Piloting a Clinical Decision Support System for Unintended Weight Loss in Primary Care: Mixed Methods Study on Early Cancer Detection

Clinical Snapshot

Key Findings

• P Value: Not reported

• Effect Size: Descriptive proportions only; no comparative effect size calculable. Formal recall rate: 14% (5/36 true UWL patients). Six-month follow-up rate: 94% (34/36). Mental health conditions accounted for 19% of diagnoses linked to UWL consultation. One-third of patients (33%) had no additional symptoms; 36% had recorded abdominal symptoms.

• Primary Outcome: Of 60 patients identified by the CDSS as potentially having UWL, 36 (60%) had confirmed true UWL — a positive predictive value of 60%. The most common reason for misclassification was intentional weight loss (16/55 misclassified patients, 30%), documented in free text in 98% of cases but in structured fields in only 20%.

• Nnt Or Sensitivity: CDSS sensitivity and specificity not formally reported. Positive predictive value (PPV) for true UWL identification: approximately 60% (36/60). No negative predictive value calculable from available data. No NNT calculable without a comparator group.

• Confidence Interval: Not reported for any outcome

Clinical Application

Feasibility is demonstrated in principle but constrained by significant implementation barriers: poor workflow integration, high false-positive rates, and conflicting patient agendas (e.g., patients actively trying to lose weight). The CDSS as currently configured requires substantial refinement — particularly access to free-text clinical notes — before broader implementation is warranted. Staff receptivity was conditional on practice culture and prior digital health experience. This study is directly embedded in the Australian general practice context and is highly relevant to RACGP members. Unintended weight loss is recognised as an alarm symptom in RACGP clinical guidelines for cancer investigation. The findings raise important questions about whether Australian primary care's existing follow-up infrastructure may already be performing adequately for this symptom, potentially reducing the marginal benefit of a CDSS overlay. The study does not address PBS-listed investigations triggered by the CDSS or TGA-regulated digital health device classification. Future iterations should consider integration with My Health Record and alignment with Cancer Australia's early detection priorities. Applicability to Aboriginal Community Controlled Health Organisations and rural/remote settings — where cancer outcomes are disproportionately poor — remains entirely unaddressed and represents a critical evidence gap. Adult patients in Australian general practice presenting with or flagged for unintended weight loss, particularly those aged 40 years and over where cancer risk is elevated. The findings are most directly applicable to well-resourced, metropolitan general practices with existing quality improvement infrastructure and EHR capability.

Abstract

BACKGROUND: Delayed cancer diagnosis leads to poorer outcomes. Unintended weight loss (UWL) is a nonspecific symptom associated with cancer and other serious conditions, which can make it complex to identify the underlying cause. Clinical decision support systems (CDSSs) can provide evidence-based recommendations to facilitate timely investigation and diagnosis. OBJECTIVE: This study aimed to pilot the implementation of a CDSS for improving early cancer detection in primary care patients with UWL. METHODS: Five practices reviewed patients identified by the UWL CDSS. Staff were interviewed on the acceptability and feasibility of the CDSS. Interviews were analyzed thematically using 2 relevant frameworks: the acceptability of health care interventions and the sociotechnical model for evaluation of digital interventions framework. Clinical audits assessed the correct identification of UWL, follow-up rates, and patient characteristics. RESULTS: Of 60 patients identified by the CDSS as potentially having UWL, 36 (60%) had true UWL. Among the misclassified cases, most patients (16/55, 30%) were intentionally trying to lose weight; this intention was documented as free text in the clinical notes for 98% (58/60) of patients and in a structured field for only 20% of patients. Of the 36 patients, 5 (14%) were actively recalled by their practices for further follow-up; the others (31/36, 86%) were not recalled, as most were deemed already under appropriate follow-up. By 6 months, 94% (34/36) of the cohort had received follow-up care regardless of whether they had been formally recalled. One-third (12/36, 33%) of patients had no additional symptoms, while 36% (13/36) had recorded additional abdominal symptoms. Mental health conditions accounted for 19% of diagnoses linked to UWL consultation. Practice staff were generally receptive to the UWL CDSS concept. It was particularly appreciated by practices with strong quality improvement processes and prior CDSS experience. A high proportion of misclassified patients, poor workflow integration, and conflicting patients' agendas were cited as implementation barriers. CONCLUSIONS: Our study revealed challenges and potential benefits of implementing a CDSS for identifying patients with UWL at risk of cancer in primary care. While integration issues and misclassification of patients were noted, high rates of follow-up care were observed regardless of the CDSS. These high follow-up rates prompt consideration of whether they reflect Australian primary care and whether a CDSS with these characteristics is the most appropriate approach to support early cancer detection. Future research should focus on improving CDSS integration with existing workflows, enhancing correct identification through access to clinical notes and the use of more sophisticated digital methods (eg, AI). These findings highlight the potential of CDSS in improving patient care and the complexities involved in their successful implementation.

References

1. 1.Martinez-Gutierrez, J., Chima, S., Hunter, B., Lee, A., De Mendonca, L., Daly, D., Fishman, G., Lim, F. S., Wang, B., Nelson, C., Nicholson, B., Manski-Nankervis, J.-A., & Emery, J. (2026). Piloting a clinical decision support system for unintended weight loss in primary care: Mixed methods study on early cancer detection. JMIR Cancer. https://doi.org/10.1136/bmjdhai-2025-000092