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:BackgroundDigital health maturity models allow healthcare organizations to evaluate digital health capability and to develop roadmaps for improving patient care through technology. There are many models available commercially for healthcare providers to use to assess their digital health maturity. Currently, there are limited evidence-based methods to assess the quality, utility, and efficacy of maturity models to select the most appropriate model for the given context.ObjectiveTo develop a framework to assess digital maturity models and facilitate recommendations for digital maturity model selection.MethodsA systematic, consultative, and iterative process was used. Literature analyses and a stakeholder needs analysis (n = 23) was conducted to develop content and design considerations. These considerations were incorporated into the initial version of the framework developed by researchers in a design workshop. External stakeholder review (n = 20) and improvements strengthened and finalized the framework.ResultsThe criteria of the framework include assessment of healthcare context, feasibility, integrity, completeness and actionability. Users can compare model performance in order to select the most appropriate model for their context.ConclusionThe framework provides healthcare stakeholders with a consistent and objective methodology to compare digital health maturity models, informing approaches to choosing a suitable model. This is a critical step as healthcare evolves towards a digital health system focused on improving the quality of care, reducing costs and improving the provider and consumer experience.
| S-EPMC9731136 | biostudies-literature
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:Healthcare has always been a strategic domain in which innovative technologies can be applied to increase the effectiveness of services and patient care quality. Recent advancements have been made in the adoption of Digital Twins (DTs) and Personal Knowledge Graphs (PKGs) in this field. Despite this, their introduction has been hindered by the complex nature of the context itself which leads to many challenges both technical and organizational. In this article, we reviewed the literature about these technologies and their integrations, identifying the most critical requirements for clinical platforms. These latter have been used to design CONNECTED (COmpreheNsive and staNdardized hEalth-Care plaTforms to collEct and harmonize clinical Data), a conceptual framework aimed at defining guidelines to overcome the crucial issues related to the development of healthcare applications. It is structured in a multi-layer shape, in which heterogeneous data sources are first integrated, then standardized, and finally used to realize general-purpose DTs of patients backed by PKGs and accessible through dedicated APIs. These DTs will be the foundation on which smart applications can be built.
| S-EPMC10733505 | 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:BackgroundDigital health in hospital settings is viewed as a panacea for achieving the "quadruple aim" of health care, yet the outcomes have been largely inconclusive. To optimize digital health outcomes, a strategic approach is necessary, requiring digital maturity assessments. However, current approaches to assessing digital maturity have been largely insufficient, with uncertainty surrounding the dimensions to assess.ObjectiveThe aim of this study was to identify the current dimensions used to assess the digital maturity of hospitals.MethodsA systematic literature review was conducted of peer-reviewed literature (published before December 2020) investigating maturity models used to assess the digital maturity of hospitals. A total of 29 relevant articles were retrieved, representing 27 distinct maturity models. The articles were inductively analyzed, and the maturity model dimensions were extracted and consolidated into a maturity model framework.ResultsThe consolidated maturity model framework consisted of 7 dimensions: strategy; information technology capability; interoperability; governance and management; patient-centered care; people, skills, and behavior; and data analytics. These 7 dimensions can be evaluated based on 24 respective indicators.ConclusionsThe maturity model framework developed for this study can be used to assess digital maturity and identify areas for improvement.
| S-EPMC9008527 | biostudies-literature
Project description:BackgroundMood disorders and depression are pervasive and significant problems worldwide. These represent severe health and emotional impairments for individuals and a considerable economic and social burden. Therefore, fast and reliable diagnosis and appropriate treatment are of great importance. Verbal communication can clarify the speaker's mental state-regardless of the content, via speech melody, intonation, and so on. In both everyday life and clinical conditions, a listener with appropriate previous knowledge or a trained specialist can grasp helpful knowledge about the speaker's psychological state. Using automated speech analysis for the assessment and tracking of patients with mental health issues opens up the possibility of remote, automatic, and ongoing evaluation when used with patients' smartphones, as part of the current trends toward the increasing use of digital and mobile health tools.ObjectiveThe primary aim of this study is to evaluate the measurements of the presence or absence of depressive mood in participants by comparing the analysis of noncontentual speech parameters with the results of the Patient Health Questionnaire-9.MethodsThis proof-of-concept study included participants in different affective phases (with and without depression). The inclusion criteria included a neurological or psychiatric diagnosis made by a specialist and fluent use of the German language. The measuring instrument was the VoiceSense digital voice analysis tool, which enables the analysis of 200 specific speech parameters based on machine learning and the assessment of the findings using Patient Health Questionnaire-9.ResultsA total of 292 psychiatric and voice assessments were performed with 163 participants (males: n=47, 28.8%) aged 15 to 82 years. Of the 163 participants, 87 (53.3%) were not depressed at the time of assessment, and 88 (53.9%) participants had clinically mild to moderate depressive phases. Of the 163 participants, 98 (32.5%) showed subsyndromal symptoms, and 19 (11.7%) participants were severely depressed. In the speech analysis, a clear differentiation between the individual depressive levels, as seen in the Patient Health Questionnaire-9, was also shown, especially the clear differentiation between nondepressed and depressed participants. The study showed a Pearson correlation of 0.41 between clinical assessment and noncontentual speech analysis (P<.001).ConclusionsThe use of speech analysis shows a high level of accuracy, not only in terms of the general recognition of a clinically relevant depressive state in the participants. Instead, there is a high degree of agreement regarding the extent of depressive impairment with the assessment of experienced clinical practitioners. From our point of view, the application of the noncontentual analysis system in everyday clinical practice makes sense, especially with the idea of a quick and unproblematic assessment of the state of mind, which can even be carried out without personal contact.Trial registrationClinicalTrials.gov NCT03700008; https://clinicaltrials.gov/ct2/show/NCT03700008.
| S-EPMC9472064 | 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: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