Use this URL to cite or link to this record in EThOS:
Title: Biostatistical and meta-research approaches to assess diagnostic test use
Author: O'Sullivan, Jack William
ISNI:       0000 0004 7430 6125
Awarding Body: University of Oxford
Current Institution: University of Oxford
Date of Award: 2018
Availability of Full Text:
Access from EThOS:
Full text unavailable from EThOS. Please try the link below.
Access from Institution:
The aim of this thesis was to assess test use from primary care. Test use is an essential part of general practice, yet there is surprisingly little data exploring and quantifying its activity. My overarching hypothesis was that test use from primary care is sub-optimal, specifically that tests are overused (overtesting) - ordered when they will lead to no patient benefit, and underused (undertesting) - not ordered when they would lead to patient benefit. Previous metrics used to identify potential over and undertesting have been categorised into direct and indirect measures. Indirect measures take a population-level approach and are 'unexpected variation' in healthcare resource use, such as geographical variation. Direct measures consider individual patient data and directly compare resource use with an appropriateness criterion (such as a guideline). In this thesis, I examined three indirect measures: temporal change in test use, between-practice variation in test use and variation between general practices in the proportion of test results that return an abnormal result. In chapter 3, I identified which tests have been subject to the greatest change in their use from 2000/1 to 2015/16 in UK primary care. In chapter 4, I identified the tests that had been subject to the greatest between-practice variation in their use in UK primary care. In chapter 5, I present a method to identify General Practices whose doctors order a lower proportion of tests that return a normal result. In chapter 6, I present a method to directly quantify over and undertesting; I conducted a systematic review of studies that measured the adherence of general practitioner's test use with guidelines. In chapter 7 I acknowledge that the use of guidelines to audit general practitioner's test use is flawed; guidelines are of varying quality and not designed to dictate clinical practice. In this chapter, I determine the quality and reporting of guidelines, the quality of the evidence underpinning their recommendations and explore the association between guideline quality and non-adherence. Overall, I have shown that most tests have increased substantially in use (MRI knee, vitamin D and MRI brain the most), there is marked between-practice variation in the use of many tests (drug monitoring, urine albumin and pelvic CT the most) and that some general practices order a significantly lower proportion of tests that return an abnormal result. I have also shown that there is marked variation in how often GPs follow guidelines, but guidelines based on highly quality evidence are adhered to significantly more frequently. Lastly, in my Discussion chapter, I discuss the implications of my thesis, how it fits into the wider literature and an idea for a proposed step-wise approach to systematically identify overtesting.
Supervisor: Aronson, Jeffrey ; Perera, Rafael ; Heneghan, Carl Sponsor: Clarendon Scholarship
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: Primary Health Care ; Overdiagnosis ; Big data ; Meta-research ; Overtesting ; Epidemiology