A Sustained Reduction of Methicillin Resistant Staphylococcus aureus (MRSA) in an Intensive Care Unit (ICU) at an Australian Tertiary Hospital over an 8-Year Period in the Absence of Intensive Infection Control Measures

Background: Intensive efforts to control nosocomial MRSA remain controversial. We report a decline in MRSA blood stream and other clinical isolates from our ICU in the absence of specific interventions against MRSA. Methods: Retrospective time series analysis of Staphylococcus aureus (SA) isolates from the Royal Melbourne Hospital ICU 2000-2007. Clinical isolates were electronically extracted from the microbiology database. Screening swabs and duplicate isolates collected within 7d from sterile and 30d from non-sterile sites respectively were excluded. Results: Consecutive 6 monthly MRSA (& total SA) clinical isolates/1000 occupied ICU bed days and MRSA (& total SA) blood culture isolates (unadjusted for occupancy) from 2000-2007 is presented in table 1. Trauma, cardiothoracic & other surgical comprised 63% (mean) of ICU admissions/ year. No MRSA specific interventions i.e. active screening, decolonisation or isolation were implemented. Interventions included antibiotic stewardship incorporating a computerized program (Jan 2001), regular rounds by infectious diseases physicians (April 2004), temporary screening & barrier nursing of Acinetobacter colonised patients during an outbreak of non-multiresistant Acinetobacter (Nov 2004-Dec 2005) and hand hygiene education (May 2005). Conclusions: Sustained reduction of endemic MRSA was achieved by quality improvement measures and limited infection control interventions. Intensive and expensive control measures may not always be necessary

UNDERSTANDING RISK FACTORS OF ELDERLY INPATIENT FALLS USING CONTEXTUAL MODEL

The field of Information Systems is about bridging the digital and information divide. Advances in the digital world enable information to be stored and structured in a manner that facilitates effective use of the information for future modelling purposes. Elderly inpatient falls are a common global phenomenon, and an inpatient fall incident can have severe consequences for the patient, caregivers and the healthcare provider. An inpatient fall can result from many causes and its risk can be increased through the combination of these causes. Many risk factors of elderly inpatient falls have been reported in various papers in the literature. However, a logical comprehensive categorisation of all these factors does not currently exist. The objective of this research in progress is to come up with a generic categorisation of the risk factors for elderly inpatient falls alongside the usage of a contextual model to illustrate the inherent interactions amongst these various factors. In addition, we found that the effect of the interaction amongst some risk factors is time dependent which also needs to be incorporated in the contextual model. Such comprehensive categorisation and contextual risk model will help health providers in the process of profiling of an elderly inpatient with respect to his/her fall risk. It is useful to experts in health informatics in formulating models to automate this process

Closing the gap in surveillance and audit of invasive mold diseases for antifungal stewardship using machine learning

Clinical audit of invasive mold disease (IMD) in hematology patients is inefficient due to the difficulties of case finding. This results in antifungal stewardship (AFS) programs preferentially reporting drug cost and consumption rather than measures that actually reflect quality of care. We used machine learning-based natural language processing (NLP) to non-selectively screen chest tomography (CT) reports for pulmonary IMD, verified by clinical review against international definitions and benchmarked against key AFS measures. NLP screened 3014 reports from 1 September 2008 to 31 December 2017, generating 784 positives that after review, identified 205 IMD episodes (44% probable-proven) in 185 patients from 50,303 admissions. Breakthrough-probable/proven-IMD on antifungal prophylaxis accounted for 60% of episodes with serum monitoring of voriconazole or posaconazole in the 2 weeks prior performed in only 53% and 69% of episodes, respectively. Fiberoptic bronchoscopy within 2 days of CT scan occurred in only 54% of episodes. The average turnaround of send-away bronchoalveolar galactomannan of 12 days (range 7-22) was associated with high empiric liposomal amphotericin consumption. A random audit of 10% negative reports revealed two clinically significant misses (0.9%, 2/223). This is the first successful use of applied machine learning for institutional IMD surveillance across an entire hematology population describing process and outcome measures relevant to AFS. Compared to current methods of clinical audit, semi-automated surveillance using NLP is more efficient and inclusive by avoiding restrictions based on any underlying hematologic condition, and has the added advantage of being potentially scalable

Baseline Chest Computed Tomography as Standard of Care in High-Risk Hematology Patients

Baseline chest computed tomography (BCT) in high-risk hematology patients allows for the early diagnosis of invasive pulmonary aspergillosis (IPA). The distribution of BCT implementation in hematology departments and impact on outcome is unknown. A web-based questionnaire was designed. International scientific bodies were invited. The estimated numbers of annually treated hematology patients, chest imaging timepoints and techniques, IPA rates, and follow-up imaging were assessed. In total, 142 physicians from 43 countries participated. The specialties included infectious diseases (n = 69; 49%), hematology (n = 68; 48%), and others (n = 41; 29%). BCT was performed in 57% (n = 54) of 92 hospitals. Upon the diagnosis of malignancy or admission, 48% and 24% performed BCT, respectively, and X-ray was performed in 48% and 69%, respectively. BCT was more often used in hematopoietic cell transplantation and in relapsed acute leukemia. European centers performed BCT in 59% and non-European centers in 53%. Median estimated IPA rate was 8% and did not differ between BCT (9%; IQR 5-15%) and non-BCT centers (7%; IQR 5-10%) (p = 0.69). Follow-up computed tomography (CT) for IPA was performed in 98% (n = 90) of centers. In high-risk hematology patients, baseline CT is becoming a standard-of-care. Chest X-ray, while inferior, is still widely used. Randomized, controlled trials are needed to investigate the impact of BCT on patient outcome

Re-imagining the surveillance of invasive mould diseases

© 2014 Dr. Michelle Ananda-RajahPublications included in thesis:Ananda-Rajah, M. R., Grigg, A., & Slavin, M. A. (2012). Making sense of posaconazole therapeutic drug monitoring: a practical approach. Current Opinion in Infectious Diseases, 25(6), 605–611. DOI: 10.1097/QCO.0b013e328359a56eAnanda-Rajah, M. R., Slavin, M. A., & Thursky, K. T. (2012). The case for antifungal stewardship. Current Opinion in Infectious Diseases, 25(1), 107–115. DOI: 10.1097/QCO.0b013e32834e0680Ananda-Rajah, M. R., Grigg, A., Downey, M. T., Bajel, A., Spelman, T., Cheng, A., et al. (2012). Comparative clinical effectiveness of prophylactic voriconazole/posaconazole to fluconazole/itraconazole in patients with acute myeloid leukaemia/myelodysplastic syndrome undergoing cytotoxic chemotherapy over a 12-year period. Haematologica, 97(3), 459–463. DOI: 10.3324/haematol.2011.051995Ananda-Rajah, M. R., Cheng, A., Morrissey, C. O., Spelman, T., Dooley, M., Neville, A. M., et al. (2011). Attributable hospital cost and antifungal treatment of invasive fungal diseases in high-risk hematology patients: an economic modelling approach. Antimicrobial Agents and Chemotherapy, 55(5), 1953–1960. DOI: 10.1128/AAC.01423-10Martinez, D., Ananda-Rajah, M. R., Suominen, H., Slavin, M. A., Thursky, K. A., & Cavedon, L. (2013). Automatic detection of patients with invasive fungal infections from free-text computed tomography (CT) scans. Manuscript submitted for publication.Ananda-Rajah, M. R., McBryde, E. S., Buising, K. L., Redl, L., MacIsaac, C., Cade, J. F., et al. (2010). The role of general quality improvement measures in decreasing the burden of endemic MRSA in a medical-surgical intensive care unit. Intensive Care Medicine, 36(11), 1890–1898. DOI: 10.1007/s00134-010-2019-xInvasive mould diseases (IMDs) have significant health and economic costs for immunocompromised patients. IMDs are now the predominant fungal pathogens in haematology-oncology patients who also carry the greatest burden of fungal infections overall. This thesis captures the high hospitalisation cost of invasive fungal diseases (IFDs) based on detailed patient level data. It explores the optimal methodology to cost these infections and postulates a novel resource metric in costly antifungal drug consumption as an alternative to currency estimates. It examines the comparative effectiveness of antifungal prophylaxis in haematology-oncology patients at high risk for IMDs documenting over a decade, the declining incidence of IMD following the adoption of mould active antifungal prophylaxis with reductions in other clinically relevant outcomes such as empiric antifungal therapy and non- specific pulmonary infiltrates also observed. Our analyses of azole and liposomal amphotericin prophylaxis go beyond demonstrating the evolving epidemiology of fungal infections in response to changing therapeutic practices but also illustrate that knowledge of local epidemiology informs clinical decision making. The latter, culminating in clinical practice recommendations regarding the optimisation of posaconazole for either prophylaxis or treatment of established IFDs and, in a broader context, recommendations strengthening antifungal drug stewardship programs in hospitals. Despite the health and cost implications of IMDs and effort invested in preventing them, prospective continuous surveillance is not routinely performed in many hospitals. Reasons for this omission include cost and the absence of an easily identifiable laboratory prompt. Traditional approaches to surveillance, which are reliant on bedside review, administrative or laboratory- based methods, are resource-intensive activities, error prone and subject to either under-reporting and/or variability in case ascertainment. This thesis will argue the case for prospective surveillance of IMDs and provide a potential technological solution to facilitate its practice in hospitals. From a surveillance standpoint, the primary screening method is critically important in order to maximise case finding while minimising its cost and effort. For IMDs however, the optimal screening method is undefined. This thesis considers targeting computed tomography (CT) reports as an appropriate screening method for IMD surveillance. CT is a key diagnostic modality for IMDs stipulated in consensus guidelines; pulmonary involvement is present in the overwhelming majority of cases; it is widely available in hospitals and being a non-invasive test it is uniformly performed when IMDs are suspected with results available in a timely fashion. Non-culture based tests (NCBTs) such as galactomannan (GM) or polymerase chain reaction (PCR) are less suitable as screening tools due to their variable availability, delays in turn- around and a diminished sensitivity in the presence of concomitant mould- active antifungal agents. This thesis describes the development of a text classifier that uses natural language processing (NLP) for the first time to flag CT reports supportive of IMDs. NLP is a computational method for analysing human language that has been applied for the detection of a variety of medical conditions, but not IMDs. As a high-throughput technology, it has the potential to identify CT reports with suspected IMD in real-time. Thus, it may deliver to hospitals a feasible, sustainable and cost-effective solution to IMD surveillance with minimal interruption to routine clinical workflow. Text analytical tools are a means of unlocking the wealth of patient-level data that is largely confined to unstructured (i.e., free-text) documents in health care. Modernisation of data management and an investment in data infrastructure could help the health industry keep pace with changing clinical practice while also supporting large scale comparative effectiveness studies of ‘real-world’ patients who are free from the protocol-driven biases of clinical trials. In future, the partnering of enormous volumes of routinely collected clinical data with genomic or molecular advances could help progress bioinformatics which predict disease and personalise treatments that are both effective and cost-beneficial

Closing the gap in the detection and diagnosis of fungal infections in patients with blood cancers using a machine learning based platform technology

Invasive fungal infections cause a life-threatening pneumonia in patients with impaired immunity. Hospitals spend millions of dollars on drugs to manage these infections but are unaware of the types of infections affecting their patients and their outcomes. Surveillance of fungal infections is not occurring in hospitals because fungi infrequently grow in the laboratory and manual surveillance is onerous. As a result, clinicians and hospitals cannot evaluate the effectiveness of preventative efforts, outbreaks may go unnoticed and tailoring therapy according to risk is hampered by the lack of large datasets for a rare disease. Variation is common in radiologist reporting affecting patient care and clinical trials. Our machine learning based platform technology incorporating natural language processing, deep learning based image recognition and the integration of clinical data in an expert system can address these performance gaps with benefits to patients, hospitals, clinicians and trial sponsors

A Sustained Reduction of Methicillin Resistant Staphylococcus aureus (MRSA) in an Intensive Care Unit (ICU) at an Australian Tertiary Hospital over an 8-Year Period in the Absence of Intensive Infection Control Measures

Background: Intensive efforts to control nosocomial MRSA remain controversial. We report a decline in MRSA blood stream and other clinical isolates from our ICU in the absence of specific interventions against MRSA.\ud Methods: Retrospective time series analysis of Staphylococcus aureus (SA) isolates from the Royal Melbourne Hospital ICU 2000-2007. Clinical isolates were electronically extracted from the microbiology database. Screening swabs and duplicate isolates collected within 7d from sterile and 30d from non-sterile sites respectively were excluded. Results:\ud Consecutive 6 monthly MRSA (& total SA) clinical isolates/1000 occupied ICU bed days and MRSA (& total SA) blood culture isolates (unadjusted for occupancy) from 2000-2007 is presented in table 1. Trauma, cardiothoracic & other surgical comprised 63% (mean) of ICU admissions/ year. No MRSA specific interventions i.e. active screening, decolonisation or isolation were implemented. Interventions included antibiotic stewardship incorporating a computerized program (Jan 2001), regular rounds by infectious diseases physicians (April 2004), temporary screening & barrier nursing of Acinetobacter colonised patients during an outbreak of non-multiresistant Acinetobacter (Nov 2004-Dec 2005) and hand hygiene education (May 2005). Conclusions: Sustained reduction of endemic MRSA was achieved by quality improvement measures and limited infection control interventions. Intensive and expensive control measures may not always be necessary