Google engineering too slow? Facebook too invested in the wrong data model to adapt? Are you kidding me?

Few things in my work life are better than finding mind-blowing information from other industries and figuring out the implications for healthcare.

I recently read a set of slides by Paul Adams, a user experience designer that worked at Google and Facebook.  Although Adams’ presentation had 224 slides, the main thesis was relatively simple and obvious. The best insights usually are. Adams pointed out that online social media applications create a single category of relationships, called “friends.” They put every social relationship in that one bucket.  Wife, college sweetheart, boss, party friends, kids …  all just “friends.”  In contrast, real-world social networks — the kind that humans have cultivated for millions of years — are characterized by various groupings of people representing different roles, life-stages and social contexts, with different levels of strength and trust.

Diagram from Paul Adams' presentation on Real World Social Networks

He described the research that shows that people typically have 4-6 different groupings of friends.  People typically have fewer than 10 strong ties that consume most of their communication attention.  They typically don’t have more than 150 weak ties.  They have many “temporary ties” that may influence their behaviors for relatively short periods of time.  He points out that existing social media applications create problems for their users because the users publish information intended for one group of people that ends up being received by others.  Like wild party pictures being viewed by your prospective employer.

I came across Adams’ presentation through a link from a CNN article by Dhanji Prasanna that tells the story of how Adams developed these ideas when he was part of a team at Google that was developing Google’s response to Facebook.  The CNN article explains that Google had an engineering culture and a technology infrastructure that made them too slow to develop an application that took Adams’ insights to heart.  Adams then left Google to join Facebook.  But, Facebook was deeply invested in the simplified one-big-bucket social graph at the heart of the system that now has 750 million users.  So, despite Facebook’s “hacker” engineering culture that allows it to develop applications rapidly, they were unable to solve their fundamental problem.  They eventually launched Facebook Groups, which is a superficial answer to the insight that people have multiple groups of relationships.  But, Facebook’s central “one-big-bucket” friends model was apparently deemed too risky to touch.

My eyes rolled.  Google’s culture makes them too slow?  Facebook can’t innovate?  Are you kidding me?  If only we could experience a tenth of the agility shown by those two companies in health care, which has long suffered from a powerful aversion to risk and change in both care delivery and information technology.

But, there are deeper connections between Adams’ insights about social networks and our challenges in transforming our health care system.

First, the health behaviors of patients are strongly influenced by their social networks. For years, health care providers, health plans and vendors of wellness and care management services have attempted to promote smoking cessation, exercise, healthy diet, compliance with medication orders, and other health and lifestyle behaviors by designing “interventions” that target individual patients.  A whole industry of “health risk assessment” and “predictive modeling” was built up to try to identify which individual patients to target.  But, such an approach has produced unimpressive results.  That should not have been surprising.  Decades old research about the diffusion of innovations has shown that lifestyle behaviors in a population change through social networks.  People follow the lead of the people around them.  Therefore, to be effective, wellness and care management programs need to be designed to work through those existing social networks.  We need to be targeting groups of people that are already connected, rather than just reaching out to individuals.  We need to be designing our communications and incentive approaches so as to augment and leverage our patients’ social networks.  To support such social-network-oriented clinical programs, we need information systems that capture information about those social networks and that are designed to interact with them.   But, when we examine the fundamental data model and features of the market-leading electronic health record (EHR) systems, such capabilities are nowhere to be found.  Those vendors, blessed with a large installed base, may be unable to make such fundamental changes to their systems.  Like Google and Facebook, the leading  EHR vendors may not be agile enough to address our emerging understanding of the importance of social networks that exist among our patients.

Second, the relationships between patients and care providers are types of social network relationships.  I call these care relationships.  When we talk about “accountable care,” we mean that some provider organization is taking responsibility for the quality and cost of care for a population of patients. When we talk about a “patient-centered medical home,” we mean a team of primary care physicians, nurses and other care providers proactively taking care of a group of patients. But, who exactly are those patients? We have developed some very crude primary care “attribution” logic that tries to derive care relationships from claims data.  But, we do a very poor job of validating such derived care relationships or proactively declaring new care relationships.  And we don’t keep track of changes in care relationships.  We don’t have established processes to inform the participants in those relationships when one of the parties determines that they don’t intend for the relationship to exist.  We don’t distinguish between different types of care relationships.  If a patient has heart failure and sees both a primary care physician and a cardiologist, we don’t explicitly declare which physician has the care responsibility for that patient problem.

Furthermore, the referral relationships among providers are also types of social network relationships.  As with Adams’ real-world social networks, these relationships among patients, primary care doctors, specialists, hospitals, home health care nurses, pharmacists, and others are complex and dynamic.   Yet, when you examine the systems we use to keep track of these relationships, they are primitive or non-existent.  Just as over-simplification of social network relationships has reeked havoc for social media users, so has over-simplification of care relationships, care responsibilities and referral relationships harmed clinical communications and accountabilities.  This deficiency ultimately reduces the effectiveness of care. As a result, patients are harmed.

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Klar 4: Why is it important for CMS to Share Claims Data with ACOs?

Ron Klar, MD, MPH

Ron Klar, MD, MPH is a health care consultant with a long history of involvement in federal health care policy and health plan innovation. He published a recent series of three posts regarding the draft rules for the Medicare Shared Savings Program (MSSP) in the Health Affairs Blog, an influential forum for debating health policy issues. This is my last in a series of 4 posts describing areas of agreement and disagreement with Dr. Klar. (The others are available at post 1, post 2 and post 3)

In his third post to the Health Affairs Blog, Dr. Klar proposed to eliminate CMS sharing of claims data with providers. He argued that it is too delayed to serve any useful purpose to the ACO, either for clinical operations or analysis.  He also argued that supplying ACOs with claims data would be expensive for both CMS and the ACOs that would need to create interfaces, databases and applications to receive and use the data.  He argued that it would distract providers from investment in electronic health records (EHR) and health information exchange (HIE).  Finally, he argued that it would violate the confidentiality of non-ACO providers who would be identified in the data.  Klar implies that all of the data needs of the ACO can be met with EHR data, augmented with HIE data.

I strongly disagree with this thinking.  The success of ACOs will require a transformation of the health care organization from one that reactively cares for individual patients to one that also proactively takes responsibility for a population of patients.  The analytics to support that transformation requires a comprehensive view of all the health care services received by the population.  Since patients are free to seek care from any provider participating in Medicare, only CMS can provide this comprehensive view of the data. An EHR may be richer and more up-to-date, but it lacks this comprehensive view.  An HIE might increase the completeness somewhat, but without data from the payer, it is not possible to know how much missing data might be beyond the reach on any particular HIE at any point in its development.  For the foreseeable future, EHR and HIE data are too inconsistently structured and too incomplete to give a true population-oriented measure of utilization.

In earlier demonstration projects of accountable care and care management, the participants complained that the data shared by CMS was not delivered in a useful and timely way.  So, not only must we keep the CMS claims data sharing in the ACO rules, we must also make sure that CMS does a better job of delivering it this time around.


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Dr. Ward’s Slides from AMGA ACO Learning Collaborative, Chicago, July 14, 2011

Presentation entitled “Developing the Economic Model for Success” from day 2 of the American Medical Group Association’s Accountable Care Organization Learning Collaborative, at the Swissotel in Chicago.  Attended by approximately 60 leaders of AMGA member physician organizations and other interested parties.

Full page PDF format.

Hand-out PDF format.

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Klar 2: The great attribution debates: Include specialists or not? Plurality or majority? Retrospective or prospective? Derived or declared?

Ron Klar, MD, MPH

Ron Klar, MD, MPH is a health care consultant with a long history of involvement in federal health care policy and health plan innovation.  He published a recent series of three posts (post 1, post 2, and post 3) regarding the draft rules of the Medicare Shared Savings Program (MSSP) in the Health Affairs Blog, an influential forum for debating health policy issues. In a recent post of my own, I described where I agree with Dr. Klar.  In this post, I’ll describe some areas of disagreement related to the methods of defining the population for which the ACO is to be held accountable.  In two future posts, I’ll cover some additional areas of disagreement.

First, let’s define some terms.

I use the term “care relationship” to describe the data linking patients to providers.  Care relationship information can be “derived” based on other data such as encounter claims records.  Care relationships can be “declared” explicitly when the participants in the relationship – patients and providers – indicate that they intend for the relationship to exist or when they explicitly validate care relationship data that has previously been derived.  Or, care relationship data can be created and maintained through a mixture of derivation and declaration.  Others typically use the terms “attribution,” “assignment,” or “alignment” to describe care relationships, revealing their tendency to think only in terms of derived care relationships.   Derived care relationships can be determined “prospectively,” in advance of an accountability period.  Or, they can be determined “retrospectively,” at the end of an accountability period.

The draft rules for the MSSP proposes to define the population using derived care relationships.  The rules call for accomplishing this derivation by selecting the primary care physician that provided a plurality of the evaluation and management (E&M) encounter claims for a beneficiary, using an assignment process that is partly prospective and partly retrospective.

Dr. Klar proposed to change many aspects of the rules regarding care relationship derivation:

  1. Include specialists, rather than just primary care physicians
  2. The selection should be based on providing a majority (more than half) of the E&M services for a beneficiary, rather than just a plurality (more than anyone else)
  3. The derivation should be purely retrospective

Include specialists or not?

Klar’s proposal to include specialists is based partly on the fact that it will increase the proportion of beneficiaries assigned to an ACO.  Some beneficiaries have visits to specialists, but not visits to PCPs.  Such beneficiaries will only be assigned to an ACO if the assignment includes specialists.  Klar also asserts that including specialists in the assignment will stimulate organizations to “tie” specialists into the ACO.

For both of these same reasons, we originally included specialists in the “attribution” algorithms in the Physician Group Incentive Program (PGIP) at Blue Cross Blue Shield of Michigan (BCBSM).  But, we determined it was necessary to switch to what we called a “pure PCP” algorithm due to unanticipated consequences of including specialists in the attribution. When attribution includes specialists, beneficiaries with expensive conditions requiring specialist care are relatively more likely to be assigned to a physician organization (PO) or ACOs that include specialists, while PO/ACOs that don’t include specialists will tend to have a lower risk population.  Within the PO/ACO, a primary care physician that manages more of the heart failure in her panel of patients will have those patients assigned to her.  Another primary care physician who chooses instead to refer his heart failure cases to higher cost cardiologists will end up with those patients being assigned to the cardiologist.  As a result, the PCP that refers out heart failure management will have a more favorable utilization and cost profile.  These biases make it difficult to interpret performance comparisons when specialists are included in attribution.  I strongly prefer the “pure PCP” attribution approach.

Use plurality or majority?

In the PGIP program, as in the draft rule for the MSSP, we derived care relationships based on a plurality of E&M services, not a majority.  Whether the topic is managed care, patient-centered medical home, organized systems of care, or accountable care organizations, the idea is for providers to take responsibility for the care of a defined population.  Patients that flutter among many PCPs and don’t see any one PCP the majority of the time are still part of the population.  In fact, convincing such patients to have a more stable, exclusive relationship with one physician, or at least one primary care practice unit, should be a key objective of an ACO.  A majority standard would leave more members of the population without a derived care relationship with a PCP.  Therefore, a plurality standard is better than a majority standard.

Prospective or retrospective?

The draft rule for the MSSP proposes an assignment process that is partly prospective and partly retrospective. Many critics of the draft rule have called for a purely prospective derivation, arguing that ACO providers should only be held responsible for the cost and quality of care for patients that they knew about in advance.  But, Dr. Klar went against the crowd, calling for a purely retrospective derivation. He argued that the delay in claims data used for the derivation is too long, resulting in too much inaccuracy in care relationship data due to people switching their actual care relationships during the year.  Based on 25-33% annual turnover in care relationships, 44-55% of beneficiaries assigned before the start of a performance year would not still be assigned after the end of that performance year.  On that point, I agree with Dr. Klar.

But then Dr. Klar went on to provide another argument against any prospective assignment.  He asserted that prospective assignment would create an “undesirable distinction” among Medicare beneficiaries, causing prospectively assigned beneficiaries to be “treated differently” by providers.  He considered such distinctions to be inconsistent with expectations for the traditional Medicare fee-for-service program.  On this point, Dr. Klar has a lot of company.  Many advocates for Medicare beneficiaries are strongly defensive of the unlimited choice of providers currently intrinsic to the traditional Medicare program.  In that spirit, the health reform legislation prohibits restrictions limiting beneficiaries’ ability to  seek care from any participating Medicare provider. This prohibition could be interpreted as implicitly forbidding providers from having care relationship declaration processes where patients document their intention to have a primary care physician relationship, since that would possibly give the impression of “lock-in.”

The underlying debate about the role of the PCP

When I step back from the technical details and look at the bigger picture, it seems to me that Dr. Klar, like many others engaged in discussions about ACOs, seems to have a different conceptualization of the role of PCPs in ACOs than I do.  In proposing the inclusion of specialists in care relationship derivation, and by expressing concern about even giving the impression of fettering beneficiaries’ choice of providers, Klar reveals a conceptualization of an ACO that emphasizes the value of the organization, but does not necessarily emphasize the central role of PCPs.

I feel that a powerful, influential care relationship between a patient and her primary care physician is the main active ingredient in achieving ACO cost savings. In this context, the process of having patients declare or validate their care relationships is an important tool to creating the type of care relationship consistent with the vision of the patient-centered medical home (PCMH). In a PCMH care relationship, the patient understands the roles and responsibilities of the members of the team, and conceptualizes the patient and family as engaged members of that team.  In a strong PCMH-style primary care relationship, the primary care team can influence the patient’s behavior, encouraging adherence to the care plan, and promote effective self-management, involvement in informed medical decision-making, and healthy lifestyle behaviors.  Moreover, in a strong PCMH primary care relationship, the PCP can influence referrals for specialty and facility care, steering the patient toward specialists and facilities that are efficient and prudent. Such a role, when enforced through HMO-style mandatory referral authorization, can seem undesirable from the patient’s perspective, earning the pejorative title “gatekeeper.”  But, in a PCMH and ACO context, the primary care physician is challenged to effectively fulfill the gatekeeper function with one hand tied behind his back.  In an ACO, the patient is not required to seek a mandatory referral authorization from the PCP.  Therefore, to have influence over referral patterns, the PCP is challenged to earn the trust of patients and their families by demonstrating clinical competence and offering excellent service.  They are challenged to exert referral influence in softer ways designed to be satisfying or at least acceptable to the patient.  This influence causes more specialty and facility care to be delivered by more efficient providers.  And, it incentivizes all specialists and facilities to be more efficient.  In my estimation, this form of influence is the strongest active ingredient driving savings in ACOs – stronger than care coordination, stronger than patient-self management support, stronger than avoiding gaps in care through clinical decision support, and stronger than the avoidance of duplication of services through health information exchange.

Of course, there needs to be clear communication to beneficiaries of the voluntary nature of care relationships.  It must be clear that any declared care relationship information maintained by ACOs will not be used to determine shared savings or for any other CMS program administration purposes. But, the worry that ACO providers might implicitly influence patients to have an exclusive primary care relationship with them is not a risk.  In fact, the success of the ACO concept depends on it.

In summary, I’m willing to join Dr. Klar in his contrarian idea of using a purely retrospective care relationship derivation to determine MSSP reward payments.  But, I feel that the care relationship should be “pure PCP,” and the derivation algorithm should cast a wide net with a plurality criteria.  And, MSSP rules should make it clear that ACOs are permitted to create their own processes to track current care relationships, including processes that involve physician and patient declarations of care relationships.


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Possible one year delay to Stage 2 Meaningful Use?

Paul Tang, MD

According to an article in Healthcare IT News, an advisory panel that is shaping measures for the next stage of meaningful use has suggested delaying Stage 2 by one year, until 2014, as an option to give vendors and healthcare providers more time to update and roll out more advanced technology.  The panel is chaired by Paul Tang, MD (the CMIO from Palo Alto Medical Foundation).  If approved, providers who achieved level 2 during 2011 would be harmed by losing one year of incentive rewards.

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Notes and Thoughts re new ONC leader Farzad Mostashari and Senators Daschle and Bennett at Bipartisan Policy Center

Today I attended a webcast sponsored by the Bipartisan Policy Center, an organization “committed to the art of principled compromise.”

The webcast featured Farzad Mostashari, MD, ScM, the newly appointed National Coordinator for Health Information Technology, U.S. Department of Health and Human Services.  He was joined in a panel discussion by Senators Tom Daschle (Democrat, South Dakota) and Bob Bennett (Republican, Utah), who is currently a senior fellow at the Bipartisan Policy Institute.Dr.Mostashari articulated the key principles that will continue to guide the Office of the National Coordinator (ONC), as well as the ONC’s “theory of change.”

ONC Principles

  • Innovation will be driven by private industry & free market
  • But recognize that problems with health care market require at least some amount of government action.  “Do the minimum amount of government action necessary, but no less.”  Government action is required to deal with the following key issues with the market:
    • Assure Market Competitiveness, particularly due to high switching costs for HIT by health care providers and due to information asymmetry, where providers have difficulty understanding technology and complex service level agreements.
    • Deal with Externalities, since the benefits of HIT investments do not all accrue to the providers
    • Deal with Public Goods, such as health IT standards

ONC Theory of Change

  • Constant attention to the goal: “Keep your eye on the prize.”
  • Pragmatism and practicality: “Keep our feet on the ground.”
  • Flexibility, particularly long rangeplans
  • Patient centeredness – always ask

I noted that Dr. Mostashari seemed to be referencing the long-acknowledged problems with the market for health care services, and then applied that to the market for HIT, where doctoral level providers are apparently at a disadvantage in buying HIT. Although I agree that HIT purchases are complex and that health care providers have historically performed poorly in making informed decisions about HIT investments, I think that this can be better resolved through making the health care delivery market itself more competitive, forcing health care providers to become more sophisticated purchasers (and more meaningful users!) of HIT, rather than having government fix that particular problem.

Other noteworthy points made by Dr. Mostashari include:

  • 65% of vendors that have HIT products that earned ONC certification have fewer than 50 employees.
  • Use of EMR was stuck at around 20% for years, and recently jumped to 30%.
  • Feds set goal for 20% reduction in readmits.
  • Another goal is to have the patient’s information follow the patient wherever they go.
  • He distinguished between the issues of interoperability of systems within a health care provider vs. interoperability of like systems between health care providers.
  • He said clinician adoption is a large problem, but interoperability is a larger problem.
  • Discussed the Direct project, in which the feds stated the provider-to-provider and provider-to-patient secure communication problem and convened diverse stakeholders to participate, creating a “do-ocracy”.  Within 90 days, they agreed upon secure e-mail as the primary method.  In another 90 days, they had developed simple common protocols.  Then, in another 90 days, most of the big HIT vendors have agreed to support those protocols.
  • Discussed goal of creating a “learning health care system” and the associated need for secondary use of data to evaluate treatment effectiveness and to serve public health, quality measurement.  These uses are not disruptive to privacy and confidentiality concerns.
  • Explained that, as technology improves, the concept of “what is de-identified” gets more difficult.
  • He envisions the need for “distributed queries” where the question goes to the data.  (I am doubtful of this concept, based on experience proving the need for sustained effort to clean and transform data to make it useful for valid analysis.)
  • Explained the challenge of rural health care, including lack of broadband internet access.  The Regional Extension Centers have an explicit mandate to address rural health care issues.

Some key points made by Senator Bennett:

  • Bennett describes the “nirvana” of HIT in terms of accessibility of health information, but he describes the intended outcome as increased quality and lower cost, asserting that if quality is not increasing and costs are not being reduced, then HIT is a waste of time.  He does not acknowledge that quality and cost are process transformation issues (not data access) and that there are many necessary ingredients to process transformation besides HIT.
  • Bennett argued for the importance of security and privacy protections by describing the risk to patients to having diseases identified and electronically documented in terms of future loss of insurance coverage.
  • Bennett told the story of the use of clinical data for analysis at Intermountain to identify the need for administering prophylactic antibiotics within one hour of an operation, but explained the externality problem: that Intermountain lost millions of dollars in revenue that was previously associated with inpatient treatment of iatrogenic infections.

Some key points made by Senator Daschle:

  • Daschle said that lack of “interoperability” is the nemesis of HIT success.
  • Daschle said that patient engagement starts with individuals taking responsibility for themselves, and at least partial responsibility for the cost of their own care.
  • Daschle says new health care marketplace will create more choices for people, and they have a responsibility to make informed choices.
  • Daschle and Bennett both advocated for individual mandate, and to begin to break the link between health insurance and employment.

Funding for Registries and Analytics?

The American College of Cardiology CEO asked for $500M federal funding for cardiology registries.  Daschle said it is logical to do so, and that we are creating a new environment for that to happen.  But then he said it starts with HIT, avoiding directly addressing the issue of plans for federal funding for registries and associated analytics.  Bennett said he also supports such funding, and joked that he is no longer in the Senate because he is a Republican that believes that not all government spending is evil.


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Why many clinical leaders prefer Registries to EHRs: Actively Structured Information

I went to the huge HIMSS’11 convention in Las Vegas a few weeks ago.  When visiting the bewildering number of vendor booths, I focused on a few key questions relevant to the challenges facing physicians and hospitals working to establish successful Accountable Care Organizations (ACOs):

1) What is the current state of clinical data exchange between Electronic Health Record (EHR) systems primarily used for acute hospital care vs. ambulatory care?

2) Do leading EHR systems have useful “registry” capabilities?

Nuance Booth at HIMSS


I have been hearing from many clinical leaders that the most popular EHR systems still do not support real clinical integration across settings, and are still weak in terms of the “population management” and clinical process improvement features that are present in existing chronic disease registry applications.  I was hoping to learn that these concerns were really based on a lack on familiarity with how to configure and use EHR systems, rather than any inadequacies of the systems themselves.  After all, clinical message and clinical document standards have been around for years, and population management features were prominently identified in recent Meaningful Use incentives.

The verdict?

Some progress has been made in leading EHR systems, but clinical integration across settings and population management are still major weaknesses.

But why?

It turns out that both problems are related to the same underlying issue: failure to appreciate the importance of “actively structured” information.

Health Information Technology (HIT) leaders have for decades focused primarily on a vision of computerizing health information, going paperless, and improving the access to that information by many members of the clinical team across settings.  To reduce the burden of capturing information that can be displayed on a computer screen, HIT vendors have developed document imaging, optical character recognition, and voice recognition technology.  And, they have created clinical documentation systems that allow the user to enter simple codes to insert blocks of text into their notes quickly.  Over the last 15 years, most HIT leaders have recognized that there is some value in “structured data” — health information in the form of codes that computers can interpret rather than just display.  In response to this recognition, EHR vendors have added “template charting” features that allow users to do exception editing of some coded values in notes.  They have developed sophisticated systems to interpret the meaning of textual information and convert that text into structured data.  And, they have created messaging standards that allow orders, clinical documents (notes) and continuity of care information to be shared across systems and care providers.

But, the problem that remains is that the structured data that is being captured and exchanged is “passively structured.”  Although the current crop of EHR systems may allow some of the health information to be represented with codes, the EHR tools and the care process itself do not assure the capture and transmission of particular pieces of information required to support particular down-stream uses of the data, such as reminders, alerts, quality and performance metrics, and comparative effectiveness studies.  The clinical leaders that are focused on improving care processes, and the health services researchers that are trying to measure performance and comparative effectiveness are well aware that missing data is crippling to the usefulness of passively structured data.  The real care process improvement and performance and effectiveness measurement efforts of Accountable Care Organizations requires “actively structured” health information.   To assure the completeness of the information, they use “registry” applications, questionnaires, and data collection forms.   And, they transmit this information in formats that rigorously enforce the meaning and completeness of the structured information.  The objective is not to capture as much structured data as possible.  The objective is to assure the accuracy and completeness of particular data elements that you are relying on for specific, strategically important purposes.

I believe that HIT professionals may be reluctant to make actively structured information a requirement because (1) they lack expertise and familiarity with the downstream uses of the data for care process improvement and measurement, and (2) they are concerned that the added burden of actively structured data capture on end-user clinicians may further worsen their problems with “clinical adoption” of their technology.   They are attracted to solutions that extract passively structured information from clinical notes, such as voice-recognition and “clinical language understanding” (CLU).  And they don’t realize that the big pile of passively structured data output by such solutions will fail to meet the requirements of Accountable Care Organizations.

To solve the problem, two main things are necessary:

  1. Refocus the design objectives of EHR products on the strategic goals of Accountable Care, rather than on the tactical goals of reducing medical records cost, “going paperless” or reducing security risks.  The biggest implication of this will be the integration of analytic and care process management functionality into EHRs, rather than viewing those as separate solutions to different problems.
  2. Create stronger organizational linkages between HIT professionals, the clinical leaders involved in care process improvement and the epidemiologists and biostatisticians that have the expertise to measure provider performance and treatment effectiveness.  Many hospitals, physician organizations and nascent ACOs are attempting to do this by hiring “chief medical informatics officers” (CMIOs).  But that will only solve this problem if the new CMIOs can bridge between HIT, process improvement and measurement disciplines.  If the CMIO role is viewed more narrowly as a liason between HIT professionals and front line clinician users, the focus will continue to be on unstructured or passively structured data to reduce barriers to HIT adoption.


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Video of ACO Breakfast at HIMSS’11 Meeting

The following is the link to a hand-held video from the “ACO Breakfast” event on February 21, 2011 at the annual Health Information Management Systems Society convention in Orlando.

The panel discussion was kicked off by Eric Dishman, Director of Health Innovation for Intel, and featured:

  • Aneesh Chopra, the Chief Technology Officer of the US Government, who explained the government’s approach to creating an “innovation management pipeline” using an Innovation Center, emphasizing interoperability to create opportunities for private innovators to create “apps” that connect to a common platform, and using Medicare and Medicaid as early adopters.  His approach sounded very much like a description of an “open source” software ecosystem, although he did not use that terminology in the proprietary vendor-dominated crowd.
  • John Mattison, MD, Chief Medical Informatics Officer for Kaiser Permanente.  I worked with John years ago when I was at Oceania and he was the Kaiser Permanente Southern California lead for KP’s EMR efforts at the time.  John emphasized the importance of working with primary care physicians, and proposed that the shortage of primary care physicians will be offset by the reduced need for specialists.  Presumably, he is theorizing that medical sub-specialists will morph their practices to emphasize primary care and deemphasize  procedures.
  • Steven Waldren, MD, Director of the Center for Health IT for the American Academy of Family Practice.  I worked with Steve when I was at Blue Cross Blue Shield of Michigan to adapt the Continuity of Care Record (CCR) standard for use in care management and health plan member health record.  Steven emphasized the challenge of scaling EMR technology down to small independent primary care practices that lack IT infrastructure, and described clinicians disappointment with the inability of commercial EMR software to do chronic disease registry functions.
  • Michael Young, CEO of Grady Memorial Hospital.  Michael used the example of Kodak’s lack of success in transitioning from a profitable film-based photography business to the “next curve” of digital photography, despite having pioneered digital photography technology.  He used this example to explain the challenge facing health care leaders in moving from the current profitable fee-for-service volume-driven model to the next curve of performance and outcomes-based reimbursement.  He expressed some optimism by noting that the timeline for developing useful health car “apps” has decreased from 5 years to 5 days.
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Learning from Manufacturers about Culture and Technology: The Case of PLM Systems

Product Lifecycle Management (PLM) systems are software tools that are used by product manufacturing companies to support the entire lifecycle of ideation, business planning, requirements, design, manufacturing, launch, and eventual retirement of products.

They are interesting to me for two reasons: (1) they are relevant to the development of software products, and (2) they share some important characteristics with health care information technology.   PLM systems, like electronic medical records (EMR), order entry, registries, care management and analytic systems used by Accountable Care Organizations (ACOs), are systems that are mission-critical to the company.  They involve complex information.  This complex information is created and maintained by business users with some technical capabilities.  This complex information must be communicated in ways that support collaboration by many different people from different professional disciplines.  They support processes that are constantly being changed and improved in ways that can create competitive advantage for the organization.   They support design and analysis, rather than just execution.

So, what can we learn from product companies and the systems that they use that can be applied to Accountable Care Organizations?

I just read a report from the Aberdeen Group on the “CIO’s role in Product Lifecycle Management (PLM) System.”

The report starts by acknowledging the tendency for CIOs to view PLM system implementations initiated by product people to be “rogue” projects.  The report explores whether such system implementations should be in the “realm” of IT, rather the product people.

This article seems to be written from the perspective of the CIO.  It concludes that to be “best in class”, a company needs to:

  • Have the PLM implementation project “under IT,” rather than have it under product area leaders who have “a day job,” asserting that, if the PLM system is supported by the product area, there will be a risk to “business continuity”.
  • Have the PLM implementation project funded through the IT budget, including funding for some dedicated staff in the IT area, but justified based on a business case tied to a business initiative of the product area.  In other words, the product people are responsible for helping argue the case to the C-suite for increasing the IT budget.
  • Minimize customization to the PLM software, even if the product people argue that customization is required to maintain some aspect of the product lifecycle process that they consider to be a competitive advantage.

At the end of the article, the authors acknowledge that less than 50% of recent PLM implementations are taking this advice and formally assigning CIO responsibility for PLM system implementations.  The companies that do so tend to be large companies that “focus on standardization.”

Of course, none of these turf issues matter if the people and departments involved are fundamentally collaborative and agile and if the right talents are represented in the collaborators.  I theorize that the problem has, as its root cause, the culture of blame that sometimes develops in large organizations.  In such organizations, IT leaders routinely experience blame when IT-related things inevitably go wrong, even in situations where the problem is  largely out of the control of the IT leaders. After receiving routine beatings over a long period of time, IT leaders and IT department culture can take on a defensive posture.  This defensiveness, in turn, does three things:

  1. It crowds out collaborativeness
  2. It fosters hiring and promotion processes that emphasizes management skills (“are you done yet?”) over design insight and creativity
  3. It encourages processes to be optimized for documentation and blame avoidance rather than agility

Then, after years of experiencing IT support that, in the opinion of product leaders,  lacks design insight, creativity and agility, the product leaders insist on keeping the PLM systems under their own control.  CIOs consider this to be “rogue” behavior that needs to be thwarted.  As a result, a reinforcing loop (a vicious cycle) is created.

This general system of causes and effects seems to apply as well to other technologies that are used for mission-critical processes by non-IT people with some technical capabilities, including workflow automation, business process management (BPM), enterprise data warehouse (EDW), and electronic medical records (EMR).  Specifically in the latter case, clinical leaders that are focused on using IT to transform their actual care processes sometimes tend to associate “EMR” with “big expensive project owned by IT people that don’t understand my clinic.”  As a result, they prefer “registries,” which connotes “little project owned by the clinicians and focused on enabling the front-line process improvements we’re trying to make right now.”

The Aberdeen Group report attempts to address some practical issues regarding budgets and organizational roles.   It does a nice job of linking survey data to recommendations.  But, in my opinion, the solution to this problem — whether it be for PLM systems in product companies or care process management systems in ACOs — is not to decide who owns the turf.  It is to address the root causes.  IT and product/clinical leaders must work together in ways that avoid finger-pointing, builds trust, attracts and retains the best talent, and invites meaningful participation by all the team members with something to contribute and a stake in the outcome.  And the information systems must be designed to enable such collaboration.  Admittedly, easier said than done.

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Improving Adult Flu Immunization


The US Preventive Services Task Force established national evidence-based guidelines for adult immunization as part of their 1993 and 1996 review processes. After a review by Henry Ford Health System (HFHS) general internists, family practitioners, and infectious disease specialists, these guidelines were endorsed by the HFHS Prevention Committee. The Prevention Committee’s recommendations were subsequently accepted by the Henry Ford Medical Group Clinical Practice Committee and by the Health Alliance Plan Quality Management Committee to form practice guidelines for the medical group and health plan, respectively.


A multi-faceted implementation approach was used to improve immunization performance within the Henry Ford Medical Group, one of the provider groups that serve the Health Alliance Plan. Multi-faceted implementation efforts have been found to be most effective for improvement processes that involve behavior change. The implementation effort involved staff training, patient and member education, continual quality improvement, and medical informatics facets.

  • Staff Training.  All senior medical staff within the Henry Ford Medical Group were sent a copy of internal adult immunization guidelines, which were incorporated into a larger preventive health services manual. In addition to this mailing, a number of clinicians had the opportunity to discuss these guidelines in an on-site continuing medical education program on the provision of preventive health services.
  • Patient education was accomplished by publishing an article in the Health Alliance Plan’s member newsletter, which is mailed to all health plan members. A slogan and cartoon character were also developed for a program to promote immunization compliance. This content was incorporated into posters and tent cards, which were placed in clinics lobbies and waiting areas.
  • Local continuous quality-improvement teams were established to develop and implement process changes. These teams launched Saturday morning walk-in flu immunization clinics during flu season. By using this approach to immunization, wait times were reduces and patients were able to avoid setting up an appointment to get the immunization.
  • Medical informatics approaches were pursued, leveraging the capabilities of the clinical information system and data depositories that are available within the insitution. Computer-generated reports were created, listing immunization status for HFHS adult patients. These reports were used by staff of the Saturday morning walk-in flu clinics. In addition, computer-generated reminder postcards and letters to patients at high risk for influenza were printed and mailed.


These mailings were formally evaluated in a randomized trial conducted during the first year of the HFHS flu immunization program. The entire patient population for whom flu immunizations were indicated were randomized into four groups. The control group (usual care) received only the posters and tent cards in the clinic. Patients in each of three treatment groups received this same clinic-based intervention and either (1) a generic postcard, (2) a tailored postcard, or (3) a tailored letter containing an explicit statement of why flu immunization was indicated for them. Indications included age over 65 and the presence of one of a number of disease states, as ascertained from diagnosis coding of ambulatory visits and inpatient admissions. These letters or postcards were addressed from the patients’ primary care clinicians. The results of randomized trial showed a 5 percentage point increase in the rates of immunization in the patient population receiving the tailored letter compared to those receiving usual care.

The cost of the letter, including printing and postage, was 42 cents. The vaccine costs just over $4.00. From the literature, it is known that annual hospital costs are reduced from an average of $355 to $215 as a result of flu immunization. Therefore, during a non-epidemic year, the flu immunization program was calculated to save the HFHS over $180,000, net of the cost of the intervention. During an epidemic year, this savings is increased to almost $400,000. Therefore, the flu immunization project serves as an example of a clinical-practice improvement effort that simultaneously benefits the health status of patients and reduces health care cost.

The National Committee for Quality Assurance (NCQA) adopted in 1996 a new adult immunization performance measure which is included in the Health Plan and Employer Data and Information Set (HEDIS 3.0). These quality indicators have been reported by hundreds of health plans across the country, and are compiled in the NCQA Quality Compass, a national health plan quality database.

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