Epidemiology of Postoperative Pai
Recruiting
- Conditions
- Postoperative PainPain ManagementAnaesthesiaSurgery
- Registration Number
- NL-OMON20021
- Lead Sponsor
- OLVG HospitalOosterpark 91091 AC AmsterdamThe NetherlandsAttention: prof. dr. M.A.A.J. van den Bosch
- Brief Summary
Not available
- Detailed Description
Not available
Recruitment & Eligibility
- Status
- Recruiting
- Sex
- Not specified
- Target Recruitment
- 120000
Inclusion Criteria
Patients aged 18y or older, elective non day care surgery and surgical emergency procedures with an admission of at least 24hr
Exclusion Criteria
Day care surgery, palliative surgery, , repeated surgery within the same hospital stay or 72 hours after the first surgery. rare surgical procedures performed less than 5 times a year.
Study & Design
- Study Type
- Observational non invasive
- Study Design
- Not specified
- Primary Outcome Measures
Name Time Method 1)Epidemiology of postoperative pain<br /><br>To establish the epidemiology of postoperative pain versus surgical procedures and type of analgesia; pain scores vs. different procedures, location surgery, patient characteristics and combinations of aforementioned. To be able to identify procedures and patients with a high risk of severe postoperative pain and to be able tot identify surgical indicator procedures that can be used as a correction model for differences in surgical case mix between hospitals.<br /><br /><br><br>2)Risk and prediction<br /><br>To Identify patient- and surgical procedure characteristics correlating with severe postoperative pain<br><br /><br /><br>3)Best practice advice<br /><br>Drafting a best practice advise for procedure specific postoperative pain treatment.<br><br>
- Secondary Outcome Measures
Name Time Method 1) Epidemiology of Postoperative Pain <br /><br>To provide a ranking of surgical procedures in relationship to severe postoperative pain and administered analgesics.<br><br /><br /><br>To identify indicator surgical procedures with high risk of postoperative pain<br><br /><br /><br>To determine the quality and quantity of VAS and NRS registration for post operative pain intensity measurement<br><br /><br /><br>2) Risk and Prediction<br /><br>To design a model predicting postoperative and form the basis of a decision support application customizing pain treatment for specific groups of patients and to the individual patient’s needs.<br /><br /><br><br>3) Best practice advice<br /><br>Build an algorithm advising for the best (procedure specific) post operative pain treatment build in the PDMS or an independent application to tailor pain treatment to the patients needs and facilitate early intervention. <br><br><br>