Commentary: Lenert, L., Sundwall, D., Lenert, M.E., Shifts in the Architecture of the Nationwide Health Information Network, Journal of the American Medical Informatics Association, Online First, January 21, 2012.

Lenert, L., Sundwall, D., Lenert, M.E.,  Shifts in the Architecture of the Nationwide Health Information Network, Journal of the American Medical Informatics Association, Online First, January 21, 2012.

Abstract: In the midst of a US $30 billion USD investment in the Nationwide Health Information Network (NwHIN) and electronic health records systems, a significant change in the architecture of the NwHIN is taking place. Prior to 2010, the focus of information exchange in the NwHIN was the Regional Health Information Organization (RHIO). Since 2010, the Office of the National Coordinator (ONC) has been sponsoring policies that promote an internet-like architecture that encourages point to-point information exchange and private health information exchange networks. The net effect of these activities is to undercut the limited business model for RHIOs, decreasing the likelihood of their success, while making the NwHIN dependent on nascent technologies for community level functions such as record locator services. These changes may impact the health of patients and communities. Independent, scientifically focused debate is needed on the wisdom of ONC's proposed changes in its strategy for the NwHIN.

This article contributes to the growing policy literature on ONC strategies to promote health information exchange through infrastructures of the Nationwide Health Information Network.  While the authors  call for an “independent, scientifically focused debate … on the wisdom of ONC’s proposed changes in its strategy…”  there is little pertinent reference to research in organizational science or institutional economics to support such a debate.  The authors focus on Regional Health Information Organizations  (RHIOs) defined most often as not-for-profit organizations providing universal services for health information exchange in the interest of the communities they serve and more generally, the public good.  The market-driven strategy for the NHIN assumes that RHIOs will develop in local communities and will interconnect to scale up to a nationwide infrastructure.  Unfortunately this politically expedient assumption is inconsistent with the nature of competitive markets.  Furthermore, since the benefits of health information exchange accrue to the broader health care system rather than entities investing in RHIO membership, no business model has been identified to support RHIOs with sustainable revenue streams independent of federal and state funding. 

Organizational research to date has documented the substantial federal and state investments in health information exchange – including variously defined RHIOs, health information exchange organizations (HIEs), and State Designated Entities (SDEs).  The authors of the present article cite publications by Adler-Milstein et al. to suggest the progress of policies for RHIOs and health information exchange.  Attentive reading of these articles reveals that the numbers of “active organizations” identified is subject to interpretation.  Based on Adler-Milstein et al. (2008),  Lenert et al. report « more than 100 active organizations » while 45 of these were in the planning stages and only 20 qualified to be included in the study sample.  In 2011 Lenert et al. contend that the number of RHIOs had grown to more than 200 based on research by Adler-Milstein et al. (2011).  In fact this number included SDEs as well as RHIOs, and analysis revealed that none of these organizations met criteria for a « comprehensive RHIO » in light of meaningful use requirements.

These misleading citations reflect an apparent bias in favor of RHIOs – entities threatened (according to Lenert et al.) by a shift to promote private networks and an Internet-like model for building the NHIN. A similar lack of careful reference to scientific research in organization science appears in other recent articles in health care policy published in Health Affairs (See Williams et al., 2012,  From the Office of the National Coordinator:  The Strategy for Advancing the Exchange of Health Information, Health Affairs, 23 ( 3)  (2012) pp. 527-536.)   as well as JAMIA (See 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. From the perspective of this reviewer, there is no evidence base to conclude that policies for RHIOs (or other entities dedicated to health information exchange) are undermined by new initiatives, particularly where public investment to sustain RHIOs is unavailable.  RHIOs also pose very significant challenges with the addition of new organizational layers for governance and accountability to numerous stakeholders.

Lenert et al.  correctly suggest that the successful development of the NHIN requires both nonpartisan consensus  in public policy and independent scientific research to evaluate the effectiveness of alternative models.  Unfortunately the highly charged political environment of an election year in the U.S. will favor neither.

REFERENCES
Adler-Milstein, J., McAfee, A.P., Bates, D.W., et al., The State of regional health information organizations: current activities and financing. Health Aff (Millwood) 2008;27:w60–9.(REF. 22)
Adler-Milstein, J., Bates, D.W., Jha, A.K.,  A survey of health information exchange organizations in the United States: implications for meaningful use. Ann Intern Med 2011;154:66–71.(REF. 23)
 
(Reviewers of this manuscript for JAMIA should have corrected errors in the reading of studies cited.)

From the Office of the National Coordinator: The Strategy for Advancing the Exchange of Health Information, HEALTH AFFAIRS, Vol. 23, No. 3 (2012) pp. 527-536.

From the Office of the National Coordinator:  The Strategy for Advancing the Exchange of Health Information, HEALTH AFFAIRS, Vol. 23, No. 3  (2012) pp. 527-536.

This important article from the Office of the National Coordinator for Health Information Technology (ONC) identifies the critical role of health information exchange in the achievement and measurement of meaningful use of electronic health records.  Infrastructures for health information exchange are prerequisite to measurement of the criteria for meaningful use, but the development of such a system on a national scale in the U.S. remains a work in progress, threatened by the vicissitudes of a fragmented political process. The authors of the article describe three types of exchange: 1- “sending and receiving health information to support coordinated care,” 2- “finding patient health information for unplanned care,” and 3-“enabling patients to aggregate their own health information.”  Each of these modes of exchange poses unique technical challenges, but all are necessary for meaningful communication of health information across the Nationwide Health Information Network (NHIN).

At issue is the design and implementation of the required supporting infrastructure.  As recognized by the authors, strategies for development of  Regional Health Information Organizations (RHIOs) have provided initial public funding under the assumption that such organizations could develop sustainable business models and eventually interconnect for health information exchange on a national scale.  Unfortunately sustainable business models for RHIOs have not emerged, while many other apparently more viable initiatives are being developed by large hospital systems, electronic health records vendors, and newly formed ACOs.  Amidst this organizational diversity, problems remain in promoting  interoperability and information exchange among competing systems.

Some recent research suggests that RHIOs and other publicly funded health information exchange organizations may be inadequate to satisfy the criteria set forth for meaningful use. (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 )

Adler-Milstein et al. 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 meaningful use criteria.   This finding portends the possible failure of the market driven “network of networks” approach to development of the NHIN. (See further comment on my blog at http://eresearchcollaboratory.blogspot.ca/2011/11/health-information-exchange.html )

In the present article, only one reference supports the statement that “the number of active private health information exchange entities tripled from 52 in 2009 to 161 in 2010.” (page 528) No definition of the “active private health information exchange entity” is offered, nor is there any description of the research methodology used to identify such entities. (The proprietary consulting report is available at https://www.klasresearch.com/store/ReportDetail.aspx?ProductID=642  )

The paucity of scientific organizational research to orient the design and governance of health information exchange and the NHIN is surprising in a community so engaged in promoting evidence-based medical practice and policy-making. Perhaps the interdisciplinary nature of the research enterprise (well beyond the comfort zone of most medical researchers dedicated to standards of the randomized controlled trial) obscures thinking in terms of large social systems.  Systems thinking, however, defines the broader context of the individual EHR and health information exchange. Without attention to the “big picture”, faulty assumptions within diverse disciplinary silos will guide ONC policies described in this article to costly and certain failure. 

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/members-download/finish/4-open/35-hie-survey-report-2010-key-findings.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/reports.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

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.