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Towards a Theory of PACS Deployment: An Integrative PACS Maturity Framework

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Abstract

Owing to large financial investments that go along with the picture archiving and communication system (PACS) deployments and inconsistent PACS performance evaluations, there is a pressing need for a better understanding of the implications of PACS deployment in hospitals. We claim that there is a gap in the research field, both theoretically and empirically, to explain the success of the PACS deployment and maturity in hospitals. Theoretical principles are relevant to the PACS performance; maturity and alignment are reviewed from a system and complexity perspective. A conceptual model to explain the PACS performance and a set of testable hypotheses are then developed. Then, structural equation modeling (SEM), i.e. causal modeling, is applied to validate the model and hypotheses based on a research sample of 64 hospitals that use PACS, i.e. 70 % of all hospitals in the Netherlands. Outcomes of the SEM analyses substantiate that the measurements of all constructs are reliable and valid. The PACS alignment—modeled as a higher-order construct of five complementary organizational dimensions and maturity levels—has a significant positive impact on the PACS performance. This result is robust and stable for various sub-samples and segments. This paper presents a conceptual model that explains how alignment in deploying PACS in hospitals is positively related to the perceived performance of PACS. The conceptual model is extended with tools as checklists to systematically identify the improvement areas for hospitals in the PACS domain. The holistic approach towards PACS alignment and maturity provides a framework for clinical practice.

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Notes

  1. Statements for maturity levels 1 and 2 were omitted for practical reasons and because all Dutch hospitals have implemented the initial maturity level. Level 2 could be deducted from the assigned scores to level 3 statements.

  2. Composite reliability is similar to Cronbach’s alpha without the assumption of the equal weighting of variables. Its mathematical formula (with the assumption that the factor variance = 1; standardized indicators) is ρ = (Σλ i )2/((Σλ i )2 + Σ1 − (λ i )2).

  3. Principle component analysis (using SPSS v18) among all manifest variables of the model showed that multiple components/factors were present, making CMV unlikely.

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Acknowledgments

The authors wish to thank participants from all hospitals for their kind cooperation and so made this study possible. In particular, we wish to thank Dr. P.M. Algra of the radiology department of the Alkmaar Medical Centre, The Netherlands, for his enthusiasm for our research, and support and assistance in stimulating higher response rates.

Author information

Authors and Affiliations

  1. Department of Information and Computing Sciences, Faculty of Sciences, Utrecht University, Fruinplantsoen 77, 3571 PT, Utrecht, The Netherlands

    Rogier van de Wetering & Ronald Batenburg

  2. Netherlands Institute for Health Services Research (NIVEL), PO Box 1568, 3500 BN, Utrecht, The Netherlands

    Ronald Batenburg

  3. Deloitte Consulting Strategy & Operations, PO Box 3502, Utrecht, GD, The Netherlands

    Rogier van de Wetering

Authors
  1. Rogier van de Wetering
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  2. Ronald Batenburg
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Corresponding author

Correspondence to Rogier van de Wetering.

Appendix: A Multistep Model Development Approach

Appendix: A Multistep Model Development Approach

In developing our conceptual model, we applied a multistep approach using path modeling to hierarchically construct latent variables as the independent part (i.e. PACS alignment) of the conceptual model and latent variables as the dependent part (i.e. PACS performance) of the conceptual model.

Like in any type of modeling, we had to balance between recognizing the details of practice and complying the need for overview and limitation.

With regard to the independent part of the conceptual model, we define the following:

  1. 1.

    The second-order construct as the five organizational domains, each representing different maturity levels, the first-order exogenous constructs;

  2. 2.

    The third-order construct, labeled as PACS alignment, as related to the underlying second-order constructs (i.e. step 1).

    With regard to the dependent part of the conceptual model, we define the following:

  3. 3.

    The second-order constructs (organizational construct and clinical performance construct), as related to the block of the underlying first-order latent constructs, i.e. patient service, end-user service, organizational efficiency, diagnostic efficacy and communication efficacy. For the sake of simplicity, these constructs were left out;

  4. 4.

    The third-order construct, labeled as PACS performance, as related to the underlying second-order constructs (i.e. step 3).

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van de Wetering, R., Batenburg, R. Towards a Theory of PACS Deployment: An Integrative PACS Maturity Framework. J Digit Imaging 27, 337–350 (2014). https://doi.org/10.1007/s10278-013-9671-y

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