“Reading between the lines” of flow sheet data: nurses' optional documentation associated with cardiac arrest outcomes
Open accessThe 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
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.
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 team has published on statistically significant signals detected in nursing data using this metadata modeling approach since 2012, demonstrating its resilience as EHR functionality and documentation policies change over time and across multiple sites.
“Our team has published on statistically significant signals detected in nursing data using this metadata modeling approach since 2012 (refs. 13,21), demonstrating its resilience, first, as EHR functionality and documentation policies change over time and across multiple sites.”
From Real-time surveillance system for patient deterioration: a pragmatic cluster-randomized controlled trial (2025) · cites this paper as [21]
Split into 2 atoms — 1 confirmed, 1 partially supported, 0 disputed, 0 misattributed, 0 unverifiable. Expand the claim to see per-atom verdicts.
Experimental — accuracy not yet measuredCONCERN EWS's methodological choices, including robust modeling of temporal data patterns and use of nursing assessment and observational data, allowed it to have accurate and robust predictive power and sufficient lead time to alter a patient's clinical trajectory.
“Several methodological choices allowed CONCERN EWS to have accurate and robust predictive power and sufficient lead time to alter a patient’s clinical trajectory as we observed in this trial, including: (1) robust modeling of temporal data patterns40–42 (for example, time of day, day of week and patient hospital day) for health care processes (for example, nurses’ surveillance and medication”
From Real-time surveillance system for patient deterioration: a pragmatic cluster-randomized controlled trial (2025) · cites this paper as [21]
Split into 2 atoms — 0 confirmed, 2 partially supported, 0 disputed, 0 misattributed, 0 unverifiable. Expand the claim to see per-atom verdicts.
Experimental — accuracy not yet measuredCONCERN leverages evidence that nurses alter their documentation behavior or use selected language in their narrative notes when they are concerned about a patient's changing clinical state.
“As such, it leverages evidence that nurses alter their documentation behavior or use selected language in their narrative notes when they are concerned about a patient’s changing clinical state [21-24].”
From Factors influencing clinician trust in predictive clinical decision support systems for in-hospital deterioration: qualitative descriptive study (2022) · cites this paper as [23]
Nurses can observe subtle patient changes that suggest clinical deterioration is more likely.
“Nurses can observe subtle patient changes that suggest clinical deterioration is more likely10,21, and early recognition and escalation of treatment for these patients by the interprofessional care team, including transfer to the ICU, can improve outcomes.”
From Real-time surveillance system for patient deterioration: a pragmatic cluster-randomized controlled trial (2025) · cites this paper as [21]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Hypoglycemia and outcome in critically ill patients
Egi, M., Bellomo, R., Stachowski, E., French, C. J., Hart, G. K., Taori, G., Hegarty, C., & Bailey, M. (2010) · Mayo Clinic Proceedings · doi:10.4065/mcp.2009.0394 · Cited by 432 · see citing works
EHR Safety: The Way Forward to Safe and Effective Systems
Walker, J. M., Carayon, P., Leveson, N., Paulus, R. A., Tooker, J., Chin, H., Bothe, A., & Stewart, W. F. (2008) · Journal of the American Medical Informatics Association · doi:10.1197/jamia.m2618 · Cited by 113 · see citing works
Flagged first, then by citations
Research works printed but not linked: 16
- [2]Collins S Bakken S Vawdrey D Coiera E Currie L Model development for EHR interdisciplinary information exchange of ICU common goals Int J Med Inform 2010 PMC3044780 20974549
- [3]National Research Council Computational Technology for Effective Health Care: Immediate Steps and Strategic Directions Washington, D.C. The National Academies Press 2009 20662117
- [4]Benner P From Novice to Expert: Excellence and Power in Clinical Nursing Practice, Commemorative Edition New Jersey Prentice Hall 2001
- [5]Gurman G Steiner Z Kriemerman S A new intensive care worksheet Int J Clin Monit Comput 1988 5 1 27 30 3351371
- [6]Collins S Bakken S Vawdrey D Coiera E Currie L Discuss Now, Document Later: CIS/CPOE Perceived to be a ‘Shift Behind’ in the ICU Proceedings of MedInfo 2010 Cape Town, South Africa in press 2010 PMC7010461 20841673
- [7]Brown PJ Borowitz SM Novicoff W Information exchange in the NICU: what sources of patient data do physicians prefer to use? Int J Med Inform 2004 73 4 349 355 15135753
- [8]Knaus WA Wagner DP Draper EA Zimmerman JE Bergner M Bastos PG Sirio CA Murphy DJ Lotring T Damiano A The APACHE III prognostic system. Risk prediction of hospital mortality for critically ill hospitalized adults Chest 1991 100 6 1619 1636 1959406
- [9]Kho A Rotz D Alrahi K Cardenas W Ramsey K Liebovitz D Noskin G Watts C Utility of commonly captured data from an EHR to identify hospitalized patients at risk for clinical deterioration AMIA Annual Symposium proceedings / AMIA Symposium 2007 404 408 PMC2655808 18693867
- [10]Chobanian A Bakris G Black H Cushman W Green L Izzo JJ Jones D Materson B Oparil S Wright JJ The Seventh Report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure: the JNC 7 report JAMA 2003 289 19 2560 2572 12748199
- [12]Knaus WA Draper EA Wagner DP Zimmerman JE APACHE II: a severity of disease classification system Critical care medicine 1985 13 10 818 829 3928249
- [13]Crocker C Scholes J The importance of knowing the patient in weaning from mechanical ventilation Nurs Crit Care 2009 14 6 289 296 19840275
- [14]Kallstrom TJ AARC Clinical Practice Guideline: oxygen therapy for adults in the acute care facility--2002 revision & update Respir Care 2002 47 6 717 720 12078655
- [15]O'Driscoll BR Howard LS Davison AG BTS guideline for emergency oxygen use in adult patients Thorax 2008 63 6 vi1 68 18838559
- [16]Vawdrey DK Gardner RM Evans RS Orme JF Jr Clemmer TP Greenway L Drews FA Assessing data quality in manual entry of ventilator settings J Am Med Inform Assoc 2007 14 3 295 303 17329731 PMC2244881
- [17]Brooks J An analysis of nursing documentation as a reflection of actual nurse work Medsurg Nurs 1998 7 4 189 196 quiz 197-188 9782888
- [18]O'Brien B Pearson A Unwritten knowledge in nursing: consider the spoken as well as the written word Sch Inq Nurs Pract 1993 7 2 111 124 discussion 125-117 8367627
Cited by
Sorted by citations
Rusanov, A., Weiskopf, N. G., Wang, S., & Weng, C. (2014) · BMC Medical Informatics and Decision Making · doi:10.1186/1472-6947-14-51 · Cited by 137 · see citing works
Schwartz, J. M., George, M., Rossetti, S. C., Dykes, P. C., Minshall, S. R., Lucas, E., & Cato, K. D. (2022) · JMIR Human Factors · doi:10.2196/33960 · Cited by 88 · see citing works
“As such, it leverages evidence that nurses alter their documentation behavior or use selected language in their narrative notes when they are concerned about a patient’s changing clinical state [21-24].”
BackgroundRossetti, S. C., Dykes, P. C., Knaplund, C., Cho, S., Withall, J., Lowenthal, G., Albers, D., Lee, R. Y., Jia, H., Bakken, S., et al. (2025) · Nature Medicine · doi:10.1038/s41591-025-03609-7 · Cited by 54 · see citing works
Rossetti, S. C., Knaplund, C., Albers, D., Dykes, P. C., Kang, M. J., Korach, T. Z., Zhou, L., Schnock, K., Garcia, J., Schwartz, J., et al. (2021) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocab006 · Cited by 42 · see citing works
- Authors
- Collins, S. A., & Vawdrey, D. K.
- Affiliations
- Columbia University (US)
- Corresponding author
- Collins, Sarah A.
- ORCID
- Collins, Sarah A.
- Venue
- Applied Nursing Research
- Publisher
- Elsevier BV
- Published
- 2012-11
- Volume
- 25
- Issue
- 4
- Pages
- 251-257
- ISSN
- 0897-1897 (ISSN-L)
- PMC
- PMC3288795
- OpenAlex
- W2118852336
- Cited by
- 50
- References
- 2
- Citations by year
- 2026: 4 · 2025: 5 · 2024: 5 · 2023: 2 · 2022: 4 · 2021: 11 · 2020: 2 · 2019: 4 · 2018: 4 · 2016: 1 · 2015: 1 · 2014: 3 · 2013: 3 · 2012: 1
- FWCI
- 9.66
- Type
- journal article
- Language
- en
- Open access
- green
- europepmc.org
- Locations
- Applied Nursing Research (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- U.S. National Library of Medicine (L30 LM010875, T15LM007079)
- Topics
- Health Sciences › Nursing › Issues, ethics and legal aspects › Nursing Diagnosis and Documentation
- Health Sciences › Health Professions › Health Information Management › Electronic Health Records Systems
- Health Sciences › Medicine › Emergency Medicine › Cardiac Arrest and Resuscitation
- Keywords
- cardiac arrest, electronic health records, process flow diagram, nursing documentation, free-text comments, mortality, survival, vital signs monitoring, intensive care unit, nursing knowledge, clinical decision-making, interdisciplinary communication
- MeSH terms
- Documentation, Heart Arrest, Humans, Nursing 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
