Factors influencing business intelligence and analytics usage extent in South African organisations

Through extensive use of business intelligence and analytics, organisations are better positioned to support fact-based decision making, ultimately leading to improved organisational performance. However, while some organisations recognise and exploit the benefits of business intelligence and analytics use, others fail to capitalise on its potential. It is pertinent therefore to examine factors influencing Business Intelligence and Analytics use within organisations. The three contexts of the Technology-Organisation-Environment (TOE) framework was used as the foundational framework. It is hoped that the findings presented will contribute to a greater understanding of factors influencing business intelligence and analytics usage extent to researchers and practitioners alike. Organisations seeking to promote fact-based decision making through greater business intelligence and analytics use will apply and be better equipped to drive such endeavours

Unnecessary use of fluoroquinolone antibiotics in hospitalized patients

<p>Abstract</p> <p>Background</p> <p>Fluoroquinolones are among the most commonly prescribed antimicrobials and are an important risk factor for colonization and infection with fluoroquinolone-resistant gram-negative bacilli and for <it>Clostridium difficile </it>infection (CDI). In this study, our aim was to determine current patterns of inappropriate fluoroquinolone prescribing among hospitalized patients, and to test the hypothesis that longer than necessary treatment durations account for a significant proportion of unnecessary fluoroquinolone use.</p> <p>Methods</p> <p>We conducted a 6-week prospective, observational study to determine the frequency of, reasons for, and adverse effects associated with unnecessary fluoroquinolone use in a tertiary-care academic medical center. For randomly-selected adult inpatients receiving fluoroquinolones, therapy was determined to be necessary or unnecessary based on published guidelines or standard principles of infectious diseases. Adverse effects were determined based on chart review 6 weeks after completion of therapy.</p> <p>Results</p> <p>Of 1,773 days of fluoroquinolone therapy, 690 (39%) were deemed unnecessary. The most common reasons for unnecessary therapy included administration of antimicrobials for non-infectious or non-bacterial syndromes (292 days-of-therapy) and administration of antimicrobials for longer than necessary durations (234 days-of-therapy). The most common syndrome associated with unnecessary therapy was urinary tract infection or asymptomatic bacteriuria (30% of all unnecessary days-of-therapy). Twenty-seven percent (60/227) of regimens were associated with adverse effects possibly attributable to therapy, including gastrointestinal adverse effects (14% of regimens), colonization by resistant pathogens (8% of regimens), and CDI (4% of regimens).</p> <p>Conclusions</p> <p>In our institution, 39% of all days of fluoroquinolone therapy were unnecessary. Interventions that focus on improving adherence with current guidelines for duration of antimicrobial therapy and for management of urinary syndromes could significantly reduce overuse of fluoroquinolones.</p

Structural Analysis to Determine the Core of Hypoxia Response Network

The advent of sophisticated molecular biology techniques allows to deduce the structure of complex biological networks. However, networks tend to be huge and impose computational challenges on traditional mathematical analysis due to their high dimension and lack of reliable kinetic data. To overcome this problem, complex biological networks are decomposed into modules that are assumed to capture essential aspects of the full network's dynamics. The question that begs for an answer is how to identify the core that is representative of a network's dynamics, its function and robustness. One of the powerful methods to probe into the structure of a network is Petri net analysis. Petri nets support network visualization and execution. They are also equipped with sound mathematical and formal reasoning based on which a network can be decomposed into modules. The structural analysis provides insight into the robustness and facilitates the identification of fragile nodes. The application of these techniques to a previously proposed hypoxia control network reveals three functional modules responsible for degrading the hypoxia-inducible factor (HIF). Interestingly, the structural analysis identifies superfluous network parts and suggests that the reversibility of the reactions are not important for the essential functionality. The core network is determined to be the union of the three reduced individual modules. The structural analysis results are confirmed by numerical integration of the differential equations induced by the individual modules as well as their composition. The structural analysis leads also to a coarse network structure highlighting the structural principles inherent in the three functional modules. Importantly, our analysis identifies the fragile node in this robust network without which the switch-like behavior is shown to be completely absent

Third generation cephalosporin use in a tertiary hospital in Port of Spain, Trinidad: need for an antibiotic policy

BACKGROUND: Tertiary care hospitals are a potential source for development and spread of bacterial resistance being in the loop to receive outpatients and referrals from community nursing homes and hospitals. The liberal use of third-generation cephalosporins (3GCs) in these hospitals has been associated with the emergence of extended-spectrum beta- lactamases (ESBLs) presenting concerns for bacterial resistance in therapeutics. We studied the 3GC utilization in a tertiary care teaching hospital, in warded patients (medical, surgical, gynaecology, orthopedic) prescribed these drugs. METHODS: Clinical data of patients (≥ 13 years) admitted to the General Hospital, Port of Spain (POSGH) from January to June 2000, and who had received 3GCs based on the Pharmacy records were studied. The Sanford Antibiotic Guide 2000, was used to determine appropriateness of therapy. The agency which procures drugs for the Ministry of Health supplied the cost of drugs. RESULTS: The prevalence rate of use of 3GCs was 9.5 per 1000 admissions and was higher in surgical and gynecological admissions (21/1000) compared with medical and orthopedic (8 /1000) services (p < 0.05). Ceftriaxone was the most frequently used 3GC. Sixty-nine (36%) patients without clinical evidence of infection received 3Gcs and prescribing was based on therapeutic recommendations in 4% of patients. At least 62% of all prescriptions were inappropriate with significant associations for patients from gynaecology (p < 0.003), empirical prescribing (p < 0.48), patients with undetermined infection sites (p < 0.007), and for single drug use compared with multiple antibiotics (p < 0.001). Treatment was twice as costly when prescribing was inappropriate CONCLUSIONS: There is extensive inappropriate 3GC utilization in tertiary care in Trinidad. We recommend hospital laboratories undertake continuous surveillance of antibiotic resistance patterns so that appropriate changes in prescribing guidelines can be developed and implemented. Though guidelines for rational antibiotic use were developed they have not been re-visited or encouraged, suggesting urgent antibiotic review of the hospital formulary and instituting an infection control team. Monitoring antibiotic use with microbiology laboratory support can promote rational drug utilization, cut costs, halt inappropriate 3GC prescribing, and delay the emergence of resistant organisms. An ongoing antibiotic peer audit is suggested

Antimicrobial management and appropriateness of treatment of urinary tract infection in general practice in Ireland

<p>Abstract</p> <p>Background</p> <p>Urinary tract infections (UTIs) are the second most common bacterial infections in general practice and a frequent indication for prescription of antimicrobials. Increasing concern about the association between the use of antimicrobials and acquired antimicrobial resistance has highlighted the need for rational pharmacotherapy of common infections in general practice.</p> <p>Methods</p> <p>Management of urinary tract infections in general practice was studied prospectively over 8 weeks. Patients presenting with suspected UTI submitted a urine sample and were enrolled with an opt-out methodology. Data were collected on demographic variables, previous antimicrobial use and urine samples. Appropriateness of different treatment scenarios was assessed by comparing treatment with the laboratory report of the urine sample.</p> <p>Results</p> <p>A total of 22 practices participated in the study and included 866 patients. Bacteriuria was established for 21% of the patients, pyuria without bacteriuria for 9% and 70% showed no laboratory evidence of UTI. An antimicrobial agent was prescribed to 56% (481) of the patients, of whom 33% had an isolate, 11% with pyuria only and 56% without laboratory evidence of UTI. When taking all patients into account, 14% patients had an isolate identified and were prescribed an antimicrobial to which the isolate was susceptible. The agents most commonly prescribed for UTI were co-amoxyclav (33%), trimethoprim (26%) and fluoroquinolones (17%). Variation between practices in antimicrobial prescribing as well as in their preference for certain antimicrobials, was observed. Treatment as prescribed by the GP was interpreted as appropriate for 55% of the patients. Three different treatment scenarios were simulated, i.e. if all patients who received an antimicrobial were treated with nitrofurantoin, trimethoprim or ciprofloxacin only. Treatment as prescribed by the GP was no more effective than treatment with nitrofurantoin for all patients given an antimicrobial or treatment with ciprofloxacin in all patients. Prescribing cost was lower for nitrofurantoin. Empirical treatment of all patients with trimethoprim only was less effective due to the higher resistance levels.</p> <p>Conclusions</p> <p>There appears to be considerable scope to reduce the frequency and increase the quality of antimicrobial prescribing for patients with suspected UTI.</p

Spatial and Temporal Trends of Global Pollination Benefit

Pollination is a well-studied and at the same time a threatened ecosystem service. A significant part of global crop production depends on or profits from pollination by animals. Using detailed information on global crop yields of 60 pollination dependent or profiting crops, we provide a map of global pollination benefits on a 5′ by 5′ latitude-longitude grid. The current spatial pattern of pollination benefits is only partly correlated with climate variables and the distribution of cropland. The resulting map of pollination benefits identifies hot spots of pollination benefits at sufficient detail to guide political decisions on where to protect pollination services by investing in structural diversity of land use. Additionally, we investigated the vulnerability of the national economies with respect to potential decline of pollination services as the portion of the (agricultural) economy depending on pollination benefits. While the general dependency of the agricultural economy on pollination seems to be stable from 1993 until 2009, we see increases in producer prices for pollination dependent crops, which we interpret as an early warning signal for a conflict between pollination service and other land uses at the global scale. Our spatially explicit analysis of global pollination benefit points to hot spots for the generation of pollination benefits and can serve as a base for further planning of land use, protection sites and agricultural policies for maintaining pollination services

Modularization of biochemical networks based on classification of Petri net t-invariants

<p>Abstract</p> <p>Background</p> <p>Structural analysis of biochemical networks is a growing field in bioinformatics and systems biology. The availability of an increasing amount of biological data from molecular biological networks promises a deeper understanding but confronts researchers with the problem of combinatorial explosion. The amount of qualitative network data is growing much faster than the amount of quantitative data, such as enzyme kinetics. In many cases it is even impossible to measure quantitative data because of limitations of experimental methods, or for ethical reasons. Thus, a huge amount of qualitative data, such as interaction data, is available, but it was not sufficiently used for modeling purposes, until now. New approaches have been developed, but the complexity of data often limits the application of many of the methods. Biochemical Petri nets make it possible to explore static and dynamic qualitative system properties. One Petri net approach is model validation based on the computation of the system's invariant properties, focusing on t-invariants. T-invariants correspond to subnetworks, which describe the basic system behavior.</p> <p>With increasing system complexity, the basic behavior can only be expressed by a huge number of t-invariants. According to our validation criteria for biochemical Petri nets, the necessary verification of the biological meaning, by interpreting each subnetwork (t-invariant) manually, is not possible anymore. Thus, an automated, biologically meaningful classification would be helpful in analyzing t-invariants, and supporting the understanding of the basic behavior of the considered biological system.</p> <p>Methods</p> <p>Here, we introduce a new approach to automatically classify t-invariants to cope with network complexity. We apply clustering techniques such as UPGMA, Complete Linkage, Single Linkage, and Neighbor Joining in combination with different distance measures to get biologically meaningful clusters (t-clusters), which can be interpreted as modules. To find the optimal number of t-clusters to consider for interpretation, the cluster validity measure, Silhouette Width, is applied.</p> <p>Results</p> <p>We considered two different case studies as examples: a small signal transduction pathway (pheromone response pathway in <it>Saccharomyces cerevisiae</it>) and a medium-sized gene regulatory network (gene regulation of Duchenne muscular dystrophy). We automatically classified the t-invariants into functionally distinct t-clusters, which could be interpreted biologically as functional modules in the network. We found differences in the suitability of the various distance measures as well as the clustering methods. In terms of a biologically meaningful classification of t-invariants, the best results are obtained using the Tanimoto distance measure. Considering clustering methods, the obtained results suggest that UPGMA and Complete Linkage are suitable for clustering t-invariants with respect to the biological interpretability.</p> <p>Conclusion</p> <p>We propose a new approach for the biological classification of Petri net t-invariants based on cluster analysis. Due to the biologically meaningful data reduction and structuring of network processes, large sets of t-invariants can be evaluated, allowing for model validation of qualitative biochemical Petri nets. This approach can also be applied to elementary mode analysis.</p