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

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.

Background: National Personal Health Records (PHRs) have been proposed to improve the transfer of medication-related information during transition of care. Objective: To evaluate the concordance between the medications captured in the Australian national PHR, My Health Record (MyHR), and the pharmacist obtained best possible medication history (BPMH) for patients upon hospital admission. Method: This prospective observational study used a convenience sample of hospital patients. For newly admitted patients, the investigating pharmacist obtained a BPMH and then compared it to the medication list captured in MyHR. Upon comparison, the medications were categorised into either complete match, partial match or mismatch. Medications with a complete or partial match were grouped together. Medications with deviations were then assessed for risk based on their potential consequence, and reported descriptively. A multivariable logistic regression was conducted to assess the factors associated with a drug being mismatched. Results: A total of 82 patients were recruited, with a cumulative total of 1,207 medications documented. Of the 1,207 medications, 714 (59.2%) medications were documented as a complete/partial match. The remaining 493 (40.8%) medications were mismatched. Of the 493 mismatched medications, 442 (89.7%) were deemed low-risk deviations and 51 (10.3%) were deemed high-risk. A medication was more likely to be mismatched, rather than completely/partially matched, if it was a regular non-prescription medication, or "when-required" prescription medication, or "when required" non-prescription medication, or if it was administered parenterally. Conclusion: National PHRs may be a secondary source to either confirm a patient's medication history or be used as a starting point for a BPMH.

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 emergence of big data holds the promise of aiding healthcare providers by identifying patterns and converting vast quantities of data into actionable insights facilitating the provision of precision medicine and decision-making. Objective: This study aimed to investigate the factors influencing use of big data within healthcare services to facilitate their use. Method: A systematic review was conducted in February 2024, adhering to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Database searches for articles published between 01 January 2020 and 18 February 2024 and included PubMed, Scopus, ProQuest and Cochrane Library. The Authority, Accuracy, Coverage, Objectivity, Date, Significance ( AACODS) checklist was used to evaluate the quality of the included articles. Subsequently, a thematic analysis was conducted on the findings of the review, using the Boyatzis approach. Results: A final selection of 46 studies were included in this systematic review. A significant proportion of these studies demonstrated acceptable quality, and the level of bias was deemed satisfactory. Thematic analysis identified seven major themes that influenced the use of big data in healthcare services. These themes were grouped into four primary categories: performance expectancy, effort expectancy, social influence, and facilitating conditions. Factors associated with "effort expectancy" were the most highly cited in the included studies (67%), while those related to "social influence" received the fewest citations (15%). Conclusion: This study underscored the critical role of "effort expectancy" factors, particularly those under the theme of "data complexity and management," in the process of using big data in healthcare services. Implications: Results of this study provide groundwork for future research to explore facilitators and barriers to using big data in health care, particularly in relation to data complexity and the efficient and effective management of big data, with significant implications for healthcare administrators and policymakers.

Background: Health Information Managers (HIMs) play a crucial role in the management and governance of health information ensuring the accuracy, confidentiality and accessibility of health data for clinical care and business operational purposes. This role also extends to education and training in the workplace.

Objective: The aim of this scoping review was to explore and elucidate the role played by HIMs when they undertake a health workplace-based (healthcare organisation or service) educational role and/or functions as evidenced in the existing body of literature.

Method: A scoping review of the literature to investigated the importance of the educator role for HIM health workplace-based educators. A three-step search strategy was designed to ensure a comprehensive exploration of relevant research.

Results: Of 63 articles assess for eligibility, 14 were included in the final analysis. All included articles acknowledged the importance of the HIM-educator workplace-based role. Half of the included articles had been published within the last 7 years. Only 8 of the 14 articles provided some description of HIM-educator attributes, suggesting that these characteristics remain unexplored.

Discussion: Findings from this scoping review have shed light on the limitations within the current available literature concerning the attributes of HIM health workplace-based educators. The findings also highlight an important gap in knowledge concerning the qualities of these HIM-educators.

Conclusion: This identified gap in the literature signals a need for further exploration and investigation into the specific attributes, skills, and characteristics that define effective HIM-educators undertaking a health workplace-based educational role.

Background: When a patient is discharged from hospital it is essential that their general practitioner (GPs) and community pharmacist are informed of changes to their medicines. This necessitates effective communication and information-sharing between hospitals and primary care clinicians.

Objective: To identify priority medicine handover issues and solutions to inform the co-design and development of a multifaceted intervention.

Method: A modified nominal group technique was used to reach consensus on medicine handover priority areas. The first hour of an interactive 2-hr workshop focused on ranking pre-identified issues drawn from literature. In the second hour, participants identified solutions that they then ranked from highest to lowest priority through an online platform. Descriptive statistics were used to analyse workshop data.

Results: In total 32 participants attended the workshop including hospital doctors (n = 8, 25.0%), GPs and hospital pharmacists (n = 6 each, 18.8%), consumers and community pharmacists (n = 4 each, 12.5%), and both hospital and aged care facility nurses (n = 2 each 6.3%). From the list of 23 issues, the highest ranked issue was high workload and time pressures impacting the discharge process (22/32). From the list of 36 solutions, the participants identified two solutions that were equally ranked highest (12/27 each). They were mandating that patients leave hospital with a discharge summary, including medication reconciliation information and, developing an integrated information technology system where medication summary and notes are accessible for primary, secondary and tertiary health provider.

Conclusion: The consensus process highlighted challenges in hospital procedures where potential solutions may be implemented through co-design of a multifaceted intervention to improve medicine handover quality.

Background: Medical records, encompassing patient histories, progress notes, and more, play a crucial role in patient care and treatment, healthcare communication, medico-legal matters, and supporting financial documentation.

Objective: Despite their significance, literature suggests inconsistencies in record quality and insufficient formal medical record-keeping education for medical students and residents. The study aimed to identify and evaluate the effectiveness of educational interventions by conducting a systematic review.

Method: A literature search covering 2003-2023 and review following Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines was undertaken.

Results: The literature search identified 44 relevant studies for inclusion. Educational methods, including lectures, feedback, workshops and discussions, addressed different components of the clinical record. The review revealed positive impacts on participant satisfaction, skills and attitudes related to record-keeping. However, some studies reported no significant positive outcomes, emphasising the need for higher-level evidence. Most studies adopted a single-group pretest-posttest design, presenting challenges in control group implementation. The Kirkpatrick evaluation levels were primarily at level 2, with few studies reaching level 3. The absence of studies at level 4 suggested the need for more robust evidence. Studies targeted medical residents more frequently than medical students, with a lack of interventions during the first year of medical education.

Conclusion: Despite limitations including language bias and methodological variations, the review revealed diverse educational strategies and highlighted the necessity for more randomised controlled trials and studies providing higher-level evidence to enhance clinical record-keeping skills among medical students and residents.

Implications: Medical record-keeping educational interventions can significantly improve the documentation skills of medical students and residents, thereby enhancing patient care, communication and medico-legal compliance.

Background: Hospital-acquired complications (HACs) have an adverse impact on patient recovery by impeding their path to full recovery and increasing healthcare costs.

Objective: The aim of this study was to create a HAC risk prediction machine learning (ML) framework using hospital administrative data collections within North Metropolitan Health Service (NMHS), Western Australia.

Method: A retrospective cohort study was performed among 64,315 patients between July 2020 to June 2022 to develop an automated ML framework by inputting HAC and the healthcare site to obtain site-specific predictive algorithms for patients admitted to the hospital in NMHS. Univariate analysis was used for initial feature screening for 270 variables. Of these, 77 variables had significant relationship with any HAC. After excluding non-contemporaneous data, 37 variables were included in developing the ML framework based on logistic regression (LR), decision tree (DT) and random forest (RF) models to predict occurrence of four specific HACs: delirium, aspiration pneumonia, pneumonia and urinary tract infection.

Results: All models exhibited similar performance with area under the curve scores around 0.90 for both training and testing datasets. For sensitivity, DT and RF exceeded LR performance while on average, false positives were lowest for LR-based models. Patient's length of stay, Charlson Index, operation length and intensive care unit stay were common predictors.

Conclusion: Integrating ML-based risk detection systems into clinical workflows can potentially enhance patient safety and optimise resource allocation. LR-based models exhibited best performance.

Implications: We have successfully developed a "real-time" risk prediction model, where patient risk scores are calculated and reviewed daily.

In 2022 the Australian Data Availability and Transparency Act (DATA) commenced, enabling accredited "data users" to access data from "accredited data service providers." However, the DATA Scheme lacks guidance on "trustworthiness" of the data to be utilised for reuse purposes. Objectives: To determine: (i) Do researchers using government health datasets trust the data? (ii) What factors influence their perceptions of data trustworthiness? and (iii) What are the implications for government and data custodians? Method: Authors of published studies (2008-2020) that utilised Victorian government health datasets were surveyed via a case study approach. Twenty-eight trust constructs (identified via literature review) were grouped into data factors, management properties and provider factors. Results: Fifty experienced health researchers responded. Most (88%) believed that Victorian government health data were trustworthy. When grouped, data factors and management properties were more important than data provider factors in building trust. The most important individual trust constructs were: "compliant with ethical regulation" (100%) and "monitoring privacy and confidentiality" (98%). Constructs of least importance were knowledge of "participant consent" (56%) and "major focus of the data provider was research" (50%). Conclusion: Overall, the researchers trusted government health data, but data factors and data management properties were more important than data provider factors in building trust. Implications: Government should ensure the DATA Scheme incorporates mechanisms to validate those data utilised by accredited data users and data providers have sufficient quality (intrinsic and extrinsic) to meet the requirements of "trustworthiness," and that evidentiary documentation is provided to support these "accredited data."

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.