Porter on Value in Health Care II

In his most recent NEJM article on value in health care (2010), Michael Porter expands the definition and measurement of this complex and elusive construct.  He considers value as health outcomes relative to costs, or efficiency.  Although he comments on outcomes as condition-specific and multidimensional, he does not adequately define effectiveness of delivered care. As is the case throughout the U.S. health care system,  the model of value is an attempt to associate cycles of health care and the “outcome measures hierarchy” with an estimate of dollar cost  for individual patients.  Certainly time  is a critical dimension in evaluation of health care value, but scaling this dimension to condition-specific cycles of individual care is itself a costly operation in measuring value.  Furthermore, this approach ignores individuals of the  population in sustainable good health due to effective preventive health care strategies or other social welfare policies. The individual patient should not be considered in isolation from the relevant population.  Rather data on patient outcomes related to value should be aggregated to reflect not only cycles of care for particular conditions of disease or ill-health, but also the presence of sustainable good health.

Porter advocates a market-based vision of health care and deplores the lack of competition among providers based on actual results, but appears very careful to recognize the threat posed by public access to data describing such provider performance. Instead of patient choice of provider based on performance data,  he emphasizes evidence based provider innovation and improvement through analysis of their own performance.    Health care services markets in the U.S. are substantially weakened by the lack of patient access to provider performance data as well as a professional culture highly protective of provider privacy with respect to such data.  Evidence based patient choice in health care services markets would significantly enhance value provided.

Health information systems for such data in the U.S. are primarily designed to support billing processes in the pervasive fee-for-service business model. This is the underlying motivation for ever more detailed and multidimensional data collection on the care of individual patients. Relentless focus on the individual renders more difficult the measurement of teamwork contributions to patient care. Thus one of the most important value-creating organizational reforms tends to be obscured in the complexity of rigorous attribution of shared clinical services and reponsibilities to individual care. It should also be emphasized that the use of billing codes for compilation of clinical conditions and treatments results in an unresolved bias in the quality of such data.

Porter's “value equation” does not consider the administrative component of the care cycle,apparently under the assumption that these costs remain invariant across medical conditions. Institutional arrangements designed to improve delivery of value in health care include Federally Qualified Health Centers (FQHCs), Rural Health Clinics (RHCs), Accountable Care Organizations (ACOs), and Patient Centered Medical Homes (PCMHs). They require varying administrative arrangements to incentivize and transact payment schemes for improvement of service quality to specific populations. These arrangements may increase the administrative component of health care costs as well as the complexity of the integrated system. Although difficult to estimate, such costs must be taken into account in the “value equation,” especially in the U.S. health care context.

I mentioned in an earlier commentary on Porter's value framework that the exclusive focus on financial dimensions of care obscures the more elusive ideological, cultural and ethical assumptions underlying the U.S. health care system. In particular, the value framework assumes that individual patients have a sustainable relationship with their care providers, which is obviously not the case. Even if it were feasible to calculate value in the “equation” suggested by Porter, the model would not be applicable in a context where there is such a high rate of patient mobility among providers as well as in and out of various insurance arrangements over relatively short time horizons. The relationship between the patient and his or her providers is probably the most important dimension of value in health care – encompassing values of access, trust, sustainability and continuity. The U.S. corporate health insurance business has designed this relationship out of the system – and thus destroyed the very foundation of health care value-creation.

References

[1] Bohmer RMJ, Lee TH. The Shifting Mission of Health Care Delivery Organizations. N.Engl.J.Med. 2009 August 6;361(6):551-553.

[2] Lee TH. Putting the Value Framework to Work. N.Engl.J.Med. 2010 12/23;363(26):2481-2483.

[3] Porter M. What is Strategy? Harvard Business Review 1996 November/December;74(6):61-78.

[4] Porter ME. A Strategy for Health Care Reform -- Toward a Value-Based System. N.Engl.J.Med. 2009 July 9;361(2):109-112.

[5] Porter ME. What Is Value in Health Care? N.Engl.J.Med. 2010;363(26):2477-2481.

[6] Porter ME, Teisberg EO. How Physicians Can Change the Future of Health Care. JAMA 2007 March 14;297(10):1103-1111.

Virtual Health Care Infrastructures: Mapping Large Systems

Qualitative case research methods offer a flexible approach to the understanding of large and complex health service delivery systems embedded within their extended social context. Taken as the relevant unit of analysis, the Indian national health care system is a complex inter-organizational network valuable to the process of scientific study as a critical case, particularly for analysis of the co-evolution and integration of networks under a diverse ideologies. Despite recognition of the importance of systems science in medical informatics, little research has focused on studies of health care at the national system level, in part because of the size and complexity of such systems and the lack of interdisciplinary consensus regarding appropriate methodologies and theoretical foundations for this important field of study. Some authors suggest that there is a pragmatist epistemic argument for use of qualitative and mixed research methodologies in the field of medical informatics as clinical practice is a hybrid sociotechnical field. This view rejects belief in a single “scientific method” and recognizes that research is always situated in a particular context.

This research contributes to development of a methodology and conceptual framework for comparative analysis of the virtual infrastructures of national health care systems. Health care is defined as the preservation of mental and physical health by prevention or treatment of illness through services offered by the health professions. A health care system is a dynamic set of interconnected individuals, institutions, organizations, and projects offering products and services in health care markets. The functions of the health system include all categories of service delivery, resource generation and allocation, and governance. Governance includes both policy making and regulation of the system. Service delivery encompasses information, research, and education services as well as public health and delivery of patient care, both preventative and curative. These functions, as well as their interrelations, are critically important to the performance of an integrated health care system and the quality of health care services.


Data are drawn from published accounts of system development and the websites of the constituent organizations, networks and services to describe the configuration of virtual infrastructures. The context of the case analysis is developed using historical data to show how the current system has unfolded over time. E-mapping software is used to visualize the linkages among institutions and resources identified in the case analysis. Electronic linkages among institutions and services are considered in the analysis as well as linkages integrating national health care systems with international institutions. Using this specialized software, an online database includes a dynamic electronic representation of virtual infrastructures identified in the research program. Visualization of data reveals how information resources are linked and integrated in development of the virtual infrastructure. These data describe configurations of web-based services revealing patterns associated with electronic markets and hierarchies.


1. India







2. Bireme:  The Latin American Region

Meaningful Use Rap

Have a look at this!

The U.S. Health Care System Infrastructure for Health Information Exchange (HIE)

Here is the abstract of a presentation on HIE infrastructure in the US:

Abstract
Health information technology and infrastructures for increasingly web-based services will drive the future development of national health care systems. However, implementation of HIT without attention to institutional infrastructure will only amplify the uncontrollable surge in health care expenditures. The objective of this talk is to consider published evidence and develop a conceptual framework for design of a national health information infrastructure integrating public and private enterprise in the health sector. A comparative analysis of the National Information Exchange Model (NIEM) and the Nationwide Health Information Network (NHIN) concludes that the NIEM would be more effective in reducing barriers to health information exchange.

Recent studies of national health care systems in the industrialized world demonstrate that health care service delivery in the U.S. performs poorly in light of the level of per capita expenditure in the sector. The U.S. lags significantly behind other developed countries in public investments for HIT; as of 2005 the U.K. had spent $192.79 per capita compared to a U.S. investment of $.43. One reason for this is policy failure in development of sustainable business models based on private investment for health information exchange (HIE).

In the U.S. multiple payer system, competing health care providers and insurance companies focus on automation of financial transactions and implementation of redundant proprietary HIS. Their incentives for new technology adoption do not take into account system level efficiencies often external to private HIS purchasers in the health care sector. While policy emphasis on electronic health records (EHR) focuses on internal efficiencies and improved health care quality, these investments require public infrastructures for effective health information exchange at the system level.
The nationwide health information network (NHIN) refers to a proposed system linking data intermediaries for health information exchange. Related policies rely primarily on the principle of regional health information organizations (RHIOs) that can collaborate and exchange data. An assumption fundamental to this model is incremental development by linkage of state designated entities (SDEs) and regional health information organizations (RHIOs). However, research on the performance of RHIOs shows a high failure rate among these organizations and offers no significant evidence to substantiate interoperability among their systems. No sustainable RHIO business model has been identified to integrate public and private stakeholders. Further complicating the design of health information exchange are policies promoting medical homes and accountable care organizations (ACOs) competing for government incentives. These organizations often lack motivation to exchange health information.

More promising than the NHIN configured among fragmented local and regional RHIOs is the National Information Exchange Model (NIEM). Even though this development of the NIEM has suffered some of the same difficulties as HIE in defining an effective and sustainable business model, it has benefited from more consistent and longer term public funding.While the NHIN is designed as a many to many mapping of communication among participating entities, the NIEM proposes a canonical mapping through the common infrastructures of the model shared among communities of interest. Such a national – and eventually global - infrastructure offers services as well as a system of governance to assure economies of scale and scope in information exchange across enterprise domains served. Extension of the NIEM to the U.S. health care system would offer much needed cost reduction advantages and help reduce barriers to health information exchange among competing organizations.

Conclusions and Recommendations:
1. Public investment in health information infrastructures and the NIEM - a single infrastructure does not necessarily imply a single payer design.
2. Design of public health information infrastructure as a public good required to promote interoperability for both public and private services offered in the U.S. health care sector.
3. Collaboration across the Americas integrating the Canadian Infoway and BIREME – the Latin American Regional Library of Medicine will serve as a foundation for large scale grid and cloud infrastructures to support research and innovation.

Stage 2 Meaningful Use Objectives

The following text is a commentary on stage 2 meaningful use objectives, criteria and measures - mainly from the perspectives of social and organizational sciences - in response to the call for public comment issued by the HIT Policy Committee. My previous commentaries on MU, Regional Health Information Organizations (and update) and Extension Centers also remain pertinent to the discussion context.

Commentary on the MU stage 2 matrix (with page references to the call for public comment):
On page 6, MU objectives refer to "unique patients" for recording vital signs and smoking status. This criterion raises a question concerning the definition of "unique patient". (It is somewhat ironic that in the US system that purports to focus on empowering the individual patient and his or her needs/choices, a unique patient identifier seems to be out of the question.) On December 9, 2010, a Patient Linking Hearing hosted by the ONC Health Information Technology Policy Committee heard testimony on idividual patient identification. Paul Oates of Cigna pointed out that in the US patient ID (and that of his/her family) is generally tied to an employer. When patients lose their jobs or move from one employment to another, their identification may be compromised. Oates further clarifies:

"The historical purpose of keeping person data was to derive eligibility for benefits and pay claims, not primarily to improve care or service an individual. So, the primary data attributes linked to a person largely revolved around tying a person to their dates of eligibility, their plan type and features."(Page 1-See oates-patient-linking-hearing-tigerteam.pdf)

This testimony suggests the tenuous relationship between clinical and claims information resulting in a dual view of patient/consumer identity. Problems in linking patient ID to relevant data further hamper the integrity of research efforts in medicine and public health. Some of these difficulties and possible solutions were suggested at the hearing by Assistant Professor Bradley Malin of the Department of Biomedical Informatics, School of Medicine, Vanderbilt University.

(The logical conclusion to this discussion would be a call for a unique biometric patient identifier, similar to that being implemented in India.)
On page 7 formulary checks are prescribed for MU, but accomplishment of this objective depends on the collaboration of multiple health plans which may or may not offer the necessary electronic support. Care must be taken to assure that this provision does not result in an excessive administrative burden to meaningful users of EHRs and health information technology.
Also on page 7, where it is stipulated that lab results should be entered into EHRs as structured data, it may be important to distinguish between test results and their interpretation. For example, where digital images are not included in the EHR, lab results constitute interpretation rather than original data. The lack of available raw data may contribute to requirements for unnecessary repetition of clinical tests in some clinical decision processes.
On page 10, the new requirement that secure online patient messaging be in use depends on the existence of supporting infrastructures and health information exchange. Individual EHR users cannot be responsible for the availability of such infrastructures. Also on page 10, the requirement that patient preferences for communication medium be recorded is not really useful under real operational contingencies. Availability of media depends on the context and may change as a patient moves from one facility or geographical area to another. Communication also frequently requires a dynamic suite of synchronous as well as asynchronous media.
Electronic self management tools (page 10) require content beyond the functions of the EHR. Patients choose such tools depending on their health care culture and provider affiliations as well as their ability to invest time and other resources in self management. The patient has access to his or her health information, but content other than that within the patient-specific EHR should not be included in criteria for MU.
For care coordination it is suggested in stage 2 (page 11) that the meaningful user connect to at least three external providers in "primary referral network" (but outside delivery system that uses the same EHR) or establish an ongoing bidirectional connection to at least one health information exchange. As I have frequently mentioned in other commentaries, requirements for health information exchange imposed on meaningful users assume the existance of effective telecommunications infrastructures and institutions such as RHIOs. Such assumptions are invalid. While policies to promote RHIOs, state health information exchanges and the Nationwide Health Information Network (NHIN) are in place, they are so far not sustainable, and public investments remain inadequate.
Submission of data including clinical and patient generated information to public health agencies (pages12-13) also depends on the availability of telecommunications infrastructures for such health information exchange. There are not necessarily any preparatory steps to be taken by health care practitioners for these stage 3 objectives. Public initiatives and investment are required rather than individual EHR user steps in stage 2 of MU. Privacy and security protections also depend significantly on design of infrastructures for health information exchange.
Section D-questions 3, 5, 6, 9, and 10 (pages 14-15):Question 3: What strategies should be used to ensure that barriers to patient access – whether secondary to limited internet access, low health literacy and/or disability – are appropriately addressed? Strategies to promote patient access to their EHRs and other electronic health information are outside the criteria for MU. However, I would like to suggest the possible usefulness of mentoring among patients and patient support groups focused on competencies necessary for access to and meaningful use of electronic health information. These programs could be offered by public or private entities, including health plans, health care providers, and patient advocacy groups. Physical access to the Internet might further be facilitated through the use of self-service kiosks designed to guide patients lacking experience in the use of electronic information and the Internet. Such kiosks could be set up in medical centers, hospitals, clinics and offices of physicians as well as other health care service providers.

Question 5: For future stages of meaningful use assessment, should CMS provide an alternative way to achieve meaningful use based on demonstration of high performance on clinical quality measures? This would be an important strategy to recognize that there may be many paths to high performance in clinical quality - with or without meaningful use of EHRs. Measurement of clinical quality is also more accessible than assessment of complex and dynamic processes of meaningful use. This strategy would focus users' motivation on the quality objective rather than the means to its achievement - and open the door to incentivize innovative methods other than meaningful use.
Question 6 : Should Stage 2 allow for a group reporting option to allow group practices to demonstrate meaningful use at the group level for all EPs in that group? The answer to this question depends on the organizational and infrastructural health care context. Groups might be defined as medical homes or accountable care organizations. Some EPs may perform part of their practice within such organizational structures. How might such participation be taken into account? Physicians and other health care professionals have multi-affiliated practices and they may also be highly mobile, moving from one US region to another - or even outside the country. It is difficult to imagine how the MU objectives, criteria and measures can take this dynamic context into account.

Question 9: What additional meaningful-use criteria could be applied to stimulate robust information exchange? As mentioned above with reference to page 11 of the MU matrix, requirements for health information exchange imposed on meaningful users assume the existence of effective telecommunications infrastructures and institutions such as RHIOs. Such assumptions are invalid. While policies to promote RHIOs, state health information exchanges and the Nationwide Health Information Network (NHIN) are in place, they are so far not sustainable, and public investments remain inadequate. EHR users cannot participate in electronic HIE without these infrastructures.

Question 10: There are some new objectives being considered for stage 3 where there is no precursor objective being proposed for stage 2 in the current matrix. We invite suggestions on appropriate stage 2 objectives that would be meaningful stepping-stone criteria for the new stage 3 objectives. The achievement of MU is not a linear process due to its complexity as well as the high rates of technological change and innovation. It may not be necessary to define stage 2 "stepping stones" towards achievement of stage 3 objectives.

The evidence base (Section E, page 15):
The list of studies presented to justify formulation of new MU objectives illustrates the difficulty in the linear (and static) definition of meaningful use. These studies represent single data points in the literature review and meta-analysis required for the propositions guiding meaningful use - under the assumption that these research results will continue to be relevant irregardless of fast moving processes of health care system reform and technological innovation. Meaningful use will also be affected by institutional evolution in the formation of regional (RHIOs) and state organizations for health information exchange as well as accountable care organizations (ACOs) and medical homes. There is little or no research evidence (or other policy information) to substantiate any scenario describing the development of these institutions - while they lie at the foundation of meaningful use.

Concluding thoughts and references:Much progress has been made in development of national policies for implementation of health information technology in the US. [1] However, as I have mentioned in earlier commentaries, rapid change and innovation[2,3,4] may result in new policy models - invalidating or competing with the current policy model of MU. The significant risk of a technological paradigm shift may compromise the credibility of MU policies as well as user motivation to accomplish early stage 1 and 2 steps to satisfy MU criteria at stage 3 - after 2015. Unfortunately, even though Blumenthal[5] describes the adoption of EHRs in the US as “inevitable,” recent research on effectiveness of EHRs (as well as ehealth more generally) has shown inconclusive results regarding both improved quality of care and cost effectiveness. [6-8] These studies suffer from a paucity of theoretical frameworks[9] as well as many methodological weaknesses. The absence of an evidence base substantiating the benefits of EHR implementation tends to discredit current policy discourse and undermine efforts to incentivize EHR adoption and meaningful use in the US. It would be useful in this regard to broaden focus on EHR context to include social networks and global telecommunications, and to consider the benefits of enhanced international collaboration for health care service delivery as well as for research in medicine and the health sciences. [10]

[1] Buntin MB, Jain SH, Blumenthal D. Health Information Technology: Laying The Infrastructure For National Health Reform. Health Affairs 2010 June 01;29(6):1214-1219.
[2] Sittig DF, Singh H. A new sociotechnical model for studying health information technology in complex adaptive healthcare systems. Quality and Safety in Health Care 2010 October 01;19(Suppl 3):i68-i74.
[3] Golembiewski RT, Billingsley K, Yeager S. Measuring Change and Persistence in Human Affairs: Types of Change Generated by OD Designs. The Journal of Applied Behavioral Science 1976 April 01;12(2):133-157.
[4] Millsap R, Hartog S. Alpha, Beta, and Gamma Change in Evaluation Research: A Structural Equation Approach. Journal of Applied Psychology 1988;73(3):574-585.
[5] Blumenthal D, Tavenner M. The “Meaningful Use” Regulation for Electronic Health Records. N.Engl.J.Med. 2010 08/05;363(6):501-504.
[6] Romano MJ, Stafford RS. Electronic Health Records and Clinical Decision Support Systems: Impact on National Ambulatory Care Quality. Arch.Intern.Med. 2011 January 24.
[7] Black A, Car J, Pagliari C, et al. The Impact of EHealth on the Quality and Safety of Health Care: A Systematic Overview. PLoS Medicine 2011;8(1):e1000387.
[8] Jones S, Adams J, Schneider E, et al. Electronic Health Record Adoption and Quality Improvement in US Hospitals. American Journal of Managed Care 2010;16(12).
[9] Pingree S, Hawkins R, Baker T, DuBenske L, Roberts LJ, Gustafson DH. The Value of Theory for Enhancing and Understanding e-Health Interventions. Am.J.Prev.Med. 2010 1;38(1):103-109.
[10] Shachak A, Jadad AR. Electronic Health Records in the Age of Social Networks and Global Telecommunications. JAMA: The Journal of the American Medical Association 2010 February 03;303(5):452-453.

Addendum: Other significant issues raised in response to the call for public comment:Issues raised concerning MU objectives, critera and measures include (1) the integration of digital imaging in EHRs and (2) consistency of public policies to promote eprescribing. These are mentioned below:

In a recent policy document, the Medical Imaging and Technology Alliance (MITA) deplores the absence of MU criteria regarding formats and electronic transmission of medical imaging. The criteria so far only address data that may be entered into the record by descriptive text or numerical data - while software certification and meaningful use of EHRs will not take medical imaging into consideration until after 2015. MITA points out the need for EHR standards to support sharing digital images generated by equipment made by different manufacturers. The Digital Imaging and Communications in Medicine (DICOM) Standard was developed by the American College of Radiology (ACR) and the National Electrical Manufacturers Association (NEMA). The current standard, DICOM 3.0 is nearly universally accepted to enable data exchange among DICOM compliant systems, either on CDs or through available transfer functions. An industry and professional initiative, Integrating the Healthcare Enterprise (IHE), further promotes adoption of EHRs by facilitating service coordination and data exchange among health care information systems. IHE tests more than 100 systems for compliance every year. These efforts supporting DICOM and health information exchange should be an integral part of the EHR MU scenario.

Another important issue is the lack of coherency between two CMS incentive programs promoting use of electronic prescriptions and EHRs. The GAO has published an analysis of program inconsistencies and their consequences.(See Electronic Prescribing: CMS Should Address Inconsistencies in Its Two Incentive Programs that Encourage Use of Health Information Technology - February 2011 - GAO-11-159)

Regional Extension Centers and HIE

The Software Advice team has written an interesting critique on recently created Regional Extension Centers (RECs) designed to advance adoption of EHRs. You are invited to complete their online survey with special emphasis on reporting anecdotal experience with these organizations. Although it is probably too early to draw substantial conclusions, I agree with Houston Neal that RECs will remain ineffective. My arguments suggest inadequate public funding and institutional arrangements, while his deplore the slow pace of government programs and their interference with free market dynamics.

As Neal points out, the eHealth Initiative has published a disappointing report on RECs to assess progress in their implementation across the US. They have also issued their 2010 report on Health Information Exchange (HIE).

Under the Health Information Technology Research Center (HITRC), RECs were created to provide technical assistance, guidance and information on best practices to support meaningful use of Electronic Health Records (EHRs). The competitively selected RECs - announced in February and April 2010 - serve health care providers within their geographical areas. The Survey of Regional Extension Centers, Planning for Adoption: The Early Direction of Regional Extension Centers (September 2010), presents the following findings (page 3):

• Many Regional Extension Centers remain in the planning stages.
• Progress has been slow in transitioning pre-award letters of commitment
  by providers to signed contracts by PCPs with a Regional Extension
  Center.
• Opinion is evenly divided on progress toward REC objectives being reliant
  upon assistance from the Health Information Technology Research Center.
• Among Regional Extension Centers planning to offer a preferred EHR
  vendor list to PCPs, the most important criteria for selecting a preferred
  EHR vendor are:
  o Price/ total cost of ownership over 3 years
  o Guarantee of meaningful use functionality
  o The number of installations locally
  o Use of an ASP hosted model
• After stimulus funds are removed, a majority of Regional Extension
  Centers will change their fees as a means to sustainability.

The sample for this survey included only 46 of the 60 RECs in operation. The above findings suggest difficulties in defining the relationships among RECs and other health care institutions, as well as the lack of a sustainable business model. It is also not clear how these centers will provide support services across the US. The competitive selection process for RECs considered neither the issue of comprehensive geographical coverage, nor design of the requisite institutional arrangements with RHIOs, the HITRC or SDEs. I pointed out some of these weaknesses in my commentary on the proposed REC design and selection process last year.

The eHealth Initiative has also published a report based on their Seventh Annual Survey of Health Information Exchange - The State of Health Information Exchange in 2010: Connecting the Nation to Achieve Meaningful Use. The survey identified 234 active health information exchange initiatives (HIEs) in the US, among which 199 responded to and qualified for inclusion in the 2010 Annual Survey on Health Information Exchange. It should be noted that 48 of 56 state designated entities (SDEs) have been included in this sample. This shift in the definition of health information organizations needs to be taken into account in the survey findings reported. On page five, a description of the geographical coverage of organizations included in the survey shows that they cannot be considered comparable in size or clientele:

"Most non-SDE initiatives are operating at a multi-county coverage area. Fifty-five
initiatives report covering a multi-county area, while 21 initiatives report covering an
entire state. Other coverage areas include: 17 at a multi-state level, 11 at a county level,
7 at a metro level, 5 that do not cover a geographic area, and 6 initiatives that cover
another area such as part of a city or county, or are working with a specific population
group."

While the 2010 survey claims an increase in the number of operational exchanges, the rate of "mortality" among the sample from 2009-2010 is not considered, nor is the redefinition of "exchange initiatives" (defined as RHIOs in earlier reports) to include state designated entities (SDEs). The interpretation of survey results makes no distinction between state and federal programs for health information exchange.

In 2009, 57 health information exchange initiatives reported being operational. In 2010,
the number of operational health information exchanges increased to 73, 5 of which
report being SDEs. (page 8)

At least 28 of the 2009 respondents who did not respond to the 2010 survey were thought to continue their pursuit of HIE - although there is no data presented to support this assertion. The research methodology does not clearly state the total number of organizations included in the 2009 survey who did not respond in 2010. This number is essential to evaluate the 2010 survey response rate as well as sample mortality. (In my commentary on the 2009 survey, I identified similar problems in the research methodology.)

The significant methodological deficiencies of the surveys conducted by the eHealth Initiative seriously undermine the optimistic claims made by their authors.
Some useful websites:

The State HIE Toolkit
The State Health Information Exchange Leadership Forum
HIMSS Health Information Exchange
The Office of the National Coordinator for Health Information Technology (ONC)
Wikipedia Regional Health Information Organization
Nationwide Health Information Network Overview (ONC)
Public Health Informatics Institute (PHII)

Reflections on Business Models

In commentaries on US policies to promote meaningful use of health information technologies and electronic health records, I have pointed out the importance of a system level view of infrastructures for health information exchange. Key to the development of such infrastructures is the underlying business model to assure nationwide integration and system sustainability. A number of papers on health care system business models are available from a variety of agencies:





A Strong State Role in HIE: Lessons from the South Carolina Health Information Exchange

(2010) AHIMA



Abstract:

HIEs provide the infrastructure for information exchange, including the business model, governance structure, operating principles, legal model, and technology model for the exchange of healthcare information among various organizations. HIEs and regional health information organizations (RHIOs) have struggled with development and sustainability. The causes of failures are varied, but a lack of a compelling value proposition for all stakeholders is often cited as the prevailing reason.1
The primary beneficiary from an HIE is often the patient, who contributes the least directly toward the HIE’s development and operational costs. Other vested stakeholders, such as payers and providers, all receive varying benefits and bear varying responsibilities for the costs. A major barrier in the development of HIEs then is the identification of a model that fairly and equitably distributes the costs and benefits among the various stakeholders. At the crux of this issue is whether HIEs should follow a private, market-driven model that requires the generation of profit and value for the participants, or if HIEs are a public good that requires public financing. RHIOs and HIEs typically rely on a mix of government and private grants in the start-up phase, with the expectation of self-sustainability in the future: Four categories of business models are: not-for-profit, public utility, physician-payer collaborative, and for-profit.




ICT for the Health Unit, Directorate General Information Society and Media, European Commission: Business Models for eHealth (2010)


Abstract:

The evidence suggests that a solid business model is required for developing and
implementing a value-creating and sustainable eHealth service. In particular, this business
model needs to map all key supporting activities, value chain relationships and
dependencies impacted by the introduction of an eHealth service. This state of affairs can
be achieved if a set of activities and steps are implemented.
First, the structuring and implementation of such business model requires strong senior
management involvement throughout the various phases of the design, development and
delivery of an eHealth service. More importantly, senior management should not just act
as a project or programme manager; instead, it should make sure that the eHealth system
that it is supporting is provided with the required funding throughout its entire
development and implementation phases. Essentially, senior management is expected to
have a clear vision of what its healthcare delivery organisation wants to achieve with a
specific eHealth service and system, and lead the required operational steps.
In addition, staff involvement is essential in designing a business model of an eHealth
service. They need to be given the opportunity to understand how the specific service is to
change their activity or role, and need to provide evidence for mapping their interactions
in order to see how the eHealth service is going to improve or modify them. All of these
activities are aimed at making sure that business models do not fall short of reflecting the
interactions of those actors who are to use them in their day-to-day professional activities.
A business model of a value-creating and sustainable eHealth system is a static entity. It
might change as a consequence of technological and organisational evolution. However, it
can evolve following an evaluation aimed at measuring the potential and current impact of
the eHealth system. This may require data collection concerning activity, costs and
benefits. It also involves the need to apply sensitivity analysis to assess different scenarios
through which it is possible to design or modify a business model. Although the literature
provides several eHealth evaluation models, their implementation requires strong senior
management and process management, since regular performance data needs to be
collected and examined in order to assess current performance and estimate future
developments.

US Regional Health Information Organizations and the Nationwide Health Information Network: Any Lessons for Canadians? D. Protti ElectronicHealthcare, 6(4) 2008: 96-103

Abstract:
There seems to be general agreement in the United States that a Regional Health Information Organization (RHIO) is a neutral, non-governmental, multi-stakeholder organization that adheres to a defined governance structure to oversee the business and legal issues involved in facilitating the secure exchange of health information to advance the effective and efficient delivery of healthcare for individuals and communities. The geographic footprint of an RHIO can range from a local community to a large multi-state region. As regional networks of stakeholders mature, they often find the need for a formal independent organizational and governance structure (i.e., an RHIO) with systems to ensure accountability and sustainability for the benefit of all stakeholders. Experts maintain that RHIOs will help reduce administrative costs associated with paper-based patient records, provide quick access to automated test results and offer a consolidated view of a patient's history. The terms RHIO and Health Information Exchange (HIE) are often used interchangeably though most would see HIE as a "concept" relating to the mobilization of healthcare information electronically across organizations within a region or community as opposed to an "organization." Typically, an HIE is a project or initiative focused around electronic data exchange between two or more organizations or stakeholders. This exchange may include clinical, administrative and financial data across a medical and or business trading area. HIEs may or may not be represented through a legal business entity or a formal business agreement between the participating parties. Local Health Information Infrastructure (LHII) is a term occasionally used synonymously with RHIO. LHII was originally termed by the Office of the National Coordinator of Health Information Technology (ONCHIT) to describe the regional or local initiatives that are anticipated to be linked together to form an envisioned National Health Information Network (NHIN). The NHIN describes the technologies, standards, laws, policies, programs and practices that enable health information to be electronically shared among multiple stakeholders and decision makers to promote healthcare delivery. When completed, the NHIN will provide the foundation for an interoperable, standards- based network for the secure exchange of healthcare information in the United States.

eHealth Initiative (2007): Health Information Exchange: From Start-up to Sustainability





University of Copenhagen Masters Thesis (2009):

Behind the Internet Business Models: An E-health Industry Case





OECD International Futures Project on
“The Bioeconomy to 2030: Designing a Policy Agenda”

Health Biotechnology:
Emerging Business Models and Institutional Drivers (2008)


Abstract:
Up until today, two business models have been dominant within the application of
biotechnology for human health, or what is called health biotech in this report. One is the
classical biotechnology model. In this model, scientific discoveries and technological
inventions have been quickly developed within entrepreneurial firms, usually based upon
venture capital. They compete through their specialized scientific knowledge, often sold to
large companies, and they also compete through their flexibility, especially quick
commercialization of new fields. The other dominant business model is that of the large,
vertically integrated company. These large firms have integrated everything inside the
boundaries of the firm, from research and development (R&D) to production to marketing
and after sales monitoring. Firms in pharmaceuticals have competed through finding the
next ‘blockbuster drug’ and those in medical devices have also competed through
developing specific technologies and devices for large numbers of customers.
The report argues that four institutional drivers will form a very different context to deliver
human health care. Those four institutional drivers for change are 1) Scientific and
technological advances; 2) Public research and the public-private interface; 3) Public policy,
institutions and regulation; and 4) Demand and consumers.