Introduction

Healthcare guidelines aim to support healthcare professionals, recipients of care and policy makers in making best decisions for care. Guidelines, and the research evidence that supports them, are not without risk of bias [1,2,3]. If bias is not managed appropriately it is possible that guideline developers could formulate an inappropriate recommendation, or guideline end-users could misinterpret a recommendation. One of the ways which the guideline development community has tried to manage bias is by recommending that the certainty of the evidence be rated and presented in the guideline [1, 3,4,5,6,7]. The goal of the exercise is to identify bias and improve the transparency of developers’ considerations that are used to formulate a recommendation. The implications of doing this are that guideline end-users may decide for themselves how and when to apply guidelines for their own needs.

The Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) approach is a framework that is widely used by guideline developers and other organizations to systematically evaluate the quality of evidence, determine the strength of healthcare recommendations, and improve transparency of guideline development methods [8]. One of the aims of the GRADE approach is to minimize the complexity while increasing transparency of evidence evaluation. In part, GRADE does this by guiding developers to consider only the health outcomes which matter to patients most. The rating and selection of important health outcomes occurs before the search for evidence because it helps narrow the search. Collectively, guideline groups generate a list of relevant health outcomes. Guideline developers using GRADE individually rate each outcome according to how important they think it might be to patients in the given healthcare scenario [9]. Outcomes are rated on a 1 to 9 scale (1–3 = low importance for decision making, 4–6 = important, but not critical for decision making, 7–9 = critical for decision making) [10]. GRADE dictates that the outcomes with the highest average rating (rated at least “important”) should be chosen for consideration of that healthcare question. These outcomes, and the corresponding evidence, are presented to guideline panels in GRADE evidence tables that summarize the key information of a systematic review and support decision-making [11,12,13,14]. The importance rating exercise intends to mitigate several challenges in guideline development. It orients panel members to the task of focusing on outcomes that matter to patients, thus reducing the number of outcomes deemed to be patient-important, identifies the level of agreement for the outcome of interest, and indicates the relative importance of the beneficial and harmful outcomes (e.g. within the “critically important” category an outcome rated as 9 will be more important than an outcome rated as 7).

Health utility ratings are used similarly in a guideline panel’s harm-benefit analysis of health outcomes [15]. Health utility is a measure of patients’ values attached to the outcomes [16]. Outcome-specific health utility ratings are often not available or are not applicable to certain target populations [17]. Therefore, panels sometimes rate the health utility of outcomes internally to most accurately measure their collective views on the relative benefits and harms of each outcome. For instance, guideline panel members may rate the outcome on the validated Visual Analogue Scale (VAS) which is anchored by the health states “dead” and “full health” at 0 and 100 respectively.

However, we identified a fundamental problem with consideration of outcomes and calibration of the importance and utility rating scales. That is, panel members often have implicit different definitions of health outcomes that can lead to differences in importance ratings, utility ratings, and final panel recommendations. In fact, a recent observation in the Guidelines Development Group (GDG) that is developing the European guidelines for breast cancer screening and diagnosis within the European Commission Initiative on Breast Cancer (ECIBC) was the impetus for this study. When asked to define health outcome “over-diagnosis of breast cancer” in a concealed fashion, each GDG member provided a considerably different description of the outcome. However, clear definitions and agreement by a guideline panel on what constitutes an outcome is required to search for evidence, balance benefits and harms, communicate with the public, and conduct research. Furthermore, to promote transparency of guideline development methods, guideline end-users require clear explanations of what constitutes each important outcome.

To tackle the issue of standardizing definitions of health outcomes in the ECIBC guideline recommendations (ECIBC guidelines), we utilized a novel template for ‘health outcome descriptors’ developed by researchers at McMaster GRADE Centre. The template is based on the concept of ‘health states’ or ‘clinical marker states’ [18, 19]. Our health outcome descriptors are primarily intended to support the generation of recommendations by guideline developers and promote understanding of development methods by guideline end-users secondarily. Here, we describe the development and use of these health outcome descriptors in the context of the ECIBC guidelines. The purpose of this case study was to determine which aspects of the development, content and use of health outcome descriptors are valuable to guideline developers broadly. We describe lessons learned to improve the structure of the tool and provide guidance for the future development and use of health outcome descriptors.

Methods

General methods

We conducted a case study of the development of health outcome descriptors in the context of the European guidelines for breast cancer screening and diagnosis. We selected a case study design to systematically collect quality feedback from guideline developers involved in the process of health outcome descriptor development. The development of the health outcome descriptors was based upon proposed guidelines for their development [20]. We developed first drafts of the health outcome descriptors for the ECIBC guidelines using a template (Fig. 1). Throughout development, GDG members provided feedback on the drafts and development process. This was done through three rounds of semi-structured interviews and online written feedback. Iterative changes were made to the content and format of the health outcome descriptors based upon the observations of McMaster University researchers and extensive GDG feedback. In between rounds of feedback, GDG members also completed two online health utility assessments. We analyzed the utility scores to quantitively assess whether the development process had an impact on harmonization of outcome definitions as well as values and preferences the GDG had towards the health outcomes.

Fig. 1
figure 1

Draft Template for Development of Health Outcome Descriptors

Participants

We formed a steering committee to coordinate the development of the health outcome descriptors for the European guidelines for breast cancer screening and diagnosis consisting of five researchers: four health methods researchers (HS, NS, PM, ZSP) and one graduate student with training in health sciences (TB).

An opportunity sample of the guidelines development group (GDG) volunteered to participate in the development of the health outcome descriptors in varying capacities. Ten of the thirty GDG members took part in 14 semi-structured interviews to collect feedback on the development methods, content, use, and implementation plans for ECIBC health outcome descriptors. Of those interviewed more than once, one panel member was interviewed three times and two were interviewed twice. Separately, twelve of the thirty GDG members participated in each of the online utility rating surveys (which were sent to every panel member), respectively. Six of those GDG members participated in both surveys.

GDG members were clinicians, epidemiologists, cancer scientists, methodologists, economists, and patients. All GDG members, including those participating in this study, were selected for the panel via an open call by DG Sante to develop the ECIBC guidelines [21]. Each GDG member declared their interests to the ECIBC as part of their agreement to participate in the guideline development. Every GDG member was requested to participate all aspects of health outcome descriptor development for this study. However, participation in this study was voluntary. Signed consent was obtained from all those providing feedback and this study was approved by the Hamilton Integrated Research Ethics Board (HiREB).

Template of health outcome descriptors

We utilized a draft template (Fig. 1) for health outcome descriptors [18,19,20]. The format was purposefully designed to be concise; written at a Grade 8 reading level (as indicated by the Flesch–Kincaid readability tests) from the perspective of the healthcare recipient, who is the primary beneficiary of any healthcare guideline. The template included 4 bulleted domains: “Symptoms”, “Time Horizon”, “Treatment and Testing”, and “Consequences”.

Development of draft health outcome descriptors

The methods for development of the first draft health outcome descriptors are summarized in Fig. 2 (steps 1–3). Realizing the need to harmonize understanding of the ECIBC health outcomes, the steering committee used the draft template (Fig. 1) to write 24 draft health outcome descriptors relevant to the healthcare questions for the ECIBC guidelines. The outcomes chosen for health outcome descriptor development in this study were selected because they had already been prioritized for the ECIBC guidelines before the start of this study. If health outcome descriptors are used in practice it should typically precede rating for importance, to ensure harmonization, accuracy and transparency of the rating exercise. To populate the draft template, the steering committee utilized information from quality of life instruments, scientific literature, and collective subject experience [22,23,24,25,26,27,28,29,30,31].

Fig. 2
figure 2

Health outcome descriptor development process. McMaster researchers developed first drafts of the health outcome descriptors using a template and relevant source material which were reviewed by the entire steering committee. Nineteen volunteers from the GDG panel provided feedback on the drafts in semi-structured interviews and/or online review. This was done through three rounds of semi-structured interviews and online written feedback. Iterative changes were made to the content and format of the health outcome descriptors based upon the observations of the steering committee and GDG feedback collected. In between rounds of feedback, a subset of GDG members also completed two online health utility assessments

Refinement of health outcome descriptor content and structure

Figure 2 summarizes our methods for reviewing the development of the health outcome descriptors (steps 4–10). After the steering committee completed internal development of the drafts, ECIBC GDG members were invited to provide feedback on the development methods, content, and structure of the health outcome descriptors by means of semi-structured interviews and online comments. All 30 GDG members were asked, and 19 participated in some capacity. Ten volunteered to participate in individual semi-structured interviews at the JRC-Ispra location and the subsequent online refinement. Separately, nine of 30 GDG members volunteered written comments only. All interviews were conducted at quarterly GDG meetings, by the same interviewer (TB), using the same list of prompting questions with transcription for analyses. Whenever possible, we repeated interviews with available panel members at different meetings to get their feedback throughout development. During the written online refinement, GDG members could actively discuss content issues with other ECIBC GDG members. We developed second drafts of all health outcome descriptors after reviewing the GDG’s feedback and making the relevant changes to the health outcome descriptors when there were factual errors or important omissions in content. When unsure whether to make changes based upon GDG feedback, the steering committee looked for supporting literature before approving the changes. We then held two additional rounds of GDG feedback (each having an interview and online component) and made edits using the same approach to develop a third and fourth draft, respectively. Throughout the development process, we ensured that all health outcome descriptors were reviewed by at least one member of the GDG. After each round of feedback with the GDG volunteers, the drafts were presented to the entire GDG for review or approval. After each presentation, the GDG discussed specific feedback and concerns about the health outcome descriptor development process with the steering committee.

Online utility rating surveys

In parallel to health outcome descriptor development, the steering committee conducted online surveys to elicit health utilities from the GDG for the 24 health outcomes using a VAS. The purpose of this exercise was to validate health outcome descriptors for evaluating the health utility of health outcomes. On the 0 to 100 VAS, 0 was anchored at “dead” and 100 at “full health” [18, 19]. The steering committee administered two surveys to the entire GDG immediately after development of the second and third health outcome descriptor drafts, respectively. Each survey was to be completed individually. Thus, by design, the GDG members that participated rated the health utility of each health outcome twice (once per survey). The most current versions of the health outcome descriptors were used to describe all health outcomes in the surveys, including the VAS anchors. The steering committee made iterative changes to the survey instructions based upon thematic analysis of the GDG’s interview feedback.

Data analysis

We conducted thematic analysis of the transcribed GDG interviews and utility surveys in six steps [32] using NVIVO version 11 software. First, two McMaster GRADE Centre researchers (TB, GPM) reviewed the interview transcripts and survey feedback. Second, each reviewer independently coded the material. Third, coding was reviewed to identify common themes. Care was taken to note the respective timing of the themes in development, and how they changed over time. Fourth, the two reviewers met to pool the themes and ensure that the codes were appropriate for each theme, and then they discussed and agreed on the refinement of the themes. Finally, the first author applied the themes during manuscript drafting for review by the steering committee.

We conducted all quantitative analyses of the health utility ratings using IBM SPSS version 20. For the descriptive analysis, we calculated the outcome-specific mean utility ratings per survey, and corresponding standard deviation for each health outcome descriptor. If our health outcome descriptors were effective for harmonizing the understanding of outcomes, we expected to observe a reduction in variance of mean health utility scores across outcomes. For each outcome we performed Levene’s F-tests to assess whether the variance in mean utility ratings for both surveys were equivalent to one another. The rates and outcomes were the same for both surveys, so we hypothesized that there would be less variance over time if, through the iterative process, the content of the health outcome descriptors had improved. We expected to observe an improvement in inter-rater agreement in the second utility rating survey because the changes in the health outcome descriptors would better represent the values of the panel. To assess the agreement in utility scores between raters on the VAS, we calculated the intraclass correlation coefficient (ICC) for raters in each survey using a two-way random effects model.

Results

Health outcome descriptors

We developed 24 health outcome descriptors (Fig. 3); each was approved by the ECIBC’s GDG. An example health outcome descriptor is provided in Fig. 4 and the full ECIBC guideline health outcome descriptors are presented both in the Appendix and the GRADEpro Guideline Development Tool health outcome descriptor database (ms.gradepro.org). This database already houses health outcome descriptors for nearly 100 outcomes for several conditions and developers are invited to submit their work to enhance the database [33].

Fig. 3
figure 3

List of Health outcome descriptors developed for ECIBC

Fig. 4
figure 4

Example Health outcome descriptor developed for ECIBC

ECIBC GDG interview feedback

Six, four, and four interviews were conducted after the development of the first, second, and third health outcome descriptor drafts, respectively. The thematic analysis of the semi-structured interview transcripts revealed six themes.

Theme 1: health outcome descriptor development process

Overall, most GDG members felt that the methods used to develop the health outcome descriptors in this study were appropriate. Specifically, most interviewees described the refinement process as acceptable, quick, and effective for improving the quality of the content to an acceptable level.

Despite repeated presentations at GDG meetings, participants felt that the purpose of health outcome descriptor development in the context of this study was not made clear to them. Therefore, GDG members described insufficient training on the development process and aims of health outcome descriptors as initial barriers to participating in their development.

Theme 2: comprehensibility of health outcome descriptors

Most members of the GDG felt that the wording of the health outcome descriptors became relatively clear and consistent by the end of the refinement process. Reading level and emotional sensitivity emerged as important factors for facilitating the use of health outcome descriptors by guideline end-users. Some GDG members felt that the reading level should be relatively high because end-users might feel intellectually insulted by a low reading level:

“The reading level should be increased. We cannot offend women.”

Other members suggested that the content should be at a lower reading level to facilitate use of health outcome descriptors by less educated members of the public:

“If [health outcome descriptors] are to be used by the broad public I think they need re-wording for someone of a lower literacy level.”

The panel was split regarding whether direct language and mention of negative health effects should be avoided to improve emotional sensitivity of the health outcome descriptors. There was mixed feedback about whether multiple versions of health outcome descriptors (e.g. for healthcare recipients, panel members, healthcare professionals, etc.) should be developed for a single guideline based upon the appropriateness of wording and emotional sensitivity for specific end-user populations.

Theme 3: data presentation

Throughout development, it was the opinion of the steering committee that the GDG members shied away from including information that might make the health outcome descriptors too specific (e.g. stating precise wait times, uncommon side effects of medical procedure, etc.). Some GDG members became concerned that the information in the health outcome descriptors would only be relevant to a small population of those experiencing a health outcome if the information was too specific. The use of descriptive statistics emerged as an important factor in improving the generalizability of health outcome descriptors. GDG members felt that use of the averages for representing quantitative information in the health outcome descriptors did not represent the variety of possibilities that an individual could experience for any health outcome:

“Whether it be weeks, days or months; there can be a lot of variation [in timing of symptoms]. So, it seems a bit artificial to state a specific time”

The health outcome descriptors were described as more representative when quantitative information was presented with only the minimum and maximum feasible data values, typically in the form of time periods and ranges.

Theme 4: health outcome descriptor structure & content

Overall, GDG members deemed the format of health outcome descriptors to be acceptable. All participants thought that the domains were comprehensive, presented in a logical order, and easily identifiable. However, they explained that the descriptor of the “Symptoms” domain should be changed to make it more intuitive.

Several GDG members acknowledged that the “Consequences” domain was necessary for describing any outcome. However, some felt that there was little variation across all the outcomes. However, it is likely that outcomes for a specific problem or disease and narrow interventions will incur similar consequences.

One GDG member mentioned that the “Testing and Treatment” domain was not appropriate for outcomes for screening programs and preventive efforts because healthcare recipients might not receive treatment:

“Most women that go for screening will not enter any kind of diagnostic efforts, let alone be treated. So, I find it very artificial to be reading up on health outcome descriptors that are directly related to the screening process, and then being pushed [to consider] the treatment area”

That GDG member recommended separating “Testing” and “Treatment” into two domains and explicitly stating when the domains are not relevant.

Theme 5: using health outcome descriptors

During early development, the aims and final users of the health outcome descriptors were not clearly understood by GDG members. However, as some GDG members became more familiar with health outcome descriptors they agreed that they could be useful for consolidating understanding of outcomes among guideline developers, facilitating panel discussion, and improving the transparency of guideline methods. One GDG member reflected upon the development process as follows:

“I think [health outcome descriptors] have been very valuable to the [GDG] because it has made us discuss with you, and the rest of the [GDG], what we really mean.”

There was agreement among GDG members that if health outcome descriptors are used during panel discussion, panel chairs should refer to outcome definitions. Some of the GDG felt that if health outcome descriptors were to be used externally, attaching them to the recommendations or publishing them online was important for making them available to end-users.

Theme 6: utility rating survey

Most GDG members indicated that the first online survey was problematic and difficult to complete. Much of the difficulty they described referenced the inappropriateness of the VAS anchors (“dead” and “full health”) for rating the health utility of outcomes which had emotional and psychological implications as opposed to physical (e.g. the health outcome descriptor ‘Awareness to Information’):

“The survey was problematic for me. I tried to complete it honestly but some of the [outcomes], did not lend themselves to the scale of dead and full health.”

After the first survey, it emerged that some participants were inappropriately making attribute-based comparisons (e.g. considering only physical or mental or emotional symptoms) or comparing the total number of implications described in each health outcome descriptor. The fact that a holistic strategy should be used to rate how the physical, emotional, and mental implications might affect overall health relative to the anchors was not sufficiently clear to participants Therefore, the instructions in the second survey were modified to better direct GDG members through the health utility rating process. Other comments from GDG members suggested that difficulties with the VAS may have manifested from problems with the initial outcome prioritization exercise carried out by the GDG:

“Some of [the outcomes] … why on earth are there health outcome descriptors for that? It becomes hard to rate if you don’t see [the outcome] as important”

Utility rating survey scores

2The mean utility ratings for each survey, the results of the pairwise comparison, and variability comparison are presented in Table 1. We attempted to evaluate if the health outcome descriptor revisions had important impact on the health utility ratings. Between the first and second surveys, we observed an increase in the mean scores of 14 outcomes and a decrease in 10 outcomes when results from all participants were analyzed. The variability, that is the magnitude of the standard deviation, of the ratings improved in 21 pairs and it remained similar in 2 pairs. In one health outcome descriptor the standard deviation increased slightly. The ICC for the first and second survey were 0.731 (CI 0.533 to 0.868; p < 0.01) and 0.942 (0.889 to 0.973; p < 0.01), respectively.

Table 1. Mean health utility ratings using a VAS (0 = ’Dead’, 100 = ’Full health’)

Discussion

Key findings

This case study assessed the development of 24 health outcome descriptors in the context of the European guidelines for breast cancer screening and diagnosis. Thematic analysis of GDG interview feedback revealed that our novel and succinct format was useful and flexible for describing health outcomes. This finding builds upon prior research that identified short narratives as the preferred health outcome descriptor format by healthcare recipients [19].

Strengthening GDG understanding of outcomes and improving the transparency of guideline development methods were identified as the most impactful uses for health outcome descriptors. Changes made to the descriptors after the second round of GDG feedback may have resulted in a reduction in variance of the mean health utility scores rated with the VAS. This suggests that the process of health outcome descriptor development helped consolidate the values and preferences of the GDG, which is crucial for decision-making during the development of recommendations.

GDG members described the insufficient training on health outcome descriptor development methods and the time needed for this process as barriers to their participation. This study was carried out only because we established the need to explicitly describe outcomes that had already been considered by the GDG. However, by starting the study when the outcomes had already been prioritised for some questions by the GDG, we may have caused confusion among the GDG about the purpose of health outcome descriptors. Most GDG members had only been introduced to the GRADE approach in the context of the ECIBC guidelines, and so insufficient exposure to methods for outcome generation and importance rating as well as other core guideline methods in an ever-expanding field may have further contributed to the confusion regarding health outcome descriptors. In practice, we recommend that panel members receive training on guideline methodology, including health outcome descriptor development and their purpose. In addition, health outcome descriptors should be created before outcome importance is rated.

Online feedback was an effective and easy method for refining outcome-specific content for the developer group. The GDG’s serious concerns with the content of the first drafts suggest that a multi-disciplinary group of experts, involving representatives from the guideline panel, should be involved from the very beginning of health outcome descriptor development. For future efforts, we propose that a small multidisciplinary subset of the panel (no more than four people) be selected to work with a steering committee of guideline development methodologists to create and refine drafts of each health outcome descriptor. The steering committee should oversee population of the template by panel members to ensure that the structure is appropriate. The use of online or in-person feedback from panel members is appropriate to modify content. Ultimately, we believe that the steering committee should approve health outcome descriptors to be used for decision-making in the guideline.

Opinions on the appropriate balance of wording, reading level, and emotional sensitivity for end-users were varied. More research must be done on the specific needs of different end-user populations to conclude whether multiple tailored versions of health outcome descriptors are necessary or helpful. We propose that the steering committee declare intended end-user populations at the beginning of development, and use their professional judgement to ensure that wording, reading level, and emotional sensitivity is appropriate.

Participants also described having significant difficulty with the VAS for health utility rating because they felt that the health states anchoring the scale were inappropriate for rating some of the health outcome descriptors. This was particularly true of the outcomes ‘Accessibility to Information’, ‘Awareness to Information’, ‘Participation in Screening’, ‘Informed Decision Making’, ‘Satisfaction with Decision Making’, and ‘Confidence with Decision Making’. For these outcomes, the desired and undesired effects may have been perceived as independent from any physical health status.

Difficulties with the anchor health states are further supported by the health outcome descriptor for “Other-Cause Mortality” valued with a mean health utility score of 10. Given that the health outcome descriptor had similar content to the anchor health state “Dead” (which was visible during the rating exercise), it was expected to be valued at 0. The rating of 10 suggests that either there were some difficulties in completing the exercise, or it may have been due to a simple error. Relevant literature on the VAS describes it as being more acceptable and practical than other validated scaling methods [34]. Furthermore, the health states “dead” and “full health” are widely-used as anchors for scaling methods [35]. Given this, it is most likely that the difficulty with the survey was due to insufficient instructions, failure to understand instructions, or context bias resulting from rating the health utility of all health outcomes in the same survey. This was our reasoning for changing the instructions between surveys.

Although one participant provided feedback that the testing and treatment domain was inappropriate for outcomes related to preventive interventions, we did not make changes to the format. We believe that testing and treatment should be considered jointly and connected to healthcare interventions on a pathway that follows from a health state, even if no testing or treatment follows which in itself is important information.

Limitations and strengths

A limitation of this study was that development of health outcome descriptors for most of the outcomes occurred after the GDG had already rated them for importance and included them in GRADE evidence tables. The development of the health outcome descriptors during the guideline development process may have caused confusion about the need and purpose of them, although the development need resulted precisely from disagreement arising about definitions of health outcomes.

Furthermore, health outcome descriptor development occurred in the context of only one breast cancer screening guideline, which limits our generalization to other panels and healthcare topics. Finally, for the utility rating this study had a small sample size which reduced the statistical power of our variance analysis.

A strength of this study is that all data was collected from a real-life guideline panel, which is rare among published literature on outcome descriptors. By conducting this case study in the context of a real guideline panel, our results can be used to inform outcome descriptor standardization efforts for guideline development, where we originally identified the problem of heterogeneity. We also carefully planned health outcome descriptor development methods and interaction with GDG members to capture reliable feedback at each stage of development. Collectively, our planning and analysis ensure that the results from this study can be used to inform all stages of health outcome descriptor development.

Implications for practice

This study’s findings highlight the attitudes towards health outcome descriptor development and use among guideline panel members. Results suggest that guideline developers using health outcome descriptors should work with a multidisciplinary subgroup of panel members in a few rounds with online or in person feedback, to develop first drafts and final versions of the health outcome descriptors respectively. Prior to development, guideline panel members should be well informed, prepared, and trained on development methods and the GRADE approach accordingly. Our findings may help inform and guide future development of health outcome descriptors for guideline development. The ECIBC guideline health outcome descriptors will be used to better inform users of the outcomes that were considered in each of the healthcare questions by publishing them on the ECIBC website and they will also be used in decision support tools.

Implications for research

Further research will show if multiple versions (e.g. policy maker, healthcare professional, etc.) of the health outcome descriptors for different target audiences are necessary, and how the reading level and wording of each version might be tailored to the different end-user populations. Our preference is that simple descriptors, that provide a common language for those providing health care and those receiving that care, should be used. A priori, there seems to be no logical reasons for a different language for different users. Using a common language will reduce the probability that misunderstandings, across different end-users, will occur.

For the use of health outcome descriptors to become more common in guideline development, there is a need to determine how guideline end-users make use of them, so instructions for their development can be altered accordingly. Most importantly, researchers should investigate whether health outcome descriptors do improve transparency and understanding of guideline methods for end-users, as some GDG members in this study suggested. Additional research efforts can build upon the present study by examining attitudes towards health outcome descriptor use by end-users, particularly healthcare recipients who may not have extensive medical knowledge [36]. Other research efforts might focus on how health outcome descriptors might be adapted for use for other purposes including, but not limited to, research and education.

Researchers should also concentrate efforts on determining the reliability of the VAS when rating the utility of health outcome descriptors, because we were unable to draw meaningful conclusions about this due to the limited statistical power in this study.

Conclusion

This study describes the experiences of health outcome descriptor development for a health care guideline and provides guidance for future efforts in this area. Our standardized health outcome descriptor format may be useful for facilitating a common understanding of the outcomes chosen for the healthcare questions covered in a guideline, and thus improving the transparency of the guideline methods used. GDG members used health outcome descriptors with the VAS to improve precision of health utility ratings, but more research must be done to validate this method and reduce measurement error.