Interventions to improve the appropriate use of polypharmacy for older people

Background
Inappropriate polypharmacy is a particular concern in older people and is associated with negative health outcomes. Choosing the best interventions to improve appropriate polypharmacy is a priority, hence interest in appropriate polypharmacy, where many medicines may be used to achieve better clinical outcomes for patients, is growing.

Objectives
This review sought to determine which interventions, alone or in combination, are effective in improving the appropriate use of polypharmacy and reducing medication-related problems in older people.

Search methods
In November 2013, for this first update, a range of literature databases including MEDLINE and EMBASE were searched, and handsearching of reference lists was performed. Search terms included 'polypharmacy', 'medication appropriateness' and 'inappropriate prescribing'.

Selection criteria
A range of study designs were eligible. Eligible studies described interventions affecting prescribing aimed at improving appropriate polypharmacy in people 65 years of age and older in which a validated measure of appropriateness was used (e.g. Beers criteria, Medication Appropriateness Index (MAI)).

Data collection and analysis
Two review authors independently reviewed abstracts of eligible studies, extracted data and assessed risk of bias of included studies. Study-specific estimates were pooled, and a random-effects model was used to yield summary estimates of effect and 95% confidence intervals (CIs). The GRADE (Grades of Recommendation, Assessment, Development and Evaluation) approach was used to assess the overall quality of evidence for each pooled outcome.

Main results
Two studies were added to this review to bring the total number of included studies to 12. One intervention consisted of computerised decision support; 11 complex, multi-faceted pharmaceutical approaches to interventions were provided in a variety of settings. Interventions were delivered by healthcare professionals, such as prescribers and pharmacists. Appropriateness of prescribing was measured using validated tools, including the MAI score post intervention (eight studies), Beers criteria (four studies), STOPP criteria (two studies) and START criteria (one study). Interventions included in this review resulted in a reduction in inappropriate medication usage. Based on the GRADE approach, the overall quality of evidence for all pooled outcomes ranged from very low to low. A greater reduction in MAI scores between baseline and follow-up was seen in the intervention group when compared with the control group (four studies; mean difference -6.78, 95% CI -12.34 to -1.22). Postintervention pooled data showed a lower summated MAI score (five studies; mean difference -3.88, 95% CI -5.40 to -2.35) and fewer Beers drugs per participant (two studies; mean difference -0.1, 95% CI -0.28 to 0.09) in the intervention group compared with the control group. Evidence of the effects of interventions on hospital admissions (five studies) and of medication-related problems (six studies) was conflicting.

Authors' conclusions
It is unclear whether interventions to improve appropriate polypharmacy, such as pharmaceutical care, resulted in clinically significant improvement; however, they appear beneficial in terms of reducing inappropriate prescribing.

Strasheela: Design and usage of a music composition environment based on the Oz programming model

Strasheela provides a means for the composer to create a symbolic score by formally describing it in a rule-based way. The environment defines a rich music representation for complex polyphonic scores. Strasheela enables the user to define expressive compositional rules and then to apply them to the score. Compositional rules can restrict many aspects of the music - including the rhythmic structure, the melodic structure and the harmonic structure - by constraining the parameters (e.g. duration or pitch) of musical events according to some numerical or logical relation. Strasheela combines this expressivity with efficient search strategies.

Beta-blocker usage after malignant melanoma diagnosis and survival: a population-based nested case-control study

Background: Beta-blockers have potential antiangiogenic and antimigratory activity. Studies have demonstrated a survival benefit in patients with malignant melanoma treated with beta-blockers.

Objectives: To investigate the association between postdiagnostic beta-blocker usage and risk of melanoma-specific mortality in a population-based cohort of patients with malignant melanoma.

Methods: Patients with incident malignant melanoma diagnosed between 1998 and 2010 were identified within the U.K. Clinical Practice Research Datalink and confirmed using cancer registry data. Patients with malignant melanoma with a melanoma-specific death (cases) recorded by the Office of National Statistics were matched on year of diagnosis, age and sex to four malignant melanoma controls (who lived at least as long after diagnosis as their matched case). A nested case–control approach was used to investigate the association between postdiagnostic beta-blocker usage and melanoma-specific death and all-cause mortality. Conditional logistic regression was applied to generate odds ratios (ORs) and 95% confidence intervals (CIs) for beta-blocker use determined from general practitioner prescribing.

Results: Beta-blocker medications were prescribed after malignant melanoma diagnosis to 20·2% of 242 patients who died from malignant melanoma (cases) and 20·3% of 886 matched controls. Consequently, there was no association between beta-blocker use postdiagnosis and cancer-specific death (OR 0·99, 95% CI 0·68–1·42), which did not markedly alter after adjustment for confounders including stage (OR 0·87, 95% CI 0·56–1·34). No significant associations were detected for individual beta-blocker types, by defined daily doses of use or for all-cause mortality.

Conclusions: Contrary to some previous studies, beta-blocker use after malignant melanoma diagnosis was not associated with reduced risk of death from melanoma in this U.K. population-based study.

Wireless networked control systems with QoS-based sampling

Closing feedback loops using an IEEE 802.11b ad hoc wireless communication network incurs many challenges sensitivity to varying channel conditions and lower physical transmission rates tend to limit the bandwidth of the communication channel. Given that the bandwidth usage and control performance are linked, a method of adapting the sampling interval based on an 'a priori', static sampling policy has been proposed and, more significantly, assuring stability in the mean square sense using discrete-time Markov jump linear system theory. Practical issues including current limitations of the 802.11 b protocol, the sampling policy and stability are highlighted. Simulation results on a cart-mounted inverted pendulum show that closed-loop stability can be improved using sample rate adaptation and that the control design criteria can be met in the presence of channel errors and severe channel contention.

Systematic Usage of Embedded Modelling Languages in Automated Model Transformation Chains

Annotation of programs using embedded Domain-Specific Languages (embedded DSLs), such as the program annotation facility for the Java programming language, is a well-known practice in computer science. In this paper we argue for and propose a specialized approach for the usage of embedded Domain-Specific Modelling Languages (embedded DSMLs) in Model-Driven Engineering (MDE) processes that in particular supports automated many-step model transformation chains. It can happen that information defined at some point, using an embedded DSML, is not required in the next immediate transformation step, but in a later one. We propose a new approach of model annotation enabling flexible many-step transformation chains. The approach utilizes a combination of embedded DSMLs, trace models and a megamodel. We demonstrate our approach based on an example MDE process and an industrial case study.

RFID based Efficient Lighting Control

The Kyoto Protocol and the European Energy Performance of Buildings Directive put an onus on governments
and organisations to lower carbon footprint in order to contribute towards reducing global warming. A key
parameter to be considered in buildings towards energy and cost savings is its indoor lighting that has a major
impact on overall energy usage and Carbon Dioxide emissions. Lighting control in buildings using Passive
Infrared sensors is a reliable and well established approach; however, the use of only Passive Infrared does not
offer much savings towards reducing carbon, energy, and cost. Accurate occupancy monitoring information can
greatly affect a building’s lighting control strategy towards a greener usage. This paper presents an approach for
data fusion of Passive Infrared sensors and passive Radio Frequency Identification (RFID) based occupancy
monitoring. The idea is to have efficient, need-based, and reliable control of lighting towards a green indoor
environment, all while considering visual comfort of occupants. The proposed approach provides an estimated
13% electrical energy savings in one open-plan office of a University building in one working day. Practical
implementation of RFID gateways provide real-world occupancy profiling data to be fused with Passive
Infrared sensing towards analysis and improvement of building lighting usage and control.

Hospital antibiotic use and its relationship to age-adjusted comorbidity and alcohol-based hand rub consumption

SUMMARY The objective of this study was to evaluate the effect of age-adjusted comorbidity and alcohol-based hand rub on monthly hospital antibiotic usage, retrospectively. A multivariate autoregressive integrated moving average (ARIMA) model was built to relate the monthly use of all antibiotics grouped together with age-adjusted comorbidity and alcohol-based hand rub over a 5-year period (April 2005-March 2010). The results showed that monthly antibiotic use was positively related to the age-adjusted comorbidity index (concomitant effect, coefficient 1·103, P = 0·0002), and negatively related to the use of alcohol-based hand rub (2-month delay, coefficient -0·069, P = 0·0533). Alcohol-based hand rub is considered a modifiable factor and as such can be identified as a target for quality improvement programmes. Time-series analysis may provide a suitable methodology for identifying possible predictive variables that explain antibiotic use in healthcare settings. Future research should examine the relationship between infection control practices and antibiotic use, identify other infection control predictive factors for hospital antibiotic use, and evaluate the impact of enhancing different infection control practices on antibiotic use in a healthcare setting.

Beta-blocker usage and breast cancer survival: a nested case-control study within a UK clinical practice research datalink cohort.

Background: To investigate the association between post-diagnostic beta-blocker usage and risk of cancer-specific mortality in a large population-based cohort of female breast cancer patients.

Methods: A nested case-control study was conducted within a cohort of breast cancer patients identified from cancer registries in England(using the National Cancer Data repository) and diagnosed between 1998 and 2007. Patients who had a breast cancer-specific death(ascertained from Office of National Statistics death registration data) were each matched to four alive controls by year and age at diagnosis. Prescription data for these patients were available through the Clinical Practice Research Datalink. Conditional logistic regression models were used to investigate the association between breast cancer-specific death and beta-blocker usage.

Results: Post-diagnostic use of beta-blockers was identified in 18.9% of 1435 breast cancer-specific deaths and 19.4% of their 5697 matched controls,indicating little evidence of association between beta-blocker use and breast cancer-specific mortality [odds ratio (OR) = 0.97,95% confidence interval (CI) 0.83, 1.13]. There was also little evidence of an association when analyses were restricted to cardio non-selective beta-blockers (OR = 0.90, 95% CI 0.69, 1.17). Similar results were observed in analyses of drug dosage frequency and duration, and beta-blocker type.

Conclusions: In this large UK population-based cohort of breast cancer patients,there was little evidence of an association between post-diagnostic beta-blocker usage and breast cancer progression. Further studies which include information on tumour receptor status are warranted to determine whether response to beta-blockers varies by tumour subtypes.

Network Usage Determination for Transmission Cost Allocation using a Transformer Analogy

This study presents a new method for determining the transmission network usage by loads and generators, which can then be used for transmission cost/loss allocation in an explainable and justifiable manner. The proposed method is based on solid physical grounds and circuit theory. It relies on dividing the currents through the network into two components; the first one is attributed to power flows from generators to loads, whereas the second one is because of the generators only. Unlike almost all the available methods, the proposed method is assumption free and hence it is more accurate than similar methods even those having some physical basis. The proposed method is validated through a transformer analogy, and theoretical derivations. The method is verified through application to the IEEE 30 bus system and the IEEE 118 test system. The results obtained verified many desirable features of the proposed method. Being more accurate in determining the network usage, in an explainable transparent manner, and in giving accurate cost signals, indicating the best locations to add loads and generation, are among the many desirable features.

A predictive maintenance system for integral type faults based on support vector machines:An application to ion implantation

In semiconductor fabrication processes, effective management of maintenance operations is fundamental to decrease costs associated with failures and downtime. Predictive Maintenance (PdM) approaches, based on statistical methods and historical data, are becoming popular for their predictive capabilities and low (potentially zero) added costs. We present here a PdM module based on Support Vector Machines for prediction of integral type faults, that is, the kind of failures that happen due to machine usage and stress of equipment parts. The proposed module may also be employed as a health factor indicator. The module has been applied to a frequent maintenance problem in semiconductor manufacturing industry, namely the breaking of the filament in the ion-source of ion-implantation tools. The PdM has been tested on a real production dataset. © 2013 IEEE.

β-Blocker usage and colorectal cancer mortality:a nested case-control study in the UK Clinical Practice Research Datalink cohort

BACKGROUND: Epidemiological and laboratory studies suggest that β-blockers may reduce cancer progression in various cancer sites. The aim of this study was to conduct the first epidemiological investigation of the effect of post-diagnostic β-blocker usage on colorectal cancer-specific mortality in a large population-based colorectal cancer patient cohort.

PATIENTS AND METHODS: A nested case-control analysis was conducted within a cohort of 4794 colorectal cancer patients diagnosed between 1998 and 2007. Patients were identified from the UK Clinical Practice Research Datalink and confirmed using cancer registry data. Patients with a colorectal cancer- specific death (data from the Office of National Statistics death registration system) were matched to five controls. Conditional logistic regression was applied to calculate odds ratios (OR) and 95% confidence intervals (95% CIs) according to β-blocker usage (data from GP-prescribing records).

RESULTS: Post-diagnostic β-blocker use was identified in 21.4% of 1559 colorectal cancer-specific deaths and 23.7% of their 7531 matched controls, with little evidence of an association (OR = 0.89 95% CI 0.78-1.02). Similar associations were found when analysing drug frequency, β-blocker type or specific drugs such as propranolol. There was some evidence of a weak reduction in all-cause mortality in β-blocker users (adjusted OR = 0.88; 95% CI 0.77-1.00; P = 0.04) which was in part due to the marked effect of atenolol on cardiovascular mortality (adjusted OR = 0.62; 95% CI 0.40-0.97; P = 0.04).

CONCLUSIONS: In this novel, large UK population-based cohort of colorectal cancer patients, there was no evidence of an association between post-diagnostic β-blocker use and colorectal cancer-specific mortality.

CLINICAL TRIALS NUMBER: NCT00888797.

Low-dose aspirin and survival from lung cancer: a population-based cohort study

Background
Preclinical evidence suggests that aspirin may inhibit lung cancer progression. In a large cohort of lung cancer patients, we investigated whether low-dose aspirin use was associated with a reduction in the risk of lung cancer-specific mortality.

Methods
We identified lung cancer patients from English cancer registries diagnosed between 1998 to 2009 from the National Cancer Data Repository. Medication usage was obtained from linkages to the UK Clinical Practice Research Datalink and lung cancer-specific deaths were identified from Office of National Statistics mortality data. Hazard ratios (HR) and 95 % confidence intervals (CI) for the association between low-dose aspirin use (before and after diagnosis) and risk of lung cancer-specific mortality were calculated using Cox regression models.

Results
A total of 14,735 lung cancer patients were identified during the study period. In analysis of 3,635 lung cancer patients, there was no suggestion of an association between low-dose aspirin use after diagnosis and cancer-specific mortality (adjusted HR = 0.96, 95 % CI: 0.85, 1.09). Similarly, no association was evident for low-dose aspirin use before diagnosis and cancer-specific mortality (adjusted HR = 1.00, 95 % CI: 0.95, 1.05). Associations were comparable by duration of use and for all-cause mortality.

Conclusion
Overall, we found little evidence of a protective association between low-dose aspirin use and cancer-specific mortality in a large population-based lung cancer cohort.

Making Social Work Education App’ier : The Process of Developing Information-based Apps for Social Work Education and Practice

Mobile App technology in social work education remains in the embryonic stages of development with a few notable exceptions. The use of Apps in College and University settings has been reported in other sectors of higher education, although there is a paucity of research in relation to its relevance to social work education and practice. The following article describes the creation of four social work education and practice Apps by a team of social work educators. The primary focus is on the design process and the partnership approach to the creation of the tools. It also outlines the rationale for the App development, the working process and the theoretical framework underpinning mobile learning. Furthermore, it provides information on the level of usage of the Apps according to geographical location, download information and time spent on each section of the App. The article also incorporates a pragmatic summary of developmental guidelines which may aid social work educators in the development and implementation of specialist information-based Apps for education and practice.

An HMM-based spectrum occupancy predictor for energy efficient cognitive radio

Spectrum sensing is the cornerstone of cognitive radio technology and refers to the process of obtaining awareness of the radio spectrum usage in order to detect the presence of other users. Spectrum sensing algorithms consume considerable energy and time. Prediction methods for inferring the channel occupancy of future time instants have been proposed as a means of improving performance in terms of energy and time consumption. This paper studies the performance of a hidden Markov model (HMM) spectrum occupancy predictor as well as the improvement in sensing energy and time consumption based on real occupancy data obtained in the 2.4GHz ISM band. Experimental results show that the HMM-based occupancy predictor outperforms a kth order Markov and a 1-nearest neighbour (1NN) predictor. Our study also suggests that by employing such a predictive scheme in spectrum sensing, an improvement of up to 66% can be achieved in the required sensing energy and time.