Dataset Information

Developing a framework for implementation of genetic services: learning from examples of testing for monogenic forms of common diseases.

ABSTRACT: Genetics in health care is shifting, and responsibilities of genetic and nongenetic specialists are changing, requiring new guidance on how to adapt health care to advances in genetic services. This paper explores facilitators and barriers in the process of implementation of innovations in genetic health care. Furthermore, lessons learnt for optimizing development of new genetic services are summarized. Barriers and facilitators in transition processes were identified using mixed methods, including an online open-ended questionnaire among professionals and an international expert meeting. A multi-case study approach was used to explore recent experiences with innovations in genetic services in different phases of implementation. Barriers encountered in transitions in genetic service provision include the following: lack of genetic knowledge and skills among nongenetic health care providers, resistance to new divisions of responsibilities, and a need for more close collaboration and communication between geneticists and nongeneticists. Facilitating factors include the following: statutory registration of genetic specialists, availability of essential staff and equipment, and existence of registries and guidelines. Other challenges are experienced in the establishment of the appropriate legal and financial structures. A set of points to consider for genetic innovation processes is proposed, addressing, e.g., transition management and cooperation and communication strategies.

SUBMITTER: Rigter T

PROVIDER: S-EPMC4159469 | biostudies-other | 2014 Oct

REPOSITORIES: biostudies-other

ACCESS DATA

Publications

Developing a framework for implementation of genetic services: learning from examples of testing for monogenic forms of common diseases.

Rigter Tessel T Henneman Lidewij L Broerse Jacqueline E W JE Shepherd Maggie M Blanco Ignacio I Kristoffersson Ulf U Cornel Martina C MC

Journal of community genetics 20140604 4

Genetics in health care is shifting, and responsibilities of genetic and nongenetic specialists are changing, requiring new guidance on how to adapt health care to advances in genetic services. This paper explores facilitators and barriers in the process of implementation of innovations in genetic health care. Furthermore, lessons learnt for optimizing development of new genetic services are summarized. Barriers and facilitators in transition processes were identified using mixed methods, includ ...[more]

PMID: 24895224

Similar Datasets

Project description:To date, more than 30 genes have been linked to monogenic diabetes. Candidate gene and genome-wide association studies have identified > 50 susceptibility loci for common type 1 diabetes (T1D) and approximately 100 susceptibility loci for type 2 diabetes (T2D). About 1-5% of all cases of diabetes result from single-gene mutations and are called monogenic diabetes. Here, we review the pathophysiological basis of the role of monogenic diabetes genes that have also been found to be associated with common T1D and/or T2D. Variants of approximately one-third of monogenic diabetes genes are associated with T2D, but not T1D. Two of the T2D-associated monogenic diabetes genes-potassium inward-rectifying channel, subfamily J, member 11 (KCNJ11), which controls glucose-stimulated insulin secretion in the ?-cell; and peroxisome proliferator-activated receptor ? (PPARG), which impacts multiple tissue targets in relation to inflammation and insulin sensitivity-have been developed as major antidiabetic drug targets. Another monogenic diabetes gene, the preproinsulin gene (INS), is unique in that INS mutations can cause hyperinsulinemia, hyperproinsulinemia, neonatal diabetes mellitus, one type of maturity-onset diabetes of the young (MODY10), and autoantibody-negative T1D. Dominant heterozygous INS mutations are the second most common cause of permanent neonatal diabetes. Moreover, INS gene variants are strongly associated with common T1D (type 1a), but inconsistently with T2D. Variants of the monogenic diabetes gene Gli-similar 3 (GLIS3) are associated with both T1D and T2D. GLIS3 is a key transcription factor in insulin production and ?-cell differentiation during embryonic development, which perturbation forms the basis of monogenic diabetes as well as its association with T1D. GLIS3 is also required for compensatory ?-cell proliferation in adults; impairment of this function predisposes to T2D. Thus, monogenic forms of diabetes are invaluable "human models" that have contributed to our understanding of the pathophysiological basis of common T1D and T2D.

Project description:BackgroundMany interventions found to be effective in health services research studies fail to translate into meaningful patient care outcomes across multiple contexts. Health services researchers recognize the need to evaluate not only summative outcomes but also formative outcomes to assess the extent to which implementation is effective in a specific setting, prolongs sustainability, and promotes dissemination into other settings. Many implementation theories have been published to help promote effective implementation. However, they overlap considerably in the constructs included in individual theories, and a comparison of theories reveals that each is missing important constructs included in other theories. In addition, terminology and definitions are not consistent across theories. We describe the Consolidated Framework For Implementation Research (CFIR) that offers an overarching typology to promote implementation theory development and verification about what works where and why across multiple contexts.MethodsWe used a snowball sampling approach to identify published theories that were evaluated to identify constructs based on strength of conceptual or empirical support for influence on implementation, consistency in definitions, alignment with our own findings, and potential for measurement. We combined constructs across published theories that had different labels but were redundant or overlapping in definition, and we parsed apart constructs that conflated underlying concepts.ResultsThe CFIR is composed of five major domains: intervention characteristics, outer setting, inner setting, characteristics of the individuals involved, and the process of implementation. Eight constructs were identified related to the intervention (e.g., evidence strength and quality), four constructs were identified related to outer setting (e.g., patient needs and resources), 12 constructs were identified related to inner setting (e.g., culture, leadership engagement), five constructs were identified related to individual characteristics, and eight constructs were identified related to process (e.g., plan, evaluate, and reflect). We present explicit definitions for each construct.ConclusionThe CFIR provides a pragmatic structure for approaching complex, interacting, multi-level, and transient states of constructs in the real world by embracing, consolidating, and unifying key constructs from published implementation theories. It can be used to guide formative evaluations and build the implementation knowledge base across multiple studies and settings.

Dataset Information

Developing a framework for implementation of genetic services: learning from examples of testing for monogenic forms of common diseases.

Publications

Developing a framework for implementation of genetic services: learning from examples of testing for monogenic forms of common diseases.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets