Dataset Information

[Research advances in the use of digital surgical guides in implantology].

ABSTRACT: Dental implants have become the main choice for patients to fill in their missing teeth. A precise placement is the basis for a functional and aesthetic restoration. A digital surgical guide is a carrier that transfers the preoperative plan of dental implants to the actual surgery. This paper provides some references that can help clinicians improve the accuracy of implant surgery by stating the development, classification, advantages and disadvantages, and factors that affect the accuracy of digital guides.

SUBMITTER: Wang XH

PROVIDER: S-EPMC7184307 | biostudies-literature | 2020 Feb

REPOSITORIES: biostudies-literature

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[Research advances in the use of digital surgical guides in implantology].

Wang Xiao-Hua XH Liu Ai-Peng AP Deng Wen-Zheng WZ

Hua xi kou qiang yi xue za zhi = Huaxi kouqiang yixue zazhi = West China journal of stomatology 20200201 1

Dental implants have become the main choice for patients to fill in their missing teeth. A precise placement is the basis for a functional and aesthetic restoration. A digital surgical guide is a carrier that transfers the preoperative plan of dental implants to the actual surgery. This paper provides some references that can help clinicians improve the accuracy of implant surgery by stating the development, classification, advantages and disadvantages, and factors that affect the accuracy of di ...[more]

PMID: 32037774

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Project description:BackgroundGaps in electronic health record (EHR) data collection and the paucity of standardized clinical data elements (CDEs) captured from electronic and digital data sources have impeded research efforts aimed at understanding the epidemiology and quality of care for opioid use disorder (OUD). We identified existing CDEs and evaluated their validity and usability, which is required prior to infrastructure implementation within EHRs.MethodsWe conducted (a) a systematic literature review of publications in Medline, Embase and the Web of Science using a combination of at least one term related to OUD and EHR and (b) an environmental scan of publicly available data systems and dictionaries used in national informatics and quality measurement of policy initiatives. Opioid-related data elements identified within the environmental scan were compared with related data elements contained within nine common health data code systems and each element was graded for alignment with match results categorized as "exact", "partial", or "none."ResultsThe literature review identified 5186 articles for title search, of which 75 abstracts were included for review and 38 articles were selected for full-text review. Full-text articles yielded 237 CDEs, only 12 (5.06%) of which were opioid-specific. The environmental scan identified 379 potential data elements and value sets across 9 data systems and libraries, among which only 84 (22%) were opioid-specific. We found substantial variability in the types of clinical data elements with limited overlap and no single data system included CDEs across all major data element types such as substance use disorder, OUD, medication and mental health. Relative to common health data code systems, few data elements had an exact match (< 1%), while 61% had a partial match and 38% had no matches.ConclusionsDespite the increasing ubiquity of EHR data standards and national attention placed on the opioid epidemic, we found substantial fragmentation in the design and construction of OUD related CDEs and little OUD specific CDEs in existing data dictionaries, systems and literature. Given the significant gaps in data collection and reporting, future work should leverage existing structured data elements to create standard workflow processes to improve OUD data capture in EHR systems.

Project description:Digital health technologies (smartphones, smartwatches, and other body-worn sensors) can act as novel tools to aid in the diagnosis and remote objective monitoring of an individual's disease symptoms, both in clinical care and in research. Nonetheless, such digital health technologies have yet to widely demonstrate value in clinical research due to insufficient data interpretability and lack of regulatory acceptance. Metadata, i.e., data that accompany and describe the primary data, can be utilized to better understand the context of the sensor data and can assist in data management, data sharing, and subsequent data analysis. The need for data and metadata standards for digital health technologies has been raised in academic and industry research communities and has also been noted by regulatory authorities. Therefore, to address this unmet need, we here propose a metadata set that reflects regulatory guidelines and that can serve as a conceptual map to (1) inform researchers on the metadata they should collect in digital health studies, aiming to increase the interpretability and exchangeability of their data, and (2) direct standard development organizations on how to extend their existing standards to incorporate digital health technologies. The proposed metadata set is informed by existing standards pertaining to clinical trials and medical devices, in addition to existing schemas that have supported digital health technology studies. We illustrate this specifically in the context of Parkinson's disease, as a model for a wide range of other chronic conditions for which remote monitoring would be useful in both care and science. We invite the scientific and clinical research communities to apply the proposed metadata set to ongoing and planned research. Where the proposed metadata fall short, we ask users to contribute to its ongoing revision so that an adequate degree of consensus can be maintained in a rapidly evolving technology landscape.

Dataset Information

[Research advances in the use of digital surgical guides in implantology].

Publications

[Research advances in the use of digital surgical guides in implantology].

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