Evidence map›Paper›PMID 40608339›Full record

ArticleJAMA network open2025

Measuring Goal-Concordant Care Using Electronic Clinical Notes.

Catherine L Auriemma, Anne Song, Lake Walsh, Jason Han, Sophia Yapalater, Alexander Bain, Lindsay Haines, Stefania Scott, Casey Whitman, Stephanie Parks Taylor and 5 more

Abstract read
In one paragraph

Article in JAMA network open, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Values elicitation among surgical oncologists: Findings from an international survey.European journal of surgical oncology : the journal of the European Society of Surgical Oncology and the British Association of Surgical Oncology · 2026
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

15 authors.

Catherine L AuriemmaDivision of Pulmonary, Allergy, and Critical Care, Hospital of the University of Pennsylvania, Philadelphia.
Anne SongPalliative and Advanced Illness Research Center, University of Pennsylvania, Philadelphia.
Lake WalshDivision of Internal Medicine and Primary Care, Brigham and Women's Hospital, Boston, Massachusetts.
Jason HanDepartment of Surgery, University of Pennsylvania, Philadelphia.
Sophia YapalaterSupportive Oncology and Palliative Care Program, Fox Chase Cancer Center, Temple University Health System, Philadelphia, Pennsylvania.
Alexander BainDivision of Pulmonary and Critical Care, New York University-Langone, New York, New York.
Lindsay HainesDepartment of Medicine, University of Pennsylvania, Philadelphia.
Stefania ScottPalliative and Advanced Illness Research Center, University of Pennsylvania, Philadelphia.
Casey WhitmanPalliative and Advanced Illness Research Center, University of Pennsylvania, Philadelphia.
Stephanie Parks TaylorDivision of Hospital Medicine, University of Michigan, Ann Arbor.
Gary E WeissmanPalliative and Advanced Illness Research Center, University of Pennsylvania, Philadelphia.
Matthew J GonzalesThe Institute for Human Caring at Providence, Gardena, California.
Roshanthi WeerasingheProvidence Health Research Accelerator, Portland, Oregon.
Staci J WendtProvidence Health Research Accelerator, Portland, Oregon.
Katherine R CourtrightPalliative and Advanced Illness Research Center, University of Pennsylvania, Philadelphia.

Funding

Training in Critical Care Health Policy ResearchT32HL098054 · NHLBI · UNIVERSITY OF PENNSYLVANIA · PI Scott D Halpern · 2010 to 2026
$8.2M
Leveraging the electronic health record and behavioral nudges to promote primary and specialist palliative care for inpatients with serious illness: A pragmatic trialR01AG073384 · NIA · UNIVERSITY OF PENNSYLVANIA · PI Katherine Rinaldi Courtright · 2022 to 2026
$3.3M
Improving sepsis care with AI-based clinical decision supportR35GM155262 · NIGMS · UNIVERSITY OF PENNSYLVANIA · PI Gary Weissman · 2024 to 2026
$1.2M
Developing and Evaluating Quality-Weighted Hospital-Free Days as a Novel, Patient-Centered Outcome for Trials of Patients with Acute Respiratory FailureK23HL163402 · NHLBI · UNIVERSITY OF PENNSYLVANIA · PI Catherine Louise Auriemma · 2022 to 2026
$1.0M
Building equitable and feasible clinical decision support tools for population health management of people living with chronic lung diseaseR03HL171424 · NHLBI · UNIVERSITY OF PENNSYLVANIA · PI WEISSMAN, GARY · 2024 to 2025
$244k
NHLBI NIH HHS K23 HL163402NHLBI NIH HHS L30 HL154185NHLBI NIH HHS R03 HL171424NHLBI NIH HHS T32 HL098054NIA NIH HHS R01 AG073384NIGMS NIH HHS R35 GM155262
6 · The paper itself

Abstract

Importance: Goal-concordant care (GCC) is recognized as the highest quality of care and most important outcome measure for serious illness research, yet practical methods for measuring it are lacking. Objective: To measure GCC using clinical notes in patients' medical records. Design, Setting, and Participants: This longitudinal cohort study involved a retrospective medical record review in 3 urban hospitals in a single health system. Participants included adults with a hospital encounter of 3 or more days between April 1 and July 31, 2019, and 50% or higher predicted 6-month mortality risk. Data abstraction occurred from July 2021 through June 2022. Exposure: Acute care hospitalization and a 50% or higher predicted 6-month mortality risk. Main Outcomes and Measures: Pairs of clinicians independently reviewed clinical notes from admission through 6 months or death to classify the care received during each epoch between patients' documented goals of care (GOC) discussions, into 1 of 4 categories: (1) comfort focused, (2) maintain or improve function, (3) life extension, or (4) unclear. The GOC discussions had been previously classified using the same 4 categories. The primary study outcome was GCC, defined as the alignment of classification of care received and GOC. Secondary outcomes included goal-discordant care, if GOC and care-received classifications were misaligned, and uncertain concordance, if either care received or GOC was classified as unclear or GOC were not documented. Interrater reliability for classification of care received was assessed using Cohen κ statistics. Results: Among 109 patients (53 female [49%]), the median (IQR) age was 70 (63-79) years. The most common serious illnesses were cardiac disease (76 patients [70%]), metastatic cancer (50 patients [45%]), and chronic kidney disease (42 patients [39%]). Interrater reliability for care-received classification was almost perfect (95% interrater agreement, Cohen κ = 0.92; 95% CI, 0.86-0.99). A total of 398 epochs of care were identified, 198 (50%) of which were classified as goal concordant. Of the remaining 200 epochs, 74 (19%) were classified as goal discordant and 126 (32%) of uncertain concordance. During at least 1 epoch of care over the 6-month follow-up, 85 patients (78%) received care of uncertain concordance and 43 (39%) received goal-discordant care. Conclusions and Relevance: In this cohort study of seriously ill adults, GCC was measured using clinical notes alone. These findings can inform automated text-based classification methods to improve the efficiency and scalability of this method and facilitate pragmatic and reliable measurement of GCC in serious illness research and quality improvement efforts.

Indexed as

Electronic Health RecordsPatient Care PlanningQuality of Health CareAgedAged, 80 and overFemaleHumansLongitudinal StudiesMaleMiddle AgedRetrospective Studies

Identifiers

PMID40608339
PMCPMC12232218

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.