Table 2

Strengths and weaknesses of common data sources

StrengthsWeaknesses
Regulatory sponsored studies
 Arrives early after marketingPatient selection may not be representative
 Targeted data collection
Learned society academic studies
 Targeted data collectionPatient selection need not be representative
 Usually wide geographical representationQuality of outcome registration can vary
Nationwide or regional registries
 Large scaleData quality may be limited given use of clinical documentation
 Less bias in patient selectionInternational generalizability uncertain
 Low cost
Claims data
 Complete selection of data within an administrative unitMany clinically important data (both independent and outcome variables) may not be available
 Low costQuality of data may be limited
Investigator-initiated and industry-sponsored studies
 Multiple centresReimbursement for participation can influence patients who consent to intervention
 Careful monitoring of data collectedCentre selection can result in unrepresentative patients
 Targeted data collectionQuestions may be designed to ensure a higher probability of a favourable outcome
Hospital cohorts
 Uniform patient selectionPatient selection not representative
 Similar expertise to all patientsData quality may not be high
Expertise of selected centres may not be generalized
StrengthsWeaknesses
Regulatory sponsored studies
 Arrives early after marketingPatient selection may not be representative
 Targeted data collection
Learned society academic studies
 Targeted data collectionPatient selection need not be representative
 Usually wide geographical representationQuality of outcome registration can vary
Nationwide or regional registries
 Large scaleData quality may be limited given use of clinical documentation
 Less bias in patient selectionInternational generalizability uncertain
 Low cost
Claims data
 Complete selection of data within an administrative unitMany clinically important data (both independent and outcome variables) may not be available
 Low costQuality of data may be limited
Investigator-initiated and industry-sponsored studies
 Multiple centresReimbursement for participation can influence patients who consent to intervention
 Careful monitoring of data collectedCentre selection can result in unrepresentative patients
 Targeted data collectionQuestions may be designed to ensure a higher probability of a favourable outcome
Hospital cohorts
 Uniform patient selectionPatient selection not representative
 Similar expertise to all patientsData quality may not be high
Expertise of selected centres may not be generalized
Table 2

Strengths and weaknesses of common data sources

StrengthsWeaknesses
Regulatory sponsored studies
 Arrives early after marketingPatient selection may not be representative
 Targeted data collection
Learned society academic studies
 Targeted data collectionPatient selection need not be representative
 Usually wide geographical representationQuality of outcome registration can vary
Nationwide or regional registries
 Large scaleData quality may be limited given use of clinical documentation
 Less bias in patient selectionInternational generalizability uncertain
 Low cost
Claims data
 Complete selection of data within an administrative unitMany clinically important data (both independent and outcome variables) may not be available
 Low costQuality of data may be limited
Investigator-initiated and industry-sponsored studies
 Multiple centresReimbursement for participation can influence patients who consent to intervention
 Careful monitoring of data collectedCentre selection can result in unrepresentative patients
 Targeted data collectionQuestions may be designed to ensure a higher probability of a favourable outcome
Hospital cohorts
 Uniform patient selectionPatient selection not representative
 Similar expertise to all patientsData quality may not be high
Expertise of selected centres may not be generalized
StrengthsWeaknesses
Regulatory sponsored studies
 Arrives early after marketingPatient selection may not be representative
 Targeted data collection
Learned society academic studies
 Targeted data collectionPatient selection need not be representative
 Usually wide geographical representationQuality of outcome registration can vary
Nationwide or regional registries
 Large scaleData quality may be limited given use of clinical documentation
 Less bias in patient selectionInternational generalizability uncertain
 Low cost
Claims data
 Complete selection of data within an administrative unitMany clinically important data (both independent and outcome variables) may not be available
 Low costQuality of data may be limited
Investigator-initiated and industry-sponsored studies
 Multiple centresReimbursement for participation can influence patients who consent to intervention
 Careful monitoring of data collectedCentre selection can result in unrepresentative patients
 Targeted data collectionQuestions may be designed to ensure a higher probability of a favourable outcome
Hospital cohorts
 Uniform patient selectionPatient selection not representative
 Similar expertise to all patientsData quality may not be high
Expertise of selected centres may not be generalized
Close
This Feature Is Available To Subscribers Only

Sign In or Create an Account

Close

This PDF is available to Subscribers Only

View Article Abstract & Purchase Options

For full access to this pdf, sign in to an existing account, or purchase an annual subscription.

Close