Dataset Information

How well do guidelines incorporate evidence on patient preferences?

ABSTRACT:

Background

Clinical practice guidelines (CPG) are meant to consider important values such as patient preferences.

Objective

To assess how well clinical practice guidelines (CPGs) integrate evidence on patient preferences compared with that on treatment effectiveness.

Design

A cross-sectional review of a listing in 2006 of CPGs judged to be the best in their fields by an external joint government and medical association body.

Study selection

Exclusion criterion was unavailability in electronic format. Sixty-five of 71 listed CPGs met selection criteria.

Measurements

Two instruments originally constructed to evaluate the overall quality of CPGs were adapted to specifically assess the quality of integrating information on patient preference vs. treatment effectiveness. Counts of words and references in each CPG associated with patient preferences vs. treatment effectiveness were performed. Two reviewers independently assessed each CPG.

Main results

Based on our adapted instruments, CPGs scored significantly higher (p < 0.001) on the quality of integrating treatment effectiveness compared with patient preferences evidence (mean instrument one scores on a scale of 0.25 to 1.00: 0.65 vs. 0.43; mean instrument two scores on a scale of 0 to 1: 0.58 vs. 0.18). The average percentage of the total word count dedicated to treatment effectiveness was 24.2% compared with 4.6% for patient preferences. The average percentage of references citing treatment effectiveness evidence was 36.6% compared with 6.0% for patient preferences.

Conclusion

High quality CPGs poorly integrate evidence on patient preferences. Barriers to incorporating preference evidence into CPGs should be addressed.

SUBMITTER: Chong CA

PROVIDER: S-EPMC2710487 | biostudies-literature | 2009 Aug

REPOSITORIES: biostudies-literature

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Publications

How well do guidelines incorporate evidence on patient preferences?

Chong Christopher A K Y CA Chen Ing-je IJ Naglie Gary G Krahn Murray D MD

Journal of general internal medicine 20090423 8

<h4>Background</h4>Clinical practice guidelines (CPG) are meant to consider important values such as patient preferences.<h4>Objective</h4>To assess how well clinical practice guidelines (CPGs) integrate evidence on patient preferences compared with that on treatment effectiveness.<h4>Design</h4>A cross-sectional review of a listing in 2006 of CPGs judged to be the best in their fields by an external joint government and medical association body.<h4>Study selection</h4>Exclusion criterion was un ...[more]

PMID: 19387746

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Project description:Background: Guidelines based on patient preferences differ from those developed solely by clinicians and may promote patient adherence to guideline recommendations. There is scant evidence on how to develop patient-informed guidelines. This study aimed to describe how guideline developers identify, incorporate and report patient preferences.Methods: We employed a descriptive cross-sectional survey design. Eligible organizations were non-profit agencies who developed at least one guideline in the past five years and had considered patient preferences in guideline development. We identified developers through the Guidelines International Network and publicly-available guideline repositories, administered the survey online, and used summary statistics to report results.Results: The response rate was 18.3% (52/284). Respondents included professional societies, and government, academic, charitable and healthcare delivery organizations from 18 countries with at least 1 to ?6?years of experience generating patient-informed guidelines. Organizations most frequently identified preferences through patient panelists (86.5%) and published research (84.6%). Most organizations (48, 92.3%) used multiple approaches to identify preferences (median 3, range 1 to 5). Most often, organizations used preferences to generate recommendations (82.7%) or establish guideline questions (73.1%). Few organizations explicitly reported preferences; instead, they implicitly embedded preferences in guideline recommendations (82.7%), questions (73.1%), or point-of-care communication tools (61.5%). Most developers had little capacity to generate patient-informed guidelines. Few offered training to patients (30.8%), or had dedicated funding (28.9%), managers (9.6%) or staff (9.6%). Respondents identified numerous barriers to identifying preferences. They also identified processes, resources and clinician- and patient-strategies that can facilitate the development of patient-informed guidelines. In contrast to identifying preferences, developers noted few approaches for, or barriers or facilitators of incorporating or reporting preferences.Conclusions: Developers emphasized the need for knowledge on how to identify, incorporate and report patient preferences in guidelines. In particular, how to use patient preferences to formulate recommendations, and transparently report patient preferences and the influence of preferences on guidelines is unknown. Still, insights from responding developers may help others who may be struggling to generate guidelines informed by patient preferences.

Project description:OBJECTIVE:Many treatment decisions are preference-sensitive and call for shared decision-making, notably when benefits are limited or uncertain, and harms impact quality of life. We explored if clinical practice guidelines (CPGs) acknowledge preference-sensitive decisions in how they motivate and phrase their recommendations. DESIGN:We performed a qualitative analysis of the content of CPGs and verified the results in semistructured interviews with CPG panel members. SETTING:Dutch oncology CPGs issued in 2010 or later, concerning primary treatment with curative intent. PARTICIPANTS:14 CPG panel members. MAIN OUTCOMES:For treatment recommendations from six CPG modules, two researchers extracted the following: strength of recommendation in terms of the Grading of Recommendations Assessment, Development and Evaluation and its consistency with the CPG text; completeness of presentation of benefits and harms; incorporation of patient preferences; statements on the panel's benefits-harm trade-off underlying recommendation; and advice on patient involvement in decision-making. RESULTS:We identified 32 recommendations, 18 were acknowledged preference-sensitive decisions. Three of 14 strong recommendations should have been weak based on the module text. The reporting of benefits and harms, and their probabilities, was sufficiently complete and clear to inform the strength of the recommendation in one of the six modules only. Numerical probabilities were seldom presented. None of the modules presented information on patient preferences. CPG panel's preferences were not made explicit, but appeared to have impacted 15 of 32 recommendations. Advice to involve patients and their preferences in decision-making was given for 20 recommendations (14 weak). Interviewees confirmed these findings. Explanations for lack of information were, for example, that clinicians know the information and that CPGs must be short. Explanations for trade-offs made were cultural-historical preferences, compliance with daily care, presumed role of CPGs and lack of time. CONCLUSIONS:The motivation and phrasing of CPG recommendations do not stimulate choice awareness and a neutral presentation of options, thus hindering shared decision-making.

Project description:BackgroundCancer is increasingly being treated as a chronic disease rather than an acute one-time illness. Additionally, oral anticancer therapies, as opposed to intravenous chemotherapy, are now available for an increasing number of cancer indications. Mobile health (mHealth) apps for use on mobile devices (eg, smartphones or tablets) are designed to help patients with medication adherence, symptom tracking, and disease management. Several previous literature reviews have been conducted regarding mHealth apps for cancer. However, these studies did not address patient preferences for the features of cancer mHealth apps.ObjectiveThe primary aim was to review the scientific literature that describes the features and functions of mHealth apps designed for cancer self-management.MethodsAs the purpose of this review was to explore the depth and breadth of research on mHealth app features for cancer self-management, a scoping review methodology was adopted. Four databases were used for this review: PubMed/MEDLINE, Embase, CINAHL, and PsycINFO. Citation and reference searches were conducted for manuscripts meeting the inclusion criteria. A gray literature search was also conducted. Data extracted from manuscripts included author, title, publication date, study type, sampling type, cancer type, treatment, age of participants, features, availability (free or subscription), design input, and patient preferences. Finally, the features listed for each app were compared, highlighting similarities across platforms as well as features unique to each app.ResultsAfter the removal of duplicates, 522 manuscripts remained for the title and abstract review, with 51 undergoing full-text review. A total of 7 manuscripts (referred to as studies hereafter) were included in the final scoping review. App features described in each study varied from 2 to 11, with a median of 4 features per app. The most reported feature was a symptom or side effect tracker, which was reported in 6 studies. Two apps specified the inclusion of patients and health care providers during the design, while 1 app noted that IT and communications experts provided design input. The utility of the apps for end users was measured in several ways, including acceptability (measuring the end users' experience), usability (assessing the functionality and performance by observing real users completing tasks), or qualitative data (reports from end users collected from interviews or focus groups).ConclusionsThis review explored the literature on cancer mHealth apps. Popular features within these mHealth apps include symptom trackers, cancer education, and medication trackers. However, these apps and features are often developed with little input from patients. Additionally, there is little information regarding patient preferences for the features of existing apps. While the number of cancer-related apps available for download continues to increase, further exploration of patient preferences for app features could result in apps that better meet patient disease self-management needs.

Dataset Information

How well do guidelines incorporate evidence on patient preferences?

Background

Objective

Design

Study selection

Measurements

Main results

Conclusion

Publications

How well do guidelines incorporate evidence on patient preferences?

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