Health Information Exchange: Infrastructures and Market Dynamics

Kuperman, G.J. 2011, “Health-information exchange: why are we doing it, and what are we doing?”  Journal of the American Medical Informatics Association, 18(5), 678-682.  http://jamia.bmj.com/content/18/5/678.full

This important article offers a very useful conceptual view of health information exchange – set in the context of  US health care sector market dynamics.  The author summarizes the early history of the Nationwide Health Information Network (NHIN) and the HITECH Act of 2009 promoting the introduction of health information technology  (HIT) on a national scale.  The article begins with the vision of health information exchange (HIE) as a key enabler of high quality and efficient health care.  According to the author, early demonstration projects conducted from 2005-2007 have shown that the interconnection of RHIOs for health information exchange in the “network of networks” requires neither a centralized national infrastructure nor a national patient identifier.  Unfortunately, these conclusions are more ideological than scientific, as there is little corroborating evidence in policy or organizational research. 

Since 2005, the eHealth Initiative has reported on the development and sustainability of RHIOs and State Designated Entities (SDEs) across the United States.   Kuperman cites the 2010 eHealth Initiative HIE Survey  findings (available at http://www.ehealthinitiative.org/resources/viewcategories.html )  to substantiate the existence of 73 “operational” initiatives, but he does not mention that among those, the report finds that only 18 can be described as “sustainable” – sustained on operational revenue alone and not dependent on federal funding. (See page 2 of the Key Findings.  One of the findings listed on page 1, states that “Sustainability is an attainable goal for health information exchange organizations. There is a small but critical mass of sustainable organizations. ”  This finding is without adequate foundation in the eHealth Initiative data analysis or other studies of health care organization.  Such data interpretation threatens the formulation of credible policy on health information technology in US system reform.)  The terms RHIO, SDE and HIE refer to organizations that address the” business issues of interoperability”, but critical review of  eHealth Initiative research as well as other published scholarly articles suggests that sustainable business models have not been identified. 

My reviews of these reports reveal some methodological deficiencies that tend to weaken published study conclusions. (See http://eresearchcollaboratory.blogspot.com/2009/10/health-information-exchange-update.html  .  My blog review was completed before the eHealth Initiative redefined their HIE reports as proprietary – despite Federal funding supporting the research.  Only the “key findings” are available for public review.  The validity of such findings cannot be evaluated without access to the research methodology.)  From year to year, the eHealth  Initiative reports that the number of HIE entities has increased - without accounting for sample mortality or changes in their definition of HIEs. 

Another publication (See  Julia Adler-Milstein, David W. Bates and Ashish K. Jha, 2009, U.S. Regional Health Information Organizations: Progress And Challenges, Health Aff , 28( 2) 483-492 available at http://content.healthaffairs.org/content/28/2/483.abstract  .) based in part on data from the  eHealth Initiative (See http://www.ehealthinitiative.org/resources/viewcategories.html  )  includes a measure of time spent in HIE planning.  This indicator seems to be negatively associated with operational status of the entities in the sample. While Adler-Milstein et al. conclude that a lengthy planning process may challenge HIE viability, it is also possible that this result reflects the short life expectancy of HIE entities – as time spent in planning may serve as a partial surrogate for longevity. 

These authors have also published another study (apparently based on some of the same data). (See Adler-Milstein et al. 2011,  A Survey of Health Information Exchange Organizations in the United States: Implications for Meaningful Use, Annals of Internal Medicine, 154(10) 666-671 available at http://www.annals.org/content/154/10/666.abstract )

They elaborated the definition of a “comprehensive RHIO” in light of the HIE requirements for meaningful use of electronic health records (EHRs).  This definition was developed by a panel of 9 national health policy experts using a Delphi methodology to arrive at consensus.  Analysis revealed that none of the RHIOs included in the sample satisfied the criteria of this definition.   This finding suggests the possible failure of the market driven “network of networks” approach to development of the NHIN.     

Such failure may also be attributed to the short time frame (2-4 years) for public funding in support of RHIOs as well as the requirement that they develop business models based on revenue streams from private stakeholders and system users.  Such business models are all the more difficult to identifiy given that the significant benefits of health information exchange often accrue at the system level rather than the individual provider or payer level of analysis.  Adler-Milstein et al. (2011) conclude that their findings “…call into question whether RHIOs in their current form can be self-sustaining and effective in helping U.S. physicians and hospitals engage in robust HIE to improve the quality and efficiency of care.” (See abstract.)  Questions raised in this study suggest that the “network of networks” strategy based on the sustainability of RHIOs cannot be assumed as in Kuperman’s analyses of other projects, such as Direct and Connect  for health information exchange in the context of health sector market dynamics.

The second issue related to health information infrastructures required for national system reform is the creation of a unique patient identifier.  As mentioned above, Kuperman suggests that such an identifier was shown to be unnecessary in early demonstration projects for the NHIN and the “network of networks” approach.  This is another ideologically convenient finding, without an evidence base in policy experience or organizational research.  Kuperman argues that the advantage of a PUSH model such as Direct is to avoid the necessity of linking patient identifiers across systems before data transfer between health care organizations.  While directories of authorized organizations (and their identifiers) would have to be established – individual patients would be identified by the authorized senders and receivers using internal matching algorithms– or even manual procedures.  This approach would probably be effective in small-scale systems,  but may be impracticable at the regional and national levels (not to mention the global level) as the volume of data increases with mobility and diversity of patient populations served.

According to Kuperman, clinicians will expect both PUSH and PULL service dynamics for health information exchange, including transmission among providers as well as retrieval of individual patient data across the entire health care system.  The responsibility for designing and managing these services apparently resides with RHIOs under the assumption of their sustainability: “As RHIOs (grapple) struggle to support interoperability-based services that improve the quality and efficiency of care, they will have the opportunity to understand how best to combine pull- and push-oriented capabilities.” (page 681) Given the ongoing failure of federal investments in RHIOs and the “network of networks” strategy to develop infrastructure, this policy direction lacks credibility and remains unfounded in research evidence or policy experience.

Kaplan and Porter: How to Solve the Cost Crisis in Health Care

This commentary is particularly relevant now in light of the ONC revision of the federal Health Information Technology Strategy:

Commentary : R. Kaplan and M. Porter, “How to Solve the Cost Crisis in Health Care”, Harvard Business Review, September, 2011,  47-64. (See the article at http://hbr.org/2011/09/how-to-solve-the-cost-crisis-in-health-care/ar/1) 

In this important publication Kaplan and Porter develop a methodology for measuring the “right” things in the “right” way to ascertain an account of costs and outcomes in health care service delivery to individual patients in the care delivery value chain (CDVC).  The authors argue that most health care costs are not fixed, and therefore accessible to managerial control.  (In my opinion, this argument is symptomatic of the absence of a health care “system”, as is the “rule of one” applied to costing expensive equipment in the context of a single health care enterprise competing with others.) In other commentaries on my blog at http://eresearchcollaboratory.blogspot.com/2011_04_01_archive.html - I have discussed Porter’s work on conceptualizing and measuring “value” in health care “per dollar expended”, and some of the pitfalls of reliance on this common denominator.  

The methodology proposed here addresses the critical need to manage cost associated with health care services. However, some implicit ideological assumptions should be examined.  First, the method of process mapping is framed in a for-profit health care services market, assuming that competition to control costs at the enterprise level will result in financial return on investments as well as system-level savings.  This approach may result in unnecessary and costly process duplication at the system level as illustrated in the case of McAllen, Texas: http://www.newyorker.com/reporting/2009/06/01/090601fa_fact_gawande .  Such costly duplication is all the more critical in the increasingly resource poor U.S. health care context.

The second apparent assumption is that health care services can effectively be conceptualized and mapped in the same way as manufacturing systems.  Kaplan’s “Time-Driven Activity-Based Costing” (TDABC) as described in earlier HBR publications also aims specifically to augment enterprise profits in competitive markets.  Many health economists reject these perspectives on service production, profitability and the efficacy of market dynamics in the health care sector.

Health care process mapping is not a new idea; it has been practiced in other national systems, including the NHS (UK- See the Institute for Innovation and Improvement at http://www.institute.nhs.uk/), Canada and Australia.  Lack of reference to other national experiences leaves the HBR article reader with the impression that such methods have not been used in the health care sector.    

Review of some of the recent literature suggests that the results of the process mapping methodology vary, for example, according to the choice of hierarchical vs. sequential mapping, as well as selection of participating stakeholders and the overall process perspective.  (See Colligan, Anderson et al., Does the process map influence the outcome of quality improvement work? A comparison of a sequential flow diagram and a hierarchical task analysis diagram,  BMC Health Services Research, 2010, 10:7doi:10.1186/1472-6963-10-7: http://www.biomedcentral.com/1472-6963/10/7)

Evidence based clinical pathways also offer an approach to link evidence to multi-disciplinary care plans for specific clinical conditions. (See Rotter, Kinsman et al., Clinical pathways:  Effects on Professional practice, patient outcomes, length of stay and hospital costs (Review), The Cochran Library, Issue 7, 2010,    http://onlinelibrary.wiley.com/doi/10.1002/14651858.CD006632.pub2/pdf/abstract ).  The Map of Medicine at http://eng.mapofmedicine.com/evidence/map-open/index.html (associated with the NHS) illustrates the development and use of clinical pathways in patient diagnosis and treatment.  The clinical pathway methodology is designed to integrate high quality evidence from research in medicine with practice-based knowledge. 

The NHS emphasizes the importance of a culture supporting performance improvement, and a focus on the patient experience.  While Kaplan and Porter apply their method at the individual level of analysis, their objective is to map those activities related to a specific medical condition that can be “costed”, thus introducing an activity selection bias in the process map.  The resulting focus is the cost of individual disease treatment cycles rather than a holistic view of the patient’s health care experience aggregated in the larger population perspective.

Kaplan and Porter seem to address more effectively the interests of private insurers, to “reinvent reimbursement” by measuring costs at the individual level of analysis – with increasing granularity (including…“consumable supplies such as medications, syringes, catheters, and bandages used directly in the process.”  p. 54).  The authors do not address the costs of such granular data collection and analysis.  Furthermore, they do not demonstrate HOW the TDABC process should be informed by health care “value” or research evidence on health care outcomes – with the result that the managerial values driving the process are not adequately subordinate to the science of medicine or the care of patients and populations. 

Comment on the Federal Strategic Plan to Reduce Health IT Disparities - An Update

As in the initial Federal HIT Strategic Plan, the need for health information infrastructures to resolve the fragmentation of the U.S. health care system has not been adequately addressed in the Plan to Reduce Health IT Disparities available at http://www.healthit.gov/buzz-blog/from-the-onc-desk/federal-strategic-plan-disparities/  .  My comments published on May 6 are still relevant on the strategy to reduce health disparities: (See http://eresearchcollaboratory.blogspot.com/2011/05/commentary-on-federal-health.html ) Individual patient empowerment and engagement in the system especially requires attention to the creation of a unique individual digital identity for health care, education for multilingual health literacy, and open access to health information and scientific research.  Moving forward without infrastructures required for a patient-centered system and outreach to under-served populations will result in significant waste in funded efforts as well as loss of credibility and trust at a critical time in health care system reform.

Central to individual empowerment is the assurance of an individual digital identity in the health care services ecosystem. (See the Analysis of Unique Patient Identifier Options prepared for the Department of Health and Human Services in 1997: http://www.ncvhs.hhs.gov/app0.htm)  While the individual patient is the focus of U.S. health care system reform efforts, there is no credible plan to provide a unique digital identity to every patient.   The National Strategy for Trusted Identities in Cyberspace published in April, 2011, (See http://www.whitehouse.gov/sites/default/files/rss_viewer/NSTICstrategy_041511.pdf ) “recognizes that trusted digital identity, authentication and authorization processes are one part of layered security. Improvements in identification and authentication are critical to attaining a trusted online environment...” (page 8).  While recognition of the critical importance of individual digital identities represents an important step, the proposed system calls for complex roles to be implemented by multiple actors in both public and private sectors. The federal government plays a significant role in the early stages of the initiative, but it is expected that new and sustainable  business models will be developed for each of the service provider roles of the system (page 37) so that the identity ecosystem will become a self- sustaining market place.

The U.S. strategy for digital identities embodies the same errors as federal policies to promote the Nation-wide Health Information Network (NHIN) for health information exchange.  A reliable and valid digital identity cannot be the output of complex private sector market dynamics.  This policy principle virtually assures that there will not be universal access to reliable digital identity, and that the U.S. model will not be interoperable with ID models of other countries.  The consequences of this stance for exclusion of underserved populations should not be underestimated.  Moreover, a market supporting for-profit digital ID roles would be a fertile context for medical and administrative error, fraud and ID theft.

The lack of a unique patient identifier also has serious consequences for patient safety as the population grows and becomes more linguistically diverse and physically mobile - both nationally and internationally.  U.S. patients are generally identified using an internally derived identifier created by a care provider, while between systems, “fuzzy matching”  is frequently used to generate lists of patients with similar names and demographic profiles for evaluation as to the “best fit” match. (See http://www.corp.att.com/healthcare/docs/mpi.pdf for an example.)  This approach certainly will incur rising costs and compromise patient safety as more diverse and multilingual health care systems become globally interconnected. (See http://gpii.info./news.php for some relevant research and publications. See also the American College of Pathologists: http://www.cap.org/apps/cap.portal?_nfpb=true&cntvwrPtlt_actionOverride=%2Fportlets%2FcontentViewer%2Fshow&_windowLabel=cntvwrPtlt&cntvwrPtlt{actionForm.contentReference}=cap_today%2F1109%2F1109j_national_id.html&_state=maximized&_pageLabel=cntvwr  , and an HIMSS White Paper (2009) on Patient Identity Integrity at http://www.himss.org/content/files/PrivacySecurity/PIIWhitePaper.pdf  ) 

In the United States, approximately 98,000 people die because of medical malpractice during hospitalization. 13% of the overall number of malpractices in surgery and 67% of errors in conjunction with blood transfusions can be traced back to erroneous patient identification. Source: 

Joint Commission International Center for Patient Safety (Eds.): Technology in
Patient Safety - Using Identification Bands to Reduce Patient Identification Errors, in:
Joint Commission Perspectives on Patient Safety, 5, 2005, pp. 1-10. (See page 2 at http://ehealth.iwi.unisg.ch/fileadmin/hne/downloads/Mettler__Fitterer__Rohner__Strategies_for_a_Systematical_Patient_Identification.pdf )

Examples of strategies for unique identification in other countries include the British NHS unique patient identifier, (See http://www.connectingforhealth.nhs.uk/systemsandservices/nhsnumber/) and the Indian “Aadhaar”,  a 12-digit unique number which the Unique Identification Authority of India (UIDAI) will issue for all residents. The number will be stored in a centralized database and linked to the basic demographics and biometric information – photograph, ten fingerprints and iris – of each individual.   The Indian “Aadhaar” is also considered a tool to combat corruption – in particular by improving the ability to extend services to the most vulnerable citizens. (See an article in Le Nouvel Observateur (Sept. 9, 2011) at  http://tempsreel.nouvelobs.com/actualite/economie/20110909.OBS0074/l-identite-biometrique-arme-anticorruption-des-indiens.html ;

see also an  interesting initiative implemented in the U.S. by the NYU Langone Medical Center at http://www.computerworld.com/s/article/9217678/Hospital_turns_to_palm_reading_to_ID_patients )

The U.S. strategy for patient empowerment and engagement should include the creation of a unique biometric patient identifier to be offered on a voluntary basis to all citizens. Similar to the Indian Aadhaar, this identifier would not be mandated for citizens, but health care service providers could require it of those seeking their services.  

  

The successful pursuit of goals for individual patient empowerment within a learning health system depends upon the public infrastructures for digital identity and health information exchange – as well as health literacy interventions to improve individual skills.  Some research suggests that only one in ten adults in the U.S. may possess the knowledge and skills required to perform at a high level of health literacy.  Population health literacy is prerequisite to individual empowerment as well as to creation of a learning health system – particularly in the complex, fragmented, and increasingly multilingual and multicultural U.S. context. (See http://www.hsph.harvard.edu/healthliteracy/research/ for more resources.)

The national capacity for innovation and research requires infrastructures developed as a public good as sustained public investments in health sciences and research contribute to the foundation for a learning health care system. An important aspect of learning systems is open access to information – including data and scientific publications.  Some important steps have been taken in the U.S. system to improve such access to federally funded research, such as the National Institutes of Health Public Access Policy applicable to any manuscript reporting research funded by the NIH - accepted for peer-reviewed publication on or after April 7, 2008.  “To help advance science and improve human health, the policy requires that these papers are accessible to the public on PubMed Central no later than 12  months after publication.” (See http://publicaccess.nih.gov/)  While this policy represents progress toward the goal of open access to scientific publications, the delay of 12 months allowed for compliance significantly reduces its effectiveness. Lack of open access to health information and research hinders patient empowerment as well as development of a learning health system.

The  Latin-American and Caribbean Center on Health Sciences Information (Bireme) illustrates a multilingual (Spanish, Portuguese and English) regional model for open access to health information and publications available through the Virtual Health Library.  (The model and methodologies for development of this library are published in the VHL Guide 2011 available at  http://guiabvs2011.bvsalud.org/en/presentation/.) 

The U.S. should develop policies to promote open access to health information and research – taking into account the increasing linguistic and cultural diversity of the nation’s population as well as the globalization of health information systems.

Chinese and U.S. Health Care System Reform

See the Westlake Forum:  Healthcare Reform in China and the US: Similarities, Differences and Challenges, held at Emory University on April 10-12, 2011.  Both slides and video presentations are available for review.  This program is a valuable reference for researchers working on health care financing reform in any context- at the state or country levels of analysis.  William Hsiao of Harvard University points out the critical importance of  professionalism and ethics among both physicians and system administrators as a foundation of the reform process.  He also emphasizes that China is ahead of the U.S. in designing a system to offer health care services to all  Chinese citizens. On the other hand, he suggests that the Chinese strategy of hospital privatization to promote competition is not based on any policy evidence from world experience.

New Research on EHR and CDS Effectiveness

The following review illustrates some of the methodological difficulties common in current research on EHR and CDS effectiveness.

Health Records and Clinical Decision Support Systems: Impact on National Ambulatory Care Quality

Max J. Romano, BA; Randall S. Stafford, MD, PhD
Arch Intern Med. 2011;171(10):897-903. doi:10.1001/archinternmed.2010.527
This article is available at : http://archinte.ama-assn.org/cgi/content/abstract/171/10/897

Background  Electronic health records (EHRs) are increasingly used by US outpatient physicians. They could improve clinical care via clinical decision support (CDS) and electronic guideline–based reminders and alerts. Using nationally representative data, we tested the hypothesis that a higher quality of care would be associated with EHRs and CDS. 

 Methods  We analyzed physician survey data on 255 402 ambulatory patient visits in nonfederal offices and hospitals from the 2005-2007 National Ambulatory Medical Care Survey and National Hospital Ambulatory Medical Care Survey. Based on 20 previously developed quality indicators, we assessed the relationship of EHRs and CDS to the provision of guideline-concordant care using multivariable logistic regression.

Results  Electronic health records were used in 30% of an estimated 1.1 billion annual US patient visits. Clinical decision support was present in 57% of these EHR visits (17% of all visits). The use of EHRs and CDS was more likely in the West and in multiphysician settings than in solo practices. In only 1 of 20 indicators was quality greater in EHR visits than in non-EHR visits (diet counseling in high-risk adults, adjusted odds ratio, 1.65; 95% confidence interval, 1.21-2.26). Among the EHR visits, only 1 of 20 quality indicators showed significantly better performance in visits with CDS compared with EHR visits without CDS (lack of routine electrocardiographic ordering in low-risk patients, adjusted odds ratio, 2.88; 95% confidence interval, 1.69-4.90). There were no other significant quality difference.

Conclusions  Our findings indicate no consistent association between EHRs and CDS and better quality. These results raise concerns about the ability of health information technology to fundamentally alter outpatient care quality.

The conclusions reported in this study are consistent with many other recent studies, suggesting that there is no consistent relationship between the use of these tools and effective patient care.  However, it is very important to examine the study design before evaluating the conclusions of this research.  Critical points to be reviewed include the delay in publication with respect to data collection, generally limited use of EHRs and CDSs in US physician practice, the choice of patient visits as the unit for statistical analysis, the procedure for defining the sample, and identification of control variables in the regression model.


The topic addressed in the study is of critical importance, but the rapidly evolving technologies associated with EHR and CDS use require more current assessment. Data collected in the period 2005-2007 provides an interesting historical perspective, but may not yield analyses relevant to the current context.  While EHR adoption in the US remains modest compared to some other industrialized countries (as pointed out by the study authors), state and federal expenditure to promote health information technology adoption is significant, and patterns of adoption have changed on some qualitative dimensions due to emergence of new practice arrangements such as ACOs and implementation of policies such as meaningful use.


The unit of analysis for the study is the patient visit rather than the patient, and performance quality was measured as adherence to guidelines by visit rather than by visits associated with a particular patient.  It was assumed that a higher proportion of guideline adherence by visit should be interpreted as higher quality care provided to eligible patients.  The data analysis does not by itself justify this interpretation.  Drawing any conclusion concerning quality of patient care is further complicated by the lack of consideration of patient clinical profiles - apparently because the authors assert that the quality guidelines should apply to any patient except those presenting potentially confounding comorbidities.  (Patients presenting such comorbidities have conveniently been eliminated from the sample. The authors provide the following example of comorbidity resulting in exclusion of patients - and their visits-  from the sample: asthma in assessing the use of β-blockers in coronary artery disease.)  This reductionist methodological strategy does simplify the statistical analysis, but it also seems to defeat the evaluation of CDS in care of patients who should potentially benefit most from its use.


The authors also mention that they have included emergency visits in the study sample because 
"they are a key source of care and a setting in which EHRs have been more widely adopted", while such visits resulting in hospitalization have been excluded.  The authors do not adequately examine the consequences of these exclusions for the sample size or for interpretation of study results.


The methodology designed for analysis of the data in this study presents several critical weaknesses that may explain the lack of significant results.  In analysis of data from NAMCS and NHAMCS and other similar data sets, future efforts are required to assure patient-centered assessment of care quality - taking into account complex clinical profiles as well as health outcomes over time. Such models would be especially useful for longitudinal analysis as new data become available.


   








 

Commentary on the Federal Health Information Technology Strategic Plan (2011-2015) - Republished

This commentary first published on 5-6-11 remains relevant, particularly in light of slow progress in development of infrastructures for health information exchange:

The Federal Health Information Technology Strategic Plan (2011-2015) lays out the HIT vision, mission and principles as well as goals, objectives and strategies to be implemented in the next five years.   My commentary will address first the guiding principles for health IT at the foundation of the overall strategy and how these principles affect  the  five goals formulated in the plan: I – Adoption and information exchange through meaningful use, II – Improvement of care and population health as well as cost reduction, III -  Promotion of confidence and trust in health IT, IV – Individual empowerment with health IT to improve care processes and the health care system, and V -  Achievement of learning and technological advancement. In conclusion, some recommendations will be outlined.

The principles on page 8  emphasize the needs and rights of individuals and the reliance “to the extent possible” on private markets to achieve societal objectives - with intervention only “when necessary” to correct market failures.  This  reliance on private markets is contrary to international development experience as well as theory and research  in health economics demonstrating inadequacies of  capital markets in provision of social services.[1,2] It is important to distinguish between competitive innovation in health services and the health information infrastructure (the NHIN) required to support such activities.  While HIT infrastructure may be defined as a public good,  both public and private services markets may share the resulting institutional ecology.

The focus on outcomes is critical to the success of health care reform, but this emphasis will not be adequate to motivate performance if national system design remains fragmented.  Private markets will not foster the emergence of a system infrastructure as seems to be an implicit principle.  Furthermore, costs associated with extensive micro-measurement of individual health care outcomes should not be underestimated.  (I have reviewed the concept of “value” in health care outcomes as formulated by M. Porter on my blog because it seems to me that his model is consistent with the ideological viewpoint of the majority of the U.S. policy-making community.[3,4])

Building on “what works” is also an essential principle of any learning system, but as I have suggested in earlier commentaries, the focus in the U.S. health care system seems restricted to experiences within its boundaries.  There are virtual natural experiments in progress  in developing countries as well as industrialized nations around the world, and the U.S. could learn valuable lessons and avoid expensive mistakes through systematic analysis of selected national health care systems. This approach would  encourage evidence-based learning and innovation to more rapidly close the significant lag in health care system performance that threatens the competitive stance of the U.S. in the global economy.

Goal I:  Achieve Adoption and Information Exchange through Meaningful Use of Health IT (page 9) should  be reformulated:  Achieve Adoption and Meaningful Use of Health IT through Information Exchange.  The creation of infrastructure for health information exchange is prerequisite to adoption of health information technology and its meaningful use.   For example the Veterans Administration (VA) (mentioned on page 10) operates a single payer system through a federally supported infrastructure that makes possible HIE. The functionalities to exchange information integrated in EHRs and to report data relevant to public health are some of the most important intrinsic motivators for HIT adoption – affecting all stakeholders: providers, payers, patients and consumers. The VA offers a demonstration of the effectiveness of an integrated single payer system, as well as the benefits of HIE.  However, the VA is a subsystem distinct from other segments of the health care sector, and thus will probably not contribute to the critical mass (or tipping point) necessary for health care system transformation as discussed on page 10.  Principles guiding the VA, Medicare and Medicaid are  very different from those at the foundation of private insurance markets for the majority of U.S. citizens.

On page 11 Strategy I.A.2 proposes implementation support to help health care providers through the Regional Extension Center (REC) Program. While funding for this program has been extended beyond the initial two-year time horizon, these organizations will be required to develop business models to become self sustainable.  As is the case for Regional Health Information Organizations (RHIOs) and State Designated Entities (SDEs), such business models have not been identified.[5]  Some observers have further noted that funded RECs may favor selected vendors for interoperability, thus introducing a significant conflict of interest in the support they offer.  (See SoftwareAdvice, 9-23-2010) It may not be realistic to assume that RECs working with competing vendor consultants will “collaborate with one another and with relevant stakeholders to identify and share best practices in EHR adoption, meaningful use, and provider support.” (page 11).  

Consistent with M. Porter, the strategic intention is to move away from the process requirements formulated in stage one of meaningful use towards improvements in outcomes and quality of care.[3,4]  However, it should not be assumed that such improvements will be correlated with meaningful use of health information technology as in the Federal HIT Strategy.  In Canada, penetration of EHR is low, comparable to rates reported in the U.S.[6],  but health care system performance measured by public health indicators and overall per capita cost is ranked  higher .[7]  This would suggest that the superior performance of the Canadian system  is explained by other factors –  possibly higher rates of sustained public investment in health IT infrastructures [8]and the single payer model[9].   Furthermore, there may be a variety of paths to improvements in outcomes and quality of care as a result, for example, of major technological, institutional or medical paradigm shifts – in progress but as yet unforeseen.  

Strategy I.A.5  emphasizes the process to certify EHR technology for meaningful use.  The strategy as formulated does not address the financial burden on software vendors to achieve certification of their products.   There is furthermore little clarification concerning validity of certification over time and the business model to be associated with continued certification: See CCHIT Town Call: ONC-ATCB 2011/2012 Certification Program (September 20,2010)

Do ONC-ATCB certified products have to undergo re-certification for each new release?

Following ONC/HHS Final Rules, Establishment of the Temporary Certification Program for Health Information Technology, certification is completed with a specific version of the technology that was tested by CCHIT and found compliant with the relevant certification criteria. For the purpose of maintaining certification, “minor product changes” are those modifications and updates to a certified product that are unlikely to affect the product’s compliance with the certification criteria. Retesting may not be required but the vendor is required to notify the ONC-ATCB and provide self-attestation that the changes are minor.

Modifications with a significant risk of affecting the product’s compliance are considered to be a “significant product change.”  Retesting is required. Applicants are required to self-classify their product modifications and updates into one of these two categories.

Will software re-certification be required for each "meaningful use" stage?

Yes; the criteria, standards and test procedures will change for each stage.  ONC has retained the right to change certification criteria at any time, but it is most likely that this will not occur until the next stage. The Final Rule states that the Temporary Certification Program is scheduled to sunset on December 31, 2011, unless HHS/ONC decides to extend it or hasn’t defined the permanent program. 

Is there an effective period for certification?  For example, if an EHR is certified in January 2011, when would the certification end and when would the technology need to be retested?

The effective period certification is determined by when ONCs publishes new rules for standards and certification criteria. If you are selling your software to providers who wish to meet the requirements of all three stages of meaningful use, you will need to recertify your EHR technology for 2013/2014 and 2015/2016.

The process of re-certification will be costly to vendors and entities implementing self-developed software products. The significant uncertainties associated with certification also increase risk inherent in such investments.  Little data is available for evaluation of such risks and published information, such as the CCHIT Toolkit is often expensive as well. (The Toolkit – developed under  federal funding - costs $1000 unless the entity seeking access to the information is committed to apply for certification.  This policy discourages detailed review by prospective CCHIT applicants as well as  researchers and the general public.)

I have already commented on policies regarding health information exchange (HIE) and meaningful use.  Objective I.B cites the lack of sustainable business model to support HIE as well as fragmented policy-making at the federal, state and local levels.  The federal strategy mistakenly states that there are “many sustainable exchange options …  for certain providers and certain types of information.” (page 15)  The federal government will: 1-Foster business models that create health information exchange, 2-Monitor health information exchange options and fill the gaps for providers that do not have viable options, and 3-Ensure that health information exchange takes place across individual exchange models. (page 15)  These roles cannot be assumed by the federal government unless the necessary infrastructure is redefined as a public good sustained by significant public investment.  In particular, it is not useful to propose “filling the gaps” where no system exists.  It would be more constructive to leverage an existing program  such as the National Information Exchange Model (NIEM),  thus assuring integration with other systems for national security and disaster management- as suggested on page 18.

Another very important policy issue related to federal health IT strategy is broadband Internet access as mentioned on page 16.  Comparative country analysis suggests that the U.S. lags behind other OECD countries in pricing, speed, penetration and access.[10]  Some observers believe that the U.S. does not now have adequate broadband infrastructure to support full deployment of HIT meaningful use and health information exchange.  The infrastructures required for HIT implementation are prerequisite to most of the policies formulated in the Federal Health IT Strategic Plan. Moving forward without these infrastructures in place will result in significant waste in funded efforts as well as loss of credibility and trust at a critical time in health care system reform.

On page 18 it is stated that the ONC is “tracking the activities of other countries and learning from their experiences with health IT and health information exchange.” There is very little evidence that this is the case, particularly with regard to our closest neighbors, Canada and the Latin American region.  Regional collaboration needs to be extended across the hemisphere to facilitate system integration for health information exchange, research and education. (Large grid and cloud systems for basic and translational research are discussed on pages 27-28, while there is no mention of extension of such systems across regional boundaries.)

Goal II of the Federal Strategic Plan (page 22) is to improve care, improve population health, and reduce health care costs through the use of health IT.  Strategy II.A.2 (page 24) calls for administrative efficiencies to reduce cost and burden for providers, payers, and government health programs.  This is a very important but also very elusive objective as programs for payment reform such as the formation of Accountable Care Organizations call for additional administrative mechanisms to assure outcome  measurement and reporting as well as distribution of savings and incentives to participants.  The strategy also calls for “more granular understanding of health care treatments and outcomes, and more complete analyses of treatment costs, ultimately allowing for better disease management and more efficient health care delivery.”(page 25)  Such detailed analysis of treatment costs is aligned with  multiple private health insurers' requirements, and is often accomplished at the expense of a system-level focus on population health.  The public funding of new health insurance exchanges -particularly in the absence of a public health insurance option - also subsidizes the interests of private health insurers by assuming the costs of infrastructure benefiting for-profit enterprise in health care services.  These costs should be assigned to the private sector.

Strategy II.D.3 (page 27) calls for a mechanism to support information exchange for research and the translation of research findings back into clinical practice. This strategy also emphasizes the importance of infrastructure for HIE as well as large grid and cloud-based systems for the exploration of the wealth of existing data on the human genome.  As mentioned above, extensive and sustainable public investments are essential to assure the creation and maintenance of such national infrastructures (including broadband) and to promote their interconnection with larger regional systems.

Goal III (page 29) calls for strategies to inspire confidence and trust in health information technology by protecting confidentiality, integrity and availability of health information, informing individuals of their rights, and improving safety and effectiveness of IT.  Central to these issues is the assurance of an individual digital identity in the health care services ecosystem.  While the individual patient is the central focus of health care system reform efforts,  there is no credible plan to provide a unique digital identity to every citizen. (This is one of the most intriguing internal contradictions in the logic of the U.S. model of reform.)  Privacy protections as they are currently designed are more consistent with the interests of private health care insurers than those of the individuals they serve.  These protections pose obstacles to data aggregation as well as disclosure relative to  insurance plan performance.

The National Strategy for Trusted Identities in Cyberspace (April, 2011)[11] “recognizes that trusted digital identity, authentication and authorization processes are one part of layered security. Improvements in identification and authentication are critical to attaining a trusted online environment; however, they must be combined with other crucial aspects of cybersecurity.” (page 8).  While recognition of the critical importance of individual digital identities represents an important step, the proposed system calls for complex roles to be implemented by multiple actors in both public and private sectors.  While the federal government plays a significant role in the early stages of the initiative, it is expected that new and sustainable  business models will be developed for each of the service provider roles of the system (page 37) so that the identity ecosystem will become a self- sustaining market place.

This strategy for trusted identities in cyberspace embodies the same errors as federal policies for promotion of the Nation-wide Health Information Network (NHIN) for health information exchange.  A reliable and valid digital identity cannot be the output of  complex private sector market dynamics.  This policy principle assures that there will not be universal access to reliable digital identity, and that the U.S. model will probably not be interoperable with those of other countries.  The consequences of this stance for U.S competitive advantage in the global economy should not be underestimated.  Moreover, a market supporting for-profit digital ID roles would be a fertile context for fraud and ID theft as well as other illegal transactions based on digital ID information.

Examples of strategies for unique citizen identification in other countries include the British NHS unique patient identifier,[12]and the Indian “Aadhaar”,  a 12-digit unique number which the Unique Identification Authority of India (UIDAI) will issue for all residents. The number will be stored in a centralized database and linked to the basic demographics and biometric information – photograph, ten fingerprints and iris – of each individual.  (The U.S. State Department has shown some interest in the Indian system - for reasons related to National Security-according to cable communications made public by Wikileaks.[13])

Goal IV (page 36) calls for individual empowerment for improvement of health and the health care system.  The successful pursuit of this goal depends upon the public infrastructures for digital identity and health information exchange as discussed above – as well as health literacy interventions to improve individual skills.  [14][15] These studies suggest that only one in ten adults in the U.S. may possess the knowledge and skills required to perform at a high level of health literacy.  Population health literacy is prerequisite to individual empowerment as well as to creation of a learning health system (Goal V).

Goal V (page 42) calls for achievement of rapid learning and technological advancement through creation of a learning health system to support quality, research and population health, as well as increased capacity for innovation and research.   The national capacity for innovation and research requires infrastructures developed as a public good.  Sustained public investments contribute to the  foundation for a learning health care system. Another important aspect of learning systems and capacity for innovation and research is open access to information.  Some important steps have been taken in the U.S. system to improve such access to federally funded research, such as the National Institutes of Health Public Access Policy applicable to any manuscript reporting research funded by the NIH - accepted for peer-reviewed publication on or after April 7, 2008.  “To help advance science and improve human health, the policy requires that these papers are accessible to the public on PubMed Central no later than 12 months after publication.” While this policy represents progress toward the goal of open access to scientific information, the delay of 12 months allowed for compliance significantly reduces its effectiveness.

The  Latin-American and Caribbean Center on Health Sciences Information (Bireme) illustrates a regional model for open access to health information available through the Virtual Health Library. The model for this library is published in the VHL Guide 2011 now available for comment and consultation.  Background information is available in the publications of A. Packer, former  director of Bireme.[16].  Dr. Pedro Urra, the new director of Bireme, has been responsible for the creation and development of INFOMED,[17-20]  the Cuban National Health Care Telecommunications Network and Portal.  [21]  The U.S. should develop policies to join this important regional initiative and to further promote open access to health sciences research.

Summary recommendations

1. Public investment in a national health information infrastructure to promote interoperability for both public and private services - a single infrastructure does not necessarily imply a single payer design. 

2. Federal government provision of goal oriented services and tools - rather than financial incentives. 
     
3. Restriction of public reimbursement for basic health care products and services to not-for-profit enterprises. 

4. Extension of open access policies governing availability of public health information and published research in medicine and the health sciences. 
  
 5. Collaboration across the Americas as a foundation for large scale grid and cloud infrastructures to support regional research and innovation through the  Latin-American and Caribbean Center on Health Sciences Information – BIREME.
                                                                                                                                                           

References

[1] Arrow K, Auerbach A, Bertko J, Brownlee S, Casalino LP, Cooper J, et al. Toward a 21st-Century Health Care System: Recommendations for Health Care Reform. Ann.Intern.Med. 2009 April 7;150(7):493-495.

[2] Arrow K. Uncertainty and the Welfare Economics of Medical Care. The American Ecocomic Review 1963;53(5):941-973.

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

[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] Adler-Milstein J, Bates DW, Jha AK. U.S. Regional Health Information Organizations: Progress And Challenges. Health Aff. 2009 March 1;28(2):483-492.

[6] Rozenblum R, Jang Y, Zimlichman E, Salzberg C, Tamblyn M, Buckeridge D, et al. A qualitative study of Canada's experience with the implementation of electronic health information technology. CMAJ 2011 March 22;183(5):E281-288.

[7] Mirror, Mirror on the Wall: How the Performance of the U.S. Health Care System Compares Internationally 2010 Update.Davis K, Schoen C, Stremikis K. 2010.

[8] Anderson G, Frogner B, Johns R, Reinhardt U. Health Care Spending and Use of Information Technology in OECD Countries. Health Affairs 2006;25(3):819-831.

[9] Tuohy CH. Single Payers, Multiple Systems: The Scope and Limits of Subnational Variation under a Federal Health Policy Framework. Journal of Health Politics Policy and Law 2009 August 1;34(4):453-496.

[10] Next Generation Connectivity:  A review of broadband Internet transitions and policy from around the world.Benkler Y, Faris R, Gasser U. 2010.

[11] National Strategy for Trusted Identities in Cyberspace:  Enhancing Online Choice, Efficiency, Security, and Privacy.The White House. 2011.

[12] Smyth RL. Regulation and governance of clinical research in the UK. BMJ 2011 January 13;342.

[13] U.S. interest in unique identification project.Srivathsan. A. The Hindu 2011;Opinion.

[14] The Health Literacy of America's Adults: Results From the 2003 National Assessment of Adult Literacy.National Center for Education Statistics. 2006;NCES 2006–483.

[15] Health Literacy Interventions and Outcomes: An Updated Systematic Review.Berkman N, Sheridan S, Donahue K, et al. 2011;11-E006.

[16] Packer AL. The SciELO Open Access:  A Gold Way from the South. Canadian Journal of Higher Education 2009;39(3):111-126.

[17] Urra González P. Internet a la Cubana: El Ser Humano en el Centro de la Red. ACIMED 2003;11(1).

[18] Urra González P. Letter: Global Alliance for Health Information. BMJ 2001;321(7264).

[19] Urra González P, Rodrígues Perojo K, Concepcíon Báez C, Canedo Andalia R. Intranet of the National Medical Sciences Information Centre- Infomed: A Working Space in the Network for the Health Information System in Cuba. ACIMED 2006;14(1).

[20] Urra González P. Program for Strengthening the Scientific and Technical Health Information System of Cuba. ACIMED 2005;13(3).

[21] Séror A. A Case Analysis of INFOMED: The Cuban National Health Care Telecommunications Network and Portal. Journal of Medical Internet Research 2006;8(1):e1.