Introduction Advance Care Planning (ACP) is a patient-centered process that enables individuals to consider their goals and priorities and make plans with their healthcare team for future care. Oncology clinicians care for critically ill patients and are central to facilitating and documenting ACP. While Australian and international guidelines strongly support ACP in oncology, clinician engagement and documentation of ACP remain suboptimal. This study aimed to explore oncology clinicians’ ACP knowledge, decision-making, and practice, including factors influencing engagement in ACP. Methods A qualitative study was conducted using semi-structured interviews with oncology clinicians from three metropolitan hospitals in New South Wales, Australia. Participants were purposefully sampled and interviewed between November 2021 and March 2022. Interviews were audio-recorded, transcribed, and analyzed using deductive thematic analysis guided by the Theoretical Domains Framework (TDF). An inductive approach was subsequently applied to develop explanatory subthemes within identified domains. Results Eleven clinicians participated, including Medical/Radiation Oncology Consultants (54.5%) and Advanced Trainees (45.5%). Interview length ranged from 17.5 to 35.5 minutes. A total of 380 quotes were coded across all 14 TDF domains, generating 33 explanatory subthemes. Four domains were most influential: Knowledge and Skills, Social/Professional Role and Identity, Environmental Context and Resources, and Social Influences. Although all participants recognized ACP as best-practice care, engagement was influenced by limited formal training and legal literacy, uncertainty regarding responsibility for initiating and documenting ACP, variable inconsistent interdisciplinary communication, workload and time constraints, electronic medical record functionality, and patient characteristics (i.e.,psychological state, health literacy, cultural complexity). Conclusion ACP in oncology is shaped by complex, interdependent socio-cultural and organizational factors. Applying the TDF identified key behavioral and contextual determinants. Improving ACP requires multilevel strategies targeting clinician capability, role clarity, and system-level supports, including structured education, clearer documentation processes, improved electronic medical record functionality, and integration of ACP into routine multidisciplinary care.

Background:Best practice standards aim to standardize care and improve outcomes. However, variation in clinical practice exists, and not all deviations are inappropriate. Measuring adherence to best practice standards remains challenging due to limitations in representation methods and data fidelity. Objective:This scoping review aims to survey and synthesize the existing literature on the computable representation of guideline recommendations and to explore methods for detecting and quantifying deviations from best practice standards. Methods:We followed the Arksey and O'Malley framework and PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) guidelines. Five databases (Ovid Medline, EMBASE, IEEE Xplore, Web of Science, and Scopus) were searched in November 2025. Studies were included if they either (1) described a computer representation of best practice standards or (2) assessed adherence to such standards using patient data, including patient data derived from electronic medical records or event logs. Screening was done using Covidence (Veritas Health Innovation). Data were extracted on representation, clinical context, data sources, adherence metrics, and modeling techniques. A narrative synthesis was conducted to identify themes. Results:Twenty-four studies were included. Most studies were published as conference proceedings (13/24, 54%). Fourteen studies (14/24, 58%) included measurement of adherence to best practice standards. Cardiovascular conditions were the most common focus (13/24, 54%). Data sources included Health Level Seven (HL7) messages, structured electronic medical record data, event logs, and Fast Healthcare Interoperability Resources (FHIR)-transformed data. Best practice standards were formalized using Business Process Model and Notation (BPMN; 6/24, 25%), ontologies (7/24, 29%), FHIR (4/24, 17%), or hybrid approaches (4/24, 17%). The most common method for adherence measurement was rule-based alignment. Several studies incorporated weighted scoring to differentiate the severity of deviations. Process mining was used in a subset to detect sequence and timing variations. However, most models lacked contextual sensitivity and rarely incorporated patient-specific factors, such as comorbidities, patient acuity, or clinician rationale. Consequently, although deviations can be automatically identified, determining whether they were clinically warranted remained largely unresolved. Conclusions:Despite promising advances, challenges persist in computer-interpretable representation and measuring adherence in a clinically meaningful way. Current approaches predominantly assess technical alignment rather than clinical relevance and are limited by data quality and standardization, thereby limiting real-world utility. This scoping review offers an innovative contribution by synthesizing evidence from 2 separate domains-the computable representation of best practice standards and the measurement of adherence. The findings emphasize the need for context-aware, standardized modeling and integration with clinical workflows to distinguish warranted from unwarranted deviations. Such advances are essential for scalable, transparent, and real-time adherence monitoring-ultimately driving safer, patient-centered care delivery.

Aim To determine the feasibility of using population-based linked data to measure an Australian multidisciplinary set of 26 colorectal cancer (CRC) quality indicators.Methods Data were obtained on adult patients diagnosed with CRC (ICD-10-AM codes C18-C20) between July 1, 2005 and December 31, 2019 from the New South Wales (NSW) Cancer Registry. The NSW Cancer Registry data were linked to the Clinical Cancer Registry, Admitted Patient Data Collection, and death records. The feasibility assessment included (1) mapping required variables to available data, (2) review of publicly available reports to identify routine reporting of the indicators, (3) assessment of data completeness and coverage using proportional analyses, and (4) pilot test calculation of feasible indicators where data exist.Results Data mapping found that 14 indicators were potentially feasible. Linked data were available for 38,430 patients to test eight surgical indicators and 8489 patients to test six neoadjuvant therapy indicators. The data required to measure these indicators had significant limitations in data coverage, completeness, and quality, rendering the calculations unreliable and some implausible. The data completeness for staging ranged from 74% to 85%, and almost one half of diagnosis dates were illogical. Overall, six of the 26 indicators were feasible and reliable to measure. These addressed unplanned reoperation/readmission, colonoscopy, surgical mortality, and survival.Conclusion This study identified six clinically relevant quality indicators feasible to measure using NSW population-based data. However, these indicators were surgical processes and outcomes. There are insufficient data to produce adequate and clinically meaningful quality measurements for a multidisciplinary CRC team, particularly in diagnostic workup, neoadjuvant therapy, and supportive care.

BACKGROUND:Monitoring delivery of cancer care is critical to improve outcomes in increasingly resource-constrained settings. The aim of this study was to develop a priority set of multidisciplinary quality indicators (QIs) for benchmarking and monitoring the quality of care for head and neck cancer (HNC) in Australia. METHODS:Following a systematic literature review, a modified Delphi consensus process was undertaken with Australian health professionals and people with lived experience of HNC. Consensus was sought over three rounds. In Rounds 2 and 3, participants rated the importance of QIs on a scale of 1 (not at all important) to 7 (highly important). QIs reached consensus if they had a mean importance score ≥ 6 (out of 7) and ≥ 75% of participants rated them 6 or 7. RESULTS:The systematic review identified 317 unique QIs, and 81 were chosen for presentation in Rounds 2 of the Delphi. In Round 2, 66 health professionals and 12 people with lived experience of HNC reached consensus on 48 QIs, with three reworded and one new QI added. Fifty-two QIs were presented in Round 3; 42 health professionals and 10 people with lived experience participated, reaching consensus on 24 QIs. Most of the QIs fell under the treatment domain, with commencement of curative treatment and documentation of surgical margins attaining the highest consensus. CONCLUSION:We developed a priority set of 24 clinically relevant QIs for HNC, which will be tested in a clinical quality registry to benchmark optimal management of HNC and outcomes.

The health sector is highly digitized, which is enabling the collection of vast quantities of electronic data about health and well-being. These data are collected by a diverse array of information and communication technologies, including systems used by health care organizations, consumer and community sources such as information collected on the web, and passively collected data from technologies such as wearables and devices. Understanding the breadth of IT that collect these data and how it can be actioned is a challenge for the significant portion of the digital health workforce that interact with health data as part of their duties but are not for informatics experts. This viewpoint aims to present a taxonomy categorizing common information and communication technologies that collect electronic data. An initial classification of key information systems collecting electronic health data was undertaken via a rapid review of the literature. Subsequently, a purposeful search of the scholarly and gray literature was undertaken to extract key information about the systems within each category to generate definitions of the systems and describe the strengths and limitations of these systems.

Introduction: Online learning is an accessible method that enables medical practitioners to undertake training to develop new, and reinforce existing, knowledge and skills. Early career medical practitioners may find engaging in online learning particularly beneficial as they have a stronger motivation to refine knowledge and skills than their more senior peers. One under-explored mechanism to strengthen the delivery of online learning for medical practitioners is the use of clinical data to tailor learning so it is closely aligned with the individual health professional’s clinical practice. Methodology: This study aimed to evaluate the feasibility of personalising an online learning program for early career doctors working in oncology using electronic medical record (EMR) data. An online program was developed by clinical domain experts that could be triggered using pathology orders and/or results closely aligned to when the test was ordered in clinical practice. The program content was designed to cover three categories: (1) test ordering, (2) interpreting test results, and (3) patient management. Early career medical practitioners undergoing oncology training were recruited to participate in the study. The program was evaluated using metrics captured by the online learning platform, and a post-program survey. Results: All early career medical practitioners eligible to participate in the study consented to participate (n=5). It was feasible to personalise the online program using pathology ordering data. Further, analysis of survey responses indicated that personalising an online learning program using EMR data was acceptable to early career doctors and facilitated engagement with the course. Conclusion: Personalising an online learning program for early career medical practitioners in cancer care using electronic health-record data is both feasible and acceptable.

AimTo develop a priority set of quality indicators (QIs) for use by colorectal cancer (CRC) multidisciplinary teams (MDTs). MethodsThe review search strategy was executed in four databases from 2009-August 2019. Two reviewers screened abstracts/manuscripts. Candidate QIs and characteristics were extracted using a tailored abstraction tool and assessed for scientific soundness. To prioritize candidate indicators, a modified Delphi consensus process was conducted. Consensus was sought over two rounds; (1) multidisciplinary expert workshops to identify relevance to Australian CRC MDTs, and (2) an online survey to prioritize QIs by clinical importance. ResultsA total of 93 unique QIs were extracted from 118 studies and categorized into domains of care within the CRC patient pathway. Approximately half the QIs involved more than one discipline (52.7%). One-third of QIs related to surgery of primary CRC (31.2%). QIs on supportive care (6%) and neoadjuvant therapy (6%) were limited. In the Delphi Round 1, workshop participants (n = 12) assessed 93 QIs and produced consensus on retaining 49 QIs including six new QIs. In Round 2, survey participants (n = 44) rated QIs and prioritized a final 26 QIs across all domains of care and disciplines with a concordance level > 80%. Participants represented all MDT disciplines, predominantly surgical (32%), radiation (23%) and medical (20%) oncology, and nursing (18%), across six Australian states, with an even spread of experience level. ConclusionThis study identified a large number of existing CRC QIs and prioritized the most clinically relevant QIs for use by Australian MDTs to measure and monitor their performance.

UNSTRUCTURED The health sector is highly digitised. This digitisation is enabling the collection of vast quantities of electronic data about health and wellbeing. The Information Communication Technologies collecting these data are varied depending on the area of healthcare but can include systems used by healthcare organisations, consumer and community sources such as information collected online, and passively collected data from technologies such as wearables and devices. Understanding the breadth of technologies, the health system uses to collect data, and the myriad ways it can be actioned is a challenge for researchers, consumers, health professionals, governments and other key stakeholders. This viewpoint aims to describe the Information Communication Technologies that collect electronic data within the health ecosystem. A secondary aim is to better understand how the data from these systems is being actioned for both primary and secondary uses. A purposeful review of the literature was undertaken to describe the different Information Communication Technologies that collect electronic health data and classify them into broad categories, and the ways in which these different electronic health data sources have been utilised to date. The review was augmented with the domain knowledge from the authors to develop use cases to illustrate how electronic health data could be actioned to improve health care in future. A taxonomy of electronic health data sources is presented. This taxonomy describes the ways in which data is currently being actioned for primary and secondary uses.

Historically, quality measurement analyses utilize manual chart abstraction from data collected primarily for administrative purposes. These methods are resource-intensive, time-delayed, and often lack clinical relevance. Electronic Medical Records (EMRs) have increased data availability and opportunities for quality measurement. However, little is known about the effectiveness of Measurement Feedback Systems (MFSs) in utilizing EMR data. This study explores the effectiveness and characteristics of EMR-enabled MFSs in tertiary care. The search strategy guided by the PICO Framework was executed in four databases. Two reviewers screened abstracts and manuscripts. Data on effect and intervention characteristics were extracted using a tailored version of the Cochrane EPOC abstraction tool. Due to study heterogeneity, a narrative synthesis was conducted and reported according to PRISMA guidelines. A total of 14 unique MFS studies were extracted and synthesized, of which 12 had positive effects on outcomes. Findings indicate that quality measurement using EMR data is feasible in certain contexts and successful MFSs often incorporated electronic feedback methods, supported by clinical leadership and action planning. EMR-enabled MFSs have the potential to reduce the burden of data collection for quality measurement but further research is needed to evaluate EMR-enabled MFSs to translate and scale findings to broader implementation contexts.

Objectives The aim of this study is to explore the current and future state of quality measurement and feedback and identify factors influencing measurement feedback systems, including the barriers and enablers to their effective design, implementation, use and translation into quality improvement. Design This qualitative study used semistructured interviews with key informants. A deductive framework analysis was conducted to code transcripts to the Theoretical Domains Framework (TDF). An inductive analysis was used to produce subthemes and belief statements within each TDF domain. Setting All interviews were conducted by videoconference and audio-recorded. Participants Key informants were purposively sampled experts in quality measurement and feedback, including clinical (n=5), government (n=5), research (n=4) and health service leaders (n=3) from Australia (n=7), the USA (n=4), the UK (n=2), Canada (n=2) and Sweden (n=2). Results A total of 17 key informants participated in the study. The interview length ranged from 48 to 66min. 12 theoretical domains populated by 38 subthemes were identified as relevant to measurement feedback systems. The most populous domains included environmental context and resources, memory, attention and decision-making, and social influences. The most populous subthemes included 'quality improvement culture', 'financial and human resource support' and 'patient-centred measurement'. There were minimal conflicting beliefs outside of 'data quality and completeness'. Conflicting beliefs in these subthemes were predominantly between government and clinical leaders. Conclusions Multiple factors were found to influence measurement feedback systems and future considerations are presented within this manuscript. The barriers and enablers that impact these systems are complex. While there are some clear modifiable factors in the design of measurement and feedback processes, influential factors described by key informants were largely socioenvironmental. Evidence-based design and implementation, coupled with a deeper understanding of the implementation context, may lead to enhanced quality measurement feedback systems and ultimately improved care delivery and patient outcomes.

International lung cancer screening (LCS) trials, using low-dose computed tomography, have demonstrated clinical effectiveness in reducing mortality from lung cancer. This systematic review aims to synthesise the key messages and strategies that could be successful in increasing awareness and knowledge of LCS, and ultimately increase uptake of screening. Studies were identified via relevant database searches up to January 2022. Two authors evaluated eligible studies, extracted and crosschecked data, and assessed quality. Results were syn-thesised narratively. Of 3205 titles identified, 116 full text articles were reviewed and 22 studies met the in-clusion criteria. Twenty studies were conducted in the United States. While the study findings were heterogenous, key messages mentioned across multiple studies were about: provision of information on LCS and the recommendations for LCS (n = 8); benefits and harms of LCS (n = 6); cost of LCS and insurance coverage for participants (n = 6) and eligibility criteria (n = 5). To increase knowledge and awareness, evidence from awareness campaigns suggests that presenting information about eligibility and the benefits and harms of screening, may increase screening intention and uptake. Evidence from behavioural studies suggests that cam-paigns supporting engagement with platforms such as educational videos and digital awareness campaigns might be most effective. Group based learning appears to be most suited to increasing health professionals' knowledge. This systematic review found a lack of consistent evidence to demonstrate which strategies are most effective for increasing participant healthcare professional and community awareness and education about LCS.

Abstract Background Radiotherapy is an effective evidence-based treatment modality for the definitive management of both early and locally advanced lung cancer. Whilst the literature reports a wide range of quality indicators (QIs) to assess the surgical management of lung cancer there is a deficit of robust QIs available to measure the quality of radiotherapy received by patients[1]. We propose a literature review and modified Delphi technique to develop a set of radiotherapy specific quality indicators and benchmarks aimed at evaluating the processes involved in the planning and delivery of radiotherapy for lung cancer. Methods A modified Delphi technique will be used and will include an international expert panel in two formal rounds with a target of 40 participants and intervening steering committee review with a minimum of 9 stakeholders. Candidate radiotherapy QIs will be selected from literature review and assessed by a steering committee to be included in the Delphi process. Both QIs and proposed benchmarks will be ranked by the expert panel in 2 rounds and included in the final set of QIs if a pre-defined consensus definition for importance is met by at least 70% of responses with a score of 7 or more on a 9-point Likert scale. Consensus criteria for feasibility and proposed benchmarks will be achieved if at least 70% of responses are reported as 3 or more on a 3-point Likert scale. Discussion We aim to address the current lack of quality indicators for assessing radiotherapy in lung cancer by using a robust modified Delphi method to attain international expert consensus for a set of QIs specific to the process involved in planning and delivering radiotherapy for definitive management of lung cancer. These have the potential to provide a foundation for QI measurement and benchmarking to guide quality improvement in radiotherapy for lung cancer.

BACKGROUND:Medical practitioners are important facilitators of advanced care planning but are often reluctant to engage in these conversations with patients and their families. Barriers to participation can be addressed through medical education for medical practitioners.INTRODUCTION:The primary objective was to examine the extent to which digital educational interventions are used to foster advanced care planning skills. Secondary objectives include understanding the acceptability of these interventions and whether electronic health records can be used to personalize learning.METHODS:Online databases were used to identify relevant articles published from 2008 to 2021. Nine articles which evaluated the impact of digital learning for medical practitioners were selected. Studies eligible for inclusion in the review assessed changes in knowledge, attitudes, and practice regarding skills used in advanced care planning.RESULTS:All publications used a pre-post study design with education delivered solely online. Only three studies focused on completing advance care plans or directives (33%). All but two studies recorded improvements in knowledge and/or attitudes toward planning (78%) while three studies recorded improvements in clinical practice (33%). The review suggests prior clinical or personal experiences could be used to personalize education.DISCUSSION:The literature revealed that using digital education to develop advanced care planning skills is relatively unexplored despite the ability of this type of learning to improve professional knowledge and confidence. Digital devices can also improve access to relevant information at the point-of-care. Personalized interventions that incorporate prior clinical experiences, potentially extracted from health records, could be used to optimize outcomes.

Telehealth facilitates access to cancer care for patients unable to attend in-person consultations, as in COVID-19. This systematic review used the reach, effectiveness, adoption, implementation, and maintenance (RE-AIM) framework to evaluate telehealth implementation and examine enablers and barriers to optimal implementation in oncology. MEDLINE, PubMed, CINAHL, and the Cochrane Database of Systematic Reviews were searched between January 2011-June 2022. Eighty-two articles representing 73 studies were included. One study explicitly used the RE-AIM framework to guide study design, conduct, or reporting. Reach (44%) and implementation (38%) were most commonly reported, maintenance (5%) least commonly. Key telehealth implementation enablers included professional-led delivery, patient-centred approaches, and positive patient perceptions. Key barriers included patient discomfort with technology, limited supporting clinic infrastructure, and poor access to reliable internet connection and videoconferencing. While a patient-centred and professional-supported approach enables telehealth implementation, technology and infrastructure constraints need surmounting for sustained implementation beyond the COVID-19 pandemic.

Lung cancer remains the leading cause of cancer death worldwide. Low dose computed tomography (LDCT) screening in high-risk populations can reduce lung cancer specific mortality as demonstrated in two landmark trials. Little is known about whether implementation of a high-risk LDCT screening program would be feasible in the Australian setting. The aim of this research was to critically review the literature about the core implementation components that would facilitate a targeted LDCT screening program in Australia.