The Sydney Adventist Hospital (the San) is currently automating its cancer services multi-disciplinary team meetings (MDTs) using a new integrated cancer information management system (ICIMS) from the Sydney firm Innovative Clinical Information Management Systems (iCIMS) and HLA is providing the Pathology feed using its Horizon Clinical Natural Language Processing platform.

The new MDT system is built on iCIMS’ LATTICE platform and is aimed at streamlining and automating data preparation, data collection and workflows for each of the San’s 10 tumour stream MDTs. MDT meetings bring together a team of healthcare professionals to determine a patient’s treatment plan and are widely used in cancer care.

This project is part of the San’s plans for a cancer centre of excellence, including its state-of-the-art multi-disciplinary meeting room (pictured above), to become the leading cancer service in Australia.

According to iCIMS managing director Ali Besiso, ICIMS creates a closed-loop cancer MDT management system that will increase patient safety and service while significantly reducing the workload on clinicians.

The implementation includes at least eight integration points with the San’s electronic clinical systems, including the SanCare EMR for clinical details, the San’s PAS for patient demographics, operating theatres for surgical data, pathology for targeted cancer data, Day Infusion Centre system for systemic therapy data, and the radiation-oncology database for radiotherapy data.

“ICIMS enables automatic delivery of all critical patient data to present the full patient story in a single patient-centric view at the MDT meeting,” Mr Besiso said. “Preparation time and effort by clinical and ancillary staff is significantly reduced, data collection is comprehensive, and decision-making is thus better informed.”

Mr Besiso said the system will drive a universal streamlined referral process across tumour streams so that MDT clinicians can electronically refer and register patients to MDT meetings from anywhere, including remotely.

Pathologists, radiologists, nuclear medicine specialists and other diagnostic specialists can easily access the system at any time leading up to an MDT meeting to prepare their cases at their own convenience, he said.

During an MDT meeting, ICIMS generates clinical summaries auto-populated with all available clinical information required for case discussion. Treatment recommendations are recorded in real-time on the system for follow-up and actioning.

Finally, the MDT summaries from each meeting are immediately sent electronically into the hospital’s EMR, enabling easy access for clinicians, distribution to others involved in the patient’s care, monitoring of the patient journey and timely follow up, so closing the information and action-taking loops.

Gavin Marx, the clinical director of the San Integrated Cancer Centre, said the system was proving to be an important collaboration between the San and iCIMS.

“The accelerating pace of improving care and treatment of our patients at the San is founded on complex multidisciplinary collaboration through efficient access to all the critical information we need for care planning and driving ongoing research,” Associate Professor Marx said.

“Our ICIMS is the bedrock for reliable collection, analysis and presentation of big data information for our multidisciplinary teams.”

HLA Pathology feed

The San is also providing the pathology feed into ICIMS via Health Language Analytics’ HORIZON CliniSearch platform, which the San began using in 2015. HLA is iCIMS’ sister company and both were established by well-known computer scientist Jon Patrick.

HORIZON’s clinical natural language processing (CNLP) extracts targeted cancer content in prose pathology reports and sends it to ICIMS to populate the structured pathology data items of an MDT case. The San’s CliniSearch implementation currently contains over two million fully indexed and coded clinical reports in its data store, which now will be connected to ICIMS.

Professor Patrick, who is leading the NLP branch of the project, said that this was “a ground-breaking advance in bringing an industrial-grade NLP pipeline to the front and centre of clinical workflow”.