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Background: Cancer stage at diagnosis is essential for understanding cancer outcomes, guiding cancer control activities and healthcare services, and enabling benchmarking nationally and internationally. Yet, most cancer registries in Australia do not routinely collect this data. This study explored key stakeholders' perceptions of implementing cancer staging utilising Natural Language Processing and Machine Learning algorithms within the Western Australian Cancer Registry. Methods: Perceptions of key breast and colorectal cancer stakeholders, including registry staff, clinicians, consumers, data scientists, biostatisticians, data management, healthcare staff, and health researchers, were collected. Prospective and retrospective qualitative proformas at two-time points of the Western Australian Cancer Staging Project were employed. The Consolidated Framework for Implementation Research was used to guide data collection, analysis and interpretation embedded in a Participatory Action Research approach. Data analysis also incorporated Framework Analysis and an adapted version of grading qualitative data using a visual traffic light labelling system to highlight the levels of positivity, negativity, and implementation concern. Results: Twenty-nine pre-proformas and 18 post-proformas were completed online via REDCap. The grading and visual presentation of barriers and enablers aided interpretation and reviewing predicted intervention outcomes. Of the selected constructs, complexity (the perceived difficulty of the intervention) was the strongest barrier and tension for change (the situation needing change) was the strongest enabler. Implementing cancer staging into the Western Australian Cancer Registry was considered vital. Benefits included improved knowledge and understanding of various outcomes (e.g., treatment received as per Optimum Care Pathways) and benchmarking. Barriers included compatibility issues with current systems/workflows, departmental/higher managerial support, and future sustainment. Conclusions: The findings aid further review of data gaps, additional cancer streams, standardising cancer staging and future improvements. The study offers an adapted version of a rapid qualitative data collection and analytic approach for establishing barriers and enablers. The findings may also assist other population-based cancer registries considering collecting cancer stage at diagnosis. [ABSTRACT FROM AUTHOR]

Introduction: Although much work has been done on US abortion ideology, less is known relative to the psychological processes that distinguish personal abortion beliefs or how those beliefs are communicated to others. As part of a forthcoming probability-based sampling designed study on US abortion climate, we piloted a study with a controlled sample to determine whether psychological indicators guiding abortion beliefs can be meaningfully extracted from qualitative interviews using natural language processing (NLP) substring matching. Of particular interest to this study is the presence of cognitive distortions—markers of rigid thinking—spoken during interviews and how cognitive distortion frequency may be tied to rigid, or firm, abortion beliefs. Methods: We ran qualitative interview transcripts against two lexicons. The first lexicon, the cognitive distortion schemata (CDS), was applied to identify cognitive distortion n-grams (a series of words) embedded within the qualitative interviews. The second lexicon, the Linguistic Inquiry Word Count (LIWC), was applied to extract other psychological indicators, including the degrees of (1) analytic thinking, (2) emotional reasoning, (3) authenticity, and (4) clout. Results: People with polarized abortion views (i.e., strongly supportive of or opposed to abortion) had the highest observed usage of CDS n-grams, scored highest on authenticity, and lowest on analytic thinking. By contrast, people with moderate or uncertain abortion views (i.e., people holding more complex or nuanced views of abortion) spoke with the least CDS n-grams and scored slightly higher on analytic thinking. Discussion and conclusion: Our findings suggest people communicate about abortion differently depending on their personal abortion ideology. Those with strong abortion views may be more likely to communicate with authoritative words and patterns of words indicative of cognitive distortions—or limited complexity in belief systems. Those with moderate views are more likely to speak in conflicting terms and patterns of words that are flexible and open to change—or high complexity in belief systems. These findings suggest it is possible to extract psychological indicators with NLP from qualitative interviews about abortion. Findings from this study will help refine our protocol ahead of full-study launch. [ABSTRACT FROM AUTHOR]

Background: After hospital discharge, patients can experience symptoms prompting them to seek acute medical attention. Early evaluation of patients' post-discharge symptoms by healthcare providers may improve appropriate healthcare utilization and patient safety. Post-discharge follow-up phone calls, which are used for routine transitional care in U.S. hospitals, serve as an important channel for provider-patient communication about symptoms. This study aimed to assess the facilitators and barriers to evaluating and triaging pain symptoms in cardiovascular patients through follow-up phone calls after their discharge from a large healthcare system in Central Massachusetts. We also discuss strategies that may help address the identified barriers.Methods: Guided by the Practical, Robust, Implementation and Sustainability Model (PRISM), we completed semi-structured interviews with 7 nurses and 16 patients in 2020. Selected nurses conducted (or supervised) post-discharge follow-up calls on behalf of 5 clinical teams (2 primary care; 3 cardiology). We used thematic analysis to identify themes from interviews and mapped them to the domains of the PRISM model.Results: Participants described common facilitators and barriers related to the four domains of PRISM: Intervention (I), Recipients (R), Implementation and Sustainability Infrastructure (ISI), and External Environment (EE). Facilitators include: (1) patients being willing to receive provider follow-up (R); (2) nurses experienced in symptom assessment (R); (3) good care coordination within individual clinical teams (R); (4) electronic health record system and call templates to support follow-up calls (ISI); and (5) national and institutional policies to support post-discharge follow-up (EE). Barriers include: (1) limitations of conducting symptom assessment by provider-initiated follow-up calls (I); (2) difficulty connecting patients and providers in a timely manner (R); (3) suboptimal coordination for transitional care among primary care and cardiology providers (R); and (4) lack of emphasis on post-discharge follow-up call reimbursement among cardiology clinics (EE). Specific barriers for pain assessment include: (1) concerns with pain medication misuse (R); and (2) no standardized pain assessment and triage protocol (ISI).Conclusions: Strategies to empower patients, facilitate timely patient-provider communication, and support care coordination regarding pain evaluation and treatment may reduce the barriers and improve processes and outcomes of pain assessment and triage. [ABSTRACT FROM AUTHOR]