Evidence map›Paper›PMID 30977852›Full record

ArticleJAMA network open2019

Evaluation of the Interrater Reliability of End-of-Life Medical Orders in the Physician Orders for Life-Sustaining Treatment Form.

Gustavo Bigaton Lovadini, Fernanda Bono Fukushima, Joao Francisco Lindenberg Schoueri, Roberto Dos Reis, Cecilia Guimarães Ferreira Fonseca, Jahaira Jeanainne Casanova Rodriguez, Cauana Silva Coelho, Adriele Ferreira Neves, Aniela Maria Rodrigues, Marina Almeida Marques and 6 more

Abstract readEvaluation Study
In one paragraph

Article in JAMA network open, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
–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

5 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. 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

16 authors.

Gustavo Bigaton LovadiniBotucatu Medical School, UNESP, Botucatu, Brazil.
Fernanda Bono FukushimaBotucatu Medical School, UNESP, Botucatu, Brazil.
Joao Francisco Lindenberg SchoueriBotucatu Medical School, UNESP, Botucatu, Brazil.
Roberto Dos ReisBotucatu Medical School, UNESP, Botucatu, Brazil.
Cecilia Guimarães Ferreira FonsecaBotucatu Medical School, UNESP, Botucatu, Brazil.
Jahaira Jeanainne Casanova RodriguezBotucatu Medical School, UNESP, Botucatu, Brazil.
Cauana Silva CoelhoBotucatu Medical School, UNESP, Botucatu, Brazil.
Adriele Ferreira NevesBotucatu Medical School, UNESP, Botucatu, Brazil.
Aniela Maria RodriguesBotucatu Medical School, UNESP, Botucatu, Brazil.
Marina Almeida MarquesBotucatu Medical School, UNESP, Botucatu, Brazil.
Alessandro Ferrari JacintoBotucatu Medical School, UNESP, Botucatu, Brazil.
Karen Harrison DeningDementia UK, London, United Kingdom.
Rick BassettCenter for Nursing Excellence, St Luke's Health System, Kansas City, Missouri.
Alvin H MossCenter for Health Ethics and Law, West Virginia University, Morgantown.
Karl E SteinbergInstitute for Palliative Care, California State University, Long Beach.
Edison Iglesias de Oliveira VidalBotucatu Medical School, UNESP, Botucatu, Brazil.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Importance: Despite its spread in much of the United States and increased international interest, the Physician Orders for Life-Sustaining Treatment (POLST) paradigm still lacks supporting evidence. The interrater reliability of the POLST form to translate patients' values and preferences into medical orders for care at the end of life remains to be studied. Objective: To assess the interrater reliability of the medical orders documented in POLST forms. Design, Setting, and Participants: This cross-sectional study was conducted in a public university hospital in southeastern Brazil. Two independent researchers interviewed the same patients or decision-making surrogates (n = 64) during a single episode of hospitalization within a time frame of 1 to 7 days. Eligible participants were hospitalized adults aged 21 years or older who were expected to remain hospitalized for at least 4 days and whose attending physician responded no to the question, Would I be surprised if this patient died in the next year? Data collection occurred between November 1, 2015, and September 20, 2016, and first data analyses were performed on October 3, 2016. Main Outcomes and Measures: Interrater reliability as measured by κ statistics. Results: Of the 64 participants interviewed in the study, 53 (83%) were patients and 11 (17%) were surrogates. Patients' mean (SD) age was 64 (14) years, and 35 patients (55%) and 8 surrogates (73%) were women. Overall, in 5 cases (8%), disagreement in at least 1 medical order for life-sustaining treatment was found in the POLST form, changing from the first interview to the second interview. The κ statistic for cardiopulmonary resuscitation was 0.92 (95% CI, 0.80-1.00); for level of medical intervention, 0.89 (95% CI, 0.76-1.00); and for artificially administered nutrition, 0.92 (95% CI, 0.83-1.00). Conclusions and Relevance: The high interrater reliability of the medical orders in POLST forms appears to offer further support for this advance care planning paradigm; in addition, the finding that this interrater reliability was not 100% underscores the need to ensure that patients or their surrogates have decision-making capacity and to confirm that the content of POLST forms accurately reflects patients' current treatment preferences.

Indexed as

Attitude to DeathAdultAdvance Care PlanningAgedAged, 80 and overBrazilCross-Sectional StudiesDecision MakingFemaleHumansLife Support CareMaleMiddle AgedObserver VariationPatient PreferencePhysicians

Identifiers

PMID30977852
PMCPMC6481595

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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.