School of Medicine and Health Sciences Poster Presentations

Title

Toward Improving the Quality Assurance Self Reporting in Anesthesia

Poster Number

159

Document Type

Poster

Status

Medical Student

Abstract Category

Clinical Specialties

Keywords

quality improvement, adverse events, reporting, medications, Anesthesia

Publication Date

Spring 2018

Abstract

Introduction

The mainstay of quality assurance (QA) programs in anesthesia is the end-of-case self report. It is well recognized that many adverse events that occur during cases are not reported, however the extent of underreporting is difficult to estimate. Medications that are not used routinely, such as pressors, anti-hypertensive agents, antidotes and reversal agents may be used as “indicators” since their use provides a window into the true incidence of adverse events (AE) during anesthesia.

In this report, we analyzed our QA database and EMR to compare the incidence of reported AE with the use of indicator medications. While the true incidence of adverse events is not knowable, analysis of indicator medications use might bridge the gap.

Methods

AE and indicator medications as documented in Epic Anesthesia (Epic Systems, Verona WI) are made available in a Qlikview (Qliktech, Radnor PA) anesthesia dashboard. The date range from January 2013 to June 2015 was selected and all reported QA indicators and all indicator meds from this time were extracted into a spreadsheet (Excel, Microsoft, Bellevue WA).

Some indicator medications were used either for prophylaxis (planned) or to manage an AE (unplanned) i.e. diphenhydramine to prevent or treat allergy. We therefore determined thresholds for each drug that would relate to an AE and (AE yes or no) was added to the spreadsheet.

Descriptive statistics were used to determine the rate an AE was reported correctly associated with classes of medications and individual medications.

Results

During the study period, 804 incidences of administrations of indicator medications were recorded. In many instances multiple administrations occurred for the same AE, resulting in 514 unique cases. In 157 (31%) of unique cases, administrations were deemed planned, leaving 357 cases to analyze if an AE was documented.

In 303/357 (85%) cases, AE were not recorded, leaving only 15% that were documented correctly. Different classes of medications were reported incorrectly with Anti-Croup, and Anti-Hypertensives not recorded 100% of the time indicating that their use was not even considered to be an AE. Opioid and benzodiazepine reversal agents and antiarrythmic agents were recorded correctly only 50% of the time. Individual drugs usage record ranged from adenosine with 100% correctly acknowledging the AE to esmolol, labetolol, and hydralazine not correctly identified with an AE 100% of the time.

Conclusion

Our study shows significant underreporting of adverse events during anesthesia. With EMR, indicator meds administration can be used to identify unreported AE. Combination of education and creative programming that directs the provider to report the use of drugs indicative of an AE would likely improve QA self report and provide a more accurate incidence of adverse during anesthesia.

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Creative Commons License
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Toward Improving the Quality Assurance Self Reporting in Anesthesia

Introduction

The mainstay of quality assurance (QA) programs in anesthesia is the end-of-case self report. It is well recognized that many adverse events that occur during cases are not reported, however the extent of underreporting is difficult to estimate. Medications that are not used routinely, such as pressors, anti-hypertensive agents, antidotes and reversal agents may be used as “indicators” since their use provides a window into the true incidence of adverse events (AE) during anesthesia.

In this report, we analyzed our QA database and EMR to compare the incidence of reported AE with the use of indicator medications. While the true incidence of adverse events is not knowable, analysis of indicator medications use might bridge the gap.

Methods

AE and indicator medications as documented in Epic Anesthesia (Epic Systems, Verona WI) are made available in a Qlikview (Qliktech, Radnor PA) anesthesia dashboard. The date range from January 2013 to June 2015 was selected and all reported QA indicators and all indicator meds from this time were extracted into a spreadsheet (Excel, Microsoft, Bellevue WA).

Some indicator medications were used either for prophylaxis (planned) or to manage an AE (unplanned) i.e. diphenhydramine to prevent or treat allergy. We therefore determined thresholds for each drug that would relate to an AE and (AE yes or no) was added to the spreadsheet.

Descriptive statistics were used to determine the rate an AE was reported correctly associated with classes of medications and individual medications.

Results

During the study period, 804 incidences of administrations of indicator medications were recorded. In many instances multiple administrations occurred for the same AE, resulting in 514 unique cases. In 157 (31%) of unique cases, administrations were deemed planned, leaving 357 cases to analyze if an AE was documented.

In 303/357 (85%) cases, AE were not recorded, leaving only 15% that were documented correctly. Different classes of medications were reported incorrectly with Anti-Croup, and Anti-Hypertensives not recorded 100% of the time indicating that their use was not even considered to be an AE. Opioid and benzodiazepine reversal agents and antiarrythmic agents were recorded correctly only 50% of the time. Individual drugs usage record ranged from adenosine with 100% correctly acknowledging the AE to esmolol, labetolol, and hydralazine not correctly identified with an AE 100% of the time.

Conclusion

Our study shows significant underreporting of adverse events during anesthesia. With EMR, indicator meds administration can be used to identify unreported AE. Combination of education and creative programming that directs the provider to report the use of drugs indicative of an AE would likely improve QA self report and provide a more accurate incidence of adverse during anesthesia.