Neoplasms

Digestive System Diseases

All Conditions

Rare Diseases

Stomach Neoplasms

Esophageal Neoplasms

Gastrointestinal Neoplasms

Digestive System Neoplasms

Gastrointestinal Diseases

Stomach Diseases

Head and Neck Neoplasms

Esophageal Diseases

Stomach Cancer

Esophageal Cancer

No intervention will be provided to the subject

Bok Yan, Jimmy So

Jimmy So, MBChB

Clinical Decision Support Systems (CDSSs) to augment clinical care and decision making. These are platforms which aim to improve healthcare delivery by enhancing medical decisions with targeted clinical knowledge, patient information, and other health information.

In view of the benefit of developing a CDSS, we sought to develop an alternative CDSS for oncologic therapy selection through a partnership with Ping An Technology (Shenzhen, China), beginning with gastric and oesophagal cancer. This would be done in a piecemeal fashion, with the prototype platform utilizing only international guidelines and high-quality published evidence from journals to arrive at case-specific treatment recommendations. This platform would then be evaluated by comparing its recommendations with that from the multidisciplinary tumour boards of several tertiary care institutions to determine the concordance rate.

Management of cancer is a complex process which involves numerous stakeholders. In view of this, institutions worldwide have adopted the use of Multidisciplinary Tumor Boards (MTBs) for delivery of cancer care. By tapping on the collective specialized knowledge and experience of various specialties, MTBs have been shown in some studies to result in more appropriate recommendations and improved patient outcomes. At our institution, cancer cases are similarly discussed at regular MTBs which comprises surgeons, oncologists, pathologists and radiologists who review and recommend treatments.

However, in smaller centres or centres with limited resources and minimal multi-disciplinary expertise, delivery of timely and appropriate cancer care could be a challenge. Additionally, clinicians, with their busy schedule, may not be able to keep abreast of new developments in cancer research. With rapid advances in scientific research, this pool of knowledge is expected to continue to burgeon, making keeping up-to-date increasingly onerous.

To address this need, clinicians have adopted the use of Clinical Decision Support Systems (CDSSs) to augment clinical care and decision-making. These are platforms which aim to improve healthcare delivery by enhancing medical decisions with targeted clinical knowledge, patient information, and other health information. Various studies have shown CDSSs to be beneficial in selected settings such as patient safety and diagnosis \[4\], and to even increase adherence to clinical guidelines. In recent years, advancements in artificial intelligence have also seen its use expand to include oncologic therapy selection, with IBM's Watson for Oncology (WFO) being the most prominent and only platform in use to-date. In a 2018 study, WFO's ability to provide treatment advice for breast cancer was compared against recommendations from a multidisciplinary board, where it showed a high degree of concordance. Since then, several other studies have sought to examine WFO's ability to provide treatment recommendations for cancer such as ovarian, gastric, lung, cervical and colorectal cancers, with mixed results. In particular, both studies which examined the recommendations for gastric cancers showed a much lower concordance rate compared to other cancers.

In view of the above, we sought to develop an alternative CDSS for oncologic therapy selection through partnership with Ping An Technology (Shenzhen, China), beginning with gastric and esophageal cancer. This would be done in a piecemeal fashion, with the prototype platform utilizing only international guidelines and high-quality published evidence from journals to arrive at case-specific treatment recommendations. This platform would then be evaluated retrospectively and prospectively by comparing its recommendations with that from the multidisciplinary tumor boards of several tertiary care institutions to determine the concordance rate.

Development of a Clinical Decision Support System With Artificial Intelligence for Cancer Care

Comparative agreement in recommendations between the two study groups, as measured by concordance rate

To identify the reason for the discordance

National University Hospital, Singapore

Skin and Connective Tissue Diseases

Respiratory Tract (Lung and Bronchial) Diseases

Breast Neoplasms

Lung Neoplasms

Colorectal Neoplasms

Intestinal Neoplasms

Colonic Diseases

Intestinal Diseases

Rectal Diseases

and treatment type (chemotherapeutic adjuvant (i.e., chemotherapy delivered after primary therapy/surgery) or neoadjuvant (i.e., chemotherapy delivered prior to primary therapy/surgery) treatment, chemotherapeutic treatment for metastatic disease, or chemotherapeutic treatment through a clinical trial).

After the presentation of the of IBM Watson Oncology at the opening of the focus group, participants will be asked to fill out a de-identified brief 15-item questionnaire to assess participants' first impressions of IBM Watson Oncology. The questionnaire will be self administered, and will take approximately 5 minutes to complete. Completed questionnaires will be collected by a member of the study staff, and the focus group will proceed with introductions. The focus group will be audio recorded from the completion of the introductions and notes will be taken. The focus group guide will address the study aims. At the end of the focus group, participants will complete a 7-item questionnaire to capture simple demographic information including education, income, and health literacy. This questionnaire will take 3-5 minutes to complete.

Focus groups

Jada Hamilton, PhD, MPH

The purpose of this study is to learn what cancer patients think about IBM Watson Oncology. IBM Watson Oncology is a computer program designed to help inform oncologists about the best chemotherapy choices for their patients. The investigators will conduct focus groups with cancer patients who have received chemotherapy treatment at MSK in order to understand cancer patients' thoughts about IBM Watson Oncology.

Examining Patient Preferences About the IBM Watson Oncology Clinical Decision Support System

Data collected through the brief questionnaires (e.g.,initial impressions of IBM Watson Oncology, sociodemographics) will be entered into an SPSS data file on the secure MSK server.

Study title	NCT ID	Conditions	Interventions	Eligibility	Organization
Development of a Clinical Decision Support System With Artificial Intelligence for Cancer Care	NCT04675138	Gastric Cancer Esophageal Canc... Esophagogastric...	No intervention...	21 Years -	National University Hospital, Singapore
Examining Patient Preferences About the IBM Watson Oncology Clinical Decision Support System	NCT02565017	Breast Cancer Lung Cancer Colorectal Canc...	Focus groups	18 Years -	Memorial Sloan Kettering Cancer Center
Development of a Clinical Decision Support System With Artificial Intelligence for Cancer Care	NCT04675138	Gastric Cancer Esophageal Canc... Esophagogastric...	No intervention...	21 Years -	National University Hospital, Singapore
Development of a Clinical Decision Support System With Artificial Intelligence for Cancer Care	NCT04675138	Gastric Cancer Esophageal Canc... Esophagogastric...	No intervention...	21 Years -	National University Hospital, Singapore

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