Advancing personalized health care through health information technology: an update from the American Health Information Community's Personalized Health Care Workgroup

Community-Based Family Health History Education: The Role of State Health Agencies in Engaging Medically Underserved Populations in Understanding Genomics and Risk of Chronic Disease

Although family health history (FHH) collection has been recognized as an influential method for assessing a person's risk of chronic disease, studies have shown that people who are low-income, from racial and ethnic minorities, and poorly educated are less likely to collect their FHH or share it with a medical professional. Programs to raise public awareness about the importance of FHH have conventionally targeted patients in primary care clinics or in the general community, but few efforts have been made to coordinate educational efforts across settings. This paper describes a project by the Connecticut Department of Public Health's Genomics Office to disseminate training materials about FHH as broadly as possible, by engaging partners in multiple settings: a local health department, a community health center, and two advocacy organizations that serve minority and immigrant populations. We used a mixed methods program evaluation to examine the efficacy of the FHH program and to assess barriers in integrating it into the groups' regular programming. Our findings highlight how a state health department can promote FHH education among underserved communities.

Person-centred health care: a critical assessment of current and emerging research approaches

RATIONALE, AIMS AND OBJECTIVES

Person-centred health care is prominent in international health care reforms. A shift to understanding and improving personal care at the point of delivery has generated debates about the nature of the person-centred research agenda. This paper purviews research paradigms that influence current person-centred research approaches and traditions that influence knowledge foundations in the field. It presents a synthesis of the emergent approaches and methodologies and highlights gaps between static academic research and the increasing accessibility of evaluation, informatics and big data from health information systems.

FINDINGS

Paradigms in health services research range from theoretical to atheoretical, including positivist, interpretive, postmodern and pragmatic. Interpretivist (subjective) and positivist (objectivist) paradigms have been historically polarized. Yet, integrative and pragmatic approaches have emerged. Nevertheless, there is a tendency to reductionism, and to reduce personal experiences to metrics in the positivist paradigm. Integrating personalized information into clinical systems is increasingly driven by the pervasive health information technology, which raises many issues about the asymmetry and uncertainty in the flow of information to support personal health journeys. The flux and uncertainty of knowledge between and within paradigmatic or pragmatic approaches highlights the uncertainty and the 'unorder and disorder' in what is known and what it means. Transdisciplinary, complex adaptive systems theory with multi-ontology sense making provides an overarching framework for making sense of the complex dynamics in research progress.

CONCLUSION

A major challenge to current research paradigms is focus on the individualizing of care and enhancing experiences of persons in health settings. There is an urgent need for person-centred research to address this complex process. A transdisciplinary and complex systems approach provides a sense-making framework.

A validation of an intelligent decision-making support system for the nutrition diagnosis of bariatric surgery patients

BACKGROUND

Bariatric surgery is an important method for treatment of morbid obesity. It is known that significant nutritional deficiencies might occur after surgery, such as, calorie-protein malnutrition, iron deficiency anemia, and lack of vitamin B12, thiamine, and folic acid.

OBJECTIVE

The objective of our study was to validate a computerized intelligent decision support system that suggests nutritional diagnoses of patients submitted to bariatric surgery.

METHODS

There were fifteen clinical cases that were developed and sent to three dietitians in order to evaluate and define a nutritional diagnosis. After this step, the cases were sent to four bariatric surgery expert dietitians who were aiming to collaborate on a gold standard. The nutritional diagnosis was to be defined individually, and any disagreements were solved through a consensus. The final result was used as the gold standard. Bayesian networks were used to implement the system, and database training was done with Shell Netica. For the system validation, a similar answer rate was calculated, as well as the specificity and sensibility. Receiver operating characteristic (ROC) curves were projected to each nutritional diagnosis.

RESULTS

Among the four experts, the rate of similar answers found was 80% (48/60) to 93% (56/60), depending on the nutritional diagnosis. The rate of similar answers of the system, compared to the gold standard, was 100% (60/60). The system sensibility and specificity were 95.0%. The ROC curves projection showed that the system was able to represent the expert knowledge (gold standard), and to help them in their daily tasks.

CONCLUSIONS

The system that was developed was validated to be used by health care professionals for decision-making support in their nutritional diagnosis of patients submitted to bariatric surgery.

Allocation of work activities in a comprehensive cancer genetics program

Hereditary cancer programs that provide risk assessment, genetic education, and counseling services are becoming increasingly common. This article describes one possible approach to providing comprehensive cancer genetics care by a credentialed genetics advanced practice nurse. In addition to the description of the program, data from a recently conducted time study are included to provide insight into work allocation of different program components. Findings from the study indicate that about 41% of the time is spent in direct clinical time with patients and families, including initial visit counseling, phone consultation, and follow-up visits. The rest of the time is spent in other indirect care activities, including previsit activities, risk calculation, clinical trials enrollment, correspondence, teaching, and administrative duties. For those developing or expanding a cancer genetics program, considering all activities that will occur and the time allocated to each activity is important.

eHealth: extending, enhancing, and evolving health care

eHealth holds the promise of revolutionizing health care by improving its efficiency; extending and enhancing its reach; energizing and engaging its practitioners and their patients; and in the process, democratizing, decentralizing, and even partially demystifying the practice of medicine. In emerging and developing countries, the use of eHealth and smart health-care planning has the potential to expand access to necessary treatments and prevention services that can serve as underpinnings of rapid economic development. In developed countries, the application of eHealth promises to restructure the business model of health-care delivery, while at the same time improving and personalizing the quality of care received. This article reviews the past, present, and future of eHealth in an effort to illuminate the potential of its impact.

Security and privacy in electronic health records: a systematic literature review

OBJECTIVE

To report the results of a systematic literature review concerning the security and privacy of electronic health record (EHR) systems.

DATA SOURCES

Original articles written in English found in MEDLINE, ACM Digital Library, Wiley InterScience, IEEE Digital Library, Science@Direct, MetaPress, ERIC, CINAHL and Trip Database.

STUDY SELECTION

Only those articles dealing with the security and privacy of EHR systems.

DATA EXTRACTION

The extraction of 775 articles using a predefined search string, the outcome of which was reviewed by three authors and checked by a fourth.

RESULTS

A total of 49 articles were selected, of which 26 used standards or regulations related to the privacy and security of EHR data. The most widely used regulations are the Health Insurance Portability and Accountability Act (HIPAA) and the European Data Protection Directive 95/46/EC. We found 23 articles that used symmetric key and/or asymmetric key schemes and 13 articles that employed the pseudo anonymity technique in EHR systems. A total of 11 articles propose the use of a digital signature scheme based on PKI (Public Key Infrastructure) and 13 articles propose a login/password (seven of them combined with a digital certificate or PIN) for authentication. The preferred access control model appears to be Role-Based Access Control (RBAC), since it is used in 27 studies. Ten of these studies discuss who should define the EHR systems' roles. Eleven studies discuss who should provide access to EHR data: patients or health entities. Sixteen of the articles reviewed indicate that it is necessary to override defined access policies in the case of an emergency. In 25 articles an audit-log of the system is produced. Only four studies mention that system users and/or health staff should be trained in security and privacy.

CONCLUSIONS

Recent years have witnessed the design of standards and the promulgation of directives concerning security and privacy in EHR systems. However, more work should be done to adopt these regulations and to deploy secure EHR systems.

Genetic counselors' current use of personal health records-based family histories in genetic clinics and considerations for their future adoption

Given the widespread adoption of electronic medical records and recent emergence of electronic family history tools, we examined genetic counselors' perspectives on the emerging technology of the personal health record (PHR)-based family history tool that links to an electronic medical record (EMR). Two-hundred thirty-three genetic counselors responded to an on-line survey eliciting current use of electronic family history (EFH) tools and familiarity with PHR-based family history tools. Additionally, after being shown a series of screen shots of a newly developed PHR-based family history tool based on the U.S. Surgeon General's My Family Health Portrait (United States Department of Health and Human Services 2009), participants were surveyed about the perceived usefulness, ease of use, and impact on current workflow that this kind of tool would have in their practices. Eighty-three percent reported that their institution has an EMR, yet only 35 % have a dedicated space for family history. Eighty-two percent reported that less than 5 % of their patients have a PHR, and only 16 % have worked with patients who have a PHR. Seventy-two percent or more agreed that a PHR-based family history tool would facilitate communication, increase accuracy of information, ensure consistency in recording information, increase focus on actual counseling, reduce repetitive questions, improve efficiency, and increase the legibility and clarity. Our findings suggest that participants were familiar with existing EFH tools, but that the majority did not use them in practice. Genetic counselors' adoption of such tools is limited due to non-existence of this kind of technology or inability to integrate it into their clinics. They are also strongly in favor of adopting a PHR-based family history tool in genetics clinics, but have practical concerns that must be addressed before the tool can be implemented.

How the electronic health record will change the future of health care

Genetic testing is expected to play a critical role in patient care in the near future. Advances in genomic research have the potential to impact medicine in very tangible and direct ways, from carrier screening to disease diagnosis and prognosis to targeted treatments and personalized medicine. However, numerous barriers to widespread adoption of genetic testing continue to exist, and health information technology will be a critical means of addressing these challenges. Electronic health records (EHRs) are a digital replacement for the traditional paper-based patient chart designed to improve the quality of patient care. EHRs have become increasingly essential to managing the wealth of existing clinical information that now includes genetic information extracted from the patient genome. The EHR is capable of changing health care in the future by transforming the way physicians use genomic information in the practice of medicine.

Clinical decision support for genetically guided personalized medicine: a systematic review

OBJECTIVE

To review the literature on clinical decision support (CDS) for genetically guided personalized medicine (GPM).

MATERIALS AND METHODS

MEDLINE and Embase were searched from 1990 to 2011. The manuscripts included were summarized, and notable themes and trends were identified.

RESULTS

Following a screening of 3416 articles, 38 primary research articles were identified. Focal areas of research included family history-driven CDS, cancer management, and pharmacogenomics. Nine randomized controlled trials of CDS interventions for GPM were identified, seven of which reported positive results. The majority of manuscripts were published on or after 2007, with increased recent focus on genotype-driven CDS and the integration of CDS within primary clinical information systems.

DISCUSSION

Substantial research has been conducted to date on the use of CDS to enable GPM. In a previous analysis of CDS intervention trials, the automatic provision of CDS as a part of routine clinical workflow had been identified as being critical for CDS effectiveness. There was some indication that CDS for GPM could potentially be effective without the CDS being provided automatically, but we did not find conclusive evidence to support this hypothesis.

CONCLUSION

To maximize the clinical benefits arising from ongoing discoveries in genetics and genomics, additional research and development is recommended for identifying how best to leverage CDS to bridge the gap between the promise and realization of GPM.

Genetic testing behavior and reporting patterns in electronic medical records for physicians trained in a primary care specialty or subspecialty

OBJECTIVE

To characterize important patterns of genetic testing behavior and reporting in modern electronic medical records (EMRs) at the institutional level.

MATERIALS AND METHODS

Retrospective observational study using EMR data of all 10,715 patients who received genetic testing by physicians trained in a primary care specialty or subspecialty at an academic medical center between January 1, 2008 and December 31, 2010.

RESULTS

Patients had a mean±SD age of 38.3±15.8 years (median 36.1, IQR 30.0-43.8). The proportion of female subjects in the study population was larger than in the general patient population (77.2% vs 55.0%, p<0.001) and they were younger than the male subjects in the study (36.5±13.2 vs 44.6±21.2 years, p<0.001). Approximately 1.1% of all patients received genetic testing. There were 942 physicians who ordered a total of 15,320 genetic tests. By volume, commonly tested genes involved mutations for cystic fibrosis (36.7%), prothrombin (13.7%), Tay-Sachs disease (6.7%), hereditary hemochromatosis (4.4%), and chronic myelogenous leukemia (4.1%). EMRs stored reports as free text with categorical descriptions of mutations and an average length of 269.4±153.2 words (median 242, IQR 146-401).

CONCLUSIONS

In this study, genetic tests were often ordered by a diverse group of physicians for women of childbearing age being evaluated for diseases that may affect potential offspring. EMRs currently serve primarily as a storage warehouse for textual reports that could potentially be transformed into meaningful structured data for next-generation clinical decision support. Further studies are needed to address the design, development, and implementation of EMRs capable of managing the critical genetic health information challenges of the future.

An Empirical Examination of Antecedents and Consequences of IT Governance in US Hospitals

Intense pressure to control costs and improve patient care quality is driving hospitals to increasingly look to information technology (IT) for solutions. As IT investment and IT capability have grown in hospitals, the need to manage IT resources aggressively has also increased. The rise in complexity and sophistication of the IT capability in hospitals has also increased the importance of IT governance in these organizations. Yet, there is limited empirical data about the antecedents and consequences of IT governance. We draw upon extant literature related to power and politics and capability management to propose, operationalize, and empirically examine a nomological model that explains and predicts IT governance and its ensuing impact on risk management and IT contribution to hospital performance. We empirically tests our hypotheses based on survey data gathered from 164 CIOs of US hospitals. The results have implications for hospitals’ readiness and predisposition for IT governance, as their structural and relational mechanisms can affect IT governance and, indirectly, IT value creation. A contribution of this study is that it is one of the first to empirically examine antecedents to IT governance and its impact on IT performance in a high-velocity environment that is riddled with technological turbulence.

Unleashing the power of human genetic variation knowledge: New Zealand stakeholder perspectives

PURPOSE

This study aimed to characterize the challenges in using genetic information in health care and to identify opportunities for improvement.

METHODS

Taking a grounded theory approach, semistructured interviews were conducted with 48 participants to collect multiple stakeholder perspectives on genetic services in New Zealand.

RESULTS

Three themes emerged from the data: (1) four service delivery models were identified in operation, including both those expected models involving genetic counselors and variations that do not route through the formal genetic service program; (2) multiple barriers to sharing and using genetic information were perceived, including technological, organizational, institutional, legal, ethical, and social issues; and (3) impediments to wider use of genetic testing technology, including variable understanding of genetic test utilities among clinicians and the limited capacity of clinical genetic services. Targeting these problems, information technologies and knowledge management tools have the potential to support key tasks in genetic services delivery, improve knowledge processes, and enhance knowledge networks.

CONCLUSION

Because of the effect of issues in genetic information and knowledge management, the potential of human genetic variation knowledge to enhance health care delivery has been put on a "leash."

Identifiability in biobanks: models, measures, and mitigation strategies

The collection and sharing of person-specific biospecimens has raised significant questions regarding privacy. In particular, the question of identifiability, or the degree to which materials stored in biobanks can be linked to the name of the individuals from which they were derived, is under scrutiny. The goal of this paper is to review the extent to which biospecimens and affiliated data can be designated as identifiable. To achieve this goal, we summarize recent research in identifiability assessment for DNA sequence data, as well as associated demographic and clinical data, shared via biobanks. We demonstrate the variability of the degree of risk, the factors that contribute to this variation, and potential ways to mitigate and manage such risk. Finally, we discuss the policy implications of these findings, particularly as they pertain to biobank security and access policies. We situate our review in the context of real data sharing scenarios and biorepositories.

Uncertainty and complexity in personal health records

New technologies in medicine have led to an explosion in the number of parameters that must be considered when diagnosing and treating a patient. Because of this high volume of data it is not possible for the human decision maker to take all information into account in arriving at a decision. Automated methods are needed to effectively evaluate electronic information in many formats and provide summaries to the medical professional. The task is complicated by the complexity of the data and the potential uncertainty of some of the results. In this article complexity and uncertainty in medical data are discussed in terms of both representation and types of analysis. Methods that can address multiple complex data types are illustrated and examples are provided for specific medical problems. These methods are particularly important for automated trend analysis in the personal health record as small errors can be propagated through the complex system resulting in incorrect diagnosis and treatment.

Emerging landscape of genomics in the Electronic Health Record for personalized medicine

The Information Technology (IT) roadmap for personalized medicine requires Electronic Health Records (EHRs), extension of Healthcare IT (HIT) standards, and understanding of how genetics/genomics should be integrated into the clinical applications. For reduced overall costs and development times, these three initiatives should run in parallel. EHRs must contain structured data and infrastructure that enables quality analysis, Clinical Decision Support (CDS) and messaging within the healthcare information network. Fortunately, as a result of sustained financial commitment to nongenetic-based healthcare, the industry has HIT data standards and understanding of EHR functionality that improves patient safety and outcomes while reducing overall healthcare costs. However, the HIT standards and EHR functional requirements, needed for personalized medicine, are only beginning to support simple genetic tests and need significant extension. In addition, our understanding of the clinical implications of genomic data is evolving and translation of new discovery into clinical care remains a challenge. Therefore, priority areas include CDS, educational resources, and knowledgebases for the EHR, clinical and research data warehouses, messaging frameworks, and continued review of healthcare policies and regulations supporting personalized medicine. Where core infrastructure remains to be developed and implemented, funding is needed for pilot projects, data standards, policy, and stakeholder collaboration.

Enhancing the quality and efficiency of newborn screening programs through the use of health information technology

A variety of efforts are underway at national, state, regional, and local levels to enhance the performance of programs for early detection of inherited diseases and conditions of newborn infants. Newborn screening programs serve a vital purpose in identifying nonsymptomatic clinical conditions and enabling early intervention strategies that lessen morbidity and mortality. Currently, the programs of most intense focus are early hearing detection and intervention, using physiological techniques for audiology screening and use of newborn dried blood spots for detection of metabolites or proteins representing inherited disorders. One of the primary challenges to effective newborn screening programs to date has been the inability to provide information in a timely and easily accessible way to a variety of users. Other challenging communication issues being faced include the complexity introduced by the diversity of conditions for which testing is conducted and laboratory methods being used by each state's screening programs, lack of an electronic information infrastructure to facilitate information exchange, and variation in policies that enable access to information while protecting patient privacy and confidentiality. In this study, we address steps being taken to understand these challenges, outline progress made to date to overcome them, and provide examples of how electronic health information exchange will enhance the utility of newborn screening. It is likely that future advances in science and technology will bring many more opportunities to prevent and preempt disabilities among children through early detection programs. To take their advantage, effective communication strategies are needed among the public health, primary care practice, referral/specialty service, and consumer advocacy communities to provide continuity of information required for medical decision-making throughout prenatal, newborn, and early childhood periods of patient care.

Integrating genomic-based clinical decision support into electronic health records

There is a growing consensus that the first and most necessary step to improving the efficiency, cost–effectiveness and quality of healthcare systems can be achieved through the implementation of interoperable patient-centric electronic health record (EHR) systems across hospitals and clinics. Targeted therapeutics (including screening, prevention and disease management) through EHR-based clinical decision support delivery may drive both the acceptance and adoption of EHR systems by providing personalized information at the point-of-care. The realization of targeted therapeutics will depend on the resolution of current political, ethical, socioeconomical and technical challenges surrounding EHR implementation efforts. There is a growing need for broad-based consensus initiatives to foster an essential level of standardization for EHRs. The timeliness of these issues is underlined by the rapid emergence of private sector efforts in this potentially lucrative field, from direct-to-consumer testing to Google-, or Microsoft-owned personal health data. This review discusses the potential value for adopting healthcare technology, with a focus on personalized medicine, and highlights the challenges that remain to achieve this.

Improving newborn screening laboratory test ordering and result reporting using health information exchange

Capture, coding and communication of newborn screening (NBS) information represent a challenge for public health laboratories, health departments, hospitals, and ambulatory care practices. An increasing number of conditions targeted for screening and the complexity of interpretation contribute to a growing need for integrated information-management strategies. This makes NBS an important test of tools and architecture for electronic health information exchange (HIE) in this convergence of individual patient care and population health activities. For this reason, the American Health Information Community undertook three tasks described in this paper. First, a newborn screening use case was established to facilitate standards harmonization for common terminology and interoperability specifications guiding HIE. Second, newborn screening coding and terminology were developed for integration into electronic HIE activities. Finally, clarification of privacy, security, and clinical laboratory regulatory requirements governing information exchange was provided, serving as a framework to establish pathways for improving screening program timeliness, effectiveness, and efficiency of quality patient care services.

Information management to enable personalized medicine: stakeholder roles in building clinical decision support

BACKGROUND

Advances in technology and the scientific understanding of disease processes are presenting new opportunities to improve health through individualized approaches to patient management referred to as personalized medicine. Future health care strategies that deploy genomic technologies and molecular therapies will bring opportunities to prevent, predict, and pre-empt disease processes but will be dependent on knowledge management capabilities for health care providers that are not currently available. A key cornerstone to the potential application of this knowledge will be effective use of electronic health records. In particular, appropriate clinical use of genomic test results and molecularly-targeted therapies present important challenges in patient management that can be effectively addressed using electronic clinical decision support technologies.

DISCUSSION

Approaches to shaping future health information needs for personalized medicine were undertaken by a work group of the American Health Information Community. A needs assessment for clinical decision support in electronic health record systems to support personalized medical practices was conducted to guide health future development activities. Further, a suggested action plan was developed for government, researchers and research institutions, developers of electronic information tools (including clinical guidelines, and quality measures), and standards development organizations to meet the needs for personalized approaches to medical practice. In this article, we focus these activities on stakeholder organizations as an operational framework to help identify and coordinate needs and opportunities for clinical decision support tools to enable personalized medicine.

SUMMARY

This perspective addresses conceptual approaches that can be undertaken to develop and apply clinical decision support in electronic health record systems to achieve personalized medical care. In addition, to represent meaningful benefits to personalized decision-making, a comparison of current and future applications of clinical decision support to enable individualized medical treatment plans is presented. If clinical decision support tools are to impact outcomes in a clear and positive manner, their development and deployment must therefore consider the needs of the providers, including specific practice needs, information workflow, and practice environment.

Are electronic health records ready for genomic medicine?

PURPOSE

The goal of this project was to assess genetic/genomic content in electronic health records.

METHODS

Semistructured interviews were conducted with key informants. Questions addressed documentation, organization, display, decision support and security of family history and genetic test information, and challenges and opportunities relating to integrating genetic/genomics content in electronic health records.

RESULTS

There were 56 participants: 10 electronic health record specialists, 18 primary care clinicians, 16 medical geneticists, and 12 genetic counselors. Few clinicians felt their electronic record met their current genetic/genomic medicine needs. Barriers to integration were mostly related to problems with family history data collection, documentation, and organization. Lack of demand for genetics content and privacy concerns were also mentioned as challenges. Data elements and functionality requirements that clinicians see include: pedigree drawing; clinical decision support for familial risk assessment and genetic testing indications; a patient portal for patient-entered data; and standards for data elements, terminology, structure, interoperability, and clinical decision support rules. Although most said that there is little impact of genetics/genomics on electronic records today, many stated genetics/genomics would be a driver of content in the next 5-10 years.

CONCLUSIONS

Electronic health records have the potential to enable clinical integration of genetic/genomic medicine and improve delivery of personalized health care; however, structured and standardized data elements and functionality requirements are needed.

Revitalizing primary health care and family medicine/primary care in India--disruptive innovation?

CONTEXT

India has rudimentary and fragmented primary health care (PHC) and family medicine systems, yet it also has the policy expectation that PHC should meet the needs of extremely large populations with slums and difficult to reach groups, rapid social and epidemiological transition from developing to developed nation profiles. Historically, the system has lacked impetus to achieve PHC.

OBJECTIVE

To provide an overview of PHC approaches and the current state of PHC and family medicine in India in order to assess the opportunities for their revitalization.

METHODS

A narrative review of the published and grey literature on PHC, family medicine, Web2.0 and health informatics key papers and policy documents, pertinent to India.

OUTCOMES

A conceptual framework and recommendations for policy makers and practitioner audiences.

FINDINGS

PHC is constructed through systems of local providers who address individual, family and local community basic health needs with strong community participation. Successful PHC is a pre-eminent strategy for India to address the determinants of health and the almost chaotic of massive social transition in its institutions and health care sector. There is a lack of an articulated comprehensive framework for the publicly stated goals of improving health and implementing PHC. Also, there exists a very limited education and organization of a medical and PHC workforce who are trained and resourced to address individual, family and local community health and who have become increasingly specialized. However, emerging technology, Health2.0 and user generated health care informatics, which are largely conducted through mobile phones, are co-evolving patient-driven health systems, and potentially enhance PHC and family medicine workforce development.

CONCLUSIONS

In order to improve health outcomes in an equitable manner in India, there is a pressing need for a framework for implementing PHC. The co-emergence of information technologies accessible to the mass population and user-driven health care provide a potential catalyst or innovation for this transition.

Diagnostic models based on personalized analysis of trends (PAT)

Many changes have taken place in medicine over the last century. In the first-half of the 20th century physicians were faced with the challenge of making diagnoses with too little information, often resorting to exploratory surgery to confirm the presence or absence of a condition. Due to rapid technological advances during the second-half of the 20th century, and continuing to this day, the position of the physician has now shifted from an information-poor environment to an environment with too much information, often exceeding the limits of human decision-making capabilities. To take full advantage of all available information, a new approach based on refined automated decision support methods is needed to assist the physician in the decision-making process. Medical decision support systems need to evolve from stand-alone systems to cooperative systems in which the physician becomes the decision maker, but relies on the decision support system to sift through information to determine relevant trends. In this paper, a decision support system that combines a number of methodologies for trend analysis is described, along with examples in cardiology. The methods have also been used in applications in neurology as well as cancer diagnosis and prognosis.

Translational bioinformatics and healthcare informatics: computational and ethical challenges

Exponentially growing biological and bioinformatics data sets present a challenge and an opportunity for researchers to contribute to the understanding of the genetic basis of phenotypes. Due to breakthroughs in microarray technology, it is possible to simultaneously monitor the expressions of thousands of genes, and it is imperative that researchers have access to the clinical data to understand the genetics and proteomics of the diseased tissue. This technology could be a landmark in personalized medicine, which will provide storage for clinical and genetic data in electronic health records (EHRs). In this paper, we explore the computational and ethical challenges that emanate from the intersection of bioinformatics and healthcare informatics research. We describe the current situation of the EHR and its capabilities to store clinical and genetic data and then discuss the Genetic Information Nondiscrimination Act. Finally, we posit that the synergy obtained from the collaborative efforts between the genomics, clinical, and healthcare disciplines has potential to enhance and promote faster and more advanced breakthroughs in healthcare.

Multidimensional medical decision making

A century ago the physician had too little information on which to determine accurate diagnoses. Due to the rapid progression of technology in the Twentieth Century and the beginning of the Twenty-First Century, this situation changed significantly. Now the physician is faced with multi-parameter analyses that include sophisticated imaging, advanced cardiovascular studies, extensive laboratory tests, and genetic information, all of which impact diagnosis, treatment, and prognosis. New informatics tools are needed to assist, not replace, the physician in the decision process. Decision analysis tools must be flexible to accommodate new methods of diagnosis as well as advances in information technology. In this article, basic structures are defined that can form the basis of such a system.

Public health genomics: translating obesity genomics research into population health benefits

We examine how a public health genomics framework can be used to move genomic discoveries into clinical and public health practice for obesity prevention and treatment. There are four phases of translational research: T1: discovery to candidate health application; T2: health application to evidence-based practice guidelines; T3: practice guidelines to health practice; and T4: practice to population health impact. Types of multidisciplinary research and knowledge synthesis needed for each phase, as well as the importance of developing and disseminating evidence-based guidelines, are discussed. Because obesity genomics research is mostly in the discovery phase or in the very early phases of translation (T1), the authors present this framework to illustrate the range of translation activities needed to move genomic discoveries in obesity to actual applications that reduce the burden of obesity at the population level.