early health technology assessment of point-of-care and laboratory diagnostics - methods and applications in acute and primary care
Michelle Kip is a PhD Student in the research group Health Technology and Services Research (HTSR). Her supervisors are Professor Ron Kusters and Professor Maarten IJzerman from the Faculty of Behavioural Management and Social Sciences.
The demand for healthcare has strongly increased in the last decades, due to the aging population, the increase in the number of people with chronic diseases, the rise of personalized medicine, and technological advances. Although this was accompanied by a strong increase in the number of available diagnostic tests, only a limited number of these tests are actually implemented and used in clinical practice. However, this rising number of diagnostic tests available raises concerns about potential overuse of tests that are already implemented in clinical practice, the accompanying (potential) negative health impact of diagnostic testing, for example caused by (unnecessary) distress about test results, as well as rising healthcare costs. Therefore, evaluating the expected health economic impact of new diagnostic tests or diagnostic strategies is highly important to enhance efficient test implementation and use, and to ensure the provision of affordable and good quality healthcare.
The aim of this thesis was therefore to investigate the health economic impact of (new) diagnostic tests or diagnostic testing strategies within three disease areas (i.e. acute coronary syndrome, sepsis and anaemia). In addition, this thesis investigated which aspects affect the implementation and use of (new) diagnostic tests (with a focus on laboratory biomarkers), and to provide recommendations and guidance on investigating the health economic impact of such diagnostic tests.
Investigating the potential added value and health economic impact of new healthcare technologies compared with the standard-of-care concerns Health Technology Assessment (HTA) and it can be used to support decisions regarding test implementation and use. However, owing to the rapid development of new diagnostic tests, assessment of these new tests should preferably be performed in early test development stages, which is referred to as ‘early HTA’. More specifically, although regular HTA is mainly used to assess the safety, effectiveness and cost-effectiveness of a technology, early HTA considers aspects that are relevant to inform the test’s development process, including implementation barriers, the predicted uptake of a new test, requirements of a new medical test, as well as patient needs.
With regard to the three main disease areas, focuses the first part of this thesis (chapters 2, 3 and 4) on early HTA of point-of-care (POC) tests to rule out acute coronary syndrome (ACS) in primary care:
Chapter 2 concerns an early HTA of a future clinical decision rule (CDR) incorporating a POC test, for diagnosing ACS in primary care as compared to current practice. The annual incidence and referral rates of chest pain patients, as well as the incidence of ACS, were estimated based on a literature review and on a Dutch and Belgian registration study. The potential impact of a future CDR on costs and effects (i.e., correct referral decisions) was estimated for several scenarios. Results indicate that a reduction of at least 29% of unnecessary referrals (i.e. referrals of patients without ACS) is required to make the addition of a POC test as predictor in a CDR cost-saving.
Chapter 3 describes the results of a survey distributed among general practitioners (GPs), investigating the perceived added value with regard to a POC troponin test, as well as its effect on referral decisions and test requirements. A total of 126 GPs (15.1%) completed at least 75% of the questions. The results indicated that 67.1% of GPs believed that a POC troponin test has moderate to high added value, and that this test may decrease (immediate) hospital referral rates. Although GPs consider the test of potential added value to exclude ACS early on, actual test implementation will depend on test characteristics, including test duration, type of blood sample required, and reimbursement of the analyzer.
Chapter 4 estimates the expected cost-effectiveness of using a POC troponin test to rule out ACS in a hypothetical cohort of Dutch chest pain patients (>35 years) consulting a GP, using a patient-level health economic model. The model incorporated both symptom duration, selection of patients in whom the POC test would be performed, as well as test performance at different time points. The POC troponin strategy was found to decrease the referral rate among non-ACS patients from 38.46% to 31.85%. Despite a small increase in non-referral among ACS patients (i.e. from 0.22% to 0.27%), the overall health effect is negligible, while substantial cost savings (i.e. €77 per patient) can be achieved. Besides, current developments in POC troponin tests will likely further improve their diagnostic performance. Therefore, future prospective (randomized) studies into the safety and diagnostic accuracy of POC troponin are warranted to investigate whether those developments make these tests to a safe and cost-effective diagnostic tool for diagnosing ACS in primary care.
The second part of this thesis (chapters 5, 6, and 7) concerns the cost-effectiveness of a procalcitonin (PCT)-guided algorithm for antibiotic discontinuation in intensive care patients with sepsis:
Chapter 5 illustrates the cost-effectiveness of such a PCT-guided antibiotic treatment algorithm in intensive care patients with sepsis. The results of a systematic literature review regarding the effectiveness of such an algorithm served as input for a health economic model. Results indicate that use of a PCT algorithm is expected to reduce the duration of antibiotic prescription with 1.7 days, as well as decrease the duration of hospital stay with 3.4 days and a decrease in direct hospital costs with -€3,503 per patient. However, as both the duration of hospital stay and antibiotic treatment are relatively short in the Netherlands compared to other countries, this model should ideally be populated with country-specific data to make valid per country estimations.
Chapter 6 shows the response to a published randomized controlled trial (RCT), regarding the use of a PCT-guided treatment algorithm in intensive care patients with sepsis in the Netherlands. When using the results of this RCT to calculate the costs of this algorithm, results indicate that it could not be conclusively demonstrated that the use of a PCT algorithm is cost saving. As the duration of intensive care stay was found to have the largest impact on the overall costs, future studies should aim to estimate the impact of such a PCT algorithm on the duration of intensive care stay.
Chapter 7 concerns a trial-based cost-effectiveness analysis in which the resource use data from this recently published RCT (as described in chapter 6) were used as input parameters. The results indicate that the impact of this PCT algorithm on costs is minimal (i.e. €-65), although both the duration of antibiotic use and in-hospital mortality are lower compared with standard-of-care (i.e. -1.2 days and -7.9%, respectively). When applying a one-year time horizon, the high healthcare-related costs occurring in sepsis survivors are however expected to lead to a (non-significant) increase in costs of the PCT group compared to standard-of-care (i.e. +€2,770). This results in an incremental cost-effectiveness ratio (ICER) of ~60,000/quality-adjusted life year (QALY) gained, which cannot be cannot be considered cost-effective when applying a WTP threshold of €20,000/QALY. Long-term follow-up studies are however required to fully quantify the costs and health impact of such a PCT algorithm from the societal perspective.
The third part of this thesis (chapters 8 and 9) concerns an evaluation of the costs and effects of using an extensive laboratory analysis for diagnosis and treatment of anaemia in primary care:
Chapter 8 describes a study on the effectiveness of two different laboratory work-ups to detect the underlying cause of anaemia by GPs. In this study, effectiveness is defined as the percentage of anaemia patients in whom the correct underlying cause is diagnosed by the GP, when using an extensive versus a routine laboratory work-up. To investigate this, an online survey was distributed among 836 GPs. This survey consisted of six cases from an existing cohort of anaemia patients. In the first three cases, GPs could choose themselves which tests to perform (from a previously defined set of 14 relevant laboratory tests), i.e. the routine work-up. In the second three cases, the results of all 14 tests, i.e. the extensive work-up, were directly presented to the GPs. Results indicate that, compared to an expert panel, the use of this extensive work-up, improves GPs’ ability to diagnose patients with the correct underlying cause of anaemia.
Subsequently, chapter 9 describes the impact of both laboratory work-ups, in terms of the number of correctly diagnosed underlying causes, associated treatment decisions and accompanying costs. Besides a 6.4% improvement in the number of patients in whom the correct underlying cause of anaemia is diagnosed, costs are expected to increase slightly from €842 per patient in the routine work-up to €845 per patient in the extensive work-up. However, as the additional costs of the extensive work-up are found to be minimal, while the chance of early diagnosis of the correct underlying cause increased, use of the extensive laboratory work-up was recommended.
The final part of this thesis (chapters 10, 11 and 12) discusses methodological issues related to performing an (early) HTA of a diagnostic test or testing strategy:
Chapter 10 illustrates how expert elicitation can be used to provide estimations for model input parameters in situations where scientific evidence is lacking. This is illustrated using a case study on the cost-effectiveness of the combined use of heart-type fatty acid binding protein (H-FABP), high-sensitive troponin, and copeptin, as compared to conventional serial high-sensitive troponin testing, to rapidly rule out non-ST elevation myocardial infarction in patients presenting with chest pain in the emergency department. The results indicate that the use of this triple biomarker in combination with high-sensitive troponin measurement after two and six hours, is expected to be the most cost-effective strategy compared to current practice. Furthermore, this case study showed that expert elicitation can be a valuable tool for early HTA to provide an initial estimate of the cost-effectiveness of new tests prior to their further development and (finally) their implementation in clinical practice.
Chapter 11 served to get insight in which features affect the implementation and use of diagnostic tests in clinical practice. This was illustrated using a case study on two POC tests in primary care (i.e. the POC glycated haemoglobin [HbA1c] test), and the POC C-reactive protein [CRP] test). After a literature review and validation by 12 experts, a list of 20 criteria was obtained. Results of an analytical hierarchy process (AHP) session with 10 of these experts revealed that the test’s clinical relevance, its technical performance, and risks (associated with making a treatment or management decision based on the test result) were considered most important with relative weights of 22.2%, 12.6% and 8.5%, respectively. The POC CRP test was preferred over its central laboratory equivalent, whereas the POC HbA1c test was not. The insights obtained from this study may both steer test development and improve the implementation use of existing POC tests in general practices.
Chapter 12 describes the development of a comprehensive reporting checklist, which is intended to increase awareness of all aspects potentially relevant in investigating the impact of diagnostic tests and biomarkers in a model-based health economic evaluation. This checklist was designed based on a scoping review which was critically assessed by four independent experts who judged the clarity, redundancy and completeness of the checklist. This resulted in a list of 43 aspects that ideally should be considered for explicit inclusion in, or exclusion from a health economic evaluation. Thereby, this reporting checklist may contribute to improving the completeness and transparency of such model-based health economic evaluations.
The results of this thesis have indicated that it is highly important to evaluate the expected impact of a diagnostic test (or combination of tests) on health outcomes and costs, prior to their implementation in clinical practice. In this regard, HTA, and especially early HTA, represent a highly valuable set of techniques to evaluate this impact. Besides health economic models, other techniques that are part of early HTA, for example multi-criteria decision analysis, are valuable to obtain insight in factors that hamper or facilitate the implementation and use of new diagnostic tests. In order to fully quantify the value of diagnostic testing, wider elements of value besides the impact on costs and patients’ health should be considered. Such wider elements of value for example include being reassured of not having a serious illness, or the knowledge of having a genetic disorder, which may affect family planning. Besides a test’s cost-effectiveness, these broader elements of value will likely also affect its implementation and use.