The intervention protocol was reported in full elsewhere (see (15)). This was a parallel pragmatic randomized controlled trial using electronic patient registers.
Setting
The study was conducted in Pihlajalinna Työterveys, a large private OHS provider, which at the time of starting the study had 28 private healthcare units across Finland. In 2015, Pihlajalinna Työterveys had approximately 68370 employees on their register. Pihlajalinna Työterveys went through several rounds of mergers and corporate acquisitions during the study period, which led to a substantial increase in patient and healthcare unit numbers.
The intervention
The intervention was multifaceted and implemented sequentially. First, a notice was sent to the entire organization informing all practitioners working in all of Pihlajalinna’s units that the study would be conducted. The intervention consisted of two separate activities: one, training, mentoring and follow-up of trainees in intervention units on how to identify and record work related illnesses in primary care visits and how to identify and record risk of work disability. Training sessions were conducted at each intervention unit, presenting the intervention and reinforcing information about work related conditions for all OH physicians and nurses at participating units. This also included training on the actions that were to be implemented after a patient was identified on the system as at risk of work disability or had a work related condition. Following the training, a project physician followed up with participants telephonically and answered any emerging questions. Second, an organization-wide change was made to the electronic health care system, clarifying the way in which work relatedness and risk of disability pension was recorded, which matched the training. The electronic change was made to clarify text in sections where work disability risk was assessed. No specific training was conducted on the change to the electronic record system, as changes were minor and had been introduced in the intervention training.
The trainees in the intervention sites were OH physicians, who were named as responsible for collaboration with a particular client company, working at any of the 22 sites included in the study. The intervention sites had 58 physicians employed as company responsible physicians during the study period, while control sites had 50 physicians during the study period. Named OH physicians are responsible for individual patient consultations, and also providing services to client companies.
If the OH physician noted a visit as work related, or a patient as at risk of work disability in the near future, a sequence of events was kicked off at the intervention sites. The OHS nurses named as responsible for the client companies collected patients from that company, identified as at risk from the electronic health record, onto an excel sheet. They then initiated recommended activities or referrals individually or together with OH physicians, either for the individual patients or for the client company. The interventions could include e.g. an occupational health collaborative negotiation to modify the employee’s tasks, or organizational interventions on workplace ergonomics or teamwork counselling. Other alternatives were e.g. medical or vocational rehabilitation for the individual patient, which involves both the workplace and the patient/employee. It was not possible to collect information on the initiated activities as we could not link individual patient identification numbers with workplace or other activities within the electronic health information system.
A full description of the intervention can be found in the TIDIER reporting guide for population health interventions: tidierguide.org/#/gen/pFqrFqw3M
Information about the study was sent to all sites in April 2016. The intervention training was conducted in May 2016. The electronic change to systems was implemented in 9.3.2017. Data collection ended in December 2017.
Randomisation
Of all clinics within Pihlajalinna Työterveys in 2016, we included 22. We treated each healthcare unit as a cluster, as individual randomisation in this context would have been challenging. NT, the team statistician conducted initial simple randomization to randomize the first four clusters of healthcare units. After this, the minimisation approach was used to randomise the remaining 18 clusters so that confounders including 1) the occupational sector (e.g. industrial, service sector, public service), 2) presence of a large industry client, and 3) client volume per site balanced across the intervention and control sites (see (15)).
Nor the occupational health professionals or the research team were blinded to the intervention.
Outcomes
Our primary outcome is reduction from baseline of the mean number of medium term (4-14 calendar days) sickness absences per intervention and control centre after 1 year of follow up as measured by OHS patient records (15). Deviating from the original protocol, we considered medium length sickness absences from 4 to 14 calendar days, instead of 9 working days as indicated in the original protocol. This was related to the Finnish Insurance Agency definitions, which limited sickness absence payments to after 9 working days (including Saturdays but not Sundays). It was not possible to separate Sundays from the electronic patient records, thus we expanded our definition from 9 days to 14 calendar days. A similar approach was used in (16).
Our secondary outcomes were
- Reduction in mean number of short term (1–3 consecutive calendar days) sickness absences from the workplace per cluster from baseline after 1 year from the start of the intervention as measured by self-reported sickness absences that were recorded on OHS records or OHS records of sickness absence written in the OHS units.
- Reduction of mean number of any form of work disability pensions as measured by an employee registering as receiving a work disability pension on the central pensions register from baseline to up to 2 years from the intervention as measured by the entry on the central pensions register
- Reduction of mean number of long-term (15 or more consecutive calendar days) sickness absences from the workplace per cluster from baseline to 1 year after the intervention as measured by OHS records
The follow-up time set at 1 year due to funding and planned study duration. This article focuses on reporting the primary outcome, medium term sickness absences, as we deemed the follow-up period too short to report on disability pensions or long-term sickness absences. We also report short-term sickness absences and the process indicators collected on recording consultations’ work relatedness and risk of work disability across control and intervention sites.
Power calculation
Our initial power calculation suggested that we would have 91% power to detect a 10% change in mean sickness absence rates across intervention and control clusters, if we had 22 occupational health units with 24892 patients. For the trial, we retained all 22 units, with 26804 patients recorded on the system during the study.
Data collection
We collected medical record data on patients’ healthcare related visits from Pihlajalinna Työterveys from 2015 to 2017. The medical information system included between 68370 patients in 2015 and 107413 patients in 2017. The cohort was dynamic, in that patients could be added to the cohort as the study progressed. Data were pseudonymised, and researchers had no access to patient identifying data. All patients above the age of 18 whose employment included a primary healthcare benefit with Pihlajalinna Työterveys were included in the study.
Data analysis
After data collection was complete, we noted that Pihlajalinna’s acquisition of another large occupational health services provider impacted on our outcomes. Therefore, we used all initially randomised sites in the intention to treat analyses and excluded acquired units in the per protocol analyses.
We included data on primary healthcare related patient visits to OHS physicians responsible for client organisations. This is because OHS services have many temporary staff, who deal with primary care patients but are not occupational health specialists. Most temporary staff were not exposed to the intervention training. We also excluded preventive visits such as health examinations. We analysed data 6 months before the intervention, during the intervention, and after the intervention for 6 months. After initial analysis we chose a period of 6 months after the intervention corresponding with the season of the 6 month baseline, to ensure that seasonal effects did not confound our analysis. We analysed data using ANCOVA, setting alpha at 0.05.
We also analysed process indicators among intervention and control clinics. These indicators included whether the recording of a visit’s relatedness to work remained the same as before or whether the physicians recording had changed practice. At each visit a physician would be asked to record whether or not the patient’s visit was related to work or not or whether it was not assessed. We analysed changes both after the educational intervention and after change in the electronic system using descriptive statistics.