Search

Objective: There is limited evidence on the development of pancreatic and oesophagogastric cancer, how patients decide to seek help and the factors impacting help‐seeking. Our study, the first in Australia, aimed to explore symptom appraisal and diagnostic pathways in these patients. A secondary aim was to examine the potential to recruit cancer patients through a cancer quality registry. Methods: Patients diagnosed with pancreatic or oesophagogastric cancer were recruited through Monash University's Upper‐Gastrointestinal Cancer Registry. Data collected through general practitioners (GP) and patient questionnaires included symptoms and their onset, whereas patient interviews focused on the patient's decision‐making in seeking help from healthcare pracitioners. Data collection and analysis was informed by the Aarhus statement. Coding was inductive, and themes were mapped onto the Model of Pathways to Treatment. Results: Between November 2018 and March 2020, 27 patient questionnaires and 13 phone interviews were completed. Prior to diagnosis, patients lacked awareness of pancreatic and oesophagogastric cancer symptoms, leading to the normalisation, dismissal and misattribution of the symptoms. Patients initially self‐managed symptoms, but worsening of symptoms and jaundice triggered help‐seeking. Competing priorities, beliefs about illnesses and difficulties accessing healthcare delayed help‐seeking. Conclusion: Increased awareness of insidious pancreatic and oesophagogastric cancer symptoms in patients and general practitioners may prompt more urgent investigations and lead to earlier diagnosis. [ABSTRACT FROM AUTHOR]

Temporal phenotyping of patient journeys, which capture the common sequence patterns of interventions in the treatment of a specific condition, is useful to support understanding of antimicrobial usage in veterinary patients. Identifying and describing these phenotypes can inform antimicrobial stewardship programs designed to fight antimicrobial resistance, a major health crisis affecting both humans and animals, in which veterinarians have an important role to play. This research proposes a framework for extracting temporal phenotypes of patient journeys from clinical practice data through the application of natural language processing (NLP) and unsupervised machine learning (ML) techniques, using cat bite abscesses as a model condition. By constructing temporal phenotypes from key events, the relationship between antimicrobial administration and surgical interventions can be described, and similar treatment patterns can be grouped together to describe outcomes associated with specific antimicrobial selection. Cases identified as having a cat bite abscess as a diagnosis were extracted from VetCompass Australia, a database of veterinary clinical records. A classifier was trained and used to label the most clinically relevant event features in each record as chosen by a group of veterinarians. The labeled records were processed into coded character strings, where each letter represents a summary of specific types of treatments performed at a given visit. The sequences of letters representing the cases were clustered based on weighted Levenshtein edit distances with KMeans+ + to identify the main variations of the patient treatment journeys, including the antimicrobials used and their duration of administration. A total of 13,744 records that met the selection criteria was extracted and grouped into 8436 cases. There were 9 clinically distinct event sequence patterns (temporal phenotypes) of patient journeys identified, representing the main sequences in which surgery and antimicrobial interventions are performed. Patients receiving amoxicillin and surgery had the shortest duration of antimicrobial administration (median of 3.4 days) and patients receiving cefovecin with no surgical intervention had the longest antimicrobial treatment duration (median of 27 days). Our study demonstrates methods to extract and provide an overview of temporal phenotypes of patient journeys, which can be applied to text-based clinical records for multiple species or clinical conditions. We demonstrate the effectiveness of this approach to derive real-world evidence of treatment impacts using cat bite abscesses as a model condition to describe patterns of antimicrobial therapy prescriptions and their outcomes. [ABSTRACT FROM AUTHOR]