Cost-effectiveness analysis of ferric carboxymaltose in iron-deficient patients with chronic heart failure in Sweden.

OBJECTIVE: Iron deficiency is a common but treatable comorbidity in chronic heart failure (CHF) that is associated with impaired health-related quality-of-life (HRQoL). This study evaluates the cost-effectiveness of the intravenous iron preparation ferric carboxymaltose (FCM) for the treatment of iron deficiency in CHF from a Swedish healthcare perspective. METHODS: A cost-effectiveness analysis with a time horizon of 24 weeks was performed to compare FCM treatment with placebo. Data on health outcomes and medical resource use were mainly taken from the FAIR-HF trial and combined with Swedish cost data. An incremental cost-effectiveness ratio (ICER) was calculated as well as the change in per-patient costs for primary care and hospital care. RESULTS: In the FCM group compared with placebo, quality-adjusted life years (QALYs) are higher (difference = 0.037 QALYs), but so are per-patient costs [(difference = SEK 2789 (€303)]. Primary care and hospital care equally share the additional costs, but within hospitals there is a major shift of costs from inpatient care to outpatient care. The ICER is SEK 75,389 (€8194) per QALY. The robustness of the result is supported by sensitivity analyses. CONCLUSIONS: Treatment of iron deficiency in CHF with FCM compared with placebo is estimated to be cost-effective. The ICER in the base case scenario is twice as high as previously thought, but noticeably below SEK 500,000 (€54,300) per QALY, an informal average reference value used by the Swedish Dental and Pharmaceutical Benefits Agency. Increased HRQoL and fewer hospitalizations are the key drivers of this result

Semantic HELM: A Human-Readable Memory for Reinforcement Learning

Reinforcement learning agents deployed in the real world often have to cope with partially observable environments. Therefore, most agents employ memory mechanisms to approximate the state of the environment. Recently, there have been impressive success stories in mastering partially observable environments, mostly in the realm of computer games like Dota 2, StarCraft II, or MineCraft. However, existing methods lack interpretability in the sense that it is not comprehensible for humans what the agent stores in its memory. In this regard, we propose a novel memory mechanism that represents past events in human language. Our method uses CLIP to associate visual inputs with language tokens. Then we feed these tokens to a pretrained language model that serves the agent as memory and provides it with a coherent and human-readable representation of the past. We train our memory mechanism on a set of partially observable environments and find that it excels on tasks that require a memory component, while mostly attaining performance on-par with strong baselines on tasks that do not. On a challenging continuous recognition task, where memorizing the past is crucial, our memory mechanism converges two orders of magnitude faster than prior methods. Since our memory mechanism is human-readable, we can peek at an agent's memory and check whether crucial pieces of information have been stored. This significantly enhances troubleshooting and paves the way toward more interpretable agents.Comment: To appear at NeurIPS 2023, 10 pages (+ references and appendix), Code: https://github.com/ml-jku/hel

Learning to Modulate pre-trained Models in RL

Reinforcement Learning (RL) has been successful in various domains like robotics, game playing, and simulation. While RL agents have shown impressive capabilities in their specific tasks, they insufficiently adapt to new tasks. In supervised learning, this adaptation problem is addressed by large-scale pre-training followed by fine-tuning to new down-stream tasks. Recently, pre-training on multiple tasks has been gaining traction in RL. However, fine-tuning a pre-trained model often suffers from catastrophic forgetting. That is, the performance on the pre-training tasks deteriorates when fine-tuning on new tasks. To investigate the catastrophic forgetting phenomenon, we first jointly pre-train a model on datasets from two benchmark suites, namely Meta-World and DMControl. Then, we evaluate and compare a variety of fine-tuning methods prevalent in natural language processing, both in terms of performance on new tasks, and how well performance on pre-training tasks is retained. Our study shows that with most fine-tuning approaches, the performance on pre-training tasks deteriorates significantly. Therefore, we propose a novel method, Learning-to-Modulate (L2M), that avoids the degradation of learned skills by modulating the information flow of the frozen pre-trained model via a learnable modulation pool. Our method achieves state-of-the-art performance on the Continual-World benchmark, while retaining performance on the pre-training tasks. Finally, to aid future research in this area, we release a dataset encompassing 50 Meta-World and 16 DMControl tasks.Comment: 10 pages (+ references and appendix), Code: https://github.com/ml-jku/L2

What do general practitioners know about ADHD? Attitudes and knowledge among first-contact gatekeepers: systematic narrative review

Background: Attention Deficit Hyperactivity Disorder (ADHD) is a common childhood disorder with international prevalence estimates of 5 % in childhood, yet significant evidence exists that far fewer children receive ADHD services. In many countries, ADHD is assessed and diagnosed in specialist mental health or neuro-developmental paediatric clinics, to which referral by General (Family) Practitioners (GPs) is required. In such ‘gatekeeper’ settings, where GPs act as a filter to diagnosis and treatment, GPs may either not recognise potential ADHD cases, or may be reluctant to refer. This study systematically reviews the literature regarding GPs’ views of ADHD in such settings. Methods: A search of nine major databases was conducted, with wide search parameters; 3776 records were initially retrieved. Studies were included if they were from settings where GPs are typically gatekeepers to ADHD services; if they addressed GPs’ ADHD attitudes and knowledge; if methods were clearly described; and if results for GPs were reported separately from those of other health professionals. Results: Few studies specifically addressed GP attitudes to ADHD. Only 11 papers (10 studies), spanning 2000–2010, met inclusion criteria, predominantly from the UK, Europe and Australia. As studies varied methodologically, findings are reported as a thematic narrative, under the following themes: Recognition rate; ADHD controversy (medicalisation, stigma, labelling); Causes of ADHD; GPs and ADHD diagnosis; GPs and ADHD treatment; GP ADHD training and sources of information; and Age, sex differences in knowledge and attitudes. Conclusions: Across times and settings, GPs practising in first-contact gatekeeper settings had mixed and often unhelpful attitudes regarding the validity of ADHD as a construct, the role of medication and how parenting contributed to presentation. A paucity of training was identified, alongside a reluctance of GPs to become involved in shared care practice. If access to services is to be improved for possible ADHD cases, there needs to be a focused and collaborative approach to training

Characteristics and trends in required home care by GPs in Austria: diseases and functional status of patients

BACKGROUND: Almost all societies carry responsibility towards patients who require continuous medical care at home. In many health systems the general practitioner cooperates with community based services of home care and coordinates all medical and non medical activities. In Austria the general practitioner together and in cooperation with relatives of the patient and professional organisations usually takes on this task by visiting his patients. This study was carried out to identify diseases that need home care and to describe the functional profile of home care patients in eastern Austria. METHODS: Cross sectional observational study with 17 GP practices participating during 2 study periods in 1997 and in 2004 in eastern Austria. Each GP identified patients requiring home care and assessed their underlying diseases and functional status by filling in a questionnaire personally after an encounter. Patients in nursing homes were excluded. Statistical tests used were t-tests, contingency tables, nonparametric Wilcoxon signed rank sum test and Fisher-combination test. RESULTS: Patients with degenerative diseases of the central nervous system (65%) caused by Alzheimer's disease and cerebrovascular occlusive disease and patients with degenerative diseases of the skeletal system (53%) were the largest groups among the 198 (1997) and 261 (2004) home care cases of the 11 (1997) and 13 (2004) practices. Malignant diseases in a terminal state constituted only 5% of the cases. More than two thirds of all cases were female with an average age of 80 years. Slightly more than 70% of the patients were at least partially mobile. CONCLUSION: Home care and home visits for patients with degenerative diseases of the central nervous and skeletal system are important elements of GP's work. Further research should therefore focus on effective methods of training and rehabilitation to better the mental and physical status of patients living in their private homes

Transforming medical professionalism to fit changing health needs

<p>Abstract</p> <p>Background</p> <p>The professional organization of medical work no longer reflects the changing health needs caused by the growing number of complex and chronically ill patients. Key stakeholders enforce coordination and remove power from the medical professions in order allow for these changes. However, it may also be necessary to initiate basic changes to way in which the medical professionals work in order to adapt to the changing health needs.</p> <p>Discussion</p> <p>Medical leaders, supported by health policy makers, can consciously activate the self-regulatory capacity of medical professionalism in order to transform the medical profession and the related professional processes of care so that it can adapt to the changing health needs. In doing so, they would open up additional routes to the improvement of the health services system and to health improvement. This involves three consecutive steps: (1) defining and categorizing the health needs of the population; (2) reorganizing the specialty domains around the needs of population groups; (3) reorganizing the specialty domains by eliminating work that could be done by less educated personnel or by the patients themselves. We suggest seven strategies that are required in order to achieve this transformation.</p> <p>Summary</p> <p>Changing medical professionalism to fit the changing health needs will not be easy. It will need strong leadership. But, if the medical world does not embark on this endeavour, good doctoring will become merely a bureaucratic and/or marketing exercise that obscures the ultimate goal of medicine which is to optimize the health of both individuals and the entire population.</p

Modeling Mortality Rates In The WikiLeaks Afghanistan War Logs

The WikiLeaks Afghanistan war logs contain more than 76 000 reports about fatalities and their circumstances in the US led Afghanistan war, covering the period from January 2004 to December 2009. In this paper we use those reports to build statistical models to help us understand the mortality rates associated with specific circumstances. We choose an approach that combines Latent Dirichlet Allocation (LDA) with negative binomial based recursive partitioning. LDA is used to process the natural language information contained in each report summary. We estimate latent topics and assign each report to one of them. These topics - in addition to other variables in the data set - subsequently serve as explanatory variables for modeling the number of fatalities of the civilian population, ISAF Forces, Anti-Coalition Forces and the Afghan National Police or military as well as the combined number of fatalities. Modeling is carried out with manifest mixtures of negative binomial distributions estimated with model-based recursive partitioning. For each group of fatalities, we identify segments with different mortality rates that correspond to a small number of topics and other explanatory variables as well as their interactions. Furthermore, we carve out the similarities between segments and connect them to stories that have been covered in the media. This provides an unprecedented description of the war in Afghanistan covered by the war logs. Additionally, our approach can serve as an example as to how modern statistical methods may lead to extra insight if applied to problems of data journalism. (author's abstract)Series: Research Report Series / Department of Statistics and Mathematic

Essays in Empirical Labor Economics

This thesis contributes to empirical research in labor economics. It consists of three self-contained papers.The first paper, The Effect of Paid Vacation on Health: Evidence from Sweden, analyzes the causal effect of paid vacation on health. Using register data on the universe of central government employees in Sweden, I exploit an age-based rule stipulated in the collective agreement covering these employees. The results indicate that no statistically significant changes in health are induced by an increase of three paid vacation days at age 30 and four days at age 40. These findings challenge the anecdotal view of additional paid vacation days as an adequate means to improve workers' health.The second paper, The Effect of Education on Poverty: A European Perspective, studies the causal relationship between education and poverty. I construct a novel database comprising compulsory schooling reforms in 32 European countries and use them as instruments for education. I find economically large poverty-reducing effects of education among people aged 30 to 80. This holds true for both objective and subjective measures of poverty. An additional year of education thus reduces not only the likelihood of being classified as poor but also the likelihood of feeling poor.The third paper, Is There Less Household Specialization in Gay and Lesbian Couples?, examines intra-couple differences in earnings potential as a source of specialization in same-sex and different-sex couples. We find that spouses with a higher earnings potential spend significantly more time on market work and less time on household work than spouses with a lower earnings potential. We observe this pattern in gay, lesbian, and different-sex couples. The effect of intra-couple differences in earnings potential on household specialization does mostly not differ statistically in gay and lesbian couples relative to different-sex couples

The Effect of Education on Poverty: A European Perspective

This paper provides evidence on the causal relationship between education and poverty. I construct a novel database comprising compulsory schooling reforms in 32 European countries and use them as instruments for education. I find economically large poverty-reducing effects of education among people aged 30 to 80. This holds true for both objective measures of poverty (relative income poverty, lack of basic necessities, weak labor market attachment) and a subjective measure of poverty (self-assessed difficulties in making ends meet). An additional year of education thus reduces not only the likelihood of being classified as living in poverty but also the likelihood of considering oneself to live in poverty. Increases in labor force participation and full-time employment as well as better health are potential mechanisms behind these results