[Morbidity and mortality conferences : Structure and clinical experiences]

S Semmler1

  • 1Klinisches Qualitäts- und Risikomanagement, Charité - Universitätsmedizin Berlin, Charitéplatz 1, 10117, Berlin, Deutschland. sibylle.semmler@charite.de.

Herz
|July 1, 2018
PubMed

Insights

Morbidity and mortality (M&M) conferences are vital for patient safety in Germany. Structured implementation is key for learning, error culture, and optimizing treatment processes, even with limited resources.

Area of Science:

  • Healthcare Management
  • Patient Safety
  • Medical Education

Background:

  • Morbidity and mortality (M&M) conferences are increasingly recognized as crucial risk management tools in German healthcare.
  • Beyond risk identification, M&M conferences aim to foster learning, a modern error culture, and treatment process optimization.

Purpose of the Study:

  • To provide recommendations for the structured implementation of M&M conferences.
  • To address challenges of limited personnel and time resources in implementing M&M conferences.
  • To emphasize the need for integration into a clinic-wide overall concept with central structures.

Main Methods:

  • The study draws upon experiences from a large university hospital.
  • Recommendations are based on practical implementation insights.

Main Results:

  • A structured approach is essential for successful M&M conference implementation.
  • Integration into a broader clinic-wide strategy with central structures is vital.
  • Effective M&M conferences require dedicated resources and planning.

Conclusions:

  • Structured M&M conferences enhance patient safety through learning and process improvement.
  • Successful implementation necessitates a strategic, integrated approach.
  • M&M conferences are a key component of modern risk management in healthcare.

Related Concept Videos

What is an Experiment?01:12

What is an Experiment?

An experiment is a planned activity carried out under controlled conditions. The purpose of an experiment is to investigate the relationship between two variables. When one variable causes change in another, we call the first variable the explanatory or independent variable. The affected variable is called the response or dependent variable. In a randomized experiment, the researcher manipulates values of the explanatory variable and measures the resulting changes in the response variable. The...
19.0K
Thomson's e/m Experiment01:19

Thomson's e/m Experiment

In a beam of charged particles created by a heated cathode, the particles move at different speeds. However, many applications need a beam with uniform particle speeds. An arrangement known as a velocity selector uses electric and magnetic fields to pick particles with a particular speed from the beam.
A particle with charge q, speed v, and mass m enters an area from the top, where the magnetic and electric fields are perpendicular both to the particle's motion and to one another. The magnetic...
6.9K
Controls in Experiments01:13

Controls in Experiments

When conducting an experiment, it is crucial to have control to reduce bias and accurately measure the dependent variables. It also marks the results more reliable. Controls are elements in an experiment that have the same characteristics as the treatment groups but are not affected by the independent variable. By sorting these data into control and experimental conditions, the relationship between the dependent and independent variables can be drawn. A randomized experiment always includes a...
18.0K
Randomized Experiments01:13

Randomized Experiments

The randomization process involves assigning study participants randomly to experimental or control groups based on their probability of being equally assigned. Randomization is meant to eliminate selection bias and balance known and unknown confounding factors so that the control group is similar to the treatment group as much as possible. A computer program and a random number generator can be used to assign participants to groups in a way that minimizes bias.
Simple randomization
Simple...
9.1K
Crossover Experiments01:16

Crossover Experiments

Crossover experiments, also called the repeated-measurements design, is a study design in which all experimental units are exposed to all treatments in different periods. Crossover experiments are generally used in psychology, the pharmaceutical industry, agriculture, and medicine.
Crossover designs are performed even with smaller sample sizes since the samples can act as their controls. These are better than simple randomized trials since patients are exposed to all the treatments.
4.6K
The Stanford Prison Experiment03:20

The Stanford Prison Experiment

The famous and controversial Stanford Prison Experiment, conducted by social psychologist Philip Zimbardo and his colleagues at Stanford University, demonstrated the power of social roles, social norms, and scripts.
24.8K