ORCID Profile
0000-0001-7883-517X
Current Organisation
Northern Adelaide Local Health Network
Does something not look right? The information on this page has been harvested from data sources that may not be up to date. We continue to work with information providers to improve coverage and quality. To report an issue, use the Feedback Form.
Publisher: Wiley
Date: 02-2022
DOI: 10.1111/IMJ.15678
Abstract: Automated information extraction might be able to assist with the collection of stroke key performance indicators (KPI). The feasibility of using natural language processing for classification‐based KPI and datetime field extraction was assessed. Using free‐text discharge summaries, random forest models achieved high levels of performance in classification tasks (area under the receiver operator curve 0.95–1.00). The datetime field extraction method was successful in 29 of 43 (67.4%) cases. Further studies are indicated.
Publisher: Wiley
Date: 31-07-2015
Publisher: Wiley
Date: 06-2023
DOI: 10.1111/IMJ.16115
Abstract: Reducing preventable readmissions is important to help manage current strains on healthcare systems. The metric of 30‐day readmissions is commonly cited in discussions regarding this topic. While such thresholds have contemporary funding implications, the rationale for in idual cut‐off points is partially historical in nature. Through the examination of the basis for the analysis of 30‐day readmissions, greater insight into the possible benefits and limitations of such a metric may be obtained.
Publisher: Wiley
Date: 10-2022
DOI: 10.1111/IMJ.15923
Publisher: Informa UK Limited
Date: 24-04-2023
Publisher: Wiley
Date: 29-06-2023
DOI: 10.1111/TME.12984
Publisher: American Thoracic Society
Date: 15-09-2022
Publisher: Elsevier BV
Date: 05-2021
DOI: 10.1016/J.AUCC.2021.04.006
Abstract: The aim of the study was to determine the response rate to a mixed-mode survey using email compared with that to a paper survey in survivors of critical illness. This is a prospective randomised controlled trial. The study was conducted at a single-centre quaternary intensive care unit (ICU) in Adelaide, Australia. Study participants were patients admitted to the ICU for ≥48 h and discharged from the hospital. The participants were randomised to receive a survey by paper (via mail) or via online (via email, or if a non-email user, via a letter with a website address). Patients who did not respond to the initial survey received a reminder paper survey after 14 days. The survey included quality of life (EuroQol-5D-5L), anxiety and depression (Hospital Anxiety and Depression Scale), and post-traumatic symptom (Impact of Event Scale-Revised) assessment. Survey response rate, extent of survey completion, clinical outcomes at different time points after discharge, and survey cost analysis were the main outcome measures. Outcomes were stratified based on follow-up time after ICU discharge (3, 6, and 12 months). A total of 239 patients were randomised. The response rate was similar between the groups (mixed-mode: 78% [92/118 patients] vs. paper: 80% [97/121 patients], p = 0.751) and did not differ between time points of follow-up. Incomplete surveys were more prevalent in the paper group (10% vs 18%). The median EuroQol-5D-5L index value was 0.83 [0.71-0.92]. Depressive symptoms were reported by 25% of patients (46/187), anxiety symptoms were reported by 27% (50/187), and probable post-traumatic stress disorder was reported by 14% (25/184). Patient outcomes did not differ between the groups or time points of follow-up. The cost per reply was AU$ 16.60 (mixed-mode) vs AU$ 19.78 (paper). The response rate of a mixed-mode survey is similar to that of a paper survey and may provide modest cost savings.
Publisher: Wiley
Date: 11-07-2023
DOI: 10.1111/AJAG.13226
Abstract: Blood tests for endocrinological derangements are frequently requested in general medical inpatients, in particular those in the older age group. Interrogation of these tests may present opportunities for healthcare savings. This multicentre retrospective study over a 2.5‐year period examined the frequency with which three common endocrinological investigations [thyroid stimulating hormone (TSH), HbA1c, 25‐hydroxy Vitamin D3] were performed in this population, including the frequency of duplicate tests within a given admission, and the frequency of abnormal test results. The Medicare Benefits Schedule was used to calculate the cost associated with these tests. There were 28,564 in idual admissions included in the study. In iduals ≥65 years old were the majority of inpatients in whom the selected tests were performed (80% of tests). TSH was performed in 6730 admissions, HbA1c was performed in 2259 admissions, and vitamin D levels were performed in 5632 admissions. There were 6114 vitamin D tests performed during the study period, of which 2911 (48%) returned outside the normal range. The cost associated with vitamin D level testing was $183,726. Over the study period, 8% of tests for TSH, HbA1c, and Vitamin D were duplicates (where a second test was performed within a single admission), which was associated with a cost of $32,134. Tests for common endocrinological abnormalities are associated with significant healthcare costs. Avenues by which future savings may be pursued include the investigation of strategies to reduce duplicate ordering and examining the rationale and guidelines associated with ordering tests such as vitamin D levels.
Publisher: Wiley
Date: 30-03-2022
Abstract: To assess the performance of an Australian pre‐hospital and retrieval medicine (PHRM) service against the National Institute for Health and Care Excellence (NICE) standard which recommends that pre‐hospital emergency anaesthesia (PHEA) in trauma patients should be conducted within 45‐min of first contact with emergency services. Retrospective observational study of all adult trauma patients in which PHEA was conducted by the PHRM service covering a 5‐year period from January 2015 to December 2019. Over the 5‐year study period, 1509 (22%) of the PHRM service workload comprised primary retrievals from scene. Most 1346 (89%) of these cases had a primary diagnosis of trauma. Of these we have complete data for 328 of the 337 cases requiring a PHEA and 121 (37%) patients received this within the recommended 45‐min time frame. The service attended in rapid response vehicles ( n = 160, 49%), rotary wing ( n = 151, 46%) and fixed wing ( n = 17, 5%) transport modalities. For a service covering 983 482 km 2 , the median distance travelled to patients was 35 (16–71) km and the median time to PHEA was 54 (38–80) min. In a cohort of 337 patients treated by a dedicated PHRM service in South Australia, the median time to PHEA was 54 (38–80) min with only 37% of patients receiving PHEA within 45 min from the activation of the team. Despite differing patient demographics, the percentage of patients receiving PHEA within the recommended time frame was greater than a similar cohort from the UK. However, both data sets still fall short of recommended targets.
Publisher: Informa UK Limited
Date: 22-07-2022
DOI: 10.1080/21548331.2022.2102778
Abstract: Poor communication and lack of standardized handover practices contribute to adverse events. Intensive care organizations recommend standardized, structured written and verbal handover. Investigate the effectiveness of, and barriers to, Intensive Care Unit (ICU) patient handover at ward transfer. Screen for patient safety incidents related to poor handover and improve practice where deficiencies are identified. A survey of ward doctors about specific ICU to ward transfers and online surveys ascertaining opinions of handover processes were sent to ward-based and ICU doctors at a large, adult, university affiliated, Australian quaternary hospital. We delivered departmental education and created then publicized a new electronic ICU transfer summary. The summary included a mandatory tick-box to confirm verbal handover completion. Surveys re-assessing practice were then performed. Forty ward-based doctors were surveyed about specific transfers, with 7 (18%) instances of issues related to handover identified. Eighty-seven ward doctors completed the pre-interventions survey 48 (55%) were aware of the existing written transfer summary. Post-interventions, 47 (75%) of 63 ward doctor responders were aware of it (p < 0.05). Pre-interventions, 14 (16%) ward doctors rated ICU handovers as excellent or good, rising to 21 (34%) post-interventions (p < 0.05). Thirty-nine ICU doctors completed the pre-interventions survey 5 (13%) rated ICU to ward handover as excellent or good, rising to 9 (35%) when re-surveyed (p = 0.097). The perceived quality of ICU to ward handover improved after our interventions. However, ICU doctors continue to transfer patients without verbally handing over, with contacting the ward team representing a significant handover barrier.
Publisher: S. Karger AG
Date: 11-11-2022
DOI: 10.1159/000526424
Abstract: b i Introduction: /i /b Penicillin allergy labels are common. However, many penicillin allergy labels have been applied incorrectly and in fact represent penicillin intolerance. Patients with penicillin intolerance can receive penicillin antibiotics. The effect of penicillin intolerance labels on prescribing practices is uncertain. b i Methods: /i /b This multicenter retrospective cohort study included consecutive general medicine patients admitted to two tertiary hospitals over a 12-month period. Electronic medical records were reviewed for allergy and prescribing practices. Instances of penicillin prescription to patients with previously labeled penicillin allergies underwent case note review. b i Results: /i /b There were 12,134 in idual hospital admissions included in the study. The number of admissions with a previous penicillin allergy label was 1,312 (10.8%) and with a penicillin intolerance label was 60 (0.5%). Penicillin allergy labels were associated with increased likelihood of being prescribed vancomycin (odds ratio 1.42, 95% confidence interval 1.16–1.75, i /i = 0.001) and moxifloxacin (odds ratio 20.0, 95% confidence interval 13.4–29.9, i /i & #x3c 0.001). Penicillin intolerance was not associated with increased likelihood of receiving these antibiotics. There were 75 admissions during which an in idual with a penicillin allergy label was prescribed one of the specified penicillins and only one adverse reaction in this group. These cases included eight deliberate challenges and 15 cases in which allergy history clarification was sufficient to delabel the allergy. b i Conclusions: /i /b This study supports that prescribing practices differ between patients with penicillin allergy labels and intolerance labels. Penicillin challenges may be undertaken safely in the inpatient setting. Further studies are required to investigate how best to interrogate penicillin allergy labels in this cohort.
Publisher: Elsevier BV
Date: 12-2021
DOI: 10.1016/J.JOCN.2021.10.024
Abstract: Clinical coding is an important task, which is required for accurate activity-based funding. Natural language processing may be able to assist with improving the efficiency and accuracy of clinical coding. The aims of this study were to explore the feasibility of using natural language processing for stroke hospital admissions, employed with open-source software libraries, to aid in the identification of potentially misclassified (1) category of Adjacent Diagnosis Related Groups (ADRG), (2) the International Statistical Classification of Diseases and Related Health Problems, Tenth Revision, Australian Modification (ICD-10-AM) diagnoses, and (3) Diagnosis Related Groups (DRG). Data was collected for consecutive in iduals admitted to the Royal Adelaide Hospital Stroke Unit over a five-month period for misclassification identification analysis. 152 admissions were included in the study. Using free-text discharge summaries, a random forest classifier correctly identified two cases classified as B70 ("Stroke and Other Cerebrovascular Disorders") that should be classified as B02 (having received endovascular thrombectomy). A regular expression-based analysis correctly identified 33 cases in which ataxia was present but was not coded. Two cases were identified that should have been classified as B70D, rather than B70A/B/C, based on transfer to another centre within five days of admission. A variety of techniques may be useful to help identify misclassifications in ADRG, ICD-10-AM and DRG codes. Such techniques can be implemented with open-source software libraries, and may have significant financial implications. Future studies may seek to apply open-source software libraries to the identification of misclassifications of all ICD-10-AM diagnoses in stroke patients.
Publisher: Elsevier BV
Date: 03-2021
Publisher: Springer Science and Business Media LLC
Date: 06-06-2023
DOI: 10.1007/S40629-023-00250-Z
Abstract: Cefalexin is a commonly prescribed oral antibiotic, with a similar side chain to amoxicillin. The objectives of this study were to (1) describe the frequency and nature of previously recorded cefalexin adverse reaction (AR) labels in the electronic medical record (EMR) in a medical inpatient cohort, (2) evaluate the accuracy of these labels and (3) examine the association between a cefalexin allergy label and the antibiotics prescribed during an inpatient admission. Consecutive admissions under general medicine in a tertiary hospital over a 1-year period were included in this retrospective cohort study. Data regarding cefalexin adverse reaction (AR) history, and antibiotics prescribed during admission were collected from the EMR. Cefalexin allergy descriptions were reviewed using expert criteria to determine whether the described reaction was most consistent with allergy or intolerance. The number of admissions included in this study was 12,134. Of the 224 (1.9%) admissions with a recorded cefalexin AR, 196 (87.5%) had a label of allergy and 28 (12.5%) of intolerance. Following the application of expert criteria, 43 (21.9%) of cefalexin allergy labels were found to be consistent with intolerance. The presence of a low-risk cefalexin allergy was associated with an increased likelihood of receiving non-penicillin antibiotics including clindamycin and ciprofloxacin. Cefalexin AR are common, and frequently incorrectly classified in the electronic medical record with consequences for in-hospital antibiotic prescribing and antimicrobial stewardship.
Publisher: Springer Science and Business Media LLC
Date: 16-03-2021
Publisher: SAGE Publications
Date: 03-2018
DOI: 10.1177/0310057X1804600210
Abstract: This study was performed to estimate the effect of the retrieval process on mortality for patients admitted to a mixed adult intensive care unit (ICU) compared with propensity-matched, non-retrieved controls. Patients retrieved to the Royal Adelaide Hospital (RAH) ICU between 2011 and 2015 were propensity-score matched for age, gender, Aboriginal and Torres Strait Islander status, Acute Physiology and Chronic Health Evaluation (APACHE) III score and diagnostic group with non-retrieved ICU patients to estimate the average treatment effect of retrieval on hospital mortality. Factors associated with mortality in those retrieved were assessed by multiple logistic regression. Retrieved patients comprised 1,597 (14%) of 11,641 index ICU admissions this group were younger, mean (standard deviation) 53 (18.5) versus 59 (17.7) years, had higher APACHE III scores, 61 (30.3) versus 56 (27.5), were more likely to be Indigenous (5.1% versus 3.7%) and to have sustained trauma (34% versus 9%). The average treatment effect for retrieval on hospital mortality, risk difference (95% confidence interval), was −0.7% (-2.8% to 1.3%), P=0.50. Variables independently associated with hospital mortality in those retrieved included age, APACHE III score and diagnostic category. Time from retrieval team activation to arrival with the patient, rural location, radial distance from the RAH and population size at the retrieval location were not significantly associated with mortality. The hospital mortality for retrieved patients was not significantly different when compared with propensity-matched controls. Mortality in those retrieved was associated with increasing age, APACHE III score and diagnostic category however, was independent of time from team activation to arrival with the patient.
Publisher: Elsevier BV
Date: 05-2022
DOI: 10.1016/J.AUCC.2021.05.007
Abstract: Disability is common following critical illness, impacting the quality of life of survivors, and is difficult to measure. 'Participation' can be quantified as involvement in life outside of their home requiring movement from their home to other locations. Participation restriction is a key element of disability, and following critical illness, participation may be diminished. It may be possible to quantify this change using pre-existing smartphone data. The feasibility of extracting location data from smartphones of survivors of intensive care unit (ICU) admission and assessing participation, using location-based outcomes, during recovery from critical illness was evaluated. Fifty consecutively admitted, consenting adult survivors of non-elective admission to ICU of greater than 48-h duration were recruited to a prospective observational cohort study where they were followed up at 3 and 6 months following discharge. The feasibility of extracting location data from survivors' smartphones and creating location-derived outcomes assessing participation was investigated over three 28-d study periods: pre-ICU admission and at 3 and 6 months following discharge. The following were calculated: time spent at home the number of destinations visited linear distance travelled and two 'activity spaces', a minimum convex polygon and standard deviation ellipse. Results are median [interquartile range] or n (%). The number of successful extractions was 9/50 (18%), 12/39 (31%), and 13/33 (39%) the percentage of time spent at home was 61 [56-68]%, 77 [66-87]%, and 67 [58-77]% (P = 0.16) the number of destinations visited was 34 [18-64], 38 [22-63], and 65 [46-88] (P = 0.02) linear distance travelled was 367 [56-788], 251 [114-323], and 747 [326-933] km over 28 d (P = 0.02), pre-ICU admission and at 3 and 6 months following ICU discharge, respectively. Activity spaces were successfully created. Limited smartphone ownership, missing data, and time-consuming data extraction limit current implementation of mass extraction of location data from patients' smartphones to aid prognostication or measure outcomes. The number of journeys taken and the linear distance travelled increased between 3 and 6 months, suggesting participation may improve over time.
Publisher: Springer Science and Business Media LLC
Date: 04-01-2202
DOI: 10.1007/S11739-019-02265-3
Abstract: Length of stay (LOS) and discharge destination predictions are key parts of the discharge planning process for general medical hospital inpatients. It is possible that machine learning, using natural language processing, may be able to assist with accurate LOS and discharge destination prediction for this patient group. Emergency department triage and doctor notes were retrospectively collected on consecutive general medical and acute medical unit admissions to a single tertiary hospital from a 2-month period in 2019. These data were used to assess the feasibility of predicting LOS and discharge destination using natural language processing and a variety of machine learning models. 313 patients were included in the study. The artificial neural network achieved the highest accuracy on the primary outcome of predicting whether a patient would remain in hospital for > 2 days (accuracy 0.82, area under the received operator curve 0.75, sensitivity 0.47 and specificity 0.97). When predicting LOS as an exact number of days, the artificial neural network achieved a mean absolute error of 2.9 and a mean squared error of 16.8 on the test set. For the prediction of home as a discharge destination (vs any non-home alternative), all models performed similarly with an accuracy of approximately 0.74. This study supports the feasibility of using natural language processing to predict general medical inpatient LOS and discharge destination. Further research is indicated with larger, more detailed, datasets from multiple centres to optimise and examine the accuracy that may be achieved with such predictions.
Publisher: SAGE Publications
Date: 11-2015
DOI: 10.1177/0310057X1504300605
Abstract: Despite a paucity of data regarding both the incidence of ocular candidiasis and the utility of ophthalmic examination in critically ill patients, routine ophthalmic examination is recommended for critically ill patients with candidaemia. The objectives were to estimate the incidence of ocular candidiasis and evaluate whether ophthalmic examination influenced subsequent management of these patients. We conducted a ten-year retrospective observational study. Data were extracted for all ICU patients who were blood culture positive for fungal infection. Risk factors for candidaemia and eye involvement were quantified and details regarding ophthalmic examination were reviewed. Candida species were cultured in 93 patients. Risk factors for ocular candidiasis were present in 57% of patients. Forty-one percent of patients died prior to ophthalmology examination and 2% of patients were discharged before candidaemia was identified. During examination, signs of ocular candidiasis were only present in one (2.9%) patient, who had a risk factor for ocular candidiasis. Based on these findings, the duration of antifungal treatment for this patient was increased. Ocular candidiasis occurs rarely in critically ill patients with candidaemia, but because treatment regimens may be altered when diagnosed, routine ophthalmic examination is still indicated.
Publisher: Ovid Technologies (Wolters Kluwer Health)
Date: 10-2017
DOI: 10.1097/CCM.0000000000002599
Abstract: Surrogate-decision maker and patient self-reported estimates of the distances walked prior to acute illness are subjective and may be imprecise. It may be possible to extract objective data from a patient’s smartphone, specifically, step and global position system data, to quantify physical activity. The objectives were to 1) assess the agreement between surrogate-decision maker and patient self-reported estimates of distance and time walked prior to resting and daily step-count and 2) determine the feasibility of extracting premorbid physical activity (step and global position system) data from critically ill patients. Prospective cohort study. Quaternary ICU. Fifty consecutively admitted adult patients who owned a smartphone, who were ambulatory at baseline, and who remained in ICU for more than 48 hours participated. There was no agreement between patients and surrogates for all premorbid walking metrics (mean bias 108% [99% lower to 8,700% higher], 83% [97% to 2,100%], and 71% [96% to 1,080%], for distance, time, and steps, respectively). Step and/or global position system data were successfully extracted from 24 of 50 phones (48% 95% CI, 35–62%). Surrogate-decision makers, but not patient self-reported, estimates of steps taken per day correlated with smartphone data (surrogates: n = 13, ρ = 0.56, p 0.05 patients: n = 13, ρ = 0.30, p = 0.317). There was a lack of agreement between surrogate-decision maker and patient self-reported subjective estimates of distance walked. Obtaining premorbid physical activity data from the current-generation smartphones was feasible in approximately 50% of patients.
Publisher: Springer Science and Business Media LLC
Date: 31-07-2021
DOI: 10.1007/S11739-021-02816-7
Abstract: Machine learning, in particular deep learning, may be able to assist in the prediction of the length of stay and timing of discharge for in idual patients. Artificial neural networks applied to medical text have previously shown promise in this area. In this study, a previously derived artificial neural network was applied to prospective and external validation datasets. In the prediction of discharge within the next 2 days, when the algorithm was applied to prospective and external datasets, the area under the receiver operator curve for this task were 0.78 and 0.74, respectively. The performance in the prediction of discharge within the next 7 days was more limited (area under the receiver operator curve 0.68 and 0.67). This study has shown that in prospective and external validation datasets the previously derived deep learning algorithms have demonstrated moderate performance in the prediction of which patients will be discharged within the next 2 days. Future studies may seek to further refine or evaluate the effect of the implementation of such algorithms.
Publisher: Elsevier BV
Date: 03-2019
DOI: 10.1016/J.AUCC.2019.01.009
Abstract: Physical activity after intensive care unit (ICU) discharge is challenging to measure but could inform research and practice. A patient's smartphone may provide a novel method to quantify physical activity. We aimed to evaluate the feasibility and accuracy of using smartphone step counts among survivors of critical illness. We performed a prospective observational cohort study in 50 patients who had an ICU length of stay>48 h, owned a smartphone, were ambulatory before admission, and were likely to attend follow-up at 3 and 6 months after discharge. At follow-up, daily step counts were extracted from participants' smartphones and two FitBit pedometers, and exercise capacity (6-min walk test) and quality of life (European Quality of Life-5 Dimensions) were measured. Thirty-nine (78%) patients returned at 3 months and 33 (66%) at 6 months, the median [interquartile range] smartphone step counts being 3372 [1688-5899] and 2716 [1717-5994], respectively. There was a strong linear relationship, with smartphone approximating 0.71 (0.58, 0.84) of FitBit step counts, P < 0.0001, R-squared = 0.87. There were weak relationships between step counts and the 6-min walk test distance. Although smartphone ownership and data acquisition limit the viability of using extracted smartphone steps at this time, mean daily step counts recorded using a smartphone may act as a surrogate for a dedicated pedometer however, the relationship between step counts and other measures of physical recovery remains unclear.
Location: United Kingdom of Great Britain and Northern Ireland
Location: United Kingdom of Great Britain and Northern Ireland
Location: United Kingdom of Great Britain and Northern Ireland
No related grants have been discovered for Samuel Gluck.