Structured Data Acquisition in Oncology

Clinical decision making in prostate cancer care-evaluation of EAU-guidelines use and novel decision support software

Keeping up to date with the latest clinical advances in prostate cancer can be challenging. We investigated the impact of guideline use on quality of treatment decisions as well as the impact of a novel, CE-certified clinical decision support tool (Siemens AIPC software) on the amount of time clinicians spend on decision-making in a multicenter setting. Ten urologists assessed ten clinical cases (screening and localized prostate cancer) in three settings: without support, using a digital version of the EAU guidelines, and with the AIPC tool, resulting in 300 clinical decisions. Comparison involved time spent, decision correct- and completeness. Using AIPC compared to digital guidelines led to a significant reduction of expenditure of time at a per case level (3.57 min and 0:14 min, p < 0.01) and for overall time per urologist (39.45 min and 02:20 min, p < 0.01). Decision options without guidelines support, online guideline usage and usage of AIPC were complete in 61%, 80% and 100%, respectively (p < 0.01). Decision making without guidelines support, online guideline usage and usage of AIPC was correct including all options in 28%, 66% and 100%, respectively (p < 0.01).Clinical decision support systems have the potential to reduces decision-making time and to enhance decision quality.

Multidisciplinary team meeting Chairs' attitudes and perceived facilitators, barriers and ideal improvements to meeting functionality: A qualitative study

AIM

Oncology care provision by multidisciplinary teams (MDTs) is widely acknowledged as best practice. Formal team meetings, led by chairpersons, coordinate decisions on diagnosis, staging, treatment planning, and review. This study addresses a gap in meeting Chairs' perspectives on factors affecting functionality across the meeting cycle, from pre-meeting patient list triage to post-meeting dissemination of recommendations.

METHODS

Semi-structured interviews were conducted in person with Chairs within two urban geographical regions in New South Wales, Australia as part of a larger project. Though the population of oncology MDT Chairs in Australia is small, the richness and depth of data from nine Chairs were considered to be valuable knowledge in support of extant literature on meeting functionality. An integrated deductive-inductive approach was applied to data analysis.

RESULTS

Perceived facilitators, barriers, and ideals relating to pre-meeting, in-meeting, and post-meeting functionality were identified across five pre-determined analytic categories: the team; meeting infrastructure; meeting organization and logistics; patient-centered clinical decision-making, and; team governance. Key barriers included inadequate information technology, limited support staff, and lack of dedicated time for Chair duties. Corresponding facilitators included robust Information Technology infrastructure and support, provision of clinically knowledgeable MDT meeting coordinators, and formal employment recognition of Chairs' responsibilities and skill sets.

CONCLUSION

Chairs across various tumor streams develop workarounds to overcome barriers and ensure quality meeting outcomes. With more robust support they could enhance value by sharing evidence, conducting audits, and engaging in research. The findings highlight the need for healthcare systems to support tumor stream clinical networks by allocating greater resources to prioritize multidisciplinary meetings and cancer care decision-making.

Initial experience with AI Pathway Companion: Evaluation of dashboard-enhanced clinical decision making in prostate cancer screening

Purpose

Rising complexity of patients and the consideration of heterogeneous information from various IT systems challenge the decision-making process of urological oncologists. Siemens AI Pathway Companion is a decision support tool that provides physicians with comprehensive patient information from various systems. In the present study, we examined the impact of providing organized patient information in comprehensive dashboards on information quality, effectiveness, and satisfaction of physicians in the clinical decision-making process.

Methods

Ten urologists in our department performed the entire diagnostic workup to treatment decision for 10 patients in the prostate cancer screening setting. Expenditure of time, information quality, and user satisfaction during the decision-making process with AI Pathway Companion were recorded and compared to the current workflow.

Results

A significant reduction in the physician’s expenditure of time for the decision-making process by -59.9% (p < 0,001) was found using the software. System usage showed a high positive effect on evaluated information quality parameters completeness (Cohen’s d of 2.36), format (6.15), understandability (2.64), as well as user satisfaction (4.94).

Conclusion

The software demonstrated that comprehensive organization of information improves physician’s effectiveness and satisfaction in the clinical decision-making process. Further development is needed to map more complex patient pathways, such as the follow-up treatment of prostate cancer.

Supporting Structured Data Capture for Patients With Cancer: An Initiative of the University of Wisconsin Carbone Cancer Center Survivorship Program to Improve Capture of Malignant Diagnosis and Cancer Staging Data

PURPOSE

Structured data elements within electronic health records are health-related information that can be entered, stored, and extracted in an organized manner at later time points. Tracking outcomes for cancer survivors is also enabled by structured data. We sought to increase structured data capture within oncology practices at multiple sites sharing the same electronic health records.

METHODS

Applying engineering approaches and the Plan-Do-Study-Act cycle, we launched dual quality improvement initiatives to ensure that a malignant diagnosis and stage were captured as structured data. Intervention: Close Visit Validation (CVV) requires providers to satisfy certain criteria before closing ambulatory encounters. CVV may be used to track open clinical encounters and chart delinquencies to encourage optimal clinical workflows. We added two cancer-specific required criteria at the time of closing encounters in oncology clinics: (1) the presence of at least one malignant diagnosis on the Problem List and (2) staging all the malignant diagnoses on the Problem List when appropriate.

RESULTS

Six months before the CVV implementation, the percentage of encounters with a malignant diagnosis on the Problem List at the time of the encounter was 65%, whereas the percentage of encounters with a staged diagnosis was 32%. Three months after cancer-specific CVV implementation, the percentages were 85% and 75%, respectively. Rates had increased to 90% and 88% more than 2 years after implementation.

CONCLUSION

Oncologist performance improved after the implementation of cancer-specific CVV criteria, with persistently high percentages of relevant malignant diagnoses and cancer stage structured data capture 2 years after the intervention.

Toward a Platform for Structured Data Acquisition in Oncology: A Pilot Study on Prostate Cancer Screening

INTRODUCTION

Physicians spend an ever-rising amount of time to collect relevant information from highly variable medical reports and integrate them into the patient's health condition.

OBJECTIVES

We compared synoptic reporting based on data elements to narrative reporting in order to evaluate its capabilities to collect and integrate clinical information.

METHODS

We developed a novel system to align medical reporting to data integration requirements and tested it in prostate cancer screening. We compared expenditure of time, data quality, and user satisfaction for data acquisition, integration, and evaluation.

RESULTS

In a total of 26 sessions, 2 urologists, 2 radiologists, and 2 pathologists conducted the diagnostic work-up for prostate cancer screening with both narrative reporting and the novel system. The novel system led to a significantly reduced time for collection and integration of patient information (91%, p < 0.001), reporting in radiology (44%, p < 0.001) and pathology (33%, p = 0.154). The system usage showed a high positive effect on evaluated data quality parameters completeness, format, understandability, as well as user satisfaction.

CONCLUSION

This study provides evidence that synoptic reporting based on data elements is effectively reducing time for collection and integration of patient information. Further research is needed to assess the system's impact for different patient journeys.