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Application of plan-do-study-act (PDSA) principles to improve patient safety and specimen labeling errors in interventional radiology (IR)
JVIR
’
Scientific Session
Tuesday
’
S147
Conclusions: Large volume patient data analysis, combined with workflow observations, can pinpoint hidden problems in an IR facility’s pre-procedure and recovery areas.
specimen labeling errors in IR to 1%. Our next goal is to decrease our error rate to 0%, since these errors threaten patient safety and are entirely avoidable.
4:12 PM
4:21 PM
Abstract No. 324
Application of plan-do-study-act (PDSA) principles to improve patient safety and specimen labeling errors in interventional radiology (IR)
Abstract No. 325
Big data in IR: operator preferences for discrete data field templates
Purpose: To improve patient safety through the reduction of specimen labeling errors in Interventional Radiology (IR). Materials: Baseline data collected by the pathology department included: number of labeling errors, types of errors (non-labeled, incompletely labeled, incorrectly labeled), and type of procedures associated with errors. These data were analyzed using a Pareto chart. Factors in IR contributing to these errors were analyzed through the development of process map, a fishbone diagram created by a multi-professional focus group (MD, RT, and RN), and a prioritization matrix. The PSDA methodology was employed with the goal to reduce specimen labeling errors. A statistical control chart was used to determine significance of these interventions to reduce specimen error rates. Results: Baseline data demonstrated an overall specimen error rate of 4.2%, ranging from 16.7% to 0%. The Pareto chart showed that incomplete requisitions accounted for more than 80% of these errors. The process map demonstrated variation in ways referring providers requested specimens, how specimens were labeled, and who was responsible for specimen labeling. Using QI tools, the focus group developed 3 interventions: (1) creation of an order entry system which allows referring providers to choose which specific labs/ specimens they want sent, (2) development of a standardized double-check process through which an RN or RT confirms the specimen labels with the operator at the end of the procedure, and (3) use of a label printer rather than handwritten labels for slides and specimen vials. Post-intervention showed a lower and more consistent error rate ranging from 2.1% to 0.2%, with an average error rate of 1.0%. Conclusions: Through the use of classic process improvement tools, we decreased the variability and overall frequency of
Purpose: Historically, IR procedure reports are free-text documents that provide a procedure narrative but do not capture data for outcomes analysis. Benefits of discrete data field templates (DDFTs) include consistent procedure data capture, automated parsing of reports into databases, and improved ability to track outcomes. There may be reluctance to adopt DDFTs, however, due to concerns of adversely affected workflow. This study evaluates the impact of adoption of DDFTs in a single tertiary care academic institution. Materials: DDFTs for all TACE procedures were implemented through a speech recognition system. Surveys were completed by IR attendings and fellows before and 6 months after DDFT implementation. Responses to survey questions were analyzed. Results: Ten IR attendings and five IR fellows completed preand post-implementation surveys with results shown in the accompanying table. For IR fellows, the primary creators of procedure reports at our institution, DDFTs were easier to use and faster to complete compared to conventional free textbased report templates. For IR attendings, DDFTs were more difficult to use and more time consuming. For all respondents, DDFTs made it easier to find, retrieve, and utilize data for quality improvement, research, and teaching. Differences in pre- and post-implementation question scores were not found to be statistically significant, likely related to sample size. Conclusions: Discrete data field templates can be implemented into an IR TACE practice with a variable impact on work flow. Improvements in work flow were perceived by users with the most experience creating reports using DDFTs.
2
3
Question
Criteria
How long does it take to dictate a TACE study?
1 ¼ o5 min – 5 ¼ 420 min
How easy-to-use are the TACE report templates? How easy is it to find, retrieve, and QI? utilize data in your dictations for Research? Teaching?
1 ¼ very easy – 5 ¼ very hard
Fellow
Attending
Pre 4.2
Post 3.6
Pre 1.6
Post 3.3
2.8 3.2 3.4 3
2.2 3.2 2.5 2.8
2.7 3.8 3.8 3.5
3.5 3.1 3.1 2.9
TUESDAY: Scientific Sessions
K. Burk , J. Martino , G. Martinez-Salazar ; 1 Massachusetts General Hospital, Jamaica Plain, MA; 2 MGH, Winthrop, MA; 3Massachusetts General Hospital, Boston, MA.
A. Eifler1, R. Shah2, G. Hwang3, W. Hwang4, V. Arendt5, L. Hofmann6; 1Stanford University, San Francisco, CA; 2 Stanford University, Stanford, CA; 3N/A, Hillsborough, CA; 4Stanford University Medical Center, Stanford, CA; 5 Stanford University School of Medicine, Stanford, CA; 6 Stanford University Medical Center, Palo Alto, CA.
1
’
Scientific Session
Tuesday
’
S147
Conclusions: Large volume patient data analysis, combined with workflow observations, can pinpoint hidden problems in an IR facility’s pre-procedure and recovery areas.
specimen labeling errors in IR to 1%. Our next goal is to decrease our error rate to 0%, since these errors threaten patient safety and are entirely avoidable.
4:12 PM
4:21 PM
Abstract No. 324
Application of plan-do-study-act (PDSA) principles to improve patient safety and specimen labeling errors in interventional radiology (IR)
Abstract No. 325
Big data in IR: operator preferences for discrete data field templates
Purpose: To improve patient safety through the reduction of specimen labeling errors in Interventional Radiology (IR). Materials: Baseline data collected by the pathology department included: number of labeling errors, types of errors (non-labeled, incompletely labeled, incorrectly labeled), and type of procedures associated with errors. These data were analyzed using a Pareto chart. Factors in IR contributing to these errors were analyzed through the development of process map, a fishbone diagram created by a multi-professional focus group (MD, RT, and RN), and a prioritization matrix. The PSDA methodology was employed with the goal to reduce specimen labeling errors. A statistical control chart was used to determine significance of these interventions to reduce specimen error rates. Results: Baseline data demonstrated an overall specimen error rate of 4.2%, ranging from 16.7% to 0%. The Pareto chart showed that incomplete requisitions accounted for more than 80% of these errors. The process map demonstrated variation in ways referring providers requested specimens, how specimens were labeled, and who was responsible for specimen labeling. Using QI tools, the focus group developed 3 interventions: (1) creation of an order entry system which allows referring providers to choose which specific labs/ specimens they want sent, (2) development of a standardized double-check process through which an RN or RT confirms the specimen labels with the operator at the end of the procedure, and (3) use of a label printer rather than handwritten labels for slides and specimen vials. Post-intervention showed a lower and more consistent error rate ranging from 2.1% to 0.2%, with an average error rate of 1.0%. Conclusions: Through the use of classic process improvement tools, we decreased the variability and overall frequency of
Purpose: Historically, IR procedure reports are free-text documents that provide a procedure narrative but do not capture data for outcomes analysis. Benefits of discrete data field templates (DDFTs) include consistent procedure data capture, automated parsing of reports into databases, and improved ability to track outcomes. There may be reluctance to adopt DDFTs, however, due to concerns of adversely affected workflow. This study evaluates the impact of adoption of DDFTs in a single tertiary care academic institution. Materials: DDFTs for all TACE procedures were implemented through a speech recognition system. Surveys were completed by IR attendings and fellows before and 6 months after DDFT implementation. Responses to survey questions were analyzed. Results: Ten IR attendings and five IR fellows completed preand post-implementation surveys with results shown in the accompanying table. For IR fellows, the primary creators of procedure reports at our institution, DDFTs were easier to use and faster to complete compared to conventional free textbased report templates. For IR attendings, DDFTs were more difficult to use and more time consuming. For all respondents, DDFTs made it easier to find, retrieve, and utilize data for quality improvement, research, and teaching. Differences in pre- and post-implementation question scores were not found to be statistically significant, likely related to sample size. Conclusions: Discrete data field templates can be implemented into an IR TACE practice with a variable impact on work flow. Improvements in work flow were perceived by users with the most experience creating reports using DDFTs.
2
3
Question
Criteria
How long does it take to dictate a TACE study?
1 ¼ o5 min – 5 ¼ 420 min
How easy-to-use are the TACE report templates? How easy is it to find, retrieve, and QI? utilize data in your dictations for Research? Teaching?
1 ¼ very easy – 5 ¼ very hard
Fellow
Attending
Pre 4.2
Post 3.6
Pre 1.6
Post 3.3
2.8 3.2 3.4 3
2.2 3.2 2.5 2.8
2.7 3.8 3.8 3.5
3.5 3.1 3.1 2.9
TUESDAY: Scientific Sessions
K. Burk , J. Martino , G. Martinez-Salazar ; 1 Massachusetts General Hospital, Jamaica Plain, MA; 2 MGH, Winthrop, MA; 3Massachusetts General Hospital, Boston, MA.
A. Eifler1, R. Shah2, G. Hwang3, W. Hwang4, V. Arendt5, L. Hofmann6; 1Stanford University, San Francisco, CA; 2 Stanford University, Stanford, CA; 3N/A, Hillsborough, CA; 4Stanford University Medical Center, Stanford, CA; 5 Stanford University School of Medicine, Stanford, CA; 6 Stanford University Medical Center, Palo Alto, CA.
1