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Does changed referral options affect the use of MRI for patients with low back pain? Evidence from a natural experiment using nationwide data

Objectives This study reports lumbar MRI referral patterns in the Region of Southern Denmark (RSD) and investigates the hypothesis that we will see an increase in imaging rates (MRI rates) following new referral options to lumbar MRI in the RSD in comparison with the other regions in Denmark from 2010 to 2013. Design A difference-in-difference (DD) analysis, using general practitioners (GPs) in other regions as control, was used to test if the new referral options had an effect on the MRI rates. Setting In 2010, RSD introduced organisational changes affecting the referral options for lumbar MRI. First, the possibility for direct referral to lumbar MRI was introduced GPs, and second, the region gathered all local spine departments into one specialist hospital called the Spine Centre. Participants We retrieved all lumbar MRIs performed on patients aged 18+ performed on Danish hospitals from 2008 to 2013 using the registries from Statistics Denmark. We use sociodemographic information from all Danish citizens aged 18+ aggregated to GP level. Primary and secondary outcome measures: lumbar MRI scans per 1000 capita enlisted with a GP (MRI rates) were calculated based on GPs patient list. Four referral types were made to describe changes in referral patterns. Results In total 183 389 patients received 240 760 lumbar MRIs in the period. The use of the direct referral option by GPs in the RSD increased by 115% in the period from 2010 to 2013 and accounted for 34% of all referrals (n=6545) in 2013. MRI rates were significantly higher in RSD following the organisational changes (DD 1.389(0.925–1.852) lumbar MRI per 1.000 enlisted with a GP). Conclusions Introduction of organisational changes in RSD as direct referral to lumbar MRI from GPs and chiropractors as well as establishing a Spine Centre increase the lumbar MRI rate in comparison with other regions in Denmark.

The factors associated with the increased use of MRI in the diagnostics of low back pain have been investigated. Research shows that the substantial geographic differences in use of spinal MRI across states in the US [5][6][7][8] can be explained by differences in local clinical practices 6 , physician ownership of specialty hospitals 9 , fee-for-service schemes 10 , MRI-scanner availability 11 and state median income per capita 12 . However, these studies were undertaken in a US-setting among populations that had limited access to health care providers and where a fee-for service incentive affected doctors' wages. Consequently, more studies are needed on factors impacting the use of lumbar MRI, in other health care settings [13][14][15] .
In this study we have the opportunity of using nation-wide data and hence evaluating a natural experiment. In 2010, Region of Southern Denmark (RSD), made two organisational changes.
These included, centralisation of regional spine specialist departments across regional hospitals in one spine specialist hospital. Further, General Practitioners (GPs) and chiropractors were given the possibility to directly refer LBP patients for lumbar MRI without prior referral to the Spine Centre or to office-based specialist doctors. In the support of the organisational changes, RSD  The study investigates the effect of the organisational changes on use of lumbar MRI in the diagnostics of LBP patients in RSD. Specifically, we describe yearly lumbar MRI rates (lumbar MRI per 1,000 enlisted with a GP) for all individuals aged 18+. We hypothesised that the yearly lumbar MRI rates from 2010 to 2013 would increase significantly in RSD compared to the other regions.

Design
A longitudinal register-based study covering the Danish population aged 18+ from 2008 to 2013.

Setting
In Denmark, five decentralised administrative regions, including 98 municipalities, manage the tax founded health care system 16 . Each region has a public elected council and is autonomously managing the secondary care sector. All services provided at hospitals and office-based physician are free of charge, while services at physiotherapist and chiropractors involve co-payments from the patient. GPs' in Denmark have a unique patient list (GP list) of citizens, to whom the GP solely  The study used data from the registries at Statistics Denmark (DST), a governmental institution providing data for research purposes 17 . All registries are linkable at the individual level, using the personal civil registration number (CPR-number), which are given to Danish citizens at birth 18 19 .
The study includes data from the following registries: The Danish National Patient Registry (NPR) 20 21 , includes information on diagnosis coded according to the International Classification of Disease (ICD-10), and procedure and surgery codes (Health Care Classification System (SKS codes)). All NPR records are unique, due to a NPR serial numbers (unique to each patient's continuum of care at a hospital) and patients' CPR-numbers.
The Danish National Health Service Register for Primary Care (DNHR) 22 , includes all contacts to the primary sector health care providers including GPs, Chiropractors, Physiotherapists, and officebased specialist doctors. The GP list and GP list size were generated by combining the unique GP id with the CPR-number from patients receiving most of their services from the GP id 23 . GPs' with patient list size less than 300 patients were deleted as they are hypothesised to be GPs either starting up or closing down the practice. Those citizens with no information of GP id in one of the study years, were allocated to a hypothetical GP id generated for each region.
Danish National Prescription Registry (DNPR) includes information on all prescription based analgesic drugs sold at Danish primacies 24 . We identified analgesic drugs according to the Anatomical Therapeutic Chemical classification (ATC) code 25 . Analgesic drugs included ATC code Statistics Denmark (DST) as an umbrella includes information from other registers and we retrieved information on income 26 , education 27 , job-and socio-economic status 28 , civil status 18 , and demographics 18 .

Definition of lumbar MRI
This study included data for lumbar MRI (SKS code: UXME30) 21 . Each MRI scan performed at a public hospital is recorded in NPR. Lumbar MRI performed on a private hospital are recorded in the NPR if they are subsidised by the government. Patients with multiple spine MRI registrations on the same NPR serial number were identified and the UXME30 code was retained for analysis. If patients showed two or more UXME30 codes for the same day only one were kept.

Definition of referral mode
A referral mode variable was defined based on two variables from the NPR; Referral directly from the GP (1), directly from the Chiropractor or initiated by private insurance (2), directly from the office-based specialist doctors (3), and from the hospital department (4). In the dataset we observe registrations with referral directly from the GP, before 2010. These are recoded into hospital registrations.

Primary outcome
The primary outcome is lumbar MRI rate per 1,000 enlisted with a GP We hypothesise that the two referral options (direct GP referral and referral to the Spine Centre) drives any change in use of lumbar MRI. As patients have not chosen to live in RSD based on the access to MRI, the assumption behind our analyses strategy is that we can interpret patients as randomly assigned to a GP who by construct of the natural experiment happen to have access to the organizational changes (RSD) or not (control regions). We therefor included GPs from the Zealand Region (ZR) and the North Denmark Region (NR) as controls for all years in the analysis.
GPs from the CR are included from 2008 to 2010, as they had the possibility to directly refer LBP patients for a lumbar MRI in 2011. GPs from the CR were excluded as controls.
The DD model estimates the effect of organisational changes by assuming that the counterfactual development in the lumbar MRI rates in the treatment group (i.e, RSD) could be approximated by the development in the lumbar MRI rates of the other regions 29 . For the control group to match the approximation of the counterfactual development in lumbar MRI rates in RSD the model, we rely on an assumption that there was a common trend in lumbar MRI rates before the interventions. The common trend assumption was visually inspected for unadjusted analyses (see  in RSD and the controls but if we expect time varying differences occurring over time we need to add covariates. Hence, second assumption behind our approach is that there were no time-varying unobservable covariates, that could explain differences in selection into a referral to lumbar MRI between GPs, and between regions. 29 . Hence, we generally assume that citizens need for MRI are identical among regions after controlling for observable patients' characteristics and supply factors related to LBP treatment did not change over time on the regional level,

Statistics
The study used difference-in-difference (DD) in a parametric Ordinary Least Squares (OLS) regression model using robust standard errors and clustering for GP id. We aggregated the individual level socio demographic data to GP level. This allowed for analysis using information from the socio demographic composition of the GPs' lists to account for any time varying patient characteristics, that is associated with LBP, and therefor explain differences in GPs' referral to lumbar MRI. A supplementary advantage of using the GP as analytical level is that we in this way obtain an unbalanced panel data structure of our dataset, with one observation per unique GP per year.
To show dynamic year effects of the models, 2009 was used as pre-intervention and each  The adjusted models add time varying covariates to the above variables. This is done to avoid that any observed change in RSD after the change is simply due to changes in the characteristics of the citizens over time -for example that citizens in RSD over time becomes more prevalent to LBP than control regions All covariates included, except GP list size, were made as proportions of enlisted patients with characteristic X divided with the GP list size. Patients characteristics X included; age 18-59, citizens in a full-time job, income DKK 0-399.000 or missing, women, citizens living as singles, and Charlson comorbidity index score 30   The common trend was visually inspected using figure 2, showing unadjusted average regional lumbar MRI rates for GPs in RDS and the control regions. Figure 2 implies common support for the unadjusted models. To capture any differences in time-varying trends we included characteristics of the GP patient list, seen in Table 1. The table show that there are statistical differences for 8 of the 12 included covariates between GPs' in RSD and control group regions in the pre-intervention years. However, the differences are small between the patient characteristics of the GPs' lists in RSD and GPs' lists in control group regions.  The results of the two DD analyses of the lumbar MRI rates per 1,000 enlisted with GPs RSD compared to GPs' in the control group, are shown in Table 2. After the organisational changes in RSD, the lumbar MRI rates increased significantly compared to control groups, for both models ranging from 1  The dynamic year effects, for both models are seen in figure 3. Figure 3 indicates that the common trend assumption support is fulfilled as a hypothesised treatment effect before the treatment occurred is insignificant. Dynamic year effects for post-intervention years were positive and significant for all years, with an observed increase positive trend of the estimates, indicating that the effect of the organisational changes increases over time.

Discussion
This study showed that establishing a Spine Centre in the RSD and introducing direct referrals for lumbar MRI by GPs was associated with an increase in the use of lumbar MRI (compared to that of other regions) in the years following the 2010 changes. On average the increase was between 1.389 to 1.832 lumbar MRI per 1.000 enlisted with GPs in RSD involving an increase in lumbar MRI of between 1.400 and 1.800 additional scans compared to the other regions. The use of the direct referral option by GPs in the RSD increased by 115% in the period from 2010 to 2013.
As in other studies from the US 7 , we find geographical variation in the use of lumbar MRI among the regions in Denmark. The reason for the difference in use of lumbar MRI among the regions is still unclear. Some points towards a special interest in back pain by specialist doctors in RSD, which relates to different regional clinical practices, which have been found in US studies 6 11 . The relationship between MRI usages and physician incentives 9 10 , is unlikely to explain the differences in a Danish setting; Firstly, physicians at public hospital receive a fixed yearly salary, thereby not having incentives to refer patients. Secondly, the public hospitals undertook 74 % of all scans. However, previous studies have shown that lumbar MRI referrals from GPs are inappropriate in up to 50% of the cases when judged against the guidelines 10 33-35 . Further, the inappropriate use of lumbar MRI has been shown to be associated with an increased use of opioids, higher health care costs and has a low impact on pain relief or functional recovery after 6 months in non-specific LBP patients, without serious pathologies such as cancer, nerve root compression, cauda equina, radiculopathy and sciatica 3 5 36-42 . Further studies are needed to investigate if the same associations are found in this setting.

Strengths and Limitations
This study used DD estimates to capture the effect of the organisational changes and LBP DMP in RSD. Difference in difference is a popular design for evaluation of policy changes, as is widely used in social science 29 . DD relies on the assumption of a common trend in the pre-treatment period for the outcomes of interest. This assumption seems to be fulfilled in the current study. The study relied on data from the newly 2018 update of the NPR at Statistics Denmark 43 . This allowed for data from all individuals aged 18+ of the population of Denmark, leaving an unseen precision of analyses performed on country level.

Conclusions
Following RSD' introduction of organisational changes in 2010, the lumbar MRI rate increased significantly in comparison with the other regions in Denmark. The issue of whether the increased usage of lumbar MRI is beneficial for the RSD's LBP patients (compared to that of other regions) requires further investigations.     Dynamic year effects using the adjusted model, with multiple difference in difference  estimates with 2009 as the pre-intervention period and all post intervention years for Region of  Southern Denmark and the control

Availability of data and material
The data that support the findings of this study are available from national databases at Statistics Denmark (Sejrøgade 11, DK-2100 København Ø, Phone +45 39 17 31 30, E-Mail forskningsservice@dst.dk), a governmental institution, but restrictions apply to the availability of these data, which were used under license for the current study, and so are not publicly available.
Data are however available from the authors upon reasonable request and with permission of Statistics Denmark and The Danish Data Protection Agency (Borgergade 28, DK-1300 Copenhagen, Phone +45 3319 3200, E-Mail dt@datatilsynet.dk).

Competing interests
The authors declare that they have no competing interests

Strengths and limitations of this study:
-Nation-wide registry data including socio-demographic information on all citizens aged 18+ -Use of a Difference-in-Difference design for possible causal inference -The study might underestimate the lumbar MRIs from private hospitals  [13][14][15] .
In this study we have the opportunity of using nation-wide data and hence evaluating a natural experiment. In 2010, Region of Southern Denmark (RSD), made two organisational changes.
These included, centralisation of regional spine specialist departments across regional hospitals in one spine specialist hospital. Further, General Practitioners (GPs) and chiropractors were given the possibility to directly refer LBP patients for lumbar MRI without prior referral to the Spine Centre or to office-based specialist doctors. In the support of the organisational changes, RSD implemented a LBP Disease Management Programme (DMP). The centralisation of the hospital

Primary outcome
The primary outcome is yearly lumbar MRI per 1,000 enlisted with a GP.

Setting
In Denmark, five decentralised administrative regions, including 98 municipalities, manage the tax founded health care system 16

Data sources
The study used data from the registries at Statistics Denmark (DST), a governmental institution providing data for research purposes 17 . All registries are linkable at the individual level, using the personal civil registration number (CPR-number), which are given to Danish citizens at birth 18 19 .
The study includes data from the following registries: The Danish National Patient Registry (NPR) 20 21 , includes information on diagnosis coded according to the International Classification of Disease (ICD-10), and procedure and surgery codes (Health Care Classification System (SKS codes)). All NPR records are unique, due to a NPR serial numbers (unique to each patient's continuum of care at a hospital) and patients' CPR-numbers.  22 , includes all contacts to the primary sector health care providers including GPs, Chiropractors, Physiotherapists, and officebased specialist doctors. The GP list and GP list size were generated by combining the unique GP id with the CPR-number from patients receiving most of their services from the GP id 23 . GPs' with patient list size less than 300 patients were deleted as they are hypothesised to be GPs either starting up or closing down the practice. Those citizens with no information of GP id in one of the study years, were allocated to a hypothetical GP id generated for each region.
Danish National Prescription Registry (DNPR) includes information on all prescription based analgesic drugs sold at Danish primacies 24 . We identified analgesic drugs according to the Anatomical Therapeutic Chemical classification (ATC) code 25 . Analgesic drugs included ATC code NN02A and NN02B; tablet cans with >100 pills of paracetamol and ibuprofen, synthetic opioids, and opioids.
Statistics Denmark (DST) as an umbrella includes information from other registers and we retrieved information on income 26 , education 27 , job-and socio-economic status 28 , civil status 18 , and demographics 18 .

Definition of lumbar MRI
This study included data for lumbar MRI (SKS code: UXME30) 21

Definition of referral mode
A referral mode variable was defined based on two variables from the NPR; Referral directly from the GP (1), directly from the Chiropractor or initiated by private insurance (2), directly from the office-based specialist doctors (3), and from the hospital department (4). In the dataset we observe registrations with referral directly from the GP, before 2010. These are recoded into hospital registrations.

Analyses strategy
The impact on MRI-rates of the well-defined organisational changes in 2010 in RSD, is analysed as a natural experiment. The change in the other regions are used as control under the assumption that the development of MRI rates in the control regions are a good indicator of how the MRI rates would have developed in RSD in absence of the organizational changes.
We hypothesise that the two referral options (direct GP referral and referral to the Spine Centre) drives any change in use of lumbar MRI. As patients have not chosen to live in RSD based on the access to MRI, the assumption behind our analyses strategy is that we can interpret patients as randomly assigned to a GP who by construct of the natural experiment happen to have access to the organizational changes (RSD) or not (control regions). We therefore included GPs from the Zealand Region (ZR) and the North Denmark Region (NR) as controls for all years in the analysis. The DD model estimates the effect of organisational changes by assuming that the counterfactual development in the lumbar MRI rates in the treatment group (i.e, RSD) could be approximated by the development in the lumbar MRI rates of the other regions 29 . For the control group to match the approximation of the counterfactual development in lumbar MRI rates in RSD the model, we rely on an assumption that there was a common trend in lumbar MRI rates before the interventions. The common trend assumption was visually inspected for unadjusted analyses. The DD approach by definition control for all time constant heterogeneity between GPs in RSD and the controls but if we expect time varying differences occurring over time we need to add covariates.
Hence, second assumption behind our approach is that there were no time-varying unobservable covariates, that could explain differences in selection into a referral to lumbar MRI between GPs, and between regions. 29 . Hence, we generally assume that citizens need for MRI are identical among regions after controlling for observable patients' characteristics and supply factors related to LBP treatment did not change over time on the regional level,

Statistics
The study used difference-in-difference (DD) in a parametric Ordinary Least Squares (OLS) regression model using robust standard errors and clustering for GP id. We aggregated the individual level socio demographic data to GP level. This allowed for analysis using information from the socio demographic composition of the GPs' lists to account for any time varying patient characteristics, that is associated with LBP, and therefore explain differences in GPs' referral to lumbar MRI. A supplementary advantage of using the GP as analytical level is that we in this way obtain an unbalanced panel data structure of our dataset, with one observation per unique GP per year.
The changes in referral modes were graphed for RSD (see Figure 1)  The adjusted models add time varying covariates to the above variables. This is done to avoid that any observed change in RSD after the change is simply due to changes in the characteristics of the citizens over time -for example that citizens in RSD over time becomes more prevalent to LBP than control regions. All covariates included, except GP list size, were made as proportions of enlisted patients with characteristic X divided with the GP list size. Patients characteristics X included; age 18-59, citizens in a full-time job, income DKK 0-399.000 or missing, women, citizens living as singles, and Charlson comorbidity index score 30 2+, patients with vocational education, patients using a prescription on an analgesic drug at a pharmacists, patients having a visit at a physiotherapist, patients having a visit a chiropractor, and patients visiting an office-based specialist doctors (rheumatologist, neurologist, orthopaedics, and radiologist). Covariates are seen in table 1.

Patient and Public Involvement
Patients were not involved in the making of the study

Ethics
The Danish Data Protection Agency approved this study (Journal number 15/14594

(insert figure 2)
The common trend was visually inspected using figure 2, showing unadjusted average regional included covariates between GPs' in RSD and control group regions in the pre-intervention years.
However, the differences are small between the patient characteristics of the GPs' lists in RSD and GPs' lists in control group regions. The results of the two DD analyses of the lumbar MRI rates per 1,000 enlisted with GPs RSD compared to GPs' in the control group, are shown in Table 2. After the organisational changes in RSD, the lumbar MRI rates increased significantly compared to control groups, for both models  The dynamic year effects, for both models are seen in figure 3. Figure 3 indicates that the common trend assumption support is fulfilled as a hypothesised treatment effect before the intervention occurred is insignificant. Dynamic year effects for post-intervention years were positive and significant for all years, with an observed increase positive trend of the estimates, indicating that the effect of the organisational changes increases over time.  1  2  3  4  5  6  7  8  9  10  11  12  13  14  15  16  17  18  19  20  21  22  23  24  25  26  27  28  29  30  31  32  33  34  35  36  37  38  39  40  41  42  43  44  45  46  47  48  49  50  51  52  53  54  55  56  57  58  59  As in other studies from the US 7 , we find geographical variation in the use of lumbar MRI among the regions in Denmark. The reason for the difference in use of lumbar MRI among the regions is still unclear. Some points towards a special interest in back pain by specialist doctors in RSD, which relates to different regional clinical practices, which have been found in US studies 6 11 . The relationship between MRI usages and physician incentives 9 10 , is unlikely to explain the differences in a Danish setting; Firstly, physicians at public hospital receive a fixed yearly salary, thereby not having incentives to refer patients. Secondly, the public hospitals undertook 74 % of all scans.
The increase in referrals for lumbar MRI following the change in GP referral access to lumbar MRI in the RSD in 2010 is noteworthy. GPs in the RSD clearly began to use the new referral option immediately and the use of the referral option increase by 115% from 2010 to 2013. This change might indicate a lowering in the threshold for a MRI referral. There could be numerous reasons for the use of direct referrals to lumbar MRI, including patient demands 31 32 and physicians' wish to provide quick reassurances to LBP patients 32 . Providing quick reassurance to patients could  10 33-35 . Further, the inappropriate use of lumbar MRI has been shown to be associated with an increased use of opioids, higher health care costs and has a low impact on pain relief or functional recovery after 6 months in non-specific LBP patients, without serious pathologies such as cancer, nerve root compression, cauda equina, radiculopathy and sciatica 3 5 36-42 . Further studies are needed to investigate if the same associations are found in this setting.

Strengths and Limitations
This study used DD estimates to capture the effect of the organisational changes and LBP DMP in RSD. Difference in difference is a popular design for evaluation of policy changes, as is widely used in social science 29 . DD relies on the assumption of a common trend in the pre-treatment period for the outcomes of interest. This assumption seems to be fulfilled in the current study, even though we have a short pre-treatment period.
Referrals from GPs is seen from 2008 to 2009 and are recoded to hospital referrals, as they did not have the opportunity to refer LBP patients for a lumbar MRI. There might be several explanations for these registrations; Firstly, registrations with referrals from GP in 2009 may be test of the electronic referral system, used in the communication of between GPs and hospitals. Secondly, referrals from GPs can be interpreted in relation to GPs referring LBP patients for a consult in secondary care, where the GP refer the patient for a lumbar MRI on the same day as the consult. This allows the hospital-based specialist doctor to assess the lumbar MRI at the consult on the hospital, and to reduce visits at the hospital for the patient.
The study relied on data from the newly 2018 update of the NPR at Statistics Denmark 43 . This allowed for the newest data from all individuals aged 18+ of the population of Denmark. The granularity of the data allows for an unseen precision of analyses performed on country level.

Ethics approval and consent to participate
The study is based on registry data, which does not require ethics approval in Denmark (Act on Research Ethics Review of Health Research Projects § 14, sec. 2 http://www.nvk.dk/english/acton-research 10.02.2017). The study group did however send the study protocol for an ethic assessment to the regional ethics committee in Region of Southern Denmark. The committee found that the study did not need ethic approval. The Danish Data Protection Agency approved this study (Journal number 15/14594).

Consent for publication
All authors' consent to publish this document

Competing interests
The authors declare that they have no competing interests

Funding
The study is a part of a three year PhD grant with contributions from Centre for Quality, Region of Southern Denmark, The Institute of Regional Health Research, University of Southern Denmark and Region of Southern Denmark. The Study further received a grant from the Regional Research Fund of Southern Denmark, Region of Southern Denmark. All grant givers had no saying in the design and interpretation of the study.

Strengths and limitations of this study:
-Nation-wide registry data including socio-demographic information on all citizens aged 18+ -Use of a Difference-in-Difference design for possible causal inference -The study might underestimate the lumbar MRIs from private hospitals  [13][14][15] .
In this study we have the opportunity of using nation-wide data and hence evaluating a natural experiment. In 2010, Region of Southern Denmark (RSD), made two organisational changes.

Primary outcome
The primary outcome is yearly lumbar MRI per 1,000 enlisted with a GP.

Setting
In Denmark, five decentralised administrative regions, including 98 municipalities, manage the tax founded health care system 16

Data sources
The study used data from the registries at Statistics Denmark (DST), a governmental institution providing data for research purposes 17 . All registries are linkable at the individual level, using the personal civil registration number (CPR-number), which are given to all Danish citizens at birth 18 19 . The study includes data from the following registries: The Danish National Patient Registry (NPR) 20 21 , includes information on diagnosis coded according to the International Classification of Disease (ICD-10), and procedure and surgery codes with the CPR-number from patients receiving most of their services from the GP id 23 . GPs with patient list size less than 300 patients were deleted as they are hypothesised to be GPs either starting up or closing down the practice. Those citizens with no information of GP id in one of the study years, were allocated to a hypothetical GP id generated for each region.

Danish National Prescription Registry (DNPR) includes information on all prescription based
analgesic drugs sold at Danish primacies 24 . We identified analgesic drugs according to the Anatomical Therapeutic Chemical classification (ATC) code 25 . Analgesic drugs included ATC code NN02A and NN02B; tablet cans with >100 pills of paracetamol and ibuprofen, synthetic opioids, and opioids.
We further retrieved registers on income 26 , education 27 , job-and socio-economic status 28 , civil status 18 , and demographics 18 from DST.

Definition of lumbar MRI
This study included data for lumbar MRI (SKS code: UXME30) 21

Definition of referral mode
A referral mode variable was defined based on two variables from the NPR; Referral directly from the GP (1), directly from the Chiropractor or initiated by private insurance (2), directly from the office-based specialist doctors (3), and from the hospital department (4). In the dataset we observe registrations with referral directly from the GP, before 2010. These are recoded into hospital registrations.

Analyses strategy
The We hypothesise that the two referral options (direct GP referral and referral to the Spine Centre) drives any change in use of lumbar MRI. As patients have not chosen to live in RSD based on the access to MRI, the assumption behind our analyses strategy is that we can interpret patients as randomly assigned to a GP who by construct of the natural experiment happen to have access to the organizational changes (RSD) or not (control regions). We therefore included GPs from the Zealand Region (ZR) and the North Denmark Region (NR) as controls for all years in the analysis.  assumption behind our approach is that there were no time-varying unobservable covariates, that could explain differences in selection into a referral to lumbar MRI between GPs, and between regions 29 . Hence, we generally assume that citizens' need for MRI are identical among regions after controlling for observable patients' characteristics and supply factors related to LBP treatment did not change over time on the regional level. A limitation of our dataset is that we only have two years of observation before the organizational changes, which makes the validation of the common trend assumption hard to assess. As a consequence we supplemented the DD analysis with two robustness checks. First, we made a replication of the analysis using quarterly 10 data instead of annual data. This gives eight pre-treatment observations, which allow for a better assessment of the common trend. Second, we estimate the treatment effect using propensity score matching (PSM) -an approach that does not rely on the common trend assumption but on common support [30][31][32] .

Statistics
The DD model is implemented using a parametric Ordinary Least Squares (OLS) regression model with robust standard errors and clustering for GP id. We aggregated the individual level socio demographic data to GP level. This allowed for analysis using information from the socio demographic composition of the GPs' lists to account for any time varying patient characteristics, that is associated with LBP, and therefore explain differences in GPs' referral to lumbar MRI. A supplementary advantage of using the GP as analytical level is that we in this way obtain an unbalanced panel data structure of our dataset, with one observation per unique GP per year. As a robustness check we organise data in quarterly observations and re-assess the DD model using 24 quarterly observations rather than 7 annual observations per GP. We further use PSM with nearest neighbour with caliper equal to ¼ of the standard deviation on the propensity scores. The supplementary material gives detailed information on the robustness check using quarterly data and PSM.
The changes in referral modes were graphed for RSD (see Figure 1). To show dynamic year effects of the models, 2009 was used as pre-intervention and each intervention year was used as the post-intervention year, in four DD regression models-one for each post treatment year (2010,  The adjusted models add time varying covariates to the above variables. This is done to avoid that any observed change in RSD after the change is simply due to changes in the characteristics of the citizens over time -for example that citizens in RSD over time becomes more prevalent to LBP than control regions. All covariates included, except GP list size, were made as proportions of enlisted patients with characteristic X divided with the GP list size. Patients characteristics X included; age 18-59, citizens in a full-time job, income DKK 0-399.000 or missing, women, citizens living as singles, and Charlson comorbidity index score 33 2+, patients with vocational education, patients using a prescription on an analgesic drug at a pharmacists, patients having a visit at a physiotherapist, patients having a visit at a chiropractor, and patients visiting an office-based

Patient and Public Involvement
Patients were not involved in the study

Ethics
The       The dynamic year effects, for both models are seen in figure 3. Figure 3 indicates that the common trend assumption support is fulfilled, as a hypothesised treatment effect before the intervention  As in other studies from the US 7 , we find geographical variation in the use of lumbar MRI among the regions in Denmark. The reason for the difference in use of lumbar MRI among the regions is still unclear. Some points towards a special interest in back pain by specialist doctors in RSD, which relates to different regional clinical practices, which have been found in US studies 6 11 . The relationship between MRI usages and physician incentives 9 10 , is unlikely to explain the differences in a Danish setting; Firstly, physicians at public hospital receive a fixed yearly salary, thereby not having incentives to refer patients. Secondly, the public hospitals undertook 74 % of all scans.

Discussion
The increase in referrals for lumbar MRI following the change in GP referral access to lumbar MRI in the RSD in 2010 is noteworthy. GPs in the RSD clearly began to use the new referral option immediately and the use of the referral option increase by 115% from 2010 to 2013. This change might indicate a lowering in the threshold for a MRI referral. There could be numerous reasons for the use of direct referrals to lumbar MRI, including patient demands 35 10 37-39 . Further, the inappropriate use of lumbar MRI has been shown to be associated with an increased use of opioids, higher health care costs and has a low impact on pain relief or functional recovery after 6 months in non-specific LBP patients, without serious pathologies such as cancer, nerve root compression, cauda equina, radiculopathy and sciatica 3 5 40-46 . Further studies are needed to investigate if the same associations are found in this setting.

Strengths and Limitations
This study used DD estimates to capture the effect of the organisational changes and LBP DMP in RSD. Difference in difference is a popular design for evaluation of policy changes, as is widely used in social science 29 . DD relies on the assumption of a common trend in the pre-treatment period for the outcomes of interest. This assumption seems to be fulfilled in the current study. However, a clear limitation of our dataset is that we have a short pre-treatment period. As a consequence we have used DD on quarterly data as well as PSM analysis to check the robustness of the results.
Both analyses support the findings and as we believe the DD approach to be the most

Consent for publication
All authors' consent to publish this document

Competing interests
The authors declare that they have no competing interests      In this supplementary material we report the details of the robustness checks of the DD model in the paper. First we present results of reorganising data to quarterly levels and re-assessment of the DD model. Second we present the PSM model and assess the assumptions behind this model.

DD model using quarterly level
The results are presented below. Figure A.1 show the trends in MRI using quarterly data, and table A.1 show the DD results where we in addition to the covariates in the paper have included quarter dummies (Q1, Q2 Q3 and Q4) to take away the obvious seasonality that shows up in figure A.1.   Model (2) 2010-13 vs 2008-9 Model (

PSM model
The PSM approach requires that the common support assumption be fulfilled. Hence, covariates that describes the bias between the treatment and control group, is needed to produce propensity scores to weigh the MRI rates. A disadvantage of the PSM as compared to DD is that it does not control for unobserved variables causing bias -hence it is relying on a rich set of covariates. However, by using the MRI rate in 2008 and 2009 as matching covariates we indirectly control for unobservable variables. The reason is that it can be argued that any unobserved selection bias between treatment-and control groups may also be present in the outcome variable before the reform. Hence, including the historic MRI rates for 2008 and 2009 as matching variables is a way to control for unobserved heterogeneity between treatment and control GPs and this approach is generally believed to be very strong -also compared to DD (G.  show the treatment effect of the reform using PSM with various sets of covariates. It is evident that the effect is positive and significant but also that the magnitude of the effect is much higher than the DD estimates. We use Stata psmatch2 command with conventional options; nearest neighbour with (caliper = ¼ of the standard deviation on the propensity scores) and bootstrapped error terms. As the DD clusters at GP level we also tried to estimate the PSM treatment effect by simply running an OLS regression on the matched sample using the propensity scores as weights and then cluster at GP level in the OLS (B. Arpino and M. Cannas, 2016). This did not change the results.  Table A.3 show that the bias between treated and control GPs has been reduced substantially for most of the covariates. This indicates that comparison after matching is valid. Some covariates are not biased in the unmatched sample but turns biased in the matched sample and therefore we try to run the PSM model with the historic outcome variables only. Table 3 show that this change the magnitude of the effect but not the significance.   1  2  3  4  5  6  7  8  9  10  11  12  13  14  15  16  17  18  19  20  21  22  23  24  25  26  27  28  29  30  31  32  33  34  35  36  37  38  39  40  41  42  43  44  45  46  47  48  49  50  51  52  53  54  55  56  57  58  59

Introduction
Background/rationale 2 Explain the scientific background and rationale for the investigation being reported 3 Objectives 3 State specific objectives, including any pre-specified hypotheses 4

Study design 4
Present key elements of study design early in the paper 5 Setting 5 Describe the setting, locations, and relevant dates, including periods of recruitment, exposure, follow-up, and data collection 5 Participants 6 (a) Cohort study-Give the eligibility criteria, and the sources and methods of selection of participants. Describe methods of follow-up Case-control study-Give the eligibility criteria, and the sources and methods of case ascertainment and control selection. Give the rationale for the choice of cases and controls Cross-sectional study-Give the eligibility criteria, and the sources and methods of selection of participants 6 (b) Cohort study-For matched studies, give matching criteria and number of exposed and unexposed Case-control study-For matched studies, give matching criteria and the number of controls per case Variables 7 Clearly define all outcomes, exposures, predictors, potential confounders, and effect modifiers. Give diagnostic criteria, if applicable 6, 7, 9 Data sources/ measurement 8* For each variable of interest, give sources of data and details of methods of assessment (measurement). Describe comparability of assessment methods if there is more than one group  1  2  3  4  5  6  7  8  9  10  11  12  13  14  15  16  17  18  19  20  21  22  23  24  25  26  27  28  29  30  31  32  33  34  35  36  37  38  39  40  41  42  43  44  45  46  47 o n l y Cross-sectional study-If applicable, describe analytical methods taking account of sampling strategy (e) Describe any sensitivity analyses 9 Results
Firstly, the possibility for direct referral to lumbar MRI was introduced GPs, and secondly the region gathered all local spine departments into one specialist hospital called the Spine Centre.

Strengths and limitations of this study:
-Nation-wide registry data including socio-demographic information on all citizens aged 18+ -Use of a Difference-in-Difference design for possible causal inference The factors associated with the increased use of MRI in the diagnostics of low back pain have been investigated. Research shows that the substantial geographic differences in use of spinal MRI across states in the US 5-8 can be explained by differences in local clinical practices 6 , physician ownership of specialty hospitals 9 , fee-for-service schemes 10 , MRI-scanner availability 11 and state median income per capita 12 . However, these studies were undertaken in a US-setting among populations that had limited access to health care providers and where a fee-for service incentive affected doctors' wages. Consequently, more studies are needed on factors impacting the use of lumbar MRI, in other health care settings [13][14][15] .
In this study we have the opportunity of using nation-wide data and hence evaluating a natural experiment. In 2010, Region of Southern Denmark (RSD), made two organisational changes.

Primary outcome
The primary outcome is yearly lumbar MRI per 1,000 enlisted with a GP.

Setting
In Denmark, five decentralised administrative regions, including 98 municipalities, manage the tax founded health care system 16

Data sources
The study used data from the registries at Statistics Denmark (DST), a governmental institution providing data for research purposes 17 . All registries are linkable at the individual level, using the personal civil registration number (CPR-number), which are given to all Danish citizens at birth 18 19 . The study includes data from the following registries: The Danish National Patient Registry (NPR) 20 21 , includes information on diagnosis coded according to the International Classification of Disease (ICD-10), and procedure and surgery codes  22 , includes all contacts to the primary sector health care providers including GPs, CP, physiotherapists, and office-based specialist doctors. The GP list and GP list size were generated by combining the unique GP id with the CPR-number from patients receiving most of their services from the GP id 23 . GPs with patient list size less than 300 patients were deleted as they are hypothesised to be GPs either starting up or closing down the practice. Those citizens with no information of GP id in one of the study years, were allocated to a hypothetical GP id generated for each region.

Danish National Prescription Registry (DNPR) includes information on all prescription based
analgesic drugs sold at Danish primacies 24 . We identified analgesic drugs according to the Anatomical Therapeutic Chemical classification (ATC) code 25 . Analgesic drugs included ATC code NN02A and NN02B; tablet cans with >100 pills of paracetamol and ibuprofen, synthetic opioids, and opioids.
We further retrieved registers on income 26 , education 27 , job-and socio-economic status 28 , civil status 18 , and demographics 18 from DST.

Definition of lumbar MRI
This study included data for lumbar MRI (SKS code: UXME30) 21 . Each MRI scan performed at a public hospital is recorded in NPR. Lumbar MRIs performed on a private hospital are recorded in

Definition of referral mode
A referral mode variable was defined based on two variables from the NPR; Referral directly from the GP (1), directly from the CP or initiated by private insurance (2), directly from the office-based specialist doctors (3), and from the hospital department (4). Before 2010, we observe referrals to lumbar MRI from GPs. These are recoded into hospital registrations.

Analyses strategy
The We hypothesise that the two referral options (direct GP referral and referral to the Spine Centre) drives any change in use of lumbar MRI. As patients have not chosen to live in RSD based on the access to MRI, the assumption behind our analyses strategy is that we can interpret patients as randomly assigned to a GP who by construct of the natural experiment happen to have access to the organizational changes (RSD) or not (control regions). We therefore included GPs from the ZR and the NR as controls for all years in the analysis. GPs from the CD are included from 2008 to  we expect time varying differences occurring over time we need to add covariates. Hence, second assumption behind our approach is that there were no time-varying unobservable covariates, that could explain differences in selection into a referral to lumbar MRI between GPs, and between regions 29 . Hence, we generally assume that citizens' need for lumbar MRI are identical among regions after controlling for observable patients' characteristics and supply factors related to LBP treatment did not change over time on the regional level. A limitation of our dataset is that we only have two years of observation before the organizational changes, which makes the validation of the common trend assumption hard to assess. As a consequence we supplemented the DD analysis with two robustness checks. First, we made a replication of the analysis using quarterly 10 data instead of annual data. This gives eight pre-treatment observations, which allow for a better assessment of the common trend. Second, we estimate the treatment effect using propensity score matching (PSM) -an approach that does not rely on the common trend assumption but on common support [30][31][32] .

Statistics
The DD model is implemented using a parametric Ordinary Least Squares (OLS) regression model with robust standard errors and clustering for GP id. We aggregated the individual level socio demographic data to GP level. This allowed for analysis using information from the socio demographic composition of the GPs' lists to account for any time varying patient characteristics, that is associated with LBP, and therefore explain differences in GPs' referral to lumbar MRI. A supplementary advantage of using the GP as analytical level is that we in this way obtain an unbalanced panel data structure of our dataset, with one observation per unique GP per year. As a robustness check we organise data in quarterly observations and re-assess the DD model using 24 quarterly observations rather than 7 annual observations per GP. We further use PSM with nearest neighbour with caliper equal to ¼ of the standard deviation on the propensity scores. The supplementary material gives detailed information on the robustness check using quarterly data and PSM.
The changes in referral modes were graphed for RSD (see Figure 1)   The adjusted models add time varying covariates to the above variables. This is done to avoid that any observed change in RSD after the change is simply due to changes in the characteristics of the citizens over time -for example that citizens in RSD over time becomes more prevalent to LBP than citizens in control regions. All covariates included, except GP list size, were made as proportions of enlisted patients with characteristic X divided with the GP list size. Patients characteristics X included; age 18-59, citizens in a full-time job, income DKK 0-399,000 or missing, women, citizens living as singles, and Charlson comorbidity index score 33 2+, patients with vocational education, patients using a prescription on an analgesic drug at a pharmacists, patients having a visit at a physiotherapist, patients having a visit at a CP, and patients visiting an office-

Patient and Public Involvement
Patients were not involved in the study

Discussion
This study showed that establishing a Spine Centre in the RSD and introducing direct referrals for lumbar MRI by GPs was associated with an increase in the use of lumbar MRI (compared to that of  1  2  3  4  5  6  7  8  9  10  11  12  13  14  15  16  17  18  19  20  21  22  23  24  25  26  27  28  29  30  31  32  33  34  35  36  37  38  39  40  41  42  43  44  45  46  47  48  49  50  51  52  53  54  55  56  57  58  59  As in other studies from the US 7 , we find geographical variation in the use of lumbar MRI among the regions in Denmark. The reason for the difference in use of lumbar MRI among the regions is still unclear. Some points towards a special interest in back pain by specialist doctors in RSD, which relates to different regional clinical practices, which have been found in US studies 6 11 . The relationship between MRI usages and physician incentives 9 10 , is unlikely to explain the differences in a Danish setting; Firstly, physicians at public hospital receive a fixed yearly salary, thereby not having incentives to refer patients. Secondly, the public hospitals undertook 74 % of all scans.
The increase in referrals for lumbar MRI following the change in GP referral access to lumbar MRI in the RSD in 2010 is noteworthy. GPs in the RSD clearly began to use the new referral option immediately and the use of the referral option increase by 115% from 2010 to 2013. This change might indicate a lowering in the threshold for a MRI referral. There could be numerous reasons for the use of direct referrals to lumbar MRI, including patient demands 35 1  2  3  4  5  6  7  8  9  10  11  12  13  14  15  16  17  18  19  20  21  22  23  24  25  26  27  28  29  30  31  32  33  34  35  36  37  38  39  40  41  42  43  44  45  46  47  48  49  50  51  52  53  54  55  56  57  58  59  60   F  o  r  p  e  e  r  r  e  v  i  e  w  o  n  l  y   17 has been shown to be associated with an increased use of opioids, higher health care costs and has a low impact on pain relief or functional recovery after 6 months in non-specific LBP patients, without serious pathologies such as cancer, nerve root compression, cauda equina, radiculopathy and sciatica 3 5 40-46 . Further studies are needed to investigate if the same associations are found in this setting.

Strengths and Limitations
This study used DD estimates to capture the effect of the organisational changes and LBP DMP in RSD. Difference in difference is a popular design for evaluation of policy changes, as is widely used in social science 29 . DD relies on the assumption of a common trend in the pre-treatment period for the outcomes of interest. This assumption seems to be fulfilled in the current study. However, a clear limitation of our dataset is that we have a short pre-treatment period. As a consequence we have used DD on quarterly data as well as PSM analysis to check the robustness of the results.

Competing interests
The authors declare that they have no competing interests

Authors' contributions
Model ( Hence the robustness check using quarterly data confirms the results in the paper.

PSM model
The PSM approach requires that the common support assumption is fulfilled. Hence, covariates that describes the bias between the treatment and control group, is needed to produce propensity scores to weigh the MRI rates. A disadvantage of the PSM as compared to DD is that it does not control for unobserved variables causing bias -hence it is relying on a rich set of covariates. However, by using the MRI rate in 2008 and 2009 as matching covariates we indirectly control for unobservable variables. The reason is that it can be argued that any unobserved selection bias between treatment-and control groups may also be present in the outcome variable before the reform. Hence, including the historic MRI rates for 2008 and 2009 as matching variables is a way to control for unobserved heterogeneity between treatment and control GPs and this approach is generally believed to be very strong -also compared to DD (G.  show the treatment effect of the reform using PSM with various sets of covariates. It is evident that the effect is positive and significant but also that the magnitude of the effect is much higher than the DD estimates. We use Stata psmatch2 command with conventional options; nearest neighbour with (caliper = ¼ of the standard deviation on the propensity scores) and bootstrapped error terms. As the DD clusters at GP level we also tried to estimate the PSM treatment effect by simply running an OLS regression on the matched  1  2  3  4  5  6  7  8  9  10  11  12  13  14  15  16  17  18  19  20  21  22  23  24  25  26  27  28  29  30  31  32  33  34  35  36  37  38  39  40  41  42  43  44  45  46  47  48  49  50  51  52  53  54  55  56  57  58  59  Figure A.2 assesses the common support assumption, which is key to PSM. As the histograms are overlapping it shows that for any GP in RSD there exists a control GP with the same propensity score -hence there exist a suitable match for all RSD GPs. Table A. 3 show that the bias between treated and control GPs has been reduced substantially for most of the covariates. This indicates that comparison after matching is valid. Some covariates are not biased in the unmatched sample but turns biased in the matched sample and therefore we try to run the PSM model with the historic outcome variables only. Table A.2 show that this change the magnitude of the effect but not the significance.   1  2  3  4  5  6  7  8  9  10  11  12  13  14  15  16  17  18  19  20  21  22  23  24  25  26  27  28  29  30  31  32  33  34  35  36  37  38  39  40  41  42  43  44  45  46  47  48  49  50  51  52  53  54  55  56  57  58  59  60 Introduction Background/rationale 2 Explain the scientific background and rationale for the investigation being reported 3 Objectives 3 State specific objectives, including any pre-specified hypotheses 4

Study design 4
Present key elements of study design early in the paper 5 Setting 5 Describe the setting, locations, and relevant dates, including periods of recruitment, exposure, follow-up, and data collection 5 Participants 6 (a) Cohort study-Give the eligibility criteria, and the sources and methods of selection of participants. Describe methods of follow-up Case-control study-Give the eligibility criteria, and the sources and methods of case ascertainment and control selection. Give the rationale for the choice of cases and controls Cross-sectional study-Give the eligibility criteria, and the sources and methods of selection of participants 6 (b) Cohort study-For matched studies, give matching criteria and number of exposed and unexposed Case-control study-For matched studies, give matching criteria and the number of controls per case Variables 7 Clearly define all outcomes, exposures, predictors, potential confounders, and effect modifiers. Give diagnostic criteria, if applicable 6, 7, 9 Data sources/ measurement 8* For each variable of interest, give sources of data and details of methods of assessment (measurement). Describe comparability of assessment methods if there is more than one group  1  2  3  4  5  6  7  8  9  10  11  12  13  14  15  16  17  18  19  20  21  22  23  24  25  26  27  28  29  30  31  32  33  34  35  36  37  38  39  40  41  42  43  44  45  46  47 o n l y Cross-sectional study-If applicable, describe analytical methods taking account of sampling strategy (e) Describe any sensitivity analyses 9 Results