Background
Interest in physical therapy utilization has grown in recent decades. In the United States, national inflation-adjusted expenditures for spine-related physical therapy have increased by 78% between 1997 and 2005, which is more than the 65% rise in total estimated care expenditures for the condition [
1]. Several authors tried to understand if physical therapy is used properly in comparing its utilization in different settings. They found variations across countries in terms of the intensity of physical therapy per treatment episode [
2]. There is a variety of acute or chronic conditions justifying physical therapy, one of the main complaint being back pain [
3,
4]. The treatment of this condition required an average of five sessions in United Kingdom, while the US average was 11 [
5,
6].
Variations in physical therapy use were analyzed based on the propensity to start physical therapy [
3,
7-
10], the number of sessions per treatment episode [
9,
11-
13] and costs [
13,
14]. Several studies have analyzed the determinants of the intensity of physical therapy use, highlighting the role of both health-related factors like age, gender, site and severity of the condition and poor health [
1,
8,
11-
15] and others, such as insurance status, education level, income and urban residence [
1,
12,
13,
15]. However, even after most of these factors are taken into account, the treatment intensity can still vary substantially between patients [
12,
16]. A Dutch study suggested that there was an overuse of physical therapy for lower back pain; patients with acute complaints, in particular, attended a much higher number of sessions than recommended. Moreover, only a minority of patients with lower back pain was treated according to national physical therapy guidelines [
17]. The introduction of professional guidelines coupled with national volume policy led to a decline in the number of physical therapy appointments and an increase in the use of evidence-based methods to treat lower back pain [
18].
We were unable to find any analyses of the relative role of patients, physicians, physiotherapists and financing regulations on the volume of physical therapy used. Switzerland is an interesting setting because there is a high density of physiotherapists, as well as a number of control mechanisms in place (deductibles, ceiling per prescription, and higher fees for first session). The density of physiotherapists is estimated at 1/700 inhabitants, which is twice the average density observed in Europe [
19]. Roughly half of physiotherapists are in private practice [
20]. In 2006, physical therapy was responsible for 7.5% of allied care costs and 1.3% of ambulatory health care services costs (including auxiliary services such as transport, radiology and laboratory) [
21].
The primary objective of our study was to ascertain the extent to which the volume of physical therapy per treatment episode depended on patient characteristics and/or on physician and physiotherapist behaviors, and whether Swiss regulations were effective. To this end, we used routinely collected data on a large national representative sample of insured, which enabled us to analyze a broad range of conditions.
Results
We identified 122,841 patients who had received physical therapy during 2005. The total number of treatment episodes was 169,305. These were dispensed by 4,029 physiotherapists based on referrals by 9,476 physicians. The decision to include only the patients’ first episode and to exclude physicians and physiotherapists with only one observation (missing coefficient of variation) led to a studied population of 87,866 episodes dispensed by 3,365 physiotherapists based on referrals by 6,131 physicians.
Table
1 compares the source and studied population. The latter exhibited a weaker severity: younger subjects, fewer conditions assigned to a clearly defined musculoskeletal condition (16% vs 26%), weaker co-morbidity burden, and less frequent incidence of treatment management by several care providers (more than 95% were treated by a single physician and physiotherapist versus 58% and 69% respectively in the source population). In contrast, physician- and physiotherapist-related variables were similar in the two samples.
Table 1
Mean volume (number of physical therapy sessions per treatment episode) according to patient, physiotherapist and referring physician characteristics in the source and studied population
Patient factors
|
Age (years) |
<18 | 10,667 (6%) | 8.9 (8.3) | 6,928 (8%) | 8.5 (7.0) |
19-39 | 30,998 (18%) | 10.3 (9.5) | 18,546 (21%) | 9.8 (8.0) |
40-59 | 59,987 (35%) | 12.1 (11.4) | 31,150 (35%) | 11.7 (10.1) |
60-79 | 52,318 (31%) | 13.1 (12.6) | 24,241 (28%) | 13.0 (11.9) |
80+ | 15,335 (9%) | 14.8 (16.4) | 7,001 (8%) | 14.8 (16.0) |
Gender |
Male | 62,869 (37%) | 11.8 (11.9) | 35,472 (40%) | 11.3 (10.6) |
Female | 106,436 (63%) | 12.3 (12.0) | 52,394 (60%) | 11.9 (10.9) |
Nature of the main condition |
Neurological disease | 6,086 (4%) | 17.5 (22.2) | 2,336 (3%) | 16.9 (21.4) |
Shoulder surgeryb | 1,722 (1%) | 16.9 (14.4) | 337 (0%) | 19.0 (15.8) |
Muscle diseaseb | 1,112 (1%) | 14.8 (14.4) | 331 (0%) | 15.3 (14.7) |
Other hip surgeryb | 1,827 (1%) | 14.6 (13.3) | 489 (1%) | 13.9 (12.3) |
Knee prosthesisb | 3,363 (2%) | 14.4 (12.7) | 661 (1%) | 16.9 (13.7) |
Rehabilitation | 863 (1%) | 14.4 (17.0) | 285 (0%) | 12.5 (11.2) |
Hip prosthesisb | 4,553 (3%) | 13.6 (12.3) | 848 (1%) | 13.9 (12.2) |
Other orthopedicsb | 3,055 (2%) | 13.6 (13.1) | 1,629 (2%) | 13.4 (14.4) |
Backb | 8,563 (5%) | 13.5 (13.6) | 2,388 (3%) | 13.6 (14.3) |
Osteoporosisb | 5,701 (3%) | 13.4 (13.2) | 2,474 (3%) | 13.6 (12.2) |
Cancer | 3,178 (2%) | 13.1 (13.4) | 1,421 (2%) | 13.2 (14.2) |
Traumab | 4,947 (3%) | 13.0 (13.6) | 2,111 (2%) | 12.5 (12.1) |
Lymphatic and breast disease | 1,587 (1%) | 13.0 (12.9) | 600 (1%) | 12.4 (11.4) |
Kneeb | 469 (0%) | 12.6 (9.2) | 173 (0%) | 13.4 (10.4) |
Rheumatologyb | 7,887 (5%) | 12.3 (11.7) | 3675 (4%) | 12.4 (11.3) |
Psychiatry | 34,242 (20%) | 12.3 (11.8) | 17,588 (20%) | 12.3 (11.5) |
Other (medical) | 41,592 (25%) | 11.0 (9.7) | 25,764 (29%) | 10.9 (9.0) |
Surgery | 5,529 (3%) | 10.8 (9.0) | 3,203 (4%) | 10.3 (7.6) |
Any of above | 33,029 (20%) | 10.7 (9.7) | 21,553 (25%) | 10.4 (8.3) |
Comorbidity burden (annual health care costs, mean in 103 CHF) |
<1000 | 27,242 (16%) | 10.3 (8.8) | 22,319 (25%) | 10.1 (8.1) |
1001-2000 | 20,062 (12%) | 10.5 (8.3) | 13,754 (16%) | 10.4 (7.9) |
2001-5000 | 44,321 (26%) | 11.2 (8.9) | 24,725 (28%) | 11.3 (8.6) |
5001-10000 | 36,000 (21%) | 12.2 (10.6) | 14,805 (17%) | 12.5 (10.5) |
10001-20000 | 24,169 (14%) | 13.4 (13.0) | 7,451 (8%) | 14.1 (13.8) |
20001-50000 | 13,626 (8%) | 16.1 (18.5) | 3,747 (4%) | 16.8 (19.2) |
>50000 | 3,885 (2%) | 22.3 (30.1) | 1,065 (1%) | 24.5 (32.8) |
Deductibles |
<=300 | 98,499 (58%) | 12.4 (12.6) | 50764 (58%) | 11.9 (11.4) |
301-600 | 55,734 (33%) | 12.2 (11.3) | 27582 (31%) | 11.7 (10.4) |
601-1500 | 11,984 (7%) | 10.4 (8.6) | 7484 (9%) | 10.1 (7.5) |
>1500 | 3,088 (2%) | 10.0 (9.5) | 2036 (2%) | 9.6 (8.3) |
Large city residencec |
No | 104,960 (62%) | 12.0 (11.8) | 55680 (63%) | 11.5 (10.7) |
Yes | 64,345 (38%) | 12.4 (12.0) | 32186 (37%) | 11.9 (10.9) |
Number of physicians per patient |
1 | 98,864 (58%) | 11.7 (10.9) | 84231 (96%) | 11.6 (10.6) |
2 | 45,346 (27%) | 12.6 (12.9) | 3633 (4%) | 12.6 (13.6) |
>2 | 25,095 (15%) | 13.1 (13.7) | 2 (0%) | 5.5 (3.5) |
Number of physiotherapists per patient |
1 | 116,868 (69%) | 12.1 (11.7) | 85332(97%) | 11.6 (10.7) |
2 | 39,471 (23%) | 12.3 (12.3) | 2426 (3%) | 12.8 (11.8) |
>2 | 12,966 (8%) | 12.0 (12.4) | 108 (0%) | 13.4 (12.7) |
Physician factors
|
Proportion of treatments by physician as a nine-session episode by quintiles rank |
1st | 22% | 10.5 (11.8) | 21% | 9.8 (10.1) |
2nd | 49% | 11.1 (11.2) | 48% | 10.6 (10.3) |
3rd | 63% | 12.4 (12.5) | 63% | 11.9 (11.3) |
4th | 73% | 13.3 (12.0) | 73% | 12.8 (11.0) |
5th | 86% | 13.4 (11.9) | 85% | 13.2 (10.7) |
Proportion of new treatments by physician by quintiles rank |
1st | 48% | 15.2 (16.8) | 50% | 14.3 (15.2) |
2nd | 60% | 12.7 (12.0) | 61% | 12.0 (10.6) |
3rd | 65% | 11.7 (10.5) | 66% | 11.5 (9.9) |
4th | 71% | 11.3 (9.8) | 72% | 10.9 (8.7) |
5th | 81% | 9.8 (7.6) | 81% | 9.6 (7.1) |
Variation coefficient of the physician (by quintiles rank)d |
1st | 0.45 | 10.3 (5.8) | 0.38 | 9.9 (4.7) |
2nd | 0.65 | 11.4 (7.8) | 0.56 | 10.8 (6.7) |
3rd | 0.76 | 11.6 (9.4) | 0.67 | 11.6 (8.3) |
4th | 0.88 | 13.0 (12.1) | 0.80 | 11.9 (10.1) |
5th | 1.19 | 14.5 (19.3) | 1.14 | 14.1 (18.2) |
Physiotherapist factors
|
Proportion of treatments by physiotherapist as a nine-session episode by quintiles rank |
1st | 29% | 11.0 (12.6) | 30% | 10.2 (11.2) |
2nd | 46% | 11.2 (11.1) | 47% | 10.8 (10.4) |
3rd | 56% | 12.0 (11.4) | 56% | 11.4 (10.0) |
4th | 68% | 12.8 (12.3) | 68% | 12.4 (10.7) |
5th | 84% | 13.8 (11.9) | 84% | 13.5 (11.1) |
Proportion of new treatments by physiotherapist by quintiles rank |
1st | 49% | 14.9 (16.9) | 51% | 14.2 (15.0) |
2nd | 60% | 12.6 (11.7) | 61% | 12.0 (10.5) |
3rd | 66% | 11.8 (10.8) | 51% | 14.2 (10.0) |
4th | 71% | 11.0 (9.4) | 61% | 12.0 (8.6) |
5th | 80% | 10.3 (8.4) | 67% | 11.5 (7.7) |
Variation coefficient of the physiotherapist (by quintiles rank)e |
1st | 0.53 | 10.8 (6.4) | 0.46 | 10.4 (5.6) |
2nd | 0.68 | 11.4 (8.2) | 0.61 | 10.7 (7.0) |
3rd | 0.78 | 11.7 (9.6) | 0.70 | 11.4 (8.4) |
4th | 0.89 | 12.5 (11.8) | 0.81 | 11.7 (9.9) |
5th | 1.20 | 14.3 (19.1) | 1.13 | 14.1 (18.0) |
The median number of sessions per episode was nine (interquartile range 6–13); the distribution had a long right tail with a maximum of 330. Such cases, which reflect the existence of chronic illness management, for instance provision of respiratory support, substantiate our choice of applying the log-linear modelling of data. In bivariate analyses, higher use was associated with older age, women, higher annual health care costs and specific conditions. We observed the highest use for neurological diseases and shoulder operations, while use was lowest for unspecific medical conditions and non-orthopedic surgery. Higher deductibles were associated with lower use. More sessions were associated with a higher proportion of nine-session episodes and a lower proportion of new treatments, computed by physician or physiotherapist. A large range of variation coefficient of the physiotherapist or the physician was associated with higher use.
The results of the multivariate analysis are shown in Table
2. We found a significant link between all of the above predictors and the number of sessions.
Table 2
Multilevel regression analysis of the number of physiotherapy session
a
Patient needs
| | |
Age and gender | | |
[20-39] men | .088 | .062- .114 |
[40–59] men | .217 | .193- .242 |
[60–79] men | .260 | .235- .285 |
[80 + ] men | .211 | .175- .247 |
[20-39] women | .095 | .071- .120 |
[40–59] women | .232 | .208- .255 |
[60–79] women | .291 | .266- .315 |
[80 + ] women | .259 | .230- .288 |
Conditionsd | | |
Shoulder operation | .324 | .257- .391 |
Total knee prosthesis | .252 | .203- .301 |
Muscular disease | .175 | .107- .242 |
Neurological diseases | .081 | .053- .109 |
Other orthopedic surgery | .043 | .011- .074 |
Osteoporosis | .035 | .008- .062 |
Rheumatic conditions | .024 | .002- .047 |
Other surgery | -.043 | -.067- -.019 |
Lymphatic problems | -.055 | -.106- -.004 |
Rehabilitation | -.084 | -.157- -.011 |
Comorbidity burden (annual costs 103 CHF) | | |
1,001–2,000 | .020 | .006- .033 |
2,001–5,000 | .065 | .053- .077 |
5,001–10,000 | .130 | .115- .144 |
10,001–20,000 | .180 | .162- .198 |
20,001–50,000 | .223 | .199- .246 |
>50,000 | .381 | .340- .421 |
Provider practices
| | |
Variation coefficient of the physician (by quintiles rank) | | |
2nd | .043 | .028- .058 |
3rd | .062 | .046- .078 |
4th | .062 | .046- .078 |
5th | .082 | .065- .099 |
Variation coefficient of the physiotherapist (by quintiles rank) | | |
2nd | .019 | .000- .038 |
3rd | .037 | .018- .057 |
4th | .065 | .044- .086 |
5th | .087 | .067- .107 |
Funding regulations
| | |
Deductibles (CHF) | | |
601–1,500 | -.060 | -.076- -.044 |
>1,500 | -.086 | -.115- -.058 |
Ceiling per prescription (proportion of treatments by physician as a nine-session episode by quintiles rank) | | |
2nd | .080 | .064-.097 |
3rd | .154 | .137- .171 |
4th | .205 | .188- .223 |
5th | .235 | .216- .254 |
Ceiling per prescription (proportion of treatment by physiotherapist as a nine-session episode by quintiles rank | | |
2nd | .081 | .059- .103 |
3rd | .114 | .092- .136 |
4th | .155 | .132- .177 |
5th | .227 | .202- .252 |
Proportion of new treatments by physician by quintiles rank | | |
2nd | -.050 | -.066- -.033 |
3rd | -.058 | -.074- -.041 |
4th | -.095 | -.112- -.078 |
5th | -.154 | -.171- -.137 |
Proportion of new treatments by physiotherapist by quintiles rank | | |
2nd | −0.045 | -.064- -.025 |
3rd | −0.071 | -.091- -.051 |
4th | −0.081 | -.101- -.060 |
5th | −0.104 | -.125- -.082 |
Context variables
e
| | |
Being treated by more than one physician | -.083 | -.122- -.045 |
Being treated by more than one physiotherapist | .060 | .015- .105 |
Residency canton (13 dummy variables) | | |
Only one had a significant coefficient | .042 | .006-.078 |
Model constant
| 1.732 | 1.688-1.776 |
Physical therapy use increased with age until 79 years; a 70-year-old man had a 4.3% higher use than a 50-year-old man (as shown by the difference between the two semi-elasticities, i.e. .260-.217). Use was slightly higher among women regardless of age (about 2% on average). Patients with the highest health care spending had almost 40% more sessions than people who spent the least. Shoulder surgery accounted for a 32.4% increase. Patients with the highest deductible had on average 8.6% fewer visits than those with the lowest deductibles.
The higher proportion of nine-session episodes was associated with higher use: switching from the lowest to the highest proportion increased use by 23% for both physicians and physiotherapists. A higher proportion of new treatments had an opposite effect: use shrank by more than 10% for physiotherapists and by more than 15% for physicians. A larger coefficient of variation, i.e. better responsiveness, was associated with higher use (about 8% for both physicians and physiotherapists).
We found no significant link between the number of sessions and the place of residence (urban or not) and cantonal indicators (except one). Being treated by several physicians lowered use, whereas being treated by several physiotherapists increased use.
Estimates of variance components are shown in Table
3. Most of the variation in the number of sessions was due to differences between patients (88.8% of the total variance) and not between physicians (4.9%) or physiotherapists (6.3%). The overall variance explained by the full model was rather weak (11.2%) despite the large coefficients of most factors.
Table 3
Proportion of variation explained by grouping structure and covariates
By grouping level
e
| | | | | | | | | |
Physician | .021 | .049 | .000 | .079 | .000 | .048 | .251 | .029 | .323 | .730 |
Physio. | .028 | .063 | .022 | .033 | .000 | .055 | .174 | .032 | .274 | .590 |
Patient | .393 | .888 | .000 | .040 | .001 | .002 | .000 | .000 | .002 | .045 |
Overall
| .442 | 1 | | | | | | | | .112 |
Our prognostic factors explained a large proportion of variance between physicians and between physiotherapists: 73% and 59%, respectively. For physicians, pricing rules explained the largest proportion: 25% for the proportion of nine-session sets, and 5% for the proportion of new treatments. For physiotherapists, it was 17% and 6%, respectively. Health status was an important explanatory factor for variations between physicians (8%). Responsiveness, health factors and context (management of condition by several physiotherapists) had a similar predictive ability on variations between physiotherapists (2 to 3%).
At 4.5%, the proportion of explained variance between patients was very low. The most powerful prognostic factor was health status.
Using the back-transformation approach, we found that switching from the lowest (<600 Swiss francs) to the next highest deductible (601–1,500 Swiss francs) would save an average of 0.7 sessions per treatment episode. Likewise, restricting the proportion of nine-session episodes to the fourth quintile, i.e. maximum of 73% for physicians and maximum of 68% for physiotherapists (upper limit of the 4th quintile) would save a total of 1.4 sessions. Increasing the proportion of new treatments above the first quintile, i.e. over 60% (upper limit of the first quintiles for both care providers), would save a total of 1.1 sessions.
The differences between the least and most parsimonious practices were 1.3 sessions per treatment for physicians and 2.7 for physiotherapists.
Discussion
The intensity of physical therapy utilization was relatively high in our population compared to other countries, which would suggest that effectiveness in Switzerland is sub-optimal. In a national non-selected sample of US adults, the average number of visits per episode was 9.6 [
13], whereas an older population of Medicare beneficiaries attended a mean of 6.8 appointments for musculoskeletal conditions [
38]. In the Netherlands, the treatment of similar conditions required an average of 10.5 visits [
39]. A cross-country comparison found substantial variation in the type of treatment given and the number of visits per episode [
2]. In this study, corrected for age, gender and episode duration, mean numbers were 10.0 in the US, 6.5 in Israel and 10.0 in the Netherlands.
Our study confirms that the considerable variation in the intensity of physical therapy per treatment episode depends on both health-related and non-health related factors.
Poorer health status, reflected by higher health care costs, was associated with a higher number of visits. A higher number of sessions among women was consistent with their usual higher level of care use [
40]. The gender difference might also be related to non-measured morbidity, such as levels of pain or impairment, which tend to be more severe for women with musculoskeletal complaints than for their male counterparts [
41]. Like other studies, we found that shoulder and knee impairments were associated with more visits [
38] and that having surgery also increased the number of visits [
42]. The decline in use among the oldest age groups has also been found by other studies [
43,
44].
Insurance status was consistently shown to affect the use of physical therapy services [
43,
44]; higher deductibles decreased utilization, suggesting underuse among patients who chose the highest out-of-pocket payment option.
More physical therapy sessions were associated with physicians and physiotherapists with the best responsiveness (i.e. highest coefficients of variation).
The higher proportion of nine-session sets was associated with more intense use of physical therapy, indicating that prescription caps did not hinder the number of sessions per episode. Restricting the number of sessions has been the standard payment policy to limit overuse. Our findings, however, challenge its effectiveness. In Israel, where there is no cap but rather long waiting lists, patients with acute complaints receive more sessions than those with chronic complaints, probably because the expected improvement is better among the former group [
2]. In Switzerland, the ceiling is set at nine sessions, corresponding to the median number of sessions. This cap might have no moderating effect on the many patients requiring less than nine sessions and may, in fact, encourage the provision of 18 sessions to patients who would require slightly more than nine sessions. We recommend a lower ceiling for the majority of acute conditions, as the literature and our own data would suggest that six sessions per prescription in non-surgery conditions is adequate [
2,
17,
45].
Physiotherapists with a higher rate of new treatments tended to provide fewer sessions than others. This might indicate that physiotherapists tend to compensate for the smaller volume of new patients by extending the treatment of existing patients. However, we found the same association for physicians (more new physical therapy referrals was associated with lower intensity of physical therapy use), even though they have no financial incentives. This finding may also reflect differences in the population served: patients with chronic complaints generally received more sessions than those with acute ailments, provided there is not an undersupply of physiotherapists [
17].
Contrary to several studies elsewhere, we did not find significant variations across urban and rural residency and across geographical areas, which would indicate that there was no overt rationing of physical therapy in Switzerland. However, more homogenous health services area than cantons on factors that determine provision and utilization of health resources might yield different findings.
The proportion of explained variation (PEV) by physician and physiotherapist characteristics represented only a small component of total variance (5% and 6% respectively). The factors introduced in the model largely explained more than half of the associated PEV (levels 2 and 2’), thereby illustrating that unobserved provider-related variables would not improve the model significantly. Funding rules in Switzerland, especially caps, were the most important determinants. Health factors accounted for a larger proportion of variation among physicians (7.9%) than among physiotherapists (3.3%). This is not surprising given that the two health care providers base their decisions on different models: physicians use the biomedical model which is based on diagnosis, while physiotherapists apply the biopsychosocial model which is based on functional deficit [
46].
These findings suggest that providers tend to maximize the benefits offered by the regulations (not necessarily for their own benefit but rather for ensuring patient satisfaction). Not only does this highlight the need to review the current nine-session ceiling but it also argues in favor of further studies that explore financial incentives with the achievement of better clinical outcomes [
45].
Episodes with multiple medical referrals were associated with fewer sessions, probably reflecting a fractioning of episodes. The inverse relation observed for physiotherapists might reflect complex and chronic conditions requiring the involvement of several physiotherapists, or the fact that a colleague replaces the attendant physiotherapist in their absence, which is a common occurrence. In fact, our case-mix measure took insufficient account of the duration of complaints, which has been consistently associated with higher use [
2,
12,
17].
Of the total unconditional variance, the largest share was attributable at the patient level (89%). However, patient characteristics, such as health conditions, explained only 4% of this variance (Table
3), suggesting that the main determinants of variability were unmeasured.
This unexplained large variation in utilization has been found in other studies, even in those which encompass more detailed clinical information or consider only specific conditions [
38]. This degree of variation, which does not appear to be attributable to illness severity or disease characteristics, is generally viewed as a potential threat to overall quality of care. However, there must be many unmeasured factors over which the provider has little control like psychosocial variables, including pain behavior, negative beliefs or coping style. Functional status is certainly also of interest but not routinely recorded. Inappropriate factors like patient requests that yield no benefits might also be part of the unexplained variation. Studies have shown that physicians’ clinical decision-making is heavily influenced by patients’ persistent requests for various services, which themselves depend more on subjective health complaints than on objective morbidity burden as measured by a count of chronic conditions [
47]. Providers might also be reluctant to restrict the provision of physical therapy services when they do not have a satisfactory alternative to offer their patients. Finally, medical intervention can have psychologically mediated benefits, even when medically unnecessary. As a result, it would be probably insufficient to undertake basic efficiency monitoring according to the expected number of required sessions. Monitoring of chronic high users should be based on a review of the treatment plan according to the following criteria: expected number of sessions to reach defined goals, compliance with the treatment plan and improvement of functional outcomes [
45].
Data on the relationship between the intensity of physical therapy use and outcomes are scarce and contradictory. According to several studies, attending more sessions was associated with an improvement in most functional outcomes [
38]. However, poorer outcomes associated with more visits among patients suffering from back problems suggested a tendency among therapists to add appointments when outcomes did not improve [
48]. For neck pain, standard physical therapy may be only marginally better than a brief physical therapy intervention which encourages self-management [
49].
Limitations
The main limitation of the study is its reliance on routinely available data. Several important utilization drivers at the patient level were missing, such as functional disability, behavioral factors and symptom severity. Considering that variance in the number of sessions is found predominantly at the patient level, additional research should focus on the contribution of these factors (possibly also using qualitative research methods) to devise strategies to improve the adequacy of physiotherapy use. Given that psychosocial factors, such as catastrophizing, fear avoidance, and poor coping skills, are known to be important predictors of outcome among musculoskeletal conditions, interventions that deal with patients’ beliefs and attitudes might therefore help to hasten recovery [
49]. This is in line with the increasing support among physiotherapists of the biopsychosocial model of care [
50]. Finally, as no information was available on patient satisfaction or outcomes, we cannot conclude from the study that opportunities exist to reduce physical therapy use.
A second limitation concerns the studied population. Theoretically, there are three possible sources of bias: 1) during the selection of the studied population (exclusion of patients who left their insurance company in 2006); 2) in selecting first episodes (multiple episodes); 3) exclusion of episodes with a final session during the second semester of 2006. We believe that there are several reasons why such bias had no significant impact on our results. First, only 17% of insured left their insurance company in 2006. Secondly, the large size of the sample and the comparisons between the source and studied population support the representativeness of the data in terms of physical therapy practices for the whole country. Thirdly, less than 3% of episodes began in 2005 and ended during the second semester of 2006. The exclusion of certain protracted episodes should not alter the analysis of the general behavior of patients, physicians and physiotherapists.
Although the data we used were eight-years-old, there have been no cost management changes in the intervening period, and the utilization patterns found in the study can be reliably generalized to the current situation.
Competing interests
Yves Eggli is the author of the SQLape patient classification system used in the article and its promoter through the SQLape s.a.r.l. The other co-authors do not have any competing interests.
Authors’ contributions
PH worked on the design, the statistical analysis and interpretation of the results, and drafted the manuscript. YE initiated the study, supervised the preparation of data, the statistical analysis and the analysis of results, and co-drafted the manuscript. YM prepared the data, made first data analyses and helped to draft the manuscript. PT performed most of the statistical analyses. All authors have read and approved the final manuscript.