Give one example of a data collection method used in one of the studies identified in your Week 5 project. What variable was this method used to measure?

Week 5: Measurement Strategies

Give one example of a data collection method used in one of the studies identified in your Week 5 project. What variable was this method used to measure?

Peer Reply: Week 5: Measurement Strategies

Give one example of a data collection method used in one of the studies identified in your Week 5 project. What variable was this method used to measure?

Data was collected retrospectively from two academic hospitals and two community hospitals in Massachusetts. Data was limited to mechanical ventilation episodes that started between March 1 and August 31 in each year from 2017 to 2020.

Data was extracted through the electronic health record systems by using the Center for Disease Control’s (CDC) ventilator associated event (VAE) criteria. The following information was also collected along with the start and stop dates of mechanical ventilation: age, sex, date of admission, date of VAE, and mortality during hospitalization.

Patients who received extracorporeal membrane oxygenation were excluded from the data as this does not beet the definition of the CDC’s VAE criteria. Comorbidities were extracted from diagnoses in the electronic medical records using the Elixhauser method.

The Elixhauser Comorbidity Index is a method of categorizing comorbidities (Links to an external site.) of patients based on the International Classification of Diseases (ICD) (Links to an external site.) diagnosis codes found in administrative data, such as hospital abstracts data. Each comorbidity category is dichotomous — it is either present or it is not. The Index can be used to predict hospital resource use and in-hospital mortality (Elixhauser et al., 1998) (Links to an external site.) (Tsai et. al., 2020).

This method was used to compare 1) VAE rates in pandemic years vs. pre-pandemic years, and 2) VAE causes in COVID-19 positive vs. COVID-19 negative patients (Weinberger et. al., 2022).

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