Quality of integrated chronic care measured by patient survey: identification, selection and application of most appropriate instruments\ud

Objective  To identify the most appropriate generic instrument to measure experience and/or satisfaction of people receiving integrated chronic care.\ud \ud Background  Health care is becoming more user-centred and, as a result, the experience of users of care and evaluation of their experience and/or satisfaction is taken more seriously. It is unclear to what extent existing instruments are appropriate in measuring the experience and/or satisfaction of people using integrated chronic care.\ud \ud Methods  Instruments were identified by means of a systematic literature review. Appropriateness of instruments was analysed on seven criteria. The two most promising instruments were translated into Dutch, if necessary, and administered to a convenience sample of 109 people with a chronic illness. Data derived from respondents were analysed statistically. Focus-group interviews were conducted to assess the semantic and technical equivalence as well as opinions of people about the applicability and relevance of the translated instruments.\ud \ud Results  From 37 instruments identified, the Patients’ Assessment of Care for chronIc Conditions (PACIC) and the short form of the Patient Satisfaction Questionnaire III (PSQ-18) were selected as most promising instruments. Both instruments produced similar median scores across people with different chronic conditions. The overall PACIC and its subscales and the overall PSQ-18 were highly internally consistent, but not the PSQ-18 subscales. Overall, the PACIC demonstrated better psychometric characteristics. PACIC and PSQ-18 scores were found to be moderately correlated. Whereas more respondents preferred the PSQ-18, focus-group participants regarded the PACIC to be more applicable and relevant. The technical and semantic equivalence of both instruments were sufficient.\ud \ud Conclusions  Because of its psychometric characteristics, perceived applicability and relevance, the PACIC is the most appropriate instrument to measure the experience of people receiving integrated chronic care\u

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 resistanc

Cost-effectiveness and resource use of implementing MRI-guided NACT in ER-positive/HER2-negative breast cancers in The Netherlands

Background: Response-guided neoadjuvant chemotherapy (RG-NACT) with magnetic resonance imaging (MRI) is effective in treating oestrogen receptor positive/human epidermal growth factor receptor-2 negative (ER-positive/HER2-negative) breast cancer. We estimated the expected cost-effectiveness and resources required for its implementation compared to conventional-NACT. Methods: A Markov model compared costs, quality-adjusted-life-years (QALYs) and costs/QALY of RG-NACT vs. conventional-NACT, from a hospital perspective over a 5-year time horizon. Health services required for and health outcomes of implementation were estimated via resource modelling analysis, considering a current (4 %) and a full (100 %) implementation scenario. Results: RG-NACT was expected to be more effective and less costly than conventional NACT in both implementation scenarios, with 94 % (current) and 95 % (full) certainty, at a willingness to pay threshold of €20.000/QALY. Fully implementing RG-NACT in the Dutch target population of 6306 patients requires additional 5335 MRI examinations and an (absolute) increase in the number of MRI technologists, by 3.6 fte (full-time equivalent), and of breast radiologists, by 0.4 fte. On the other hand, it prevents 9 additional relapses, 143 cancer deaths, 23 congestive heart failure events and 2 myelodysplastic syndrome/acute myeloid leukaemia events. Conclusion: Considering cost-effectiveness, RG-NACT is expected to dominate conventional-NACT. While personnel capacity is likely to be sufficient for a full implementation scenario, MRI utilization needs to be intensified

Return-to-work intervention for cancer survivors: budget impact and allocation of costs and returns in the Netherlands and six major EU-countries

Background Return-to-work (RTW)-interventions support cancer survivors in resuming work, but come at additional healthcare costs. The objective of this study was to assess the budget impact of a RTW-intervention, consisting of counselling sessions with an occupational physician and an exercise-programme. The secondary objective was to explore how the costs of RTW-interventions and its financial revenues are allocated among the involved stakeholders in several EU-countries. Methods The budget impact (BI) of a RTW-intervention versus usual care was analysed yearly for 2015–2020 from a Dutch societal- and from the perspective of a large cancer centre. The allocation of the expected costs and financial benefits for each of the stakeholders involved was compared between the Netherlands, Belgium, England, France, Germany, Italy, and Sweden. Results The average intervention costs in this case were €1,519/patient. The BI for the Netherlands was €-14.7 m in 2015, rising to €-71.1 m in 2020, thus the intervention is cost-saving as the productivity benefits outweigh the intervention costs. For cancer centres the BI amounts to €293 k in 2015, increasing to €1.1 m in 2020. Across European countries, we observed differences regarding the extent to which stakeholders either invest or receive a share of the benefits from offering a RTW-intervention. Conclusion The RTW-intervention is cost-saving from a societal perspective. Yet, the total intervention costs are considerable and, in many European countries, mainly covered by care providers that are not sufficiently reimbursed

An appeal to the global health community for a tripartite innovation: an ‘‘Essential Diagnostics List,’’ ‘‘Health in All Policies,’’ and ‘‘See-Through 21st Century Science and Ethics"

Diagnostics spanning a wide range of new biotechnologies, including proteomics, metabolomics, and nanotechnology, are emerging as companion tests to innovative medicines. In this Opinion, we present the rationale for promulgating an ‘‘Essential Diagnostics List.’’ Additionally, we explain the ways in which adopting a vision for ‘‘Health in All Policies’’ could link essential diagnostics with robust and timely societal outcomes such as sustainable development, human rights, gender parity, and alleviation of poverty. We do so in three ways. First, we propose the need for a new, ‘‘see through’’ taxonomy for knowledge-based innovation as we transition from the material industries (e.g., textiles, plastic, cement, glass) dominant in the 20th century to the anticipated knowledge industry of the 21st century. If knowledge is the currency of the present century, then it is sensible to adopt an approach that thoroughly examines scientific knowledge, starting with the production aims, methods, quality, distribution, access, and the ends it purports to serve. Second, we explain that this knowledge trajectory focus on innovation is crucial and applicable across all sectors, including public, private, or public–private partnerships, as it underscores the fact that scientific knowledge is a co-product of technology, human values, and social systems. By making the value systems embedded in scientific design and knowledge co-production transparent, we all stand to benefit from sustainable and transparent science. Third, we appeal to the global health community to consider the necessary qualities of good governance for 21st century organizations that will embark on developing essential diagnostics. These have importance not only for science and knowledge based innovation, but also for the ways in which we can build open, healthy, and peaceful civil societies today and for future generations

Improving early cycle economic evaluation of diagnostic technologies

The rapidly increasing range and expense of new diagnostics, compels consideration of a different, more proactive approach to health economic evaluation of diagnostic technologies. Early cycle economic evaluation is a decision analytic approach to evaluate technologies in development so as to increase the return on investment as well as patient and societal impact. This paper describes examples of ‘early cycle economic evaluations’ as applied to diagnostic technologies and highlights challenges in its real-time application. It shows that especially in the field of diagnostics, with rapid technological developments and a changing regulatory climate, early cycle economic evaluation can have a guiding role to improve the efficiency of the diagnostics innovation process. In the next five years the attention will move beyond the methodological and analytic challenges of early cycle economic evaluation towards the challenge of effectively applying it to improve diagnostic research and development and patient value. Future work in this area should therefore be ‘strong on principles and soft on metrics’, that is, the metrics that resonate most clearly with the various decision makers in this fiel

Belief Elicitation to Populate Health Economic Models of Medical Diagnostic Devices in Development

Background and Objective Bayesian methods can be used to elicit experts’ beliefs about the clinical value of healthcare technologies. This study investigates a belief–elicitation method for estimating diagnostic performance in an early stage of development of photoacoustic mammography (PAM) imaging versus magnetic resonance imaging (MRI) for detecting breast cancer. Research Design Eighteen experienced radiologists ranked tumor characteristics regarding their importance to detect malignancies. With reference to MRI, radiologists estimated the true positives and negatives of PAM using the variable interval method. An overall probability density function was determined using linear opinion pooling, weighted for individual experts’ experience. Result The most important tumor characteristics are mass margins and mass shape. Respondents considered MRI the better technology to visualize these characteristics. Belief elicitation confirmed this by providing an overall sensitivity of PAM ranging from 58.9 to 85.1 % (mode 75.6 %) and specificity ranging from 52.2 to 77.6 % (mode 66.5 %). Conclusion Belief elicitation allowed estimates to be obtained for the expected diagnostic performance of PAM, although radiologists expressed difficulties in doing so. Heterogeneity within and between experts reflects this uncertainty and the infancy of PAM. Further clinical trials are required to validate the extent to which this belief–elicitation method is predictive for observed test performanc

Shifting breast cancer surveillance from current hospital setting to a community based setting: A cost-effectiveness study

Background: This study explores the effectiveness and cost-effectiveness of surveillance after breast cancer treatment provided in a hospital-setting versus surveillance embedded in the community-based National Breast Cancer Screening Program (NBCSP). Methods: Using a decision tree, strategies were compared on effectiveness and costs from a healthcare perspective over a 5-year time horizon. Women aged 50-75 without distant metastases that underwent breast conserving surgery in 2003-2006 were selected from the Netherlands Cancer Registry (n = 14,093). Key input parameters were mammography sensitivity and specificity, risk of loco regional recurrence (LRR), and direct healthcare costs. Primary outcome measure was the proportion true test results (TTR), expressed as the positive and negative predictive value (PPV, NPV). The incremental cost-effectiveness ratio (ICER) is defined as incremental costs per TTR forgone. Results: For the NBCSP-strategy, 13,534 TTR (8 positive; 13,526 negative), and 12,923 TTR (387 positive; 12,536 negative) were found for low and high risks respectively. For the hospital-based strategy, 26,663 TTR (13 positive; 26,650 negative) and 24,883 TTR (440 positive; 24,443 negative) were found for low and high risks respectively. For low risks, the PPV and NPV for the NBCSP-based strategy were 3.31% and 99.88%, and 2.74% and 99.95% for the hospital strategy respectively. For high risks, the PPV and NPV for the NBCSP-based strategy were 64.10% and 98.87%, and 50.98% and 99.71% for the hospital-based strategy respectively. Total expected costs of the NBCSP-based strategy were lower than for the hospital-based strategy (low risk: €1,271,666 NBCSP vs €2,698,302 hospital; high risk: €6,939,813 NBCSP vs €7,450,150 hospital), rendering ICERs that indicate cost savings of €109 (95%CI €95-€127) (low risk) and €43 (95%CI €39-€56) (high risk) per TTR forgone. Conclusion: Despite expected cost-savings of over 50% in the NBCSP-based strategy, it is nearly 50% lower accurate than the hospital-based strategy, compromising the goal of early detection of LRR to an extent that is unlikely to be acceptable