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Quality Assurance01:19

Quality Assurance

4.0K
Quality assurance is the overarching term used to describe the activities employed to ensure the proper performance of a system. These activities can be classified into three categories: quality control, quality assessment, and internal corrective measures. Typically, these activities work cyclically: quality control is performed before and during the analysis, while quality assessment occurs during and after the investigation. Internal corrective measures are implemented based on the findings...
4.0K
Quality Control01:05

Quality Control

4.3K
Quality control is one of the three cyclical quality assurance activities that help keep a system under statistical control. Typical quality control activities include creating quality control charts, conducting proficiency testing, and documenting and archiving results.
Quality control helps track data, visualize trends, and identify variations, making it easier to detect deviations that may affect the accuracy of an analysis. One way to do this is by generating a quality control chart, which...
4.3K
Errors occurring during blood pressure monitoring01:25

Errors occurring during blood pressure monitoring

1.6K
Blood pressure monitoring is a crucial clinical procedure in diagnosing and managing various cardiovascular conditions. Despite its significance, the accuracy of blood pressure measurements can be compromised by multiple factors, potentially leading to either falsely high or low readings. These inaccuracies are critical as they can significantly impact patient care. So, it is vital to understand these challenges deeply and adopt strategic approaches to minimize errors.
Several factors...
1.6K
Testing a Claim about Standard Deviation01:19

Testing a Claim about Standard Deviation

2.1K
A complete procedure to test a claim about population standard deviation or population variance is explained here.
The hypothesis testing for the claim of population standard deviation (or variance) requires the data and samples to be random and unbiased. The population distribution also must be normal. There is no specific requirement on the sample size as the estimation is based on the chi-square distribution.
As a first step, the hypothesis (null and alternative) concerning the claim about...
2.1K
Uncertainty in Measurement: Reading Instruments02:46

Uncertainty in Measurement: Reading Instruments

37.7K
Counting is the type of measurement that is free from uncertainty, provided the number of objects being counted does not change during the process. Such measurements result in exact numbers. By counting the eggs in a carton, for instance, one can determine exactly how many eggs are there in the carton. Similarly, the numbers of defined quantities are also exact. For example, 1 foot is exactly 12 inches, 1 inch is exactly 2.54 centimeters, and 1 gram is exactly 0.001 kilograms. Quantities...
37.7K
Uncertainty in Measurement: Accuracy and Precision03:37

Uncertainty in Measurement: Accuracy and Precision

94.0K
Scientists typically make repeated measurements of a quantity to ensure the quality of their findings and to evaluate both the precision and the accuracy of their results. Measurements are said to be precise if they yield very similar results when repeated in the same manner. A measurement is considered accurate if it yields a result that is very close to the true or the accepted value. Precise values agree with each other; accurate values agree with a true value. 
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Conducting Respiratory Oscillometry in an Outpatient Setting
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Conducting Respiratory Oscillometry in an Outpatient Setting

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Crecientes demandas para la medición de la calidad.

Robert J Panzer1, Richard S Gitomer, William H Greene

  • 1Department of Medicine, General Medicine Division, University of Rochester Medical Center, Rochester, New York2Department of Public Health Sciences, Division of Healthcare Management, University of Rochester Medical Center, Rochester, New York.

JAMA
|November 14, 2013
PubMed
Resumen
Este resumen es generado por máquina.

Mejorar la medición de la calidad de la atención médica es crucial para la reforma basada en valores. Los desafíos clave incluyen sistemas fragmentados y la dependencia de datos erróneos, lo que requiere un enfoque en medidas integrales y transformadoras.

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Área de la Ciencia:

  • Servicios de salud Investigación Servicios de salud Investigación
  • Mejora de la calidad de la atención sanitaria Mejora de la calidad de la atención sanitaria
  • La seguridad del paciente.

Sus antecedentes:

  • La medición de la calidad de la atención médica y la seguridad del paciente están evolucionando debido a las reformas del sistema de salud de los Estados Unidos centradas en el valor.
  • El Foro Nacional de Calidad guía el desarrollo y la selección de medidas de calidad para la evaluación de la atención.

Objetivo del estudio:

  • Identificar los desafíos en los actuales sistemas de medición de la calidad de la atención médica.
  • Proponer recomendaciones para mejorar el sistema de medición de calidad de los Estados Unidos.

Principales métodos:

  • Análisis de los sistemas de medición de calidad existentes y sus limitaciones.
  • Revisión de la estrategia nacional de calidad y las asociaciones público-privadas.

Principales resultados:

  • Los desafíos incluyen diversos propósitos de medición, la dependencia de datos de reclamos defectuosos, la fragmentación del sistema y la tensión de los recursos de numerosas medidas.
  • La proliferación de medidas crea problemas logísticos para los médicos, hospitales y aseguradoras.

Conclusiones:

  • Las recomendaciones incluyen elevar el estándar de las medidas de calidad para impulsar el cambio transformacional.
  • Es esencial promover sistemas de medición armonizados e integrales, reducir las medidas basadas en reclamos y la transición a medidas de registros médicos electrónicos.