Stroke clinical coding education program in Australia and New Zealand.

BACKGROUND: Accurate coded diagnostic data are important for epidemiological research of stroke. OBJECTIVE: To develop, implement and evaluate an online education program for improving clinical coding of stroke. METHOD: The Australia and New Zealand Stroke Coding Working Group co-developed an education program comprising eight modules: rationale for coding of stroke; understanding stroke; management of stroke; national coding standards; coding trees; good clinical documentation; coding practices; and scenarios. Clinical coders and health information managers participated in the 90-minute education program. Pre- and post-education surveys were administered to assess knowledge of stroke and coding, and to obtain feedback. Descriptive analyses were used for quantitative data, inductive thematic analysis for open-text responses, with all results triangulated. RESULTS: Of 615 participants, 404 (66%) completed both pre- and post-education assessments. Respondents had improved knowledge for 9/12 questions (p < 0.05), including knowledge of applicable coding standards, coding of intracerebral haemorrhage and the actions to take when coding stroke (all p < 0.001). Majority of respondents agreed that information was pitched at an appropriate level; education materials were well organised; presenters had adequate knowledge; and that they would recommend the session to colleagues. In qualitative evaluations, the education program was beneficial for newly trained clinical coders, or as a knowledge refresher, and respondents valued clinical information from a stroke neurologist. CONCLUSION: Our education program was associated with increased knowledge for clinical coding of stroke. To continue to address the quality of coded stroke data through improved stroke documentation, the next stage will be to adapt the educational program for clinicians.

Epidemiology of sepsis in cancer patients in Victoria, Australia: a population-based study using linked data.

OBJECTIVE: To determine the clinical characteristics, outcomes and longitudinal trends of sepsis occurring in cancer patients. METHOD: Retrospective study using statewide Victorian Cancer Registry data linked to various administrative datasets. RESULTS: Among 215,763 incident cancer patients, incidence of sepsis within one year of cancer diagnosis was estimated at 6.4%. The incidence of sepsis was higher in men, younger patients, patients diagnosed with haematological malignancies and those with de novo metastatic disease. Of the 13,316 patients with a first admission with sepsis, 55% had one or more organ failures, 29% required care within an intensive care unit and 13% required mechanical ventilation. Treatments associated with the highest sepsis incidence were stem cell/bone marrow transplant (33%), major surgery (4.4%), chemotherapy (1.1%) and radical radiotherapy (0.6%). The incidence of sepsis with organ failure increased between 2008 and 2015, while 90-day mortality decreased. CONCLUSIONS: Sepsis in patients with cancer has high mortality and occurs most frequently in the first year after cancer diagnosis. Implications for public health: The number of cancer patients diagnosed with sepsis is expected to increase, causing a substantial burden on patients and the healthcare system.

Reconciling hospital-acquired complications and CHADx+ in Victorian coded hospital data.

BACKGROUND: The Council of Australian Governments has focused the attention of health service managers and state health departments on a list of hospital-acquired complications (HACs) proposed as the basis of funding adjustments for poor quality of hospital inpatient care. These were devised for the Australian Commission on Safety and Quality in Health Care as a subset of their earlier classification of hospital-acquired complications (CHADx) and designed to be used by health services to monitor safety performance for their admitted patients. OBJECTIVE: To improve uptake of both classification systems by clarifying their purposes and by reconciling the ICD-10-AM code sets used in HACs and the Victorian revisions to the CHADx system (CHADx+). METHOD: Frequency analysis of individual clinical codes with condition onset flag (COF 1) included in both classification systems using the Victorian Admitted Episodes Dataset for 2014/2015 ( n = 2,623,275 separations). Narrative description of the resulting differences in definition of "adverse events" embodied in the two systems. RESULTS: As expected, a high proportion of ICD-10-AM codes used in the HACs also appear in CHADx+, and given the wider scope of CHADx+, it uses a higher proportion of all COF 1 diagnoses than HACs (82% vs. 10%). This leads to differing estimates of rates of adverse events: 2.12% of cases for HACs and 11.13% for CHADx+. Most CHADx classes (70%) are not covered by the HAC system; discrepancies result from the exclusion from HACs of several major CHADx+ groups and from a narrower definition of detailed HAC classes compared with CHADx+. Case exclusion criteria in HACs (primarily mental health admissions) resulted in a very small proportion of discrepancies (0.13%) between systems. DISCUSSION: Issues of purpose and focus of these two Australian systems, HACs for clinical governance and CHADx+ for local quality improvement, explain many of the differences between them, and their approach to preventability, and risk stratification. CONCLUSION: A clearer delineation between these two systems using routinely coded hospital data will assist funders, clinicians, quality improvement professionals and health information managers to understand discrepancies in case identification between them and support their different information needs.