DATA QUALITY MANAGEMENT How widespread is the problem of poor data quality in the U.S. healthcare system? According to a recent audit of Medicare-based reimbursement, the Office of Inspector General (OIG) of the Department of Health and Human Services (HHS) found a 5 percent increase in erroneous payments to physicians attributed to databased flaws or lack of data documentation compared to the previous year. Inadequate or inappropriate data documentation also was the top reason for erroneous payments to physicians (Gibbs-Brown, 2000). More troubling is the fact that incorrect coding accounted for almost 15 percent of the total improper payment made by Medicare; more than 90 percent of those payments were made to physicians. Although the reimbursement aspects of incorrect coding are apparent, systematically identifying the causes and remedies remains a problem for medical systems developers (Gibbs-Brown, 2000). Data warehouse managers must be able to facilitate accuracy, determine an application’s purpose, and focus on the rationale for collecting certain data elements (Mendelsohn & Kraemer, 1998). Information managers are further charged with ensuring accuracy, requiring appropriate education and training, and communicating timely and appropriate data definitions to those who collect data. Data warehouse managers are charged with ensuring that appropriate edits are in place to guarantee accuracy. Adherence to approved coding principles that generate coded data of the highest quality remains important, but that is just a part of the overall data quality picture (Gorla & Krehbiel, 1999). Ensuring the accuracy of coded data is a responsibility shared between information systems professionals and clinicians. Most significantly, the accreditation standards of the Joint Commission on Accreditation of Healthcare Organizations (JCAHO) as well as the Medicare Conditions of Participation also require that final diagnoses and procedures are recorded in the health record and authenticated by healthcare practitioners. Congress has mandated a series of regulations, under the Health Insurance Portability and Accountability Act of 1996 (HIPAA), intended to reduce the administrative costs and burden associated with health care by standardizing data and facilitating electronic transmission of many administrative and financial transactions. Because of the belief that the electronic movement of health information creates patient privacy and security concerns, Congress also directed the Secretary of HHS to develop standards to protect the privacy and security of individually identifiable health information (P.L. 104-191, 1996). Such requirements for standardized information management practices suggest that, while the implementation and impact of such mandates remain uncertain, the goal of HIPPA is clear: organizations need to devise some type of formal data management strategy to ensure the standardized collection of information within their structural bounds (HHS, 2000).

Disease identification in public health monitoring routinely employs analyte detection systems capable of discriminating mixtures of analytes, toxins, cells and/or bacteria in medical and/or environmental solutions. The development of smart sensors capable of discriminating such compounds has become increasingly important for clinical, environmental, and health applications. While some sensors have been fashioned for single analyte detection, methods and systems that facilitate rapid screening of multiple clinical components are needed, serving as triggers for potential epidemics or more specific confirmatory testing. In public health applications, there is like need for immediate collection of geocoded data tagged by disease identification characteristics, with corresponding alerting capabilities. In this technology review we propose one promising model for using a combination of emerging systems-based technologies in multi sensor cartridges, integrated with GPS-enabled, alert-capable mobile phone devices.

Recent US health reform initiatives now require extensive consumer involvement through healthcare purchasing exchanges. The opportunity exists to monitor and plan for peak service needs in such an environment. The use of computational systems and methods for health services planning and utilization review have traditionally been employed in post-facto or financial analysis settings. In this technology review we propose one innovative model and attribute-based method that collects and analyzes indicators of consumers or patients within a defined network, accepts sensor data about individuals, and presents a set of health care service options at least partially based on the acceptance of indications of member attributes as well as sensor data about network actors.

Developing standards and technology models that will facilitate e-prescribing is one of the key action items in the federal government's plan to build a nationwide electronic health information infrastructure in the United States. E-prescribing has the potential to drive change in the healthcare industry, but the unavailability of diagnostic testing and detection equipment outside of clinical settings makes expanded collection and use of information problematic. Most solutions are provider-based, and limited by organization-wide startup & maintenance costs, and risk-averse data distribution policies. Objective, consumer-provided standardized data can facilitate the use of distributed information networks in polypharmacy detection and avoidance. In this technology review we propose here one promising model for polypharmacy management and integrated diagnostics through the use of breath-based, multiple array sensing and data capture.

The use of computerized, digital video as a means for interactive data capture has been suggested as an alternative to direct observation of behavior. The appeal of observational measures is that they are presumed to be less vulnerable to potential biases from informants, such as parents or teachers, and permit more individualized assessment that may be lost with the use of rating scales. As a potential tool for long-term, automated observation and analysis. In this technology review we propose one promising model for the integration of computerized primitives recognition and annotated video patterns as an approach to large-scale autism diagnosis and research.

Monitoring of blood glucose levels is important to persons with diabetes or pre-diabetic, abnormal glucose indications. Such individuals must determine when insulin is needed to reduce glucose levels in their bodies, or when additional glucose must be administered to raise levels. A conventional technique used by many diabetics to personally monitor their glucose level includes the periodic drawing of blood, the application of blood to a test strip, and determination of blood glucose level using calorimetric, electrochemical, or photometric detection. This technique does not permit continuous or automatic monitoring of levels in the body, but typically must be performed manually, and on a periodic basis. Unfortunately, checking consistency varies widely among individuals, where wide variation of high or low levels of glucose or other analytes may have detrimental effects. The ongoing capture of data through continuous and/or automatic in vivo monitoring of analyte levels, and its inclusion with a user-friendly computer interface, is now possible using a subcutaneous implanted sensor. Such devices are small and comfortable when used, allowing a wide range of life activities. In this technology review we propose one promising model using a combination of emerging, systems-based technologies in non-invasive analyte monitoring, as integrated within household-based health monitoring using home appliances.

Goal Two of the US ONCHIT Plan focuses on enabling the use of electronic health information for critical health improvement activities that promote the health of targeted communities, and the US population as a whole. Because of the focus on communities and populations, the activities under this second goal differ fundamentally from those of the first goal, which focus on the care of individuals. Proposed here is a model for health information management in such population-based environments, which allows selective access and use of information, and maintains transportability while ensuring security and confidentiality.

Electronic Medical Record (EMR) and Electronic Health Record (EHR) adoption continues to lag across the US. Cost, inconsistent formats, and concerns about control of patient information are among the most common reasons for non-adoption in physician practice settings. The emergence of wearable and implanted mobile technologies, employed in distributed environments, promises a fundamentally different information infrastructure, which could serve to minimize existing adoption resistance. Proposed here is one technology model for overcoming adoption inconsistency and high organization-specific implementation costs, using seamless, patient controlled data collection. While the conceptual applications employed in this technology set are provided by way of illustration, they may also serve as a transformative model for emerging EMR/EHR requirements.

Recent ONCHIT mandates call for increased individual health data collection efforts as well as heightened security measures. To date most healthcare organizations have been reluctant to exchange information, citing confidentiality concerns and unshared costs incurred by specific organizations. Implantable monitoring and treatment devices are rapidly emerging as data collection interface tools in response to such mandates. Proposed here is a translational, device-independent consumer-based solution, which focuses on information controlled by specific patients, and functions within a distributed (organization neutral) environment. While the conceptual applications employed in this technology set are provided by way of illustration, they may also serve as a transformative model for emerging EMR/EHR requirements.

Recent initiatives by the US ONCHIT highlight the need for electronic population health data collection relating to aspects of Public Health Case (PH Case) reporting and Adverse Event (AE) reporting. Proposed solutions to date have been primarily provider-based, limited by organization-wide startup & maintenance costs, and hampered by risk-averse data distribution policies. Little attention has been given to consumer-focused, distributed data collection models, where objective, consumer-provided standardized data can be used prior to case identification to facilitate earlier use of extensible and distributed information networks in biosurveillance. We propose here one promising model for pre-case biosurveillance management, employing the use of breath-based, multiple array sensing and data capture. The conceptual applications employed in this technology set are provided by way of illustration, and may also serve as a transformative model for emerging EMR/EHR requirements.

Advancements in the procurement, classification and storage of genetic material have yielded opportunities for increased sharing and collaboration across research networks. Such complex arrangements, however, pose unique problems for managers. As source material is drawn from disparate and often incompatible entities, standardised policies and practices are needed well before data is collected, transmitted and utilised by network collaborators. Presented here are some of the key intellectual property (IP) challenges facing managers of biomedical research, including examples of model agreements used in an innovative online tissue biomarker sharing network.

The unregulated manufacture of prescription drugs, sold under a known generic or brand name, poses an increasing safety risk to unsuspecting healthcare consumers around the world. Those who receive a counterfeit medication may be at risk for a number of dangerous health consequences. Patients may experience unexpected side effects, allergic reactions, or worsening of their medical condition. Many counterfeits do not contain any active ingredient and instead use inert substances which provide no medical treatment benefit. Counterfeit medications may also contain incorrect ingredients, improper dosages of the correct ingredients, or may contain hazardous ingredients. As a collaborative countermeasure model, we summarise here joint anti-counterfeiting efforts through intellectual property rights (IPR) enforcement by the US and China. Such cooperative work serves as a model for enforcement and illustrates how intellectual property (IP) law is being applied across borders to combat unregulated prescription drug manufacture and sale.

The Bayh-Dole Act of 1980 was a US initiative designed to maximise returns on university-based, federally supported research and development by encouraging transfer of technology to commercial applications. Through collaborative partnerships, especially with small business concerns, for the first time inventors were permitted to reap the rewards of their discoveries or innovations through commercial licensing of their publicly-financed work product. Questions remain, however, related to the effectiveness of the Act in meeting its objectives.

The WTO Agreement on Trade-Related Aspects of Intellectual Property Rights (TRIPs Agreement) has historically been interpreted as recognising the difficulties associated with patent protection for pharmaceuticals needed to protect public health and welfare. Where a sovereign state's law or policy allows for use of the subject matter of a patent without the authorisation of the rights holder, such use may only be permitted if, prior to such use, the proposed user has made efforts to obtain authorisation from the rights holder on reasonable commercial terms. Many countries, however, are beginning to challenge such 'negotiated' use, opting instead to institute unilateral patent use policies. Summarised here is a compulsory license policy for patented pharmaceuticals recently enacted by the Government of Thailand, supported by their ten point argument which could serve as a template for less restrictive licensing policies needed by developing countries around the world.

Expanding the role of distributed health care, recent ONCHIT initiatives highlight the utilization of remote and home-based monitoring as a model for health care that is accessible, comprehensive and coordinated, delivered in the context of family and community. Extensible information technology in this context can be used to collect and store expanded data about patients and their environment, especially in assisted living and group home environments. Proposed here is a distributed model for meeting related ONC mandates, which include emerging patient data collection opportunities, especially within nursing homes, assisted living, and other group home arrangements. The conceptual applications employed in this technology set are provided by way of illustration, and may also serve as a transformative model for emerging EMR/EHR requirements.

The objective of this study was to determine the extent of decline in level of access and quality of services reported by healthcare consumers during a media campaign to limit recovery for damages incurred through medical malpractice. Serving as a natural experiment, this campaign involved a widely publicized statewide "malpractice crisis," promoted as causing mass exodus of medical providers from the state. The (reported) resulting reduction in services, especially for the most underserved areas and populations, though unproven, had been touted as justification for amending the state constitution. Patient survey responses collected during the crisis indicated relatively high levels of satisfaction with access and quality of care during the publicized crisis (and alleged provider exodus). Similar organized malpractice crises examined from previous years suggest that policymakers should demonstrate caution when responding to a perceived crisis, especially when economic benefit for a particular interest group is at stake. Further, a lack of ethics in media through inaccurate reporting and sensationalism may lead to a seductive invitation to like ethical lapses by medical professionals in their attempts to shape policy through artificial crises creation.

The burgeoning backlog of patent applications at the US Patent and Trademark Office (USPTO) has created an urgent need for Office reform. Review of related application reference material, or prior art, is a necessary but time consuming step in the patent process. As a pilot project, the USPTO initiated the use of social networking software as a means to facilitate discussion amongst groups of volunteer review experts. The peer-to-patent pilot project allows experts outside the patent office to upload prior art references, participate in discussion forums, rate other user submissions and add research references to pending applications. This may help examiners to better focus their review on the submission of prior art that has the highest relevance to an application and thus streamline the overall application process.

Proposed here as a technology transfer practice, we highlight the adoption of a fair profit/for profit model as a means for sustainable biomedical commercialisation. This model de-emphasises short-term, profit maximisation (full-profit) strategies and highlights the tech transfer advantages of niche markets and localised manufacturing, coupled with proven best practices of medical specialties and focused on global market needs. This model recognises, but is not driven by, local regulatory barriers and minimises or eliminates the development and marketing costs traditionally associated with new medical products in industrialised nations. Such a model can be sustainable and profitable, when adopted as part of a global, controlled-growth commercialisation strategy.

The availability of quality medical information is a central issue in the management of healthcare technology. Within this function there are emerging 'domains of uncertainty' or areas of healthcare wherein either diagnosis and/or treatment are somewhat disputed within a given community of practice. This study sought to demonstrate an integrated approach to evaluating the quality of medical information available on the internet for the little-understood domain of sudden infant death syndrome (SIDS). Information was derived from web sites and search engines returned as the highest priority results from search engine queries. Results were examined from a management perspective, with implications addressed for the growing field of web-based healthcare.

The growing popularity of the internet has made it easier and faster to find health information on rare and poorly understood disease topics. Much of this information is valuable, though the internet also allows the rapid and widespread distribution of false and misleading information, especially through peer-based networks. Providers frequently advise that it is important for health consumers to carefully consider the source of lay information and to discuss the clinical information they find with their health care provider. Beyond clinical indicators and standards, however, there exist few evaluative frameworks for assessing health information, especially within peer-to-peer networks. Employing a grounded theoretical approach, analysis of online, domain-specific interaction examined in this study demonstrates the decision making influences of "virtual support groups" and the related emergence of "cybertherapy" as a peer-based tool for healthcare consumers.