Clinical guidelines have been shown to improve the quality of medical care and to reduce its costs. However, most guidelines exist in a free-text representation and, without automation, are not sufficiently accessible to clinicians at the point of care. A prerequisite for automated guideline application is a machine-comprehensible representation of the guidelines. In this study, we designed and implemented a scalable architecture to support medical experts and knowledge engineers in specifying and maintaining the procedural and declarative aspects of clinical guideline knowledge, resulting in a machine comprehensible representation. The new framework significantly extends our previous work on the Digital electronic Guidelines Library (DeGeL) The current study designed and implemented a graphical framework for specification of declarative and procedural clinical knowledge, Gesher. We performed three different experiments to evaluate the functionality and usability of the major aspects of the new framework: Specification of procedural clinical knowledge, specification of declarative clinical knowledge, and exploration of a given clinical guideline. The subjects included clinicians and knowledge engineers (overall, 27 participants). The evaluations indicated high levels of completeness and correctness of the guideline specification process by both the clinicians and the knowledge engineers, although the best results, in the case of declarative-knowledge specification, were achieved by teams including a clinician and a knowledge engineer. The usability scores were high as well, although the clinicians’ assessment was significantly lower than the assessment of the knowledge engineers.
Medical informatics; clinical guidelines; decision support systems; knowledge representation; knowledge acquisition; knowledge bases; ontologies; information retrieval; human computer interaction; artificial intelligence; digital libraries; service oriented architecture.
The Digital Electronic Guideline Library (DeGeL) is a Web-based framework and a set of distributed tools that facilitate gradual conversion of clinical guidelines from free text, through semi-structured text, to a fully structured, executable representation. Thus, guidelines exist in a hybrid, multiple-format representation The three formats support increasingly sophisticated computational tasks. The tools perform semantic markup, classification, search, and browsing, and support computational modules that we are developing, for run-time application and retrospective quality assessment. We describe the DeGeL architecture and its collaborative-authoring authorization model, which is based on (1) multiple medical-specialty authoring groups, each including a group manager who controls group authorizations, and (2) a hierarchical authorization model based on the different functions involved in the hybrid guideline-specification process. We have implemented the core modules of the DeGeL architecture and demonstrated distributed markup and retrieval using the knowledge roles of two guidelines ontologies (Asbru and GEM). We are currently evaluating several of the DeGeL tools.
Automated support for guideline-based care would be enhanced considerably by a standard representation of clinical guidelines. To faciliate use and reuse, we suggest a representation that includes the explicit intentions of the guideline's author. These intentions include the desirable actions of the care provider and the patient states to be achieved before, during, and after the administration of the guideline. Intentions are temporal patterns of provider actions or patient states to be maintained, achieved, or avoided. We view automated support as a collaborative effort of the health-care provider and an automated assistant and involves several different tasks. We defined the syntax and, the semantics of a text-based language (ASBRU) for representation and annotation of clinical guidelines. The language supports maintenance of the automated assistant's knowledge base and could improve the quality and flexibility of the automated assistant's recommendations. In the ASGAARD project, we are developing reasoning mechanisms that use the ASBRU language for execution and critiquing tasks in conjunction with online electronic patient medical records.
Formalization of a clinical guideline for purposes of automated application
and quality assessment mainly involves conversion of its free-text
representation into a machine comprehensible representation, i.e., a
formal language, thus enabling automated support. The main issues involved
in this process are related to the collaboration between the expert
physician and the knowledge engineer. We introduce GESHER - a graphical
framework for specification of clinical guidelines at multiple representation
levels. The GESHER architecture facilitates incremental
specification through a set of views adapted to each representation level, enabling
this process to proceed smoothly and in a transparent fashion, fostering
extensive collaboration among the various types of users. The
GESHER framework supports specification of guidelines at multiple
representation levels, in more than one specification language, and
uses the DeGeL digital guideline library architecture as its knowledge
base. The GESHER architecture also uses a temporal abstraction knowledge
base to store its declarative knowledge, and a standard medical-vocabularies
server for generic specification of key terms, thus enabling
reuse of the specification at multiple sites.
Clinical practice guidelines (CPGs) are means to provide evidence-based medical knowledge. In order to make up-to-date “best” scientific evidence available these documents need to be updated on an ongoing basis. An effective method to accomplish this aim is offered by the so-called “living guidelines”: Living guidelines are documents presenting up-to-date and state-of-the-art knowledge to practitioners. To have guidelines implemented by computer-support they have to be formalized in a computer-interpretable form in a first step. Due to the complexity of such formats the formalization process is burdensome and time-consuming. Automating parts of the modeling process and, consequently, modeling updates of these guideline documents are demanded.
Methods and material
The LASSIE methodology supports this task by formalizing guidelines in several steps from the textual form to the guideline representation language Asbru using a document-centric approach. LASSIE uses information extraction techniques to semi-automatically accomplish these steps. We apply LASSIE to support the implementation of living guidelines.
Based on a living guideline published by the Scottish Intercollegiate Guidelines Network (SIGN) we show that adaptations of previously formalized guidelines can be accomplished easily and fast. Thereby, the different versions of guideline documents are compared and updates are identified. Due to the traceable formalization method of linking text parts and their corresponding formal models, we are able to inherit unchanged models from previously formalized versions. Thus, we only need to formalize updated text parts using the semi-automatic formalization method LASSIE.
We propose a simple, time-saving, but effective method called LASSIE to formalize new guideline versions of previously formalized CPGs. Furthermore, models that have been added or modified by knowledge engineers in previous versions can also be transferred easily. This will result in a faster implementation of new guideline versions also known as living guidelines to provide up-to-date knowledge necessary for accomplishing the daily work of health care professionals.
Information extraction; Clinical practice guidelines; Living guidelines; Computer-interpretable guidelines; Guideline representation; Treatment processes; Asthma
Implementing Computer-Interpretable Guidelines (CIGs) in active computer-based decision support systems promises to improve the acceptance and application of guidelines in daily practice. The model and underlying language are the core characteristics of every CIG approach. However, currently no standard model or language has been accepted by the CIG community. This aim of this chapter is to provide an overview of well-known approaches and to formulate a set of (minimal) requirements that can be used in the process of developing new CIG approaches or improving existing ones. It presents five CIG approaches (the Arden Syntax, GLIF, PROforma, Asbru and EON), followed by a general discussion of the strong points of each approach as well as their implications for future research.
Computer-interpretable Guidelines; Knowledge Representation; Decision Support Systems
Decision-support systems based on clinical practice guidelines can support
physicians and other health-care personnel in the process of following
best practice consistently. A knowledge-based approach to represent
guidelines makes it possible to encode computer-interpretable guidelines
in a formal manner, perform consistency checks, and use the guidelines
directly in decision-support systems.
Decision-support authors and guideline users require guidelines in human-readable
formats in addition to computer-interpretable ones (e.g., for
guideline review and quality assurance). We propose a new document-oriented
information architecture that combines knowledge-representation
models with electronic and paper documents. The approach integrates
decision-support modes with standard document formats to create a combined
clinical-guideline model that supports on-line viewing, printing, and
Computerization of clinical practice guidelines (CPGs) has been proposed as one solution to enhance the use of guidelines in influencing standard clinical care. However, the conversion of text guidelines to the format required by a computer program is a major barrier. Clinicians who best understand the content of CPGs are typically ill equipped to convert textual guidelines into a computer accessible format. The potential of knowledge acquisition tools to assist in this process has been documented in the literature. In this paper we describe an application prototype, the Guideline Entry Wizard, created to assist in the conversion of text CPGs to a structured format within a relational database. We have tested this application through the input of information from several CPG. The application is a prototype for a more advanced tool. We have used this prototype to enter several CPGs and have demonstrated its effectiveness in inputting guideline content into a knowledge base.
Languages used to specify computer-interpretable guidelines (CIGs) differ in their approaches to addressing particular modeling challenges. The main goals of this article are: (1) to examine the expressive power of CIG modeling languages, and (2) to define the differences, from the control-flow perspective, between process languages in workflow management systems and modeling languages used to design clinical guidelines.
The pattern-based analysis was applied to guideline modeling languages Asbru, EON, GLIF, and PROforma. We focused on control-flow and left other perspectives out of consideration.
We evaluated the selected CIG modeling languages and identified their degree of support of 43 control-flow patterns. We used a set of explicitly defined evaluation criteria to determine whether each pattern is supported directly, indirectly, or not at all.
PROforma offers direct support for 22 of 43 patterns, Asbru 20, GLIF 17, and EON 11. All four directly support basic control-flow patterns, cancellation patterns, and some advance branching and synchronization patterns. None support multiple instances patterns. They offer varying levels of support for synchronizing merge patterns and state-based patterns. Some support a few scenarios not covered by the 43 control-flow patterns.
CIG modeling languages are remarkably close to traditional workflow languages from the control-flow perspective, but cover many fewer workflow patterns. CIG languages offer some flexibility that supports modeling of complex decisions and provide ways for modeling some decisions not covered by workflow management systems. Workflow management systems may be suitable for clinical guideline applications.
A major obstacle in deploying computer-based clinical guidelines at the point of care is the variability of electronic medical records and the consequent need to adapt guideline modeling languages, guideline knowledge bases, and execution engines to idiosyncratic data models in the deployment environment. This paper reports an approach, developed jointly by researchers at Newcastle and Stanford, where guideline models are encoded assuming a uniform virtual electronic medical record and guideline-specific concept ontologies. For implementing a guideline-based decision-support system in multiple deployment environments, we created mapping knowledge bases to link terms in the concept ontology with the terminology used in the deployment systems. Mediation components use these mapping knowledge bases to map data in locally deployed medical record architectures to the virtual medical record. We discuss the possibility of using the HL7 Reference Information Model (RIM) as the basis for a standardized virtual medical record, showing how this approach also complies with the European pre-standard ENV13606 for electronic healthcare record communication.
Clinical practice guidelines are increasingly important for improving the quality and the process of healthcare delivery. Unfortunately, most guidelines are available only in a text-based format, which is difficult to integrate into clinical practice. Computers can facilitate guideline integration into clinical practice; however, this migration to computers requires translating text into intermediary representations. One type of representation that is readily adaptable for computerization is a linear algorithm. This paper describes a systematic process to convert text-based clinical practice guidelines into a linear algorithm with structured content, as an intermediate step to electronic implementation. The process includes: 1) defining applicability criteria, 2) identifying entry points, 3) defining decision points, 4) defining actions, 5) creating a linear algorithm that links decision points and actions, and 6) adding supporting resources. This process has been used successfully to prepare more than two dozen guidelines for computerization. It has been tested by several physicians and informaticians and shown to be transferable to various user groups. The availability of a systematic process to convert text-based guidelines into a structured intermediary format for electronic implementation can facilitate the computerization of guidelines and can inform guideline content developers regarding the critical elements that need to be explicitly stated in guidelines to support electronic implementation.
Practice guidelines are an integral part of evidence-based
health care delivery. When the authors decided to install the clinical
documentation component of an electronic health record in a nurse practitioner
faculty practice, however, they found that they lacked the resources to
integrate it immediately with other systems and components that would support
the processing of clinical rules. They were thus challenged to devise an
initial approach for decision support related to clinical practice guidelines
that did not include interfacing with an inference engine and set of decision
rules. The authors developed a prototypic application within the WAVE
electronic health record that demonstrates the feasibility of representing a
guideline as structured encoded text organized into an online
patient-encounter template. Although this approach may be more broadly
applicable, it is described within the context of the management of diabetes
mellitus by nurse practitioners. The advantages of the approach relate
primarily to the integration of the guideline recommendations with the
encounter form, the online interaction of the clinician with the system, and
the ease of creation and modification of the guideline-based encounter form.
However, there are several limitations of the current approach as a result of
the inability to do inference and the lack of integration with
patient-specific data to trigger specific rules.
Clinical guidelines are usually written as text documents that are meant for human consumption. Implementing clinical guidelines as decision-support systems that deliver patient-specific advice at the point of care could increase the effectiveness of clinical guidelines. Several researchers studied the transition from narrative guidelines to computer-interpretable guidelines and have identified specific barriers to guideline implementation. GuideLine Implementability Appraisal (GLIA) is a comprehensive instrument for identifying such barriers, such that they could be revised. We used the GLIA instrument to appraise a historic thyroid nodule guideline that is now being reviewed by the American Association of Clinical Endocrinologists. Our analysis uncovered new guideline implementation barriers related to control-flow that we integrated into GLIA.
In social insurance, the evaluation of work disability is becoming stricter as priority is given to the resumption of work, which calls for a guarantee of quality for these evaluations. Evidence-based guidelines have become a major instrument in the quality control of health care, and the quality of these guidelines' development can be assessed using the AGREE instrument. In social insurance medicine, such guidelines are relatively new. We were interested to know what guidelines have been developed to support the medical evaluation of work disability and the quality of these guidelines.
Five European countries that were reported to use guidelines were approached, using a recent inventory of evaluations of work disability in Europe. We focused on guidelines that are disease-oriented and formally prescribed in social insurance medicine. Using the AGREE instrument, these guidelines were appraised by two researchers. We asked two experts involved in guideline development to indicate if they agreed with our results and to provide explanations for insufficient scores.
We found six German and sixteen Dutch sets of disease-oriented guidelines in official use. The AGREE instrument was applicable, requiring minor adaptations. The appraisers reached consensus on all items. Each guideline scored well on 'scope and purpose' and 'clarity and presentation'. The guidelines scored moderately on 'stakeholder involvement' in the Netherlands, but insufficiently in Germany, due mainly to the limited involvement of patients' representatives in this country. All guidelines had low scores on 'rigour of development', which was due partly to a lack of documentation and of existing evidence. 'Editorial independence' and 'applicability' had low scores in both countries as a result of how the production was organised.
Disease-oriented guidelines in social insurance medicine for the evaluation of work disability are a recent phenomenon, so far restricted to Germany and the Netherlands. The AGREE instrument is suitably applicable to assess the quality of guideline development in social insurance medicine, but some of the scoring rules need to be adapted to the context of social insurance. Existing guidelines do not meet the AGREE criteria to a sufficient level. The way patients' representatives can be involved needs further discussion. The guidelines would profit from more specific recommendations and, for providing evidence, more research is needed on the functional capacity of people with disabilities.
To demonstrate the feasibility of capturing the knowledge required to create guideline recommendations in a systematic, structured, manner using a software assistant. Practice guidelines constitute an important modality that can reduce the delivery of inappropriate care and support the introduction of new knowledge into clinical practice. However, many guideline recommendations are vague and underspecified, lack any linkage to supporting evidence or documentation of how they were developed, and prove to be difficult to transform into systems that influence the behavior of care providers.
The BRIDGE-Wiz application (Building Recommendations In a Developer's Guideline Editor) uses a wizard approach to address the questions: (1) under what circumstances? (2) who? (3) ought (with what level of obligation?) (4) to do what? (5) to whom? (6) how and why? Controlled natural language was applied to create and populate a template for recommendation statements.
The application was used by five national panels to develop guidelines. In general, panelists agreed that the software helped to formalize a process for authoring guideline recommendations and deemed the application usable and useful.
Use of BRIDGE-Wiz promotes clarity of recommendations by limiting verb choices, building active voice recommendations, incorporating decidability and executability checks, and limiting Boolean connectors. It enhances transparency by incorporating systematic appraisal of evidence quality, benefits, and harms. BRIDGE-Wiz promotes implementability by providing a pseudocode rule, suggesting deontic modals, and limiting the use of ‘consider’.
Users found that BRIDGE-Wiz facilitates the development of clear, transparent, and implementable guideline recommendations.
Controlled natural language; controlled terminologies and vocabularies; developing/using clinical decision support (other than diagnostic) and guideline systems; developing/using wireless and in-the-field applications (mHealth); guideline development; guidelines; implementation; knowledge bases; knowledge representations; ontologies; portable; practice guidelines
We present a methodology and tool for providing retrospective review and critiquing of guideline-based medical care given to patients. We show how our guideline representation language, Asbru, which supports the use of physicians intentions in addition to physician's actions, allows us to compare the care given to a patient at the level of the intention to treat in addition to the more detailed plan carried out. We have developed an algorithm based on this representation for retrospective quality assessment of guideline-based care. Our method takes the physician's and institution's preferences and policies into account in explaining or justifying physician deviations from the recommendations of a guideline.
Validated guidelines to manage low-density lipoprotein (LDL)-cholesterol are utilized inconsistently or not at all even though their application lowers the incidence of coronary events. New approaches are needed, therefore, to implement these guidelines in everyday practice.
Methods and results
We compared an automated method for applying The National Cholesterol Education Panel (NCEP) guidelines with results from routine care for managing LDL-cholesterol. The automated method comprised computerized history-taking and analysis of historical data without physician input. Results from routine care were determined for 213 unselected patients and compared with results from interviews of the same 213 patients by a computerized history-taking program. Data extracted from hospital charts showed that routine care typically did not collect sufficient information to stratify risk and assign treatment targets for LDL-cholesterol and that there were inconsistencies in identifying patients with normal or elevated levels of LDL-cholesterol in relation to risk. The computerized interview program outperformed routine care in collecting historical data relevant to stratifying risk, assigning treatment targets, and clarifying the presence of hypercholesterolemia relative to risk.
Computerized history-taking coupled with automated analysis of the clinical data can outperform routine medical care in applying NCEP guidelines for stratifying risk and identifying patients with hypercholesterolemia in relation to risk.
dyslipidemia; coronary disease; prevention; management; computerized-history taking
Computer-based clinical guidelines and protocols are being increasingly applied in diverse areas. Although there is still little standardization to facilitate sharing, various parties are engaged in the development of shareable guideline representation formalisms and corresponding decision support systems. This paper mentions some of these developed representations, discusses their pros en cons, and demonstrates and discusses a new approach, which combines common elements from earlier-developed formalisms with new ones to improve the reusability and shareability of developed guidelines. An ontological representation is presented that formalizes guidelines in terms of domain-specific knowledge and employed generic strategies that use this domain-specific knowledge in order to solve particular guideline tasks. Furthermore, a framework is described that supports this representation and three examples are shown of guidelines of various granularity and complexity that were developed by means of this approach.
Medical informaticians who seek to implement clinical guidelines by computer must be aware of a significant gap that exists between guideline development and utilization. In order to be effective, guideline recommendations must be followed by clinicians; in order for clinicians to follow willingly, they must agree with the guidelines. This paper presents a model process for building consensus among clinicians that can be used to obtain support for guideline recommendations prior to their electronic implementation. This approach involves initial presentation of the guidelines by a specialist, iterative cycles of surveying clinicians' opinions about the guidelines and revising the guidelines, supervision of the process by a practice opinion leader, and final group discussion of the revised guidelines to reach consensus. This model was successfully used to adapt guidelines for the continuing care of patients with diabetes mellitus that were subsequently implemented electronically with broad support of the primary care clinicians using them. The model minimized the need for lengthy group discussion by surveying individuals' attitudes and working through a practice opinion leader to gain consensus support for the guidelines. An efficient approach for developing support for guidelines among practitioners will facilitate the electronic implementation of guidelines and lead to enhanced compliance with guidelines after implementation.
Electronic medical record systems and clinical practice guideline (CPG) support applications are emerging in the clinical environment to document and support care. Applications which integrate online documentation with CPG are often complex systems bound to a proprietary infrastructure and as such, can be difficult to adapt to changing care guidelines. This paper describes integration of point-of-care clinical documentation to an Internet-based CPG system that was easily modified, utilized available software resources, and separated patient information from CPG. The system combined a text-based encounter documentation tool, Inbox, with a web-based CPG system, SIEGFRIED (System for Interactive Electronic Guidelines with Feedback and Resources for Instructional and Educational Development), which interactively presented care guidelines to providers. Age-specific well child care documentation templates were developed using Inbox for point-of-care documentation. SIEGFRIED contained the knowledge base of child safety education guidelines and executed independent of the program presenting the guidelines. The CPG were accessed from within the documentation template via an Internet hyperlink. Patient chart evaluation indicated that 77% of safety topics were reviewed and 32% of the charts contained documentation indicating all the safety topics were reviewed. Last, routine use of the Inbox-SIEGFRIED system was not realized due to the clinical time constraints and workload of the medical providers, and lack of data entry experience. A user survey indicated time cost (network access and software execution) were negative aspects of the system. However, the system function was highly regarded and the Internet-based patient education materials were described as useful and accurate. In summary, the system was functional, met original development goals, and provided valuable patient education materials; however, routine system use was prevented by time requirements. We recommend further development be oriented towards integrating the identified beneficial components of the system into clinician workflow.
Numerous approaches have been proposed to integrate the text of guideline documents with guideline-based care systems. Current approaches range from serving marked up guideline text documents to generating advisories using complex guideline knowledge bases. These approaches have integration problems mainly because they tend to rigidly link the knowledge base with text. We are developing a bridge approach that uses an information retrieval technology. The new approach facilitates a versatile decision-support system by using flexible links between the formal structures of the knowledge base and the natural language style of the guideline text.
The Guideline Interchange Format (GLIF) is a language for structured representation of guidelines. It was developed to facilitate sharing clinical guidelines. GLIF version 2 enabled modeling a guideline as a flowchart of structured steps, representing clinical actions and decisions. However, the attributes of structured constructs were defined as text strings that could not be parsed, and such guidelines could not be used for computer-based execution that requires automatic inference. GLIF3 is a new version of GLIF designed to support computer-based execution. GLIF3 builds upon the framework set by GLIF2 but augments it by introducing several new constructs and extending GLIF2 constructs to allow a more formal definition of decision criteria, action specifications and patient data. GLIF3 enables guideline encoding at three levels: a conceptual flowchart, a computable specification that can be verified for logical consistency and completeness, and an implementable specification that can be incorporated into particular institutional information systems.
Formalizing clinical practice guidelines (CPGs) for a subsequent computer-supported processing is a challenging, but burdensome and time-consuming task. Existing methods and tools to support this task demand detailed medical knowledge, knowledge about the formal representations, and a manual modeling. Furthermore, formalized guideline documents mostly fall far short in terms of readability and understandability for the human domain modeler.
Methods and material:
We propose a new multi-step approach using information extraction methods to support the human modeler by both automating parts of the modeling process and making the modeling process traceable and comprehensible. This paper addresses the first steps to obtain a representation containing processes which is independent of the final guideline representation language.
We have developed and evaluated several heuristics without the need to apply natural language understanding and implemented them in a framework to apply them to several guidelines from the medical subject of otolaryngology. Findings in the evaluation indicate that using semi-automatic, step-wise information extraction methods are a valuable instrument to formalize CPGs.
Our evaluation shows that a heuristic-based approach can achieve good results, especially for guidelines with a major portion of semi-structured text. It can be applied to guidelines irrespective to the final guideline representation format.
Information extraction and integration; Clinical practice guidelines; Computer-interpretable guidelines; Guideline representation; Treatment processes; Time-oriented information; Otolaryngology
The Guideline Elements Model (GEM) uses XML to represent the heterogeneous knowledge contained in clinical practice guidelines. GEM has important applications in computer aided guideline authoring and clinical decision support systems. However, its XML representation format could limit its potential impact, as semantic web ontology languages, such as OWL, are becoming major knowledge representation frameworks in medical informatics. In this work, we present a faithful translation of GEM from XML into OWL. This translation is intended to keep the knowledge model of GEM intact, as this knowledge model has been carefully designed and has become a recognized standard. An OWL representation would make GEM more applicable in medical informatics systems that rely on semantic web. This work will also be the initial step in making GEM a guideline recommendation ontology.
Evidence-based guidelines have the potential to improve healthcare. However, their de-novo-development requires substantial resources – especially for complex conditions, and adaptation may be biased by contextually influenced recommendations in source guidelines. In this paper we describe a new approach to guideline development – the systematic guideline review method (SGR), and its application in the development of an evidence-based guideline for family physicians on chronic heart failure (CHF).
A systematic search for guidelines was carried out. Evidence-based guidelines on CHF management in adults in ambulatory care published in English or German between the years 2000 and 2004 were included. Guidelines on acute or right heart failure were excluded. Eligibility was assessed by two reviewers, methodological quality of selected guidelines was appraised using the AGREE instrument, and a framework of relevant clinical questions for diagnostics and treatment was derived. Data were extracted into evidence tables, systematically compared by means of a consistency analysis and synthesized in a preliminary draft. Most relevant primary sources were re-assessed to verify the cited evidence. Evidence and recommendations were summarized in a draft guideline.
Of 16 included guidelines five were of good quality. A total of 35 recommendations were systematically compared: 25/35 were consistent, 9/35 inconsistent, and 1/35 un-rateable (derived from a single guideline). Of the 25 consistencies, 14 were based on consensus, seven on evidence and four differed in grading. Major inconsistencies were found in 3/9 of the inconsistent recommendations. We re-evaluated the evidence for 17 recommendations (evidence-based, differing evidence levels and minor inconsistencies) – the majority was congruent. Incongruity was found where the stated evidence could not be verified in the cited primary sources, or where the evaluation in the source guidelines focused on treatment benefits and underestimated the risks. The draft guideline was completed in 8.5 man-months. The main limitation to this study was the lack of a second reviewer.
The systematic guideline review including framework development, consistency analysis and validation is an effective, valid, and resource saving-approach to the development of evidence-based guidelines.