Category Archives: awareness

Can Clinical Guidelines be Trusted?

Status

Can Clinical Guidelines be Trusted?

In a recent BMJ article, “Why we can’t trust clinical guidelines,” Jeanne Lenzer raises a number of concerns regarding clinical guidelines[1]. She begins by summarizing the conflict between 1990 guidelines recommending steroids for acute spinal injury versus 2013 cllinical recommendations against using steroids in acute spinal injury. She then asks, “Why do processes intended to prevent or reduce bias fail?

Her proposed answers to this question include the following—

  • Many doctors follow guidelines, even if not convinced about the recommendations, because they fear professional censure and possible harm to their careers.
    • Supporting this, she cites a poll of over 1000 neurosurgeons which showed that—
      • Only 11% believed the treatment was safe and effective.
      • Only 6% thought it should be a standard of care.
      • Yet when asked if they would continue prescribing the treatment, 60% said that they would. Many cited a fear of malpractice if they failed to follow “a standard of care.” (Note: the standard of care changed in March 2013 when the Congress of Neurological Surgeons stated there was no high quality evidence to support the recommendation.)
  • Clinical guideline chairs and participants frequently have financial conflicts.
    • The Cochrane reviewer for the 1990 guideline she references had strong ties to industry.

Delfini Comment

  • Fear-based Decision-making by Physicians

We believe this is a reality. In our work with administrative law judges, we have been told that if you “run with the pack,” you better be right, and if you “run outside the pack,” you really better be right. And what happens in court is not necessarily true or just. The solution is better recommendations constructed from individualized, thoughtful decisions based on valid critically appraised evidence found to be clinically useful, patient preferences and other factors. The important starting place is effective critical appraisal of the evidence.

  • Financial Conflicts of Interest & Industry Influence

It is certainly true that money can sway decisions, be it coming from industry support or potential for income. However, we think that most doctors want to do their best for patients and try to make decisions or provide recommendations with the patient’s best interest in mind. Therefore, we think this latter issue may be more complex and strongly affected in both instances by the large number of physicians and others involved in health care decision-making who 1) do not understand that many research studies are not valid or reported sufficiently to tell; and, 2) lack the skills to be able to differentiate reliable studies from those which may not be reliable.

When it comes to industry support, one of the variables traveling with money includes greater exposure to information through data or contacts with experts supporting that manufacturer’s products. We suspect that industry influence may be less due to financial incentives than this exposure coupled with lack of critical appraisal understanding. As such, we wrote a Letter to the Editor describing our theory that the major problem of low quality guidelines might stem from physicians’ and others’ lack of competency in evaluating the quality of the evidence. Our response is reproduced here.

Delfini BMJ Rapid Response [2]:

We (Delfini) believe that we have some unique insight into how ties to industry may result in advocacy for a particular intervention due to our extensive experience training health care professionals and students in critical appraisal of the medical literature. We think it is very possible that the outcomes Lenzer describes are less due to financial influence than are due to lack of knowledge. The vast majority of physicians and other health care professionals do not have even rudimentary skills in identifying science that is at high to medium risk of bias or understand when results may have a high likelihood of being due to chance. Having ties to industry would likely result in greater exposure to science supporting a particular intervention.

Without the ability to evaluate the quality of the science, we think it is likely that individuals would be swayed and/or convinced by that science. The remedy for this and for other problems with the quality of clinical guidelines is ensuring that all guideline development members have basic critical appraisal skills and there is enough transparency in guidelines so that appraisal of a guideline and the studies utilized can easily be accomplished.

References

1. Lenzer J. Why we can’t trust clinical guidelines. BMJ 2013; 346:f3830

2. Strite SA, Stuart M. BMJ Rapid Response: Why we can’t trust clinical guidelines. BMJ 2013;346:f3830; http://www.bmj.com/content/346/bmj.f3830/rr/651876

Facebook Twitter Linkedin Digg Delicious Reddit Stumbleupon Tumblr Email

Webinar: “Using Real-World Data & Published Evidence in Pharmacy Quality Improvement Activities”

Status

“Using Real-World Data & Published Evidence in Pharmacy Quality Improvement Activities”

On Monday, May 20, 2013, we presented a webinar on “Using Real-World Data & Published Evidence in Pharmacy Quality Improvement Activities” for the member organizations of the Alliance of Community Health Plans (ACHP).

The 80-minute discussion addressed four topic areas, all of which have unique critical appraisal challenges. Webinar goals were to discuss issues that arise when conducting quality improvement efforts using real world data, such as data from claims, surveys and observational studies and other published healthcare evidence.

Key pitfalls were cherry picked for these four mini-seminars—

  • Pitfalls to avoid when using real-world data, dealing with heterogeneity, confounding-by-indication and causality.
  • Key issues in evaluating oncology studies — outcome issues and focus on how to address large attrition rates.
  • Important issues when conducting comparative safety reviews — assessing patterns through use of RCTs, systematic reviews, observational studies and registries.
  • Key issues in evaluating studies employing Kaplan-Meier estimates — time-to-event basics with attention to the important problem of censoring.

A recording of the webinar is available at—

https://achp.webex.com/achp/lsr.php?AT=pb&SP=TC&rID=45261732&rKey=1475c8c3abed8061&act=pb

Facebook Twitter Linkedin Digg Delicious Reddit Stumbleupon Tumblr Email

Review of Endocrinology Guidelines

Status

Review of Endocrinology Guidelines

Decision-makers frequently rely on the body of pertinent research in making decisions regarding clinical management decisions. The goal is to critically appraise and synthesize the evidence before making recommendations, developing protocols and making other decisions. Serious attention is paid to the validity of the primary studies to determine reliability before accepting them into the review.  Brito and colleagues have described the rigor of systematic reviews (SRs) cited from 2006 until January 2012 in support of the clinical practice guidelines put forth by the Endocrine Society using the Assessment of Multiple Systematic Reviews (AMSTAR) tool [1].

The authors included 69 of 2817 studies. These 69 SRs had a mean AMSTAR score of 6.4 (standard deviation, 2.5) of a maximum score of 11, with scores improving over time. Thirty five percent of the included SRs were of low-quality (methodological AMSTAR score 1 or 2 of 5, and were cited in 24 different recommendations). These low quality SRs were the main evidentiary support for five recommendations, of which only one acknowledged the quality of SRs.

The authors conclude that few recommendations in field of endocrinology are supported by reliable SRs and that the quality of the endocrinology SRs is suboptimal and is currently not being addressed by guideline developers. SRs should reliably represent the body of relevant evidence.  The authors urge authors and journal editors to pay attention to bias and adequate reporting.

Delfini note: Once again we see a review of guideline work which suggests using caution in accepting clinical recommendations without critical appraisal of the evidence and knowing the strength of the evidence supporting clinical recommendations.

1. Brito JP, Tsapas A, Griebeler ML, Wang Z, Prutsky GJ, Domecq JP, Murad MH, Montori VM. Systematic reviews supporting practice guideline recommendations lack protection against bias. J Clin Epidemiol. 2013 Jun;66(6):633-8. doi: 10.1016/j.jclinepi.2013.01.008. Epub 2013 Mar 16. PubMed PMID: 23510557.

Facebook Twitter Linkedin Digg Delicious Reddit Stumbleupon Tumblr Email

Review of Bias In Diabetes Randomized Controlled Trials

Status

Review of Bias In Diabetes Randomized Controlled Trials

Healthcare professionals must evaluate the internal validity of randomized controlled trials (RCTs) as a first step in the process of considering the application of clinical findings (results) for particular patients. Bias has been repeatedly shown to increase the likelihood of distorted study results, frequently favoring the intervention.

Readers may be interested in a new systematic review of diabetes RCTs. Risk of bias (low, unclear or high) was assessed in 142 trials using the Cochrane Risk of Bias Tool.  Overall, 69 trials (49%) had at least one out of seven domains with high risk of bias. Inadequate reporting frequently hampered the risk of bias assessment: the method of producing the allocation sequence was unclear in 82 trials (58%) and allocation concealment was unclear in 78 trials (55%). There were no significant reductions in the proportion of studies at high risk of bias over time nor in the adequacy of reporting of risk of bias domains. The authors conclude that these trials have serious limitations that put the findings in question and therefore inhibit evidence-based quality improvement (QI). There is a need to limit the potential for bias when conducting QI trials and improve the quality of reporting of QI trials so that stakeholders have adequate evidence for implementation. The entire freely-available study is available at—

http://bmjopen.bmj.com/content/3/4/e002727.long

Ivers NM, Tricco AC, Taljaard M, Halperin I, Turner L, Moher D, Grimshaw JM. Quality improvement needed in quality improvement randomised trials: systematic review of interventions to improve care in diabetes. BMJ Open. 2013 Apr 9;3(4). doi:pii: e002727. 10.1136/bmjopen-2013-002727. Print 2013. PubMed PMID: 23576000.

 

Facebook Twitter Linkedin Digg Delicious Reddit Stumbleupon Tumblr Email

Critical Appraisal Tool for Clinical Guidelines & Other Secondary Sources

Status

Critical Appraisal Tool for Clinical Guidelines & Other Secondary Sources

Everything citing medical science should be appraised for validity and clinical usefulness. That includes clinical guidelines and other secondary sources. Our tool for evaluating these resources— the Delfini QI Project Appraisal Tool—has been updated and is available in the Delfini Tools & Educational Library at www.delfini.org.  For quick access to the PDF version, go to—

http://www.delfini.org/delfiniNew.htm

 

Facebook Twitter Linkedin Digg Delicious Reddit Stumbleupon Tumblr Email

When Is a Measure of Outcomes Like a Coupon for a Diamond Necklace?

Status

When Is a Measure of Outcomes Like a Coupon for a Diamond Necklace?

For those of you who struggle with the fundamental difference between absolute risk reduction (ARR) versus relative risk reduction (RRR) and their counterparts, absolute and relative risk increase (ARI/RRI), we have always explained that only knowing the RRR or the RRI without other quantitative information about the frequency of events is akin to knowing that a store is having a half-off sale—but when you walk in, you find that they aren’t posting the actual price!  And so your question is 50 percent off of what???

You should have the same question greet you whenever you are provided with a relative measure (and if you aren’t told whether the measure is relative or absolute, you may be safer off assuming that it is relative). Below is a link to a great short cartoon that turns the lens a little differently and which might help.

However, we will add that, in our opinion, ARR alone isn’t fully informative either, nor is its kin, the number-needed-to-treat or NNT, and for ARI, the number-needed-to-harm or NNH.  A 5 percent reduction in risk may be perceived very differently when “10 people out of a hundred benefit with one intervention compared to 5 with placebo” as compared to a different scenario in which “95 people out of a hundred benefit with one intervention as compared to 90 with placebo.” As a patient, I might be less likely to want to expose myself to side effects if it is highly likely I am going to improve without treatment, for example.  Providing this full information–for critically appraised studies that are deemed to be valid–of course, may best provide patients with information that helps them make choices based on their own needs and requirements including their values and preferences.

We think that anyone involved in health care decision-making—including the patient—is best helped by knowing the event rates for each of the groups studied—i.e., the numerators and denominators for the outcome of interest by group which comprise the 4 numbers that make up the 2 by 2 table which is used to calculate many statistics.

Isn’t it great when learning can be fun too!  Enjoy!

http://www.ibtimes.com/articles/347476/20120531/relative-risk-absolute-comic-health-medical-reporting.htm

Facebook Twitter Linkedin Digg Delicious Reddit Stumbleupon Tumblr Email

Our Current Thinking About Attrition Bias

Status

Delfini Thoughts on Attrition Bias

Significant attrition, whether it be due to loss of patients or discontinuation or some other reason, is a reality of many clinical trials. And, of course, the key question in any study is whether attrition significantly distorted the study results. We’ve spent a lot of time researching the evidence-on-the-evidence and have found that many researchers, biostatisticians and others struggle with this area—there appears to be no clear agreement in the clinical research community about how to best address these issues. There also is inconsistent evidence on the effects of attrition on study results.

We, therefore, believe that studies should be evaluated on a case-by-case basis and doing so often requires sleuthing and sifting through clues along with critically thinking through the unique circumstances of the study.

The key question is, “Given that attrition has occurred, are the study results likely to be true?” It is important to look at the contextual elements of the study. These contextual elements may include information about the population characteristics, potential effects of the intervention and comparator, the outcomes studied and whether patterns emerge, timing and setting. It is also important to look at the reasons for discontinuation and loss-to-follow up and to look at what data is missing and why to assess likely impact on results.

Attrition may or may not impact study outcomes depending, in part, upon the reasons for withdrawals, censoring rules and the resulting effects of applying those rules, for example. However, differential attrition issues should be looked at especially closely. Unintended differences between groups are more likely to happen when patients have not been allocated to their groups in a blinded fashion, groups are not balanced at the onset of the study and/or the study is not effectively blinded or an effect of the treatment has caused the attrition.

One piece of the puzzle, at times, may be whether prognostic characteristics remained balanced. One item that would be helpful authors could help us all out tremendously by assessing comparability between baseline characteristics at randomization and for those analyzed. However, an imbalance may be an important clue too because it might be informative about efficacy or side effects of the agent understudy.

In general, we think it is important to attempt to answer the following questions:

Examining the contextual elements of a given study—

  • What could explain the results if it is not the case that the reported findings are true?
  • What conditions would have to be present for an opposing set of results (equivalence or inferiority) to be true instead of the study findings?
  • Were those conditions met?
  • If these conditions were not met, is there any reason to believe that the estimate of effect (size of the difference) between groups is not likely to be true.
Facebook Twitter Linkedin Digg Delicious Reddit Stumbleupon Tumblr Email

Reliable Clinical Guidelines

Status

Reliable Clinical Guidelines—Great Idea, Not-Such-A-Great Reality

Although clinical guideline recommendations about managing a given condition may differ, guidelines are, in general, considered to be important sources for individual clinical decision-making, protocol development, order sets, performance measures and insurance coverage. The Institute of Medicine [IOM] has created important recommendations that guideline developers should pay attention to—

  1. Transparency;
  2.  Management of conflict of interest;
  3.  Guideline development group composition;
  4. How the evidence review is used to inform clinical recommendations;
  5.  Establishing evidence foundations for making strength of recommendation ratings;
  6. Clear articulation of recommendations;
  7. External review; and,
  8. Updating.

Investigators recently evaluated 114 randomly chosen guidelines against a selection from the IOM standards and found poor adherence [Kung 12]. The group found that the overall median number of IOM standards satisfied was only 8 out of 18 (44.4%) of those standards. They also found that subspecialty societies tended to satisfy fewer IOM methodological standards. This study shows that there has been no change in guideline quality over the past decade and a half when an earlier study found similar results [Shaneyfeld 99].  This finding, of course, is likely to have the effect of leaving end-users uncertain as to how to best incorporate clinical guidelines into clinical practice and care improvements.  Further, Kung’s study found that few guidelines groups included information scientists (individuals skilled in critical appraisal of the evidence to determine the reliability of the results) and even fewer included patients or patient representatives.

An editorialist suggests that currently there are 5 things we need [Ransohoff]. We need:

1. An agreed-upon transparent, trustworthy process for developing ways to evaluate clinical guidelines and their recommendations.

2. A reliable method to express the degree of adherence to each IOM or other agreed-upon standard and a method for creating a composite measure of adherence.

From these two steps, we must create a “total trustworthiness score” which reflects adherence to all standards.

3. To accept that our current processes of developing trustworthy measures is a work in progress. Therefore, stakeholders must actively participate in accomplishing these 5 tasks.

4. To identify an institutional home that can sustain the process of developing measures of trustworthiness.

5. To develop a marketplace for trustworthy guidelines. Ratings should be displayed alongside each recommendation.

At this time, we have to agree with Shaneyfeld who wrote an accompanying commentary to Kung’s study [Shaneyfeld 12]:

What will the next decade of guideline development be like? I am not optimistic that much will improve. No one seems interested in curtailing the out-of-control guideline industry. Guideline developers seem set in their ways. I agree with the IOM that the Agency for Healthcare Research and Quality (AHRQ) should require guidelines to indicate their adherence to development standards. I think a necessary next step is for the AHRQ to certify guidelines that meet these standards and allow only certified guidelines to be published in the National Guidelines Clearinghouse. Currently, readers cannot rely on the fact that a guideline is published in the National Guidelines Clearinghouse as evidence of its trustworthiness, as demonstrated by Kung et al. I hope efforts by the Guidelines International Network are successful, but until then, in guidelines we cannot trust.

References

1. IOM: Graham R, Mancher M, Wolman DM,  et al; Committee on Standards for Developing Trustworthy Clinical Practice Guidelines; Board on Health Care Services.  Clinical Practice Guidelines We Can Trust. Washington, DC: National Academies Press; 2011 http://www.nap.edu/catalog.php?record_id=13058

2. Kung J, Miller RR, Mackowiak PA. Failure of Clinical Practice Guidelines to Meet Institute of Medicine Standards: Two More Decades of Little, If Any, Progress. Arch Intern Med. 2012 Oct 22:1-6. doi: 10.1001/2013.jamainternmed.56. [Epub ahead of print] PubMed PMID: 23089902.

3.  Ransohoff DF, Pignone M, Sox HC. How to decide whether a clinical practice guideline is trustworthy. JAMA. 2013 Jan 9;309(2):139-40. doi: 10.1001/jama.2012.156703. PubMed PMID: 23299601.

4. Shaneyfelt TM, Mayo-Smith MF, Rothwangl J. Are guidelines following guidelines? The methodological quality of clinical practice guidelines in the peer-reviewed medical literature. JAMA. 1999 May 26;281(20):1900-5. PubMed PMID: 10349893.

5. Shaneyfelt T. In Guidelines We Cannot Trust: Comment on “Failure of Clinical Practice Guidelines to Meet Institute of Medicine Standards”. Arch Intern Med. 2012 Oct 22:1-2. doi: 10.1001/2013.jamainternmed.335. [Epub ahead of print] PubMed PMID: 23089851.

Facebook Twitter Linkedin Digg Delicious Reddit Stumbleupon Tumblr Email

Quickly Finding Reliable Evidence

Status

Quickly Finding Reliable Evidence

Good clinical recommendations for various diagnostic and therapeutic interventions incorporate evidence from reliable published research evidence. Several online evidence-based textbooks are available for clinicians to use to assist them in making healthcare decisions. Large time lags in updating are a common problem for medical textbooks.  Online textbooks offer a solution to these delays.

For readers who plan to create decision support, we strongly recommend DynaMed [full disclosure: we are on the editorial board in an unpaid capacity, though a few years ago we did receive a small gift]. DynaMed is a point-of-care evidence-based medical information database created by Brian S. Alper MD, MSPH, FAAFP. It continues to grow from its current 30,000+ clinical topics that are updated frequently. DynaMed monitors the content of more than 500 medical journals and systematic evidence review databases.  Each item is thoroughly reviewed for clinical relevance and scientific reliability. DynaMed has been compared with several products, including in a new review by McMaster University. The DynaMed website is https://dynamed.ebscohost.com/.

The McMaster University maintains a Premium Literature Service (PLUS) database which is a continuously updated, searchable database of primary studies and systematic reviews. Each article from over 120 high quality clinical journals and evidence summary services is appraised by research staff for methodological quality, and articles that pass basic criteria are assessed by practicing clinicians in the corresponding discipline.  Clinical ratings are based on 7-point scales, where clinical relevance ranges from 1 (“not relevant”) to 7 (“directly and highly relevant”), and newsworthiness ranges from 1 (“not of direct clinical interest”) to 7 (“useful information, most practitioners in my discipline definitely don’t know this).

Investigators from McMaster evaluated four evidence-based textbooks—UpToDate, PIER, DynaMed and Best Practice [Jeffery 12].  For each they determined the proportion of 200 topics which had subsequent articles in PLUS with findings different from those reported in the topics. They also evaluated the number of topics available in each evidence-based textbook compared with the topic coverage in the PLUS database, and the recency of updates for these publications.  A topic was in need of an update if there was at least one newer article in PLUS that provided information that differed from the topic’s recommendations in the textbook.

Results

The proportion of topics with potential for updates was significantly lower for DynaMed than the other three textbooks, which had statistically similar values. For DynaMed topics, updates occurred on average of 170 days prior to the study, while the other textbooks averaged from 427 to 488 days. Of all evidence-based textbooks, DynaMed missed fewer articles reporting benefit or no effect when the direction of findings (beneficial, harmful, no effect) was investigated. The proportion of topics for which there was 1 or more recently published articles found in PLUS with evidence that differed from the textbooks’ treatment recommendations was 23% (95% CI 17 to 29%) for DynaMed, 52% (95% CI 45 to 59%) for UpToDate, 55% (95% CI 48 to 61%) for PIER, and 60% (95% CI 53 to 66%) for Best Practice (?23=65.3, P<.001). The time since the last update for each textbook averaged from 170 days (range 131 to 209) for DynaMed, to 488 days (range 423 to 554) for PIER (P<.001 across all textbooks).

Summary

Healthcare topic coverage varied substantially for leading evidence-informed electronic textbooks, and generally a high proportion of the 200 common topics had potentially out-of-date conclusions and missing information from 1 or more recently published studies. PIER had the least topic coverage, while UpToDate, DynaMed, and Best Practice covered more topics in similar numbers. DynaMed’s timeline for updating was the quickest, and it had by far the least number of articles that needed to be updated, indicating that quality was not sacrificed for speed.

Note: All textbooks have access to the PLUS database to facilitate updates, and also use other sources for updates such as clinical practice guidelines.

Conclusion

The proportion of topics with potentially outdated treatment recommendations in on-line evidence-based textbooks varies substantially.

Reference

Jeffery R, Navarro T, Lokker C, Haynes RB, Wilczynski NL, Farjou G. How current are leading evidence-based medical textbooks? An analytic survey of four online textbooks. J Med Internet Res. 2012 Dec 10;14(6):e175. doi: 10.2196/jmir.2105. PubMed PMID: 23220465.

 

 

Facebook Twitter Linkedin Digg Delicious Reddit Stumbleupon Tumblr Email

Canadian Knowledge Translation Website

Status

Canadian Knowledge Translation Website

The Knowledge Translation (KT) Clearinghouse is a useful website for EBM information and tools. It is funded by the Canadian Institute of Health Research (CIHR) and has a goal of improving the quality of care by developing, implementing and evaluating strategies that bridge the knowledge-to-practice gap and to research the most effective ways to translate knowledge into action. Now added to Delfini web links.

http://ktclearinghouse.ca/

Facebook Twitter Linkedin Digg Delicious Reddit Stumbleupon Tumblr Email