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Examining the public health delivery system in the United States, it can be concluded that its complexity does not hinder the considerable amount of its activities. Both governmental and non-governmental health agencies are active participants of the processes of public health delivery at different levels. For the purpose of improvement of the quality of health care services, a lot of activities are carried out inside of the agencies as well as through inter-organizational and intergovernmental partnerships. By uniting the efforts, resources, and skills of multiple agencies, these partnerships address complex health issues which cannot be addressed by a single institution. This paper will compare and contrast the purposes, goals, structural models, and other characteristics of three public-private partnerships, namely the Biomarkers Consortium, the Genetic Association Information Network, and the Alzheimers Disease Initiative.
The Biomarkers Consortium
The Biomarkers Consortium is a public-private partnership which was launched for the purpose of advancing the molecular understanding of diseases and treatment outcomes by defining the biomarkers which can be used for addressing the medical needs (Zerhouni, Sanders, & von Eschenbach, 2007, p. 250). For example, blood pressure and total cholesterol are currently accepted as biomarkers as biomarkers of risks of cardiovascular diseases. The purpose of this partnership is to unite efforts of the state and private health care agencies for discovering new biomarkers and accelerating the processes of detection, diagnosis and treatment of a wide range of diseases, and cancer is only one of them. The purpose of this partnership is to catalyze the development of medicines by conducting research on pre-competitive stages and making the results of studies available to a wide audience (Wagner et al., 2010, p. 240).
The Biomarkers Consortium is managed by the Foundation for the National Institutes of Health (FNIH). The rest of the founding partners include the National Institutes of Health (NIH), Food and Drug Administration (FDA), and Pharmaceutical Research and Manufacturers of America (PhRMA). The structure of the Biomarkers Consortium is aimed at providing a fair and collaborative platform on pre-competitive stages of research. Serious consideration is given to the policies for intellectual property, on the one hand, and principles of data sharing and data access, on the other hand.
The Biomarkers Consortium was successful in achieving the goals of accelerating the development of medicines and sharing the research findings on pre-competitive stages. For example, as it can be seen from one of its first projects, the evaluation of the utility of adiponectin for measuring the glycemic efficacy, the initiatives of the Biomarkers Consortium were effective for achieving the goals of this partnership. Regardless of a number of challenges and pitfalls, this data-sharing project allowed answering questions which could not be resolved by each individual company (Wagner et al., 2010, p. 240).
The Biomarkers Consortium was launched on November 5, 2006 and currently remains operational. The main reason for the launch of this partnership was the ineffectiveness of modern biomedical researches. It was hypothesized that precompetitive collaboration can be a driver for the increased productivity and innovation. The model of sharing information at early stages of research can be advantageous for all stakeholders.
Due to the specifics of the goals of this partnership dealing with intellectual property, the interorganizational relationships within it can be defined as contractual agreements. Legal mechanisms are created for regulating the processes of sharing and accessing the information. Novick, Morrow and Mays (2007) noted that the contractual agreements are used when collaborative efforts imply substantial financial risks (p. 116). Taking into account the risks of sharing the findings of biomedical research, it can be stated that the contractual agreement is the most appropriate relationship for the Biomarkers Consortium.
Genetic Association Information Network
The Genetic Association Information Network is a public-private partnership launched for the purpose of conducting cost-effective genome studies to identify genes which can be related to health and/or certain diseases. Previously, genome studies focused on a single phenotype in a single study. However, with the advancements in genotyping technologies, there was a pressing need for creating collaboration networks containing a variety of study samples and phenotypes. Therefore, the Genetic Association Information Network is one of such partnerships focused on developing effective approaches to study selection, genotyping and quality control (Manolio et al., 2007, p. 1045).
The structure of the Genetic Association Information Network involves the FNIH, the NIH and partners from academic and private domains. The partners from the private sector include Pfizer, Affymetrix, Perlegen Schiences, Abbott and others. The goal pursued by this partnership is to release date of projects as widely as possible and ensure equal access to data for all users giving their consent to protect the confidentiality of study participants and respect the intellectual property of contributors. The structure of the collaborative research group of the Genetic Association Information Network includes a Steering Committee responsible for guiding the projects and three subcommittees, namely the Principal Investigators Group, the Genotyping Group, and the Analysis Methodology Group.
This partnership was effective in achieving its goals of assisting the research community in defining genetic causes of major diseases. Focusing on six diseases, including those of ADHD, diabetic nepropathy, depression, bipolar disorder, schizophrenia and psoriasis, the network compared the genetic makeup of patients suffering from these diseases to the one of healthy people. This data can be helpful for better diagnosing, treating or preventing diseases. Disseminating the research findings among the research community, the network facilitated the streamlining of the genetic research process.
This partnership was created as a response to the pressing need for creating collaborative networks involving a wide range of phenotypes and study samples. With the advancements in genotyping technologies, multiple samples and studies were required for conducting cost-effective genetic studies and identifying genes which can be related to health or certain diseases.
The applications for participating in this network were submitted in May 2006, and by the year 2007, the Genetic Association Information Network completed its first studies. Therefore, during the first year of its operation, this partnership made significant achievements and contributed to the findings of genetic research.
As to the structural model used in this health partnership, it can be defined as shared governance. Rather than formalizing the content of interaction, this network formalizes the processes of decision making and collaborative actions, such as the selection of studies, data analysis and interpretation.
The Alzheimers Disease Neuroimaging Initiative
The Alzheimers Disease Initiative was launched for the purpose of defining whether certain biological markers can be used for measuring the progression of Alzheimers disease. This private-public partnership is aimed at comparing the neuroimaging and other biological markers of patients to track the progression of memory loss in patients suffering from the symptoms of Alzheimers and mild cognitive impairment (MCI). The primary purpose of this initiative is to assist researchers in developing new treatments and improving the cost-effectiveness of clinical trials.
The structure of the Alzheimers Disease Initiative includes the National Institute on Aging, the NIH, the National Institute of Biomedical Imaging and Bioengineering (NIBIB) and a number of pharmaceutical companies (Pfizer, Merck, GlaxoSmithKline and other among them). This initiative is recognized as one of the most comprehensive efforts to identify biomarkers in relation to functional and cognitive changes in patients with MCI or AD (Mueler et al., 2005, p. 872). This initiative consists of several cores, including those of a clinical coordination center, two neuroimaging sectors, specialized biomarker, informatics and biostatistics cores.
The goals of the Alzheimers Disease Initiative included the development of optimized methods and uniform standards for making the measurements of biomarkers in participants of the study. The second goal was to use the optimized methods and obtain longitudinal imaging data. The third goal was to identify the types of measurements and biomarkers possessing the maximum power for diagnosing AD and MCI at early stages. The final goal of the network was to create a clinical data repository and make it generally accessible to a wide audience. The initiative was rather successful in achieving these goals.
The initiative was launched because of the increased socioeconomic impact of AD and the importance of increasing knowledge on the pathophysiologic mechanisms leading to this disease in elderly people. There was evidence that neuroimaging and biomarkers can be used for tracking the changes in functional and cognitive processes and evaluating the effectiveness of particular treatments. Due to the lack of research on the value of particular biomarkers, this partnership was launched for the purpose of narrowing the existing gap. The total duration of this partnership was 5 years, starting from the year 2006. The study participants were 800 subjects, including those of 200 healthy individuals, 400 subjects with symptoms of MCI and 200 subjects with symptoms of AD.
The structural model used for the Alzheimers Disease Initiative is shared governance because more attention is paid to the formalization of the processes of decision making than to the content of interaction. The partnership was formal, but only the processes of developing the optimized methods and uniform standards were formalized.
Contrasting the three partnerships
Comparing and contrasting the three partnerships under consideration, namely the Biomarkers Consortium, the Genetic Association Information Network and the Alzheimers Disease Initiative, it can be stated that all of then were rather effective for achieving their goals and facilitating the high quality health care services in the United States. The differences in the structural models and goals of these partnerships can be explained with the specifics of their research areas and initial purposes. Therefore, formalization of the content of interaction was especially important for the Biomarkers Consortium because it was related to substantial financial risks of the involved parties which could share the research findings only on precompetitive stages. Another issue is the duration of partnership which was limited only for the Alzheimers Disease Initiative, whereas the duration of the rest of partnerships was not limited and new projects could be included into them. Zahner (2005) stated that financial support, a wide range of partners and sufficient time for partnerships are the most important influential factors to be considered for improvement of partnership effectiveness (p. 82). Therefore, it can be concluded that most of these criteria were met in the three networks under consideration.
References
Manolio, T., Rodriguez, L., Brooks, L., & Abecasis, G. (2007). New models of collaboration in genome-wide association studies: The Genetic Association Information Network. Nature Genetics, 39, 1045 101.
Mueler, S., Weiner, M., Thal, L., Petersen, R., Clifford, J., & Beckett, L. (2005). The Alzheimers Disease Neuroimaging Initiative. Neuroimaging Clinics of North America, 15, 869 877.
Novick, L., Morrow, C. & Mays, G. (2007). Public health administration: Principles for population-based management. Sudbury, MA: Jones and Bartlett Publishing.
Wagner, J., Prince, E., Ennis, M., Kochan, J., Nunez, D., Schneider, B., Wang, M., & Chen, Y. (2010). The Biomarkers Consortium: Practice and pitfalls of open-source precompetitive collaboration. Clinical Pharmacology and Therapeutics, 87 (5), 539 542.
Zanher, S. (2005). Local public health system partnerships. Public Health Reports, 120, 76 83.
Zerhouni, E., Sanders, C., & von Eschenbach, A. (2007). The Biomarkers Consortium: Public and private sectors working in partnership to improve the public health. The Oncologist, 12 (3), 250 252.
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