Quality of Quality Data (QoQ)
Recruitment status was Recruiting
Data on quality of clinical anesthesia are important for the improvement of both quality and patient safety in this field. Routine quality data are often collected by professionals busy with patient care. This study examines the reliability of routinely collected quality data by comparing the electronic anesthesia record with the respective reports on quality-indicating events, i.e. whether events during the anesthetic (e.g., drop of blood pressure, irregular heart rhythm, and others) were actually reported or not. Additionally, interviews with reporting staff (physicians and nurses) are performed to gain insight in possible obstacles to reporting during the working process.
|Study Design:||Time Perspective: Retrospective|
|Official Title:||Quality of Quality Data - A Retrospective Study on Routine Quality Data Reporting in Anesthesia|
- Event reporting rate [ Time Frame: Outcome measure is assessed at the end of each included anesthetic. Event reporting rate comprises reporting rate of defined events occurring during the given anesthetic. Durations of anesthetics are approximately between 0.5 and 5 hours. ] [ Designated as safety issue: No ]For defined events (hypotensive, hypertensive, bradycardic, tachycardic, and hypoxemic episodes), occurrence documented in the electronic anesthesia record is compared with their actual reporting in the reporting section of the record. From this, reporting rate is calculated for the various event types.
|Study Start Date:||November 2011|
|Estimated Study Completion Date:||March 2012|
|Estimated Primary Completion Date:||March 2012 (Final data collection date for primary outcome measure)|
Anesthesia staff Interviewees
Staff entering quality data into the electronic anesthesia record are interviewed regarding working conditions and record layout
Anesthesia records (all types of procedures) are checked for correct reporting of defined events
Reliable quality data are an important basis for attempts to improve quality and safety of patient care. For anesthetic practice in Switzerland, an "Absolute Minimal Data Set" (AMDS) of preoperative patient characteristics and intra- and postoperative quality indicators is provided by the Institute of Social and Preventive Medicine (IUMSP, University of Lausanne) in cooperation with the Swiss Society of Anaesthesiology and Reanimation (SGAR-SSAR). Data are electronically forwarded by the participating institutions to IUMSP, whereas primary collection can be achieved by traditional paper records or electronic records as part of anesthesia information management systems (AIMS).
In the investigator's institution, physician and nurse anesthetists are supposed to use a window in the electronic anesthesia record for this purpose. This form should be completed at the end of each case. If an event according to the AMDS definitions occurs at least once during anesthesia, the respective box (e.g., "intraoperative hypotension") should be ticked in the form. The anesthesia record cannot be closed unless the quality form is filled, which can notably be done even in advance "on the quick" by ticking "no events". Considering the numerous duties of anesthesia staff at the end of a case, the investigators questioned the reliability of data generated during this busy phase.
A pilot study of 50 consecutive unselected cases of the year 2010 revealed a low rate of reporting (10.8%) of selected perioperative events related to anesthesia (specifically: hypotensive, hypertensive, bradycardic, tachycardic, and hypoxemic episodes). Consequently, the current extensive study with more representative sample size was initiated. To gain insight into possible causes (among others: time pressure, unclear definitions, fear of litigation), interviews with anesthesia staff are performed and will hopefully provide a basis for possible improvements. For the time being and considering the common nature of possible causes, the investigators suspect that their results may not be specific for their institution. The incidence of perioperative events may be grossly underestimated if the process of data collection is not properly designed and monitored.
|Contact: Johannes Wacker, MDfirstname.lastname@example.org|
|Contact: Georg Mols, MD, Prof.||+41443872368|
|Institute of Anesthesiology and Intensive Care, Klinik Hirslanden Zürich, Switzerland||Recruiting|
|Zürich, Switzerland, CH-8032|
|Contact: Johannes Wacker, MD +41443872365 email@example.com|
|Contact: Georg Mols, MD, Prof +41443872368|
|Principal Investigator: Johannes Wacker, MD|
|Sub-Investigator: Elke Leisinger, MD|
|Principal Investigator:||Johannes Wacker, MD||IFAI, Klinik Hirslanden, Zürich, Switzerland|
|Study Director:||Georg Mols, MD, Prof.||IFAI, Klinik Hirslanden Zürich, Switzerland|
|Study Director:||Reto Stocker, MD, Prof.||IFAI, Klinik Hirslanden Zürich, Switzerland|