George Michel

Bridging the Guideline Implementation Gap: A Systematic, Document-Centered Approach to Guideline Implementation

OBJECTIVE A gap exists between the information contained in published clinical practice guidelines and the knowledge and information that are necessary to implement them. This work describes a process to systematize and make explicit the translation of document-based knowledge into workflow-integrated clinical decision support systems. DESIGN This approach uses the Guideline Elements Model (GEM) to represent the guideline knowledge. Implementation requires a number of steps to translate the knowledge contained in guideline text into a computable format and to integrate the information into clinical workflow. The steps include: (1) selection of a guideline and specific recommendations for implementation, (2) markup of the guideline text, (3) atomization, (4) deabstraction and (5) disambiguation of recommendation concepts, (6) verification of rule set completeness, (7) addition of explanations, (8) building executable statements, (9) specification of origins of decision variables and insertions of recommended actions, (10) definition of action types and selection of associated beneficial services, (11) choice of interface components, and (12) creation of requirement specification. RESULTS The authors illustrate these component processes using examples drawn from recent experience translating recommendations from the National Heart, Lung, and Blood Institutes guideline on management of chronic asthma into a workflow-integrated decision support system that operates within the Logician electronic health record system. CONCLUSION Using the guideline document as a knowledge source promotes authentic translation of domain knowledge and reduces the overall complexity of the implementation task. From this framework, we believe that a better understanding of activities involved in guideline implementation will emerge.

The Yale Guideline Recommendation Corpus: A representative sample of the knowledge content of guidelines

OBJECTIVE To develop and characterize a large, representative sample of guideline recommendations that can be used to better understand how current recommendations are written and to test the adequacy of guideline models. We refer to this sample as the Yale Guideline Recommendation Corpus (YGRC). METHOD To develop the YGRC, we extracted recommendations from guidelines downloaded from the National Guideline Clearinghouse (NGC). We evaluated the representativeness of the YGRC by comparing the frequency of use of controlled vocabulary terms in the YGRC sample and in the NGC. We examined semantic and formatting indicators that were used to denote recommendation statements. RESULTS In the course of reviewing 7527 recommendation statements, we extracted 1275 recommendations from the NGC and characterized the guidelines from which they were derived. Both semantic and formatting indicators were used inconsistently to denote recommendations. Recommendation statements were not reliably identifiable in 31.6% (310/982) of the guidelines and many recommendations were not executable as written. We also found variability and inconsistency in the way strength of recommendation is currently reported. Over half of the recommendations (52.7%), did not indicate strength, while 6.5% inaccurately indicated strength. CONCLUSION The YGRC provides a representative sample of current guideline recommendations and demonstrates considerable variability and inconsistency in the way recommendations are written and in the way the recommendation strength is currently reported.

Writing clinical practice guidelines in controlled natural language

Clinicians could benefit from decision support systems incorporating the knowledge contained in clinical practice guidelines. However, the unstructured form of these guidelines makes them unsuitable for formal representation. To address this challenge we translated a complete set of pediatric guideline recommendations into Attempto Controlled English (ACE). One experienced pediatrician, one physician and a knowledge engineer assessed that a suitably extended version of ACE can accurately and naturally represent the clinical concepts and the proposed actions of the guidelines. Currently, we are developing a systematic and replicable approach to authoring guideline recommendations in ACE.

How “should” we write guideline recommendations? Interpretation of deontic terminology in clinical practice guidelines: survey of the health services community

Objective To describe the level of obligation conveyed by deontic terms (words such as “should”, “may”, “must” and “is indicated”) commonly found in clinical practice guidelines. Design Cross-sectional electronic survey. Setting A clinical scenario was developed by the researchers, and recommendations containing 12 deontic terms and phrases were presented to the participants. Participants All 1332 registrants of the 2008 annual conference of the US Agency for Healthcare Research and Quality. Main outcome measures Participants indicated the level of obligation they believed guideline authors intended by using a slider mechanism ranging from “No obligation” (leftmost position recorded as 0) to “Full obligation” (rightmost position recorded as 100.) Results 445/1332 registrants (36%) submitted the on-line survey; 254/445 (57%) reported that they have experience in developing clinical practice guidelines; 133/445 (30%) indicated that they provide healthcare. “Must” conveyed the highest level of obligation (median=100) and least amount of variability (interquartile range=5.) “May” (median=37) and “may consider” (median=33) conveyed the lowest levels of obligation. All other terms conveyed intermediate levels of obligation characterised by wide and overlapping interquartile ranges. Conclusions Members of the health services community believe guideline authors intend variable levels of obligation when using different deontic terms within practice recommendations. Ranking of a subset of terms by intended level of obligation is possible. Matching deontic terminology to the intended recommendation strength can help standardise the use of deontic terminology by guideline developers.

Validation of a 52-gene risk profile for outcome prediction in patients with idiopathic pulmonary fibrosis: an international, multicentre, cohort study

Background The clinical course of Idiopathic Pulmonary Fibrosis (IPF) is unpredictable. Clinical prediction tools are not accurate enough to predict disease outcomes. Methods All-comers with Idiopathic Pulmonary Fibrosis diagnosis were enrolled in a six-cohort study. Peripheral blood mononuclear cells or whole blood was collected at baseline from 425 participants and during follow up from 98 patients. The 52-gene signature was measured by the nCounter® analysis system in four cohorts and extracted from microarray data in two others. The Scoring Algorithm for Molecular Subphenotypes (SAMS) was used to classify patients into low or high risk groups based on a 52-gene signature. Mortality and transplant-free survival were studied using Competing risk and Cox proportional-hazard models, respectively. Time course data and response to anti-fibrotic drugs were analyzed using linear mixed-effect models. Findings The application of SAMS to the 52-gene signature identified two groups of IPF patients (low and high risk) with significant differences in mortality or transplant-free survival in each of the six cohorts (HR 2·03–4·37). Pooled data revealed similar results for mortality (HR:2·18, 95%CI:1·53–3·09, P<0·0001) or transplant-free survival (HR:2·04, 95%CI: 1·52–2·74, P<0·0001). Adding 52-gene risk profiles to the Gender, Age and Physiology (GAP) index significantly improved its mortality predictive accuracy. Temporal changes in SAMS scores were associated with changes in forced vital capacity (FVC) in two cohorts. Untreated patients did not shift their risk profile over time. A simultaneous increase in up score and decrease in down score was predictive of transplant-free survival (HR:3·18· 95%CI 1·16, 8·76, P=0·025) in the Pittsburgh cohort. A simultaneous decrease in up score and increase in down score after initiation of anti-fibrotic drugs was associated with a significant (P=0·005) improvement in FVC in the Yale cohort. Interpretation The peripheral blood 52-gene expression signature is predictive of outcome in patients with IPF. The potential value of the 52-gene signature in predicting response to therapy should be determined in prospective studies.

Preference phenotypes to facilitate shared decision-making in rheumatoid arthritis

Objective Implementing treat-to-target (TTT) strategies requires that patients with rheumatoid arthritis (RA) and their rheumatologists decide on how best to escalate care when indicated. The objective of this study was to develop preference phenotypes to facilitate shared decision-making at the point of care for patients failing methotrexate monotherapy. Methods We developed a conjoint analysis survey to measure the preferences of patient with RA for triple therapy, biologics and Janus kinase (JAK) inhibitors. The survey included seven attributes: administration, onset, bothersome side effects, serious infection, very rare side effects, amount of information and cost. Each choice set (n=12) included three hypothetical profiles. Preference phenotypes were identified by applying latent class analysis to the conjoint data. Results 1273 participants completed the survey. A five-group solution was chosen based on progressively lower values of the Akaike and Bayesian information criteria. Members of the largest group (group 3: 38.4%) were most strongly impacted by the cost of the medication. The next largest group (group 1: 25.8%) was most strongly influenced by the risk of bothersome side effects. Members of group 2 (11.2%) were also risk averse, but were most concerned with the risk of very rare side effects. Group 4 (6.6%) strongly preferred oral over parenteral medications. Members of group 5 (18.0%) were most strongly and equally influenced by onset of action and the risk of serious infections. Conclusions Treatment preferences of patients with RA can be measured and represented by distinct phenotypes. Our results underscore the variability in patients’ values and the importance of using a shared decision-making approach to implement TTT.

The Impact of Information Presentation Format on Preferencefor Total Knee Replacement Surgery

Patients have a poor understanding of outcomes related to total knee replacement (TKR) surgery, with most patients underestimating the potential benefits and overestimating the risk of complications. In this study, we sought to compare the impacts of descriptive information alone or in combination with an icon array, experience condition (images), or spinner on participants’ preference for TKR.

Preference phenotypes can be used to support shared decision-making at point-of-care for patients with rheumatoid arthritis: A proof of concept study

In this proof‐of‐concept study, we sought to evaluate whether a value clarification tool enabling patients to view a set of rheumatoid arthritis (RA) treatment preference phenotypes could be used to support shared decision‐making at the point‐of‐care.