The DOI matches its Crossref record.
Toward a National Framework for the Secondary Use of Health Data: An American Medical Informatics Association White Paper
Open accessAbstract
Secondary use of health data applies personal health information (PHI) for uses outside of direct health care delivery. It includes such activities as analysis, research, quality and safety measurement, public health, payment, provider certification or accreditation, marketing, and other business applications, including strictly commercial activities. Secondary use of health data can enhance health care experiences for individuals, expand knowledge about disease and appropriate treatments, strengthen understanding about effectiveness and efficiency of health care systems, support public health and security goals, and aid businesses in meeting customers' needs. Yet, complex ethical, political, technical, and social issues surround the secondary use of health data. While not new, these issues play increasingly critical and complex roles given current public and private sector activities not only expanding health data volume, but also improving access to data. Lack of coherent policies and standard "good practices" for secondary use of health data impedes efforts to strengthen the U.S. health care system. The nation requires a framework for the secondary use of health data with a robust infrastructure of policies, standards, and best practices. Such a framework can guide and facilitate widespread collection, storage, aggregation, linkage, and transmission of health data. The framework will provide appropriate protections for legitimate secondary use.
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
Cited by
Weiskopf, N. G., & Weng, C. (2013) · Journal of the American Medical Informatics Association · doi:10.1136/amiajnl-2011-000681 · Cited by 1,216
“As the adoption of electronic health records (EHRs) has made it easier to access and aggregate clinical data, there has been growing interest in conducting research with data collected during the course of clinical care.(1) 2 The Natonal Institutes of Health has called for increasing the reuse of electronic records fo…”
MethodThe ethics of big data: current and foreseeable issues in biomedical contexts
Mittelstadt, B. D., & Floridi, L. (2016) · Science and Engineering Ethics · doi:10.1007/s11948-015-9652-2 · Cited by 714
Kahn, M. G., Callahan, T. J., Barnard, J., Bauck, A. E., Brown, J., Davidson, B. N., Estiri, H., Goerg, C., Holve, E., Johnson, S. G., et al. (2016) · eGEMs (Generating Evidence & Methods to improve patient outcomes) · doi:10.13063/2327-9214.1244 · Cited by 697
A systematic review of barriers to data sharing in public health
van Panhuis, W. G., Paul, P., Emerson, C., Grefenstette, J., Wilder, R., Herbst, A. J., Heymann, D., & Burke, D. S. (2014) · BMC Public Health · doi:10.1186/1471-2458-14-1144 · Cited by 579
Grand challenges in clinical decision support
Sittig, D. F., Wright, A., Osheroff, J. A., Middleton, B., Teich, J. M., Ash, J. S., Campbell, E., & Bates, D. W. (2008) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2007.09.003 · Cited by 582
Metadata
- Authors
- Safran, C., Bloomrosen, M., Hammond, W. E., Labkoff, S., Markel-Fox, S., Tang, P. C., & Detmer, D. E.
- Venue
- Journal of the American Medical Informatics Association
- Publisher
- Oxford University Press (OUP)
- Published
- 2007-01-01
- Volume
- 14
- Issue
- 1
- Pages
- 1-9
- ISSN
- 1067-5027 (ISSN-L)
- 1527-974X
- OpenAlex
- W2124972954
- Cited by
- 705
- References
- 0
- FWCI
- 27.94
- Type
- journal article
- Language
- en
- Open access
- green
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: Toward a National Framework for the Secondary Use of Health Data: An American Medical Informatics Association White Paper. https://app.cochat.ai/papers/10.1197/jamia.m2273
- The paper
- Safran, C., Bloomrosen, M., Hammond, W. E., Labkoff, S., Markel-Fox, S., Tang, P. C., & Detmer, D. E. (2007). Toward a National Framework for the Secondary Use of Health Data: An American Medical Informatics Association White Paper. Journal of the American Medical Informatics Association. https://doi.org/10.1197/jamia.m2273
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.