Shared decision making development in Switzerland: room for improvement!

In Switzerland there is a strong movement at a national policy level towards strengthening patient rights and patient involvement in health care decisions. Yet, there is no national programme promoting shared decision making. First decision support tools (prenatal diagnosis and screening) for the counselling process have been developed and implemented. Although Swiss doctors acknowledge that shared decision making is important, hierarchical structures and asymmetric physician-patient relationships are still prevailing. The last years have seen some promising activities regarding the training of medical students and the development of patient support programmes. Swiss direct democracy and the habit of consensual decision making and citizen involvement in general may provide a fertile ground for SDM development in the primary care setting.

Development and Demonstration of a Freezing Drizzle Algorithm for Roadway Environmental Sensing Systems, Final Report, October 2012

The primary goal of this project is to demonstrate the accuracy and utility of a freezing drizzle algorithm that can be implemented on roadway environmental sensing systems (ESSs). The types of problems related to the occurrence of freezing precipitation range from simple traffic delays to major accidents that involve fatalities. Freezing drizzle can also lead to economic impacts in communities with lost work hours, vehicular damage, and downed power lines. There are means for transportation agencies to perform preventive and reactive treatments to roadways, but freezing drizzle can be difficult to forecast accurately or even detect as weather radar and surface observation networks poorly observe these conditions. The detection of freezing precipitation is problematic and requires special instrumentation and analysis. The Federal Aviation Administration (FAA) development of aircraft anti-icing and deicing technologies has led to the development of a freezing drizzle algorithm that utilizes air temperature data and a specialized sensor capable of detecting ice accretion. However, at present, roadway ESSs are not capable of reporting freezing drizzle. This study investigates the use of the methods developed for the FAA and the National Weather Service (NWS) within a roadway environment to detect the occurrence of freezing drizzle using a combination of icing detection equipment and available ESS sensors. The work performed in this study incorporated the algorithm developed initially and further modified for work with the FAA for aircraft icing. The freezing drizzle algorithm developed for the FAA was applied using data from standard roadway ESSs. The work performed in this study lays the foundation for addressing the central question of interest to winter maintenance professionals as to whether it is possible to use roadside freezing precipitation detection (e.g., icing detection) sensors to determine the occurrence of pavement icing during freezing precipitation events and the rates at which this occurs.

The InterActive Choice Aid: A new approach to supporting online consumer decision making

Interactive Choice Aid (ICA) is a decision aid, introduced in this paper, that systematically assists consumers with online purchase decisions. ICA integrates aspects from prescriptive decision theory, insights from descriptive decision research, and practical considerations; thereby combining pre-existing best practices with novel features. Instead of imposing an objectively ideal but unnatural decision procedure on the user, ICA assists the natural process of human decision-making by providing explicit support for the execution of the user's decision strategies. The application contains an innovative feature for in-depth comparisons of alternatives through which users' importance ratings are elicited interactively and in a playful way. The usability and general acceptance of the choice aid was studied; results show that ICA is a promising contribution and provides insights that may further improve its usability.

Toxic substances in blood: an analysis of current recommendations under a Bayesian (decision) approach

This article extends existing discussion in literature on probabilistic inference and decision making with respect to continuous hypotheses that are prevalent in forensic toxicology. As a main aim, this research investigates the properties of a widely followed approach for quantifying the level of toxic substances in blood samples, and to compare this procedure with a Bayesian probabilistic approach. As an example, attention is confined to the presence of toxic substances, such as THC, in blood from car drivers. In this context, the interpretation of results from laboratory analyses needs to take into account legal requirements for establishing the 'presence' of target substances in blood. In a first part, the performance of the proposed Bayesian model for the estimation of an unknown parameter (here, the amount of a toxic substance) is illustrated and compared with the currently used method. The model is then used in a second part to approach-in a rational way-the decision component of the problem, that is judicial questions of the kind 'Is the quantity of THC measured in the blood over the legal threshold of 1.5 μg/l?'. This is pointed out through a practical example.

Altered decision-making in multiple sclerosis: a sign of impaired emotional reactivity?

We assessed decision-making capacity and emotional reactivity in 20 patients with multiple sclerosis (MS) and in 16 healthy subjects using the Gambling Task (GT), a model of real-life decision making, and the skin conductance response (SCR). Demographic, neurological, affective, and cognitive parameters were analyzed in MS patients for their effect on decision-making performance. MS patients persisted longer (slope, -3.6%) than the comparison group (slope, -6.4%) in making disadvantageous choices as the GT progressed (p < 0.001), suggesting significant slower learning in MS. Patients with higher Expanded Disability Status Scale scores (EDSS >2.0) showed a different pattern of impairment in the learning process compared with patients with lower functional impairment (EDSS </=2.0). This slower learning was associated with impaired emotional reactivity (anticipatory SCR 3.9 vs 6.1 microSiemens [microS] for patients vs the comparison group, p < 0.0001; post-choice SCR 3.9 vs 6.2 microS, p < 0.0001), but not with executive dysfunction. Impaired emotional dimensions of behavior (assessed using the Dysexecutive Questionnaire, p < 0.002) also correlated with slower learning. Given the considerable consequences that impaired decision making can have on daily life, we suggest that this factor may contribute to handicap and altered quality of life secondary to MS and is dependent on emotional experience. Ann Neurol 2004.

Decision criteria for optimizing postemergence johnsongrass control in soybean crops in Argentina

Field studies were established in Zavalla and Oliveros, Argentina, during four years in order to optimize Johnsongrass (Sorghum halepense (L.) Pers.) chemical control by means of the thermal calendar model in comparison with other criteria (weed height or days after sowing). The effect of three application dates of postemergence herbicides was determined by visual control, density of tillers originated from rhizome bud regrowth, and from crown and shoot bud regrowth, and soybean yield. Following the thermal calendar model criterion, applications during the second date afforded the best control. Weed height for the first date showed little variability between experiments but was highly variable in the second and third application dates, achieving in some cases values greater than 120 cm. For all years, no significant differences were detected for crop yield between the first and second application dates, and yields were always lower for the third date. The greatest rhizome bud regrowth was observed for the earliest application date and the highest crown and shoot bud regrowth was determined for the last application date. Parameters associated with control efficiency showed the best behaviour for the second date. However, plant height at this moment may interfere with herbicide application and the variability exhibited by this parameter highlights the risk of determining control timing using only one decision criterion.

A program of nurse algorithm-guided care for adult patients with acute minor illnesses in primary care

Background: Attention to patients with acute minor-illnesses requesting same-day consultation represents a major burden in primary care. The workload is assumed by general practitioners in many countries. A number of reports suggest that care to these patients may be provided, at in least in part, by nurses. However, there is scarce information with respect to the applicability of a program of nurse management for adult patients with acute minor-illnesses in large areas. The aim of this study is to assess the effectiveness of a program of nurse algorithm-guided care for adult patients with acute minor illnesses requesting same-day consultation in primary care in a largely populated area. Methods: A cross-sectional study of all adult patients seeking same day consultation for 16 common acute minor illnesses in a large geographical area with 284 primary care practices. Patients were included in a program of nurse case management using management algorithms. The main outcome measure was case resolution, defined as completion of the algorithm by the nurse without need of referral of the patient to the general practitioner. The secondary outcome measure was return to consultation, defined as requirement of new consultation for the same reason as the first one, in primary care within a 7-day period. Results: During a two year period (April 2009-April 2011), a total of 1,209,669 consultations were performed in the program. Case resolution was achieved by nurses in 62.5% of consultations. The remaining cases were referred to a general practitioner. Resolution rates ranged from 94.2% in patients with burns to 42% in patients with upper respiratory symptoms. None of the 16 minor illnesses had a resolution rate below 40%. Return to consultation during a 7-day period was low, only 4.6%. Conclusions: A program of algorithms-guided care is effective for nurse case management of patients requesting same day consultation for minor illnesses in primary care.