The societal impact of implementing an at-home blood sampling device for chronic care patients: patient preferences and cost impact.

BACKGROUND: Diabetes mellitus, cardiovascular diseases, chronic kidney disease, and thyroid diseases are chronic diseases that require regular monitoring through blood tests. This paper first investigates the experiences of chronic care patients with venipuncture and their expectations of an at-home blood-sampling device, and then assesses the impact on societal costs of implementing such a device in current practice. METHODS: An online survey was distributed among chronic care patients to gain insight into their experience of blood sampling in current practice, and their expectations of an at-home blood-sampling device. The survey results were used as input parameters in a patient-level monte carlo analysis developed to represent a hypothetical cohort of Dutch chronically ill patients to investigate the impact on societal costs compared to usual care. RESULTS: In total, 1311 patients participated in the survey, of which 31% experience the time spent on the phlebotomy appointment as a burden. Of all respondents, 71% prefer to use an at-home blood-sampling device to monitor their chronic disease. The cost analysis indicated that implementing an at-home blood-sampling device increases the cost of phlebotomy itself by €27.25 per patient per year, but it reduces the overall societal costs by €24.86 per patient per year, mainly due to limiting productivity loss. CONCLUSIONS: Patients consider an at-home blood-sampling device to be more user-friendly than venous phlebotomy on location. Long waiting times and crowded locations can be avoided by using an at-home blood-sampling device. Implementing such a device is likely cost-saving as it is expected to reduce societal costs.

Health Economic Evidence of Point-of-Care Testing: A Systematic Review.

OBJECTIVE: Point-of-care testing (POCT) has become an essential diagnostic technology for optimal patient care. Its implementation, however, still falls behind. This paper reviews the available evidence on the health economic impact of introducing POCT to assess if poor POCT uptake may be related to lacking evidence. STUDY DESIGN: The Scopus and PubMed databases were searched to identify publications describing a health economic evaluation of a point-of-care (POC) test. Data were extracted from the included publications, including general and methodological characteristics as well as the study results summarized in either cost, effects or an incremental cost-effectiveness ratio. Results were sorted into six groups according to the POC test's purpose (diagnosis, screening or monitoring) and care setting (primary care or secondary care). The reporting quality of the publications was determined using the CHEERS checklist. RESULTS: The initial search resulted in 396 publications, of which 44 met the inclusion criteria. Most of the evaluations were performed in a primary care setting (n = 31; 70.5%) compared with a secondary care setting (n = 13; 29.5%). About two thirds of the evaluations were on POC tests implemented with a diagnostic purpose (n = 28; 63.6%). More than 75% of evaluations concluded that POCT is recommended for implementation, although in some cases only under specific circumstances and conditions. Compliance with the CHEERS checklist items ranged from 20.8% to 100%, with an average reporting quality of 72.0%. CONCLUSION: There were very few evaluations in this review that advised against the implementation of POCT. However, the uptake of POCT in many countries remains low. Even though the evaluations included in this review did not always include the full long-term benefits of POCT, it is clear that health economic evidence across a few dimensions of value already indicate the benefits of POCT. This suggests that the lack of evidence on POCT is not the primary barrier to its implementation and that the low uptake of these tests in clinical practice is due to (a combination of) other barriers. In this context, aspects around organization of care, support of clinicians and quality management may be crucial in the widespread implementation of POCT.

Understanding the adoption and use of point-of-care tests in Dutch general practices using multi-criteria decision analysis.

BACKGROUND: The increasing number of available point-of-care (POC) tests challenges clinicians regarding decisions on which tests to use, how to efficiently use them, and how to interpret the results. Although POC tests may offer benefits in terms of low turn-around-time, improved patient's satisfaction, and health outcomes, only few are actually used in clinical practice. Therefore, this study aims to identify which criteria are, in general, important in the decision to implement a POC test, and to determine their weight. Two POC tests available for use in Dutch general practices (i.e. the C-reactive protein (CRP) test and the glycated haemoglobin (HbA1c) test) serve as case studies. The information obtained from this study can be used to guide POC test development and their introduction in clinical practice. METHODS: Relevant criteria were identified based on a literature review and semi-structured interviews with twelve experts in the field. Subsequently, the criteria were clustered in four groups (i.e. user, organization, clinical value, and socio-political context) and the relative importance of each criterion was determined by calculating geometric means as implemented in the Analytic Hierarchy Process. Of these twelve experts, ten participated in a facilitated group session, in which their priorities regarding both POC tests (compared to central laboratory testing) were elicited. RESULTS: Of 20 criteria in four clusters, the test's clinical utility, its technical performance, and risks (associated with the treatment decision based on the test result) were considered most important for using a POC test, with relative weights of 22.2, 12.6 and 8.5%, respectively. Overall, the experts preferred the POC CRP test over its laboratory equivalent, whereas they did not prefer the POC HbA1c test. This difference was mainly explained by their strong preference for the POC CRP test with regard to the subcriterion 'clinical utility'. CONCLUSIONS: The list of identified criteria, and the insights in their relative impact on successful implementation of POC tests, may facilitate implementation and use of existing POC tests in clinical practice. In addition, having experts score new POC tests on these criteria, provides developers with specific recommendations on how to increase the probability of successful implementation and use.

Cost-effectiveness of procalcitonin testing to guide antibiotic treatment duration in critically ill patients: results from a randomised controlled multicentre trial in the Netherlands.

BACKGROUND: Procalcitonin (PCT) testing can help in safely reducing antibiotic treatment duration in intensive care patients with sepsis. However, the cost-effectiveness of such PCT guidance is not yet known. METHODS: A trial-based analysis was performed to estimate the cost-effectiveness of PCT guidance compared with standard of care (without PCT guidance). Patient-level data were used from the SAPS trial in which 1546 patients were randomised. This trial was performed in the Netherlands, which is a country with, on average, low antibiotic use and a short duration of hospital stay. As quality of life among sepsis survivors was not measured during the SAPS, this was derived from a Dutch follow-up study. Outcome measures were (1) incremental direct hospital cost and (2) incremental cost per quality-adjusted life year (QALY) gained from a healthcare perspective over a one-year time horizon. Uncertainty in outcomes was assessed with bootstrapping. RESULTS: Mean in-hospital costs were €46,081/patient in the PCT group compared with €46,146/patient with standard of care (i.e. - €65 (95% CI - €6314 to €6107); - 0.1%). The duration of the first course of antibiotic treatment was lower in the PCT group with 6.9 vs. 8.2 days (i.e. - 1.2 days (95% CI - 1.9 to - 0.4), - 14.8%). This was accompanied by lower in-hospital mortality of 21.8% vs. 29.8% (absolute decrease 7.9% (95% CI - 13.9% to - 1.8%), relative decrease 26.6%), resulting in an increase in mean QALYs/patient from 0.47 to 0.52 (i.e. + 0.05 (95% CI 0.00 to 0.10); + 10.1%). However, owing to high costs among sepsis survivors, healthcare costs over a one-year time horizon were €73,665/patient in the PCT group compared with €70,961/patient with standard of care (i.e. + €2704 (95% CI - €4495 to €10,005), + 3.8%), resulting in an incremental cost-effectiveness ratio of €57,402/QALY gained. Within this time frame, the probability of PCT guidance being cost-effective was 64% at a willingness-to-pay threshold of €80,000/QALY. CONCLUSIONS: Although the impact of PCT guidance on total healthcare-related costs during the initial hospitalisation episode is likely negligible, the lower in-hospital mortality may lead to a non-significant increase in costs over a one-year time horizon. However, since uncertainty remains, it is recommended to investigate the long-term cost-effectiveness of PCT guidance, from a societal perspective, in different countries and settings.

Toward Alignment in the Reporting of Economic Evaluations of Diagnostic Tests and Biomarkers: The AGREEDT Checklist.

OBJECTIVES: General frameworks for conducting and reporting health economic evaluations are available but not specific enough to cover the intricacies of the evaluation of diagnostic tests and biomarkers. Such evaluations are typically complex and model-based because tests primarily affect health outcomes indirectly and real-world data on health outcomes are often lacking. Moreover, not all aspects relevant to the evaluation of a diagnostic test may be known and explicitly considered for inclusion in the evaluation, leading to a loss of transparency and replicability. To address this challenge, this study aims to develop a comprehensive reporting checklist. METHODS: This study consisted of 3 main steps: 1) the development of an initial checklist based on a scoping review, 2) review and critical appraisal of the initial checklist by 4 independent experts, and 3) development of a final checklist. Each item from the checklist is illustrated using an example from previous research. RESULTS: The scoping review followed by critical review by the 4 experts resulted in a checklist containing 44 items, which ideally should be considered for inclusion in a model-based health economic evaluation. The extent to which these items were included or discussed in the studies identified in the scoping review varied substantially, with 14 items not being mentioned in ≥47 (75%) of the included studies. CONCLUSIONS: The reporting checklist developed in this study may contribute to improved transparency and completeness of model-based health economic evaluations of diagnostic tests and biomarkers. Use of this checklist is therefore encouraged to enhance the interpretation, comparability, and-indirectly-the validity of the results of such evaluations.

Assessing the cost-effectiveness of a routine versus an extensive laboratory work-up in the diagnosis of anaemia in Dutch general practice.

Background Establishing the underlying cause of anaemia in general practice is a diagnostic challenge. Currently, general practitioners individually determine which laboratory tests to request (routine work-up) in order to diagnose the underlying cause. However, an extensive work-up (consisting of 14 tests) increases the proportion of patients correctly diagnosed. This study investigates the cost-effectiveness of this extensive work-up. Methods A decision-analytic model was developed, incorporating all societal costs from the moment a patient presents to a general practitioner with symptoms suggestive of anaemia (aged ≥ 50 years), until the patient was (correctly) diagnosed and treated in primary care, or referred to (and diagnosed in) secondary care. Model inputs were derived from an online survey among general practitioners, expert estimates and published data. The primary outcome measure was expressed as incremental cost per additional patient diagnosed with the correct underlying cause of anaemia in either work-up. Results The probability of general practitioners diagnosing the correct underlying cause increased from 49.6% (95% CI: 44.8% to 54.5%) in the routine work-up to 56.0% (95% CI: 51.2% to 60.8%) in the extensive work-up (i.e. +6.4% [95% CI: -0.6% to 13.1%]). Costs are expected to increase slightly from €842/patient (95% CI: €704 to €994) to €845/patient (95% CI: €711 to €994), i.e. +€3/patient (95% CI: €-35 to €40) in the extensive work-up, indicating incremental costs of €43 per additional patient correctly diagnosed. Conclusions The extensive laboratory work-up is more effective for diagnosing the underlying cause of anaemia by general practitioners, at a minimal increase in costs. As accompanying benefits in terms of quality of life and reduced productivity losses could not be captured in this analysis, the extensive work-up is likely cost-effective.

The effectiveness of a routine versus an extensive laboratory analysis in the diagnosis of anaemia in general practice.

Background We investigated the percentage of patients diagnosed with the correct underlying cause of anaemia by general practitioners when using an extensive versus a routine laboratory work-up. Methods An online survey was distributed among 836 general practitioners. The survey consisted of six cases, selected from an existing cohort of anaemia patients ( n = 3325). In three cases, general practitioners were asked to select the laboratory tests for further diagnostic examination from a list of 14 parameters (i.e. routine work-up). In the other three cases, general practitioners were presented with all 14 laboratory test results available (i.e. extensive work-up). General practitioners were asked to determine the underlying cause of anaemia in all six cases based on the test results, and these answers were compared with the answers of an expert panel. Results A total of 139 general practitioners (partly) responded to the survey (17%). The general practitioners were able to determine the underlying cause of anaemia in 53% of cases based on the routine work-up, whereas 62% of cases could be diagnosed using an extensive work-up ( P = 0.007). In addition, the probability of a correct diagnosis decreased with the patient's age and was also affected by the underlying cause itself, with anaemia of chronic disease being hardest to diagnose ( P = 0.003). Conclusion The use of an extensive laboratory work-up in patients with newly diagnosed anaemia is expected to increase the percentage of correct underlying causes established by general practitioners. Since the underlying cause can still not be established in 31.3% of anaemia patients, further research is necessary.

Early health technology assessment of future clinical decision rule aided triage of patients presenting with acute chest pain in primary care.

The objective of the paper is to estimate the number of patients presenting with chest pain suspected of acute coronary syndrome (ACS) in primary care and to calculate possible cost effects of a future clinical decision rule (CDR) incorporating a point-of-care test (PoCT) as compared with current practice. The annual incidence of chest pain, referrals and ACS in primary care was estimated based on a literature review and on a Dutch and Belgian registration study. A health economic model was developed to calculate the potential impact of a future CDR on costs and effects (ie, correct referral decisions), in several scenarios with varying correct referral decisions. One-way, two-way, and probabilistic sensitivity analyses were performed to test robustness of the model outcome to changes in input parameters. Annually, over one million patient contacts in primary care in the Netherlands concern chest pain. Currently, referral of eventual ACS negative patients (false positives, FPs) is estimated to cost €1,448 per FP patient, with total annual cost exceeding 165 million Euros in the Netherlands. Based on 'international data', at least a 29% reduction in FPs is required for the addition of a PoCT as part of a CDR to become cost-saving, and an additional €16 per chest pain patient (ie, 16.4 million Euros annually in the Netherlands) is saved for every further 10% relative decrease in FPs. Sensitivity analyses revealed that the model outcome was robust to changes in model inputs, with costs outcomes mainly driven by costs of FPs and costs of PoCT. If PoCT-aided triage of patients with chest pain in primary care could improve exclusion of ACS, this CDR could lead to a considerable reduction in annual healthcare costs as compared with current practice.

Using expert elicitation to estimate the potential impact of improved diagnostic performance of laboratory tests: a case study on rapid discharge of suspected non-ST elevation myocardial infarction patients.

Early health technology assessment can provide insight in the potential cost-effectiveness of new tests to guide further development decisions. This can increase their potential benefit but often requires evidence which is lacking in early test development stages. Then, expert elicitation may be used to generate evidence on the impact of tests on patient management. This is illustrated in a case study on a new triple biomarker test (copeptin, heart-type fatty acid binding protein, and high-sensitivity troponin [HsTn]) at hospital admission. The elicited evidence enables estimation of the impact of using the triple biomarker on time to exclusion of non-ST elevation myocardial infarction compared with current serial HsTn measurement (performed 0, 2, and 6 h after admission). Cardiologists were asked to estimate the effect of the triple biomarker on patient's discharge rates and interventions performed, depending on its diagnostic performance. This elicited evidence was combined with Dutch reimbursement data and published evidence into a decision analytic model. Direct hospital costs and patients' discharge rates were assessed for 3 testing strategies including this triple biomarker (ie, only at admission or combined with HsTn measurements after 2 and 6 h). Direct hospital costs of suspected non-ST elevation myocardial infarction patients using serial HsTn measurements are estimated at €1825 per patient. Combining this triple biomarker with HsTn measurements after 2 and 6 hours is expected to be the most cost-effective strategy. Depending on the diagnostic performance of the triple biomarker, this strategy is estimated to reduce costs with €66 to €205 per patient (ie, 3.6%-11.3% reduction). Expert elicitation can be a valuable tool for early health technology assessment to provide an initial estimate of the cost-effectiveness of new tests prior to their implementation in clinical practice. As demonstrated in our case study, improved diagnostic performance of the triple biomarker may have benefits that should be further explored.

The cost-utility of point-of-care troponin testing to diagnose acute coronary syndrome in primary care.

BACKGROUND: The added value of using a point-of-care (POC) troponin test in primary care to rule out acute coronary syndrome (ACS) is debated because test sensitivity is inadequate early after symptom onset. This study investigates the potential cost-utility of diagnosing ACS by a general practitioner (GP) when a POC troponin test is available versus GP assessment only. METHODS: A patient-level simulation model was developed, representing a hypothetical cohort of the Dutch population (>35 years) consulting the GP with chest complaints. All health related consequences as well as cost consequences were included. Both symptom duration, selection of patients in whom the POC troponin test is performed, and test performance at different time points were incorporated. Health outcomes were expressed as Quality-Adjusted Life Years (QALYs). The main outcome parameters involve the effect of POC troponin testing on (in)correct hospital referrals, QALYs, and costs. RESULTS: The POC troponin strategy decreases the referral rate in non-ACS patients from 38.46% to 31.85%. Despite a small increase in non-referral among ACS patients from 0.22% to 0.27%, the overall health effect is negligible. Costs will decrease with €77.25/patient (95% CI €-126.81 to €-33.37). CONCLUSIONS: The POC troponin strategy is likely cost-saving, by reducing hospital referrals. The small increase in missed ACS patients can be partly explained by conservative assumptions used in the analysis. Besides, current developments in POC troponin tests will likely further improve their diagnostic performance. Therefore, future prospective studies are warranted to investigate whether those developments make the POC troponin test to a safe and cost-effective diagnostic tool for diagnosing ACS in general practices.

A PCT algorithm for discontinuation of antibiotic therapy is a cost-effective way to reduce antibiotic exposure in adult intensive care patients with sepsis.

OBJECTIVE: Procalcitonin (PCT) is a specific marker for differentiating bacterial from non-infective causes of inflammation. It can be used to guide initiation and duration of antibiotic therapy in intensive care unit (ICU) patients with suspected sepsis, and might reduce the duration of hospital stay. Limiting antibiotic treatment duration is highly important because antibiotic over-use may cause patient harm, prolonged hospital stay, and resistance development. Several systematic reviews show that a PCT algorithm for antibiotic discontinuation is safe, but upfront investment required for PCT remains an important barrier against implementation. The current study investigates to what extent this PCT algorithm is a cost-effective use of scarce healthcare resources in ICU patients with sepsis compared to current practice. METHODS: A decision tree was developed to estimate the health economic consequences of the PCT algorithm for antibiotic discontinuation from a Dutch hospital perspective. Input data were obtained from a systematic literature review. When necessary, additional information was gathered from open interviews with clinical chemists and intensivists. The primary effectiveness measure is defined as the number of antibiotic days, and cost-effectiveness is expressed as incremental costs per antibiotic day avoided. RESULTS: The PCT algorithm for antibiotic discontinuation is expected to reduce hospital spending by circa € 3503 per patient, indicating savings of 9.2%. Savings are mainly due to reductions in length of hospital stay, number of blood cultures performed, and, importantly, days on antibiotic therapy. Probabilistic and one-way sensitivity analyses showed the model outcome to be robust against changes in model inputs. CONCLUSION: Proven safe, a PCT algorithm for antibiotic discontinuation is a cost-effective means of reducing antibiotic exposure in adult ICU patients with sepsis, compared to current practice. Additional resources required for PCT are more than offset by downstream cost savings. This finding is highly important given the aim of preventing widespread antibiotic resistance.