Boston University School of Public Health, Boston, MA,

1. Development and Use of Ambulatory Adverse Event Trigger ToolsAmy K. Rosen, PhDAHRQ Conference Sept. 14, 2009 Boston University School of Public Health, Boston, MA, VA Center for Healthcare Quality, Outcomes, and Economic Research (CHQOER), Bedford MA akrosen@bu.edu

2. Acknowledgements • PI Amy Rosen, PhD • Co-PI Jonathan Nebeker, MD, MS • Co-Investigators: • Stephan Gaehde, MD • Haytham Kaafarani, MD, MPH • Brenna Long, MA • Hillary Mull, MPP • Brian Nordberg, BS • Steve Pickard, MS • Peter Rivard, PhD • Lucy Savitz, PhD, MBA • Chris Shanahan, MD, MPH • Stephanie Shimada, PhD Sponsored by AHRQ Contract No. HHSA290200600012, Task Order Officer Amy Helwig, MD

3. Project Goal and Settings • Goal: Develop adverse event (AEs) triggers for the outpatient setting • Outpatient surgery • Outpatient adverse drug events (ADEs) • Three sites for patient data: • Boston Medical Center (BMC) • Intermountain Healthcare • Veterans Health Administration (VA)

4. Background • Triggers are algorithms that use electronic patient data to identify patterns consistent with a possible adverse event • e.g. , the combination of a lab value threshold and an active prescription • Global vs. AE specific trigger: • Flags the chart for the suspicion of occurrence of any AE or the occurrence of a specific AE • Interventionist triggers: • Mostly ADEs • Gives providers a chance to respond and avoid alert overload

5. Literature Review Clinical Input Focus Groups Clinical Advisory Panel Modified Delphi Panel Final List of Triggers Methods Document existing triggers Establish prevalence of outpatient AEs Establish primary causes of outpatient AEs

6. Literature Review Clinical Input Focus Groups Modified Delphi Panel Final List of Triggers Methods Document existing triggers Establish prevalence of outpatient AEs Establish primary causes of outpatient AEs Review epidemiological basis for AEs Input clinical knowledge and data needed into trigger rules Clinical Advisory Panel

7. Literature Review Clinical Input Focus Groups Clinical Advisory Panel Modified Delphi Panel Final List of Triggers Methods Document existing triggers Establish prevalence of outpatient AEs Establish primary causes of outpatient AEs Review epidemiological basis for AEs Input clinical knowledge and data needed into trigger rules Research data limitations Determine priority areas for trigger development Develop methods to critique triggers

8. Literature Review Clinical Input Focus Groups Clinical Advisory Panel Modified Delphi Panel Methods Document existing triggers Establish prevalence of outpatient AEs Establish primary causes of outpatient AEs Review epidemiological basis for AEs Input clinical knowledge and data needed into trigger rules Research data limitations Determine priority areas for trigger development Develop methods to critique triggers Refine rules/trigger logic Refine priority areas priority areas for trigger development Final List of Triggers

9. Literature Review Clinical Input Focus Groups Clinical Advisory Panel Modified Delphi Panel Final List of Triggers Methods Document existing triggers Establish prevalence of outpatient AEs Establish primary causes of outpatient AEs Review epidemiological basis for AEs Input clinical knowledge and data needed into trigger rules Research data limitations Determine priority areas for trigger development Develop methods to critique triggers Refine rules/trigger logic Refine priority areas priority areas for trigger development Rate priority of AE causes Rate priority of AEs Rate triggers based on system- and patient-level perspectives

10. Methods • Obtained de-identified clinical data from each site • Combined the data fields from each site into a SQL database • Created a mock electronic medical record (EMR) interface to enable case classification Boston Medical Ctr Intermountain VA (VISN 19) Mock EMR Trigger Database

11. Global Trigger Tools – Outpatient Surgery

12. AE-Specific Trigger Tools – Outpatient Surgery

13. Surgery Trigger Logic: Procedure • Fire if: • Same-day surgery • AND • procedure (interventional radiological OR urological OR cardiac OR gastroenterological) • OR re-operation ≤ 30 days

14. AE-Specific Trigger Tools – ADE

15. AE-Specific Trigger Tools – ADE (cont’d)

16. ADE Trigger Logic: Change in Renal Clearance • Fire if: • Subsequent increase in creatinine > 33% and dose > than dose prior to creatinine measurement (This is the reference creatinine level) AND • NOT (trimethoprim started in interval between 1 day prior to creatinine measurement and after reference creatinine level) AND • NOT (all GFR reducers and renal toxins discontinued or expired > 3 months prior to triggering value) • Remove trigger if response taken within window: • Renal toxin discontinued or GFR reducer dose reduced 0-6 days after firing criteria satisfied OR • Creatinine resulted 0-6 days after firing criteria satisfied

17. Data Challenges – Accessing Data • Political/Logistical Barriers • Gaining permission to access the data • Developed de-identification algorithm • Challenge meeting HIPAA compliance • Administrative barriers to obtaining access • Encrypting/ ensuring safe transfer of data between sites • Safe storage of data from multiple institutions • IT Resources • Availability of personnel for data pulls • Computing infrastructures • Pulling notes too resource intensive

18. Data Challenges – Data Elements • “IT Black Box” • Researchers reliant on IT staff’s programming, no way to ascertain completeness of data • Inconsistencies in coding across institutions • Same information, different coding: • Gender: M/F vs 1/2/3 • Units of measure: metric vs US vs missing • ICD-9-CM codes stored with or without periods • ICD-9-CM procedure codes were unavailable for some procedures • Lab titles inconsistent across settings • Lack of documentation re: coding practices • Numeric results within text data

19. Data Challenges – Data Elements (cont’d) • Missing data • Loss of information from text de-identification algorithm • Fuzzy pattern and word matching removed some key clinical terms from clinical notes • De-identification made notes difficult to read • Removal of dates resulted in loss of information about clinical order • Missing National Drug Codes (NDCs) in pharmacy data • Free text vs. standardized daily dosage information • TAKE ONE-HALF TABLET BY MOUTH EVERY DAY FOR 2 WEEKS, THEN TAKE  ONE-HALF TABLET TWO (2) TIMES A DAY FOR 2 WEEKS, THEN TAKE ONE TABLET  TWO (2) TIMES A DAY FOR 2 WEEKS, THEN TAKE TWO TABLETS TWO (2) TIMES A  DAY FOR 2 WEEKS, THEN TAKE THREE TABLETS TWO (2) TIMES A DAY FOR 2  WEEKS, THEN TAKE FOUR TABLETS TWO (2) TIMES A DAY INCREASE DOSE  GRADUALLY.  WHEN GOING FROM 25 TO 50 MG START WITH INCREASING THE AM  DOSE FOR 2WEEKS, THEN THE AM AND PM DOSE.  DO THIS WHEN INCREASING  FROM 50 TO 75 AND 75 TO 100.  IF QUESTIONS PLEASE CALL. • Lack of units in lab data

20. Next Steps • Case classification • RNs classifying surgery AE trigger-flagged cases • Pharmacists classifying ADE trigger-flagged cases • Calculate positive predictive value (PPV) for each trigger • Conduct a second round of focus groups at each institution • Hold phone call with trigger experts to review logic and discuss results

21. Dissemination to Date • Triggers and Targeted Injury Detection Systems (TIDS)Expert Panel Meeting , Rockville, MD. June 2008. See proceedings at http://www.ahrq.gov/QUAL/triggers/ • Mull HJ & Nebeker, JR. Informatics Tools for the Development of Triggers for Outpatient Adverse Drug Events. AMIA Annual Symposium Proceedings. Nov 2008, 6:505-9. • Kaafarani H, Rosen AK, et al. What is a Trigger Tool to a Surgeon: Designing Trigger Tools for Surveillance of Adverse Events in Ambulatory Surgery. Massachusetts Chapter of the American College of Surgeons 55th Annual Meeting, Boston, MA. Dec 2008. • Kaafarani H, Rosen AK, et al. Development of Trigger Tools for Surveillance of Adverse Events in Ambulatory Surgery. VA HSR&D QUERI National Meeting, Phoenix, AZ. Dec 2008. • Kaafarani H, Rosen AK, et al. Developing Trigger Tools for Surveillance of Adverse Events in Same-Day Surgery: A Literature-Based, End-User Inspired & Expert-Evaluated Methodology. VA HSR&D Annual Meeting, Baltimore, MD. Feb 2009. • Shimada S, Rivard P, et al. Priorities & Preferences of Potential Ambulatory Trigger Tool Users. AcademyHealth Annual Research Meeting, Chicago, IL. June 2009. • Kaafarani H, Rosen AK, et al. Developing Trigger Tools for Surveillance of Adverse Events in Same-Day Surgery: A Literature-Based, End-User Inspired and Expert-Evaluated Methodology. AHRQ Annual Meeting, Bethesda, MD. Sept 2009. • Kaafarani H, Rosen AK, et al. Development of Trigger Tools for Surveillance of Adverse Events in Ambulatory Surgery. Quality and Safety in Health Care. (forthcoming)