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

{"title":"Demystifying environmental health-related diseases: Using ICD codes to facilitate environmental health clinical referrals.","authors":"Melissa Stoneham, Peter Schneider, James Dodds","doi":"10.1177/18333583241300235","DOIUrl":"https://doi.org/10.1177/18333583241300235","url":null,"abstract":"<p><p><b>Background:</b> 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. <b>Objective:</b> 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. <b>Method and Results:</b> 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 <i>International Statistical Classification of Diseases and Related Health Problems</i> (ICD) system, already in use in hospitals. <b>Conclusion and Implications:</b> 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.</p>","PeriodicalId":73210,"journal":{"name":"Health information management : journal of the Health Information Management Association of Australia","volume":" ","pages":"18333583241300235"},"PeriodicalIF":0.0,"publicationDate":"2024-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142735202","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"System-wide analysis of qualitative hospital incident data: Feasibility of semi-automated content analysis to uncover insights.","authors":"Teyl Engstrom, Danelle Kenny, Wallace Grimmett, Mary-Anne Ramis, Chris Foley, Clair Sullivan, Jason D Pole","doi":"10.1177/18333583241299433","DOIUrl":"https://doi.org/10.1177/18333583241299433","url":null,"abstract":"<p><strong>Background: </strong>Advances in technology have increased the ease of reporting hospital incidents, resulting in large amounts of qualitative descriptive data. Health services have little experience analysing these data at scale to incorporate into routine reporting.</p><p><strong>Objective: </strong>We aimed to explore the feasibility of applying a semi-automated content analysis (SACA) tool (Leximancer™) to qualitative descriptions of system-wide hospital incidents to provide insights into safety issues at all health service levels.</p><p><strong>Method: </strong>Data from 1245 incidents reported across a network of hospitals in Australia were analysed using the SACA tool. Summaries were generated using a variety of techniques, including inductive and deductive approaches to extract key concepts in the data.</p><p><strong>Results: </strong>The analysis was feasible and provided an actionable summary of the types of incidents reported in the data; the visual interface allowed users to explore the underlying text for a deeper understanding. Deductive analysis was utilised to explore specific areas of interest, and stratified analysis revealed more detailed concepts. The SACA tool was more efficient than manual processes; however, due to the context present in the incident descriptions, significant time, reading and subject matter expertise is still required to refine the analysis.</p><p><strong>Conclusion: </strong>Semi-automated tools provide an opportunity for improving patient safety culture and practices by providing rapid content analysis of vast datasets that can be customised for specific organisational contexts and deployed at scale. Further research is required to assess usefulness with system users.</p><p><strong>Implications: </strong>Qualitative data abound and system-wide analysis is essential to creating actionable insights.</p>","PeriodicalId":73210,"journal":{"name":"Health information management : journal of the Health Information Management Association of Australia","volume":" ","pages":"18333583241299433"},"PeriodicalIF":0.0,"publicationDate":"2024-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142693413","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"From data collection to downstream data use: Malaysia's experience with ICD-11.","authors":"Erwyn Chin Wei Ooi, Zaleha Md Isa, Mohd Rizal Abdul Manaf, Ahmad Soufi Ahmad Fuad, Hammad Fahli Sidek, Mimi Nurakmal Mustapa, Azman Ahmad, Fawzi Zaidan Ali, Mohamad Fadli Kharie, Shahidah Adilah Shith, Nuraidah Mohd Marzuki","doi":"10.1177/18333583241295717","DOIUrl":"https://doi.org/10.1177/18333583241295717","url":null,"abstract":"<p><strong>Background: </strong>The transition of systems to the <i>International Statistical Classification of Diseases 11th Version</i> (ICD-11) allows access to comprehensive data that accurately portray the complexity of morbidity and mortality data in Malaysia.</p><p><strong>Objective: </strong>To demonstrate Malaysia's experience in implementing ICD-11, from data collection to downstream data use applications.</p><p><strong>Method and implementation: </strong>We describe improvements to existing data source systems and downstream data applications. For non-HIS and HIS (ICD-10) systems, data were manually entered into the health management information system equipped with ICD-11 or automatically mapped from ICD-10 to ICD-11. Following these system improvements, we collected and reported ICD-11 data from all hospitals nationwide, regardless of the individual systems' status in ICD-11 use.</p><p><strong>Discussion: </strong>Lessons learnt related to legacy systems; ICD-11 releases and system updates; mapping; reporting; human resources and related applications.</p><p><strong>Conclusion: </strong>With careful planning, standardisation of the collection and use of ICD-11 data can be accomplished with limited resources and in a complex environment with heterogeneous systems.</p><p><strong>Implications: </strong>Use of ICD-11 data in downstream data applications improves data quality to answer specific business or research questions.</p>","PeriodicalId":73210,"journal":{"name":"Health information management : journal of the Health Information Management Association of Australia","volume":" ","pages":"18333583241295717"},"PeriodicalIF":0.0,"publicationDate":"2024-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142692946","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluation of virtual training delivery for health information systems implementation in Canada: A qualitative study.","authors":"Inaara Karsan, Hafsa Hasan, Tharshini Jeyakumar, Sharon Ambata-Villaneuva, Katharine Fur, Ivanka Hanley, Sarah McClure, Maram Omar, Tamee Sheriff, David Wiljer","doi":"10.1177/18333583241289151","DOIUrl":"https://doi.org/10.1177/18333583241289151","url":null,"abstract":"<p><strong>Introduction: </strong>As health information systems (HIS) become a critical part of patient care, it is crucial to build an effective education strategy that facilitates the adoption and sustained use of these systems. The COVID-19 pandemic (2019-2023) has contributed to the rapid shift in virtual education and training for healthcare staff.</p><p><strong>Objective: </strong>We sought to evaluate the efficacy and long-term sustainability of virtual training for using a HIS by examining opportunities and challenges.</p><p><strong>Method: </strong>An exploratory, multimethods study was conducted with staff who had taken part in a virtual HIS training program as part of the clinical transformation journey at a large academic health science center in Canada. The study was guided by the Accelerating the Learning Cycle framework. Data were collected through pre- and post-training surveys, as well as semi-structured interviews. An iterative, inductive, constant comparative analysis approach, outlined by Braun and Clarke, was taken to thematically analyse the data.</p><p><strong>Results: </strong>Of the 33 participants in this study, 13 were educational champions, and 20 were end-users. The pre- and post-training surveys yielded a total of 1479 responses in both groups. Three prominent themes emerged from this study: (1) fostering dynamic facilitation techniques to cultivate an inclusive culture and adapt to diverse learning needs; (2) integrating practical learning activities that contribute to knowledge retention; and (3) ensuring training resources are accessible and consistent for an optimal training experience.</p><p><strong>Conclusion: </strong>As HIS continue to be part of the transformation of the healthcare ecosystem, education is vital in preparing healthcare providers to perform their clinical tasks and effectively use these technologies. Findings from this study can be used to inform the development of virtual training that is inclusive and addresses the needs of care providers.</p>","PeriodicalId":73210,"journal":{"name":"Health information management : journal of the Health Information Management Association of Australia","volume":" ","pages":"18333583241289151"},"PeriodicalIF":0.0,"publicationDate":"2024-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142683593","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The health information management professionals' role in supporting individuals considering genetic testing: An exploratory study.","authors":"Christina Turrietta, Barbara Hewitt, Jackie Moczygemba, Alexander McLeod","doi":"10.1177/18333583241283518","DOIUrl":"https://doi.org/10.1177/18333583241283518","url":null,"abstract":"<p><p><b>Background:</b> An increasing number of people are exploring their genetic predisposition to many diseases, allowing them to make healthcare decisions with improved knowledge. <b>Objectives:</b> The aim of this study was to identify factors that influence individuals to consider genetic testing utilising a modified health belief model (HBM). <b>Method:</b> The authors tested the modified HBM using a convenience sample of individuals from across the United States after a pilot study was used to test the validity and reliability of the constructs. Using SmartPLS, the researchers determined that the modified HBM explains the decision-making process used to determine what influences individuals to consider genetic testing. <b>Results:</b> Results suggested that perceived susceptibility, perceived benefits, cues to action, self-efficacy, e-health literacy and normative belief all play a role in an individual's decision to test their genetics. <b>Conclusion:</b> By conducting genetic testing, individuals may benefit from knowing they are predisposed to certain cancers and other diseases. Yet, research results have indicated that most individuals are unaware of resources available online that will help them in understanding genetic test results and associated diseases. <b>Implications:</b> Since healthcare literacy is an issue reported by these individuals, health information management professionals are well qualified to support them in e-health literacy by assisting them to evaluate the trustworthiness of available resources, and to educate them about privacy rights regarding access to and protection of their genetic information.</p>","PeriodicalId":73210,"journal":{"name":"Health information management : journal of the Health Information Management Association of Australia","volume":" ","pages":"18333583241283518"},"PeriodicalIF":0.0,"publicationDate":"2024-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142677965","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Clinically meaningful categorisation of ICD-10-AM (Australian modification).","authors":"Graeme J Duke, Steven Hirth, John D Santamaria, Carla Read, Adina Hamilton, Melisa Lau, Tharanga Fernando, Zhuoyang Li, Teresa Le, Kirstie Walkley","doi":"10.1177/18333583241296224","DOIUrl":"https://doi.org/10.1177/18333583241296224","url":null,"abstract":"<p><p><b>Background:</b> Current methods of categorising the <i>International Statistical Classification of Diseases and Related Health Problems</i> (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. <b>Objective:</b> Describe novel methodology for clinically meaningful categorisation of 12th Edition of ICD Version 10 Australian modification (ICD-10-AM). <b>Setting:</b> State of Victoria (Australia), population of 6.6 million with over 3 million separations per annum. <b>Method:</b> 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. <b>Results:</b> 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. <b>Conclusion:</b> The CDG list provides a clinically meaningful method of categorisation and interrogating datasets based on ICD-10-AM and complements existing methods.</p>","PeriodicalId":73210,"journal":{"name":"Health information management : journal of the Health Information Management Association of Australia","volume":" ","pages":"18333583241296224"},"PeriodicalIF":0.0,"publicationDate":"2024-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142677964","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Perceptions of Portuguese medical coders on the transition to ICD-10-CM/PCS: A national survey.","authors":"Filipa Santos Martins, Fernando Lopes, Júlio Souza, Alberto Freitas, João Vasco Santos","doi":"10.1177/18333583231180294","DOIUrl":"10.1177/18333583231180294","url":null,"abstract":"<p><strong>Background: </strong>In Portugal, trained physicians undertake the clinical coding process, which serves as the basis for hospital reimbursement systems. In 2017, the classification version used for coding of diagnoses and procedures for hospital morbidity changed from the International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) to the International Classification of Diseases, Tenth Revision, Clinical Modification/Procedure Coding System (ICD-10-CM/PCS).</p><p><strong>Objective: </strong>To assess the perceptions of medical coders on the transition of the clinical coding process from ICD-9-CM to ICD-10-CM/PCS in terms of its impact on data quality, as well as the major differences, advantages, and problems they faced.</p><p><strong>Method: </strong>We conducted an observational study using a web-based survey submitted to medical coders in Portugal. Survey questions were based on a literature review and from previous focus group studies.</p><p><strong>Results: </strong>A total of 103 responses were obtained from medical coders with experience in the two versions of the classification system (i.e. ICD-9-CM and ICD-10-CM/PCS). Of these, 82 (79.6%) medical coders preferred the latest version and 76 (73.8%) considered that ICD-10-CM/PCS guaranteed higher quality of the coded data. However, more than half of the respondents (<i>N</i> = 61; 59.2%) believed that more time for the coding process for each episode was needed.</p><p><strong>Conclusion: </strong>Quality of clinical coded data is one of the major priorities that must be ensured. According to the medical coders, the use of ICD-10-CM/PCS appeared to achieve higher quality coded data, but also increased the effort.</p><p><strong>Implications: </strong>According to medical coders, the change off classification systems should improve the quality of coded data. Nevertheless, the extra time invested in this process might also pose a problem in the future.</p>","PeriodicalId":73210,"journal":{"name":"Health information management : journal of the Health Information Management Association of Australia","volume":" ","pages":"237-242"},"PeriodicalIF":0.0,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9824741","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Medical and nursing clinician perspectives on the usability of the hospital electronic medical record: A qualitative analysis.","authors":"Sheree Lloyd, Karrie Long, Yasmine Probst, Josie Di Donato, Abraham Oshni Alvandi, Jeremy Roach, Christopher Bain","doi":"10.1177/18333583231154624","DOIUrl":"10.1177/18333583231154624","url":null,"abstract":"<p><strong>Background: </strong>Electronic medical records (EMRs) have been widely implemented in Australian hospitals. Their usability and design to support clinicians to effectively deliver and document care is essential, as is their impact on clinical workflow, safety and quality, communication, and collaboration across health systems. Perceptions of, and data about, usability of EMRs implemented in Australian hospitals are key to successful adoption.</p><p><strong>Objective: </strong>To explore perspectives of medical and nursing clinicians on EMR usability utilising free-text data collected in a survey.</p><p><strong>Method: </strong>Qualitative analysis of one free-text optional question included in a web-based survey. Respondents included medical and nursing/midwifery professionals in Australian hospitals (85 doctors and 27 nurses), who commented on the usability of the main EMR used.</p><p><strong>Results: </strong>Themes identified related to the status of EMR implementation, system design, human factors, safety and risk, system response time, and stability, alerts, and supporting the collaboration between healthcare sectors. Positive factors included ability to view information from any location; ease of medication documentation; and capacity to access diagnostic test results. Usability concerns included lack of intuitiveness; complexity; difficulties communicating with primary and other care sectors; and time taken to perform clinical tasks.</p><p><strong>Conclusion: </strong>If the benefits of EMRs are to be realised, there are good reasons to address the usability challenges identified by clinicians. Easy solutions that could improve the usability experience of hospital-based clinicians include resolving sign-on issues, use of templates, and more intelligent alerts and warnings to avoid errors.</p><p><strong>Implications: </strong>These essential improvements to the usability of the EMR, which are the foundation of the digital health system, will enable hospital clinicians to deliver safer and more effective health care.</p>","PeriodicalId":73210,"journal":{"name":"Health information management : journal of the Health Information Management Association of Australia","volume":" ","pages":"189-197"},"PeriodicalIF":0.0,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11401339/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9074770","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Analysis of data items and gaps in Australia's national mental health services activity and capacity data collections for integrated regional service planning.","authors":"Claudia Pagliaro, Arabella Mundie, Harvey Whiteford, Sandra Diminic","doi":"10.1177/18333583231175770","DOIUrl":"10.1177/18333583231175770","url":null,"abstract":"<p><p><b>Background:</b> Services data are an important source of information for policymakers and planners. In Australia, significant work has been undertaken to develop and implement collections of mental health services data. Given this level of investment, it is important that collected data are fit for purpose. <b>Objective:</b> This study aimed to: (1) identify existing national mandated and best endeavours collections of mental health services activity (e.g. occasions of service) and capacity (e.g. full-time equivalent staff) data in Australia; and (2) review the content of identified data collections to determine opportunities for data development. <b>Method:</b> A grey literature search was conducted to identify data collections. Where available, metadata and/or data were analysed. <b>Results:</b> Twenty data collections were identified. For services that received funding via multiple funding streams, data were often captured across several collections corresponding with each funder. There was significant variability in the content and format of collections. Unlike other service sectors, there is no national, mandated collection for psychosocial support services. Some collections have limited utility as they do not include key activity data; others do not include descriptive variables like service type. Workforce data are often not collected, and where data are collected, they are often not comprehensive. <b>Conclusion:</b> Findings are an important source of information for policymakers and planners who use services data to inform priorities. <b>Implications:</b> This study provides recommendations for data development, including mandating standardised reporting for psychosocial supports, filling workforce data gaps, streamlining data collections and including key missing data items in some collections.</p>","PeriodicalId":73210,"journal":{"name":"Health information management : journal of the Health Information Management Association of Australia","volume":" ","pages":"206-216"},"PeriodicalIF":0.0,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9590031","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Unsupervised algorithms to identify potential under-coding of secondary diagnoses in hospitalisations databases in Portugal.","authors":"Diana Portela, Rita Amaral, Pedro P Rodrigues, Alberto Freitas, Elísio Costa, João A Fonseca, Bernardo Sousa-Pinto","doi":"10.1177/18333583221144663","DOIUrl":"10.1177/18333583221144663","url":null,"abstract":"<p><strong>Background: </strong>Quantifying and dealing with lack of consistency in administrative databases (namely, under-coding) requires tracking patients longitudinally without compromising anonymity, which is often a challenging task.</p><p><strong>Objective: </strong>This study aimed to (i) assess and compare different hierarchical clustering methods on the identification of individual patients in an administrative database that does not easily allow tracking of episodes from the same patient; (ii) quantify the frequency of potential under-coding; and (iii) identify factors associated with such phenomena.</p><p><strong>Method: </strong>We analysed the Portuguese National Hospital Morbidity Dataset, an administrative database registering all hospitalisations occurring in Mainland Portugal between 2011-2015. We applied different approaches of hierarchical clustering methods (either isolated or combined with partitional clustering methods), to identify potential individual patients based on demographic variables and comorbidities. Diagnoses codes were grouped into the Charlson an Elixhauser comorbidity defined groups. The algorithm displaying the best performance was used to quantify potential under-coding. A generalised mixed model (GML) of binomial regression was applied to assess factors associated with such potential under-coding.</p><p><strong>Results: </strong>We observed that the hierarchical cluster analysis (HCA) + k-means clustering method with comorbidities grouped according to the Charlson defined groups was the algorithm displaying the best performance (with a Rand Index of 0.99997). We identified potential under-coding in all Charlson comorbidity groups, ranging from 3.5% (overall diabetes) to 27.7% (asthma). Overall, being male, having medical admission, dying during hospitalisation or being admitted at more specific and complex hospitals were associated with increased odds of potential under-coding.</p><p><strong>Discussion: </strong>We assessed several approaches to identify individual patients in an administrative database and, subsequently, by applying HCA + k-means algorithm, we tracked coding inconsistency and potentially improved data quality. We reported consistent potential under-coding in all defined groups of comorbidities and potential factors associated with such lack of completeness.</p><p><strong>Conclusion: </strong>Our proposed methodological framework could both enhance data quality and act as a reference for other studies relying on databases with similar problems.</p>","PeriodicalId":73210,"journal":{"name":"Health information management : journal of the Health Information Management Association of Australia","volume":" ","pages":"174-182"},"PeriodicalIF":0.0,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11408983/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10752193","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}