A Qualitative Description of Clinician Free-Text Rationales Entered within Accountable Justification Interventions is a research paper published in Applied Clinical Informatics (2022). On theSindex it has a DataRank of 0.330. It has been cited 8 times.
Scored on demand from live citation data
Linked data & code
DataRank reads this dataset's downstream impact straight off the citation graph — no black box, no proprietary weighting. How is this computed?
FAIR checklist signals are shown for context only and do not affect DataRank scoring.
We only score data papers we can read in full — never from an abstract alone.
Base Score Contribution
0.330
From this paper's citation signal
Citation Network Contribution
0
Citation network not refreshed for this result
This paper's DataRank is currently driven only by its base citation score. Citation network data was not refreshed for this result.
Learn more about DataRank methodology →NIA NIH HHS
Grant: R33 AG057383
NCATS NIH HHS
Grant: UL1 TR001422
NIA NIH HHS
Grant: R21 AG057396
NIA NIH HHS
Grant: R33 AG057395
NCATS NIH HHS
Grant: UL1 TR001855
NIA NIH HHS
Grant: R21 AG057383
NIA NIH HHS
Grant: P30 AG059988
NIA NIH HHS
Grant: R21 AG057395
National Institutes of Health
Grant: 5R21AG057383-02
Behavioral Economics Applications to Geriatrics Leveraging EHRs (BEAGLE)
National Institutes of Health
Grant: 1R21AG057396-01
Reducing High-Risk Geriatric Polypharmacy via EHR Nudges
National Institutes of Health
Grant: 1RC4AG039115-01
Use of Behavioral Economics to Improve Treatment of Acute Respiratory Infections
National Institutes of Health
Grant: 1P30AG059988-01A1
The Claude D. Pepper Older Americans Independence Center (OAIC) at Northwestern University
National Institutes of Health
Grant: 5R21AG057395-02
Application of Economics & Social psychology to improve Opioid Prescribing Safety (AESOPS) Trial
Fields of Study
MeSH Terms
Keywords
Sustainable Development Goals
Additional file 1 of Developing and testing a framework for coding general practitioners’ free-text diagnoses in electronic medical records - a reliability study for generating training data in natural language processing
Additional file 1 of Developing and testing a framework for coding general practitioners’ free-text diagnoses in electronic medical records - a reliability study for generating training data in natural language processing
Additional file 2 of Developing and testing a framework for coding general practitioners’ free-text diagnoses in electronic medical records - a reliability study for generating training data in natural language processing
Additional file 2 of Developing and testing a framework for coding general practitioners’ free-text diagnoses in electronic medical records - a reliability study for generating training data in natural language processing