진통제 디지털 워크 플로 알고리즘 검증 및 평가 (PGS 1.0)
Pain Medicine Digital Workflow의 알고리즘의 전향 적 검증 및 성능 평가 (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.
연구 개요
상태
상태
정황
정황
상세 설명
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.
연구 유형
연구 유형
등록 (추정된)
등록
연락처 및 위치
연구 연락처
연구 연락처
- 이름: Shany Blum, MD PhD
- 전화번호: +972545331773
- 이메일: shany@pgmeds.com
연구 장소
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Haifa, 이스라엘, 31906
- 모병
- Pain Medicine Institute, Rambam Health Care Campus
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수석 연구원:
- Simon Vulfsons, MD
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연락하다:
- May Haddad, PhD
- 전화번호: +97247772166
- 이메일: ma_haddad@rambam.health.gov.il
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부수사관:
- Amir Minerbi, MD PhD
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참여기준
자격 기준
자격 기준
공부할 수 있는 나이
건강한 자원 봉사자를 받아들입니다
연구 대상 성별
샘플링 방법
연구 인구
Male and Female patients aged 18-80, consecutively all patients referred to a pain expert.
설명
Inclusion Criteria:
- Patient is willing and capable of providing Informed Consent.
- Pain persisting for at least 1 month.
Exclusion Criteria:
None
공부 계획
연구는 어떻게 설계됩니까?
디자인 세부사항
- 관찰 모델: CASE_ONLY
- 시간 관점: PROSPECTIVE
연구는 무엇을 측정합니까?
주요 결과 측정
주요 결과 측정
결과 측정 |
측정값 설명 |
기간 |
|---|---|---|
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Agreement by percent agreement
기간: 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).
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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. |
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).
|
2차 결과 측정
2차 결과 측정
결과 측정 |
측정값 설명 |
기간 |
|---|---|---|
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Agreement by Cohen's Kappa coefficient.
기간: 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' diagnosis as measured by Cohen's Kappa coefficient. |
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).
|
공동 작업자 및 조사자
수사관
수사관
- 수석 연구원: Simon Vulfsons, MD, Rambam Health Care Campus
연구 기록 날짜
연구 주요 날짜
연구 시작 (실제)
연구 시작
기본 완료 (추정된)
기본 완료
연구 완료 (추정된)
연구 완료
연구 등록 날짜
최초 제출
최초 제출
QC 기준을 충족하는 최초 제출
QC 기준을 충족하는 최초 제출
처음 게시됨 (실제)
처음 게시됨
연구 기록 업데이트
마지막 업데이트 게시됨 (실제)
마지막 업데이트 게시됨
QC 기준을 충족하는 마지막 업데이트 제출
QC 기준을 충족하는 마지막 업데이트 제출
마지막으로 확인됨
마지막으로 확인됨
추가 정보
이 연구와 관련된 용어
기타 연구 ID 번호
기타 연구 ID 번호
- PG-100-004
개별 참가자 데이터(IPD) 계획
개별 참가자 데이터(IPD)를 공유할 계획입니까?
약물 및 장치 정보, 연구 문서
미국 FDA 규제 의약품 연구
미국 FDA 규제 기기 제품 연구
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