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Norway has a high degree of digitalisation. In the public sector, there is a long tradition of automation of parts of case management. This includes automation of cases where a public sector body makes a so-called individual administrative decision, that is, a decision made in the exercise of public authority through which the rights or duties of one or more specified private persons are determined. In the last five years, various amendments to public sector legislation were proposed by a number of government departments and agencies in Norway to ensure that the relative administrative agency has a legal basis to carry out fully automated individual decisions. This is challenging both from an administrative law and from a data protection law standpoint. Among the main reasons for the move towards fully automated legal decision-making that are mentioned in the preparatory works to the proposed amendments are greater efficiency in decision-making, equal treatment of citizens and a claim that such decisions will be less prone to error than human decisions. This paper examines this trend in Norway and identifies the statutes and regulations that have been amended or are in the process of being amended. It analyses the measures specified in these amendments to safeguard the individual party's rights, freedoms and legitimate interests. Finally, it discusses the tightrope that must be walked to safeguard important administrative law principles and rules such as protection from arbitrary decisions, the audi alternam partem rule and the right under the European Union's General Data Protection Regulation not to be subject to fully automated decisions. [ABSTRACT FROM AUTHOR]

We examined the short-term risk of stroke associated with drugs prescribed in Norway or Sweden in a comprehensive, hypothesis-free manner using comprehensive nation-wide data. We identified 27,680 and 92,561 cases with a first ischemic stroke via the patient- and the cause-of-death registers in Norway (2004–2014) and Sweden (2005–2014), respectively, and linked these data to prescription databases. A case-crossover design was used that compares the drugs dispensed within 1 to 14 days before the date of ischemic stroke occurrence with those dispensed 29 to 42 days before the index event. A Bolasso approach, a version of the Lasso regression algorithm, was used to select drugs that acutely either increase or decrease the apparent risk of ischemic stroke. Application of the Bolasso regression algorithm selected 19 drugs which were associated with increased risk for ischemic stroke and 11 drugs with decreased risk in both countries. Morphine in combination with antispasmodics was associated with a particularly high risk of stroke (odds ratio 7.09, 95% confidence intervals 4.81–10.47). Several potentially intriguing associations, both within and across pharmacological classes, merit further investigation in focused, follow-up studies. [ABSTRACT FROM AUTHOR]

Abstract: Purpose: This paper analyses the problem of allocating beds among hospital wards in order to minimise crowding. Method: We present a generic discrete event simulation model of patient flow through the wards of a hospital. In the generic model, each ward can have separate probability distributions for arrival times and length of stay, which may be time dependent. Output of the model is a matrix, with statistics on the utilisation of different hypothetical numbers of beds for each ward. This matrix is fed into an allocation algorithm, which distributes the available beds among the wards in an optimal way. We define bed utilisation either in terms of how often it is in use (prevalence), or in terms of how often a newly arriving patient is placed in it (incidence). For these classes of utilisation measures we develop efficient allocation algorithms, which we prove to be optimal. Application: The model was applied to Akershus University Hospital in Norway. In 2011, some of the wards of this hospital experienced a high occupancy rate, while others had a lower utilisation. Our model was applied in order to reallocate the hospital beds among the wards. For each ward, acute arrivals were modelled with Poisson-distributions with time-varying intensity, while elective arrivals were programmed to arrive in specific numbers at specific times. The arrival rates were based on empirical data for 2010, scaled up by an expected increase of 40% due to a restructuring of the hospital districts in Oslo and the greater metropolitan area in 2011. Length of stay was modelled as beta-distributions, using a combination of subject matter experts’ evaluations and empirical data from 2010. The model has been verified and validated. Results: Intuitively, both prevalence (average number of crowding beds in use) and incidence (number of patients placed in crowding beds) might seem like relevant optimisation criteria. However, our experiments show that prevalence optimisation gives more sensible solutions than incidence optimisation, as the latter tends to sacrifice entire wards where length of stay is long and patient turnover is slow. Prevalence optimisation was therefore used. The main results show that when the bed distribution is optimised, the share of crowding patient nights is reduced from 6.5% to 4.2%. Conclusion: This model provides a powerful tool for optimising hospital bed utilisation, and the application showed an important reduction in crowding bed usage. The generic model is flexible, as the level of detail in the modelling of arrivals and length of stay can vary according to the data available and accuracy required. [Copyright &y& Elsevier]

The article offers implementation details on the integration between a security suite and a cooperative algorithm in autonomous mobile sensors. It discusses the use of an underwater acoustic network to secure cooperation of the sensors. It explores the development of the security suite to ensure trustworthiness of the sensors. The performance of the sensors during an Autonomous Underwater Vehicle (AUV) project sea trial held in Trondheim, Norway, in May 2011 is discussed.

Background: Patients and clinicians often struggle to choose the optimal management strategy for posttraumatic knee osteoarthritis (OA) after an anterior cruciate ligament (ACL) injury. An evaluation of radiographic outcomes after a decision-making and treatment algorithm applicable in clinical practice can help to inform future recommendations and treatment choices. Purpose: To describe and compare 5-year radiographic outcomes and knee pain in individuals who had gone through our decision-making and treatment algorithm and chosen (1) early (<6 months) ACL reconstruction (ACLR) with pre- and postoperative rehabilitation, (2) delayed (>6 months) ACLR with pre- and postoperative rehabilitation, or (3) progressive rehabilitation alone. Study Design: Cohort study; Level of evidence, 2. Methods: We included 276 patients with unilateral ACL injury from a prospective cohort study. Patients chose management using a shared decision-making process and treatment algorithm, and 5-year postoperative radiographs of the index and contralateral knees were assessed using the Kellgren and Lawrence (K&L) classification and minimum joint space width measurements. We defined radiographic tibiofemoral OA as K&L grade ≥2 and knee pain as a Knee injury and Osteoarthritis Outcome Score for Pain ≤72. To further explore early radiographic changes, we included alternative cutoffs for radiographic knee OA using K&L grade ≥2/osteophyte (definite osteophyte without joint space narrowing) and K&L grade ≥1. Results: At 5 years, 64% had undergone early ACLR; 11%, delayed ACLR; and 25%, progressive rehabilitation alone. Radiographic examination was attended by 187 patients (68%). Six percent of the cohort had radiographic tibiofemoral OA (K&L grade ≥2) in the index knee; 4%, in the contralateral knee. Using the alternative cutoffs at K&L grade ≥2/osteophyte and K&L grade ≥1, the corresponding numbers were 20% and 33% in the index knee and 18% and 29% in the contralateral knee. Six percent had a painful index knee. There were no statistically significant differences in any radiographic outcomes or knee pain among the 3 management groups. Conclusion: There were no statistically significant differences in any 5-year radiographic outcomes or knee pain among the 3 management groups. Very few of the patients who participated in our decision-making and treatment algorithm had knee OA or knee pain at 5 years. [ABSTRACT FROM AUTHOR]

Background: The Medical Birth Registry of Norway (MBRN) provides national coverage of all births. While retrieval of most of the information in the birth records is mandatory, mothers may refrain to provide information on her smoking status. The proportion of women with unknown smoking status varied greatly over time, between hospitals, and by demographic groups. We investigated if incomplete data on smoking in the MBRN may have contributed to a biased smoking prevalence.Methods: In a study population of all 904,982 viable and singleton births during 1999-2014, we investigated main predictor variables influencing the unknown smoking status of the mothers' using linear multivariable regression. Thereafter, we applied machine learning to predict annual smoking prevalence (95% CI) in the same group of unknown smoking status, assuming missing-not-at-random.Results: Overall, the proportion of women with unknown smoking status was 14.4%. Compared to the Nordic country region of origin, women from Europe outside the Nordic region had 15% (95% CI 12-17%) increased adjusted risk to have unknown smoking status. Correspondingly, the increased risks for women from Asia was 17% (95% CI 15-19%) and Africa 26% (95% CI 23-29%). The most important machine learning prediction variables regarding maternal smoking were education, ethnic background, marital status and birth weight. We estimated a change from the annual observed smoking prevalence among the women with known smoking status in the range of - 5.5 to 1.1% when combining observed and predicted smoking prevalence.Conclusion: The predicted total smoking prevalence was only marginally modified compared to the observed prevalence in the group with known smoking status. This implies that MBRN-data may be trusted for health surveillance and research. [ABSTRACT FROM AUTHOR]

The evolution of drug resistant parasitic sea lice is of major concern to the salmon farming industry worldwide and challenges sustainable growth of this enterprise. To assess current status and development of L. salmonis sensitivity towards different pesticides used for parasite control in Norwegian salmon farming, a national surveillance programme was implemented in 2013. The programme aims to summarize data on the use of different pesticides applied to control L. salmonis and to test L. salmonis sensitivity to different pesticides in farms along the Norwegian coast. Here we analyse two years of test-data from biological assays designed to detect sensitivity-levels towards the pesticides azamethiphos and deltamethrin, both among the most common pesticides used in bath-treatments of farmed salmon in Norway in later years. The focus of the analysis is on how different variables predict the binomial outcome of the bioassay tests, being whether L. salmonis are immobilized/die or survive pesticide exposure. We found that local kernel densities of bath treatments, along with a spatial geographic index of test-farm locations, were significant predictors of the binomial outcome of the tests. Furthermore, the probability of L. salmonis being immobilized/dead after test-exposure was reduced by odds-ratios of 0.60 (95% CI: 0.42–0.86) for 2014 compared to 2013 and 0.39 (95% CI: 0.36–0.42) for low concentration compared to high concentration exposure. There were also significant but more marginal effects of parasite gender and developmental stage, and a relatively large random effect of test-farm. We conclude that the present data support an association between local intensities of bath treatments along the coast and the outcome of bioassay tests where salmon lice are exposed to azamethiphos or deltamethrin. Furthermore, there is a predictable structure of L. salmonis phenotypes along the coast in the data, characterized by high susceptibility to pesticides in the far north and far south, but low susceptibility in mid Norway. The study emphasizes the need to address local susceptibility to pesticides and the need for restrictive use of pesticides to preserve treatment efficacy. [ABSTRACT FROM AUTHOR]

Organophosphates (OP) are one of the major treatments used against the salmon louse (Lepeophtherius salmonis) in Norwegian salmonid aquaculture. The use of OP since the late 1970s has resulted in widespread resistant parasites. Recently, we reported a single mutation (Phe362Tyr) in acetylcholinesterase (AChE) as the major mechanism behind resistance in salmon louse towards OP. The present study was carried out to validate this mechanism at the field level. A total of 6658 salmon louse samples were enrolled from 56 different fish farms across the Norwegian coast, from Vest Agder in the south to Finnmark in the north. All the samples were genotyped using a TaqMan probe assay for the Phe362Tyr mutation. A strong association was observed between areas with frequent use of the OP (azamethiphos) and the Phe362Tyr mutation. This was confirmed at 15 sites where results from independently conducted bioassays and genotyping of parasites correlated well. Furthermore, genotyping of surviving and moribund parasites from six bioassay experiments demonstrated a highly significant negative correlation between the frequency of resistance alleles and the probability of dying when exposed to azamethiphos in a bioassay. Based on these observations, we could strongly conclude that the Phe362Tyr mutation is a major factor responsible for OP resistance in salmon louse on Norwegian fish farms. [ABSTRACT FROM AUTHOR]

The article explores the waveforms of seismic signals at the front of Kronebreen, Svalbard, Norway to determine the glacier-related seismic events and examine their relation to calving process. It employs a scheme which combines established seismic event detection utilizing a sensitive trigger algorithm. It reveals that the temporal distribution of glacier-related events demonstrates an increase in event rate during autumn, specifically for the category that is associated with iceberg calving.

We describe the development and implementation of a method for extracting altimetric information using the Passive Reflectometry and Interferometry System (PARIS), i.e., from GPS signals after their reflection off the sea surface. We have formalized one idea laid out in the description of a bistatic system for ocean altimetry using the GPS signal, by Hajj and Zuffada (Jet Propulsion Laboratory), and have extended it to real situations encountered in PARIS aircraft experiments. Second, we have developed the corresponding algorithms to produce real-time altimetric observables to be used in dedicated digital signal processors. Finally, we have applied this method to estimate sea-surface height from one flight experiment in the North Sea off the coast of Norway. [ABSTRACT FROM AUTHOR]