Diffusion dynamics of electronic health records: A longitudinal observational study comparing data from hospitals in Germany and the United States

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Highlights

  • •

    Bass Diffusion Models were applied to model EHR diffusion dynamics in both, Germany and the US.

  • •

    Adoption rates of basic EHRs in Germany seem to stagnate from 2011 onwards at a level of about 50%.

  • •

    The coefficient of imitation was much higher in the US than in Germany which points at the importance of direct governmental support.

  • •

    “Imitation” needs to be reinterpreted as a driver that less depends on communication but rather on incentives and regulations.

Abstract

Background

While aiming for the same goal of building a national eHealth Infrastructure, Germany and the United States pursued different strategic approaches – particularly regarding the role of promoting the adoption and usage of hospital Electronic Health Records (EHR).

Objective

To measure and model the diffusion dynamics of EHRs in German hospital care and to contrast the results with the developments in the US.

Materials and methods

All acute care hospitals that were members of the German statutory health system were surveyed during the period 2007–2017 for EHR adoption. Bass models were computed based on the German data and the corresponding data of the American Hospital Association (AHA) from non-federal hospitals in order to model and explain the diffusion of innovation.

Results

While the diffusion dynamics observed in the US resembled the typical s-shaped curve with high imitation effects (q = 0.583) but with a relatively low innovation effect (p = 0.025), EHR diffusion in Germany stagnated with adoption rates of approx. 50% (imitation effect q = -0.544) despite a higher innovation effect (p = 0.303).

Discussion

These findings correlate with different governmental strategies in the US and Germany of financially supporting EHR adoption. Imitation only seems to work if there are financial incentives, e.g. those of the HITECH Act in the US. They are lacking in Germany, where the government left health IT adoption strategies solely to the free market and the consensus among all of the stakeholders.

Conclusion

Bass diffusion models proved to be useful for distinguishing the diffusion dynamics in German and US non-federal hospitals. When applying the Bass model, the imitation parameter needs a broader interpretation beyond the network effects, including driving forces such as incentives and regulations, as was demonstrated by this study.

Section snippets

Diffusion of hospital EHRs in different health care systems

Electronic Health Records (EHR) have been repeatedly linked to efficiency and quality gains in patient care [[1], [2], [3], [4], [5], [6]] and have, therefore, become a natural objective for health policymakers and care delivering organisations (CDOs) alike [[7], [8], [9]]. They are the necessary (yet insufficient) precondition for building national, patient-centred eHealth solutions [10] as well as to shift health care towards a paradigm of Learning Health Systems (LHS) [9,11]. The

German sample

We used the historical survey data collected by the “IT Report Healthcare”, a research based, independent initiative that monitors the IT maturity of hospitals in Germany and neighbouring countries. It is the only German data source offering longitudinal data in a consistent manner. Based on the German hospital index, a complete census of all German hospitals which includes demographic information such as bed count and ownership, all hospitals with Chief Information Officers (CIO) were

EHR diffusion curve in Germany

Referring to the development of EHRs in Germany, Fig. 1a and b show the diffusion of the composite EHR variable and the any type EHR variable in Germany over time. Both curves feature a similar pattern with initial increases followed by stagnating rates from 2013 onwards. The any type EHR variable had been measured to test the validity of the diffusion curve of the composite EHR variable. Both variables differed only with respect to the absolute values. The adoption rates of any type EHRs

EHR diffusion dynamics in Germany and the US

The present study is the first to describe and model the diffusion of health IT innovation in German hospitals, thereby enabling a comparison with other countries, i.e. a comparison with the developments in the US in this study. Contrasting the diffusion of EHR technology in both countries is rewarding as both differ with regard to the political intent and strategy of their eHealth legislation. Hereby, the composite EHR variable turned out to be a sound basis for performing the comparison. It

Conclusion

Longitudinal designs are a methodological imperative for interpreting EHR adoption and diffusion, particularly as point estimators can be misleading. The obtained Bass models with their parameters help to better describe and compare the underlying processes. However, its interpretation needs reconsideration, particularly regarding the interpretation of the role of imitation. To treat HIT innovation as if it took place under self-regulating market conditions – as was done in Germany – appears to

Authors contribution

This paper is the result of the close collaboration between all the authors. UH was the first to initiate the project. ME, JPW, and UH subsequently developed the general concept and analyses with JH being in charge of the methodology and statistical computations. JR and JPW were responsible for consolidating the data from the different data sources. ME was primarily responsible for the content components and writing the manuscript with large contributions from UH and JH in all parts.

Declaration of Competing Interest

The authors declare no conflict of interest.

Acknowledgements

We wish to thank our present and past colleagues who contributed to this study over the last 13 years by designing, implementing and analysing the surveys of the IT-Report Healthcare. In particular, we would like to acknowledge the crucial contributions of Jan-David Liebe, Johannes Thye, Nicole Egbert, Matthias Christopher Straede, Daniel Flemming and Björn Sellemann. We also thank Thorsten Litfin for his valuable comments on the paper. The study was funded by the State of Lower Saxony, Germany

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