The State and Pattern of Health Information Technology Adoption

The State and Pattern of Health Information Technology Adoption

Kateryna Fonkych
Roger Taylor
Copyright Date: 2005
Edition: 1
Published by: RAND Corporation
Pages: 66
https://www.jstor.org/stable/10.7249/mg409hlth
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  • Book Info
    The State and Pattern of Health Information Technology Adoption
    Book Description:

    Helps focus the policy agenda for incentives to speed Healthcare Information Technology (HIT) adoption by estimating the current level and pattern of HIT adoption in the different types of healthcare organizations, according to information the Healthcare Information and Management Systems Society (HIMSS)-Dorenfest database, and evaluates factors that affect this diffusion process, using existing empirical studies and regression analysis.

    eISBN: 978-0-8330-4098-5
    Subjects: Health Sciences

Table of Contents

  1. Front Matter
    (pp. i-ii)
  2. Preface
    (pp. iii-iv)
  3. Table of Contents
    (pp. v-vi)
  4. Figures
    (pp. vii-viii)
  5. Tables
    (pp. ix-x)
  6. Summary
    (pp. xi-xii)
  7. Acronyms
    (pp. xiii-xiv)
  8. CHAPTER ONE Introduction and Review of the Literature
    (pp. 1-6)

    The call for government intervention in the adoption process for Health Information Technology (HIT) is based on the widespread belief that the diffusion of HITs is too slow to be socially optimal. Innovations in information technology (IT) have improved the efficiency and quality of many industries; however, healthcare has yet to realize the tremendous potential of information technologies. It is widely perceived that, although some administrative IT systems, such as those for billing, scheduling, and inventory management, are already in place, little progress has occurred in adopting clinical IT, such as Electronic Medical Records Systems (EMR-S) and Clinical Decision Support...

  9. CHAPTER TWO Estimates of Current HIT Adoption and of HIT Diffusion
    (pp. 7-22)

    In this chapter, we set out to derive a population-wide adoption level of administrative and clinical HIT applications according to information in the Healthcare Information and Management Systems Society (HIMSS)-Dorenfest database (formerly the Dorenfest IHDS+TM Database, second release, 2004) and compare our estimates with alternative estimates. We then attempt to summarize the current state and dynamics of HIT adoption according to these data and briefly review existing empirical studies on the HIT-adoption process.

    There is no unique way to measure the adoption of a particular technology, because the definition ofadoptionvaries by the stage in the adoption process and...

  10. CHAPTER THREE Factors Related to HIT Adoption
    (pp. 23-48)

    In this chapter, we estimate the current level and pattern of HIT adoption in the different types of healthcare organizations, and we evaluate factors that affect this diffusion process. By comparing adoption rates across different types of healthcare providers and geographical areas, we help focus the policy agenda by identifying which healthcare providers lag behind and may need the most incentives to adopt HIT. Next, we employ regression analysis to separate the effects of the provider’s characteristics and factors on adoption of Electronic Medical Records (EMR), Computerized Physician Order Entry (CPOE), and Picture Archiving Communications Systems (PACS), and compare the...

  11. CHAPTER FOUR Summary of Results and Conclusions
    (pp. 49-50)

    Certain results may be the most useful for HIT policymaking. We summarize those results in this chapter.

    The overall EMR adoption rate, as defined by having made a contractual commitment to adopt, is between 20 and 30 percent for hospitals and up to 12 percent for physician practices. Further, the overall rate of adoption is growing, especially in non-profit healthcare organizations. Our analysis supports earlier findings that the pattern of HIT adoption differs drastically from for-profit to non-profit hospitals. Not only is the adoption of major clinical HIT systems, such as EMR, CPOE, and PACS, significantly lower in for-profits, even...

  12. References
    (pp. 51-52)