Satisfaction survey for a medication management program : satisfaction guaranteed?

BACKGROUND Providing clinical pharmacy services to patients in their homes after discharge from hospital has been reported to reduce health care costs and improve outcomes. The Medication Management Program of the Fraser Health Authority involves pharmacists making home visits to provide clinical pharmacy services to elderly patients who have recently been discharged from hospital and others considered to be at high risk for adverse drug events. Although clinical and economic outcomes of this program have been evaluated, humanistic outcomes such as satisfaction have not been assessed. Moreover, very little evaluation of patient satisfaction with home pharmacy services has been reported in the literature. OBJECTIVE To evaluate patient satisfaction with the Medication Management Program. METHODS A telephone survey instrument, consisting of 7 Likert-scale items and 2 open-ended questions, was developed and administered to patients who received a home pharmacist visit between September 1 and November 23, 2011. In addition to the survey responses, demographic and clinical data for both respondents and nonrespondents were collected. RESULTS Of the 175 patients invited to participate in the survey, 103 (58.9%) agreed to participate. The majority of respondents agreed or strongly agreed with all of the survey items, indicating satisfaction with the program. For example, 97 (94%) agreed or strongly agreed that they would recommend the pharmacist home visit program continue to be available, and all 103 (100%) agreed or strongly agreed that they were satisfied with the pharmacist home visit. Respondents provided some suggestions for program improvement. CONCLUSIONS The survey findings demonstrate that patients were satisfied with the home clinical pharmacy services offered through the Fraser Health Medication Management Program.

Selective combination of visual and thermal imaging for resilient localization in adverse conditions : day and night, smoke and fire

Long-term autonomy in robotics requires perception systems that are resilient to unusual but realistic conditions that will eventually occur during extended missions. For example, unmanned ground vehicles (UGVs) need to be capable of operating safely in adverse and low-visibility conditions, such as at night or in the presence of smoke. The key to a resilient UGV perception system lies in the use of multiple sensor modalities, e.g., operating at different frequencies of the electromagnetic spectrum, to compensate for the limitations of a single sensor type. In this paper, visual and infrared imaging are combined in a Visual-SLAM algorithm to achieve localization. We propose to evaluate the quality of data provided by each sensor modality prior to data combination. This evaluation is used to discard low-quality data, i.e., data most likely to induce large localization errors. In this way, perceptual failures are anticipated and mitigated. An extensive experimental evaluation is conducted on data sets collected with a UGV in a range of environments and adverse conditions, including the presence of smoke (obstructing the visual camera), fire, extreme heat (saturating the infrared camera), low-light conditions (dusk), and at night with sudden variations of artificial light. A total of 240 trajectory estimates are obtained using five different variations of data sources and data combination strategies in the localization method. In particular, the proposed approach for selective data combination is compared to methods using a single sensor type or combining both modalities without preselection. We show that the proposed framework allows for camera-based localization resilient to a large range of low-visibility conditions.

Error modeling and calibration of exteroceptive sensors for accurate mapping applications

Reliable robotic perception and planning are critical to performing autonomous actions in uncertain, unstructured environments. In field robotic systems, automation is achieved by interpreting exteroceptive sensor information to infer something about the world. This is then mapped to provide a consistent spatial context, so that actions can be planned around the predicted future interaction of the robot and the world. The whole system is as reliable as the weakest link in this chain. In this paper, the term mapping is used broadly to describe the transformation of range-based exteroceptive sensor data (such as LIDAR or stereo vision) to a fixed navigation frame, so that it can be used to form an internal representation of the environment. The coordinate transformation from the sensor frame to the navigation frame is analyzed to produce a spatial error model that captures the dominant geometric and temporal sources of mapping error. This allows the mapping accuracy to be calculated at run time. A generic extrinsic calibration method for exteroceptive range-based sensors is then presented to determine the sensor location and orientation. This allows systematic errors in individual sensors to be minimized, and when multiple sensors are used, it minimizes the systematic contradiction between them to enable reliable multisensor data fusion. The mathematical derivations at the core of this model are not particularly novel or complicated, but the rigorous analysis and application to field robotics seems to be largely absent from the literature to date. The techniques in this paper are simple to implement, and they offer a significant improvement to the accuracy, precision, and integrity of mapped information. Consequently, they should be employed whenever maps are formed from range-based exteroceptive sensor data. © 2009 Wiley Periodicals, Inc.

Contact lens prescribing in Canada 2011

For the past 12 years, the International Contact Lens Prescribing Survey Consortium has sent surveys to a selection of Canadian optometrists in order to collect information on the contact lenses they fit and basic demographic data of the patients. Canada is one of about 40 countries that contributes to the global study and while annual reviews of the study data are presented, information published for any one market is limited due to the size of the dataset.1 This manuscript presents a more detailed analysis on the Canadian market for 2011.

Bonding and bridging : transition to school and social capital formation among a community of Indigenous Australian children

This study reports on an intervention program designed to facilitate transition to school of a whole community of Indigenous Australian children who had previously not been attending. The children were from families displaced from their traditional lands and experienced on-going social marginalisation and transience. A social capital framework was employed to track change in the children’s social inclusion and family-school engagement for two years, from school entry. Sociometric measurement and interview techniques were applied to assess the children’s social connectedness and peer relationship quality. Using these data, analyses examined whether bonding within the group supported or inhibited formation of new social relationships. Although transience disrupted attendance, there was a group trend towards increased social inclusion with some evidence that group bonds supported bridging to new social relationships. Change in family-school engagement was tracked using multi-informant interviews. Limited engagement between school and families presented an on-going challenge to sustained educational engagement.

Crime, justice, and inequality : Oh Canada, where art thou?

Since Canada’s colonial beginnings, it has become increasingly riddled with classism, racism,sexism, and other damaging outcomes of structured social inequality. In 2006, however,many types of social injustice were turbo‐charged under the federal leadership of the Harper government. For example, a recent southern Ontario study shows that less than half of working people between the ages of 25 and 65 have full‐time jobs with benefits. The main objective of this paper is to critique the dominant Canadian political economic order and the pain and suffering it has caused for millions of people. Informed by left realism and other progressive ways of knowing, I also suggest some ways of turning the tide.

Reasons for non-urgent presentations to the emergency department in Saudi Arabia

Background The majority of patients who attend emergency departments (EDs) in Saudi Arabia have non-urgent problems, resulting in overcrowding, excessive waiting times and delayed care for more acutely ill patients. The purpose of this research was to examine the reasons for non-urgent visits to a Saudi ED and factors associated with patient perceptions of urgency. Methods We administered a survey to 350 consecutively presenting Canadian Triage and Acuity Scale (CTAS) IV or V adult patients at a large tertiary ED in Riyadh region, Saudi Arabia, during 25 days of data collection in March 2013. Results Over half of the sample usually visited the ED to access healthcare. The most common reasons for attending the ED were not having a regular healthcare provider (63%), being able to receive care on the same day (62%), and the convenience of and access to medical care 24/7 (62%). Approximately two-thirds of CTAS V patients and one-third of CTAS IV patients believed their condition was more urgent than their triage nurse rating. Conclusion Multiple factors influence non-urgent visits to the ED in the Saudi context including insufficient community awareness of the role of the ED and perceived lack of access to primary healthcare services.

Autonomous multisensor calibration and closed-loop fusion for SLAM

The vast majority of current robot mapping and navigation systems require specific well-characterized sensors that may require human-supervised calibration and are applicable only in one type of environment. Furthermore, if a sensor degrades in performance, either through damage to itself or changes in environmental conditions, the effect on the mapping system is usually catastrophic. In contrast, the natural world presents robust, reasonably well-characterized solutions to these problems. Using simple movement behaviors and neural learning mechanisms, rats calibrate their sensors for mapping and navigation in an incredibly diverse range of environments and then go on to adapt to sensor damage and changes in the environment over the course of their lifetimes. In this paper, we introduce similar movement-based autonomous calibration techniques that calibrate place recognition and self-motion processes as well as methods for online multisensor weighting and fusion. We present calibration and mapping results from multiple robot platforms and multisensory configurations in an office building, university campus, and forest. With moderate assumptions and almost no prior knowledge of the robot, sensor suite, or environment, the methods enable the bio-inspired RatSLAM system to generate topologically correct maps in the majority of experiments.