Effect of an ML Electronic Alert Management System to Reduce the Use of ED Visits and Hospitalizations

NCT05221697 | Unknown DMC

• 1 other identifier: PRESAGE_2021-01
• Study Type: interventional
• Target: 800
• Locations: 1 country
• Sites: 2

Brief Summary

Development, validation and impact of an alert management system using social workers' observations and machine learning algorithms to predict 7-to-14-day alerts for the risk of Emergency Department (ED) Visit and unplanned hospitalization. Multi-center trial implementation of electronic Home Care Aides-reported outcomes measure system among patients, frail adults \>= 65 years living at home and receiving assistance from home care aides (HCA).

Conditions

Emergencies

Keywords

Emergency Department visits,; machine learning; smartphone

Outcome Measures

Primary Outcomes (4)

• Unplanned Hospitalization rate

  Comparison between unplanned hospitalization ratio from 2 randomized groups (intervention and control arms). P values \<.05 will be considered statistically significant.

  through study completion, an average of 1 year

• Event-free survival (EFS)

  Comparison average Time for first adverse event between intervention and control groups. P values \<.05 will be considered statistically significant.

  through study completion, an average of 1 year

• Impact on older adults and relatives' quality of life (European Quality of Life 5 Dimensions and 3 Lines scale)

  Comparison of the average score of EQ5D-3L quality of life scale (European Quality of Life 5 Dimensions and 3 Lines) between intervention and control groups. P values \<.05 will be considered statistically significant.

  through study completion, an average of 1 year

• Cost-effectiveness

  Incremental cost-effectiveness ratio (ICER), QALY. Willingness-to-pay thresholds of €30,000 per quality-adjusted life year (QALY) and €90,000 per QALY were used to define a very cost-effective and cost-effective strategy, respectively

  through study completion, an average of 1 year

Secondary Outcomes (6)

• Impact on users : time needed to complete questionnaire

  through study completion, an average of 1 year

• Intervention rate

  through study completion, an average of 1 year

• Intervention time

  through study completion, an average of 1 year

• Time needed to analysis patient statut

  through study completion, an average of 1 year

• Impact on quality of care

  through study completion, an average of 1 year

Study Arms (2)

Intervention

EXPERIMENTAL

PRESAGE Care ATIH + Nurse or GP consultation

Device: PRESAGE CARE

Control group

NO INTERVENTION

usual care

Interventions

PRESAGE CARE DEVICE

Participants in this arm will be followed by HCA and might benefit from Nurse health interventions

Intervention

Eligibility Criteria

• Age: 75 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Older Adult (65+)

You may qualify if:

• age of 75 yo mini
• receiving the help of a social worker
• patient should give their consent
• patient should had seen their primary care professional within the past 12 months

You may not qualify if:

• People with severe dependence (French national instrument, which stratifies dependency level from group iso-resources (GIR) : 1 (very severe dependency) and 2 (severe dependency)

Sponsors & Collaborators

• Presage: lead
• Assistance Publique Hopitaux De Marseille: collaborator
• Assistance Publique - Hôpitaux de Paris: collaborator
• University Hospital, Lille: collaborator

Study Sites (2)

Grand Versailles

Le Chesnay, 78150, France

Location

Marseille-1

Marseille, 13011, France

Location

Related Publications (35)

• Clerencia-Sierra M, Calderon-Larranaga A, Martinez-Velilla N, Vergara-Mitxeltorena I, Aldaz-Herce P, Poblador-Plou B, Machon-Sobrado M, Egues-Olazabal N, Abellan-van Kan G, Prados-Torres A. Multimorbidity Patterns in Hospitalized Older Patients: Associations among Chronic Diseases and Geriatric Syndromes. PLoS One. 2015 Jul 24;10(7):e0132909. doi: 10.1371/journal.pone.0132909. eCollection 2015.

  PMID: 26208112 BACKGROUND

• Kahn JH, Magauran BG Jr, Olshaker JS, Shankar KN. Current Trends in Geriatric Emergency Medicine. Emerg Med Clin North Am. 2016 Aug;34(3):435-52. doi: 10.1016/j.emc.2016.04.014.

  PMID: 27475008 BACKGROUND

• Gasperini B, Cherubini A, Pierri F, Barbadoro P, Fedecostante M, Prospero E. Potentially preventable visits to the emergency department in older adults: Results from a national survey in Italy. PLoS One. 2017 Dec 21;12(12):e0189925. doi: 10.1371/journal.pone.0189925. eCollection 2017.

  PMID: 29267333 BACKGROUND

• McCusker J, Verdon J. Do geriatric interventions reduce emergency department visits? A systematic review. J Gerontol A Biol Sci Med Sci. 2006 Jan;61(1):53-62. doi: 10.1093/gerona/61.1.53.

  PMID: 16456194 BACKGROUND

• Inglis SC, Clark RA, McAlister FA, Ball J, Lewinter C, Cullington D, Stewart S, Cleland JG. Structured telephone support or telemonitoring programmes for patients with chronic heart failure. Cochrane Database Syst Rev. 2010 Aug 4;(8):CD007228. doi: 10.1002/14651858.CD007228.pub2.

  PMID: 20687083 BACKGROUND

• Chen CC, Wang C, Huang GH. Functional trajectory 6 months posthospitalization: a cohort study of older hospitalized patients in Taiwan. Nurs Res. 2008 Mar-Apr;57(2):93-100. doi: 10.1097/01.NNR.0000313485.18670.e2.

  PMID: 18347480 BACKGROUND

• Iwashyna TJ, Ely EW, Smith DM, Langa KM. Long-term cognitive impairment and functional disability among survivors of severe sepsis. JAMA. 2010 Oct 27;304(16):1787-94. doi: 10.1001/jama.2010.1553.

  PMID: 20978258 BACKGROUND

• Camargo CA Jr, Tsai CL, Sullivan AF, Cleary PD, Gordon JA, Guadagnoli E, Kaushal R, Magid DJ, Rao SR, Blumenthal D. Safety climate and medical errors in 62 US emergency departments. Ann Emerg Med. 2012 Nov;60(5):555-563.e20. doi: 10.1016/j.annemergmed.2012.02.018.

  PMID: 23089089 BACKGROUND

• Crane SJ, Tung EE, Hanson GJ, Cha S, Chaudhry R, Takahashi PY. Use of an electronic administrative database to identify older community dwelling adults at high-risk for hospitalization or emergency department visits: the elders risk assessment index. BMC Health Serv Res. 2010 Dec 13;10:338. doi: 10.1186/1472-6963-10-338.

  PMID: 21144042 BACKGROUND

• Hu Z, Jin B, Shin AY, Zhu C, Zhao Y, Hao S, Zheng L, Fu C, Wen Q, Ji J, Li Z, Wang Y, Zheng X, Dai D, Culver DS, Alfreds ST, Rogow T, Stearns F, Sylvester KG, Widen E, Ling XB. Real-time web-based assessment of total population risk of future emergency department utilization: statewide prospective active case finding study. Interact J Med Res. 2015 Jan 13;4(1):e2. doi: 10.2196/ijmr.4022.

  PMID: 25586600 BACKGROUND

• Takahashi PY, Heien HC, Sangaralingham LR, Shah ND, Naessens JM. Enhanced risk prediction model for emergency department use and hospitalizations in patients in a primary care medical home. Am J Manag Care. 2016 Jul;22(7):475-83.

  PMID: 27442203 BACKGROUND

• Denis F, Krakowski I. How Should Oncologists Choose an Electronic Patient-Reported Outcome System for Remote Monitoring of Patients With Cancer? J Med Internet Res. 2021 Sep 9;23(9):e30549. doi: 10.2196/30549.

  PMID: 34499046 BACKGROUND

• Bouazza YB, Chiairi I, El Kharbouchi O, De Backer L, Vanhoutte G, Janssens A, Van Meerbeeck JP. Patient-reported outcome measures (PROMs) in the management of lung cancer: A systematic review. Lung Cancer. 2017 Nov;113:140-151. doi: 10.1016/j.lungcan.2017.09.011. Epub 2017 Sep 23.

  PMID: 29110842 BACKGROUND

• Schick-Makaroff K, Karimi-Dehkordi M, Cuthbertson L, Dixon D, Cohen SR, Hilliard N, Sawatzky R. Using Patient- and Family-Reported Outcome and Experience Measures Across Transitions of Care for Frail Older Adults Living at Home: A Meta-Narrative Synthesis. Gerontologist. 2021 Apr 3;61(3):e23-e38. doi: 10.1093/geront/gnz162.

  PMID: 31942997 BACKGROUND

• Veyron JH, Friocourt P, Jeanjean O, Luquel L, Bonifas N, Denis F, Belmin J. Home care aides' observations and machine learning algorithms for the prediction of visits to emergency departments by older community-dwelling individuals receiving home care assistance: A proof of concept study. PLoS One. 2019 Aug 13;14(8):e0220002. doi: 10.1371/journal.pone.0220002. eCollection 2019.

  PMID: 31408458 BACKGROUND

• Huntley AL, Chalder M, Shaw ARG, Hollingworth W, Metcalfe C, Benger JR, Purdy S. A systematic review to identify and assess the effectiveness of alternatives for people over the age of 65 who are at risk of potentially avoidable hospital admission. BMJ Open. 2017 Aug 1;7(7):e016236. doi: 10.1136/bmjopen-2017-016236.

  PMID: 28765132 BACKGROUND

• Seibert K, Domhoff D, Bruch D, Schulte-Althoff M, Furstenau D, Biessmann F, Wolf-Ostermann K. Application Scenarios for Artificial Intelligence in Nursing Care: Rapid Review. J Med Internet Res. 2021 Nov 29;23(11):e26522. doi: 10.2196/26522.

  PMID: 34847057 BACKGROUND

• Gray JT, Walker A. Avoiding admissions from the ambulance service: a review of elderly patients with falls and patients with breathing difficulties seen by emergency care practitioners in South Yorkshire. Emerg Med J. 2008 Mar;25(3):168-71. doi: 10.1136/emj.2007.050732.

  PMID: 18299372 BACKGROUND

• Mason S, O'Keeffe C, Knowles E, Bradburn M, Campbell M, Coleman P, Stride C, O'Hara R, Rick J, Patterson M. A pragmatic quasi-experimental multi-site community intervention trial evaluating the impact of Emergency Care Practitioners in different UK health settings on patient pathways (NEECaP Trial). Emerg Med J. 2012 Jan;29(1):47-53. doi: 10.1136/emj.2010.103572.

  PMID: 22186262 BACKGROUND

• Mason S, Knowles E, Colwell B, Dixon S, Wardrope J, Gorringe R, Snooks H, Perrin J, Nicholl J. Effectiveness of paramedic practitioners in attending 999 calls from elderly people in the community: cluster randomised controlled trial. BMJ. 2007 Nov 3;335(7626):919. doi: 10.1136/bmj.39343.649097.55. Epub 2007 Oct 4.

  PMID: 17916813 BACKGROUND

• Soril LJ, Leggett LE, Lorenzetti DL, Noseworthy TW, Clement FM. Reducing frequent visits to the emergency department: a systematic review of interventions. PLoS One. 2015 Apr 13;10(4):e0123660. doi: 10.1371/journal.pone.0123660. eCollection 2015.

  PMID: 25874866 BACKGROUND

• Belmin J, Auffray JC, Berbezier C, Boirin P, Mercier S, de Reviers B, Golmard JL. Level of dependency: a simple marker associated with mortality during the 2003 heatwave among French dependent elderly people living in the community or in institutions. Age Ageing. 2007 May;36(3):298-303. doi: 10.1093/ageing/afm026. Epub 2007 Mar 24.

  PMID: 17384419 BACKGROUND

• O'Connell S, Palmer R, Withers K, Saha N, Puntoni S, Carolan-Rees G; PROMs, PREMs and Effectiveness Programme. Requirements for the collection of electronic PROMS either "in clinic" or "at home" as part of the PROMs, PREMs and Effectiveness Programme (PPEP) in Wales: a feasibility study using a generic PROM tool. Pilot Feasibility Stud. 2018 Jul 4;4:90. doi: 10.1186/s40814-018-0282-8. eCollection 2018.

  PMID: 29997899 BACKGROUND

• Duncanson E, Bennett PN, Viecelli A, Dansie K, Handke W, Tong A, Palmer S, Jesudason S, McDonald SP, Morton RL; Symptom monitoring WIth Feedback Trial (SWIFT) Investigators. Feasibility and acceptability of e-PROMs data capture and feedback among patients receiving haemodialysis in the Symptom monitoring WIth Feedback Trial (SWIFT) pilot: protocol for a qualitative study in Australia. BMJ Open. 2020 Nov 6;10(11):e039014. doi: 10.1136/bmjopen-2020-039014.

  PMID: 33158824 BACKGROUND

• Anderson KO, Palos GR, Mendoza TR, Cleeland CS, Liao KP, Fisch MJ, Garcia-Gonzalez A, Rieber AG, Nazario LA, Valero V, Hahn KM, Person CL, Payne R. Automated pain intervention for underserved minority women with breast cancer. Cancer. 2015 Jun 1;121(11):1882-90. doi: 10.1002/cncr.29204. Epub 2015 Feb 24.

  PMID: 25711974 BACKGROUND

• Adam R, Burton CD, Bond CM, de Bruin M, Murchie P. Can patient-reported measurements of pain be used to improve cancer pain management? A systematic review and meta-analysis. BMJ Support Palliat Care. 2017 Dec;7(4):0. doi: 10.1136/bmjspcare-2016-001137. Epub 2016 Nov 22.

  PMID: 27879472 BACKGROUND

• Mooney KH, Beck SL, Friedman RH, Farzanfar R, Wong B. Automated monitoring of symptoms during ambulatory chemotherapy and oncology providers' use of the information: a randomized controlled clinical trial. Support Care Cancer. 2014 Sep;22(9):2343-50. doi: 10.1007/s00520-014-2216-1. Epub 2014 Apr 1.

  PMID: 24687538 BACKGROUND

• Vasey B, Ursprung S, Beddoe B, Taylor EH, Marlow N, Bilbro N, Watkinson P, McCulloch P. Association of Clinician Diagnostic Performance With Machine Learning-Based Decision Support Systems: A Systematic Review. JAMA Netw Open. 2021 Mar 1;4(3):e211276. doi: 10.1001/jamanetworkopen.2021.1276.

  PMID: 33704476 BACKGROUND

• Adler-Milstein J, Chen JH, Dhaliwal G. Next-Generation Artificial Intelligence for Diagnosis: From Predicting Diagnostic Labels to "Wayfinding". JAMA. 2021 Dec 28;326(24):2467-2468. doi: 10.1001/jama.2021.22396. No abstract available.

  PMID: 34882190 BACKGROUND

• Barrachina-Fernandez M, Maitin AM, Sanchez-Avila C, Romero JP. Wearable Technology to Detect Motor Fluctuations in Parkinson's Disease Patients: Current State and Challenges. Sensors (Basel). 2021 Jun 18;21(12):4188. doi: 10.3390/s21124188.

  PMID: 34207198 BACKGROUND

• Khalil H, Bell B, Chambers H, Sheikh A, Avery AJ. Professional, structural and organisational interventions in primary care for reducing medication errors. Cochrane Database Syst Rev. 2017 Oct 4;10(10):CD003942. doi: 10.1002/14651858.CD003942.pub3.

  PMID: 28977687 BACKGROUND

• Beaudouin, Valérie and Bloch, Isabelle and Bounie, David and Bounie, David and Clémençon, Stéphan and d'Alché-Buc, Florence and Eagan, James and Maxwell, Winston and Mozharovskyi, Pavlo and Parekh, Jayneel, Flexible and Context-Specific AI Explainability: A Multidisciplinary Approach (March 23, 2020). Available at SSRN: https://ssrn.com/abstract=3559477 or http://dx.doi.org/10.2139/ssrn.3559477

  BACKGROUND

• Havreng-Thery C, Fouchard A, Denis F, Veyron JH, Belmin J. Cost-Effectiveness Analysis of a Machine Learning-Based eHealth System to Predict and Reduce Emergency Department Visits and Unscheduled Hospitalizations of Older People Living at Home: Retrospective Study. JMIR Form Res. 2025 Apr 11;9:e63700. doi: 10.2196/63700.

  PMID: 40215100 DERIVED

• Veyron JH, Deparis F, Al Zayat MN, Belmin J, Havreng-Thery C. Postimplementation Evaluation in Assisted Living Facilities of an eHealth Medical Device Developed to Predict and Avoid Unplanned Hospitalizations: Pragmatic Trial. J Med Internet Res. 2024 Dec 10;26:e55460. doi: 10.2196/55460.

  PMID: 39657177 DERIVED

• Belmin J, Villani P, Gay M, Fabries S, Havreng-Thery C, Malvoisin S, Denis F, Veyron JH. Real-world Implementation of an eHealth System Based on Artificial Intelligence Designed to Predict and Reduce Emergency Department Visits by Older Adults: Pragmatic Trial. J Med Internet Res. 2022 Sep 8;24(9):e40387. doi: 10.2196/40387.

  PMID: 35921685 DERIVED

MeSH Terms

Conditions

Emergencies

Condition Hierarchy (Ancestors)

Disease Attributes; Pathologic Processes; Pathological Conditions, Signs and Symptoms

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: RANDOMIZED
• Masking: NONE
• Purpose: PREVENTION
• Intervention Model: PARALLEL
• Sponsor Type: INDUSTRY
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: January 7, 2022
• First Posted: February 3, 2022
• Study Start: September 1, 2020
• Primary Completion: December 31, 2021
• Study Completion: June 30, 2024
• Last Updated: August 30, 2023

Record last verified: 2023-08

Data Sharing

• IPD Sharing: Will not share

Locations

FR (2)