Serious Choices: A Systematic Environmental Scan of Decision Aids and Their Use for Seriously Ill People Near Death
Seriously ill people near death face difficult decisions about life-sustaining treatments such as cardiopulmonary resuscitation and mechanical ventilation. Patient decision aids may improve alignment between patients’ preferences and the care they receive, but the quantity, quality, and routine use of these tools are unknown. We conducted a systematic environmental scan to identify all decision aids for seriously ill people at high risk of death facing choices about life-sustaining treatments, assess their quality, and explore their use in clinical settings. We searched MEDLINE, Google, and mobile application stores and surveyed experts. We included 27 decision aids in our scan. Concerning content, 14 of 27 decision aids for seriously ill people near death were for people with specific diseases and conditions (ie, advanced cancer or kidney disease); 11 concerned individual life-sustaining treatment decisions (ie, cardiopulmonary resuscitation or mechanical ventilation). Only two focused on more general care pathways (ie, life-sustaining intervention, palliative care, and hospice). Twenty-four of 27 decision aids presented options in a balanced way; 23 identified funding sources, and 19 of 27 reported their publication date. Just 11 used plain language. A minority, 11 of 27, listed evidence sources, five documented rigorous evidence-synthesis methods, six disclosed competing interests, and three offered update policies. Preliminary results suggest that few health systems use decision aids in routine patient care. Although many decision aids exist for life-sustaining treatment decisions during serious illness, the tools are deficient in some key quality areas.
© 2019 Society of Hospital Medicine
Once we banked and organized the decision aids, one reviewer (KP) systematically collected information about decision aid characteristics using a data collection form (see Appendix 2. Table 3). The data we collected for decision aids from all sources included (1) the index decision, (2) secondary decision(s), (3) the disease/condition, (4) availability (whether the decision aids are available publicly or proprietorially), and (5) use, ie, whether we learned anything about routine use in clinical environments.
Decision Aid Quality Grading Methods
At least two or three reviewers (C.H.S., K.P., M.A.D.), independently assessed the quality of each included patient decision aid, using the NQF standards. Before assessing the quality of each decision aid, we tested an NQF quality assessment form on five decision aids. We subsequently added specificity to the NQF quality criteria for this review. At least two of three reviewers (CHS, KP, MAD) assessed the quality of all included patient decision aids. We calculated interrater reliability using both Cohen’s Kappa statistic for individual quality categories and Spearman’s correlations for overall scores.
Notably, one of the NQF items concerns plain language. We assessed plain language using average readability scores, generated via Readable.io. If readability scores were below seventh-grade level, we considered them plain language. When we could not assess readability using an average score, ie, in the case of video decision aids, the researchers made a qualitative judgment about the plain language criteria.
Statistical Analysis
Our primary outcome was the number and variety of decision aids available for seriously ill individuals near death facing choices about life-sustaining treatments. Secondary outcomes included the quality, actual availability, and use of the available decision aids. We used Stata 13 to synthesize our results. We also reported overall quality and use. We conducted subgroup analyses, including quality, availability, and use of decision aids by category.
RESULTS
Decision Aid Selection Process
We identified 608 links with information about potential decision aids from our Google search. The two raters had substantial interrater reliability according to Cohen’s Kappa statistic (K = 0.64).20 We did not detect any possible decision aids with our app store searches. We identified 31 studies from our MEDLINE search with information about potential decision aids eligible for inclusion. We received 60 responses to our expert survey from the 187 administered (a 32% response rate).
Altogether, we identified 105 potential decision aids from these sources. We excluded 22/105 potential decision aids from our analysis because they were not publicly accessible, and we could not successfully obtain them from the developers. It remains unknown whether these tools would have qualified for inclusion in our review. We excluded 55/105 tools for not meeting one of the following criteria: 1) not being decision aids according to the NQF criteria 2) not concerning life-sustaining treatments 3) not being targeted at people with serious illness near death. A majority of decision aids for life-sustaining treatment decisions are intended for people who do not yet have an advanced serious illness or are not near death. There were 27 decision aids in our final review (Figure 1).
