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Performing the Study Data Collection. Paula Peyrani, MD Director Clinical Research Program Infectious Diseases Division, University of Louisville Louisville, Kentucky, USA. Objectives. To review important tools for the collection of clinical data . Data collection form Pretesting
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Performing the StudyData Collection Paula Peyrani, MD Director Clinical Research Program Infectious Diseases Division, University of Louisville Louisville, Kentucky, USA
Objectives To review important tools for the collection of clinical data. • Data collection form • Pretesting • Data entry • Data management • Study database
Objectives To review important tools for the collection of clinical data. • Data collection form • Pretesting • Data entry • Data management • Study database
Performing the Study Data Collection Form Data Collection Form (CRF) Inclusion Criteria Exclusion Criteria Predictor Variables Outcome Variables Confounding Variables
Performing the Study Data Collection Form Data Collection Form (CRF) Entries that involve judgment should be summarized briefly on the data collection form and explain with more detail on the study manual Inclusion Criteria Exclusion Criteria Predictor Variables Outcome Variables Confounding Variables
Performing the Study Data Collection Form Entries that involve judgment should be summarized briefly on the data collection form and explain with more detail on the study manual Criteria for diagnosis of CAP: New pulmonary infiltrate New or increased cough Fever or hypothermia Changes in WBC
Performing the Study Data Collection Form Entries that involve judgment should be summarized briefly on the data collection form and explain with more detail on the study manual Criteria for diagnosis of CAP: New pulmonary infiltrate (at time of hospitalization) New or increased cough Fever >37.8o C (100.0o F) or hypothermia <35.6o C (96.0o F) Changes in WBC (leukocytosis, left shift, or leukopenia)
Performing the Study Data Collection Form Data Collection Form (CRF) Entries that involve judgment should be summarized briefly on the data collection form and explain with more detail on the study manual Inclusion Criteria Exclusion Criteria Predictor Variables Outcome Variables Confounding Variables
Performing the Study Data Collection Form PREDICTOR VARIABLE
Performing the Study Data Collection Form EMPIRIC THERAPY PREDICTOR VARIABLE
Performing the Study Data Collection Form EMPIRIC THERAPY PREDICTOR VARIABLE Empiric antibiotic therapy for CAP ■ Patients admitted to ward
Performing the Study Data Collection Form EMPIRIC THERAPY PREDICTOR VARIABLE Empiric antibiotic therapy for CAP ■ Patients admitted to ward Beta-lactam plus macrolide Or Respiratory quinolone
Performing the Study Data Collection Form EMPIRIC THERAPY PREDICTOR VARIABLE Empiric antibiotic therapy for CAP ■ Patients admitted to ward Beta-lactam plus macrolide or Respiratory quinolone ■ Patients admitted to ICU
Performing the Study Data Collection Form EMPIRIC THERAPY PREDICTOR VARIABLE Empiric antibiotic therapy for CAP ■ Patients admitted to ward Beta-lactam plus macrolide or Respiratory quinolone ■ Patients admitted to ICU Beta-lactam plus macrolide Or Beta-lactam plus respiratory quinolone
Performing the Study Data Collection Form EMPIRIC THERAPY PREDICTOR VARIABLE
Performing the Study Data Collection Form
Performing the Study Data Collection Form Data Collection Form (CRF) Inclusion Criteria Exclusion Criteria Predictor Variables Outcome Variables Confounding Variables
Performing the Study Data Collection Form OUTCOME VARIABLE
Performing the Study Data Collection Form IN-HOSPITAL MORTALITY OUTCOME VARIABLE
Performing the Study Data Collection Form IN-HOSPITAL MORTALITY OUTCOME VARIABLE ■ Death of any cause during hospitalization
Performing the Study Data Collection Form Data Collection Form (CRF) Inclusion Criteria Exclusion Criteria Variable associated with the predictor variable and is a cause of the outcome variable Predictor Variables Outcome Variables Confounding Variables
Performing the Study Data Collection Form CONFOUNDING VARIABLE Variable associated with the predictor variable and is a cause of the outcome variable
Performing the Study Data Collection Form CONFOUNDING VARIABLE Variable associated with the predictor variable and is a cause of the outcome variable SEVERITY OF DISEASE
Performing the Study Data Collection Form CONFOUNDING VARIABLE Variable associated with the predictor variable and is a cause of the outcome variable SEVERITY OF DISEASE ■ Pneumonia severity index score ■ CURB-65 score ■ ICU admission
Performing the Study Data Collection Form CONFOUNDING VARIABLE Variable associated with the predictor variable and is a cause of the outcome variable COMORBIDITIES
Performing the Study Data Collection Form CONFOUNDING VARIABLE Variable associated with the predictor variable and is a cause of the outcome variable COMORBIDITIES ■ CHF (defined as systolic or diastolic ventricular dysfunction documented by history, physical examination, CXR, echocardiogram) ■ Diabetes (defined as a history of diabetes documented in the medical records that requires treatment with insulin or oral hypoglycemic drugs) ■ Respiratory (defined as a history of COPD documented in the medical records)
Objectives To review important tools for the collection of clinical data. • Data collection form • Pretesting • Data entry • Data management • Study database
Performing the Study Pretesting A problem-freeprotocol on paper usually has important problems in practice
Performing the Study Pretesting A problem-freeprotocol on paper usually has important problems in practice Pretesting can discover these problems before the initiation of the study
Performing the Study Pretesting A problem-freeprotocol on paper usually has important problems in practice Pretesting can discover these problems before the initiation of the study Small pilot studies that take only a few days or weeks are very useful to guide appropriate changes in the protocol before the study begins
Performing the Study Pretesting A pilot study to evaluate the methods for recruiting the study subjects
Performing the Study Pretesting A pilot study to evaluate the methods for recruiting the study subjects A pilot study to evaluate if the desired information has been systematically recorded in the medical record
Performing the Study Pretesting A pilot study to evaluate the methods for recruiting the study subjects A pilot study to evaluate if the desired information has been systematically recorded in the medical record A pilot study to develop the best approach to measuring predictor or outcome variables
Performing the Study Pretesting A pilot study to evaluate the methods for recruiting the study subjects A pilot study to evaluate if the desired information has been systematically recorded in the medical record A pilot study to develop the best approach to measuring predictor or outcome variables Pretesting helps the research team to finalize the study protocol and study manual
Objectives To review important tools for the collection of clinical data. • Data collection form • Pretesting • Data entry • Data management • Study database
Performing the Study Data Entry: CAPO Study Keyboard data entry using various interfaces in the computer screen An interface can be constructed to be identical to the paper case report form The operator clicks the box displayed in the computer screen and the entry is then automatically converted by the program to the correct code Data Entry CRF e-CRF
Performing the Study www.caposite.com
Performing the Study www.caposite.com
Performing the Study www.caposite.com
Performing the Study www.caposite.com
Performing the Study www.caposite.com
Performing the Study www.caposite.com
Performing the Study www.caposite.com
Objectives To review important tools for the collection of clinical data. • Data collection form • Pretesting • Data entry • Data management • Study database
Performing the Study Data Management 1. Define each variable 2. Set up study database and data dictionary 3. Data editing 4. Back up the dataset regularly 5. Create a dataset for analysis
Performing the Study Data Management 1. Define each variable 2. Set up study database and data dictionary 3. Data editing 4. Back up the dataset regularly 5. Create a dataset for analysis
Performing the Study Data Management To define the variables: 1. Use the CRF to identify and name each variable 2. Use short, understandable, and consistent names 3. Use abbreviations consistently 4. Use lower case (check software programs!)
Performing the Study Data Management To define the variables:
Performing the Study Data Management
Performing the Study Data Management