1) Use “Roddy and Ganz Worksheets” to complete an assessment of the research studies: “Evidence-Based Clinical Guidelines: A New System to Better Determine True Strength of Recommendation” by Roddy et al., and “ICU Nurses’ Oral-Care Practices and the Current Best Evidence” by Ganz et al.
2) In a paper (1,000-1,250 words), analyze and support whether you believe that the changes recommended are statistically valid and sound enough to make practice changes in a hospital.
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Write My Essay For Me!3) Prepare this assignment according to the APA guidelines found in the APA Style Guide, located in the Student Success Center. An abstract is not required.
4) This assignment uses a grading rubric. Instructors will be using the rubric to grade the assignment; therefore, students should review the rubric prior to beginning the assignment to become familiar with the assignment criteria and expectations for successful completion of the assignment.
Journal of Evaluation in Clinical Practice,
12
, 3, 347–352
2006 Blackwell Publishing Ltd
347
Blackwell Science, LtdOxford, UKJEPJournal of Evaluation in Clinical Practice1356-1294Blackwell Publishing Ltd 200512
3347352
Original Article
Grading strength of guideline recommendationsE. Roddy
et al.
Correspondence
Edward Roddy Academic Rheumatology Clinical Sciences Building Nottingham City Hospital Hucknall Road NG5 1PB UK E-mail: edward.roddy@nottingham.ac.uk
Keywords:
clinical guidelines, evidence-based medicine, strength of recommendation
Accepted for publication:
27 April 2005
Evidence-based clinical guidelines: a new system to better determine true strength of recommendation
Edward Roddy MRCP (Specialist Registrar in Rheumatology),
1
Weiya Zhang PhD (Senior Lecturer in Musculoskeletal Epidemiology),
1
Michael Doherty MA MD FRCP (Professor of Rheumatology),
1
Nigel K. Arden MD MSc MRCP (Senior Lecturer in Rheumatology),
2
Julie Barlow PhD (Professor of Health Psychology),
3
Fraser Birrell MA PhD MRCP (Senior Lecturer in Rheumatology),
4
Alison Carr PhD (Special Lecturer in Musculoskeletal Epidemiology),
1
Kuntal Chakravarty FRCP (Consultant Rheumatologist),
5
John Dickson FRCP MRCGP (Community Specialist in Rheumatology),
6
Elaine Hay MD FRCP (Professor of Community Rheumatology),
7
Gillian Hosie FRCP (General Practitioner),
8
Michael Hurley PhD (Reader in Physiotherapy & ARC Research Fellow),
9
Kelsey M. Jordan MRCP (Rheumatology Research Fellow),
2
Christopher McCarthy PhD (Research Physiotherapist),
10
Marion McMurdo MD FRCP (Professor of Ageing and Health),
11
Simon Mockett MPhil (Senior Lecturer),
12
Sheila O’Reilly MD MRCP (Consultant Rheumatologist),
13
George Peat PhD MCSP (Research Fellow),
7
Adrian Pendleton MD MRCP (Specialist Registrar in Rheumatology),
14
Selwyn Richards MA MSc FRCP (Consultant Rheumatologist)
15
1
Academic Rheumatology, Clinical Sciences Building, Nottingham City Hospital, Hucknall Road, Nottingham, UK
2
MRC Epidemiology Resource Centre, Southampton General Hospital, Tremona Road, Southampton, Hampshire, UK
3
Interdisciplinary Research Centre in Health, School of Health and Social Sciences, Coventry University, Priory St, Coventry, UK
4
Musculoskeletal Research Group, University of Newcastle upon Tyne, UK
5
Haroldwood Hospital, Gubbins Lane, Romford, Essex, UK
6
Langbaurgh PCT, Langbaurgh House, Bow Street, Guisborough, Cleveland, UK
7
Primary Care Sciences Research Centre, Keele University, Staffordshire, UK
8
Primary Care Rheumatology Society, Northallerton, North Yorkshire, UK
9
King’s College London, Rehabilitation Research Unit, Dulwich Hospital, East Dulwich Grove, London, UK
10
The Centre for Rehabilitation Science, University of Manchester, Oxford Road, Manchester, UK
11
Department of Medicine, University of Dundee, Ninewells Hospital, Dundee, UK
12
Division of Physiotherapy Education, School of Community Health Sciences, University of Nottingham, Nottingham City Hospital, Hucknall Road, Nottingham, UK
13
Derbyshire Royal Infirmary, London Road, Derby, UK
14
Craigavon Area Hospital, 68 Lurgan Road, Portadown, Co Armagh, UK
15
Poole Hospital, Longfleet Road, Poole, UK
Abstract
Rationale, aims and objectives
Clinical practice guidelines often grade the ‘strength’ of their recommendations according to the robustness of the sup- porting research evidence. The existing methodology does not allow the strength of recommendation (SOR) to be upgraded for recommendations for which randomized controlled trials are impractical or unethical. The pur- pose of this study was to develop a new method of determining SOR, incor- porating both research evidence and expert opinion.
Methods
A Delphi technique was employed to produce 10 recommendations for the role of exercise therapy in the management of osteoarthritis of the hip or knee. The SOR for each recommendation was determined by the traditional method, closely linked to the category of research evidence found on a systematic literature search, and on a visual analogue scale (VAS). Recommendations were grouped A-D according to the traditional SOR allocated and the mean VAS calculated. Difference across the groups was assessed by one-
E. Roddy
et al.
348
©
2006 Blackwell Publishing Ltd,
Journal of Evaluation in Clinical Practice
,
12
, 3, 347–352
way
ANOVA
variance analysis.
Results
Mean VAS scores for the tradi- tional SOR groups A-D and one proposition which was ‘not recommended’ showed significant linearity on one-way
ANOVA
. However, certain recom- mendations which, for practical reasons, could not assessed in randomized controlled trials and therefore could not be recommended strongly by the traditional methodology, were allocated a strong recommendation by VAS.
Conclusions
This new system of grading strength of SOR is less con- strained than the traditional methodology and offers the advantage of allowing SOR for procedures which cannot be assessed in RCTs for prac- tical or ethical reasons to be upgraded according to expert opinion.
Introduction
Clinical guidelines have been defined as ‘systemati- cally developed statements to assist practitioner and patient decisions about appropriate health care for specific clinical conditions’ (Field & Lohr 1990). Guidelines that employ an evidence-based format currently grade each recommendation in two ways: first, by classifying the ‘category of evidence’ and, second, by giving a ‘strength of recommendation’. Although several methods of producing such grades are described, in most of these, including the method most commonly used by clinical guidelines in rheu- matology (Pendleton
et al
. 2000; Jordan
et al
. 2003; Dougados
et al
. 2004; Zhang
et al
. 2004; Roddy
et al
. 2005), the latter is strongly dependent on the former (Shekelle
et al
. 1999) (Table 1). That is, the strength of recommendation (SOR) primarily reflects the
robustness of the research evidence, with evidence from randomized controlled trials (RCTs) and systematic reviews automatically conferring the strongest recommendation. However, although this traditional method allows a downgrading of the SOR for reasons including side effects or inconsistent studies, it does not allow an upgrading of recommen- dations in situations where RCTs are impractical or unethical, e.g. total joint replacement, but effective- ness is not in doubt. Furthermore, the practice of evidence-based medicine requires the integration of clinical expertise with the best available evidence from systematic research (Sackett
et al
. 1996). Dur- ing the development of recent recommendations for the role of exercise in the management of osteo- arthritis (OA) of the hip or knee (Roddy
et al
. 2005), we found that the SOR allocated by this method was often discordant with the consensus opinion of the
Table 1 Traditional hierarchy for category of evidence and strength of recommendation (Shekelle
et al
. 1999)
Categories of evidence
1A. meta-analysis of RCT 1B. at least one RCT 2A. at least one CT without randomization 2B. at least one type of quasi-experimental study 3. descriptive studies (comparative, correlation, case-control) 4. expert committee reports/opinions and/or clinical opinion of respected authorities
Strength of recommendation
A. Directly based on category 1 evidence B. Directly based on category 2 evidence or extrapolated recommendation from category 1 evidence C. Directly based on category 3 evidence or extrapolated recommendation from category 1 or 2 evidence D. Directly based on category 4 evidence or extrapolated recommendation from category 1, 2 or 3 evidence
RCT, randomized controlled trial; CT, controlled trial.
Grading strength of guideline recommendations
©
2006 Blackwell Publishing Ltd,
Journal of Evaluation in Clinical Practice
,
12
, 3, 347–352
349
panel. Therefore, we developed an alternative method to better capture the true opinion of the panel, whilst still requiring them to consider the research evidence. We examined whether this alter- native approach affected the support afforded to each recommendation.
Methods
A multi-disciplinary panel employed a Delphi tech- nique to produce 10 recommendations relating to the role of exercise in the management of OA of the hip or knee (Roddy
et al
. 2005). Following a literature search and summary analysis of results, the evidence for each recommendation was assessed. The category of evidence and SOR was assigned for each according to the method previ- ously described (Shekelle
et al
. 1999). In addition, each participant was asked to indicate how strongly they rated each recommendation, based not just on research evidence but also on all aspects relating to their knowledge and clinical opinion. This was recorded using a 10-cm visual analogue scale (VAS) anchored with two descriptors labelled ‘not recom- mended at all’ at the far left (0 cm) and ‘fully rec- ommended’ at the far right (10 cm). The mean VAS and standard deviation for each recommendation were calculated. The recommendations were then grouped according to their original SOR (A-D) and the mean VAS and 95% confidence interval calcu- lated for each group. A one-way
ANOVA
variance analysis was performed to assess the difference between the groups.
Results
The recommendations and the categories of evi- dence, SOR and VAS for each, are shown in Table 2. Figure 1 shows the mean VAS and 95% confidence interval for recommendation groups A, C and D in addition to one recommendation which was contra- dicted by the research evidence and could not there- fore be graded according to the traditional method (‘not recommended’). No recommendations were allocated a grade B SOR. The one-way
ANOVA
vari- ance analysis identified a significant difference across the groups (
P
<
0.001) and significant linearity (
P
<
0.001).
Discussion
There was similarity between the SOR produced by this method and the traditional methodology (Shek- elle
et al
. 1999). The mean VAS for each recommen- dation group (A, C, D) increased with the traditional SOR, and therefore the category of evidence, and the lowest mean was seen for the recommendation which could not be recommended by the research evidence ie was based solely on expert opinion.
This new system has the advantage of allowing the SOR to be upgraded or downgraded based on ex- pert opinion relating to global aspects of health care delivery, such as generalizability, safety, cost- effectiveness and patient preference, and common sense. It therefore gives an additional dimension and weighting to guideline recommendations other than just the support from research evidence alone. In the traditional system, the term ‘strength of recommen- dation’ is almost a misnomer as it directly relates to the category of evidence and provides little extra information beyond that afforded by the ‘category of evidence’. This is an important limitation of currently practised evidence-based guideline methodology that was overlooked in a recent critique of the meth- odology of OA guidelines (Pencharz
et al
. 2002). During the development of guidelines there are
many situations for which the existing SOR method- ology (Shekelle
et al
. 1999) is not ideal. Interventions for which placebo-controlled trials are impractical or unethical (e.g. total joint replacement) cannot score highly on the existing hierarchy and yet clearly may
Figure 1 Comparison of mean VAS (95% confidence intervals) and traditional strength of recommendation. VAS, visual analogue scale; NR, not recommended.
0 1 2 3 4 5 6 7 8 9
A C D NR
Strength of recommendation (Traditional method)
M ea
n V
A S
( cm
)
VAS = visual analogue scale, NR = not recommended
E. Roddy
et al.
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2006 Blackwell Publishing Ltd,
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,
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, 3, 347–352
be very efficacious and warrant strong recommenda- tion for clinical practice. The new method allows the recommendation for such interventions to be upgraded beyond that afforded by the category of research evidence. Furthermore, when recommenda- tions are not easily assessed in the setting of a clinical trial yet have clear face validity, as with our third and fourth recommendations (Table 2), the panel may
feel a much stronger recommendation is warranted than that permitted by the current research-linked method. For example, the mean VAS for both prop- ositions 4 and 5B (Table 2) was 7.7, yet the SOR according to the traditional methodology were D and 1B respectively. This reflects that although proposi- tion 4 would be impractical to assess in the setting of a RCT, it was highly supported by the expert panel
Table 2 Evidence-based recommendations for the role of exercise in the management of osteoarthritis of the hip or knee: category of evidence, strength of recommendation (Shekelle
et al
. 1999) and visual analogue score (VAS)
Recommendation Category of
Evidence (1–4) Strength of
Recommendation (A-D)
Strength of recommendation
(VAS) – Mean (SD) cms
1. Both strengthening and aerobic exercise can reduce pain and improve function and health status in patients with knee and hip OA.
Knee 1B Hip 4
A C (extrapolated from knee OA)
8.9 (1.1) 6.3 (2.1)
2. There are few contra-indications to the prescription of strengthening or aerobic exercise to patients with hip or knee OA.
4 C (extrapolated from adverse event data)
8.0 (1.5)
3. Prescription of both general (aerobic fitness training) and local (strengthening) exercises is an essential, core aspect of management for every patient with hip or knee OA.
4 D 7.1 (2.5)
4. Exercise therapy for OA of the hip or knee should be individualized and patient-centred taking into account factors such as age, co-morbidity and overall mobility.
4 D 7.7 (1.9)
5. To be effective, exercise programmes should include advice and education to promote a positive lifestyle change with an increase in physical activity.
4
1B
D
A
6.1 (2.6)
7.7 (1.4)
6. Group exercise and home exercise are equally effective and patient preference should be considered.
1A 4
A D
8.0 (1.5) 7.6 (2.3)
7. Adherence is the principal predictor of long-term outcome from exercise in patients with knee or hip OA.
4 D 5.1 (2.4)
8. Strategies to improve and maintain adherence should be adopted, e.g. long-term monitoring/review and inclusion of spouse/family in exercise.
1B A 7.6 (1.5)
9. The effectiveness of exercise is independent of the presence or severity of radiographic findings.
4 Not recommended 4.5 (2.8)
10. Improvements in muscle strength and proprioception gained from exercise programmes may reduce the progression of knee and hip OA.
4 D 4.2 (2.5)
Grading strength of guideline recommendations
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2006 Blackwell Publishing Ltd,
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, 3, 347–352
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whereas robust evidence from RCTs exists to sup- port proposition 5B. Finally, the traditional hierarchy does not accommodate the scenario where research evidence contradicts a recommendation, as with our ninth recommendation (Table 2).
Other guideline methodology groups have attempted to overcome these limitations and reduce the dependence of the SOR on the category of research evidence. However, the grading systems, produced by American College of Cardiology/ American Heart Association (ACC/AHA) Task Force (ACA/AHA 2004), the US Preventive Services Task Force (2003), the National Institute for Clinical Excellence (NICE) (NICE 2004) and the New Zealand Guidelines Group (New Zealand Guide- lines Group 2004), derive the SOR primarily from the category of research evidence. The ACC/AHA guidelines state that any combination of classification of recommendation and level of evidence is possible and that a recommendation can be strongly sup- ported even if it is based entirely on expert opinion and no research studies have ever been conducted on the recommendation (ACA/AHA 2004). However, this system does not provide for the incorporation of factors such as cost-effectiveness and safety, and the descriptive and quantitative criteria for assigning the classification and evidence ratings weight research evidence and clinical expertise equally, which may not be appropriate for some modalities, e.g. total joint replacement. The guideline development methods of NICE state that when the evidence is very strong, this should translate directly into a rec- ommendation, yet when the literature search finds no evidence to answer the clinical question, the guide- line development group should consider using con- sensus methods to identify current best practice, suggesting that consensus methods are only needed when there is no robust evidence (NICE 2004). Furthermore, NICE produces guidance on the role of individual treatments rather than disease-orientated recommendations on global treatment strategies. The recently published GRADE collaboration (Atkins
et al
. 2004), although highlighting the difficulties in producing clinical guidelines and grading strength of recommendation, has not produced a simple, practi- cal solution. The VAS, on the other hand, has the advantage of being simple to apply and allows all facets to be incorporated, e.g. category of research
evidence, safety, cost-effectiveness, generalizability and expert opinion.
A limitation of the VAS-SOR methodology is that as the basis for the VAS is not based on explicit criteria, it cannot be examined and assessed readily by external groups. However, we recommend that the VAS method should be used alongside the tra- ditional method of determining the category of research evidence supporting each recommendation. Any discrepancy between the category of evidence and SOR would therefore be highlighted and should then be justified in the ensuing discussion. A further limitation is that this method has only been used in the setting of recommendations for exercise in osteoarthritis by a single group of experts, so evi- dence of its generalizability to other fields and other groups is required.
Other possible methods for grading SOR include the development of an ordinal scale. A numerical scale, however, is commonly used to assess self- reported pain and disability in clinical trials, and applying this principle to SOR seemed preferable. Although the numerical scale scores themselves do not have intrinsic comparability between different sets of guidelines, there is at least scope for grading or even ranking of different recommendations within each set of guidelines. Other groups that prefer verbal scales may wish to develop an ordinal scale with descriptors to help guide practice in a clinical setting.
Our guideline development group concludes that, in comparison to existing traditional methodology, this new system of grading SOR is less constrained and offers the advantage of allowing the SOR for procedures which cannot be assessed in RCTs to be upgraded according to expert opinion consistent with the principles of evidence-based medicine (Sackett
et al
. 1996). We would encourage other groups that develop management recommendations or guide- lines to try this approach, so that its clinical applica- bility and usefulness can be determined more widely.
Acknowledgements
We are grateful for an educational grant from MOVE (http://www.move.uk.net) and are also indebted to the Arthritis Research Campaign, UK for financial support (ICAC grant D0593; WZ Senior
E. Roddy
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2006 Blackwell Publishing Ltd,
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Lectureship D0565). We would also like to thank Dr Jinying Lin, a visiting scholar from The People’s Hospital of Guangxi Province, China, for assistance with data entry.
John Dickson during the past 5 years has received support to attend or organize symposia, or has received a speaker’s honoraria, or a board member’s honoraria from one or more of the following com- panies – MSD, Wyeth, Pfizer, BI, TSB Chemedica, GSK. He has received research funding from Q-med. He has shares in Merck and Pfizer.
Marion McMurdo is a Director of D D Develop- ments Limited, a University of Dundee company whose mission is to provide exercise opportunities for older people. Profits go to ageing research.
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