The DOI matches its Crossref record; 12 of the 12 references it cites were found in a registry or an index.
HITECH Act Drove Large Gains In Hospital Electronic Health Record Adoption
Abstract
The extent to which recent large increases in hospitals' adoption of electronic health record (EHR) systems can be attributed to the Health Information Technology for Economic and Clinical Health (HITECH) Act of 2009 is uncertain and debated. Because only short-term acute care hospitals were eligible for the act's meaningful-use incentive program, we used national hospital data to examine the differential effect of HITECH on EHR adoption among eligible and ineligible hospitals in the periods before (2008-10) and after (2011-15) implementation of the program. We found that annual increases in EHR adoption rates among eligible hospitals went from 3.2 percent in the pre period to 14.2 percent in the post period. Ineligible hospitals experienced much smaller annual increases of 0.1 percent in the pre period and 3.3 percent in the post period, a significant difference-in-differences of 7.9 percentage points. Our results support the argument that recent gains in EHR adoption can be attributed specifically to HITECH, which suggests that the act could serve as a model for ways to drive the adoption of other valuable technologies.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Stimulating the Adoption of Health Information Technology
Blumenthal, D. (2009) · New England Journal of Medicine · doi:10.1056/nejmp0901592 · Cited by 725
Systematic review: Effects, design choices, and context of pay-for-performance in health care
Van Herck, P., De Smedt, D., Annemans, L., Remmen, R., Rosenthal, M. B., & Sermeus, W. (2010) · BMC Health Services Research · doi:10.1186/1472-6963-10-247 · Cited by 523
Health 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
Electronic Health Record Adoption In US Hospitals: Progress Continues, But Challenges Persist
Adler-Milstein, J., DesRoches, C. M., Kralovec, P., Foster, G., Worzala, C., Charles, D., Searcy, T., & Jha, A. K. (2015) · Health Affairs · doi:10.1377/hlthaff.2015.0992 · Cited by 310
Self-citationImpact of the HITECH Act on physicians’ adoption of electronic health records
Mennemeyer, S. T., Menachemi, N., Rahurkar, S., & Ford, E. W. (2015) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocv103 · Cited by 152
EHR Adoption and Hospital Performance: Time‐Related Effects
Adler‐Milstein, J., Everson, J., & Lee, S. D. (2015) · Health Services Research · doi:10.1111/1475-6773.12406 · Cited by 125
Self-citationField, T. S., Rochon, P. A., Lee, M. H., Gavendo, L., Baril, J. L., & Gurwitz, J. H. (2009) · Journal of the American Medical Informatics Association · doi:10.1197/jamia.m2981 · Cited by 119
Prescribers' Responses to Alerts During Medication Ordering in the Long Term Care Setting
Judge, J., Field, T. S., DeFlorio, M., LaPrino, J., Auger, J., Rochon, P. A., Bates, D. W., & Gurwitz, J. H. (2006) · Journal of the American Medical Informatics Association · doi:10.1197/jamia.m1945 · Cited by 116
Gurwitz, J. H., Field, T. S., Rochon, P., Judge, J., Harrold, L. R., Bell, C. M., Lee, M., White, K., LaPrino, J., Erramuspe‐Mainard, J., et al. (2008) · Journal of the American Geriatrics Society · doi:10.1111/j.1532-5415.2008.02004.x · Cited by 106
Electronic Health Record Adoption and Rates of In-hospital Adverse Events
Furukawa, M. F., Eldridge, N., Wang, Y., & Metersky, M. L. (2016) · Journal of Patient Safety · doi:10.1097/pts.0000000000000257 · Cited by 45
Cited by
Personalized Medicine and the Power of Electronic Health Records
Abul-Husn, N. S., & Kenny, E. E. (2019) · Cell · doi:10.1016/j.cell.2019.02.039 · Cited by 355
Healthcare on the brink: navigating the challenges of an aging society in the United States
Jones, C. H., & Dolsten, M. (2024) · npj Aging · doi:10.1038/s41514-024-00148-2 · Cited by 363
Chen, F., Wang, L., Hong, J., Jiang, J., & Zhou, L. (2024) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocae060 · Cited by 178
Metrics for assessing physician activity using electronic health record log data
Sinsky, C. A., Rule, A., Cohen, G., Arndt, B. G., Shanafelt, T. D., Sharp, C. D., Baxter, S. L., Tai-Seale, M., Yan, S., Chen, Y., et al. (2020) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocz223 · Cited by 162
Self-citationUsing Electronic Health Records To Generate Phenotypes For Research
Pendergrass, S. A., & Crawford, D. C. (2019) · Current Protocols in Human Genetics · doi:10.1002/cphg.80 · Cited by 120
Metadata
- Authors
- Adler-Milstein, J., & Jha, A. K.
- Venue
- Health Affairs
- Publisher
- Health Affairs Publishing, LLC
- Published
- 2017-08
- Volume
- 36
- Issue
- 8
- Pages
- 1416-1422
- ISSN
- 0278-2715 (ISSN-L)
- 1544-5208
- OpenAlex
- W2743298989
- Cited by
- 396
- References
- 12
- FWCI
- 35.57
- Type
- journal article
- Language
- en
- Open access
- closed
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
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: HITECH Act Drove Large Gains In Hospital Electronic Health Record Adoption. https://app.cochat.ai/papers/10.1377/hlthaff.2016.1651
- The paper
- Adler-Milstein, J., & Jha, A. K. (2017). HITECH Act Drove Large Gains In Hospital Electronic Health Record Adoption. Health Affairs. https://doi.org/10.1377/hlthaff.2016.1651
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
