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 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

Data Collection Form (CRF) Confounding Variables 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

with more detail on the study manual Criteria for diagnosis of CAP: 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

with more detail on the study manual Criteria for diagnosis of CAP: 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) Mention the problem with the European group with the ABG Other countries where they use a period for commas and viceversa

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 EMPIRIC THERAPY

Empiric antibiotic therapy for CAP ■ Patients admitted to ward Performing the Study Data Collection Form PREDICTOR VARIABLE EMPIRIC THERAPY Empiric antibiotic therapy for CAP ■ Patients admitted to ward

Performing the Study Data Collection Form EMPIRIC THERAPY PREDICTOR VARIABLE EMPIRIC THERAPY 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 THERAPY 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 THERAPY 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 EMPIRIC THERAPY

Performing the Study Data Collection Form

Data Collection Form (CRF) Confounding Variables 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 OUTCOME VARIABLE MORTALITY

■ Death of any cause during hospitalization Performing the Study Data Collection Form OUTCOME VARIABLE IN-HOSPITAL MORTALITY ■ Death of any cause during hospitalization

Data Collection Form (CRF) Confounding Variables Performing the Study Data Collection Form Data Collection Form (CRF) Inclusion Criteria Exclusion Criteria Predictor Variables Variable associated with the predictor variable and is a cause of the outcome variable 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

■ Pneumonia severity index score 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-free protocol on paper usually has important problems in practice

Performing the Study Pretesting A problem-free protocol 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-free protocol 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!)

To define the variables: Performing the Study Data Management To define the variables:

Performing the Study Data Management

Performing the Study Data Management

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

To set up the study database: Performing the Study Data Management To set up the study database: Simple Databases Complex Databases Spreadsheet Program Interface Builder Excel Microsoft Access

Performing the Study Data Management To set up the data dictionary: 1. Do it before any data is collected! 2. Describe variable location (e.g. tables) 3. Describe variable name 4. Describe variable type and permitted ranges

Performing the Study Data Management

The data dictionary establishes the basis for editing Performing the Study Data Management The data dictionary establishes the basis for editing Detection of potential errors in the data should generate a written or electronic query including the name of the variable and the reason that it may be incorrect The response to a query may be to accept the variable value, to correct it, or to confirm that it is missing

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 identify and correct errors in the data Data editing includes checking to be sure that: 1. Variables are not missing 2. Variables are within the permitted range 3. Variables are logically consistent with other variables

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 create a dataset for analysis: Simple Databases Complex Databases Excel Microsoft Access Data Transfer to Statistical Analysis Software Statistical Analysis System (SAS) Statistical Package for the Social Sciences (SPSS)

Performing the Study Data Management

Performing the Study Data Management

Performing the Study Data Management

Objectives To review important tools for the collection of clinical data. Data collection form Pretesting Data entry Data management Study database

Performing the Study Database: CAPO Study Data Entry Data Editing CRF e-CRF e-CRF Final Database Database

Performing the Study Study Database

Objectives To review important tools for the collection of clinical data. Data collection form Pretesting Data entry Data management Study database