Diagnostic Informatics-The Role of Digital Health in Diagnostic Stewardship and the Achievement of Excellence, Safety, and Value.

Diagnostic investigations (pathology laboratory and medical imaging) aim to: increase certainty of the presence or absence of disease by supporting the process of differential diagnosis; support clinical management; and monitor a patient's trajectory (e. g., disease progression or response to treatment). Digital health can be defined as the collection, storage, retrieval, transmission, and utilization of data, information, and knowledge to support healthcare. Digital health has become an essential component of the diagnostic process, helping to facilitate the accuracy and timeliness of information transfer and enhance the effectiveness of decision-making processes. Digital health is also important to diagnostic stewardship, which involves coordinated guidance and interventions to ensure the appropriate utilization of diagnostic tests for therapeutic decision-making. Diagnostic stewardship and informatics are thus important in efforts to establish shared decision-making. This is because they contribute to the establishment of shared information platforms (enabling patients to read, comment on, and share in decisions about their care) based on timely and meaningful communication. This paper will outline key diagnostic informatics and stewardship initiatives across three interrelated fields: (1) diagnostic error and the establishment of outcomes-based diagnostic research; (2) the safety and effectiveness of test result management and follow-up; and (3) digitally enhanced decision support systems.

The NSW Pathology Atlas of Variation: Part II-The Association of Variation in Emergency Department Laboratory Investigations With Outcomes for Patients Presenting With Chest Pain.

STUDY OBJECTIVE: Laboratory test use varies across emergency departments (EDs), yet little is known about the effect of this variation on outcomes. The aim of this study is 2-fold: to stratify EDs into clusters based on similar test use, and to determine whether the clusters differ in patient operational outcomes among patients presenting to EDs with undifferentiated chest pain. METHODS: We conducted a retrospective cohort study of 222,788 patients presenting with undifferentiated chest pain at 44 EDs across New South Wales, Australia, from January 2017 to September 2018. The operational outcomes measured in this study included ED length of stay, hospital admission, the Emergency Treatment Performance target, and 7- and 15-day all-cause and same-cause ED revisit rates. We performed a hierarchic cluster analysis to identify ED clusters and mixed-effects models to determine the association between the clusters and the operational outcomes. RESULTS: Two ED clusters, moderate users (18 EDs) and high users (26 EDs), were identified. After adjustment for confounders, the median ED length of stay was greater by 15.7% (equivalent to 33.4 minutes) in high versus moderate users (95% confidence interval 6.62 to 25.52 minutes), and high users were less likely to achieve the Emergency Treatment Performance target versus moderate users (odds ratio 0.66; 95% confidence interval 0.50 to 0.86). There were no significant differences between the users in hospital admission and ED revisit rates. CONCLUSION: Our findings suggest that reducing test use may reduce ED length of stay and improve the chance of achieving the Emergency Treatment Performance target.

The NSW Pathology Atlas of Variation: Part I-Identifying Emergency Departments With Outlying Laboratory Test-Ordering Practices.

STUDY OBJECTIVE: Abdominal pain and chest pain are leading reasons for emergency department (ED) presentations, with laboratory tests frequently ordered to aid the diagnostic process. Our study aims to identify EDs with outlying laboratory ordering practices for patients presenting with undifferentiated abdominal pain and chest pain. METHODS: This was a retrospective observational study of 519,597 patients who presented with the complaint of abdominal or chest pain at 44 major hospital EDs across New South Wales, Australia, from January 2017 to September 2018. For each condition, we evaluated the risk-adjusted rate of ordering at least 1 laboratory test and of each of the top 15 ordered tests. We used funnel plots to graph variations in test ordering and identify EDs with outlying test-ordering practices. EDs lying above or below the 99.8% funnel control limits were regarded as outliers. RESULTS: From 3,360,152 unplanned presentations, abdominal pain and chest pain represented 8.8% (n=296,809) and 6.6% (n=222,788) of all cases, respectively. No major outliers were observed for ordering at least one laboratory test; however, variations were observed for individual tests. For abdominal pain, the top 3 tests with the highest ordering variation included glucose (20 outlier EDs), C-reactive protein (10 outliers), and calcium-magnesium-phosphate (7 outliers). For chest pain, the top 3 tests with the highest ordering variation were glucose (21 outlier EDs), C-reactive protein (17 outliers), and liver function test (14 outliers). CONCLUSION: Identifying EDs with outlying laboratory-ordering practices is the first step in initiating context-specific evaluation of whether outlying variations are unwarranted.

Potentially redundant repeat liver function test ordering practices in australian hospitals: A 5-year multicentre retrospective observational study.

BACKGROUND: Repeat Liver Function Tests (LFTs) are often necessary for monitoring purposes, but retesting within a short time interval may suggest potentially redundant repeat test (PRRT) ordering practices. We aimed to determine the proportion of potentially redundant repeat LFT ordering and identify associated factors in hospitals. METHODS: A 5-year (2014-2018) retrospective cohort study in six hospitals in New South Wales, Australia. A total of 131 885 patient admissions with repeat LFTs in the general ward (n = 102 852) and intensive care unit (ICU) (n = 29 033) met the inclusion criteria. Existing guidelines do not support retesting LFT for at least 48-72 hours. We used 24 hours as a conservative minimum retesting interval to examine PRRT ordering. We fit binary logistic regression to identify factors associated with PRRT ordering in two conditions with the highest repeat LFTs. RESULTS: There were a total of 298 567 repeat LFTs (medians of 2 repeats/admission and retesting interval of 25.6 hours) in the general ward and 205 929 (medians of 4 repeats/admission and retesting interval of 24.1 hours) in the ICU. The proportions of PRRT ordering were 35.2% (105 227/298 567) and 47.7% (98 307/205 929) in the general ward and ICU, respectively. The proportions of patients who received at least one PRRT were 52.3% (53 766/102 852) and 83.9% (24 365/29 033) in the general ward and ICU, respectively. Age, gender and the number of comorbidities and procedures were associated with the likelihood of ordering PRRT depending on the settings. CONCLUSION: Repeat LFT testing is common in Australian hospitals, often within 24 hours, despite guidelines not supporting too-early repeat testing. Further research should be conducted to understand whether better adherence to existing guidelines is required, or if there is any case for guidelines to be updated based on certain patient subpopulations.

Evaluating the long-term effects of a data-driven approach to reduce variation in emergency department pathology investigations: study protocol for evaluation of the NSW Health Pathology Atlas of variation.

INTRODUCTION: Variation in test ordering is a major issue in Australia and globally with significant financial and clinical impacts. There is currently a lack of research identifying and remediating variation in the use of pathology tests in emergency departments (EDs). In 2019, NSW Health Pathology introduced the Pathology Atlas of Variation that uses a data-driven tool (the Atlas Analytical Model) to investigate test order variation across New South Wales (NSW) and engage with local health districts (LHDs) to reduce variation. The objectives of this study are to evaluate whether this data-driven approach is associated with: (1) a reduction in test order variation; (2) improvements in patient outcomes and (3) cost benefits, for the five most frequent ED presentations. METHODS AND ANALYSIS: This is a large multisite study including 45 major public hospitals across 15 LHDs in NSW, Australia. The Atlas Analytical Model is a data analytics and visualisation tool capable of providing analytical insights into variation in pathology investigations across NSW EDs, which will be used as feedback to inform LHDs efforts to reduce variation. Interrupted time series analyses using 2 years pre Atlas (2017-2018) and 2 years post Atlas (2021-2022) data will be conducted. Study data will be obtained by linking hospital and laboratory databases. Funnel plots will be used to identify EDs with outlying pathology test ordering practices. The outcome measures include changes in test ordering practices, ED length of stay, hospital admission and cost benefits (total pathology costs per ED encounter). ETHICS AND DISSEMINATION: The study has received ethical approval from the NSW Population and Health Service Research Ethics Committee (reference, 2019/ETH00184). The findings of the study will be published in peer-reviewed journals and disseminated via presentations at conferences. We will also engage directly with key stakeholders to disseminate the findings and to inform policies related to pathology testing in the ED.

An evaluation of variation in pathology investigations and associated factors for adult patients presenting to emergency departments with chest pain: An observational study.

OBJECTIVE: To determine variation in pathology test ordering practices and identify associated factors for adult patients presenting to emergency departments (ED) with chest pain and subsequently admitted with ischaemic heart disease. METHODS: A retrospective study across six hospital EDs in New South Wales, Australia. A total of 6769 patient presentations between January 2014 and December 2017 met the inclusion criteria. Ordered pathology tests were grouped into three categories based on Australasian College for Emergency Medicine and the Royal College of Pathologists of Australasia recommendations: category I (no restriction in ordering), category II (can be ordered after consulting a supervisor) and category III (not for routine ordering in ED). The primary outcome was the proportion of category III test ordering across study EDs. Factors associated with category III test ordering were identified using a logistic regression. RESULTS: A total of 34 936 pathology tests were ordered: 65.6% (n = 22 932) were category I/II tests and 34.4% (n = 12 004) were category III tests. Five tests (Calcium Magnesium Phosphate, Coagulation Studies, Lipase, C-reactive Protein and Blood Gas tests) accounted for 84.7% of all category III tests. The proportion of category III tests ordered varied by hospitals from 29.8% to 45.9%. The proportion of patients with at least one category III test was 76.3% (range across hospitals: 68.3%-95.6%). Increasing age, presentation to an ED at night, and those in an imminently life-threatening triage category were significantly associated with increased likelihood of category III test ordering. The proportion of category III tests decreased over time. EDs in medium and/or regional hospitals were more likely to order a category III test. CONCLUSION: Pathology investigations for patients presenting with chest pain varied significantly across EDs suggesting opportunities to improve standardisation of test ordering practices.

Missed detection of significant positive and negative shifts in gentamicin assay: implications for routine laboratory quality practices.

INTRODUCTION: A product recall was issued for the Roche/Hitachi Cobas Gentamicin II assays on 25th May 2016 in Australia, after a 15 - 20% positive analytical shift was discovered. Laboratories were advised to employ the Thermo Fisher Gentamicin assay as an alternative. Following the reintroduction of the revised assay on 12th September 2016, a second reagent recall was made on 20th March 2017 after the discovery of a 20% negative analytical shift due to erroneous instrument adjustment factor. MATERIALS AND METHODS: The practices of an index laboratory were examined to determine how the analytical shifts evaded detection by routine internal quality control (IQC) and external quality assurance (EQA) systems. The ability of the patient result-based approaches, including moving average (MovAvg) and moving sum of outliers (MovSO) approaches in detecting these shifts were examined. RESULTS: Internal quality control data of the index laboratory were acceptable prior to the product recall. The practice of adjusting IQC target following a change in assay method resulted in the missed negative shift when the revised Roche assay was reintroduced. While the EQA data of the Roche subgroup showed clear negative bias relative to other laboratory methods, the results were considered as possible 'matrix effect'. The MovAvg method detected the positive shift before the product recall. The MovSO did not detect the negative shift in the index laboratory but did so in another laboratory 5 days before the second product recall. CONCLUSIONS: There are gaps in current laboratory quality practices that leave room for analytical errors to evade detection.

The effect of laboratory testing on emergency department length of stay: a multihospital longitudinal study applying a cross-classified random-effect modeling approach.

OBJECTIVES: The objective was to examine the relationship between laboratory testing (including test volume and turnaround time [TAT]) and emergency department (ED) length of stay (LOS), using linked patient-level data from four hospitals across 4 years. METHODS: This was a retrospective, multisite cohort study of patients presenting to any one of four EDs in New South Wales, Australia, during a 2-month period (August and September) in 2008, 2009, 2010, and 2011. Data from ED information systems were linked to laboratory test data. A cross-classified random-effect modeling approach was applied to identify factors affecting ED LOS, taking into account the correlation between patients' presentations at the same hospital and/or in the same calendar year. Number of test order episodes (tests ordered at one point in time during the ED stay) and TAT (time from laboratory order receipt to result available) were examined. RESULTS: As the number of test order episodes increased, so did the duration of patient ED LOS (p < 0.0001). For every five additional tests ordered per test order episode, the median ED LOS increased by 10 minutes (2.9%, p < 0.0001); each 30-minute increase in TAT was, on average, associated with a 5.1% (17 minutes; p < 0.0001) increase in ED LOS, after adjustment for other factors. Patients presenting to the ED at night (7 p.m. to 7 a.m.) had longer stays than those presenting during the daytime, although the median TATs at nights were shorter than those during the daytime. CONCLUSIONS: Laboratory testing has a direct effect on patients' LOS in ED. Laboratory TAT, number of testing episodes, and test volume influence ED LOS. Targeted increases of ED resources and staffing after-hours may also contribute to reductions in ED LOS.

What is the effect of electronic pathology ordering on test re-ordering patterns for paediatric patients?

Electronic ordering systems have the potential to enhance the efficient utilisation of pathology services. The aim of this study was to assess the effect of electronic pathology ordering on repeat test ordering for paediatric patients (ages 0 to 18 years) who were in intensive care units (ICUs) and non-ICU wards. The dataset described 85,728 pathology tests ordered for 5,073 children before and after the implementation of electronic ordering. This study showed that, for children in ICUs, the repeat test order rate was significantly lower for electronic orders than for paper-based orders. Similarly, the rate of repeat tests ordered within short intervals (up to 23-hours), for children older than one-year in non-ICU wards, was lower for electronic ordering than for paper ordering. The proportion of repeat tests occurring within one-hour of the previous test was consistently lower for tests ordered using electronic ordering than it was for tests ordered using the paper based system for patients older than one-year in all wards and for patients under one-year in ICUs. These results suggest that features of the electronic system, including alerts about previously ordered tests and the availability of information about previous orders, can help clinicians to identify and reduce unnecessary repeat tests.

Monitoring health IT integration--the effect of an EMR on laboratory service timeliness across six Australian hospitals.

The Electronic Medical Record (EMR) incorporates computerised provider order entry systems which allow clinicians to order diagnostic tests electronically, thus eliminating the need for cumbersome handwritten orders. In many situations the EMR relies on a manual transition of information across systems (e.g., integration with the Laboratory Information System). This study, based in a laboratory setting requiring such a transition across systems, aimed to compare the data entry time (from when a specimen arrives in the Central Specimen Reception [CSR] area of the laboratory, to when it is forwarded on for processing), along with a laboratory turnaround time (TAT) (from the time a specimen is received to the time a verified result is issued) for paper and EMR orders, for two high volume tests, across six hospitals. Results showed that the median data entry time for all hospitals combined, was three minutes shorter for EMR entered orders than paper orders. This difference was consistent and significant for Electrolytes, Urea, Creatinine (EUC) and Automated Differential (including full blood count) tests in 2010 and 2011. These decreases contributed to significantly lower median Laboratory TATs for EMR orders (for EUC tests the difference in medians was 12 minutes in 2010 and six minutes in 2011; for Automated Differential tests, the difference was four minutes in 2010 and two minutes in 2011).

Monitoring the impact of the electronic medical record on the quality of laboratory test ordering practices.

The aim of this study was to examine the impact of the Electronic Medical Record (EMR) on the quality of laboratory test orders made by clinicians. The study assessed the type and frequency of pre-analytical laboratory test order errors that were associated with the EMR across three hospitals and one pathology service. This involved a retrospective audit of the laboratory error logs for the period 1 March 2010 to 9 October 2011. Test order problems associated with the EMR occurred at a total rate of 1.34 per 1000 test order episodes across the three hospitals. In the majority of cases these errors were caused by the inappropriate use of the EMR system by clinicians. The errors resulted in increased data entry time for laboratory staff in the Central Specimen Reception area and led to a median increase of 181 minutes in test turnaround times for those test orders. The study highlights the importance of monitoring and comparing the impact of EMR systems in different locations over time in order to identify (and act upon) factors that can adversely impact on the effectiveness of pathology laboratory processes.

The effect of electronic pathology ordering in emergency departments on one aspect of test turn around time: a failure time analysis.

Electronic ordering systems have the potential to enhance the effective and efficient utilisation of pathology services. This study examined the influence of electronic ordering of pathology tests in four emergency departments on data entry times, a contributing factor to test turnaround time using failure time analysis. Data relating to tests ordered for 50,854 emergency department patients at four hospitals were analysed. The introduction of electronic test ordering significantly reduced turnaround time associated with laboratory data entry at the four hospitals, but there was significant variation between hospitals. Investigation of the impact of electronic ordering on efficiency of pathology services must take into account specific aspects of turnaround time measurement.

Examination of changes in pathology tests ordered by Diagnosis-Related Group (DRGs) following CPOE introduction.

Electronic test ordering, via the Electronic Medical Record (EMR), which incorporates computerised provider order entry (CPOE), is widely considered as a useful tool to support appropriate pathology test ordering. Diagnosis-related groups (DRGs) are clinically meaningful categories that allow comparisons in pathology utilisation by patient groups by controlling for many potentially confounding variables. This study used DRG data linked to pathology test data to examine changes in rates of test ordering across four years coinciding with the introduction of an EMR in six hospitals in New South Wales, Australia. This method generated a list of high pathology utilisation DRGs. We investigated patients with a Chest pain DRG to examine whether tests rates changed for specific test groups by hospital emergency department (ED) pre- and post-EMR. There was little change in testing rates between EDs or between time periods pre- and post-EMR. This is a valuable method for monitoring the impact of EMR and clinical decision support on test order rates.