Electronic Health Records: Where Do We Go From Here?

Web Sites

Center for Advanced Information Management
Promotes collaboration between Columbia faculty and industry to develop and commercialize new technologies.

Eclipsys
Company that designs and implements advanced health care IT systems.

Meaningful Use Workgroup
Group that makes recommendations to the Health Information Technology Policy Committee on the meaningful use of electronic health records.

New York State Department of Health
Established within the Department of Health (DOH) in 2007, the Office of Health Information Technology Transformation (OHITT) is charged with coordinating health IT programs and policies across the public and private health care sectors. The state also has a page describing its use of ARRA funding.

Primary Care Information Project
Organizations and projects at the New York State Department of Public Health involved in HER adoption.

Partners Healthcare™
Non-profit, integrated health system founded by Brigham and Women's Hospital and Massachusetts General Hospital.

Philips Research
Company that develops new technologies in a wide range of areas, including healthcare.

Recovery.gov
Government website that provides information on the distribution of ARRA funds.

Transforming Healthcare Through Secondary Use of Electronic Health Data
Consulting firm publication on the secondary use of EHRs.

Publications

Seeing the Big Picture of HIT and EHR Design

Hripcsak G, Kaushal R, Johnson KB, et al. 2007. The United Hospital Fund meeting on evaluating health information exchange. J. Biomed. Inform. 40: S3-10. Full Text

Koll BS, Straub TA, Jalon HS, et al. 2008. The CLABs collaborative: a regionwide effort to improve the quality of care in hospitals. Jt. Comm. J. Qual. Patient Saf. 34: 713-723.

Jenkins M, Levy J, Cohen E, et al. 2009. Integration of self-management tools in personal and provider e-health records. Stud. Health Technol. Inform. 146: 179-184.

Singer J, Lou JQ, Malecki J, et al. 2006. Outcome assessment of preventive medicine guidelines compliance in providers using a computerized reminder system. AMIA Annu. Symp. Proc. 1100. Full Text

Hripcsak G, Soulakis ND, Li L, et al. 2009. Syndromic surveillance using ambulatory electronic health records. J. Am. Med. Inform. Assoc. 16: 354-361. Full Text

Shea S, Hripcsak G. 2010. Accelerating the use of electronic health records in physician practices. N. Engl. J. Med. 362: 192-195. Full Text

Wang X, Hripcsak G, Markatou M, et al. 2009. Active computerized pharmacovigilance using natural language processing, statistics, and electronic health records: a feasibility study. J. Am. Med. Inform. Assoc. 16: 328-337. Full Text

Sinha A, Hripcsak G, Markatou M. 2009. Large datasets in biomedicine: a discussion of salient analytic issues. J. Am. Med. Inform. Assoc. 16: 759-767.

Wang X, Hripcsak G, Friedman C. 2009. Characterizing environmental and phenotypic associations using information theory and electronic health records. BMC Bioinformatics. 10 Suppl 9: S13. Full Text

Rabadan R, Calman N, Hripcsak G. 2009. Next generation syndromic surveillance: molecular epidemiology, electronic health records and the pandemic Influenza A (H1N1) virus. PLoS Curr. Influenza RRN1012. Full Text

Ball MJ, Silva JS, Bierstock S, et al. 2008. Failure to provide clinicians useful IT systems: opportunities to leapfrog current technologies. Methods Inf. Med. 47: 4-7.

EHRs as a part of clinical decision making and institutional workflows

Aronsky D, Haug PJ, Lagor C, et al. 2005. Accuracy of administrative data for identifying patients with pneumonia. Am. J. Med. Qual. 20: 319-328.

Lagor C, Elliott CG, Stoddard GJ, et al. 2005. Weaknesses in the classification criteria for antithrombotic-related major bleeding events. Thromb. Haemost. 94: 997-1003.

van Zon K, Lord WP, Lagor C, et al. 2008. Stroke navigator—a clinical decision support system for acute stroke. AMIA Annu. Symp. Proc. 1227.

Cao H, Markatou M, Melton GB, et al. 2005. Mining a clinical data warehouse to discover disease-finding associations using co-occurrence statistics. AMIA Annu. Symp. Proc. 106-110. Full Text

Cao H, Melton GB, Markatou M, et al. 2008. Use abstracted patient-specific features to assist an information-theoretic measurement to assess similarity between medical cases. J. Biomed. Inform. 41: 882-888. Full Text

Han M, Song X, DeHaan J, et al. 2006. CPOE/EHR-driven healthcare workflow generation and scheduling. AMIA Annu. Symp. Proc. 940. Full Text

Dykes PC, Carroll DL, Benoit A, et al. 2007. A randomized trial of standardized nursing patient assessment using wireless devices. AMIA Annu. Symp. Proc. 206-210. Full Text

Dykes PC, Carroll DL, Hurley AC, et al. 2009. Why do patients in acute care hospitals fall? Can falls be prevented? J. Nurs. Adm. 39: 299-304.

Dykes PC, Hurley A, Cashen M, et al. 2007. Development and psychometric evaluation of the Impact of Health Information Technology (I-HIT) scale. J. Am. Med. Inform. Assoc. 14: 507-514. Full Text

Dykes PC, Hurley AC, Brown S, et al. 2009. Validation of the Impact of Health Information Technology (I-HIT) Scale: an international collaborative. Stud. Health Technol. Inform. 146: 618-622.

Dykes PC, Kim HE, Goldsmith DM, et al. 2009. The adequacy of ICNP version 1.0 as a representational model for electronic nursing assessment documentation. J. Am. Med. Inform. Assoc. 16: 238-246. Full Text

Goldsmith D, Zuyev L, Benoit A, et al. 2009. Usability testing of a Falls Prevention Tool Kit for an inpatient acute care setting. Stud Health Technol Inform. 146: 801-802.

Hurley AC, Dykes PC, Carroll DL, et al. 2009. Fall TIP: validation of icons to communicate fall risk status and tailored interventions to prevent patient falls. Stud. Health Technol. Inform. 146: 455-459.

Kim H, Dykes P, Goldsmith D, et al. 2009. A strategy for preparing contents for a computerized documentation system. Stud Health Technol Inform. 146: 752-753.

Clancy TR. 2008. Fractals: Nature's formula for managing hospital performance metrics. J. Nurs. Adm. 38: 510-513.

Clancy TR. 2009. In search of elegance: making the complex simple. J. Nurs. Adm. 39: 507-510.

Clancy TR. 2009. Self-organization versus self-management: two sides of the same coin? J. Nurs. Adm. 39: 106-109.

Clancy TR. 2010. Diamonds in the rough: positive deviance and complexity. J. Nurs. Adm. 40: 53-56.

Clancy TR, Effken JA, Pesut D. 2008. Applications of complex systems theory in nursing education, research, and practice. Nurs. Outlook 56: 248-256 e3.

Clancy TR, White-Delaney C, Mako M. 2009. Improving the academic programming process in a school of nursing using computational modeling and simulation. Stud. Health Technol. Inform. 146: 587-592.

Promises and potential pitfalls of EHR adoption

Chen ES, Hripcsak G, Patel VL, et al. 2003. Automated identification of shortcuts to patient data for a wireless handheld clinical information system. AMIA Annu. Symp. Proc. 809. Full Text

Forman B, Sengupta S, Lorenzi V. 2007. An informatics course on applied clinical information systems. AMIA Annu. Symp. Proc. 957.

Hripcsak G, Sengupta S, Wilcox A, et al. 2007. Emergency department access to a longitudinal medical record. J. Am. Med. Inform. Assoc. 14: 235-238.

Sengupta S, Calman NS, Hripcsak G. 2008. A model for expanded public health reporting in the context of HIPAA. J. Am. Med. Inform. Assoc. 15: 569-574. Full Text

Guirguis HS, Rogoff EG. 2004. Strategies and impacts of new drug introduction: hemophilia treatment. J. Health Care Finance 31: 1-12.

Rogoff EG, Guirguis HS, Lipton RA, et al. 2002. The upward spiral of drug costs: a time series analysis of drugs used in the treatment of hemophilia. Thromb. Haemost. 88: 545-553.

Kim D, Labkoff S, Holliday SH. 2008. Opportunities for electronic health record data to support business functions in the pharmaceutical industry—a case study from Pfizer, Inc. J. Am. Med. Inform. Assoc. 15: 581-584. Full Text

Labkoff SE, Yasnoff WA. 2007. A framework for systematic evaluation of health information infrastructure progress in communities. J. Biomed. Inform. 40: 100-105.

Safran C, Bloomrosen M, Hammond WE, et al. 2007. Toward a national framework for the secondary use of health data: an American Medical Informatics Association White Paper. J. Am. Med. Inform. Assoc. 14: 1-9. Full Text

Buck MD, Atreja A, Brunker CP, et al. 2009. Potentially inappropriate medication prescribing in outpatient practices: prevalence and patient characteristics based on electronic health records. Am. J. Geriatr. Pharmacother. 7: 84-92.

Currie L, Sheehan B, Graham PL, 3rd, et al. 2009. Sociotechnical analysis of a neonatal ICU. Stud. Health Technol. Inform. 146: 258-262.

Dorr DA, Wilcox AB, Brunker CP, et al. 2008. The effect of technology-supported, multidisease care management on the mortality and hospitalization of seniors. J. Am. Geriatr. Soc. 56: 2195-2202.

Kern LM, Dhopeshwarkar R, Barron Y, et al. 2009. Measuring the effects of health information technology on quality of care: a novel set of proposed metrics for electronic quality reporting. Jt. Comm. J. Qual. Patient Saf. 35: 359-369.

Van Vleck TT, Wilcox A, Stetson PD, et al. 2008. Content and structure of clinical problem lists: a corpus analysis. AMIA Annu. Symp. Proc. 753-757. Full Text

Wilcox A, Bowes WA, Thornton SN, et al. 2008. Physician use of outpatient electronic health records to improve care. AMIA Annu. Symp. Proc. 809-813. Full Text

Sponsors

Silver

This event is funded in part by the Life Technologies™ Foundation.

Academy Friends

The Center for Advanced Information Management is a NYSTAR-sponsored Center for Advanced Technology at Columbia University.

• •  The New York Presbyterian Hospital
• •  NLP International Corporation
• •  Surgical Information Systems

The great debate over health care reform is clearly one of the most contentious topics of our time. Yet despite vast differences of opinion on how and whether health care reform should be implemented, there seems to be one area in which most stakeholders (employers, consumers, insurance companies, medical providers, and others) have reached an agreement: the current pace of cost increases must be slowed down substantially if our overall health care system is to remain viable.

One way to contain health care costs is to take control of the immense stream of health care data that is produced each year. Tracking data on patient care and resulting outcomes can identify areas where care is not delivered optimally, avoiding expenditures that are wasteful and unnecessary. This data is already captured in some ways, but with millions of patients and hundreds of thousands of health care providers involved, it is clear that a much broader, more uniformly implemented system of health care information technology (HIT) is needed.

A central component of HIT is the electronic health record (EHR), a computerized version of the familiar paper chart kept for each patient. Collecting these records in an electronic form would allow patient care data to be centralized, standardized, and mined for information, improving care both for the individual patient and for the population as a whole. As one of the largest health care payers, in the form of Medicare and Medicaid, the federal government is a strong proponent of EHRs. The American Recovery and Reinvestment Act of 2009 (ARRA) provided millions of dollars in stimulus funds for health care institutions to invest in designing and implementing HIT systems that will collect, manage and facilitate sharing of EHRs between institutions.

Efforts to define the best way to implement health information technology in the U.S. are underway.

On February 5, 2010, a cross section of researchers in this field convened to discuss progress toward these highly labor intensive and far reaching goals. The Center for Advanced Information Management (CAIM), a New York State Center for Advanced Technology located at Columbia University, and the New York Academy of Sciences presented a conference entitled "Electronic Health Records: Where Do We Go From Here?" The conference brought together representatives from industry, academia, and government organizations to discuss their work towards the common goal of implementing EHRs in a broad, cost effective, and meaningful way.

In the first of three sessions, researchers with experience working in the trenches of HIT implementation provided insights into the institutional and technological components needed to support EHR adoption and use. Rachel Block of the New York State Department of Health described the coordinated strategy underway in that state, providing an overview of the building blocks, such as policies, regulations, standards, definitions, and financial incentives needed to support widespread, effective adoption by the stakeholders involved. George Hripcsak of Columbia University's CAIM discussed the work of the federal HIT Policy Committee and its Meaningful Use Workgroup, which is charged with defining the standards to which HIT must be implemented in order for participating institutions to receive ARRA stimulus funds. Jesse Singer of The New York City Department of Health and Mental Hygiene described his work with the Primary Care Information Project, a program working to promote the implementation of EHRs among small primary care providers in underserved communities in New York City. On a much broader scale, Jay Srini of the University of Pittsburgh Medical Center presented her work towards developing HIT standards that will allow systems from different institutions to mesh and share information, while at the same time serving stakeholders with a multitude of different needs and perspectives.

The second session included two representatives of the HIT industry, followed by a panel discussion that included participants with different institutional viewpoints on how HIT can be designed to meet the needs of individual health care providers and their institutions. Charles Lagor of Philips Research North America described software programs developed by his company that are designed to use EHRs to support clinical decision making by physicians. These systems are intended to make care for complex conditions such as stroke more consistent and effective by reminding physicians of previous outcomes and relevant guidelines. John P. Gomez of Eclipsys Corporation analyzed the factors that play into the design of an HIT system, including the increasingly important role of the internet and social networking, the need for data sharing, and the possibilities for collective problem solving.

The ensuing panel discussion, which was moderated by Ken Ong of Catholic Health Services of Long Island, brought together an HIT consultant, a HIT manager working within a health care institution, and a computational expert to describe work on HIT design and implementation. Hui Cao of Deloitte Consulting described the process by which health care institutions select vendors to design and build HIT systems, with an eye towards developing systems that are integrated across the institution while meeting the needs of each individual component effectively. Patricia Dykes of Partners Healthcare System described her work on designing electronic versions of current workflows with the intent of improving efficiency and ensuring that the ability to meet future needs is built into the design of new systems. Thomas Clancy of the University of Minnesota explained how computational modeling and simulations can be used to predict the effects of implementing electronic workflows, providing a tool to help institutions better understand their own needs and to help visualize the effects of implementing a given system.

Speakers in the third and final session provided insight into some specific topics related to the adoption of EHRs, including security considerations, economic aspects, secondary uses of EHR data for pharmaceutical research, and the use of mobile devices in the HIT environment. Soumitra Sengupta of Columbia University/New York Presbyterian Hospital detailed security and privacy issues from perspective of an Information Security Officer, describing potential security risks of EHRs and the measures that institutions will need to have in place to conform with government regulations and disclosure rules. Edward Rogoff of Baruch College/CUNY provided a comprehensive analysis of the potential economic costs and savings associated with adoption of EHRs. Steven Labkoff of Pfizer Pharmaceuticals described how data extracted from EHRs might assist pharmaceutical companies in pursuing important comparative effectiveness and safety studies outside the framework of clinical trials, capturing the vast amount of clinical data that could be generated once a drug is in widespread use. Finally, Adam Wilcox of Columbia University described his work on the most effective uses of mobile devices in HIT, which is intended to find out what tasks these devices are most useful for and how they can fit effectively into electronic workflows to best support the clinical decision-making needs of health care professionals.

At the beginning of the day, George Hripcsak described how HIT was once considered a "crazy idea" that was not worthy of the attention of an academic researcher. While there is still a lot of work to do, there has been an immense turn around for this field, particularly since the advent of financial incentives such as those provided by ARRA. With the efforts of these individuals and many others like them, it appears that at least one aspect of health care reform will come to fruition, although the timeline, and ultimate price tag, for these efforts are still uncertain.

Speakers:
Rachel Block, New York State Department of Health
George Hripcsak, Columbia University's CAIM
Jesse Singer, New York City Department of Health and Mental Hygiene, Primary Care Information Project
Jay Srini, University of Pittsburgh Medical Center

Highlights

• Widespread adoption of EHRs will require the development of significant regulatory infrastructure as well as buy-in from stakeholders across multiple institutions.
• EHRs can improve efficiency and quality of care among small medical "mom and pop" medical practices in economically disadvantaged areas.
• Meaningful use of EHRs includes data collection and dissemination, data use to improve quality of care, data sharing between institutions and public agencies, and demonstrated improvements in population health outcomes.
• EHRs should be designed for portability and flexibility to support sharing between institutions to facilitate their use for both clinical and nonclinical purposes and to provide individuals with access to their own health records.

New York State is an acknowledged leader in the adoption of health information technology having awarded more than $150 million in state grant funds since 2004, more than all other states combined. As the Deputy Commissioner of the Office of Health Information Technology Transformation, Rachel Block is closely involved with the distribution of these, in addition to state funds, as grants intended to reconfigure New York's health care systems. Block noted that the implementation of technology is not the ultimate goal of these projects. The overarching goal is in fact "transformation," in the form of comprehensive systems changes leading to more effective and efficient delivery of health care. She outlined many of the building blocks that need to be put into place to achieve these changes, which include everything from appropriate state policies and regulations, to identification of clinical needs and uses for technology, to buy-in by participants at every level of the system. She emphasized the importance of collaboration and consensus. New York's broadly coordinated strategy is one that is likely to be emulated by other states as they progress towards their own implementations of HIT systems.

As another representative of New York State, Jesse Singer provided a more ground level view of one of the many projects encompassed by the state's HIT effort. Singer is the Director of Quality Informatics for the Primary Care Information Project, a state program that is working to implement HIT in disadvantaged communities in New York City, as a means of improving care and overall population health in these areas. He and his colleagues are designing, and helping to implement, prevention-oriented EHRs that will improve health care provider workflows and patient self-management, and allow for detailed measures of quality of care in primary care practices. Many of the patients in these areas are uninsured, so this program will also provide an important source of data on such individuals. The program focuses on small physician-led practices, which provide the majority of primary care in the U.S. but are the least likely to implement EHRs because of the time and expense involved. These small practices will benefit from the efficiency of HIT, and those that show improvements in quality of care will eventually receive financial incentives as well. Echoing Block, Singer emphasized that HIT implementation is not the real goal of this project; rather, it is intended to have an positive impact on public health.

The ultimate goal of the Primary Care Information Project is to improve care and health outcomes.

Because of the time and expense involved in implementation, incentives are an important part of the effort to promote EHR adoption at all levels of the health care system. As part of ARRA, the federal government established incentives that are tied to "meaningful use" of HIT by health care institutions. George Hripcsak is a member of the Meaningful Use Workgroup within the HIT Policy Committee of the Office of the National Coordinator of Health Information Technology. This workgroup is charged with defining the meaningful use of EHRs. It has identified three stages of meaningful use that can be achieved by health care institutions. Stage 1, which is the most fully defined to date, addresses five key areas: quality, safety, and efficiency; engaging patients and families; improving care coordination; improving population and public health; and ensuring privacy and security protections. Stage 2, which remains to be fully defined, is to begin using this data to improve clinical decision making, disease management and patient self-management, and to set up systems for sharing data with other institutions, including public health agencies. Institutions that reach stage 3 will be those that can show improvements in quality of care measures, population health, and other parameters that will indicate a successfully implemented program. As an institution reaches each stage, it will be rewarded with a new set of ARRA stimulus funds. Hripcsak and fellow committee members are working to define the rules that will govern whether an institution has reached each of these stages. He noted that they are seeking a balance between leniency and strictness, in an attempt to define rules that will encourage institutions to make improvements without becoming an undue burden. "The people at CMS [the Centers for Medicare and Medicaid Services] want to do what's right for the nation," he said, and are expending considerable effort to ensure that the program is fair and workable for all types of institutions.

Jay Srini is an expert on emerging technologies who spoke of her work on EHR design, particularly as it relates to creating data records that can be shared and utilized by a wide range of participants in the health care system, including institutions such as hospitals, community-based medical practices, and individual patients who may wish to access their personal health records. She envisions a national HIT framework in which data can be shared by multiple users, not just for clinical purposes but in order to provide for more efficient billing and reimbursement as well. Patient data records will need to be "liquid and portable," she said, if they are be used in the wide range of settings found within the health care system. In addition, EHRs will need to be designed to meet future needs that are already in development, such as remote patient monitoring and telemedicine. Srini said that she sees an opportunity for HIT designers to be creative, since standards are still in a state of flux. EHRs that are designed to meet the widest range of needs will have the most value to all users, facilitating more widespread adoption.

Speakers:
Charles Lagor, Philips Research North America
John P. Gomez, Eclipsys Corporation
Ken Ong, Catholic Health Services of Long Island
Hui Cao, Deloitte Consulting
Patricia Dykes, Partners Healthcare System
Thomas Clancy, University of Minnesota

Highlights

• Patient treatment and outcomes data gathered from EHRs can be used to improve clinical decision making for complex conditions in time-dependent situations.
• The incorporation of internet-based tools, including the ready availability of EHRs in "the cloud" and the use of social networking sites, has the potential to improve medical practice.
• EHRs should be designed to fit into workflows that are optimized for individual use as well as to fit into departmental and institutional "mega-workflows" that are well-coordinated and work together efficiently.

As more than one speaker emphasized in the first session, HIT implementation is not an end in itself but rather a means towards the end of improving quality of care and promoting more efficient use of scarce resources. Two speakers from the HIT industry provided insights into the potential uses of EHRs to promote clinical decision making that is faster, conforms better to the expert guidelines intended to ensure high quality care, and takes advantage of group problem solving resources offered by social networking and other internet innovations.

Charles Lagor presented details on several systems that Philips Research has designed that use EHR data to support clinical decision making at the bedside. These systems are designed to solve specific clinical challenges. For example, despite the plethora of monitoring systems and alarms in the typical intensive care unit, physicians and other staff often do not realize that a patient's condition has worsened soon enough to head off serious consequences. Lagor described a system that uses data from previous patients to recognize complex patterns of changes in vital signs that indicate that a problem is imminent. Even if all vital signs are within normal ranges, certain combinations of changes will lead to an alarm that prompts early attention by the medical staff, leading to better outcomes for patients. In another example, he described a system that provides rapid decision making support for stroke, where the need for a quick choice of treatment often precludes the consultation of lengthy and complex expert guidelines. The Philips system would compare the present patient's condition to data on similar cases and make recommendations based on both previous outcomes and relevant guidelines. These systems are designed to utilize the data encoded in EHRs in a way that promotes better patient care and thus better health outcomes.

On a broader level, the EHR has the potential to be the "backbone of the health care ecosystem," according to John P. Gomez, who provided an overview of the potential impact of EHRs on medical practice in general. Gomez emphasized that freeing medical records from the physical location dictated by the use of a paper chart has the potential to make them available anywhere, anytime, on demand by the user. Placing EHRs in "the cloud" will remove barriers that currently prevent access to patient health care records by caregivers and patients alike, a particularly useful trait in emergency situations, where faster access to patient records means faster decision making. In addition, improved data sharing among individual practitioners as well as institutions will allow for increased collective problem solving, facilitated by the growing use of social networking and other internet innovations. Gomez noted that there are both positive and negative aspects to these developments. On the plus side, physicians will be able to work with data that is more accurate because it does not depend on patients' memories, and this more accurate data can be accessed in a more timely fashion. On the negative side, there is the potential for data to become corrupted, to overload clinical decision makers, to increase liability exposure, and to reduce control of clinical decisions by the individual practitioner. These are issues that will need to be addressed in the coming paradigm shift likely to occur as EHRs are more widely adopted and become available over the internet.

Placing EHRs in "the cloud" will remove barriers that currently prevent access to patient health care records.

The ensuing panel discussion brought together individuals with a range of perspectives on HIT and EHR design. HIT consultant Hui Cao discussed the factors that institutions must consider when designing a new HIT system, including issues of integration into existing workflows, coordination across departments with different individual needs, and planning for future needs. She emphasized the need to look at the institution as a whole, designing "mega-workflows" in which EHRs will be used for different purposes. HIT manager Patricia Dykes described ongoing work in her institution to better define both present and future workflows so that needed information can be built into EHR design. Dykes highlighted usability as a critically important feature of HIT design, and described her institution's efforts to include end-users in the development process. Computational expert Thomas Clancy described his research, which takes a different tack towards developing efficient workflows. He has designed computer models that can simulate the potential effects of a specific workflow design, allow institutions to see ahead of time the implications of specific designs, and to better understand their needs. These simulations can test multiple scenarios, allowing for workflow optimization that is built into the design of the HIT system.

Speakers:
Soumitra Sengupta, Columbia University / New York Presbyterian Hospital
Edward Rogoff, Baruch College/CUNY
Steven Labkoff, Pfizer Pharmaceuticals
Adam Wilcox, Columbia University

Highlights

• The use of EHRs creates a need for HIT systems that can track, manage, and safeguard disclosures of patient data.
• EHRs are likely to reduce wasteful spending on ineffective treatments and unnecessary or duplicated tests, but the overall cost-effectiveness of EHR adoption may ultimately be difficult to measure due to the high cost of adoption and because there may be unforeseen circumstances.
• EHRs could be highly valuable as a source of data on the effectiveness and safety of pharmaceuticals that have been used in large populations under real-life conditions.
• The widespread adoption of mobile devices makes it very likely that these devices will play an important role in future HIT designs, particularly for point-of-care applications.

The third and final session focused on practical aspects of EHRs, with speakers considering security matters associated with electronic data, whether EHRs will be cost-effective, the use of EHR data as an important tool in pharmaceutical research, and how the rapidly growing adoption of handheld devices, such as the iPhone, could be integrated in HIT systems.

Security expert Soumitra Sengupta started the session with a trip through the challenges posed by electronic health data, which include the need to protect patients' rights, the potential for malicious or inadvertent security violations, and the need to follow complex new regulations on disclosure set forth by ARRA. Patient records can be used within the institution to access data on treatment and payments, for example, or they may be shared with other institutions, in which case this access is defined as disclosure. Patients must authorize the disclosure of their data, except when it is requested by certain outside institutions such as law enforcement, courts, or government agencies working towards public health goals. Patients are also entitled to an accounting of any disclosures of their data within a certain period of time if they ask for one. Institutions also have a responsibility to ensure that patient data is not released to unauthorized parties, whether by accident or because of malicious intent. Sengupta described the system design consequences of these requirements, which include the need for components that identify users, create an audit trail that shows who accessed what data and when, and capture reasons for access that can be conveyed to patients when they are notified that their data has been disclosed.

What will be the economic impact of EHRs? Edward Rogoff considered this question from a variety of standpoints. The current estimate is that an approximately $19 billion investment will lead to $40 to $100 billion a year in savings for the U.S. health care system. This estimate is based on the potential savings generated by the efficiency of centralized patient records and the reduction of wasteful and unnecessary treatments and duplicated tests. Fewer physical records also means less staff is needed to pull those records. But the costs are considerable as well, for such things as new computers, staff to operate the computers, and training for physicians and others. It is also feared that physicians will order more tests to reduce their potential liability if patient records become more accessible to outside parties. Rogoff estimated that the true cost of implementing EHRs will be more on the order of $200 billion, but that it is likely to happen anyway, in the next 5 to 10 years. Will this conversion ultimately be cost-effective? In his estimation the adoption of EHRs will lead to "huge savings," but he cautioned that the savings may be hard to measure definitively.

One area in which EHRs could potentially lead to huge savings, as well as considerable reductions in morbidity and mortality, is the use of EHR data to collect post-marketing information on the effectiveness and safety of pharmaceuticals. Steven Labkoff described the dilemma of pharmaceutical companies, who are increasingly pushed to provide "real life" data on the effectiveness of their products outside of clinical trials, but who own only a fraction of the data generated once a drug has reached market. Labkoff suggested that such companies could partner with the academic and government institutions that own most of this data to build consortia in which post-marketing data would be shared, with appropriate controls, standards, and regulations. The companies themselves could also form cooperative organizations that would pool resources to develop HIT systems that would be able to use this and other data effectively. Such efforts could greatly reduce drug development costs by allowing the mechanisms and side effects of currently used drug classes to be understood more thoroughly.

Pharmaceutical companies need to collect information about drug effects after the product is launched.

The final speaker, Adam Wilcox, reminded listeners that the future of HIT will include not just full-fledged computers but also handheld computing devices. Smartphones and the like are no longer niche devices: it is estimated that at least 80% of physicians will use one by 2012. However, these devices have characteristics that are likely to make them very useful for some tasks and not as useful for others. They are not able to display large amounts of data, and typing on them is awkward, so it is unlikely that they will ever be useful for data entry tasks. Their greatest advantage is that they are highly portable and they are always near at hand, which means they would be most useful for tasks that need to be done away from a desk, whether at the patient's bedside or outside of the institution. Such tasks could include displaying checklists or standing orders for patient care, alerting physicians to medication errors or potential drug–drug interactions, and notifying physicians of laboratory test results. Away from the bedside and the patient, these devices could also provide follow-up reminders and patient status updates in a timely fashion. These devices are increasingly integrated into IT systems and it is likely that health-related IT will be no exception.

Will EHRs fulfill the promise of improving quality of care, including care delivered to disadvantaged populations?

Will systems designers and hospital administrators achieve their dream of integrated, effective HIT systems that improve workflows and reduce costs?

How much will the adoption of EHRs ultimately cost?

Will pharmaceutical companies be able to develop cooperative methods of sharing post-marketing drug data and will this data improve drug safety?

How will handheld devices be integrated into HIT systems?

Will ARRA funding provide the push that is needed to promote widespread adoption of EHRs?

What new, unforeseen opportunities with EHRs provide in the future for improving healthcare delivery and effectiveness in the U.S.?