Chronic PainNCT07195162
Validating and Evaluating the Pain Medicine Digital Workflow Algorithm (PGS 1.0)
An observational study of Chronic Pain, run by PG Medical Systems Ltd. at 1 site in Israel.
Trial summary
This is a prospective, non-randomized, double blind, single center, single arm, validation study, to evaluate the performance of PGS 1.0 algorithm in analyzing pain specific symptoms and medical history data of pain patients referred to a pain expert consultation. Read more about this study
- Who is it for?
- Ages 18 to 80 years
- Conditions the study is for
- Chronic Pain
- How many people
- 200 participants
- Where
- 1 siteIsrael
- Study dates
- 17 Sep 2025to Feb 2027
- Phase
- Observational
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 to 80 years
- All sexes
- No healthy volunteers
- Adult, Older adult
Study population: Male and Female patients aged 18-80, consecutively all patients referred to a pain expert.
Who may be able to join
- Patient is willing and capable of providing Informed Consent.
- Pain persisting for at least 1 month.
Who cannot join
- None
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
Israel1 site, 1 recruiting
- Recruiting
Pain Medicine Institute, Rambam Health Care Campus
Haifa, 31906
May Haddad, PhD, +97247772166, ma_haddad@rambam.health.gov.il
Simon Vulfsons, MD
About this study
Official title: Prospective Validation and Performance Evaluation of the Algorithm of the Pain Medicine Digital Workflow (PGS 1.0)
This is a prospective, non-randomized, double blind, single center, single arm, validation study, to evaluate the performance of PGS 1.0 algorithm in analyzing pain specific symptoms and medical history data of pain patients referred to a pain expert consultation.
Read the detailed description
Background and Rationale:
Chronic pain is a global epidemic. On average, 20% of the Western population suffers from chronic pain, and in some countries, such as the U.S., the number reaches up to 30%. When chronic pain is not properly diagnosed and treated, it leads not only to patient suffering but also to serious comorbidities, increased use of healthcare services, and, in growing numbers, addiction and misuse of prescription drugs.
Pain medicine, a relatively young medical field, offers evidence-based diagnosis and treatment tailored to the patient's pain mechanisms. However, there is a major gap between the large number of patients and the very limited number of pain specialists (around 4,000 in the U.S. and about 80 in Israel). This shortage leads to extremely long waiting times (5-6 months) while patients continue to suffer.
To help close this gap, PG Medical Systems, together with Dr. Simon Wolfson (Head of the Pain Institute at Rambam Health Care Campus), developed an algorithm that analyzes patient symptoms and provides recommendations for pain diagnosis and treatment pathways.
Study Objective:
The study aims to prospectively validate the algorithm's performance by collecting patient data via an online questionnaire at the Rambam Pain Institute. The results will compare the algorithm's diagnoses to those of pain specialists.
Study Procedures:
Patients visiting the Rambam Pain Institute (first-time or follow-up appointments) will be invited to join the study. After signing informed consent, they will complete an online questionnaire with the help of a research assistant. This is a one-time activity, following their medical consultation. The study does not involve additional clinical follow-up. Participation will not affect the patient's diagnosis or treatment.
Duration:
Each participant will spend about 45-60 minutes, including the consent process and questionnaire completion.
Compensation:
Participants will receive 100 NIS for their time.
Data Management and Privacy:
The study will collect only non-identifiable patient data. Each participant will be assigned a code number. Identifying details will remain securely stored at Rambam, linked only by the consent form. This allows for possible follow-up research but ensures that the sponsor company has access only to de-identified data.
Data Security:
All data is stored on Amazon's secure cloud with advanced encryption. Access requires strict authentication, servers are closed to public internet, and only approved private networks can connect. All data is encrypted in transfer and storage. Importantly, the system does not collect identifiable patient information.
- Conditions
- Chronic Pain
- Keywords
- Chronic Pain, Diagnosis, Algorithm
- Medical subject headings
- Chronic Pain, Disease
What is being measured
The primary outcome is the main question the study is designed to answer.
Agreement by percent agreement
Interrater reliability defined as the agreement between the PGS 1.0 algorithm and Pain Expert in rating pain patients' pain diagnosis as measured by percent agreement.
Measured: At the completion of patients' enrollment, agreement will be assessed between PGS 1.0 diagnosis and the expert diagnosis per patient (diagnosis of expert at the intake to the pain clinic and PGS 1.0 diagnosis as per the data the patient filled in).
Secondary outcomes (1)
Agreement by Cohen's Kappa coefficient.
Interrater reliability defined as the agreement between the PGS 1.0 algorithm and Pain Expert in rating pain patients' diagnosis as measured by Cohen's Kappa coefficient.
Measured: At the completion of patients' enrollment, agreement will be assessed between PGS 1.0 diagnosis and the expert diagnosis per patient (diagnosis of expert at the intake to the pain clinic and PGS 1.0 diagnosis as per the data the patient filled in).
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted26 Sep 2025
- Study start17 Sep 2025
- Primary completionDec 2026 (estimated)
- Study completionFeb 2027 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Chronic PainStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Case only
- Time perspective
- Prospective
- Enrolment
- 200 participants (estimated)
Sponsor and investigators
- Lead sponsor
- PG Medical Systems Ltd.
- Sponsor type
- Industry (pharma, biotech, devices)
- Responsible party
- Sponsor
- Investigators
- Simon Vulfsons, MD, Principal investigator, Rambam Health Care Campus
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07195162
- Sponsor's protocol ID
- PG-100-004
- Status last verified
- Sep 2026
- First submitted
- 16 Sep 2025
- Last updated
- 25 Sep 2026
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Study at a glance
From the registry record, last updated by the sponsor on 25 Sep 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Prospective Validation and Performance Evaluation of the Algorithm of the Pain Medicine Digital Workflow (PGS 1.0)
- ClinicalTrials.gov ID
- NCT07195162
- Acronym / sponsor ID
- PG-100-004
- Conditions
- Chronic Pain
- Keywords
- Chronic Pain, Diagnosis, Algorithm
- Study type
- Observational
- Recruitment status
- Recruiting
- Enrolment
- 200 participants (estimated)
- Lead sponsor
- PG Medical Systems Ltd.Industry (pharma, biotech, devices)
- Study start
- 17 Sep 2025 (actual)
- Primary completion
- Dec 2026 (estimated)
- Study completion
- Feb 2027 (estimated)
- First posted
- 26 Sep 2025 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
This is a prospective, non-randomized, double blind, single center, single arm, validation study, to evaluate the performance of PGS 1.0 algorithm in analyzing pain specific symptoms and medical history data of pain patients referred to a pain expert consultation.
Detailed description
Background and Rationale:
Chronic pain is a global epidemic. On average, 20% of the Western population suffers from chronic pain, and in some countries, such as the U.S., the number reaches up to 30%. When chronic pain is not properly diagnosed and treated, it leads not only to patient suffering but also to serious comorbidities, increased use of healthcare services, and, in growing numbers, addiction and misuse of prescription drugs.
Pain medicine, a relatively young medical field, offers evidence-based diagnosis and treatment tailored to the patient's pain mechanisms. However, there is a major gap between the large number of patients and the very limited number of pain specialists (around 4,000 in the U.S. and about 80 in Israel). This shortage leads to extremely long waiting times (5-6 months) while patients continue to suffer.
To help close this gap, PG Medical Systems, together with Dr. Simon Wolfson (Head of the Pain Institute at Rambam Health Care Campus), developed an algorithm that analyzes patient symptoms and provides recommendations for pain diagnosis and treatment pathways.
Study Objective:
The study aims to prospectively validate the algorithm's performance by collecting patient data via an online questionnaire at the Rambam Pain Institute. The results will compare the algorithm's diagnoses to those of pain specialists.
Study Procedures:
Patients visiting the Rambam Pain Institute (first-time or follow-up appointments) will be invited to join the study. After signing informed consent, they will complete an online questionnaire with the help of a research assistant. This is a one-time activity, following their medical consultation. The study does not involve additional clinical follow-up. Participation will not affect the patient's diagnosis or treatment.
Duration:
Each participant will spend about 45-60 minutes, including the consent process and questionnaire completion.
Compensation:
Participants will receive 100 NIS for their time.
Data Management and Privacy:
The study will collect only non-identifiable patient data. Each participant will be assigned a code number. Identifying details will remain securely stored at Rambam, linked only by the consent form. This allows for possible follow-up research but ensures that the sponsor company has access only to de-identified data.
Data Security:
All data is stored on Amazon's secure cloud with advanced encryption. Access requires strict authentication, servers are closed to public internet, and only approved private networks can connect. All data is encrypted in transfer and storage. Importantly, the system does not collect identifiable patient information.
Study design
- Observational model
- Case only
- Time perspective
- Prospective
Who may qualify
- Ages
- 18 to 80 years
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- Male and Female patients aged 18-80, consecutively all patients referred to a pain expert.
Key inclusion criteria (2 listed)
- Patient is willing and capable of providing Informed Consent.
- Pain persisting for at least 1 month.
Key exclusion criteria (1 listed)
- None
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Primary outcome
Agreement by percent agreement
Time frame: At the completion of patients' enrollment, agreement will be assessed between PGS 1.0 diagnosis and the expert diagnosis per patient (diagnosis of expert at the intake to the pain clinic and PGS 1.0 diagnosis as per the data the patient filled in).
Interrater reliability defined as the agreement between the PGS 1.0 algorithm and Pain Expert in rating pain patients' pain diagnosis as measured by percent agreement.
1 secondary outcome
Agreement by Cohen's Kappa coefficient.
Time frame: At the completion of patients' enrollment, agreement will be assessed between PGS 1.0 diagnosis and the expert diagnosis per patient (diagnosis of expert at the intake to the pain clinic and PGS 1.0 diagnosis as per the data the patient filled in).
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 25 Sep 2026.
- Individual participant dataSharing planned: No
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
Simon Vulfsons, MD principal investigator
Rambam Health Care Campus
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Chronic Pain, run by PG Medical Systems Ltd. at 1 site in Israel.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 2 inclusion and 1 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: looking for participants now, as of the sponsor's last update on 25 Sep 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in Israel. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact Shany Blum, MD PhD (+972545331773, shany@pgmeds.com), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Agreement by percent agreement (time frame: At the completion of patients' enrollment, agreement will be assessed between PGS 1.0 diagnosis and the expert diagnosis per patient (diagnosis of expert at the intake to the pain clinic and PGS 1.0 diagnosis as per the data the patient filled in).). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 25 Sep 2026; AzTrials last refreshed its copy on 1 Nov 2026.