Guidance for researchers wanting to link NHS data using non-consent approaches: a thematic analysis of feedback from the Health Research Authority Confidentiality Advisory Group

Lauren Cross; Lauren Carson; Amelia Jewell; Margaret Heslin; David Osborn; Johnny Downs; Robert Stewart

Guidance for researchers wanting to link NHS data using non-consent approaches: a thematic analysis of feedback from the Health Research Authority Confidentiality Advisory Group

Research output: Contribution to journal › Article › peer-review

Original language	English
Journal	The International Journal of Population Data Science
Publication status	Accepted/In press - 19 Aug 2020

Cite this

@article{b5cf7a7d5600471faa92d14635dc30ba,

title = "Guidance for researchers wanting to link NHS data using non-consent approaches: a thematic analysis of feedback from the Health Research Authority Confidentiality Advisory Group",

author = "Lauren Cross and Lauren Carson and Amelia Jewell and Margaret Heslin and David Osborn and Johnny Downs and Robert Stewart",

year = "2020",

month = aug,

day = "19",

language = "English",

journal = "The International Journal of Population Data Science ",

issn = "2399-4908",

publisher = "Swansea University",

}

Guidance for researchers wanting to link NHS data using non-consent approaches: a thematic analysis of feedback from the Health Research Authority Confidentiality Advisory Group. / Cross, Lauren ; Carson, Lauren; Jewell, Amelia et al.
In: The International Journal of Population Data Science , 19.08.2020.

Research output: Contribution to journal › Article › peer-review

TY - JOUR

T1 - Guidance for researchers wanting to link NHS data using non-consent approaches: a thematic analysis of feedback from the Health Research Authority Confidentiality Advisory Group

AU - Cross, Lauren

AU - Carson, Lauren

AU - Jewell, Amelia

AU - Heslin, Margaret

AU - Osborn, David

AU - Downs, Johnny

AU - Stewart, Robert

PY - 2020/8/19

Y1 - 2020/8/19

M3 - Article

SN - 2399-4908

JO - The International Journal of Population Data Science

JF - The International Journal of Population Data Science

ER -