What’s New in the Patient Safety World

January 2014

Trigger Tools to Prevent Diagnostic Delays

 

 

In our March 2013 What’s New in the Patient Safety World column “Diagnostic Error in Primary Care” we highlighted a study by Singh and colleagues (Singh 2013) on diagnostic errors in primary care that used a trigger tool methodology. Now Singh and colleagues (Murphy 2014) have gone a step further and used trigger tool methodology to identify cases in ambulatory care where certain red flags for possible cancers have not been acted upon.

 

The beauty of trigger tool methodology (See our Patient Safety Tips of the Week for October 30, 2007 “Using IHI's Global Trigger Tool” and April 15, 2008 “Computerizing Trigger Tools”) is that it allows you to screen a large number of records that potentially have the item you are really looking for. Then in the subset of records that contain the “trigger” you can then do manual chart review to verify details. It basically streamlines what would otherwise be a very labor- and time-intensive process that would not otherwise be practical.

 

One of the diagnostic errors we’ve talked about most frequently is the missed diagnosis due to failure to follow up on test results (see the list of our prior columns on this topic at the end of today’s column). The Murphy study identified 4 markers (or “red flags”) of potential cancer (elevated PSA level, positive fecal occult blood test, hematochezia, and iron deficiency anemia) to be used as the “triggers” and then did data mining of almost 300,000 electronic patient medical records at two facilities looking for these triggers. They also applied an algorithm to exclude instances where the marker had already been followed up, or where the patient already had a known cancer, or where the patient had a known terminal illness. They then did a random chart audit of records identified by the above process to see how often those markers had not, in fact, been appropriately followed up. The positive predictive value (PPV) for each of these triggers was in the 60-70% range. They estimate that this system could pick up 1048 instances of delayed or missed followup at their facilities.

 

Note that the time interval set in their trigger tool was important. If the interval is too short many cases where followup had already been planned would be falsely identified as outliers. If the interval is too long, the delay in followup might lead to progression of a cancer.

 

Their findings came from retrospective application of the trigger tool to a patient population. But the real potential value would be to apply the tool prospectively and identify cases in which intervention could still be taken to identify cancer sooner.

 

The authors expect that the tool may yet be further refined. In many cases where the trigger was positive, chart review revealed information in the free text areas of charts that indicated appropriate action had already been taken or scheduled. They speculate that use of tools such as natural language processing might be able to identify those cases, further narrowing the number of charts identified by the trigger tool to an even more manageable number of cases needing manual chart review.

 

The accompanying editorial (Schiff 2014) notes how use of such electronic screens can be used to identify other potential diagnostic errors. By linking laboratory and pharmacy databases, Schiff and colleagues uncovered patients who did not undergo follow-up for abnormal TSH results, helping to avoid failure or delay in diagnosing hypothyroidism (Schiff 2005).

 

In our April 15, 2008 Patient Safety Tip of the Week “Computerizing Trigger Tools” we speculated how computerized trigger tools might be used to identify opportunities to intervene before harm came to patients. The Murphy study has pushed that one step closer to reality.

 

 

 

Some of our prior columns on trigger tool methodology:

·        October 30, 2007        Using IHI's Global Trigger Tool

·        April 15, 2008 Computerizing Trigger Tools

·        January 2011                No Improvement in Patient Safety: Why Not?

·        May 2011                    Just How Frequent Are Hospital Medical Errors?

·        March 2013                 Diagnostic Error in Primary Care

·        January 2014                Trigger Tools to Prevent Diagnostic Delays

 

 

Some of our prior columns on diagnostic error:

·        September 28, 2010     Diagnostic Error

·        November 29, 2011     More on Diagnostic Error

·        May 15, 2012              Diagnostic Error Chapter 3

·        May 29, 2008             If You Do RCA’s or Design Healthcare Processes…Read Gary Klein’s Work

·        August 12, 2008           Jerome Groopman’s “How Doctors Think”

·        August 10, 2010           It’s Not Always About The Evidence

·        January 24, 2012          Patient Safety in Ambulatory Care

·        October 9, 2012          Call for Focus on Diagnostic Errors

·        March 2013                  Diagnostic Error in Primary Care

·        May 2013                    Scope and Consequences of Diagnostic Errors

·        August 2013                 Clinical Intuition

·        January 2014                Trigger Tools to Prevent Diagnostic Delays

·        And our review of Malcolm Gladwell’s “Blink” in our Patient Safety Library

 

 

 

See also our other columns on communicating significant results:

 

 

 

References:

 

 

Singh H, Giardina TD, Meyer AND, et al. Types and Origins of Diagnostic Errors in Primary Care Settings. JAMA Intern Med 2013; published online February 25, 2013

http://archinte.jamanetwork.com/article.aspx?articleid=1656540

 

 

Murphy DR, Laxmisan A, Reis BA, et al. Electronic health record-based triggers to detect potential delays in cancer diagnosis. BMJ Qual Saf 2014; 23: 8-16 Published Online First: 19 July 201

http://qualitysafety.bmj.com/content/23/1/8.full.pdf+html

 

 

Schiff GD. Diagnosis and diagnostic errors: time for a new paradigm. BMJ Qual Saf 2014; 23: 1-3 Published Online First: 19 September 2013

http://qualitysafety.bmj.com/content/23/1/1.full

 

 

Schiff GD, Kim S, Krosnjar N, et al. Missed hypothyroidism diagnosis uncovered by linking laboratory and pharmacy data. Arch Intern Med 2005; 165: 574

http://archinte.jamanetwork.com/article.aspx?articleid=486445

 

 

 

 

 

 

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