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Not yet recruitingNCT06522698SPBUpdated Jul 26, 2024

Optimizing Research Data Acquisition With Smart Pill Bottles

An interventional study of Smart Pill Bottle in Post Operative Pain and Opioid Use, sponsored by Ciusss de L'Est de l'Île de Montréal. Not yet recruiting at 1 site in Canada. Open to participants aged 18 Years and older. Per ClinicalTrials.gov, last updated 2024-07-26.

Sponsored by Ciusss de L'Est de l'Île de Montréal · Not applicable, Interventional, and Supportive care

From the registry’s dates

  • Primary completion was expected by Jul 2025, 1 year 3 months ago, but the record still lists the study as not yet recruiting.
Phase
Not applicable
Study type
Interventional
Enrollment
155
Allocation
Not applicable
Ages
18 Years and older
Sex
All
01

Study summary

The goal of this clinical trial is to learn if smart pill bottles can be used as a tool to optimize data collection in clinical trials by increasing the quality of data collected and limiting the associated cost. The main questions it aims to answer are:

Is the use of smart pill bottles a feasible method of data collection in clinical trials in terms of patient adherence.

Is the data collected by the smart pill bottles of higher quality than that collected through human resources? What is the impact of the use of smart pill bottles on the costs involved in clinical trials ?

Researchers will collect data on postoperative opioid medication consumption with the smart pill bottle and assess the adherence of patients to the device along with the quality of data collected and the costs involved in the process.

Participants will:

Use the smart pill bottle to consume opioid medication following surgery for 3 months At the end of the 3 month period, the group will have filled out surveys detailing their opioid consumption, surgical pain and other relevant information.

Read the detailed description

Several studies involving harnessing new technology to approach data collection have suggested that a streamlined and automated method of collecting data through connected technology can help set up cohort studies more cost-effectively. Evaluating the use of a connected device as a research tool in clinical trials and comparing it with traditional data collection using human resources would provide valuable insights into its efficiency and effectiveness. Smart medication adherence monitoring devices are a novel technology that provides objective and granular medication utilization data along with engaging patients with their treatment. Particularly, the smart pill bottle (SPB) is a rapidly developing technology that allows for medication monitoring of solid doses with the use of electronic sensors that can collect data on medication usage in real time and offer direct communication between patients and healthcare professionals or trialists. SPBs have shown efficacy in monitoring compliance and possibly increasing medication adherence in the clinical setting and the technology has been suggested as a potential research tool that would allow automatic collection of granular and precise data on the time of medication intake, dose, and frequency. However, there hasn't been a trial comparing the efficacy of using SPBs for data collection in clinical trials versus the traditional method reliant on human resources in comparable contexts. Based on the properties of SPBs and available literature supporting the automatization and streamlining of data in clinical trials, the investigators believe that the use of these devices may allow data collection of higher quality regarding granularity, number of losses of follow-up, completeness, missing data points along with a reduction of costs incurred by avoiding the use of human resources.

The aim of this study is to evaluate the feasibility of using smart pill bottles (SPBs) to optimize data collection in the context of randomized control trials.

The project will be a prospective observational study conducted at the CIUSSS-de-l'Est-de-l'Île-de-Montréal (Hôpital Maisonneuve-Rosemont) over a period of 6 to 12 months.

To do so, 155 patients undergoing major abdominal surgery with postoperative opioid medication prescription will be recruited. These patient's medication consumption will be monitored with the use of a smart pill bottle for a duration of 90 days. The results of this cohort will be compared with a historical cohort from a previous study conducted within the same hospital network. The protocol for the current trial was purposefully designed to be comparable to that of this historical cohort.

A loan of 50 SPBs will be obtained from Thess Corporate (Company producing smart pill bottles).

02

Conditions studied

  • Post Operative Pain
  • Opioid Use

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Keywords

  • Major abdominal surgery
  • Connected Technology
  • Chronic Pain
  • Postoperative pain
  • Opioid consumption
  • Smart Pill Bottles
03

In context

Pain, Postoperative

5,093 studies on the registry are indexed under Pain, Postoperative; 1,140 are open to participants now.

This study's planned enrollment of 155 is above the median of 75 across 4,344 interventional studies indexed under Pain, Postoperative.

Browse Pain, Postoperative studies →

Lead sponsor

Ciusss de L'Est de l'Île de Montréal is the lead sponsor of 87 studies on the registry; 32 are open to participants now.

Counted across the registry records on this site, refreshed daily.

04

Who can participate

Ages eligible
18 Years and older
Sexes eligible
All
Accepts healthy volunteers
No

Inclusion criteria

  • All consenting adult patients (age >17 years) undergoing major abdominal surgery via laparotomy (any open surgery involving the abdominal compartment or its wall, excluding appendectomies, inguinal hernia repairs, abdominal wall hernia repairs, and incisional hernia repairs)

Exclusion criteria

Exclusion Criteria:

  • Patients enrolled in the historical cohort (POCAS study)
  • Patients currently participating in another study
  • Patients planned to undergo additional surgery within 90 days after the surgery
  • Patients who do not understand French or English.
  • Patients planned to be redirected to a secondary care or rehabilitation establishment following discharge
  • Patients with diagnosed cognitive impairment
05

Study design

Phase
Not applicable
Primary purpose
Supportive care
Allocation
Not applicable
Intervention model
Single group
Masking
None (open label)
Enrollment
155 participants (estimated)

Study arms

  • Experimental
    Smart Pill Bottle Data Collection Group

    Group of patients in which data on postoperative opioid medication consumption will be collected through the use of smart pill bottles.

    Device: Smart Pill Bottle

Interventions

  • DeviceSmart Pill Bottle

    Patients in the intervention group will have their opioid medication consumption monitored through a smart pill bottle that records medication usage and streamlines the data into an online platform accessible by the medical staff. This group will also fill out surveys delivered through the smart pill bottle's online platform.

    Also known as: Connected Pill Bottle

06

What researchers measure

Primary outcomes

  1. Patient adherence to data collection method

    The percentage of patients that will have used the smart pill bottle (SPB) until the end of the 90-day period or until the absence of pain, as opposed to any change in medication intake strategy that results in ceasing the use of the SPB. (High percentage is a better outcome)

    Time frame: 3 months

Secondary outcomes

  1. The quality of data acquired through the SPBs

    The granularity of data acquired, the preciseness of data points, the number of loss of follow-up compared with the historical cohort from the POCAS study which collected data from a comparable patient group through human resources.

    Time frame: 3 months

  2. The costs incurred from carrying out the project

    The costs incurred from carrying out the project compared with the historical cohort from the POCAS study which collected data from a comparable patient group through human resources.

    Time frame: 3 months

  3. The time for recruitment of patients

    The time for recruitment of patients compared with the historical cohort from the POCAS study which collected data from a comparable patient group through human resources. (Lower time is a better outcome)

    Time frame: Up to12 months

  4. Prevalence of persistent opioid consumption 90 days after surgery

    Persistent opioid consumption (POC) 90 days after surgery as reported by the SPBs. POC will be defined as consumption of any quantity of opioids in the 7 days prior to the 90-day interrogation. This definition will be accurate for both preoperative chronic and non-chronic opioid users. (Higher rate of persistent consumption is a worse outcome)

    Time frame: 7 days

  5. Prevalence of Chronic post-surgical pain 90 days after surgery

    The presence of chronic post-surgical pain (CPSP) in the 7 days prior to the interrogation (interrogation occurs at 90 days post-op). CPSP will be defined as any pain at the surgical site for patients who had pain at that site before surgery (by 1 point on the general numerical pain scoring question of the BPI questionnaire) (12).

    Time frame: 7 days

  6. Change in Quality of Life

    The change in the reported quality of life at 90 days post-op. QOL will be measured as a continuous variable on the SF-12 questionnaire.

    Time frame: 3 months

07

Study locations

1 site
  • Maisonneuve-Rosemont Hospital - CIUSSS de l'Est de l'Île de Montréal
    Montréal-Est, Quebec H1T2M4, Canada
08

References and documents

Publications

  • Catala-Lopez F, Aleixandre-Benavent R, Caulley L, Hutton B, Tabares-Seisdedos R, Moher D, Alonso-Arroyo A. Global mapping of randomised trials related articles published in high-impact-factor medical journals: a cross-sectional analysis. Trials. 2020 Jan 7;21(1):34. doi: 10.1186/s13063-019-3944-9. PubMed 31910857 ↗
  • Vinkers CH, Lamberink HJ, Tijdink JK, Heus P, Bouter L, Glasziou P, Moher D, Damen JA, Hooft L, Otte WM. The methodological quality of 176,620 randomized controlled trials published between 1966 and 2018 reveals a positive trend but also an urgent need for improvement. PLoS Biol. 2021 Apr 19;19(4):e3001162. doi: 10.1371/journal.pbio.3001162. eCollection 2021 Apr. PubMed 33872298 ↗
  • Setia MS. Methodology Series Module 1: Cohort Studies. Indian J Dermatol. 2016 Jan-Feb;61(1):21-5. doi: 10.4103/0019-5154.174011. PubMed 26955090 ↗
  • Toledano MB, Smith RB, Brook JP, Douglass M, Elliott P. How to Establish and Follow up a Large Prospective Cohort Study in the 21st Century--Lessons from UK COSMOS. PLoS One. 2015 Jul 6;10(7):e0131521. doi: 10.1371/journal.pone.0131521. eCollection 2015. PubMed 26147611 ↗
  • Barrera-Valencia C, Perea-Florez EX. Comparison of Costs in Teledermatology Using PC and Camera Versus Smartphone. Telemed J E Health. 2024 Jun;30(7):e2087-e2095. doi: 10.1089/tmj.2023.0369. Epub 2024 Apr 26. PubMed 38669106 ↗
  • Pavlovic I, Miklavcic D. Web-based electronic data collection system to support electrochemotherapy clinical trial. IEEE Trans Inf Technol Biomed. 2007 Mar;11(2):222-30. doi: 10.1109/titb.2006.879581. PubMed 17390992 ↗
  • Zijp TR, Touw DJ, van Boven JFM. User Acceptability and Technical Robustness Evaluation of a Novel Smart Pill Bottle Prototype Designed to Support Medication Adherence. Patient Prefer Adherence. 2020 Mar 20;14:625-634. doi: 10.2147/PPA.S240443. eCollection 2020. PubMed 32256053 ↗
  • Aldeer M, Javanmard M, Martin RP. A Review of Medication Adherence Monitoring Technologies. Applied System Innovation. 2018; 1(2):14. https://doi.org/10.3390/asi1020014
  • Schwed A, Fallab CL, Burnier M, Waeber B, Kappenberger L, Burnand B, Darioli R. Electronic monitoring of compliance to lipid-lowering therapy in clinical practice. J Clin Pharmacol. 1999 Apr;39(4):402-9. doi: 10.1177/00912709922007976. PubMed 10197299 ↗
  • Ellsworth GB, Burke LA, Wells MT, Mishra S, Caffrey M, Liddle D, Madhava M, O'Neal C, Anderson PL, Bushman L, Ellison L, Stein J, Gulick RM. Randomized Pilot Study of an Advanced Smart-Pill Bottle as an Adherence Intervention in Patients With HIV on Antiretroviral Treatment. J Acquir Immune Defic Syndr. 2021 Jan 1;86(1):73-80. doi: 10.1097/QAI.0000000000002519. PubMed 33306564 ↗
  • Toscos T, Drouin M, Pater JA, Flanagan M, Wagner S, Coupe A, Ahmed R, Mirro MJ. Medication adherence for atrial fibrillation patients: triangulating measures from a smart pill bottle, e-prescribing software, and patient communication through the electronic health record. JAMIA Open. 2020 Apr 28;3(2):233-242. doi: 10.1093/jamiaopen/ooaa007. eCollection 2020 Jul. PubMed 32734164 ↗
  • Cleeland CS, Ryan KM. Pain assessment: global use of the Brief Pain Inventory. Ann Acad Med Singap. 1994 Mar;23(2):129-38. PubMed 8080219 ↗
  • Huo T, Guo Y, Shenkman E, Muller K. Assessing the reliability of the short form 12 (SF-12) health survey in adults with mental health conditions: a report from the wellness incentive and navigation (WIN) study. Health Qual Life Outcomes. 2018 Feb 13;16(1):34. doi: 10.1186/s12955-018-0858-2. PubMed 29439718 ↗
  • Nafziger AN, Barkin RL. Opioid Therapy in Acute and Chronic Pain. J Clin Pharmacol. 2018 Sep;58(9):1111-1122. doi: 10.1002/jcph.1276. Epub 2018 Jul 9. PubMed 29985526 ↗
  • Schug SA, Lavand'homme P, Barke A, Korwisi B, Rief W, Treede RD; IASP Taskforce for the Classification of Chronic Pain. The IASP classification of chronic pain for ICD-11: chronic postsurgical or posttraumatic pain. Pain. 2019 Jan;160(1):45-52. doi: 10.1097/j.pain.0000000000001413. PubMed 30586070 ↗
  • Richebe P, Capdevila X, Rivat C. Persistent Postsurgical Pain: Pathophysiology and Preventative Pharmacologic Considerations. Anesthesiology. 2018 Sep;129(3):590-607. doi: 10.1097/ALN.0000000000002238. PubMed 29738328 ↗
  • Page MG, Kudrina I, Zomahoun HTV, Croteau J, Ziegler D, Ngangue P, Martin E, Fortier M, Boisvert EE, Beaulieu P, Charbonneau C, Cogan J, Daoust R, Martel MO, Neron A, Richebe P, Clarke H. A Systematic Review of the Relative Frequency and Risk Factors for Prolonged Opioid Prescription Following Surgery and Trauma Among Adults. Ann Surg. 2020 May;271(5):845-854. doi: 10.1097/SLA.0000000000003403. No abstract available. PubMed 31188226 ↗
  • https://www.thess-corp.fr/
  • Nasreddine ZS, Phillips NA, Bedirian V, Charbonneau S, Whitehead V, Collin I, Cummings JL, Chertkow H. The Montreal Cognitive Assessment, MoCA: a brief screening tool for mild cognitive impairment. J Am Geriatr Soc. 2005 Apr;53(4):695-9. doi: 10.1111/j.1532-5415.2005.53221.x. Erratum In: J Am Geriatr Soc. 2019 Sep;67(9):1991. doi: 10.1111/jgs.15925. PubMed 15817019 ↗
  • Schirle L, Stone AL, Morris MC, Osmundson SS, Walker PD, Dietrich MS, Bruehl S. Leftover opioids following adult surgical procedures: a systematic review and meta-analysis. Syst Rev. 2020 Jun 11;9(1):139. doi: 10.1186/s13643-020-01393-8. PubMed 32527307 ↗

Individual participant data

Plan to share: No

09

Updates

Tracking since Sep 25, 2026
No changes since tracking began. The registry record was last updated on Jul 26, 2024, before this site started recording changes on Sep 25, 2026. Its history is on ClinicalTrials.gov ↗
10

Registry details

Key details

Study ID
NCT06522698
Lead sponsor
Ciusss de L'Est de l'Île de Montréal
Responsible party
Pascal Laferrière-Langlois (Clinical assistant professor, Ciusss de L'Est de l'Île de Montréal) — Principal investigator
First posted
Jul 26, 2024
Start date
Sep 1, 2024 (estimated)
Primary completion
Jul 1, 2025 (estimated)
Completion
Jul 1, 2025 (estimated)
Last update
Jul 26, 2024

Study contacts

Pascal Laferriere-Langlois, MD, MSc
Contact
pascal.laferriere-langlois@umontreal.ca
+1-819-432-5847
Nadia Godin, NR
Contact
ngodin.hmr@ssss.gouv.qc.ca
514-252-3400 ext. 3193
Pascal Laferriere-Langlois, MD, MSc
principal investigator · Ciusss de L'Est de l'Île de Montréal

Oversight

Data monitoring committee
No
FDA-regulated drug
No
FDA-regulated device
No
View the source record on ClinicalTrials.gov ↗

Not currently enrolling

This study is not yet recruiting, as verified in Jul 2024. You cannot join it, but the record below documents what was studied.

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