| 1. |
- Colson, Abigail R., et al.
(författare)
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Antimicrobial Resistance : Is Health Technology Assessment Part of the Solution or Part of the Problem?
- 2021
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Ingår i: Value in Health. - : Elsevier. - 1098-3015 .- 1524-4733. ; 24:12, s. 1828-1834
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Tidskriftsartikel (refereegranskat)abstract
- Antimicrobial resistance is a serious challenge to the success and sustainability of our healthcare systems. There has been increasing policy attention given to antimicrobial resistance in the last few years, and increased amounts of funding have been channeled into funding for research and development of antimicrobial agents. Nevertheless, manufacturers doubt whether there will be a market for new antimicrobial technologies sufficient to enable them to recoup their investment. Health technology assessment (HTA) has a critical role in creating confidence that if valuable technologies can be developed they will be reimbursed at a level that captures their true value. We identify 3 deficiencies of current HTA processes for appraising antimicrobial agents: a methods-centric approach rather than problem-centric approach for dealing with new challenges, a lack of tools for thinking about changing patterns of infection, and the absence of an approach to epidemiological risks. We argue that, to play their role more effectively, HTA agencies need to broaden their methodological tool kit, design and communicate their analysis to a wider set of users, and incorporate long-term policy goals, such as containing resistance, as part of their evaluation criteria alongside immediate health gains.
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| 2. |
- Baltzer, Nicholas
(författare)
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Predictive Healthcare : Cervical Cancer Screening Risk Stratification and Genetic Disease Markers
- 2019
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- The use of Machine Learning is rapidly expanding into previously uncharted waters. In the medicine fields there are vast troves of data available from hospitals, biobanks and registries that now are being explored due to the tremendous advancement in computer science and its related hardware. The progress in genomic extraction and analysis has made it possible for any individual to know their own genetic code. Genetic testing has become affordable and can be used as a tool in treatment, discovery, and prognosis of individuals in a wide variety of healthcare settings. This thesis addresses three different approaches to-wards predictive healthcare and disease exploration; first, the exploita-tion of diagnostic data in Nordic screening programmes for the purpose of identifying individuals at high risk of developing cervical cancer so that their screening schedules can be intensified in search of new dis-ease developments. Second, the search for genomic markers that can be used either as additions to diagnostic data for risk predictions or as can-didates for further functional analysis. Third, the development of a Ma-chine Learning pipeline called ||-ROSETTA that can effectively process large datasets in the search for common patterns. Together, this provides a functional approach to predictive healthcare that allows intervention at early stages of disease development resulting in treatments with reduced health consequences at a lower financial burden
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| 3. |
- Gefenaite, Giedre, et al.
(författare)
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Estimating burden of influenza-associated influenza-like illness and severe acute respiratory infection at public healthcare facilities in Romania during the 2011/12-2015/16 influenza seasons
- 2018
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Ingår i: Influenza and other Respiratory Viruses. - : Wiley. - 1750-2640. ; 12:1, s. 183-192
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Tidskriftsartikel (refereegranskat)abstract
- Background: Influenza is responsible for substantial morbidity and mortality, but there is limited information on reliable disease burden estimates, especially from middle-income countries in the WHO European Region. Objectives: To estimate the incidence of medically attended influenza-associated influenza-like illness (ILI) and hospitalizations due to severe acute respiratory infection (SARI) presenting to public healthcare facilities in Romania. Patients/Methods: Sentinel influenza surveillance data for ILI and SARI from 2011/12-2015/16, including virological data, were used to estimate influenza-associated ILI and SARI incidence/100 000 and their 95% confidence intervals (95% CI). Results: The overall annual incidence of ILI and influenza-associated ILI per 100 000 persons in Romania varied between 68 (95% CI: 61-76) and 318 (95% CI: 298-338) and between 23 (95% CI: 19-29) and 189 (95% CI: 149-240), respectively. The highest ILI and influenza incidence was among children aged 0-4 years. We estimated that SARI incidence per 100 000 persons was 6 (95% CI: 5-7) to 9 (95% CI: 8-10), of which 2 (95% CI: 1-2) to 3 (95% CI: 2-4) were due to influenza. Up to 0.3% of the Romanian population were annually reported with ILI, and 0.01% was hospitalized with SARI, of which as much as one-third could be explained by influenza. Conclusions: This evaluation was the first study estimating influenza burden in Romania. We found that during each influenza season, a substantial number of persons in Romania suffer from influenza-related ILI or are hospitalized due to influenza-associated SARI.
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| 4. |
- Jombart, Thibaut, et al.
(författare)
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Real-time monitoring of COVID-19 dynamics using automated trend fitting and anomaly detection
- 2021
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Ingår i: Philosophical Transactions of the Royal Society of London. Biological Sciences. - : The Royal Society. - 0962-8436 .- 1471-2970. ; 376:1829
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Tidskriftsartikel (refereegranskat)abstract
- As several countries gradually release social distancing measures, rapid detection of new localized COVID-19 hotspots and subsequent intervention will be key to avoiding large-scale resurgence of transmission. We introduce ASMODEE (automatic selection of models and outlier detection for epidemics), a new tool for detecting sudden changes in COVID-19 incidence. Our approach relies on automatically selecting the best (fitting or predicting) model from a range of user-defined time series models, excluding the most recent data points, to characterize the main trend in an incidence. We then derive prediction intervals and classify data points outside this interval as outliers, which provides an objective criterion for identifying departures from previous trends. We also provide a method for selecting the optimal breakpoints, used to define how many recent data points are to be excluded from the trend fitting procedure. The analysis of simulated COVID-19 outbreaks suggests ASMODEE compares favourably with a state-of-art outbreak-detection algorithm while being simpler and more flexible. As such, our method could be of wider use for infectious disease surveillance. We illustrate ASMODEE using publicly available data of National Health Service (NHS) Pathways reporting potential COVID-19 cases in England at a fine spatial scale, showing that the method would have enabled the early detection of the flare-ups in Leicester and Blackburn with Darwen, two to three weeks before their respective lockdown. ASMODEE is implemented in the free R package trendbreaker.
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| 5. |
- Oppong, Raymond, et al.
(författare)
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Cost-effectiveness of point-of-care C-reactive protein testing to inform antibiotic prescribing decisions
- 2013
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Ingår i: British Journal of General Practice. - 1478-5242. ; 63:612, s. 465-471
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Tidskriftsartikel (refereegranskat)abstract
- Background Point-of-care C-reactive protein (POCCRP) is a biomarker of inflammation that offers clinicians a rapid POC test to guide antibiotic prescribing decisions for acute cough and lower respiratory tract infections (LRTI). However, evidence that POCCRP is cost-effective is limited, particularly outside experimental settings. Aim To assess the cost-effectiveness of POCCRP as a diagnostic tool for acute cough and LRTI from the perspective of the health service. Design and setting Observational study of the presentation, management, and outcomes of patients with acute cough and LRTI in primary care settings in Norway and Sweden. Method Using hierarchical regression, data were analysed in terms of the effect on antibiotic use, cost, and patient outcomes (symptom severity after 7 and 14 days, time to recovery, and EQ-5D), while controlling for patient characteristics (self-reported symptom severity, comorbidities, and health-related quality of life) at first attendance. Results POCCRP testing is associated with non-significant positive reductions in antibiotic prescribing (P = 0.078) and increased cost (P = 0.092). Despite the uncertainty, POCCRP testing is also associated with a cost per quality-adjusted life year (QALY) gain of (sic)9391. At a willingness-to-pay threshold of (sic)30 000 per QALY gained, there is a 70% probability of CRP being cost-effective. Conclusion POCCRP testing is likely to provide a cost-effective diagnostic intervention both in terms of reducing antibiotic prescribing and in terms of QALYs gained.
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