LOGIN TO YOUR ACCOUNT

Username
Password
Remember Me
Or use your Academic/Social account:

CREATE AN ACCOUNT

Or use your Academic/Social account:

Congratulations!

You have just completed your registration at OpenAire.

Before you can login to the site, you will need to activate your account. An e-mail will be sent to you with the proper instructions.

Important!

Please note that this site is currently undergoing Beta testing.
Any new content you create is not guaranteed to be present to the final version of the site upon release.

Thank you for your patience,
OpenAire Dev Team.

Close This Message

CREATE AN ACCOUNT

Name:
Username:
Password:
Verify Password:
E-mail:
Verify E-mail:
*All Fields Are Required.
Please Verify You Are Human:
fbtwitterlinkedinvimeoflicker grey 14rssslideshare1
Lord, P; Willis, T; Carder, P; West, R; Foy, RC (2016)
Publisher: Oxford University Press
Languages: English
Types: Article
Subjects:
Background: Recruitment of representative samples in primary care research is essential to ensure high-quality, generalisable results. This is particularly important for research using routinely recorded patient data to examine the delivery of care. Yet little is known about how different recruitment strategies influence the characteristics of the practices included in research. We describe three approaches for recruiting practices to data sharing studies, examining differences in recruitment levels and practice representativeness. Method: We examined three studies that included varying populations of practices from West Yorkshire, UK. All used anonymised patient data to explore aspects of clinical practice. Recruitment strategies were ‘opt-in’, ‘mixed opt-in and opt-out’, and ‘opt-out’. We compared aggregated practice data between recruited and not-recruited practices for practice list size, deprivation, chronic disease management, patient experience and rates of unplanned hospital admission. Results: The opt-out strategy had the highest recruitment (80%), followed by mixed (70%), and opt-in (58%). Practices opting-in were larger (median 7153 vs. 4722 patients, p=0.03) than practices that declined to opt-in. Practices recruited by mixed approach were larger (median 7091 vs. 5857 patients, p=0.04) and had differences in the clinical quality measure (58.4% vs 53.9% of diabetic patients with HbA1c <=59mmol/mol, p<0.01). We found no differences between practices recruited and not-recruited using the opt-out strategy for any demographic or quality-of-care measures. Conclusion: Opt-out recruitment appears to be a relatively efficient approach to ensuring participation of typical general practices. Researchers should, with appropriate ethical safeguards, consider opt-out recruitment of practices for studies involving anonymised patient data sharing.
  • No references.
  • No related research data.
  • No similar publications.

Share - Bookmark

Cite this article