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

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.

Background: The percentage of total body surface area (%TBSA) burned and burn depth provide valuable information on burn injury severity.

Objective: This study investigated the concordance between The International Statistical Classification of Diseases and Related Health Problems, Tenth Revision, Australian Modification (ICD-10-AM) codes and expert burn clinicians in assessing burn injury severity.

Method: We conducted a retrospective population-based review of all patients who sustained a burn injury between July 1, 2009, and June 30, 2019, requiring admission into a specialist burn service across Australia and New Zealand. The %TBSA burned (including the percentage of full thickness burns) recorded by expert burn clinicians within the Burns Registry of Australia and New Zealand (BRANZ) were compared to ICD-10-AM coding.

Results: 20,642 cases (71.5%) with ICD-10-AM code data were recorded. Overall, kappa scores (95% confidence interval [CI]) for burn size ranged from 0.64 (95% CI 0.63-0.66) to 0.86 (95% CI 0.78-0.94) indicating substantial to almost perfect agreement across all %TBSA groups. When stratified by depth, the lowest agreement was observed for < 10% TBSA and < 10% full thickness (kappa 0.03; 95% CI 0.02-0.04) and the highest agreement was observed for burns of ≥ 90% TBSA and ≥ 90% full thickness (kappa 0.72; 95% CI 0.58-0.85).

Conclusion: Overall, there was substantial agreement between the BRANZ and ICD-10-AM coded data for %TBSA classification. When %TBSA classification was stratified by burn depth, greater agreement was observed for larger and deeper burns compared with smaller and superficial burns.

Implications: Greater consistency in the classification of burns is needed.

Background: The professional identity and motivation of qualified health information managers (HIMs) is largely unexplored.

Objectives: A larger study has investigated the motivators of HIMs in the construction of their professional identity and associated relationships to job satisfaction and engagement with their profession. The aims of this component of the study were to: (i) identify and analyse the characteristics of members of the profession who have different motivation profiles; (ii) obtain HIMs' perspectives on their professional identity; and (iii) measure correlation between HIMs' professional identity and different motivating factors. Method: A cross-sectional study design, with a convergent mixed-methods approach to data collection was employed. An online survey was administered to the 1985, 1995, 2005 and 2015 Australian health information management and medical record administration graduate cohorts from one university in Victoria.

Results: Response rate: 72.7% (n = 72). There were no statistically significant correlations between the HIMs' motivation profile and professional identity. The HIMs were largely motivated by a need for achievement (striving for excellence) and continuous improvement; maintained high standards of work quality (95.8%); valued their work (94.4%) and work collaborations (84.7%); satisfactorily applied skills-knowledge (94%); demonstrated a very strong professional association (92% were proud to belong to the profession). Key factors in motivation that were consistently reported by members of all cohorts in the open-ended questions were as follows: intrinsic motivation; colleagues and teamwork; the variety of work performed; and contribution to the bigger picture. Overall, and notwithstanding between-cohort differences: 65.3% confidently directed others, 45.8% aspired to leadership and 38% actively networked. They related difficulty in explaining the profession to outsiders.

Conclusion: There was no correlation between motivation profile and professional identity. Significantly, the HIMs demonstrated exceptionally strong positive professional identity, reflected particularly in pride in membership of the profession and their belief in the importance of their professional work.

Context: Access to real-time data that provide accurate and timely information about the status and extent of disease spread could assist management of the COVID-19 pandemic and inform decision-making.

Aim: To demonstrate our experience with regard to implementation of technical and architectural infrastructure for a near real-time electronic health record-based surveillance system for COVID-19 in Iran.

Method: This COVID-19 surveillance system was developed from hospital information and electronic health record (EHR) systems available in the study hospitals in conjunction with a set of open-source solutions; and designed to integrate data from multiple resources to provide near real-time access to COVID-19 patients' data, as well as a pool of health data for analytical and decision-making purposes.

Outcomes: Using this surveillance system, we were able to monitor confirmed and suspected cases of COVID-19 in our population and to automatically notify stakeholders. Based on aggregated data collected, this surveillance system was able to facilitate many activities, such as resource allocation for hospitals, including managing bed allocations, providing and distributing equipment and funding, and setting up isolation centres.

Conclusion: Electronic health record systems and an integrated data analytics infrastructure are effective tools to enable policymakers to make better decisions, and for epidemiologists to conduct improved analyses regarding COVID-19.

Implications: Improved quality of clinical coding for better case finding, improved quality of health information in data sources, data-sharing agreements, and increased EHR coverage in the population can empower EHR-based COVID-19 surveillance systems.

Background: The Australian hospital-acquired complication (HAC) policy was introduced to facilitate negative funding adjustments in Australian hospitals using ICD-10-AM codes.

Objective: The aim of this study was to determine the positive predictive value (PPV) of the ICD-10-AM codes in the HAC framework to detect hospital-acquired pneumonia in patients with cancer and to describe any change in PPV before and after implementation of an electronic medical record (EMR) at our centre.

Method: A retrospective case review of all coded pneumonia episodes at the Peter MacCallum Cancer Centre in Melbourne, Australia spanning two time periods (01 July 2015 to 30 June 2017 [pre-EMR period] and 01 September 2020 to 28 February 2021 [EMR period]) was performed to determine the proportion of events satisfying standardised surveillance definitions.

Results: HAC-coded pneumonia occurred in 3.66% (n = 151) of 41,260 separations during the study period. Of the 151 coded pneumonia separations, 27 satisfied consensus surveillance criteria, corresponding to an overall PPV of 0.18 (95% CI: 0.12, 0.25). The PPV was approximately three times higher following EMR implementation (0.34 [95% CI: 0.19, 0.53] versus 0.13 [95% CI: 0.08, 0.21]; p = .013).

Conclusion: The current HAC definition is a poor-to-moderate classifier for hospital-acquired pneumonia in patients with cancer and, therefore, may not accurately reflect hospital-level quality improvement. Implementation of an EMR did enhance case detection, and future refinements to administratively coded data in support of robust monitoring frameworks should focus on EMR systems.

Implications: Although ICD-10-AM data are readily available in Australian healthcare settings, these data are not sufficient for monitoring and reporting of hospital-acquired pneumonia in haematology-oncology patients.