Evidence map›Paper›PMID 29230500›Full record

ArticleDer Anaesthesist2018

[Analysis and options for optimization of preoperative assessment for anesthesia at a university hospital].

M Kieninger, C Eissnert, M Seitz, K Judemann, T Seyfried, B Graf, B Sinner

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In one paragraph

Article in Der Anaesthesist, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.0field-weighted citation impact, top 19% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 13 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 1 institution in 1 country.

M KieningerKlinik für Anästhesiologie, Universitätsklinikum Regensburg, Franz-Josef-Strauß-Allee 11, 93053, Regensburg, Deutschland. martin.kieninger@ukr.de.
C EissnertKlinik für Anästhesiologie, Universitätsklinikum Regensburg, Franz-Josef-Strauß-Allee 11, 93053, Regensburg, Deutschland.
M SeitzKlinik für Anästhesiologie, Universitätsklinikum Regensburg, Franz-Josef-Strauß-Allee 11, 93053, Regensburg, Deutschland.
K JudemannKlinik für Anästhesiologie, Universitätsklinikum Regensburg, Franz-Josef-Strauß-Allee 11, 93053, Regensburg, Deutschland.
T SeyfriedKlinik für Anästhesiologie, Universitätsklinikum Regensburg, Franz-Josef-Strauß-Allee 11, 93053, Regensburg, Deutschland.
B GrafKlinik für Anästhesiologie, Universitätsklinikum Regensburg, Franz-Josef-Strauß-Allee 11, 93053, Regensburg, Deutschland.
B SinnerKlinik für Anästhesiologie, Universitätsklinikum Regensburg, Franz-Josef-Strauß-Allee 11, 93053, Regensburg, Deutschland.
University Hospital Regensburg · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundRisk assessment prior to elective surgery is an important tool in the context of perioperative patient care; however, only a few studies have been carried out to address the processes and problems during preoperative assessment for anesthesia.

aimOver a period of several weeks all preoperative anesthesia evaluations prior to elective surgery were prospectively recorded in order to generate a data pool with a view to identifying options for process optimization. MATERIAL AND

methodsAll preoperative evaluations over a period of 38 working days at the University Medical Center Regensburg were recorded and analyzed with respect to waiting time for the patient and the duration of the preoperative consultation on medication. Also documented were the patient age, ASA score, the faculty carrying out the operation, type and risk of surgery, planned time of surgery, professional experience of the anesthesiologist and the approval status for surgery. In addition, all problems which occurred during the preoperative anesthesia evaluation were documented using a questionnaire.

resultsOverall 2233 preoperative assessments for anesthesia were recorded and analyzed. The number of patients attending the preoperative assessment clinic differed markedly in the course of a day and was lower at the end of the week. Approval for surgery with no reservations was given more frequently by anesthesiologists with more than 5 years professional experience and consultants compared to younger colleagues. The main reason for approval with reservations or no approval was the lack of patient records and test results, which should have been presented according to the in-house standard for preoperative assessment for anesthesia. The mean waiting time was 58.6 ± 30.3 min, the mean duration of the patient documentation review and physician-patient consultation together was 33.6 ± 16.3 min. Anesthesiologists with 2-5 years professional experience needed significantly less time for patient documentation reviews and physician-patient consultations than younger and more experienced colleagues. The duration of the preoperative assessment for anesthesia correlated with the ASA score and risks of surgery.

conclusionThe analysis of processes and problems in the context of preoperative assessment for anesthesia revealed several options for optimization. Major efforts should be the implementation of an appointment system for the preoperative assessment clinic in order to generate a homogeneous distribution of patients during the course of a day. Furthermore, surgeons and case managers should be requested to refer patients to the preoperative assessment clinic only with complete records and test results according to the in-house standard.

Indexed as

AnesthesiaElective Surgical ProceduresHospitals, UniversityHumansPerioperative CarePhysician-Patient RelationsPreoperative CareReferral and ConsultationRisk AssessmentSurveys and QuestionnairesPreanesthesia visitPreoperative assessment clinicProcess optimizationRisk evaluationWaiting time

Identifiers

PMID29230500
OpenAlexW2774454886

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.