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

Background: The COVID-19 pandemic has highlighted the critical role of mobile health applications in the management of health crises. Despite the promising outcomes of these technologies, however, their acceptance and use among physicians in the developing world such as Saudi Arabia are notably low. Objective: The study aimed to explore the factors influencing the acceptance and adoption of mobile health applications by physicians in Saudi Arabia during the COVID-19 pandemic. Method: The study employed a qualitative research method, guided by the Unified Theory of Acceptance and Use of Technology (UTAUT). The study collected data through semi-structured interviews with 16 physicians to delve into the determinants of their readiness to adopt m-health technologies. Data were analysed using template analysis to identify key themes and patterns. Results: In line with the UTAUT, the study identified performance expectancy, effort expectancy, social influence and facilitating conditions as significant influencing factors of the acceptance and adoption of mobile health applications by physicians in Saudi Arabia during the pandemic. This study also inquired into context-specific determinants, such as data privacy concerns, patient engagement, organisational support and compatibility with religious and cultural norms, which are especially relevant in Saudi Arabia and similar developing countries, where these factors, alongside the exigencies arising from the COVID-19 pandemic, have shaped the landscape of mobile health applications utilisation. Conclusions: This study enriches the literature by expanding the UTAUT model to include context-specific drivers of acceptance and adoption. It highlights the need for tailored adoption frameworks to fit local contexts for successful m-health integration. Implications: This research broadens the UTAUT model by including cultural compatibility and data privacy concerns, offering deeper insights into mHealth adoption during crises. It highlights the need for policies and practices that support culturally sensitive app design, strengthen data privacy measures and provide improved training and patient engagement to enhance mHealth adoption.

Background: Work-integrated learning (WIL) is integral to most health disciplines' profession-qualifying degree programs. Objectives: To analyse the categories, locales and foci of final-year (capstone), health information management professional practice (WIL) placements, 2012-2021, at La Trobe University, Australia. Method: A documentary analysis of 614 placement agency proposals, 2012-2021, interrogated multiple characteristics: agency type, placement (sub-) category (WIL model), project type, agency-required student capabilities, intended learning outcomes. Results: Public hospitals offered 50% of all placements. Medical research/health or disease screening/clinical registries offered 17.8%, incorporating 86.7% of "research-based" placements. Government department offerings were consistently stable; private hospital, primary care and community healthcare offerings declined. The majority (64.8%) of offerings were "project-based," followed by "internship" (28.7%: Health Information Service (14%) and "other" (14.7%)), research-based (4.9%) and other (1.6%). Ninety-nine (16.1%) proposals specified additional, pre-placement skills and capabilities: technical (information technologies, software applications; 58.6% of 99 proposals); working independently (49.5%); communications (written, verbal; 45.5%); targeted interest (38.4%) in "informatics and data quality," "quality and safety," "software development," "coding"; organisational and/or time management skills (29.9%); teamwork skills (20.2%); data analysis skills (18.2%); enthusiasm and/or self-motivation (15.2%). Conclusion: The project-based model for the capstone placement is ideal for preparing health information management students for complex, graduate professional work. Agencies' pre-placement expectations of students (knowledge, technical skills, soft skills) are consistent with findings from the WIL literature and align with course curricula and Australia's Health Information Manager (HIM) Profession-entry Competency Standards. Implications: The findings will strengthen the health information management profession's knowledge base of WIL and inform educators, students and agency supervisors.

Background: The quality of care in nursing homes (NHs) in the United States has long been a matter of policy concern. Although electronic health records (EHRs) are argued to improve quality, implementation has lagged due to various factors such as financial constraints and limited research on their impact on NH quality. Objective: This study examined the relationship between EHR implementation and NH quality using Donabedian's structure-process-outcome model. Method: Data on EHR implementation were collected via a 2018 survey of all Federally certified Arkansas NHs (n = 223). Of the 63 responding NHs, 48 reported EHR implementation. Survey data were merged with secondary sources such as Certification and Survey Provider Enhanced Reporting. A total of 744 NH-years for the period 2008-2020 were included in the final sample. A pre-post negative binomial panel data regression was used to examine the relationship between EHR implementation (dichotomous variable) and NH deficiencies (dependent count variable) with facility/community-level control variables. Results were reported as incidence rate ratios (IRR). Results: NHs that had implemented EHR experienced an 18% reduction in the rate of deficiencies compared to those without EHR systems (IRR = 0.82, 95% CI [0.70, 0.99], p = 0.035). Conclusion: EHR implementation had a favourable impact on NH quality. Implications: Past research suggests that higher NH quality may be associated with improved financial performance. Therefore, EHR implementation has the potential to address two critical challenges: enhancing care quality and improving financial outcomes. However, government financial incentives may be necessary to address the high-cost of implementing EHR systems.

Background: The World Health Organization (WHO) announced the release of the 11th edition of the International Classification of Diseases (ICD) in May 2019. Although Statistics Korea has been involved in the ongoing research on ICD-11 since 2017, we have been unable to achieve agreement on the gold standards for case scenario clinical coding in previous studies due to high levels of variance in the coding results of participants. Objective: The purpose of this study was to enhance clinical coding accuracy and consistency in ICD-11 by identifying and clarifying the reasons for these inconsistencies through the use of clear clinical coding rules. Method: A pre-experimental design was applied. Two clinical coding field trials (FTs) were conducted in 'ICD-11 for Mortality and Morbidity Statistics (2022 Mar)' targeting diagnostic terms and case scenarios. In the first FT, clinical coding rules were derived by analysing the results, while the second FT was performed under the clinical coding rules set by the first FT. Results: Across the two FTs, accuracy rates for diagnostic terms (75.8% and 71.8%, respectively) were higher than for case scenarios (62.5% and 71.9%). The main reason for the low accuracy levels was post-coordination. Conclusion: For case scenario clinical coding, low accuracy could be explained by variance in clustering methods between participants. This suggests that the accuracy of ICD-11 clinical coding could be increased if the variance between clustering methods can be reduced through the use of a clear coding guide. A guide for various ambiguous cases in each institution and the provision of a proper post-coordination list in the stem code could also be effective.

Background: The burden of disease of Aboriginal and Torres Strait Islander people is estimated as 2.3 times that of the broader Australian population, with between 30% and 50% of health inequalities attributable to poor environmental health. Objective: Although many Australian states and territories have clinical policy initiatives that seek to reduce the burden of preventable disease in this population, including field-based environmental health clinical referrals (EHCRs), there is little consistency across the jurisdictions, resulting in less potential to break the cycle of recurrent diseases within the home environment. Method and Results: This study addresses this inconsistency by recommending recognition and categorisation of environmental health risks to allow for accurate diagnosis and comparability across health services and locations by using the International Statistical Classification of Diseases and Related Health Problems (ICD) system, already in use in hospitals. Conclusion and Implications: Developing a list of mutually agreed environmental health attributable diseases for the EHCR process using assigned ICD-10-AM codes would influence the provision of primary care to include recognition of the impact of environmental health conditions and allow environmental health staff to provide a response and education at both community and household levels to break disease cycles.

Background: Current methods of categorising the International Statistical Classification of Diseases and Related Health Problems (ICD) have limitations when deciphering administrative data and monitoring healthcare outcomes. These include many-to-one relationships, non-linear sequencing, collinearity, and ambiguous miscellaneous (residual) codes. Objective: Describe novel methodology for clinically meaningful categorisation of 12th Edition of ICD Version 10 Australian modification (ICD-10-AM). Setting: State of Victoria (Australia), population of 6.6 million with over 3 million separations per annum. Method: Diagnosis codes from ICD-10-AM were aggregated into Clinical Diagnosis Group (CDG) sets according to clinical features and associated risk of in-hospital death and complications. Residual codes were excluded. Administrative data from July 2020 to June 2023 were interrogated to ascertain frequency of diagnoses captured by CDG sets. Results: 12,716 (87.9%) of 14,470 total ICD-10-AM codes were aggregated into 406 CDG sets; mean 32 (range 1-288) codes per set. One thousand seven hundred fifty-three (12.1%) were excluded (not allocated): 775 (5.4%) residual codes; 702 (4.9%) indicating reason for healthcare encounter; and 276 (1.9%) ill-defined clinical symptom codes. Over 36-months, 11.8 million separations were coded with 11,898 (82.2%) unique ICD-10-AM diagnoses, including 10,721 (90.1%) present in a CDG set. Of the 8571 (59.2%) codes associated with death or complications, 7813 (91.2%) were present in a CDG set. Conclusion: The CDG list provides a clinically meaningful method of categorisation and interrogating datasets based on ICD-10-AM and complements existing methods.

Aim: To conduct and report on psychometric tests for a valid and reliable measurement tool for evaluating digital hospitals by healthcare professionals. Method: This psychometric study took place in a public digital hospital in Turkey. It was carried out with the participation of 355 healthcare professionals. Data were collected between September and October 2023 using an online survey and non-probability convenience sampling method. Statistical Package for Social Science Version (SPSS) 26.0 and analysis of moment structures version 24.0 were used to analyse the data. It was used for the psychometric properties and analyses of the scale (item analysis, explanatory factor analysis, confirmatory factor analysis (CFA), convergent and divergent validity statistics, Cronbach Alpha internal consistency coefficient, dependent sample t-test, and intraclass correlation). Results: The content validity index of the scale is 0.92. As a result of exploratory factor analysis (EFA) and CFA in separate samples, a total of 30 items and four sub-factors were obtained. Cronbach Alpha value of the scale is over 0.90 for both samples. In the four-factor structure, 82.64% of the total variance was explained. The 30-item and four-factor structure obtained in EFA was confirmed in CFA, and convergent and divergent validity statistics were provided. Test-retest results showed that the scale has high reliability. Conclusion: The digital hospital evaluation scale is valid and reliable for healthcare professionals to evaluate digital hospitals.

Background: Digital health records (DHR) systems have emerged as crucial tools for enhancing healthcare delivery by improving clinical decision-making, promoting patient safety and facilitating efficient health information management. However, the adoption and implementation of DHR systems in developing countries, including Tanzania, face various challenges that impact workflow efficiency and service delivery.

Objective: This review examined the adoption, implementation and impact of DHR systems on workflow and service efficiency within healthcare systems in developing countries, with a particular focus on Tanzania. It also sought to identify common barriers and propose a context-specific conceptual framework to guide future research and implementation efforts.

Method: A systematic literature review was conducted using various academic databases, including PubMed, Scopus, IEEE Xplore and Google Scholar, focusing on studies published between 2019 and 2025. Studies were selected based on predefined inclusion and exclusion criteria following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework.

Results: A total of 21 studies met the inclusion criteria and were included in the final analysis. Four main themes emerged from the analysis: adoption factors, implementation challenges, workflow integration and service efficiency. Key barriers included limited e-health literacy, inadequate infrastructure, a lack of interoperability and concerns about data privacy. Studies have shown that the successful integration of DHR systems into clinical workflows is essential for realising efficiency gains. The review also highlighted context-specific gaps in current frameworks and proposed a conceptual model grounded in empirical evidence from Tanzania and comparable settings.

Conclusion: This systematic review highlights the need for context-sensitive approaches to DHR adoption and implementation, particularly in resource-constrained settings. Drawing from thematic synthesis, the study proposes a conceptual framework that consolidates insights from recent empirical studies to inform future implementation strategies and research in Tanzania and similar contexts.Implications for health information management practice:Strengthening digital infrastructure, improving healthcare workers' digital competencies and promoting system interoperability are key priorities. Policymakers and stakeholders should invest in targeted capacity-building, continuous in-service training and enforce data governance measures to support the sustainable integration of DHR systems and improve efficiency in healthcare delivery.

Background: Accurate varicella (chickenpox) and zoster (shingles)-coded hospitalisation data are important for disease surveillance and to examine the impact of immunisation programs. Varicella and zoster generally occur many years apart, with hospital episodes coded for both diseases concurrently implausible.

Objective: We aimed to describe varicella-zoster virus-related hospital episodes coded for both varicella and zoster or postherpetic neuralgia ('dual-coded') in Australia.

Method: Hospital episodes with ICD-10-AM code for varicella, zoster or postherpetic neuralgia between 2002 and 2021 were included and examined for dual-code assignment of both varicella and zoster or postherpetic neuralgia code, by principal diagnosis, age group and state/territory. Trends over time were assessed with segmented linear or negative binomial regression models.

Results: The proportion of hospital episodes with principal diagnosis varicella that were dual-coded increased substantially between 2009 and 2015 (p < 0.001; proportion <4% until 2009, 22.5%-28.8% from 2015 onwards), and with age (<15 years:<13%, ⩾65 years:>40%, from 2015 onwards). The proportion of hospital episodes with principal diagnosis zoster that were dual-coded also increased over time (p < 0.001), though was lower than observed in hospital episodes with principal diagnosis varicella. Hospital episodes with principal diagnosis post-herpetic neuralgia were rarely dual-coded.

Conclusion: After 2009, hospital episodes with principal diagnosis varicella, particularly in older age groups, frequently and increasingly have an additional zoster or postherpetic neuralgia code. Increased availability of real-time polymerase chain reaction testing and inadequate documentation in hospital medical records may have contributed to this.Implications for health information management practice:As hospitalisation data are extensively used to estimate disease burden and inform public health policy, the dual-coding issues identified require further investigation and mitigation.

Background: Proper clinical record-keeping is critical for effective communication, quality control and legal compliance in health care. Despite its importance, studies indicate that physicians often lack adequate documentation skills. Current medical curricula primarily address these skills during clinical years, leaving pre-clinical students underprepared.

Objective: This study aims to describe the implementation of a clinical record-keeping training program for pre-clinical medical students and evaluate its outcomes.

Method: This experimental study had a non-randomised controlled pre- and post-test design. The study involved implementing a 12-week training program for pre-clinical students, consisting of lectures and standardised patient interviews. A control group of students who received only the traditional curriculum was included for comparison. Pre-test and post-test assessments were conducted, and student satisfaction with the program was evaluated through a questionnaire.

Results: Results indicated a significant improvement in clinical record-keeping scores among students who received the new training program compared to the control group. Student satisfaction with the program was also positive.

Conclusion: Results demonstrated that early clinical record-keeping training significantly enhanced the skills and preparedness of pre-clinical students for their clinical years and eventual professional practice. Initiating such training during the pre-clinical phase is crucial for ensuring the development of competencies essential for effective healthcare delivery.Implications for health information management practice:Introducing structured record-keeping education before clinical exposure can bridge skill gaps early, foster better documentation habits, and ultimately improve the quality of health information management across healthcare systems. This strategy may also lead to improved clinical efficiency and patient care quality in the long term.