Health information management : journal of the Health Information Management Association of Australia最新文献

Background: Healthcare data frequently lack the specificity level needed to achieve clinical and operational objectives such as optimising bed management. Pneumonia is a disease of importance as it accounts for more bed days than any other lung disease and has a varied aetiology. The condition has a range of SNOMED CT concepts with different levels of specificity.

Objective: This study aimed to quantify the importance of the specificity of an SNOMED CT concept, against well-established predictors, for forecasting length of stay for pneumonia patients.

Method: A retrospective data analysis was conducted of pneumonia admissions to a tertiary hospital between 2011 and 2021. For inclusion, the primary diagnosis was a subtype of bacterial or viral pneumonia, as identified by SNOMED CT concepts. Three linear mixed models were constructed. Model One included known predictors of length of stay. Model Two included the predictors in Model One and SNOMED CT concepts of lower specificity. Model Three included the Model Two predictors and the concepts with higher specificity. Model performances were compared.

Results: Sex, ethnicity, deprivation rank and Charlson Comorbidity Index scores (age-adjusted) were meaningful predictors of length of stay in all models. Inclusion of lower specificity SNOMED CT concepts did not significantly improve performance (ΔR² = 0.41%, p = .058). SNOMED CT concepts with higher specificity explained more variance than each of the individual predictors (ΔR² = 4.31%, p < .001).

Conclusion: SNOMED CT concepts with higher specificity explained more variance in length of stay than a range of well-studied predictors.

Implications: Accurate and specific clinical documentation using SNOMED CT can improve predictive modelling and the generation of actionable insights. Resources should be dedicated to optimising and assuring clinical documentation quality at the point of recording.

Background: The health and well-being of children in the first 2000 days has a lasting effect on educational achievement and long-term chronic disease in later life. However, the lack of integration between high-quality data, analytic capacity and timely health improvement initiatives means practitioners, service leaders and policymakers cannot use data effectively to plan and evaluate early intervention services and monitor high-level health outcomes.

Objective: Our exploratory study aimed to develop an in-depth understanding of the system and clinical requirements of a state-wide paediatric learning health system (LHS) that uses routinely collected data to not only identify where the inequities and variation in care are, but also to also inform service development and delivery where it is needed most.

Method: Our approach included reviewing exemplars of how administrative data are used in Australia; consulting with clinical, policy and data stakeholders to determine their needs for a child health LHS; mapping the existing data points collected across the first 2000 days of a child's life and geospatially locating patterns of key indicators for child health needs.

Results: Our study identified the indicators that are available and accessible to inform service delivery and demonstrated the potential of using routinely collected administrative data to identify the gap between health needs and service availability.

Conclusion: We recommend improving data collection, accessibility and integration to establish a state-wide LHS, whereby there is a streamlined process for data cleaning, analysis and visualisation to help identify populations in need in a timely manner.

Background: The implementation of emerging technologies has resulted in an increase of data breaches in healthcare organisations, especially during the COVID-19 pandemic. Health information and cybersecurity managers need to understand if, and to what extent, breach types and locations are associated with their organisation's business type.

Objective: To investigate if breach type and breach location are associated with business type, and if so, investigate how these factors affect information systems and protected health information in for-profit versus non-profit organisations.

Method: The quantitative study was performed using chi-square tests for association and post-hoc comparison of column proportions analysis on an archival data set of reported healthcare data breaches from 2020 to 2022. Data from the Department of Health and Human Services website was retrieved and each organisation classified as for-profit or non-profit.

Results: For-profit organisations experienced a significantly higher number of breaches due to theft, and non-profit organisations experienced a significantly higher number of breaches due to unauthorised access. Furthermore, the number of breaches that occurred on laptops and paper/films was significantly higher in for-profit organisations.

Conclusion: While the threat level of hacking techniques is the same in for-profit and non-profit organisations, certain breach types are more likely to occur within specific breach locations based on the organisation's business type. To protect the privacy and security of medical information, health information and cybersecurity managers need to align with industry-leading frameworks and controls to prevent specific breach types that occur in specific locations within their environments.

Objective: This article describes the first digital clinical information system tailored to support the operational needs of a forensic unit in Greece and to maintain its archives.

Method: The development of our system was initiated towards the end of 2018, as a close collaboration between the Medical School of the University of Crete and the Forensic Medicine Unit of the University Hospital of Heraklion, Crete, where forensic pathologists assumed active roles during the specification and testing of the system.

Results: The final prototype of the system was able to manage the life cycle of any forensic case by allowing users to create new records, assign them to forensic pathologists, upload reports, multimedia and any required files; mark the end of processing, issue certificates or appropriate legal documents, produce reports and generate statistics. For the first 4 years of digitised data (2017-2021), the system recorded 2936 forensic examinations categorised as 106 crime scene investigations, 259 external examinations, 912 autopsies, 102 post-mortem CT examinations, 804 histological examinations, 116 clinical examinations, 12 anthropological examinations and 625 embalmings.

Conclusion: This research represents the first systematic effort to record forensic cases through a digital clinical information system in Greece, and to demonstrate its effectiveness, daily usability and vast potential for data extraction and for future research.

Background: Historically, national programs for collecting stroke data in Australia required the use of multiple online tools. Clinicians were required to enter overlapping variables for the same patient in the different databases. From 2013 to 2016, the Australian Stroke Data Tool (AuSDaT) was built as an integrated data management solution.

Objective: In this article, we have described the development, implementation, and evaluation phases of establishing the AuSDaT.

Method: In the development phase, a governance structure with representatives from different data collection programs was established. Harmonisation of data variables, drawn from six programs used in hospitals for monitoring stroke care, was facilitated through creating a National Stroke Data Dictionary. The implementation phase involved a staged deployment for two national programs over 12 months. The evaluation included an online survey of people who had used the AuSDaT between March 2018 and May 2018.

Results: By July 2016, data entered for an individual patient was, for the first time, shared between national programs. Overall, 119/422 users (90% female, 61% aged 30-49 years, 57% nurses) completed the online evaluation survey. The two most positive features reported about the AuSDaT were (i) accessibility of the system (including simultaneous user access), and (ii) the ability to download reports to benchmark local data against peer hospitals or national performance. More than three quarters of respondents (n = 92, 77%) reported overall satisfaction with the data collection tool.

Conclusion: The AuSDaT reduces duplication and enables users from different national programs for stroke to enter standardised data into a single system.

Implications: This example may assist others who seek to establish a harmonised data management solution for different disease areas where multiple programs of data collection exist. The importance of undertaking continuous evaluation of end-users to identify preferences and aspects of the tool that are not meeting current requirements were illustrated. We also highlighted the opportunities to increase interoperability, utility, and facilitate the exchange of accurate and meaningful data.

Background: The International Classification of Diseases (ICD) is widely used by clinical coders worldwide for clinical coding morbidity data into administrative health databases. Accordingly, hospital data quality largely depends on the coders' skills acquired during ICD training, which varies greatly across countries.

Objective: To characterise the current landscape of international ICD clinical coding training.

Method: An online questionnaire was created to survey the 194 World Health Organization (WHO) member countries. Questions focused on the training provided to clinical coding professionals. The survey was distributed to potential participants who met specific criteria, and to organisations specialised in the topic, such as WHO Collaborating Centres, to be forwarded to their representatives. Responses were analysed using descriptive statistics.

Results: Data from 47 respondents from 26 countries revealed disparities in all inquired topics. However, most participants reported clinical coders as the primary person assigning ICD codes. Although training was available in all countries, some did not mandate training qualifications, and those that did differed in type and duration of training, with college or university degree being most common. Clinical coding certificates most frequently entailed passing a certification exam. Most countries offered continuing training opportunities, and provided a range of support resources for clinical coders.

Conclusion: Variability in clinical coder training could affect data collection worldwide, thus potentially hindering international comparability of health data.

Implications: These findings could encourage countries to improve their resources and training programs available for clinical coders and will ultimately be valuable to the WHO for the standardisation of ICD training.

Background: Standardised terminologies and classification systems play an increasingly important role in the continuous work towards high quality patient care. Currently, a standardised terminology for nutrition care, the Nutrition Care Process (NCP) Terminology (NCPT), is being implemented across the world, with terms for four steps: Nutrition Assessment (NA), Nutrition Diagnosis (ND), Nutrition Intervention (NI) and Nutrition Monitoring and Evaluation (NME).

Objective: To explore associations between individual and contextual factors and implementation of a standardised NCPT among Swedish dietitians.

Method: A survey was completed by 226 dietitians, focussing on: (a) NCPT implementation level; (b) individual factors; and (c) contextual factors. Associations between these factors were explored through a two-block logistic regression analysis.

Results: Contextual factors such as intention from management to implement the NCPT (OR (odds ratio) ND 15.0, 95% Confidence Interval (CI) 3.9-57.4, NME 3.7, 95% CI 1.1-13.0) and electronic health record (EHR) headings from the NCPT (OR NI 3.6, 95% CI 1.4-10.7, NME 3.8, 95% CI 1.1-11.5) were associated with higher implementation. A positive attitude towards the NCPT (model 1 OR ND 3.8, 95% CI 1.5-9.8, model 2 OR ND 5.0, 95% CI 1.4-17.8) was also associated with higher implementation, while other individual factors showed less association.

Conclusion: Contextual factors such as intention from management, EHR structure, and pre-defined terms and headings are key to implementation of a standardised terminology for nutrition and dietetic care.

Implications for practice: Clinical leadership and technological solutions should be considered key areas in future NCPT implementation strategies.

Background: Medical certification of cause of death (MCCD) provides valuable data regarding disease burden in a community and for formulating health policy. Inaccurate MCCDs can significantly impair the precision of national health information.

Objective: To evaluate the accuracy of cause of death certificates prepared at two tertiary cancer care hospitals in Northern India during the study period (May 2018 to December 2020).

Method: A retrospective observational study at two tertiary cancer care hospitals in Varanasi, India, over a period of two and a half years. Medical records and cause of death certificates of all decedents were examined. Demographic characteristics, administrative details and cause of death data were collected using the WHO recommended death certificates. Accuracy of death certification was validated by electronic medical records and errors were graded.

Results: A total of 778 deaths occurred in the two centres during the study period. Of these, only 30 (3.9%) certificates were error-free; 591 (75.9%) certificates had an inappropriate immediate cause of death; 231 (29.7%) certificates had incorrectly labelled modes of death as the immediate cause of death; and 585 (75.2%) certificates had an incorrect underlying cause of death. The majority of certificates were prepared by junior doctors and were significantly associated with higher certification errors.

Conclusion: A high rate of errors was identified in death certification at the cancer care hospitals during the study period. Inaccurate MCCDs related to cancers can potentially influence cancer statistics and thereby affect policy making for cancer control.

Implications: This study has identified the pressing need for appropriate interventions to improve quality of certification through training of doctors.

Background: Administrative data are used extensively for research purposes, but there remains limited information on the quality of these data for identifying comorbidities related to stroke.

Objective: To compare the prevalence of comorbidities of stroke identified using International Classification Diseases, Australian Modification (ICD-10-AM) or Anatomical Therapeutic Chemical codes, with those from (i) self-reported data and (ii) published studies.

Method: The cohort included patients with stroke or transient ischaemic attack admitted to hospitals (2012-2016; Victoria and Queensland) in the Australian Stroke Clinical Registry (N = 26,111). Data were linked with hospital and pharmaceutical datasets to ascertain comorbidities using published algorithms. The sensitivity, specificity, and positive predictive value of these comorbidities were compared with survey responses from 623 patients (reference standard). An indirect comparison was also performed with clinical data from published stroke studies.

Results: The sensitivity of hospital ICD-10-AM data was poor for most comorbidities, except for diabetes (93.0%). Specificity was excellent for all comorbidities (87-96%), except for hypertension (70.5%). Compared to published stroke studies (3 clinical trials and 1 incidence study), the prevalence of diabetes and atrial fibrillation in our cohort was similar using ICD-10-AM codes, but lower for dyslipidaemia and anxiety/depression. Whereas in the pharmaceutical dispensing data, the sensitivity was excellent for dyslipidaemia (94%) and modest for anxiety/depression (77%). In the pharmaceutical data, specificity was modest for hypertension (78%) and anxiety or depression (76%), but specificity was poor for dyslipidaemia (19%) and heart disease (46%).

Conclusion: Variation was observed in the reporting of comorbidities of stroke in administrative data, and consideration of multiple sources of data may be necessary for research. Further work is needed to improve coding and clinical documentation for reporting of comorbidities in administrative data.