Making decisions about antibiotic use in the Australian primary healthcare sector

Background Australia has one of the highest rates of antibiotic use amongst OECD countries. Data from the Australian primary healthcare sector suggests unnecessary antibiotics were prescribed for self-resolving conditions. We need to better understand what drives general practitioners (GPs) to prescribe antibiotics, consumers to seek antibiotics, and pharmacists to fill repeat antibiotic prescriptions. It is also not clear how these individuals trade-off between the possible benefits that antibiotics may provide in the immediate/short term, against the longer term societal risk of antimicrobial resistance. This project investigates what factors drive decisions to use antibiotics for GPs, pharmacists and consumers, and how these individuals discount the future. Methods Factors will be gleaned from published literature and from semi-structured interviews, to inform the development of Discrete Choice Experiments (DCEs). Three DCEs will be constructed – one for each group of interest – to allow investigation of which factors are more important in influencing (a) GPs to prescribe antibiotics, (b) consumers to seek antibiotics, and (c) pharmacists to fill legally valid but old or repeat prescriptions of antibiotics. Regression analysis will be conducted to understand the relative importance of these factors. A Time Trade Off exercise will be developed to investigate how these individuals discount the future. Results Findings from the DCEs will provide an insight into which factors are more important in driving decision making in antibiotic use for GPs, pharmacists and consumers. Findings from the Time Trade Off exercise will show what individuals are willing to trade for preserving the miracle of antibiotics. Conclusion Research findings will contribute to existing national programs to bring about a reduction in inappropriate use of antibiotic in Australia. Specifically, influencing how key messages and public health campaigns are crafted, and clinical education and empowerment of GPs and pharmacists to play a more responsive role as stewards of antibiotic use in the community.

Healthcare-Associated Infections in Pediatrics

Healthcare-associated infections (HAIs) are known to increase the risk for patient morbidity and mortality in different healthcare settings and thereby to cause additional costs. HAIs typically affect patients with severe underlying conditions. HAIs are prevalent also among pediatric patients, but the distribution of the types of infection and the causative agents differ from those detected in adults. The aim of this study was to obtain information on pediatric HAIs in Finland through an assessment of the surveillance of bloodstream infections (BSIs), through two outbreak investigations in a neonatal intensive care unit (NICU), and through a study of postoperative HAIs after open-heart surgery. The studies were carried out at the Hospital for Children and Adolescents of Helsinki University Central Hospital. Epidemiological features of pediatric BSIs were assessed. For the outbreak investigations, case definitions were set and data collected from microbiological and clinical records. The antimicrobial susceptibilities of the Serratia marcescens and the Candida parapsilosis isolates were determined and they were genotyped. Patient charts were reviewed for the case-control and cohort studies during the outbreak investigations, as well as for the patients who acquired surgical site infections (SSIs) after having undergone open-heart surgery. Also a prospective postdischarge study was conducted to detect postoperative HAIs in these patients. During 1999-2006, the overall annual BSI rate was 1.6/1,000 patient days (range by year, 1.2–2.1). High rates (average, 4.9 and 3.2 BSIs/1,000 patient days) were detected in hematology and neonatology units. Coagulase-negative staphylococci were the most common pathogens both hospital-wide and in each patient group. The overall mortality was 5%. The genotyping of the 15 S. marcescens isolates revealed three independent clusters. All of the 26 C. parapsilosis isolates studied proved to be indistinguishable. The NICU was overcrowded during the S. marcescens clusters. A negative correlation between C. parapsilosis BSIs and fluconazole use in the NICU was detected, and the isolates derived from a single initially susceptible strain became less susceptible to fluconazole over time. Eighty postoperative HAIs, including all severe infections, were detected during hospitalization after open-heart surgery; 34% of those HAIs were SSIs and 25% were BSIs. The postdischarge study found 65 infections that were likely to be associated with hospitalization. The majority (89%) of them were viral respiratory or gastrointestinal infections, and these often led to rehospitalizations. The annual hospital-wide BSI rates were stable, and the significant variation detected in some units could not be seen in overall rates. Further studies with data adequately adjusted for risk factors are needed to assess BSI rates in the patient groups with the highest rates (hematology, neonatology). The outbreak investigations showed that horizontal transmission was common in the NICU. Overcrowding and lapses in hand hygiene probably contributed to the spreading of the pathogens. Following long-term use of fluconazole in the NICU, resistance to fluconazole developed in C. parapsilosis. Almost one-fourth of the patients who underwent open-heart surgery acquired at least one HAI. All severe HAIs were detected during hospitalization. The postdischarge study found numerous viral infections, which often caused rehospitalization.

Understanding data flow and security requirements in wireless Body Area Networks for healthcare

The Body Area Network (BAN) is an emerging technology that focuses on monitoring physiological data in, on and around the human body. BAN technology permits wearable and implanted sensors to collect vital data about the human body and transmit it to other nodes via low-energy communication. In this paper, we investigate interactions in terms of data flows between parties involved in BANs under four different scenarios targeting outdoor and indoor medical environments: hospital, home, emergency and open areas. Based on these scenarios, we identify data flow requirements between BAN elements such as sensors and control units (CUs) and parties involved in BANs such as the patient, doctors, nurses and relatives. Identified requirements are used to generate BAN data flow models. Petri Nets (PNs) are used as the formal modelling language. We check the validity of the models and compare them with the existing related work. Finally, using the models, we identify communication and security requirements based on the most common active and passive attack scenarios.

Novel application of a discrete choice experiment to identify preferences for a national healthcare-associated infection surveillance programme: A cross-sectional study

Objective: To identify key stakeholder preferences and priorities when considering a national healthcare-associated infection (HAI) surveillance programme through the use of a discrete choice experiment (DCE). Setting: Australia does not have a national HAI surveillance programme. An online web-based DCE was developed and made available to participants in Australia. Participants: A sample of 184 purposively selected healthcare workers based on their senior leadership role in infection prevention in Australia. Primary and secondary outcomes: A DCE requiring respondents to select 1 HAI surveillance programme over another based on 5 different characteristics (or attributes) in repeated hypothetical scenarios. Data were analysed using a mixed logit model to evaluate preferences and identify the relative importance of each attribute. Results: A total of 122 participants completed the survey (response rate 66%) over a 5-week period. Excluding 22 who mismatched a duplicate choice scenario, analysis was conducted on 100 responses. The key findings included: 72% of stakeholders exhibited a preference for a surveillance programme with continuous mandatory core components (mean coefficient 0.640 (p<0.01)), 65% for a standard surveillance protocol where patient-level data are collected on infected and non-infected patients (mean coefficient 0.641 (p<0.01)), and 92% for hospital-level data that are publicly reported on a website and not associated with financial penalties (mean coefficient 1.663 (p<0.01)). Conclusions: The use of the DCE has provided a unique insight to key stakeholder priorities when considering a national HAI surveillance programme. The application of a DCE offers a meaningful method to explore and quantify preferences in this setting.

e-SURAKSHAK: A Cyber-Physical Healthcare System with Service Oriented Architecture

In this paper we present the design of ``e-SURAKSHAK,'' a novel cyber-physical health care management system of Wireless Embedded Internet Devices (WEIDs) that sense vital health parameters. The system is capable of sensing body temperature, heart rate, oxygen saturation level and also allows noninvasive blood pressure (NIBP) measurement. End to end internet connectivity is provided by using 6LoWPAN based wireless network that uses the 802.15.4 radio. A service oriented architecture (SOA) 1] is implemented to extract meaningful information and present it in an easy-to-understand form to the end-user instead of raw data made available by sensors. A central electronic database and health care management software are developed. Vital health parameters are measured and stored periodically in the database. Further, support for real-time measurement of health parameters is provided through a web based GUI. The system has been implemented completely and demonstrated with multiple users and multiple WEIDs.

Innovation processes within the healthcare industry: Determining critical success factors aligned to product strategies

The impact of differing product strategies on product innovation processes pursued by healthcare firms is discussed. The critical success factors aligned to product strategies are presented. A definite split between pioneering product strategies and late entrant product strategies is also recognised.