Lee Nedkoff

Background: Accurate and complete clinical documentation underpins the assignment of International Classification of Disease codes used for epidemiological research, hospital activity based funding, and health service planning. Objective: To develop, implement, and evaluate an education program for clinicians and clinical documentation specialists (CDS) to improve clinical documentation of stroke. Method: An education program to improve clinical documentation of stroke was developed by the Australia and New Zealand Stroke Coding Working Group. Eligible participants were clinicians (doctors, nurses, and allied health) and CDS in Australia or New Zealand. The education program comprised 4 modules in a pre-recorded 10-minute educational video. Surveys were administered before and after the educational video to evaluate knowledge (Kirkpatrick level 2) and obtain feedback. Quantitative data were summarised using descriptive statistics. Open-text responses to the feedback survey were analysed using inductive thematic analysis. Results: Among 72 eligible participants, 41 (57%) completed the pre- and post-educational knowledge assessment surveys ( n = 35 clinicians, n = 6 CDS). Compared with the pre-education survey, the median number of correct responses significantly increased in the post-education survey (pre: 3 [interquartile range (IQR) 2–4]; post: 5 [IQR 4–5]; p < 0.001). Most respondents (>90%) were satisfied with the education program, stating it provided “practical and transferrable knowledge” and that the education was “quick, clear, concise.” Conclusion: Our education program was associated with an increased knowledge of appropriate clinical documentation of stroke. Ongoing monitoring of clinical coding and clinical documentation is required to ascertain whether the education of the participants translates to improved clinical coding of stroke. Implications for health information management practice: Accurate and complete clinical documentation directly impacts clinical coding, which in turn affects reimbursement, patient safety, and data quality for epidemiological research, resource allocation, and health policy decision-making.

Background: Stroke mortality rates have declined in recent decades; however, data on contemporary drivers of this trend are limited. This study compared the contribution of trends in stroke event rates and 30-day case fatality to declines in stroke mortality from 2002 to 2018. Methods: Linked hospitalization and mortality data were obtained from Western Australia (WA), England, New Zealand, British Columbia (BC), and Ontario. Age-standardized and age-specific stroke mortality and event rates and 30-day case fatality were calculated and age-adjusted trends estimated from Poisson and binomial regression models. The relative contribution of trends in stroke events and 30-day case fatality to trends in stroke mortality were calculated. Results: There were 2 248 242 stroke events identified. Age-adjusted reductions in event rates ranged from −0.96%/year [95% confidence interval (CI) − 1.22, 0.70%] in men in WA to −2.51%/year (95% CI −2.61, −2.40%) in women in Ontario. Age-standardized 30-day case fatality was highest in England in 2002 (men 43.7%, women 45.5%), but declined at a greater rate than in other jurisdictions. Declines in stroke mortality ranged from −3.3%/year to −5.5%/year. Reductions in 30-day case fatality were the major contributor to declines in stroke mortality [range: men, 63.5% (Ontario)–80.9% (England); women, 55.3% (BC)–73.1% (England)]. In people aged <65 years, stroke mortality declines were almost completely driven by reductions in 30-day case fatality with increasing or attenuated event rates among those aged 35–64 years. Conclusion: Improvements in 30-day case fatality had a greater impact on stroke mortality than trends in event rates, suggesting that further gains could be achieved with targeted prevention. Adverse trends in event rates in people aged <65 years could signal future increases in stroke mortality.

Background: Despite advances in acute coronary syndrome (ACS) management, contemporary data assessing long-term prognosis after ST-segment elevation myocardial infarction (STEMI), non-STEMI (NSTEMI) and unstable angina (UA) are scarce. Methods: Linked hospitalisation and mortality data identified all 30-day survivors of index STEMI, NSTEMI and UA hospitalisation in Western Australia between 2002 and 2019. We assessed the cumulative 5-year incidence of major adverse cardiovascular events (MACE), comprising non-fatal MI, stroke, heart failure hospitalisation or cardiovascular death and separately all-cause death in 30-day survivors of index ACS hospitalisation. Associations were examined using Cox proportional hazards modelling after adjustment for potential confounders. Results: The cohort totalled 73 321 patients with ACS, 65% males, 22.3% with STEMI, 43.2% NSTEMI and 34.6% UA with mean age 63.2, 68.8 and 66.4 years, respectively. Patients with NSTEMI and UA compared with STEMI were more likely to be female with additional comorbidities. Cumulative 5-year MACE rates after NSTEMI were 29.7% vs 19.4% and 19.9% after STEMI and UA, respectively (log-rank p<0.001), while all-cause mortality was 29.8% vs 15.9% and 17.2%, respectively (log-rank p<0.001). There was no temporal improvement in multivariable-adjusted risk of outcomes for all ACS subtypes throughout the study period. The adjusted HRs for MACE and all-cause death were 1.5-fold or higher in males and females with STEMI or NSTEMI versus UA. Conclusions: Long-term risk of MACE and all-cause death remains high and unchanged among 30-day survivors of all ACS subtypes in the recent era. Long-term surveillance and optimal secondary prevention are important in survivors of all ACS subtypes.

Introduction: Rheumatic heart disease (RHD) is the acquired autoimmune heart valve damage resulting from untreated infection with the Streptococcus pyogenes bacterium, which affects people experiencing socioeconomic disadvantage globally. This study measured RHD‐associated major adverse cardiovascular events (MACE) and the increased risk associated with pregnancy among women diagnosed with RHD. Material and Methods: Population‐level analysis of all births to women with RHD in four Australian jurisdictions was conducted, which covered 71% of the total population and 88% of the Aboriginal and Torres Strait Islander population (a group who experience some of the highest RHD rates reported globally). A retrospective cohort study using linked RHD register and midwives, hospital, and death data collections was designed. Females with at least one birth record aged 12–44 years, whose first RHD diagnosis occurred prior to 20 weeks' gestation and age < 35 years, were identified during 2002–2017. Survival methods (incorporating mixed effects and time‐varying covariates) estimated proportions and hazard ratios. Probability of hospitalization for new RHD‐associated MACE was measured for pulmonary hypertension secondary to left heart disease, heart failure, valvular surgery, stroke, infective endocarditis, atrial fibrillation, acute pulmonary edema, cardiomyopathy, and/or death. Results: We identified 558 pregnancies in women with uncomplicated RHD (345 women) and 88 pregnancies in women with complicated RHD (60 women). During pregnancy, 4.5% of women with uncomplicated RHD and 31.8% of women with complicated RHD experienced new RHD‐associated MACE. Risk of RHD‐associated MACE was three‐ to six‐fold higher during periods of pregnancy (compared with non‐pregnancy) and did not differ by RHD stage. Conclusions: After 20 weeks of gestation, women with RHD experienced RHD‐associated MACE outcomes at frequencies that were contingent upon RHD stage at 20 weeks of gestation. Awareness of RHD status before 20 weeks of gestation, especially in regions where RHD is endemic, is critical for ensuring women's cardiovascular health in pregnancy and beyond.

BACKGROUND: Aboriginal Australians experience a disproportionate burden of acute coronary syndrome (ACS), contributing to health disparities. Evidence on changes in ACS incidence is limited. This study investigates temporal changes in the gap between Aboriginal and non-Aboriginal populations in ACS incidence and case fatality within the context of the Closing the Gap initiative, a national policy framework to reduce inequalities. METHODS: This population-based cohort study used linked hospital and mortality data for Western Australian residents aged 25 to 84 years. Incident ACS cases (2003–2020) were identified using a fixed 18-year lookback. Age-standardized incidence rates were calculated using prevalence-adjusted denominators and direct standardization. Average annual percentage changes in incidence, case fatality, and Aboriginal-to-non-Aboriginal incidence rate ratios were estimated from Poisson regression, stratified by sex and age-group (25–54, 55–84 years). Estimates were derived separately for pre–Closing the Gap (2003–2008) and post–Closing the Gap periods (2009–2016; 2017–2020). RESULTS: The annual at-risk population was 1 215 300 in 2003 and 1 765 564 in 2020. We identified 4097 Aboriginal (mean age: 52.3, 40.8% women) and 64 805 non-Aboriginal (mean age: 65.1, 31.3% women) incident ACS cases. Aboriginal people had a higher prevalence of diabetes (58.5% versus 26.4%) and chronic kidney disease (27.5% versus 10.9%). ACS rates declined across all Aboriginal age/sex groups, although only significant between 2009 and 2016 for older men (–4.9%/y [95% CI, −8.9% to −0.7%]) and younger women (–4.8%/y [95% CI, –8.7% to –0.7%]). There were limited changes in incidence rate ratios between 2003 to 2008 and 2017 to 2020, respectively, in men (25–54 years, 5.2–5.6; 55–84 years, 2.9–2.1) and women (25–54 years, 10.3–10.0; 55–84 years, 2.9–3.6). Case fatality remained 20% to 50% higher among Aboriginal than non-Aboriginal people across periods and age-sex strata (risk ratios, 1.2–1.5). CONCLUSIONS: Despite some evidence of declines in ACS incidence among Aboriginal groups, disparities with non-Aboriginal people persisted. Sustained Aboriginal-led efforts are needed to address underlying determinants and reduce the gap.

Introduction: Sustainable and low-cost data systems for national and global surveillance of stroke are urgently needed to address the growing burden of stroke. Routinely collected health data (including registries and administrative data) are proliferating at a rapid pace, offering promise for systematic and enduring global stroke surveillance. However, several challenges exist in utilising these routinely collected data from across the globe for global stroke surveillance, such as non-standardised definitions and coding, missingness of data, and lack of transparent or reproducible methods. We aim to describe the vision and methods for a new global collaboration to leverage and harmonise population-level health data for global stroke surveillance. Methods: The International Network for Standardised Population Insights and Real-world Evidence for STROKE (INSPIRE-STROKE) was established in October 2023 and currently includes 39 collaborators from 16 countries. The vision of INSPIRE-STROKE is to develop new methods that will harmonise and combine health databases across the world to facilitate reliable and robust multi-country stroke surveillance. Through this scientific community, we are initially collaborating to: (1) summarise existing methods for calculating and reporting measures of post-stroke outcomes using routinely collected health data; (2) develop consensus-based standards for analysing routinely collected health data on post-stroke outcomes; and (3) conduct proof-of-concept studies to align variables/definitions in routinely collected health data and create standardised statistical code to measure post-stroke outcomes (e.g., medication adherence, readmissions, and mortality) according to consensus-based definitions. Conclusion: INSPIRE-STROKE will support more reliable investigations into country-level trends in stroke incidence and outcomes, by leveraging routinely collected health data at a global scale. The large and diverse data compiled for INSPIRE-STROKE could facilitate exploration of rare stroke outcomes, particularly among under-represented groups (e.g., pregnant women, children). INSPIRE-STROKE will strengthen health policy and resource planning by providing high-quality evidence to improve access to stroke care and maximise patient outcomes.

Background Switching from a conventional to a high-sensitivity cardiac troponin (hs-cTn) assay enables detection of smaller amounts of myocardial damage, but the clinical benefit is unclear. We investigated whether switching to a hs-cTnI assay with a sex-specific 99th centile diagnostic threshold was associated with lower 1-year death or new myocardial infarction (MI) in patients with suspected acute coronary syndrome (ACS). Methods This pre–post study included nine tertiary hospitals in Australia. During the pre-hs-cTn period, all hospitals used conventional troponin assays, and during the postperiod, four switched to using hs-cTnI. Participants were ≥20 years old and presenting to emergency departments (EDs) with suspected ACS between March 2011 and November 2015. Outcomes were determined using linked administrative data and compared using Kaplan-Meier and Cox regression analyses. Results We identified 179 681 consecutive patients (62 (SD 19) years, 47% women), 87 019 (48%) during the preperiod, and 92 662 (52%) during the postperiod. Following the switch to hs-TnI, the proportion of patients diagnosed with new MI was not significantly different (3.9% postperiod vs 4.2% preperiod; p=0.08) while diagnoses of unstable angina were lower (1.5% postperiod vs 2.5% preperiod; pConclusion The use of an hs-cTnI assay in an ED population with suspected ACS was associated with lower mortality at 1 year.

Background: Research priority setting projects provide a method to engage stakeholders in the prioritisation of research activities. We conducted a priority setting project to identify priorities for research into the primary and secondary prevention of stroke. Methods: A modified James Lind Alliance method was used for this project undertaken in Australia and New Zealand with two online surveys (September–November 2021 and May‐June 2022) and an online workshop (August 2022). The main question addressed was ‘What question about preventing stroke would you like to see answered by researchers?’ Responses to Survey 1 were refined and reviewed to identify evidence uncertainties. Questions with uncertain evidence were presented in Survey 2 where participants rated the importance of questions. Quantitative analysis of the importance ratings identified highly rated questions. These questions were taken to the online workshop with two rounds of facilitated discussion to create a final list of priorities. A postworkshop evaluation questionnaire explored user’s perceptions of the process. Results: In Survey 1, 375 people proposed > 700 research questions. These were refined to 134 questions that were checked against evidence with 47 determined to be unanswered and distributed for consideration in Survey 2. Respondents to Survey 2 ( n = 97) rated 24 of the 47 questions highly that were then discussed in the online workshop ( n = 16 participants). There was agreement on the most highly rated question ‘How can we improve early detection and measurement of stroke risk?’ but limited agreement on the remaining questions. Participants favoured keeping all questions but presenting them thematically. The final list includes 22 questions under behavioural; pharmacological/clinical; structural; policy; individual; population and secondary prevention themes. Participants rated the workshop experience as acceptable. Conclusion: A suite of research priorities for the primary and secondary prevention of stroke were identified by a broad range of stakeholders including people with lived experience of stroke, the public and health professionals.

Purpose: Measures of disease burden using hospital administrative data are susceptible to over-inflation if the patient is transferred during their episode of care. We aimed to identify and compare measures of coronary heart disease (CHD) and myocardial infarction (MI) episodes using six algorithms that account for transfers. Patient and Methods: We used person-linked hospitalisations for CHD and MI for 2000– 2016 in Western Australia based on the interval between discharge and subsequent admission (date, datetime algorithms), pathway (admission source, discharge destination) and any combination to generate machine learning models (random forest [RF], gradient boosting machine [GBM]). The date and datetime algorithms used deidentified patient identifiers to identify records belonging to the same individual. We calculated counts, age-standardised rates (ASR) and age-adjusted trends for CHD and MI for each algorithm. Results: Counts of CHD increased from 11,733 in 2000 to 13,274 in 2016, while MI increased from 2605 to 4480 using the date algorithm. Correspondingly ASR for CHD decreased from 2086.2 to 1463.1 while MI increased from 468.2 to 498.1 per 100,000 person-years. ASR for CHD and MI for datetime algorithm were consistently 1– 2% higher than the date algorithm. Differences in ASR of CHD and MI counts increased over time with the admission source, RF and GBM algorithms relative to the date algorithm. Age-adjusted trends in CHD and MI episode rates using RF and GBM differed significantly from all other algorithms. Only 86.7% and 87.6% of MI episodes identified by the date algorithm were identified by the admission source and discharge destination algorithms, respectively. Conclusion: The date and datetime algorithms produced the most valid measures of CHD and MI episodes. Findings underscore the importance of identifying admission and discharge dates/times belonging to the same individual in enumerating these episodes.