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Practice variation in the use of tests in UK primary care: a retrospective analysis of 16 million tests performed over 3.3 million patient years in 2015/16.

Practice variation in the use of tests in UK primary care: a retrospective analysis of 16 million tests performed over 3.3 million patient years in 2015/16.
Practice variation in the use of tests in UK primary care: a retrospective analysis of 16 million tests performed over 3.3 million patient years in 2015/16.
Background
The UK’s National Health Service (NHS) is currently subject to unprecedented financial strain. The identification of unnecessary healthcare resource use has been suggested to reduce spending. However, there is little very research quantifying wasteful test use, despite the £3 billion annual expenditure. Geographical variation has been suggested as one metric in which to quantify inappropriate use. We set out to identify tests ordered from UK primary care that are subject to the greatest between-practice variation in their use.

Methods
We used data from 444 general practices within the Clinical Practice Research
Datalink to calculate a co-efficient of variation (CoV) for the ordering of 44 specific tests from UK general practices. The co-efficient of variation was calculated after adjusting for differences between practice populations. We also determined the tests that had both a higher-than-average CoV and a higher-than-average rate of use.

Results
In total, 16,496,218 tests were ordered for 4,078,091 patients over 3,311,050 personyears from April 1st 2015 to March 31st 2016. The tests subject to the greatest variation was drug monitoring 158% (95%CI: 153% to 163%), Urine Microalbumin (52% (95%CI: 49.9% to 53.2%)), Pelvic CT (51% (95%CI: 50% to 53%)) and Pap smear (49% (95%CI: 48% to 51%). Seven tests were classified as high variability and high rate (Clotting, Vitamin D, Urine Albumin, Prostate Specific Antigen (PSA), Bone profile, Urine MCS and C-reactive Protein (CRP)).

Conclusions
There are wide variations in the use of common tests, which is unlikely to be explained by clinical indications. Since £3 billion annually are spent on tests this represents considerable variation in the use of resources and inefficient management in the NHS. Our results can be of value to policy makers, researchers, patients, and clinicians as the NHS strives towards identifying overuse and underuse of tests.
O'Sullivan, Jack
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Stevens, Sarah
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Hobbs, Richard
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Salisbury, Chris
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Little, Paul
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Goldacre, Ben
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Bankhead, Clare
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Aronson, Jeffrey
ac718303-1b50-4781-81c2-beedc3a6b24c
Heneghan, Carl
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Perera, Rafael
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O'Sullivan, Jack
0282aa71-2ef2-499c-baac-37c072d0fb21
Stevens, Sarah
f6c54ce5-8103-4454-a88e-209e70f6c163
Hobbs, Richard
405b31a3-606d-4cec-8e05-325f49df85cc
Salisbury, Chris
50e9a5a0-c074-4af8-9b1b-e1e8408aae3c
Little, Paul
1bf2d1f7-200c-47a5-ab16-fe5a8756a777
Goldacre, Ben
128d22c8-5626-4bb6-a6ec-ec108ab4cb2e
Bankhead, Clare
0afada46-df00-4b18-a78e-295667231d86
Aronson, Jeffrey
ac718303-1b50-4781-81c2-beedc3a6b24c
Heneghan, Carl
ab54c700-8c86-420a-98b9-45e071b1c842
Perera, Rafael
72025ce5-fb66-42f1-9a38-1694e485e754

O'Sullivan, Jack, Stevens, Sarah, Hobbs, Richard, Salisbury, Chris, Little, Paul, Goldacre, Ben, Bankhead, Clare, Aronson, Jeffrey, Heneghan, Carl and Perera, Rafael (2018) Practice variation in the use of tests in UK primary care: a retrospective analysis of 16 million tests performed over 3.3 million patient years in 2015/16. BMC Medicine, 16, [229]. (doi:10.1186/s12916-018-1217-1).

Record type: Article

Abstract

Background
The UK’s National Health Service (NHS) is currently subject to unprecedented financial strain. The identification of unnecessary healthcare resource use has been suggested to reduce spending. However, there is little very research quantifying wasteful test use, despite the £3 billion annual expenditure. Geographical variation has been suggested as one metric in which to quantify inappropriate use. We set out to identify tests ordered from UK primary care that are subject to the greatest between-practice variation in their use.

Methods
We used data from 444 general practices within the Clinical Practice Research
Datalink to calculate a co-efficient of variation (CoV) for the ordering of 44 specific tests from UK general practices. The co-efficient of variation was calculated after adjusting for differences between practice populations. We also determined the tests that had both a higher-than-average CoV and a higher-than-average rate of use.

Results
In total, 16,496,218 tests were ordered for 4,078,091 patients over 3,311,050 personyears from April 1st 2015 to March 31st 2016. The tests subject to the greatest variation was drug monitoring 158% (95%CI: 153% to 163%), Urine Microalbumin (52% (95%CI: 49.9% to 53.2%)), Pelvic CT (51% (95%CI: 50% to 53%)) and Pap smear (49% (95%CI: 48% to 51%). Seven tests were classified as high variability and high rate (Clotting, Vitamin D, Urine Albumin, Prostate Specific Antigen (PSA), Bone profile, Urine MCS and C-reactive Protein (CRP)).

Conclusions
There are wide variations in the use of common tests, which is unlikely to be explained by clinical indications. Since £3 billion annually are spent on tests this represents considerable variation in the use of resources and inefficient management in the NHS. Our results can be of value to policy makers, researchers, patients, and clinicians as the NHS strives towards identifying overuse and underuse of tests.

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BMC BMED-D-18-01116 accepted 12 Nov 2018 - Accepted Manuscript
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More information

Accepted/In Press date: 12 November 2018
e-pub ahead of print date: 20 December 2018

Identifiers

Local EPrints ID: 426430
URI: http://eprints.soton.ac.uk/id/eprint/426430
PURE UUID: a530a9aa-6299-4954-9ed6-2c96dd62f28a
ORCID for Paul Little: ORCID iD orcid.org/0000-0003-3664-1873

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Date deposited: 27 Nov 2018 17:30
Last modified: 12 Jul 2024 01:35

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Contributors

Author: Jack O'Sullivan
Author: Sarah Stevens
Author: Richard Hobbs
Author: Chris Salisbury
Author: Paul Little ORCID iD
Author: Ben Goldacre
Author: Clare Bankhead
Author: Jeffrey Aronson
Author: Carl Heneghan
Author: Rafael Perera

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