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Efficient Secondary Use of Representative Social and Health Care Data In Finland: Isaacus Data Lake, Analytics and Knowledge Management Pre-Production Project
... More specifically, the assessment and implementation of digitalized customerresponsive health and social care services including, for example, Omahoito ja Digitaaliset Arvopalvelut (ODA)digitalized services for primary health and social care, 73,74 together with the associated Health Village are under their way. Moreover, the secondary use data lakes covering social and health data have been tested through so-called Isaacus pre-production projects, 75,76 and the remote use platforms for the data lakes together with scientist tools are being built to enable knowledge management and research. 75 Tools with novel data collecting software such as PEUS [25][26][27][28][29] are likely to fit well to this ongoing development. ...
... Moreover, the secondary use data lakes covering social and health data have been tested through so-called Isaacus pre-production projects, 75,76 and the remote use platforms for the data lakes together with scientist tools are being built to enable knowledge management and research. 75 Tools with novel data collecting software such as PEUS [25][26][27][28][29] are likely to fit well to this ongoing development. ...
Purpose
Osteoporosis is asymptomatic morbidity of the elderly which develops slowly over several years. Osteoporosis diagnosis has typically involved Fracture Risk Assessment (FRAX) followed by dual energy X-ray absorptiometry (DXA) in specialist care. Point-of-care pulse-echo ultrasound (PEUS) was developed to overcome DXA-related access issues and to enable faster fracture prevention treatment (FPT) initiation. The objective of this study was to evaluate the cost-effectiveness of two proposed osteoporosis management (POMs: FRAX→PEUS-if-needed→DXA-if-needed→FPT-if-needed) pathways including PEUS compared with the current osteoporosis management (FRAX→DXA-if-needed→FPT-if-needed).
Materials and methods
Event-based probabilistic cost–utility model with 10-year duration for osteoporosis management was developed. The model consists of a decision tree for the screening, testing, and diagnosis phase and is followed by a Markov model for the estimation of incidence of four fracture types and mortality. Five clinically relevant patient cohorts (potential primary FPT in women aged 75 or 85 years, secondary FPT in women aged 65, 75, or 85 years) were modeled in the Finnish setting. Generic alendronate FPT was used for those diagnosed with osteoporosis, including persistence overtime. Discounted (3%/year) incremental cost-effectiveness ratio was the primary outcome. Discounted quality-adjusted life-years (QALYs), payer costs (year 2016 value) at per patient and population level, and cost-effectiveness acceptability frontiers were modeled as secondary outcomes.
Results
POMs were cost-effective in all patient subgroups with noteworthy mean per patient cost savings of €121/76 (ranges €107–132/52–96) depending on the scope of PEUS result interpretation (test and diagnose/test only, respectively) and negligible differences in QALYs gained in comparison with current osteoporosis management. In the cost-effectiveness acceptability frontiers, POMs had 95%–100% probability of cost-effectiveness with willingness to pay €24,406/QALY gained. The results were robust in sensitivity analyses. Even when assuming a high cost of PEUS (up to €110/test), POMs were cost-effective in all cohorts.
Conclusion
The inclusion of PEUS to osteoporosis management pathway was cost-effective.
... • The vast part of the data collected within the research sub-domain is unstructured and data extraction becomes a challenge within this subdomain. This means that only the data lake solution is applicable, see e.g., Soini et al. (2017); Miloslavskaya and Tolstoy (2016);Fang (2015). ...
Cannabinoid research requires the cooperation of experts from various field biochemistry and chemistry to psychological and social sciences. The data that have to be managed and analysed are highly heterogeneous, especially because they are provided by a very diverse range of sources. A number of approaches focused on data collection and the corresponding analysis, restricting the scope to a sub-domain. Our goal is to elaborate a solution that would allow for automated management and analysis of heterogeneous data within the complete cannabinoids domain. The corresponding integration of diverse data sources would increase the quality and preciseness of the analysis. In this paper, we introduce the core ideas of the proposed framework as well as present the implemented prototype of a cannabinoids data platform.
... However, more studies are needed to model the outcomes of different treatment sequences and the real-world HE outcomes of an RSS, where implemented. HE/ outcomes research studies and RSSs in Finland are likely to get easier because of the interest of current care working groups in HE issues [59], and the planned launch of Isaacus (in early 2018), a Finnish data operator that is expected to provide nationally representative well-being data from different information sources and registers on a one-stop-shop basis [60]. ...
Purpose:
To model the American College of Rheumatology (ACR) outcomes, cost-effectiveness, and budget impact of certolizumab pegol (CZP) (with and without a hypothetical risk-sharing scheme at treatment initiation for biologic-naïve patients) versus the current mix of reimbursed biologics for treatment of moderate-to-severe rheumatoid arthritis (RA) in Finland.
Methods:
A probabilistic model with 12-week cycles and a societal approach was developed for the years 2015-2019, accounting for differences in ACR responses (meta-analysis), mortality, and persistence. The risk-sharing scheme included a treatment switch and refund of the costs associated with CZP acquisition if patients failed to achieve ACR20 response at week 12. For the current treatment mix, ACR20 at week 24 determined treatment continuation. Quality-adjusted life years were derived on the basis of the Health Utilities Index.
Results:
In the Finnish target population, CZP treatment with a risk-sharing scheme led to a estimated annual net expenditure decrease ranging from 1.7% in 2015 to 5.6% in 2019 compared with the current treatment mix. Per patient over the 5 years, CZP risk sharing was estimated to decrease the time without ACR response by 5%-units, decrease work absenteeism by 24 days, and increase the time with ACR20, ACR50, and ACR70 responses by 5%-, 6%-, and 1%-units, respectively, with a gain of 0.03 quality-adjusted life years. The modeled risk-sharing scheme showed reduced costs of €7866 per patient, with a more than 95% probability of cost-effectiveness when compared with the current treatment mix.
Conclusion:
The present analysis estimated that CZP, with or without the risk-sharing scheme, is a cost-effective alternative treatment for RA patients in Finland. The surplus provided by the CZP risk-sharing scheme could fund treatment for 6% more Finnish RA patients.
Funding:
UCB Pharma.
Aim: To estimate the drug administration, travelling, and productivity costs associated with infusion or subcutaneous proteasome inhibitor (PI) treatments (specifically carfilzomib and bortezomib) for multiple myeloma (MM) patients in Finland.
Materials and methods: Price tariffs of Finnish hospital districts are used as the basis of invoicing sent to health care service payers. A review of these price tariff lists was conducted and obtained data analyzed to estimate the mean unit cost of PI administration visit. Travelling costs stratified by areas with different population densities were assessed, based on the national travelling reimbursement register data maintained by the Social Insurance Institution of Finland. Productivity costs due to time spent on administration visits and travelling were estimated based on an expert interview and a spatial health care accessibility analysis.
Results: Nineteen (95%) of the Finnish hospital districts were included in the review. Relevant unit cost information was found for 15 (75%) of the districts. The mean PI administration cost alone was 270€(95%CI 189€– 351€) per administration and increased to 371€when travelling costs were included. Productivity costs added, the mean PI administration costs totaled 405€for bortezomib and 437€for carfilzomib.
Limitations: The costing rationale of price tariffs may vary between hospital districts. Productivity costs were estimated conservatively, due to lack of data.
Conclusions: The administration of intravenous or subcutaneous PIs to treat MM in health care facilities causes significant and potentially avoidable health care, travelling and indirect costs and they should be included in all health economic evaluations (HEEs). As the cost estimates utilized in this study represent most of central hospitals in the country, they provide useful information for future HEEs. A broader conclusion is that novel oral medications, such as the first oral PI, have a significant potential for reducing administration-related costs of subcutaneous or intravenous PIs.
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