A mixed-methods feasibility study of a novel AI-enabled, web-based, clinical decision support system for the treatment of major depression in adults
Background: The objective of this paper is to discuss perceived clinical utility and impact on physician-patient relationship of a novel, artificial-intelligence (AI) enabled clinical decision support system (CDSS) for use in treating adults with major depression. Methods: A single arm, naturalistic...
| Main Authors: | , , , , , , , , , , , , , , , , , , , , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2023-12-01
|
| Series: | Journal of Affective Disorders Reports |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2666915323002159 |
| _version_ | 1797526205125099520 |
|---|---|
| author | Sabrina Qassim Grace Golden Dominique Slowey Mary Sarfas Kate Whitmore Tamara Perez Elizabeth Strong Eryn Lundrigan Marie-Jeanne Fradette Jacob Baxter Bennet Desormeau Myriam Tanguay-Sela Christina Popescu Sonia Israel Kelly Perlman Caitrin Armstrong Robert Fratila Joseph Mehltretter Karl Looper Warren Steiner Soham Rej Jordan F. Karp Katherine Heller Sagar V. Parikh Rebecca McGuire-Snieckus Manuela Ferrari Howard Margolese David Benrimoh |
| author_facet | Sabrina Qassim Grace Golden Dominique Slowey Mary Sarfas Kate Whitmore Tamara Perez Elizabeth Strong Eryn Lundrigan Marie-Jeanne Fradette Jacob Baxter Bennet Desormeau Myriam Tanguay-Sela Christina Popescu Sonia Israel Kelly Perlman Caitrin Armstrong Robert Fratila Joseph Mehltretter Karl Looper Warren Steiner Soham Rej Jordan F. Karp Katherine Heller Sagar V. Parikh Rebecca McGuire-Snieckus Manuela Ferrari Howard Margolese David Benrimoh |
| author_sort | Sabrina Qassim |
| collection | DOAJ |
| description | Background: The objective of this paper is to discuss perceived clinical utility and impact on physician-patient relationship of a novel, artificial-intelligence (AI) enabled clinical decision support system (CDSS) for use in treating adults with major depression. Methods: A single arm, naturalistic follow-up study aimed at assessing the acceptability and useability of the software. Patients had a baseline appointment, followed by a minimum of two appointments with the CDSS. Study exit questionnaires and interviews were conducted to assess perceived clinical utility, impact on patient-physician relationship, and understanding and trust. 7 physicians and 17 patients, of which 14 completed, consented to participate. Results: 86 % of physicians (6/7) felt the information provided by the CDSS provided more comprehensive understanding of patient situations. 71 % (5/7) felt the information was helpful. 86 % of physicians (6/7) reported the AI/predictive model was useful when deciding treatment. 62 % of patients (8/13) reported improved care due to the tool, and 46 %(6/13) reported a significantly or somewhat improved physician-patient relationship 54 % reported no change. 71 % of physicians (5/7) and 62 % of patients (8/13) rated trusting the tool. Limitations: Small sample size and treatment changes prior to CDSS introduction limits ability to verify impact on outcomes. Conclusions: Qualitative results from 12 patient exit interviews are analyzed and presented. Findings suggest physicians perceived the tool as useful in conducting appointments and used it while deciding treatment. Physicians and patients generally found the tool trustworthy, and it may have positive effects on physician-patient relationships. (Study identifier: NCT04061642). |
| first_indexed | 2024-03-10T09:25:56Z |
| format | Article |
| id | doaj.art-ade7a21ee6d3402da91c6bda29e3dbd2 |
| institution | Directory Open Access Journal |
| issn | 2666-9153 |
| language | English |
| last_indexed | 2024-03-10T09:25:56Z |
| publishDate | 2023-12-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Journal of Affective Disorders Reports |
| spelling | doaj.art-ade7a21ee6d3402da91c6bda29e3dbd22023-11-22T04:49:13ZengElsevierJournal of Affective Disorders Reports2666-91532023-12-0114100677A mixed-methods feasibility study of a novel AI-enabled, web-based, clinical decision support system for the treatment of major depression in adultsSabrina Qassim0Grace Golden1Dominique Slowey2Mary Sarfas3Kate Whitmore4Tamara Perez5Elizabeth Strong6Eryn Lundrigan7Marie-Jeanne Fradette8Jacob Baxter9Bennet Desormeau10Myriam Tanguay-Sela11Christina Popescu12Sonia Israel13Kelly Perlman14Caitrin Armstrong15Robert Fratila16Joseph Mehltretter17Karl Looper18Warren Steiner19Soham Rej20Jordan F. Karp21Katherine Heller22Sagar V. Parikh23Rebecca McGuire-Snieckus24Manuela Ferrari25Howard Margolese26David Benrimoh27University of Waterloo, Canada, ON, Waterloo, N2L 3G1; Aifred Health Inc., Canada, Quebec, Montreal, H3J 1M1University of Waterloo, Canada, ON, Waterloo, N2L 3G1; Aifred Health Inc., Canada, Quebec, Montreal, H3J 1M1McGill University, Canada, Quebec, Montreal, H3A 0G4; Aifred Health Inc., Canada, Quebec, Montreal, H3J 1M1McGill University, Canada, Quebec, Montreal, H3A 0G4; Aifred Health Inc., Canada, Quebec, Montreal, H3J 1M1McGill University, Canada, Quebec, Montreal, H3A 0G4; Aifred Health Inc., Canada, Quebec, Montreal, H3J 1M1McGill University, Canada, Quebec, Montreal, H3A 0G4; Aifred Health Inc., Canada, Quebec, Montreal, H3J 1M1McGill University, Canada, Quebec, Montreal, H3A 0G4; Aifred Health Inc., Canada, Quebec, Montreal, H3J 1M1McGill University, Canada, Quebec, Montreal, H3A 0G4; Aifred Health Inc., Canada, Quebec, Montreal, H3J 1M1McGill University, Canada, Quebec, Montreal, H3A 0G4; Aifred Health Inc., Canada, Quebec, Montreal, H3J 1M1McGill University, Canada, Quebec, Montreal, H3A 0G4; Aifred Health Inc., Canada, Quebec, Montreal, H3J 1M1McGill University, Canada, Quebec, Montreal, H3A 0G4; Aifred Health Inc., Canada, Quebec, Montreal, H3J 1M1Aifred Health Inc., Canada, Quebec, Montreal, H3J 1M1Aifred Health Inc., Canada, Quebec, Montreal, H3J 1M1Aifred Health Inc., Canada, Quebec, Montreal, H3J 1M1McGill University, Canada, Quebec, Montreal, H3A 0G4; Aifred Health Inc., Canada, Quebec, Montreal, H3J 1M1Aifred Health Inc., Canada, Quebec, Montreal, H3J 1M1Aifred Health Inc., Canada, Quebec, Montreal, H3J 1M1Aifred Health Inc., Canada, Quebec, Montreal, H3J 1M1Department of Psychiatry, McGill University, Canada, Quebec, Montreal, H3A 0G4Department of Psychiatry, McGill University, Canada, Quebec, Montreal, H3A 0G4Department of Psychiatry, McGill University, Canada, Quebec, Montreal, H3A 0G4University of Arizona, United States, Arizona, Tucson, 85721Duke University, United States, North Carolina, Durham, 27708University of Michigan, United States, Ann Arbor, 48109Barts and the London School of Medicine, United Kingdom, England, London, E1 2ADDouglas Mental Health University Institute, McGill University, Canada, Quebec, Verdun, H4H 1R3Department of Psychiatry, McGill University, Canada, Quebec, Montreal, H3A 0G4Aifred Health Inc., Canada, Quebec, Montreal, H3J 1M1; Department of Psychiatry, McGill University, Canada, Quebec, Montreal, H3A 0G4; Corresponding author at: 304-1600 Rue Notre-Dame O, Montreal, QC, Canada, H3J 1M1.Background: The objective of this paper is to discuss perceived clinical utility and impact on physician-patient relationship of a novel, artificial-intelligence (AI) enabled clinical decision support system (CDSS) for use in treating adults with major depression. Methods: A single arm, naturalistic follow-up study aimed at assessing the acceptability and useability of the software. Patients had a baseline appointment, followed by a minimum of two appointments with the CDSS. Study exit questionnaires and interviews were conducted to assess perceived clinical utility, impact on patient-physician relationship, and understanding and trust. 7 physicians and 17 patients, of which 14 completed, consented to participate. Results: 86 % of physicians (6/7) felt the information provided by the CDSS provided more comprehensive understanding of patient situations. 71 % (5/7) felt the information was helpful. 86 % of physicians (6/7) reported the AI/predictive model was useful when deciding treatment. 62 % of patients (8/13) reported improved care due to the tool, and 46 %(6/13) reported a significantly or somewhat improved physician-patient relationship 54 % reported no change. 71 % of physicians (5/7) and 62 % of patients (8/13) rated trusting the tool. Limitations: Small sample size and treatment changes prior to CDSS introduction limits ability to verify impact on outcomes. Conclusions: Qualitative results from 12 patient exit interviews are analyzed and presented. Findings suggest physicians perceived the tool as useful in conducting appointments and used it while deciding treatment. Physicians and patients generally found the tool trustworthy, and it may have positive effects on physician-patient relationships. (Study identifier: NCT04061642).http://www.sciencedirect.com/science/article/pii/S2666915323002159Clinical decision support systemMajor depressive disorderArtificial intelligenceFeasibilityPhysician-patient relationshipTrust |
| spellingShingle | Sabrina Qassim Grace Golden Dominique Slowey Mary Sarfas Kate Whitmore Tamara Perez Elizabeth Strong Eryn Lundrigan Marie-Jeanne Fradette Jacob Baxter Bennet Desormeau Myriam Tanguay-Sela Christina Popescu Sonia Israel Kelly Perlman Caitrin Armstrong Robert Fratila Joseph Mehltretter Karl Looper Warren Steiner Soham Rej Jordan F. Karp Katherine Heller Sagar V. Parikh Rebecca McGuire-Snieckus Manuela Ferrari Howard Margolese David Benrimoh A mixed-methods feasibility study of a novel AI-enabled, web-based, clinical decision support system for the treatment of major depression in adults Journal of Affective Disorders Reports Clinical decision support system Major depressive disorder Artificial intelligence Feasibility Physician-patient relationship Trust |
| title | A mixed-methods feasibility study of a novel AI-enabled, web-based, clinical decision support system for the treatment of major depression in adults |
| title_full | A mixed-methods feasibility study of a novel AI-enabled, web-based, clinical decision support system for the treatment of major depression in adults |
| title_fullStr | A mixed-methods feasibility study of a novel AI-enabled, web-based, clinical decision support system for the treatment of major depression in adults |
| title_full_unstemmed | A mixed-methods feasibility study of a novel AI-enabled, web-based, clinical decision support system for the treatment of major depression in adults |
| title_short | A mixed-methods feasibility study of a novel AI-enabled, web-based, clinical decision support system for the treatment of major depression in adults |
| title_sort | mixed methods feasibility study of a novel ai enabled web based clinical decision support system for the treatment of major depression in adults |
| topic | Clinical decision support system Major depressive disorder Artificial intelligence Feasibility Physician-patient relationship Trust |
| url | http://www.sciencedirect.com/science/article/pii/S2666915323002159 |
| work_keys_str_mv | AT sabrinaqassim amixedmethodsfeasibilitystudyofanovelaienabledwebbasedclinicaldecisionsupportsystemforthetreatmentofmajordepressioninadults AT gracegolden amixedmethodsfeasibilitystudyofanovelaienabledwebbasedclinicaldecisionsupportsystemforthetreatmentofmajordepressioninadults AT dominiqueslowey amixedmethodsfeasibilitystudyofanovelaienabledwebbasedclinicaldecisionsupportsystemforthetreatmentofmajordepressioninadults AT marysarfas amixedmethodsfeasibilitystudyofanovelaienabledwebbasedclinicaldecisionsupportsystemforthetreatmentofmajordepressioninadults AT katewhitmore amixedmethodsfeasibilitystudyofanovelaienabledwebbasedclinicaldecisionsupportsystemforthetreatmentofmajordepressioninadults AT tamaraperez amixedmethodsfeasibilitystudyofanovelaienabledwebbasedclinicaldecisionsupportsystemforthetreatmentofmajordepressioninadults AT elizabethstrong amixedmethodsfeasibilitystudyofanovelaienabledwebbasedclinicaldecisionsupportsystemforthetreatmentofmajordepressioninadults AT erynlundrigan amixedmethodsfeasibilitystudyofanovelaienabledwebbasedclinicaldecisionsupportsystemforthetreatmentofmajordepressioninadults AT mariejeannefradette amixedmethodsfeasibilitystudyofanovelaienabledwebbasedclinicaldecisionsupportsystemforthetreatmentofmajordepressioninadults AT jacobbaxter amixedmethodsfeasibilitystudyofanovelaienabledwebbasedclinicaldecisionsupportsystemforthetreatmentofmajordepressioninadults AT bennetdesormeau amixedmethodsfeasibilitystudyofanovelaienabledwebbasedclinicaldecisionsupportsystemforthetreatmentofmajordepressioninadults AT myriamtanguaysela amixedmethodsfeasibilitystudyofanovelaienabledwebbasedclinicaldecisionsupportsystemforthetreatmentofmajordepressioninadults AT christinapopescu amixedmethodsfeasibilitystudyofanovelaienabledwebbasedclinicaldecisionsupportsystemforthetreatmentofmajordepressioninadults AT soniaisrael amixedmethodsfeasibilitystudyofanovelaienabledwebbasedclinicaldecisionsupportsystemforthetreatmentofmajordepressioninadults AT kellyperlman amixedmethodsfeasibilitystudyofanovelaienabledwebbasedclinicaldecisionsupportsystemforthetreatmentofmajordepressioninadults AT caitrinarmstrong amixedmethodsfeasibilitystudyofanovelaienabledwebbasedclinicaldecisionsupportsystemforthetreatmentofmajordepressioninadults AT robertfratila amixedmethodsfeasibilitystudyofanovelaienabledwebbasedclinicaldecisionsupportsystemforthetreatmentofmajordepressioninadults AT josephmehltretter amixedmethodsfeasibilitystudyofanovelaienabledwebbasedclinicaldecisionsupportsystemforthetreatmentofmajordepressioninadults AT karllooper amixedmethodsfeasibilitystudyofanovelaienabledwebbasedclinicaldecisionsupportsystemforthetreatmentofmajordepressioninadults AT warrensteiner amixedmethodsfeasibilitystudyofanovelaienabledwebbasedclinicaldecisionsupportsystemforthetreatmentofmajordepressioninadults AT sohamrej amixedmethodsfeasibilitystudyofanovelaienabledwebbasedclinicaldecisionsupportsystemforthetreatmentofmajordepressioninadults AT jordanfkarp amixedmethodsfeasibilitystudyofanovelaienabledwebbasedclinicaldecisionsupportsystemforthetreatmentofmajordepressioninadults AT katherineheller amixedmethodsfeasibilitystudyofanovelaienabledwebbasedclinicaldecisionsupportsystemforthetreatmentofmajordepressioninadults AT sagarvparikh amixedmethodsfeasibilitystudyofanovelaienabledwebbasedclinicaldecisionsupportsystemforthetreatmentofmajordepressioninadults AT rebeccamcguiresnieckus amixedmethodsfeasibilitystudyofanovelaienabledwebbasedclinicaldecisionsupportsystemforthetreatmentofmajordepressioninadults AT manuelaferrari amixedmethodsfeasibilitystudyofanovelaienabledwebbasedclinicaldecisionsupportsystemforthetreatmentofmajordepressioninadults AT howardmargolese amixedmethodsfeasibilitystudyofanovelaienabledwebbasedclinicaldecisionsupportsystemforthetreatmentofmajordepressioninadults AT davidbenrimoh amixedmethodsfeasibilitystudyofanovelaienabledwebbasedclinicaldecisionsupportsystemforthetreatmentofmajordepressioninadults AT sabrinaqassim mixedmethodsfeasibilitystudyofanovelaienabledwebbasedclinicaldecisionsupportsystemforthetreatmentofmajordepressioninadults AT gracegolden mixedmethodsfeasibilitystudyofanovelaienabledwebbasedclinicaldecisionsupportsystemforthetreatmentofmajordepressioninadults AT dominiqueslowey mixedmethodsfeasibilitystudyofanovelaienabledwebbasedclinicaldecisionsupportsystemforthetreatmentofmajordepressioninadults AT marysarfas mixedmethodsfeasibilitystudyofanovelaienabledwebbasedclinicaldecisionsupportsystemforthetreatmentofmajordepressioninadults AT katewhitmore mixedmethodsfeasibilitystudyofanovelaienabledwebbasedclinicaldecisionsupportsystemforthetreatmentofmajordepressioninadults AT tamaraperez mixedmethodsfeasibilitystudyofanovelaienabledwebbasedclinicaldecisionsupportsystemforthetreatmentofmajordepressioninadults AT elizabethstrong mixedmethodsfeasibilitystudyofanovelaienabledwebbasedclinicaldecisionsupportsystemforthetreatmentofmajordepressioninadults AT erynlundrigan mixedmethodsfeasibilitystudyofanovelaienabledwebbasedclinicaldecisionsupportsystemforthetreatmentofmajordepressioninadults AT mariejeannefradette mixedmethodsfeasibilitystudyofanovelaienabledwebbasedclinicaldecisionsupportsystemforthetreatmentofmajordepressioninadults AT jacobbaxter mixedmethodsfeasibilitystudyofanovelaienabledwebbasedclinicaldecisionsupportsystemforthetreatmentofmajordepressioninadults AT bennetdesormeau mixedmethodsfeasibilitystudyofanovelaienabledwebbasedclinicaldecisionsupportsystemforthetreatmentofmajordepressioninadults AT myriamtanguaysela mixedmethodsfeasibilitystudyofanovelaienabledwebbasedclinicaldecisionsupportsystemforthetreatmentofmajordepressioninadults AT christinapopescu mixedmethodsfeasibilitystudyofanovelaienabledwebbasedclinicaldecisionsupportsystemforthetreatmentofmajordepressioninadults AT soniaisrael mixedmethodsfeasibilitystudyofanovelaienabledwebbasedclinicaldecisionsupportsystemforthetreatmentofmajordepressioninadults AT kellyperlman mixedmethodsfeasibilitystudyofanovelaienabledwebbasedclinicaldecisionsupportsystemforthetreatmentofmajordepressioninadults AT caitrinarmstrong mixedmethodsfeasibilitystudyofanovelaienabledwebbasedclinicaldecisionsupportsystemforthetreatmentofmajordepressioninadults AT robertfratila mixedmethodsfeasibilitystudyofanovelaienabledwebbasedclinicaldecisionsupportsystemforthetreatmentofmajordepressioninadults AT josephmehltretter mixedmethodsfeasibilitystudyofanovelaienabledwebbasedclinicaldecisionsupportsystemforthetreatmentofmajordepressioninadults AT karllooper mixedmethodsfeasibilitystudyofanovelaienabledwebbasedclinicaldecisionsupportsystemforthetreatmentofmajordepressioninadults AT warrensteiner mixedmethodsfeasibilitystudyofanovelaienabledwebbasedclinicaldecisionsupportsystemforthetreatmentofmajordepressioninadults AT sohamrej mixedmethodsfeasibilitystudyofanovelaienabledwebbasedclinicaldecisionsupportsystemforthetreatmentofmajordepressioninadults AT jordanfkarp mixedmethodsfeasibilitystudyofanovelaienabledwebbasedclinicaldecisionsupportsystemforthetreatmentofmajordepressioninadults AT katherineheller mixedmethodsfeasibilitystudyofanovelaienabledwebbasedclinicaldecisionsupportsystemforthetreatmentofmajordepressioninadults AT sagarvparikh mixedmethodsfeasibilitystudyofanovelaienabledwebbasedclinicaldecisionsupportsystemforthetreatmentofmajordepressioninadults AT rebeccamcguiresnieckus mixedmethodsfeasibilitystudyofanovelaienabledwebbasedclinicaldecisionsupportsystemforthetreatmentofmajordepressioninadults AT manuelaferrari mixedmethodsfeasibilitystudyofanovelaienabledwebbasedclinicaldecisionsupportsystemforthetreatmentofmajordepressioninadults AT howardmargolese mixedmethodsfeasibilitystudyofanovelaienabledwebbasedclinicaldecisionsupportsystemforthetreatmentofmajordepressioninadults AT davidbenrimoh mixedmethodsfeasibilitystudyofanovelaienabledwebbasedclinicaldecisionsupportsystemforthetreatmentofmajordepressioninadults |