Laura M. Lee, Laura M. Lee, R.N. R.N. Clinical Clinical Center, NIH Center, NIH The Epidemiology The Epidemiology of Clinical Errors of Clinical Errors in a Research Hospital: in a Research Hospital: Mining Occurrence Mining Occurrence Reporting Data for Reporting Data for “ “ Low Hanging Fruit” Low Hanging Fruit”
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Laura M. Lee, R.N. Clinical Center, NIH The Epidemiology of Clinical Errors in a Research Hospital: Mining Occurrence Reporting Data for Mining Occurrence.
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Laura M. Lee, R.N.Laura M. Lee, R.N.Clinical Center, NIHClinical Center, NIH
The Epidemiology The Epidemiology of Clinical Errors of Clinical Errors
in a Research Hospital:in a Research Hospital: Mining Occurrence Reporting Mining Occurrence Reporting
Data for Data for ““Low Hanging Fruit”Low Hanging Fruit”
Bona BenjaminBona Benjamin Steve BergstromSteve BergstromGinnie DaineGinnie Daine Charles DanielsCharles DanielsClare HastingsClare Hastings David HendersonDavid HendersonMary SparksMary Sparks
• 250 bed hospital at NIH250 bed hospital at NIH• Mission is clinical research; Mission is clinical research;
primary primary product is scienceproduct is science• All patients are volunteers All patients are volunteers • Over 1100 protocols (Phase I or Over 1100 protocols (Phase I or
II clinical trials, natural history)II clinical trials, natural history)• ““High risk; high reward” High risk; high reward”
The Clinical CenterThe Clinical Center
The TeamThe Team
• First implemented in 1980First implemented in 1980• Part of Medical Information SystemPart of Medical Information System• Exceeded regulatory requirementsExceeded regulatory requirements• User feedback – uniformly negativeUser feedback – uniformly negative
Inflexible architectureInflexible architecture Limited data entry optionsLimited data entry options ““Black hole” - no feedback Black hole” - no feedback Limited use as an improvement toolLimited use as an improvement tool
• In 1998 reengineered entire system based In 1998 reengineered entire system based on stakeholder requirementson stakeholder requirements Non-punitive environmentNon-punitive environment Web-basedWeb-based Logical, user-friendly data entryLogical, user-friendly data entry Automatic notification of “content Automatic notification of “content
experts”experts” Users ability to view occurrence reports Users ability to view occurrence reports
and follow-up informationand follow-up information Flexible architecture that allows for Flexible architecture that allows for
customizable data collection customizable data collection Customization of reports (e.g., unit, Customization of reports (e.g., unit,
Total reports classified as errorsTotal reports classified as errors 38%38%Did not reach patientDid not reach patient 24%24%Reached patient but no change in patient statusReached patient but no change in patient status 36%36%Resulted in increased monitoringResulted in increased monitoring 37%37%Temporary change in statusTemporary change in status 2%2%Prolonged LOS or harmProlonged LOS or harm <1%<1%Near-death eventNear-death event <1%<1%DeathDeath --------
Errors adversely affecting Errors adversely affecting clinical researchclinical research <1%<1%
Impact on Patient Care and Impact on Patient Care and Clinical ResearchClinical Research
So we know that bad things So we know that bad things happen… happen…
• We now haveWe now have lots lots of data about “untoward of data about “untoward events” that occur in our clinical research events” that occur in our clinical research environmentenvironment
• Needed a process / methodology for:Needed a process / methodology for: Managing the dataManaging the data Identifying clusters of eventsIdentifying clusters of events Driving process improvementDriving process improvement Continuously monitoring the eventsContinuously monitoring the events
• Implementation of a non-punitive, interactive Implementation of a non-punitive, interactive Occurrence Reporting System dramatically Occurrence Reporting System dramatically increased reporting of clinical care events in a increased reporting of clinical care events in a clinical research institution;clinical research institution;
• The ORS database facilitates The ORS database facilitates epidemiological identification of clusters of epidemiological identification of clusters of adverse events;adverse events;
• Data from the ORS can be used to drive Data from the ORS can be used to drive clinical performance improvement activities clinical performance improvement activities and increase patient safety in our and increase patient safety in our environment;environment;
The ORS is a reliable mechanism for The ORS is a reliable mechanism for monitoring the efficacy of improvement monitoring the efficacy of improvement interventions.interventions.