the maximum. I contend, therefore, that we ought to evaluate HIT tools in terms of (a) the depth and breadth of information they can manage cost-effectively and (b) whether that information enables patients and clinicians to make ever-better decisions by providing patient-centered cognitive support (PCCS). That is how innovation is sparked and meaningful change is encouraged; anything less promotes a glut of me-too commodities with minimal usefulness.

He also wrote: So, first we need to exchange information before we can take action on the data. In order to exchange the data we need a universally agreed upon data format. There are RHIOs and HIEs [i.e., organizations designed to enable data exchange in closed networks of providers] in place now that are functional but are not appropriate for a broader exchange of information. For the most part, those early implementations are proprietary systems that are scaled out to serve a region. While they have provided a valuable service, they need to adapt to a common data exchange that can be used to share data among other HIEs thus, a Nationwide Healthcare Information Network.

And I replied: Information exchange is certainly crucial. And I agree that intra-RHIO/HIE data exchange alone is not enough; there must also be inter-organizational information exchange across RHIOs/HIEs. While data and technology standards offer a way to handle information exchange challenges, they come with issues posing serious problems in terms of cost, effort, time, hassle, complexity, inefficiency, usability, reliability, information loss, political influence, etc. One innovative low cost solution we've been proposing is a publisher-subscriber node-to-node architecture with universal translation. I discussed these issue two years ago in a series of posts at this link.

He also wrote: Other than HIMSS desire to see CCHIT as the certification body, I believe their proposal is sound. That only brings us to the first step. I'm sure we would all agree that this will be an iterative process. ONC [The Health and Human Services' Office of the National Coordinator for Health Information Technology] needs to place a stake in the ground so we can move forward. Give us version 1 of a data object and we can start building Exchanges to get data to the EHR. Now we can start making use (even meaningful use) of the data and work toward improving healthcare. In time give us version 2 of the data standard and we will ratchet up functionality.

And I replied: Under the last administration—during the ONC NHIN initiative—$18.6 million was awarded to four large organizations, after deciding to renege on a promised 2/5 small business set-aside despite receiving many applications from small businesses around the country (see this link). Those millions, in the end, did not bring us any closer to an NHIN and left a very bad taste in the mouths of many innovative small businesses. Thus, it is important to guide ONC in guiding us by assuring that innovative ideas from "weak voices" (i.e., individuals and small businesses) be heard loudly and clearly, and be influential!

He also wrote: We have the data, we just need to improve the delivery and presentation of the data otherwise we'll be buried under information overload). We have the knowledge; we just need direction from the powers above. Give us clearly defined objectives and we will build an Information System that will be forward thinking and will enable us to use the patient's records as part of the treatment process. Keep us in the dark and we will go a hundred different directions, building dozens of perfectly functional systems that are each islands of information. One of the big failures of our healthcare system is not that we don't have the technology or the data; it's that we don't have the data where we need it when we need it.

And I replied: Yes we have data, but we do NOT have the data needed to create the necessary information and emerge the knowledge required to realize substantially improvements in care effectiveness and efficiency. And this goes well beyond the data distribution challenge. But even if we did have the necessary data, information, and exchange mechanisms, mainstream HIT tools would still NOT provide adequate decision making assistance because they fail to implement the patient-centered cognitive support process. Furthermore, I previously commented, there are serious problems with being overly reliant on restrictive standards on the "powers above."

So, we ought not to be squabbling about minimal data set and the use of conventional technology standards, but instead focusing our collective efforts on widespread collaboration to define the requirements for PCCS-enabled HIT that are able to manage comprehensive/complete multidisciplinary data sets with the potential to be maximally usefulness in both clinicians and patients/consumer in their decision making. I much rather see us going in "hundred different directions" in search of truly useful, disruptive HIT innovations, than to have the powers that be encourage adoption of the same old commodities that simply cannot do the job.

Having said that, there is a place for today's EHR and CPOE commodities, i.e., to define the strengths and weaknesses of the "AS IS" HIT model, so we can start building the "TO BE" model by adopting the most advanced and promising HIT tools that can overcome the AS IS model's deficits. These next-generation tools could be add-ons to today's commodity products, or they may be completely new types of tools that will replace what's currently available.

He also wrote: I'm an optimist and believe that we will pull it all together. The timeline that we've been given however is not realistic. How many practices are going to be in a position to satisfy the requirement that have not yet been issued before January 2011? The bonus payment that takes the 2011 reimbursement to $18,000 is based on meaningful use before January 2011.

And I replied: I contend that meaningful use of next-generation HIT can very well happen by 2011 and without great expense! Success will depend on the promotion and adoption of radical (disruptive, discontinuous) innovation. [Full disclosure note: My company is offering a novel cost-efficient way to exchange and evolve computational models in loosely coupled professional and social networks, which is an essential function for developing and deploying PCCS-enabled HIT.]

Saturday, June 20, 2009

Meaningful Healthcare Reform: Challenges and Solutions

David Koitz of The Concord Coalition, who is a former analyst for The Congressional Research Service and the Congressional Budget Office, just published a provocative paper entitled: Electronic Record Keeping, Wellness Programs, and Care Coordination -- Would They Yield Real Savings, and When? While he makes many good points about the shortcomings and uncertainties of current strategies being proposed to realize meaningful healthcare reform, the paper overlooks certain important factors. Here are some excerpts from Mr. Koitz's paper, followed by my comments:

The Obama Administration has proposed a number of changes aimed at increasing efficiencies in the nation's health care system… But their potential to control rising medical costs should not be overstated. It is unclear whether…they would have a positive effect on the tendency of an entrenched fee-for-service health care system to encourage excessive services and other forms of volume driven expenditures.

Even assuming that they would have a positive effect, it is unlikely to be seen for many years...[and] health care costs are projected to grow by $2 trillion between now and 2018, and at an annual rate of 6.2 percent, or about one third faster than the economy.

The Congressional Budget Office (CBO) projects that the current effort to promote health IT would reduce health care spending by less than half of one percent over this period…[The] effort would do little to ease rapidly growing health care costs at a time when population trends are expected to exacerbate them. And while promoting wellness programs and care coordination may prompt healthier life styles and better treatment outcomes, studies suggest their potential to create long-term savings has not been demonstrated.

…Many health providers have not made the investment because the cost is greater than the potential savings in lower office costs or increased revenues…Overall, startup costs can exceed $40,000 per physician…No one really knows the true potential of health IT, not only to improve outcomes of medical care, but to control costs. Moreover, CBO's projections suggest that the development process would be lengthy with any real benefits not materializing for a number of years. And even if the rise in health care spending is slowed…any such effects would eventually diminish. CBO further points out that by improving adherence to treatment protocols, the proliferation of health IT could increase the amount of care provided, and thus offset the potential savings…For health IT to succeed, the security of those records is paramount.

...Wellness programs are intended to alter lifestyle choices that people make which contribute to ill health and disease, and that eventually may require medical intervention to ease or remedy… As with efforts to promote health IT, expectations of savings from wellness programs may be inflated…[Wellness programs] have been adopted by too many businesses, insurance companies, and health care providers with success to dismiss their significance in improving the nation's health…However, they too carry costs, and other factors can limit or offset their potential to contain the nation's health expenditures…[because] modification of the public's adverse behavior can take years of costly information campaigns and financial incentives, so the immediate impact on health spending may be limited…[and because such] efforts can lead to greater expense…[if preventive medicine leads] to additional services for some who are generally in good health and don't need costly medical care…[Futhermore,] spending on diseases caused by unhealthy behavior could decline substantially in the long run, but the impact on federal entitlement spending would rise as people live longer… As with health care IT, the investment in wellness is better justified as a public good than as a strategy for controlling overall costs.

Yet a third initiative suggested by the Administration involves…"care coordination," [whose] goal is to improve medical outcomes, limit hospital and nursing home stays, and reduce cost by…[delivering care in] a more comprehensive or holistic fashion… Medicare experiments and demonstrations with care coordination, disease management, and case management, have shown some positive impacts on the quality of service and patient satisfaction, but…none yet has conclusively shown it can reduce program costs significantly.

…The basic concept of the medical home model is to have a designated primary care physician coordinate all types of care and services needed by a patient -- preventative, acute, and chronic -- from a full range of potential providers, whether they be medical specialists, hospitals, rehabilitation facilities, laboratories, or other… Proponents believe that the continuity of oversight and better coordination of care will yield health care savings…[by reducing] health care spending by ensuring that services and treatments are based on a comprehensive view of the patient, follow evidence-based guidelines, and avoid unnecessary or duplicative tests and procedures.

However,…it relies on an adequate supply of primary care physicians, which appears to be lacking today…[In addition,] the medical home model could actually lead to increases in health care spending if patients responded by seeking more services -- or if payments to primary care physicians merely added to Medicare expenditures…The bottom line is that the impact on spending from improved care coordination of the chronically and multiply impaired patient remains unclear.

Another strategy…is the creation of voluntary accountable care organizations…[which] would allow groups of providers meeting threshold requirements to share in the savings they achieve from serving a minimum number of patients. There would be no "gatekeeper" or other change from current payment systems or benefits. Instead, the ACO as a whole would be responsible for the overall cost and quality of care for those patients assigned to it. Savings to be shared by ACO members would be calculated from an estimated baseline for serving its assigned recipients, who would remain free to seek medical care beyond the ACO… Proponents believe that ACOs would provide a flexible approach to fostering cost control by creating an incentive, not currently in existence, for providers to reduce unnecessary volume of services while improving quality of care…While the general concept has shown promise…success in broader applications would depend on several factors that are far from certain… Still, according to CBO, "By encouraging providers to begin developing more efficient systems for delivering care, this option could be an initial step toward changing providers' current systems of delivering care and could pave the way for greater changes in the future."

…[In conclusion,] with the exception of ACOs,…[these three initiatives] don't address head on the proclivity of our fee-for-service systems to profit from more rather than less service…For the most part, the predisposition of the nation's health care providers will still be to spend whatever the public's mélange of health care financing options permits, which in the aggregate operates with few dictates of what constitutes the most cost-efficient care…[These] initiatives are probably best seen as only the beginning of what likely will be a complex and stressful search for health care savings.

The concerns raised by Mr. Koitz are valid, but he overlooks certain important things about the potential of health IT (HIT) if it is used in meaningful ways. Specifically, it fails to consider the possibility of very low-cost EHRs and PHRs bundled with next-generation clinical decision support tools providing patient centered cognitive support (PCCS). These tools would deliver the following benefits:

  • They would not only reduce duplication in services and error rates, but also help lower overall expenditures by promoting consistent delivery of the most cost-effective care based on the most recent research.
  • They would guide clinicians and patients in selecting the treatment and preventive options demonstrating the greatest efficacy for the lowest cost and with the least risk.
  • They would promote ongoing clinical outcomes research by feeding an evolving data warehouse that researchers and other collaborators use to develop and evolve evidence-based practice guidelines that are incorporated into the decision support tools.
  • They would enable clinicians to override guideline recommendations and offer valid justifications for such variance. The variant procedures and their outcomes would be added to the research data warehouse, thereby (a) reducing the likelihood of unnecessary, inappropriate, ineffective, and inefficient care and (b) continually improving the guidelines themselves.
  • By including a cyberinfrastructure promoting development and evolution of PCCS-based decision support models, those tools would become ever more reliable and useful.
  • All of this would counter the tendency for fee-for-service providers to profit from the delivery of unnecessary or excessively costly care by replacing the fallacious notion that more (expensive) care is better care. Instead, the focus would be on identifying and delivering cost-effective care and rewarding providers who render such high-value products and services.
  • It would also facilitate the medical home, ACO, and care coordination strategies—which I contend have great potential—as well as make wellness programs more effective.

Mr. Koitz also make a valid point about how keeping people healthier longer through wellness programs and medical homes is more likely to result in greater number of elderly with multiple expensive chronic conditions (even though they may occur later in life). I don't have a solution for this since there is no way refute the fact that our healthcare costs would be much lower if many more people were to die younger, and even more so if they were healthy and young when they died (a disgusting proposition!).

When it comes to dealing with security and privacy of personal health information (PHI), there are innovative solutions in which the patient/consumer is in control of one's own PHI without great expense (such as I describe at this link).

I also agree with Mr. Koitz in his assertion that significant short-term savings are unlikely, no matter what is done at this time. This sad situation, I contend, is the result of years of inaction; it is not due to any inherent shortcomings of strategies focused on deployment of next-generation HIT, medical homes, and care coordination. I say this after years of frustration. Similar strategies were recommended over 20 years ago, but our calls fell on deaf ears. If such strategies were implemented back then, we would have already been enjoying the benefits of lower cost and higher quality. In fact, we may very well have avoided our current catastrophic situation!

Radical transformation of our healthcare system is a MUST DO, and if our priorities are right, it's also a CAN DO. Moving slowly or continuing to wait is unacceptable since the situation will only worsen. While I'm hopeful that fundamental change is about to happen, my enthusiasm is tempered by our history. After all, there's good reason to believe that Winston Churchill was correct when he said: "You can always count on Americans to do the right thing — after they've tried everything else." We've been engaged in slow, incremental change for decades and it has failed miserably. It's now time to do the right thing…and that's NOT more of the same!

My next post debates gradual versus radical change.

Friday, June 12, 2009

Toward a Meaningful Definition of Meaningful Use (part 2 of 2)

As I discussed in a prior post, the federal government's $20 billion stimulus programs for health IT (HIT) —called HITECH—will fund the development of innovative HIT and use a "carrot & stick" financial approach to encourage clinicians to use HIT in meaningful ways. Unfortunately, the government did not clearly define term “meaningful use,” which has led to an intense debate over its meaning.

The definition I proposed was “using HIT to increase care value (effectiveness and efficiency) by providing ever-better patient-centered cognitive support.” This definition raises the bar over other definitions being offered because it focuses realizing the benefits of ever-increasing care value (effectiveness and efficiency), which is something mainstream HIT does not do.

In this post, I do four things:
  1. Refine the patient-centered cognitive support (PCCS) definition
  2. Compare and contrast PCSS with clinical decision support (CDS)
  3. Clarify why PCCS capabilities in HIT tools should be a requirement of meaningful use
  4. Explain why radical innovation is essential.

Defining Patient-Centered Cognitive Support

As discussed in a recent report by the National Research Council of the National Academies, PCCS is a computerized process that improves decision making by fostering profound understanding through use of a "virtual patient" model.

According to their definition, the PCCS process employs a computerized model of a "virtual patient" that reflects (i.e., is an "abstraction of") an actual patient. An HIT tool would use this virtual patient to guide the selection and analysis of data. These targeted data would be:
…relevant to a specific patient and suggest their clinical implications…[This would] provide decision support…that helps clinicians decide on a course of action in response to an understanding of the patient's status…[These tools would take into account] patient utilities, values, and resource constraints…[and they would] support holistic plans [of care]…These virtual patient models are the computational counterparts of the clinician's conceptual model of a patient. They depict and simulate the clinician's working theory about interactions going on in the patient and enable patient-specific parameterization and multicomponent alerts. They build on submodels of biological and physiological systems and also exploit epidemiological models that take into account the local prevalence of diseases. The availability of these models would free clinicians from having to scan raw data, and thus they would have a much easier time defining, testing, and exploring their own working theories. What links the raw data to the abstract models might be called medical logic—that is, computer-based tools examine raw data relevant to a specific patient and suggest their clinical implications given the context of the models and abstractions. Computers can then provide decision support—that is, tools that help clinicians decide on a course of action in response to an understanding of the patient's status. At any time, clinicians have the ability to access the raw data as needed if they wish to explore the presented interpretations and abstractions in greater depth.
In other words, the virtual patient used in the PCCS process is a computer program with advanced computational algorithms (mathematical and logical operations/steps). The algorithms "…incorporate physics (such as mechanical and electrical properties of tissue) and biology (from physiological to biochemical information) into a platform so that responses to varied stimuli (biological, chemical, physical, and…psychological) can be predicted and results viewed" [Ref: Oak Ridge National Laboratory].

Furthermore, a HIT tool implementing the PCCS process takes "…observations of an individual patient and relates them to a vast dataset of observations of others with similar symptoms and known conditions. By processing all this information, the model can simulate the likely reaction of the individual patient to possible treatments or interventions. Such tools will not only improve the quality of treatment offered to patients who are already ill or injured, but could also be used in preventive medicine, to predict occurrence or worsening of specific diseases in people at risk, for example through family history [Ref: Europe's Information Society Portal]. These simulations and predictions are used to support decisions by identifying the treatment and preventive approaches most beneficial to the virtual patient model, which would then be most likely to benefit the actual patient upon which the virtual model is based.


Unfortunately, today's mainstream HIT systems do not employ the PCCS process. This, according to same National Research Council report, is a most serious HIT gap. The reason is that PCCS-enabled HIT tools are essential for helping clinicians to understand their patients' problems and needs without having to:
…spend a great deal of time and energy searching and sifting through raw data about patients and trying to integrate the data with their general medical knowledge to form relevant mental abstractions and associations relevant to the patient's situation…[Unfortunately, today's HIT systems] squeeze all cognitive support for the clinician through the lens of health care transactions and the related raw data, without an underlying representation of a conceptual model for the patient showing how data fit together and which data are important or unimportant…As a result, an understanding of the patient can be lost amidst all the data, all the tests, and all the monitoring equipment. In the committee's vision of patient-centered cognitive support, the clinician interacts with models and abstractions of the patient that place the raw data into context and synthesize them with medical knowledge in ways that make clinical sense for that patient.
Since they do not use the PCCS process, mainstream HIT tools do not:
  • Help clinicians gain substantially greater understanding of their patients' situations (i.e., their strengths, weaknesses, risks, needs, and options)
  • Enable patients to understand their own situations better.
Decision-making suffers as a consequence.

Eliminating the HIT-PCCS gap would enhance understanding and promote better shared decision-making about treatment, prevention, health promotion, and self-maintenance (see this link and this link). Because both clinicians and patients would be better informed through the PCCS process, the decisions they make would be more likely result in better outcomes (higher quality and safety) at lower cost. This would translate into increased care value (effectiveness and efficiency). In other words, using HIT tools that implement the PCCS process would help realize important benefits to individuals and society. These benefits include achieving the goals of both the Federal HIT Strategic Plan and the Institutes for Healthcare Improvement's "Triple Aim."

Federal HIT Strategic Plan Goals

PCCS-enabled HIT would help achieve the goals of the Federal government's HIT strategy. According to the Office of the National Coordinator for Health Information Technology, the American Recovery and Reinvestment Act (ARRA) Implementation Plan:
American patients and their caretakers will be the ultimate beneficiaries of the following activities aimed at achieving the President's health IT initiative to accelerate the adoption of health IT and utilization of electronic health records. All of the activities discussed in this section support the current two Federal Health IT Strategic Plan goals:
  1. Inform Health Care Professionals: Provide critical information to health care professionals to improve the quality of care delivery, reduce errors, and decrease costs.
  2. Improve Population Health: Simplify collection, aggregation, and analysis of anonymized health information for use to improve public health and safety [Ref: ONC HIT] 

Institutes for Healthcare Improvement's "Triple Aim"

PCCS-enabled HIT also helps achieve the goals of the Institute for Healthcare Improvement (IHI) recently proposed healthcare improvement design—called the Triple Aim—which has these three critical objectives:
  • Improve the health of the population
  • Enhance the patient experience of care (including quality, access, and reliability)
  • Reduce, or at least control, the per capita cost of care [Ref: About the Triple Aim Initiative].
It is essential, therefore, that utilization of the PCCS process be included in the definition of meaningful use of HIT since sustainable healthcare reform benefits cannot be achieved without it!

PCCS and Meaningful Use of HIT

Based on the discussion to his point, it seems reasonable to conclude that HIT tools are used meaningfully if they employ the PCCS process in order to:
  • Save clinicians time and energy by automating searching and sifting through a patient's clinical details and related research guided by a virtual patient model.
  • Promote a deep and broad understanding of a patient's health status, including the interplay of biological, psychological, and social (i.e., biopsychosocial) influences—past, present, and future.
  • Provide effective, personalized decision support regarding diagnosis, treatment, prevention, and health promotion. And this decision support would:
    • Account for patient preferences, qualities, and circumstances
    • Help improve overall care value
    • Continually evolve.
The following section discusses how PCCS provides superior decision support.

PCCS and Decision Support

A key question concerning PCCS and decision support is: What HIT tools provide decision support and is this decision support based on the PCCS process? To answer this question, let's examine two classes of HIT tools that offering decision support: electronic health records (EHRs) and clinical decision support (CDS) systems.

Electronic Health Records

One type of HIT tool providing some decision support is the EHR (and its electronic medical record counterpart). According to the Concise Guide to CCHIT Certification Criteria, certified EHRs deliver the following decision support capabilities (note that I combined ambulatory and inpatient EHR decision support criteria in the following list):
  • Alerts and Warnings
    • Provide alerts/warnings when
      • There are abnormal test results
      • Patient's vital signs fall outside the normal range
      • Patient is allergic to a drug being ordered
      • Drug or food interactions may occur
      • A follow up test is recommended
      • Patient is currently on a drug for which an allergy has been newly entered
      • Drug side effects may occur based on diagnosis
      • More appropriate or cost-effective therapy could be substituted
      • Drug or food interactions may occur
      • Medication dose is out of recommended range
      • Patient is already on similar drug
      • Patient is currently on a drug for which an allergy has been newly entered
      • Order may be a duplicate
      • More appropriate or cost-effective therapy could be substituted
      • A follow-up or related order is recommended
      • Immunizations are due or overdue
    • Give the reasoning behind an alert, and allow override if appropriate
    • Allow adjusting alert severity based on the clinician's role
    • Report the effect of alerts on clinical decisions
    • Provide dosing guidance based on:
      • Patient weight
      • Lab results
      • Scientific reference material
    • Warn when a medication should not be given because of:
      • Patient age or weight
      • Pregnancy or mother who is nursing
    • Block ordering medications via the wrong route (such as oral vs I.V.)
  • Reminders
    • Provide reminders of recommended care that is due or overdue
    • Generate a list of patients for whom care is due or overdue
    • Generate letters to patients automatically for care that is due or overdue
  • Identify patients for disease and wellness management according to guidelines
    • Based on age, gender, diagnoses, medications, lab results
    • Allow physicians to personalize the care guidelines for individual patients
  • Generate patient education material for medications, diagnosis, procedures and tests
    • Allow tailoring for the patient
  • For inpatient nursing staff:
    • Display for the nurse at the time of administering medications:
      • Any previous alerts
      • Patient's test results and allergies
      • Allow the nurse to use bar-code technology to assure "5 rights" (right patient, drug, dose, time and route)
    • Require the nurse to complete tasks, such as allergy verifications, prior to giving medications.
This list of criteria defines EHR-based decision support as: (a) warnings and alerts about abnormal test results and vital signs, medication issues, duplicate orders, follow-ups, immunizations, and certain therapy substitutions; (b) reminders regarding care due dates; (c) assistance with selection of basic general guidelines in certain situations; (d) general patient education materials; and (e) basic information for hospital nursing staff.

Such EHR-based decision support can be helpful in certain ways. However, since they do not employ the PCCS process, conventional EHRs do not:
  • Search and sift through all of a patient's clinical data and the related research
  • Take into account all the relevant aspects of patient's particular combination of personal preferences, qualities, and circumstances
  • Examine the interactions between a patient's biopsychosocial health problems, threats, needs, and strengths
  • Do an adequate job reporting quality measures (as indicated in a draft report by the National Quality Forum).
And as a result, they do not:
  • Help emerge a deep understanding of a patient's particular health status and risks
  • Generate detailed, personalized, holistic plans of care.
So, even when EHRs provide decision support, their failure to employ the PCCS process severely limits their value in improving healthcare quality and controlling costs. The same can be said, by the way, for personal health records (PHRs).

Today's EHRs (and PHRs), therefore, fall far short of what is needed for "meaningful use" because they do not employ the PCCS process.

Let us now examine another type of HIT tool providing decision support: Clinical decision support (CDS) systems

Clinical Decision Support Systems

Clinical decision support (CDS) systems, not surprisingly, go well beyond the typical EHR in the area of decision support, and some may be add-ons to EHRs. These CDS systems offer:
  • Evidence-based diagnostic assistance
  • Personalized rather than generic information based on a patient's unique symptoms and background
  • In-depth evidence-based guidelines and clinical pathways.
Following are some examples of CDS systems:
Do such CDS systems employ the PCCS process? Well, things tend to get a bit blurry here. A CDS system does implement the PCCS process if it uses evolving virtual patient models to help increase care value by:
  • Automating data searching and sifting
  • Enabling a deep and broad understanding of a patient's biopsychosocial health status
  • Providing personalized decision support precise enough to account for an individual patient's preferences, qualities, and circumstances.
Even if certain CDS systems do utilize the PCCS process, this HIT class is not commonly used in clinical practice or by patients, which only adds to HIT-PCCS gap. 

Establishing Meaningful Use by Bridging the HIT-PCCS Gap

Bridging the HIT-PCCS gap means deploying mainstream HIT tools the implement the PCCS process. These tools would demonstrate a meaningful use of HIT, as discussed below.

Why Meaningful HIT Use Requires PCCS

The reason for making the PCCS process a requirement of meaningful HIT use is because it fosters profound understanding, supports evidence-based decisions, and promotes ever-greater care value by helping to answer questions such as:
  • What are the person's current health problems and risks, taking into account (a) all pertinent physiological and psychological signs and symptoms, (b) all relevant biomedical and psychosocial influences, (c) any related treatments and medications received, and (d) the outcomes of care already rendered? What are the metabolic, genetic, emotional, and behavioral factors affecting the person's health and wellbeing?
  • Is the person's health status being affected by a mind-body interaction and, if so, how is this interaction manifested (see this link for more)?
  • How does the person compare to other people having the same kind of problems, qualities, and circumstances? How are the person's similarities and differences associated with clinical outcomes?
  • What is the prognosis (likely outcome)—short-term and long-term, physically and psychologically—if the person makes no lifestyle changes?
  • What should the plan of care be for treating the person's problems, or for avoid his/her risks from becoming problems—taking into (a) account all relevant research (including conventional allopathic and complementary and alternative approaches), as well as (b) the person's preferences, qualities, and circumstances? What are the risks, benefits, and costs of different plan of care options according to the research?
  • When should certain tests, procedures, or prescriptions not be done/given because they were already done/given, or because they are unnecessary or inappropriate?
  • If an error is made, how can it be rectified with least adverse impact on the person?
  • When has a recommended test or treatment been missed or overlooked, and what should be done about it now?
  • How should the care be coordinated for efficient, effective continuity of care across the healthcare continuum? Who should be collaborating in delivering the person's care and why? What particular personal health information can and should be exchanged with each particular collaborator?
  • How effective is the care currently being rendered (refers to treatment process assessment)? When should a plan of care be modified, why should it be changed, and how should it be different?
  • What was the outcome of each episode of care? What positive and negative factors contributed to the outcome?
  • When does variance from (departure from, non-adherence to) a preferred practice guideline result in better outcomes for a certain types of patients than compliance to it? Why does the variance happen? Who is most likely to benefit from a particular guideline?
  • What patient education/training is required for people with a particular condition in order to promote good self-maintenance?
  • Is the patient adhering to the plan of care? If not, then what are his/her psychological blocks, economic and social obstacles, etc. and how can a patient become more motivated to follow the plan? When is it good that a patient does not adhere to a particular care plan and why?
  • What about a person's social relationships are likely to improve or worsen outcomes? How should one's plan of care be adjusted accordingly?
Unless questions such as these can be answered validly and reliably, there is little chance that HIT decision-support will increase care value and realize sustained improvements in care effectiveness and efficiency. This is why bridging the HIT-PCCS gap is essential to the meaningful use of HIT.

How HIT Tools Can Provide PCCS

Creating and evolving innovative HIT tools that provide PCCS can be a daunting challenge. Accomplishing this goal would require innovative PCCS-enabled HIT tools that:
  • Manage complete personal health information (PHI)
  • Develop and using virtual patient models
  • Support collaboration in loosely-coupled professional and social networks
  • Fit the HIT tools into existing clinical workflows. 

Managing complete protected health information (PHI)

Innovative HIT systems that employ PCCS should securely manage (obtain, analyze, and present) complete biopsychosocial protected health information (PHI) over people's entire lifetimes. To be useful, this PHI should:

Developing and using virtual patient models

It is important that these virtual patient models present decision-support information that is relevant to the specific patient (a) in the context of the current situation and (b) in relation to the whole patient and his/her predispositions. Following are examples of what the models should do.

The virtual patient models should obtain comprehensive PHI from any data streams, manual inputs, biometric sensors, and data stores (databases, files, etc.). In addition to patient status and health history, this information should encompass clinical process data, as well as results tracking, which includes outcomes data, guideline compliance rates, and the reasons for variance (departures) from the guideline recommendations.

The virtual patient models should use computational algorithms that analyze the data obtained in order to identify important patterns (e.g., trends, associations, clusters, and differences) useful for making predictions, linking diagnosis to cost-effective treatments, conducting health-related surveillance (biosurveillance and post-market drug & medical device surveillance), etc. And test the data for statistical relevance to determine which information provides reasonable explanations. The results of such analyses would help determine, for example:
  • Whether a person's risk factors and changes in lab test results or vital signs indicate an imminent or worsening health condition
  • How a person's attributes (e.g., gender, age, medical history, conditions, vital signs, symptoms, genetics, attitudes, etc.) compare to people in different diagnostic groups
  • What treatment options and self-management approaches are most likely to result in the best outcomes for a particular person by accounting for the individuals particular attributes
  • If a medication currently in the market is evidencing side-effects at a higher rate than found in clinical trials
  • If clusters of a particular illness are widespread and indicative of a pandemic, or if the clusters are localized and indicative of environmental toxin, etc.
The virtual patient models should also provide feedback (including suggestions and reminders) and guidance (e.g., diagnostic aids and evidence-based guidelines) presented in personalized views that facilitate decision making, care coordination, and competent care delivery. This would help:
  • Clinicians (a) make valid diagnostic decisions; (b) make evidence-based preventive and therapeutic determinations; (c) deliver appropriate care cost-effectively through efficient, safe and effective procedures; and (d) avoid under-testing, over-testing, under-treating, and over-treating their patients.
  • Patients understand their diagnoses, risks, and treatment options, as well as learn how to self-managements their own health wisely and responsibly.
These models would, therefore, provide PCCS through useful personalized information that increases the likelihood of positive outcomes.

Supporting collaboration in loosely-coupled professional and social networks

Loosely-coupled professional and social networks (as opposed to technical networks) consist of people from multiple locations—who have different roles, responsibilities and experiences—who collaborate to make decisions beyond the knowledge or skills of any individual. These loosely-coupled networks would enable clinicians, researchers, patients, and informal caregivers to pool their wide diversities of knowledge, ideas, and points of view, thereby providing a larger collection of intellectual resource and offering access to a greater variety of non-redundant information and knowledge on which to base decisions.

For example, collaborating researchers and clinicians would foster the emergence of health science knowledge by analyzing, discussing, and interpreting care process and outcome data in light of patients’ diagnoses and qualities. This would promote the development and evolution of virtual patient models by transforming this knowledge into evolving evidence-based guidelines aimed at the continuous improvement of care effectiveness and efficiency.
Another important thing these collaborative networks can do is share and "play seriously with" different virtual patient models. That is, they would compare models and test them for their ability to reflect reality accurately; they manipulate the models to represent different scenarios, such as "what if" scenarios about the probability of future occurrences; and they 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, looking for logical flaws and inconsistencies and debating about the assumptions and practical value of the model. By challenging the model's assumptions, useful counterintuitive insights often emerge, innovative thought is sparked, new questions arise, and compelling and unexpected issues are discovered. This means that sharing and playing with models is an effective path to innovation and value creation.

As such, these loosely-coupled networks provide the greatest opportunities for emerging creative ways to develop, evolve, and use the virtual patient models that provide PCCS.
These loosely-coupled networks should be supported by a cyberinfrastructure that, as described by the National Science Foundation,"…combines computing, information management, networking and intelligent sensing systems into powerful tools for…collecting and analyzing large volumes of data, performing experiments with computer models and bringing together collaborators from many disciplines." [Ref: NSF]. The cyberinfrastructure should be secure, economical, easy-to-use, and convenient.

Fitting the HIT tools into clinical workflows

PCCS-enabled HIT tools should assist clinicians in making decisions during their natural course of work, rather than requiring major adjustments of their workflows. This would increase the likelihood that clinicians will take advantage of that PCCS. 

The Need for Radical Innovation

The National Research Council’s report calls for radical change this way:
Change in the health care system can be viewed through two equally important
lenses—those of evolutionary and of radical change. Evolutionary change means
continuous, iterative improvement of existing processes sustained over long
periods of time. Radical change means qualitatively new ways of conceptualizing
and solving health and health care problems and revolutionary ways of addressing those problems. Any approach to health care IT should enable and anticipate both types of change since they work together over time.
Unfortunately, the HIT industry is focused on the gradual evolutionary change of existing products in lieu of radical leaps of change through development of new breeds PCCS-enabled HIT tools. This is why an abundance of conventional EHR commodities now crowd the mainstream market (see, for example, this link and this link), yet there is little attention given to CDS systems and almost no attention to PCCS.

As a result, there is a tendency to define meaningful use simply in terms of conventional HIT commodities, instead of “raising the bar” to new heights by requiring disruptive (radical, discontinuous) PCCS-enabled innovations. For example, the HIMSS definition of meaningful use, which was developed by a HIT vendors’ association, calls for the immediate use of current day EHRs and related HIT commodities, but doesn’t require CDS systems to be used until 4-7 years from now. Furthermore, the degree of decision support to be delivered by the CDS systems is minimal and falls far short of delivering the benefits of the PCCS process.

The meaningful use definition, therefore, ought to balance these evolutionary changes with the requirement for dramatically different types of software applications—a new generation of radical innovations—that employ the kind of PCCS able to help transform our healthcare system for the better.


Any good definition of meaningful use of HIT ought to include the implementation of the PCCS process to drive ever-evolving clinical decision support.

Since mainstream HIT tools to not employ the PCCS process, realizing such meaningful use will require substantial long-term commitment by diverse groups of collaborators in the development, use, and evolution of virtual patient models. If increasing healthcare value is truly our nation's goal, then there is no good alternative!