How to Measure Digitalization? A Critical Evaluation of Digital Maturity Models
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ABSTRACT:
SUBMITTER: Hattingh M
PROVIDER: S-EPMC7134267 | biostudies-literature | 2020 Mar
REPOSITORIES: biostudies-literature
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Project description:In the visually challenging situation of microsurgery with many altered depth cues, digitalization of surgical systems disrupts two further depth cues, namely focus and parallax. Although in purely optical surgical systems accommodation and eye movements induce expected focus and parallax changes, they become statically fixed through digitalization. Our study evaluates the impact of static focus and parallax onto performance and subjective 3D perception. Subjects reported decreased depth realism under static parallax and focus. Thus surgeons’ depth perception is impacted further through digitalization of microsurgery, increasing the potential of artificial stereo-induced fatigue.
| S-EPMC7000911 | biostudies-literature
Project description:BackgroundThe recent proliferation and application of digital technologies in public health has spurred interest in digital public health. However, as yet, there appears to be a lack of conceptual clarity and consensus on its definition.ObjectiveIn this scoping review, we seek to assess formal and informal definitions of digital public health in the literature and to understand how these definitions have been conceptualized in relation to digitization, digitalization, and digital transformation.MethodsWe conducted a scoping literature search in Ovid MEDLINE, Embase, Google Scholar, and 14 government and intergovernmental agency websites encompassing 6 geographic regions. Among a total of 409 full articles identified, we reviewed 11 publications that either formally defined digital public health or informally described the integration of digital technologies into public health in relation to digitization, digitalization, and digital transformation, and we conducted a thematic analysis of the identified definitions.ResultsTwo explicit definitions of digital public health were identified, each with divergent meanings. The first definition suggested digital public health was a reimagination of public health using new ways of working, blending established public health wisdom with new digital concepts and tools. The second definition highlighted digital public health as an asset to achieve existing public health goals. In relation to public health, digitization was used to refer to the technical process of converting analog records to digital data, digitalization referred to the integration of digital technologies into public health operations, and digital transformation was used to describe a cultural shift that pervasively integrates digital technologies and reorganizes services on the basis of the health needs of the public.ConclusionsThe definition of digital public health remains contested in the literature. Public health researchers and practitioners need to clarify these conceptual definitions to harness opportunities to integrate digital technologies into public health in a way that maximizes their potential to improve public health outcomes.International registered report identifier (irrid)RR2-10.2196/preprints.27686.
| S-EPMC8665390 | biostudies-literature
Project description:This paper proposes the creation and application of maturity models to guide institutional strategic investment in research informatics and information technology (research IT) and to provide the ability to measure readiness for clinical and research infrastructure as well as sustainability of expertise. Conducting effective and efficient research in health science increasingly relies upon robust research IT systems and capabilities. Academic health centers are increasing investments in health IT systems to address operational pressures, including rapidly growing data, technological advances, and increasing security and regulatory challenges associated with data access requirements. Current approaches for planning and investment in research IT infrastructure vary across institutions and lack comparable guidance for evaluating investments, resulting in inconsistent approaches to research IT implementation across peer academic health centers as well as uncertainty in linking research IT investments to institutional goals. Maturity models address these issues through coupling the assessment of current organizational state with readiness for deployment of potential research IT investment, which can inform leadership strategy. Pilot work in maturity model development has ranged from using them as a catalyst for engaging medical school IT leaders in planning at a single institution to developing initial maturity indices that have been applied and refined across peer medical schools.
| S-EPMC6390403 | biostudies-literature
Project description:The digital transformation of firms plays an increasingly important role in the economy and society. However, limited access to data on firm-level digital intensity is an impediment to advancement of multiple research projects concerned with firm digitalization. To alleviate this challenge, this paper proposes a method for estimating firm-level digital intensity based on other more readily available firm-level data and reference data on digitalization, which is available on sector-level. The proposed method utilizes firm-level revenue breakdown by sector to estimate sector revenue-weighted digital intensity scores, which lead to classification of firms into low, medium and high digital intensity groups. The output from the proposed method can be directly used in research concerned with firm digitalization and investigating this multifaceted phenomenon. Results from the application of the proposed method to an illustrative sample of large US and non-US firms (2000 observations in total) indicate that firm-level digital intensity can be efficiently estimated for large samples using data commonly available to researchers. The key differences between the proposed method and alternative methods are:•Recognition of the fact that firms might participate in more than one sector or industry, which partially explains within-sector heterogeneity in firm-level digital intensity. We found that 67.8% of large US firms and 78.6% of large non-US firms were engaged in more than one industry.•Use of reference sector-level digital intensity scores, which allows for rapid update, application across geographies and time, as well as parallel calculation of multiple digital intensity scores for each reference data. Furthermore, use of reference data enables supplementation of firm-level data on digitalization.•Replicability of the method and reproducibility of the results through inclusion of the source code and availability of data through research and commercial databases.
| S-EPMC8374197 | biostudies-literature
Project description:The ATP-gated P2X7 receptor (P2X7R) is a non-selective cation channel which senses high extracellular ATP concentrations and has been suggested as a target for the treatment of neuroinflammation and neurodegenerative diseases. The use of P2X7R antagonists may therefore be a viable approach for treating CNS pathologies, including epileptic disorders. Recent studies showed anticonvulsant potential of P2X7R antagonists in certain animal models. To extend this work, we tested three CNS-permeable P2X7R blocker (Brilliant Blue G, AFC-5128, JNJ-47965567) and a natural compound derivative (tanshinone IIA sulfonate) in four well-characterized animal seizure models. In the maximal electroshock seizure threshold test and the pentylenetetrazol (PTZ) seizure threshold test in mice, none of the four compounds demonstrated anticonvulsant effects when given alone. Notably, in combination with carbamazepine, both AFC-5128 and JNJ-47965567 increased the threshold in the maximal electroshock seizure test. In the PTZ-kindling model in rats, useful for testing antiepileptogenic activities, Brilliant Blue G and tanshinone exhibited a moderate retarding effect, whereas the potent P2X7R blocker AFC-5128 and JNJ-47965567 showed a significant and long-lasting delay in kindling development. In fully kindled rats, the investigated compounds revealed modest effects to reduce the mean seizure stage. Furthermore, AFC-5128- and JNJ-47965567-treated animals displayed strongly reduced Iba 1 and GFAP immunoreactivity in the hippocampal CA3 region. In summary, our results show that P2X7R antagonists possess no remarkable anticonvulsant effects in the used acute screening tests, but can attenuate chemically-induced kindling. Further studies would be of interest to support the concept that P2X7R signalling plays a crucial role in the pathogenesis of epileptic disorders.
| S-EPMC4900628 | biostudies-literature
Project description:Since the early days of the intestinal microbiota research, mouse models have been used frequently to study the interaction of microbes with their host. However, to translate the knowledge gained from mouse studies to a human situation, the major spatio-temporal similarities and differences between intestinal microbiota in mice and humans need to be considered. This is done here with specific attention for the comparative physiology of the intestinal tract, the effect of dietary patterns and differences in genetics. Detailed phylogenetic and metagenomic analysis showed that while many common genera are found in the human and murine intestine, these differ strongly in abundance and in total only 4% of the bacterial genes are found to share considerable identity. Moreover, a large variety of murine strains is available yet most of the microbiota research is performed in wild-type, inbred strains and their transgenic derivatives. It has become increasingly clear that the providers, rearing facilities and the genetic background of these mice have a significant impact on the microbial composition and this is illustrated with recent experimental data. This may affect the reproducibility of mouse microbiota studies and their conclusions. Hence, future studies should take these into account to truly show the effect of diet, genotype or environmental factors on the microbial composition.
| S-EPMC5752736 | biostudies-literature
Project description:Introduction:Lessons captured from interviews with 12 European regions are represented in a new instrument, the B3-Maturity Model (B3-MM). B3-MM aims to assess maturity along 12 dimensions reflecting the various aspects that need to be managed in order to deliver integrated care. The objective of the study was to test the content validity of B3-MM as part of SCIROCCO (Scaling Integrated Care into Context), a European Union funded project. Methods:A literature review was conducted to compare B3-MM's 12 dimensions and their measurement scales with existing measures and instruments that focus on assessing the development of integrated care. Subsequently, a three-round survey conducted through a Delphi study with international experts in the field of integrated care was performed to test the relevance of: 1) the dimensions, 2) the maturity indicators and 3) the assessment scale used in B3-MM. Results:The 11 articles included in the literature review confirmed all the dimensions described in the original version of B3-MM. The Delphi study rounds resulted in various phrasing amendments of indicators and assessment scale. Full agreement among the experts on the relevance of the 12 B3-MM dimensions, their indicators, and assessment scale was reached after the third Delphi round. Conclusion and discussion:The B3-MM dimensions, maturity indicators and assessment scale showed satisfactory content validity. While the B3-MM is a unique instrument based on existing knowledge and experiences of regions in integrated care, further testing is needed to explore other measurement properties of B3-MM.
| S-EPMC5853880 | biostudies-other
Project description:The advantages of intraoral model scanning have yielded recent developments. However, few studies have explored the orthodontic clinical use of this technique particularly among young patients. This study aimed to evaluate the reliability, reproducibility and validity of the orthodontic measurements: tooth width, arch length and arch length discrepancy in each digital model obtained by model scanner and intraoral scanner, relative to a plaster model. Arch length measured using two methods: curved arch length (CAL) measured automatically by digital program and sum of sectional liner arch length (SLAL) measured sum of anterior and posterior liner arch lengths. Arch length discrepancy calculated each arch length measurement methods: curved arch length discrepancy (CALD) and sum of sectional liner arch length discrepancy (SLALD). Forty young patients were eligible for the study. A plaster model (P), model-scanned digital model (MSD) and intraoral scanned digital model (ISD) were acquired from each patient. The reliability of the measurements was evaluated using Pearson's correlation coefficient, while the reproducibility was evaluated using the intraclass correlation coefficient. The validity was assessed by a paired t-test. All measurements measured in P, MSD and ISD exhibited good reliability and reproducibility. Most orthodontic measurements despite of CAL in MSD exhibited high validity. Only the SLAL and SLALD in ISD group differed significantly, despite the good validity of the tooth width, CAL and CALD. The measurements based on the digital program appeared high reliability, reproducibility and accurate than conventional measurement. However, SLAL and SLALD in ISD group appeared shorter because of distortion during intraoral scanning. However, this could be compensated by using digital programed curved arch. Although the validity of SLAL and SLALD in the ISD group differed statistically, the difference is not considered clinically significant. Although MSD and ISD are acceptable for a clinical space analysis, clinicians should be aware of digital model-induced errors.
| S-EPMC7564383 | biostudies-literature
Project description:BACKGROUND:Digital transformation in health care is being driven by the need to improve quality, reduce costs, and enhance the patient experience of health care delivery. It does this through both the direct intervention of technology to create new diagnostic and treatment opportunities and also through the improved use of information to create more engaging and efficient care processes. OBJECTIVE:In a modern digital hospital, improved clinical and business processes are often driven through enhancing the information flows that support them. To understand an organization's ability to transform their information flows requires a clear understanding of the capabilities of an organization's information technology infrastructure. To date, hospital facilities have been challenged by the absence of uniform ways of describing this infrastructure that would enable them to benchmark where they are and create a vision of where they would like to be. While there is an industry assessment measure for electronic medical record (EMR) adoption using the Healthcare Information and Management Systems Society Analytics EMR Adoption Model, there is no equivalent for assessing the infrastructure and associated technology capabilities for digital hospitals. Our aim is to fill this gap, as hospital administrators and clinicians need to know how and why to invest in information infrastructure to support health information technology that benefits patient safety and care. METHODS:Based on an operational framework for the Capability Maturity Model, devised specifically for health care, we applied information use characteristics to define eight information systems maturity levels and associated technology infrastructure capabilities. These levels are mapped to user experiences to create a linkage between technology infrastructure and experience outcomes. Subsequently, specific technology capabilities are deconstructed to identify the technology features required to meet each maturity level. RESULTS:The resulting assessment framework clearly defines 164 individual capabilities across the five technology domains and eight maturity levels for hospital infrastructure. These level-dependent capabilities characterize the ability of the hospital's information infrastructure to support the business of digital hospitals including clinical and administrative requirements. Further, it allows the addition of a scoring calculation for each capability, domain, and the overall infrastructure, and it identifies critical requirements to meet each of the maturity levels. CONCLUSIONS:This new Infrastructure Maturity Assessment framework will allow digital hospitals to assess the maturity of their infrastructure in terms of their digital transformation aligning to business outcomes and supporting the desired level of clinical and operational competency. It provides the ability to establish an international benchmark of hospital infrastructure performance, while identifying weaknesses in current infrastructure capability. Further, it provides a business case justification through increased functionality and a roadmap for subsequent digital transformation while moving from one maturity level to the next. As such, this framework will encourage and guide information-driven, digital transformation in health care.
| S-EPMC6329893 | biostudies-other
Project description:Objective: Assessing brain connectivity from electrophysiological signals is of great relevance in neuroscience, but results are still debated and depend crucially on how connectivity is defined and on mathematical instruments utilized. Aim of this work is to assess the capacity of bivariate Transfer Entropy (TE) to evaluate connectivity, using data generated from simple neural mass models of connected Regions of Interest (ROIs). Approach: Signals simulating mean field potentials were generated assuming two, three or four ROIs, connected via excitatory or by-synaptic inhibitory links. We investigated whether the presence of a statistically significant connection can be detected and if connection strength can be quantified. Main Results: Results suggest that TE can reliably estimate the strength of connectivity if neural populations work in their linear regions, and if the epoch lengths are longer than 10 s. In case of multivariate networks, some spurious connections can emerge (i.e., a statistically significant TE even in the absence of a true connection); however, quite a good correlation between TE and synaptic strength is still preserved. Moreover, TE appears more robust for distal regions (longer delays) compared with proximal regions (smaller delays): an approximate a priori knowledge on this delay can improve the procedure. Finally, non-linear phenomena affect the assessment of connectivity, since they may significantly reduce TE estimation: information transmission between two ROIs may be weak, due to non-linear phenomena, even if a strong causal connection is present. Significance: Changes in functional connectivity during different tasks or brain conditions, might not always reflect a true change in the connecting network, but rather a change in information transmission. A limitation of the work is the use of bivariate TE. In perspective, the use of multivariate TE can improve estimation and reduce some of the problems encountered in the present study.
| S-EPMC7292208 | biostudies-literature