Innovative Power of Health Care Organisations Affects IT Adoption: A bi-National Health IT Benchmark Comparing Austria and Germany
Abstract
Multinational health IT benchmarks foster cross-country learning and have been employed at various levels, e.g. OECD and Nordic countries. A bi-national benchmark study conducted in 2007 revealed a significantly higher adoption of health IT in Austria compared to Germany, two countries with comparable healthcare systems. We now investigated whether these differences still persisted. We further studied whether these differences were associated with hospital intrinsic factors, i.e. the innovative power of the organisation and hospital demographics. We thus performed a survey to measure the "perceived IT availability" and the "innovative power of the hospital" of 464 German and 70 Austrian hospitals. The survey was based on a questionnaire with 52 items and was given to the directors of nursing in 2013/2014. Our findings confirmed a significantly greater IT availability in Austria than in Germany. This was visible in the aggregated IT adoption composite score "IT function" as well as in the IT adoption for the individual functions "nursing documentation" (OR = 5.98), "intensive care unit (ICU) documentation" (OR = 2.49), "medication administration documentation" (OR = 2.48), "electronic archive" (OR = 2.27) and "medication" (OR = 2.16). "Innovative power" was the strongest factor to explain the variance of the composite score "IT function". It was effective in hospitals of both countries but significantly more effective in Austria than in Germany. "Hospital size" and "hospital system affiliation" were also significantly associated with the composite score "IT function", but they did not differ between the countries. These findings can be partly associated with the national characteristics. Indicators point to a more favourable financial situation in Austrian hospitals; we thus argue that Austrian hospitals may possess a larger degree of financial freedom to be innovative and to act accordingly. This study is the first to empirically demonstrate the effect of "innovative power" in hospitals on health IT adoption in a bi-national health IT benchmark. We recommend directly including the financial situation into future regression models. On a political level, measures to stimulate the "innovative power" of hospitals should be considered to increase the digitalisation of healthcare.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The introduction of novel patient monitoring applications in the ICU remains a lagging process compared to other industry sectors.
“Despite these technological developments, the introduction of novel patient monitoring applications in the ICU remains a lagging process compared to other industry sectors [17,18].”
From Clinical requirements of future patient monitoring in the intensive care unit: qualitative study (2019) · cites this paper as [17]
Cites
Lewis, Agarwal, & Sambamurthy, V. (2003) · MIS Quarterly · doi:10.2307/30036552 · Cited by 1,089 · see citing works
Cresswell, K., & Sheikh, A. (2013) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2012.10.007 · Cited by 690 · see citing works
LUDWICK, D., & DOUCETTE, J. (2009) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2008.06.005 · Cited by 668 · cited 1× · see citing works
“Multinational health IT benchmarks have become a common instrument to measure IT indicators that give an account of the readiness for health IT in a country and to stimulate crosscountry learning [1].”
BackgroundMair, F. S., May, C., O’Donnell, C., Finch, T., Sullivan, F., & Murray, E. (2012) · Bulletin of the World Health Organization · doi:10.2471/blt.11.099424 · Cited by 553 · cited 1× · see citing works
“IT often needs time to unfold its potential and contribute to a positive cost-benefit ratio because of a Austria and Germany at the top complex implementation and integration process [29, 30].”
BackgroundHealth Information Technology: An Updated Systematic Review With a Focus on Meaningful Use
Jones, S. S., Rudin, R. S., Perry, T., & Shekelle, P. G. (2014) · Annals of Internal Medicine · doi:10.7326/m13-1531 · Cited by 475 · see citing works
OECD (2015) · Health at a glance · doi:10.1787/health_glance-2015-en · Cited by 439 · see citing works
DesRoches, C. M., Charles, D., Furukawa, M. F., Joshi, M. S., Kralovec, P. D., Mostashari, F., Worzala, C., & Jha, A. K. (2013) · Health Affairs · doi:10.1377/hlthaff.2013.0308 · Cited by 221 · see citing works
Adler‐Milstein, J., DesRoches, C. M., Furukawa, M. F., Worzala, C., Charles, D., Kralovec, P. D., Stalley, S., & Jha, A. K. (2014) · Health Affairs · doi:10.1377/hlthaff.2014.0453 · Cited by 173 · see citing works
TSIKNAKIS, M., & KOUROUBALI, A. (2009) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2008.07.001 · Cited by 167 · see citing works
The use of weights to account for non-response and drop-out
H�fler, M., Pfister, H., Lieb, R., & Wïttchen, H. (2005) · Social Psychiatry and Psychiatric Epidemiology · doi:10.1007/s00127-005-0882-5 · Cited by 119 · see citing works
Analysing the impact of health-care system change in the EU member states - Germany
Wörz, M., & Busse, R. (2005) · Health Economics · doi:10.1002/hec.1032 · Cited by 111 · see citing works
Zailani, S. H. M., Gilani, M. S., Nikbin, D., & Iranmanesh, M. (2014) · Journal of Medical Systems · doi:10.1007/s10916-014-0111-4 · Cited by 108 · see citing works
The adoption of hospital information systems
McCullough, J. S. (2007) · Health Economics · doi:10.1002/hec.1283 · Cited by 101 · see citing works
The alignment of information systems with organizational objectives and strategies in health care
Bush, M., Lederer, A. L., Li, X., Palmisano, J., & Rao, S. (2009) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2009.02.004 · Cited by 99 · see citing works
Hikmet, N., Bhattacherjee, A., Menachemi, N., Kayhan, V. O., & Brooks, R. G. (2007) · Health Care Management Science · doi:10.1007/s10729-007-9036-5 · Cited by 91 · see citing works
Benchmarking health IT among OECD countries: better data for better policy
Adler‐Milstein, J., Ronchi, E., Cohen, G. R., et al. (2013) · Journal of the American Medical Informatics Association · doi:10.1136/amiajnl-2013-001710 · Cited by 74 · see citing works
Hübner, U., Ammenwerth, E., Flemming, D., Schaubmayr, C., & Sellemann, B. (2010) · BMC Medical Informatics and Decision Making · doi:10.1186/1472-6947-10-8 · Cited by 49 · see citing works
Self-citationSelf-Reinforcing Processes in and among Organizations
Sydow, J., & Schreyögg, G. (2013) · Palgrave Macmillan UK eBooks · doi:10.1057/9780230392830 · Cited by 36 · see citing works
Catan, G., Espanha, R., Mendes, R. V., Toren, O., & CHINITZ, D. P. (2015) · Israel Journal of Health Policy Research · doi:10.1186/s13584-015-0040-9 · Cited by 34 · see citing works
The status of IT service management in health care - ITIL® in selected European countries
Hoerbst, A., Hackl, W. O., Blomer, R., et al. (2011) · BMC Medical Informatics and Decision Making · doi:10.1186/1472-6947-11-76 · Cited by 31 · see citing works
Self-citationAmarasingham, R., Diener‐West, M., Plantinga, L., Cunningham, A. C., Gaskin, D. J., & Powe, N. R. (2008) · BMC Medical Informatics and Decision Making · doi:10.1186/1472-6947-8-39 · Cited by 28 · see citing works
Liebe, J., Hüsers, J., & Hübner, U. (2015) · BMC Medical Informatics and Decision Making · doi:10.1186/s12911-016-0244-0 · Cited by 25 · see citing works
Self-citationSommersguter‐Reichmann, M., & Stepan, A. (2015) · Socio-Economic Planning Sciences · doi:10.1016/j.seps.2015.09.001 · Cited by 18 · see citing works
Hyppönen, H., Kangas, M., Surname, N., Reponen, J., Koch, S., Surname, A., Villumsen, S., Nøhr, C. G., Harðardóttir, G. A., Gilstad, H., et al. (2015) · TemaNord · doi:10.6027/tn2015-539 · Cited by 17 · see citing works
What Are Complex eHealth Innovations and How Do You Measure Them?
Hübner, U. (2014) · Methods of Information in Medicine · doi:10.3414/me14-05-0001 · Cited by 17 · see citing works
Self-citationDeveloping a Workflow Composite Score to Measure Clinical Information Logistics
Liebe, J.-D., Straede, M.-C., Thye, J., & Hübner, U. (2015) · Methods of Information in Medicine · doi:10.3414/me14-02-0025 · Cited by 12 · see citing works
Self-citationCharacteristics of German Hospitals Adopting Health IT Systems – Results from an Empirical Study
Liebe, J.-D., Nicole, E., Andreas, F., & Ursula, H. U. B. (2011) · Studies in health technology and informatics · doi:10.3233/978-1-60750-806-9-335 · Cited by 11 · see citing works
Self-citationThe Natural Hospital Environment: A Socio-Technical-Material perspective
Fernando, J., & Dawson, L. (2013) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2013.10.008 · Cited by 9 · see citing works
Lapão, L. V. (2015) · Israel Journal of Health Policy Research · doi:10.1186/s13584-015-0036-5 · Cited by 8 · see citing works
Wittie, M., Ngo‐Metzger, Q., Lebrun‐Harris, L. A., Shi, L., & Nair, S. (2014) · Journal for Healthcare Quality · doi:10.1111/jhq.12067 · Cited by 8 · see citing works
Song, D. D., Li, D., & Qiu, L. (2010) · Frontiers of Business Research in China · doi:10.1007/s11782-010-0116-x · Cited by 8 · see citing works
Die ökonomische Zukunft der Krankenhäuser in Deutschland
Neubauer, G. (2014) · Gesundheitsökonomie & Qualitätsmanagement · doi:10.1055/s-0033-1356449 · Cited by 5 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Perceptions of Digital Health Education Among European Medical Students: Mixed Methods Survey
Machleid, F., Kaczmarczyk, R., Johann, D., Balčiūnas, J., Atienza-Carbonell, B., von Maltzahn, F., & Mosch, L. (2020) · Journal of Medical Internet Research · doi:10.2196/19827 · Cited by 190 · see citing works
Clinical requirements of future patient monitoring in the intensive care unit: qualitative study
Poncette, A.-S., Spies, C., Mosch, L., Schieler, M., Weber-Carstens, S., Krampe, H., & Balzer, F. (2019) · JMIR Medical Informatics · doi:10.2196/13064 · Cited by 136 · see citing works
- Authors
- Hüsers, J., Hübner, U., Esdar, M., Ammenwerth, E., Hackl, W. O., Naumann, L., & Liebe, J. D.
- Affiliations
- Osnabrück University (DE)
- UMIT TIROL - Private University for Health Sciences and Health Technology (AT)
- Corresponding author
- Hübner, Ursula
- Venue
- Journal of Medical Systems
- Published
- 2017-01-04
- Volume
- 41
- Issue
- 2
- Pages
- 33-33
- ISSN
- 0148-5598 (ISSN-L)
- 1573-689X
- OpenAlex
- W2571237652
- Cited by
- 18
- References
- 32
- Citations by year
- 2025: 1 · 2024: 1 · 2023: 1 · 2022: 3 · 2021: 2 · 2020: 2 · 2019: 4 · 2018: 3 · 2017: 1
- FWCI
- 3.75
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Medical Systems (publishedVersion)
- PubMed (publishedVersion)
- Library Osnabrück University (Hochschule Osnabrück) (submittedVersion)
- Funders
- Ministry of Science and Culture Lower Saxony (VWZN3062)
- Topics
- Health Sciences › Health Professions › Health Information Management › Electronic Health Records Systems
- Health Sciences › Nursing › Issues, ethics and legal aspects › Nursing Diagnosis and Documentation
- Health Sciences › Health Professions › General Health Professions › Social Policies and Healthcare Reform
- Keywords
- health information technology adoption, Austria, Germany, nursing documentation, electronic health records, hospital financial situation, hospital size, digitalization of healthcare, cross-national comparison
- MeSH terms
- Austria, Documentation, Germany, Hospital Administration, Hospital Bed Capacity, Humans, Information Systems, Intensive Care Units, Medication Systems, Organizational Innovation, Benchmarking, Electronic Health Records
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review