Evidence map›Paper›PMID 28825182›Full record

ReviewThe patient2018

Serious Choices: A Protocol for an Environmental Scan of Patient Decision Aids for Seriously Ill People at Risk of Death Facing Choices about Life-Sustaining Treatments.

Catherine H Saunders, Glyn Elwyn, Kathryn Kirkland, Marie-Anne Durand

Abstract readReview
PubMed Publisher
In one paragraph

Review in The patient, 2018. 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

4 authors.

Catherine H SaundersThe Dartmouth Institute for Health Policy and Clinical Practice, 1 Medical Center Drive, Lebanon, NH, 03766, USA. Catherine.H.Saunders.GR@dartmouth.edu.
Glyn ElwynThe Dartmouth Institute for Health Policy and Clinical Practice, 1 Medical Center Drive, Lebanon, NH, 03766, USA.
Kathryn KirklandThe Dartmouth Institute for Health Policy and Clinical Practice, 1 Medical Center Drive, Lebanon, NH, 03766, USA.
Marie-Anne DurandThe Dartmouth Institute for Health Policy and Clinical Practice, 1 Medical Center Drive, Lebanon, NH, 03766, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSeriously ill people at high risk of death face difficult decisions, especially concerning the extent of medical intervention. Given the inherent difficulty and complexity of these decisions, the care they receive often does not align with their preferences. Patient decision aids that educate individuals about options and help them construct preferences about life-sustaining care may reduce the mismatch between the care people say they want and the care they receive. The quantity and quality of patient decision aids for those at high risk of death, however, are unknown.

objectiveThis protocol describes an approach for conducting an environmental scan of life-sustaining treatment patient decision aids for seriously ill patients, identified online and through informant analysis. We intend for the outcome to be an inventory of all life-sustaining treatment patient decision aids for seriously ill patients currently available (either publicly or proprietarily) along with information about their content, quality, and known use.

methodsWe will identify patient decision aids in a three-step approach (1) mining previously published systematic reviews; (2) systematically searching online and in two popular app stores; and (3) undertaking a key informant survey. We will screen and assess the quality of each patient decision aid identified using the latest published draft of the U.S. National Quality Forum National Standards for the Certification of Patient Decision Aids. Additionally, we will evaluate readability via readable.io and content via inductive content analysis. We will also use natural language processing to assess the content of the decision aids. DISCUSSION: Researchers increasingly recognize the environmental scan as an optimal method for studying real-world interventions, such as patient decision aids. This study will advance our understanding of the availability, quality, and use of decision aids for life-sustaining interventions targeted at seriously ill patients. We also aim to provide patients, their families, and friends, along with their clinicians, a broad set of resources for making life-sustaining treatment decisions. Although we intend to capture all patient decision aids for the seriously ill in our review, we anticipate the possibility that we may miss some decision aids. In addition to publishing our findings in an academic journal, we plan to post our inventory online in an easy-to-read format for public and clinical consumption.

Indexed as

Decision Support TechniquesPatient ParticipationPatient PreferenceChoice BehaviorCritical IllnessDecision MakingFamilyHumansLife Support CareLiteracyPatient Education as TopicPatientsReproducibility of ResultsResearch DesignRisk Factors

Identifiers

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.