A Cost-efficiency Analysis of Primary Assessors for Patients With Knee Pain in Primary Care

Summary

Participation Requirements

Description

Problem statements: What is the difference in cost efficiency between a healthcare process with a physical therapist as primary assessor and a physician as primary assessor for patients with suspected KOA? Which effect does a clinical pathway with a physical therapist as primary assessor for patient...

Problem statements: What is the difference in cost efficiency between a healthcare process with a physical therapist as primary assessor and a physician as primary assessor for patients with suspected KOA? Which effect does a clinical pathway with a physical therapist as primary assessor for patients with suspected knee osteoarthritis have on quality adjusted life years compared with a physician as primary assessor? What are the differences in costs between the two healthcare processes initiated by either a physiotherapist or a physician set against the differences in effects? Patient recruitment: Some data has already been collected for another clinical trial (ID: NCT03715764), which will be used in this study too. The patient recruitment is finished, while data collection regarding cost variables has not started yet. Patients were recruited from primary care centers and rehabilitation centers in southwestern Sweden. Screening procedure: Nurses and administration personnel at the recruitment units got information about the study and the screening protocol from the data collector and project leader. Each recruiting unit had a contact person that were responsible for the protocols and to contact the data collector when an eligible patient was found. It was regular contact between the project leader and the contact persons at the recruiting units. All screening protocols were sent to the data collector. All participants got orally and written information about the study from the data collector, and patients provided written informed consent. Randomization: A computer-generated list of random numbers was used, where participants were randomly assigned to being assessed, diagnosed and treated either by a physiotherapist or a physician first. The project coordinator managed the sequence generation, allocation concealment, enrolment and assignments of participants and kept the concealed randomization scheme and sequentially numbered, sealed envelopes in a locked cupboard (in the same building where the enrolment will be), only available for the project coordinator. The project coordinator revealed the allocation to the participant shortly after the baseline measurement and to the health care providers. Data collector, data analyst and statistician were blinded of allocation until completion of data collection for the primary outcome measures at the 12 months follow up for the last recruited patient. Group allocation was revealed when analysing data for the other clinical trial (ID: NCT03715764). The project coordinator was not involved in the screening procedure nor the data collection, and was included among the healthcare providers in the study. The blinded data collector and analyst, whom is a physical therapist, were not involved in assessing, diagnosing and treating patients with knee osteoarthritis while the first study (ID: NCT03715764) was conducted. Data collection: Demographic data and measurements of HrQoL has already been collected for another clinical trial (ID: NCT03715764). These data will also be used for the cost-efficiency analysis. Demographic data were collected at baseline. Measurements of HrQoL were measured with EuroQol 5 dimensions 3 levels (EQ5D-3L) and collected at baseline (before randomization), 3- , 6- and 12 months follow ups. New data collection will be made for cost variables. Data regarding costs for the healthcare processes will be extracted from patient journals. The costs for visits to physical therapist, physician or other healthcare provider will be collected from the healthcare organization. The drug prices will be collected from the Swedish Association of Local Authorities and Regions for the time period the drugs were prescribed. Production loss due to sick-leave and health care visits will be valued according to mean gross salary (including taxes and social fees). Calculating total costs (number of contacts per patient * costs ) for: Physiotherapy contacts in primary care Physician contacts in primary care Referral to x-ray Referrals to other healthcare givers Drug prescription Sick-leave days Data management: All data will be coded and managed according to the General Data Protection Regulation. All data will be confidential and only authorized will have access to the patient registry. No individual information can be identified since the results will be presented at group level. Data will be saved for at least 10 years to enable audit. Sample size: A sample size of 50 patients per group will be necessary to detect a minimal clinical improvement of 0.121(SD 0.2) on the EQ5D-3L-index, given an anticipated dropout rate of 14%. The sample size calculation was calculated with a two-sided 5% significance level and a power of 80%. Statistical analysis plan: Data will be analyzed descriptively and presented as numbers and percent, mean and standard deviation or median and 25th to 75th percentiles. Statistical analysis will be made in SPSS Windows and the analysis will be applied with intention-to-treat (ITT). The economic evaluation will be developed together with a health economist. The method will be a cost-effectiveness analysis alongside the clinical trial comparing costs and effects for the two alternatives based on collected data from the trial. The EQ5D-3L measurements will be used for analyzing quality adjusted life years. The result will be presented as an incremental cost-effectiveness ratio (ICER) and a non-parametric bootstrapping will be conducted to demonstrate the uncertainties surrounding the ICER.

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