Evolutionistic or revolutionary paths? A PACS maturity model for strategic situational planning

Wetering, Rogier van de; Batenburg, Ronald; Lederman, Reeva

doi:10.1007/s11548-010-0414-y

Cited by 18 publications

(7 citation statements)

References 36 publications

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“…Highlighted in Table 2, the CAMM differs from many generic adoption models, such as the diffusion of innovation, TAM, and UTAUT, as it is contextualized to the clinical domain. And, unlike several clinical adoption models, such as the PACS maturity model [32,33], the HIMSS EMRAMs [29,30], or EMR Adoption Model [34], the CAMM is less focused on purely feature adoption and is also is generic enough to be applied to a range of clinical adoption contexts and clinical information systems from personal health records to hospital systems. CAMM is explicitly focused on the measurable outcomes that are linked to integration of IT into clinical practice over time, unlike the FITT [9] or Design-Reality Gap model [10].…”

Section: Discussionmentioning

confidence: 99%

“…Diagnostic imaging have models to describe capability for collaborative jurisdictional infrastructure maturity [31]. The PACS maturity model [32,33] describes the process maturity of hospital based PACS systems in terms of functionality and integration into practice workflow. The EMR (Electronic Medical Records) Adoption Model [34] provides an adoption assessment tool that breaks down office-based EMR adoption into 10 functional areas.…”

Section: Introductionmentioning

confidence: 99%

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The clinical adoption meta-model: a temporal meta-model describing the clinical adoption of health information systems

Price

Lau

2014

BMC Med Inform Decis Mak

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Health information systems (HISs) hold the promise to transform health care; however, their adoption is challenged. We have developed the Clinical Adoption Meta-Model (CAMM) to help describe processes and possible challenges with clinical adoption. The CAMM, developed through an action research study to evaluate a provincial HIS, is a temporal model with four dimensions: availability, use, behaviour changes, and outcome changes. Seven CAMM archetypes are described, illustrating classic trajectories of adoption of HISs over time. Each archetype includes an example from the literature. The CAMM and its archetypes can support HIS implementers, evaluators, learners, and researchers.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

The clinical adoption meta-model: a temporal meta-model describing the clinical adoption of health information systems

Price

Lau

2014

BMC Med Inform Decis Mak

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“…The strategic focus indicator was the most prevalent, with an emphasis on quality and safety [ 26 - 28 ], sustainability and cost effectiveness [ 39 ], and ensuring the systematic evaluation of quantifiable results and objectives [ 24 , 26 - 28 ]. While the strategic focus indicator centers on the core elements that health care organizations focus on, the strategic alignment indicator details the need for the digital strategy to be aligned with the organizational strategy [ 12 , 43 ]. To accomplish this, the digital strategy needs to be grounded on clinical benefits and outcomes [ 1 , 11 ].…”

Section: Resultsmentioning

confidence: 99%

Synthesizing Dimensions of Digital Maturity in Hospitals: Systematic Review

et al. 2022

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Background Digital 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. Objective The aim of this study was to identify the current dimensions used to assess the digital maturity of hospitals. Methods A 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. Results The 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. Conclusions The maturity model framework developed for this study can be used to assess digital maturity and identify areas for improvement.

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“…Now, following our alignment models' logic, firms can define improvement activities that can be executed along the various dimension of our model under the following conditions: (1) investments meet a firms' current and future assessed needs; they are conditional on given situations such as the given state of alignment and the specified strategic alignment direction and (2) improvement activities are done simultaneously and hence by an integrated management perspective. In practice, firms define their own improvement roadmaps incrementally, radical or both as a strategy (Van de Wetering, Batenburg, & Lederman, 2010). In the course of the execution of all improvement activities, the level of alignment between the dimensions should be monitored so that synergies between improvement projects are developed.…”

Section: Toward Alignment Assessments In Practicementioning

confidence: 99%

Strategic Alignment Between IT Flexibility and Dynamic Capabilities

Wetering

Mikalef

Pateli

2018

International Journal of IT/Business Alignment and Governance

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Dynamic capabilities theory (DCT) emerged as a leading framework in the process of value creation for firms. Its core notion complements the premise of the resource-based view of the firm and is considered an important theoretical and management framework in modern information systems research. However, despite DCT's significant contributions, its strength and core focus are essentially in its use for historical firm performance explanation. Furthermore, valuable contributions have been made by several researchers to extend the DCT to fit the constantly changing IT environments and other imperative drivers for competitive performance. However, no DCT extension has been developed which allows firms to integrally assess their current state of maturity to derive imperative steps for further performance enhancements. In light of empirical advancement, this article aims to develop a strategic alignment model for IT flexibility and dynamic capabilities and empirically validates proposed hypotheses using correlation and regression analyses on a large data sample of 322 international firms. The authors conjecture that the combined synergetic effect of the underlying dimensions of a firm's IT flexibility architecture and dynamic capabilities enables organizations to cope with changing environmental conditions and drive competitive firm performance. Findings of this study suggest that there is a significant positive relationship between firms' degree of strategic alignment—defined as the degree of balance between all dimensions—and competitive firm performance. Strategic alignment can, therefore, be seen as an important condition that significantly influences a firm's competitive advantage in constantly changing environments. The proposed framework helps firms assess and improve their maturity and alignment of IT flexibility and dynamic capabilities. This article concludes with a discussion, suggestions for future research and managerial implications are also discussed.

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Evolutionistic or revolutionary paths? A PACS maturity model for strategic situational planning

Cited by 18 publications

References 36 publications

The clinical adoption meta-model: a temporal meta-model describing the clinical adoption of health information systems

The clinical adoption meta-model: a temporal meta-model describing the clinical adoption of health information systems

Synthesizing Dimensions of Digital Maturity in Hospitals: Systematic Review

Strategic Alignment Between IT Flexibility and Dynamic Capabilities

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