Low Back Pain in Primary Care

SPINE Volume 35, Number 18, pp 1714 –1720
©2010, Lippincott Williams & Wilkins
Low Back Pain in Primary Care
Costs of Care and Prediction of Future Health Care Utilization
Annette Becker, MD, MPH,* Heiko Held, MD,* Marcus Redaelli, MD,†
Konstantin Strauch, PhD,‡ Jean F. Chenot, MD, MPH,§ Corinna Leonhardt, PhD,¶
Stefan Keller, PhD,储 Erika Baum, MD, PhD,* Michael Pfingsten, PhD,**
Jan Hildebrandt, MD, PhD,** Heinz-Dieter Basler, PhD,¶
Michael M. Kochen, MD, MPH, PhD, FRCGP,§
and Norbert Donner-Banzhoff, MD, MHSc, PhD*
Study Design. Cost of illness study alongside a randomized controlled trial.
Objective. To describe the costs of care for patients
with low back pain (1) and to identify patient characteristics as predictors for high health care cost during a 1-year
follow-up (2).
Summary of Background Data. Low back pain (LBP) is
one of the leading causes of high health care costs in
industrialized countries (Life time prevalence, 70%). A lot
of research has been done to improve primary health care
and patients⬘ prognosis. However, the cost of health care
does not necessarily follow changes in patient outcomes.
Methods. General practitioners (n ⫽ 126) recruited
1378 patients consulting for LBP. Sociodemographic data,
pain characteristics, and LBP-related cost data were collected by interview at baseline and after 6 and 12 months.
Costs were evaluated from the societal perspective. Predictors of high cost during the subsequent year were
studied using logistic regression analysis.
Results. Mean direct and indirect costs for LBP care
are about twice as high for patients with chronic LBP
compared to acutely ill patients. Indirect costs account for
more than 52% to 54% of total costs. About 25% of direct
costs refer to therapeutic procedures and hospital or rehabilitational care. Patients with high disability and limitations in daily living show a 2- to 5-fold change for subsequent high health care costs. Depression seems to be
highly relevant for direct health care utilization.
From the *Department of General Practice, Preventive, and Rehabilitation
Medicine, University of Marburg, Marburg, Germany; †Institute of General Practice and Family Medicine, Private University Witten/Herdecke
gGmbH, Witten, Germany; ‡Institute of Medical Biometry and Epidemiology, University of Marburg, Marburg, Germany; §Department of General Practice, University of Göttingen, Göttingen, Germany; ¶Institute of
Medical Psychology, University of Marburg, Marburg, Germany; 储Department of Public Health Sciences, University of Hawaii at Manoa, Honolulu, HI; and **Department of Anaesthesiology, Pain Clinic, University
of Göttingen, Göttingen, Germany.
Acknowledgment date: October 30, 2008. Revision date: September
23, 2009. Acceptance date: September 28, 2009.
The manuscript submitted does not contain information about medical
device(s)/drug(s).
Fedral funds were received in support of this work. No benefits in any
form have been or will be received from a commercial party related
directly or indirectly to the subject of this manuscript.
Supported by the German Ministry for Education and Research
(BMBF, FKZ 01 EM 0113).
The study was approved by the institutional review boards of the Göttingen university and Marburg university, Germany.
Address correspondence and reprint requests to Annette Becker, MD,
MPH, Department of General Practice, Preventive, and Rehabilitation
Medicine, University of Marburg, Karl-von-Frisch-Str. 4, 35032 Marburg, Germany; E-mail: [email protected]
1714
Conclusion. Interventions designed to reduce high
health care costs for LBP should focus on patients with
severe LBP and depressive comorbidity. Our results add
to the economic understanding of LBP care and may give
guidance for future actions on health care improvement
and cost reduction.
Key words: back pain, primary care, cost-of-illness,
severity of low back, depression. Spine 2010;35:1714 –1720
Low back pain (LBP) poses a major health burden on
industrialized countries with a point prevalence of 15%
to 30% and a life time prevalence between 50% and
85%.1–3 About 10% of patients develop chronic pain,
which leads to early retirement and high health care
costs. LBP is 1 of the 7 most expensive illnesses in Germany.4 In 1998, about 17.4 billion Euros per year of the
total costs went to treat LBP.5 Several European cost of
illness studies underline the burden of the illness on society, showing mean total costs of €211 per person in
Sweden6 or €260 per person in the United Kingdom.7
Health care for patients with LBP is characterized by
the variability of providers offering a spectrum of therapies, which are mostly not evidence based. A lot of research has been done to improve treatment effectiveness
and efficiency. However, even though intervention studies often show mild effects on clinical outcomes, these
effects do not necessarily correlate with economic benefits. The identification and description of subgroups of
LBP patients who are likely to induce high cost of care in
the future and who would gain most by cost saving actions is mandatory.8,9 But even though the majority of
patients are seen in primary care settings,10 the distribution and factors associated with high primary health care
costs are hardly known. In fact most cost of illness studies refer to databases of communities or specialized
health care settings based on a top down approach with
often limited information on patient or illness-related
factors.6,7,11,12
The aim of our study was (1) to describe the composition of LBP-related costs of patients having consultations in general practice and (2) to identify patient- and
disease-related predictors of high health care costs during a 1-year follow-up. We refer to a secondary analysis
of patient interrogation data drawn from a clusterrandomized controlled trial in primary care.
LBP: Costs of Illness Study • Becker et al 1715
Table 1. Unit Costs and Valuation of the Most Frequent Categories Used in the Study
Description (Available Data)
Direct medical costs
Medical consultations (general practitioners,
specialists) (speciality and no. of contacts)
Therapeutic procedures (type and no. sessions)
Diagnostic procedures (type and number)
Drugs (packages)
Hospital care (d)
Rehabilitational care (d)
Unit Cost Range (€)
Estimation and Sources
6.76–100.55
Consultation charges for initiating (the first two contacts per 6 mo)
and follow-up contacts14–18 plus 10€ patient co-payment per
initiating visit with 13.1% exemption rate*
Charges for consultations and therapeutic procedures14–19*
Procedure specific charges.14–18* If necessary assuming the most
likely provider based on the specified consultation rates
Pharmacy prices for 200420
DRG or department specific daily charges (year 2000) inflated for
200421,22 plus patient co-payment
Sector specific daily charges (year 2000) for ambulatory and
inpatient care. inflated for 200421–23 plus patient co-payment
Average prices from 2001 inflated for 200421,22 and prices from
medical supply stores
3.50–5000.00
0.75–837.25
1.00–696.27
306–313/d (Daily charges)
7476.65–7480.41 (DRG)
56.24–117.46
Auxiliaries (type and number)
10.00–700.00
Indirect costs
Paid work (days on sick leave)
108.38/d
Average hourly labour cost multiplied with work hours forgone
(Human capital approach). Thirty percent reduction after 42
calender days of sick leave (change to sickness benefits from
the statutory health insurance)24
*Assumption of 10% privately insured patients.25
DRG indicates diagnose related groups.
Materials and Methods
Study Design and Data Sources
This study is a secondary analysis of a 3-armed randomized controlled guideline implementation study in primary care.13 Primary
aim was to assess the impact of a guideline-based treatment and
motivational counseling on functional capacity in patients with
LBP compared to the postal dissemination of the guideline. The
intervention consisted of intensive seminars for general practitioners on an evidence-based LBP guideline (in both intervention
arms) and of training nurses in motivational counseling to promote physical activity of patients (in 1 intervention arm). The cost
of illness data is drawn from the cross sectional sample in a bottom up approach referring to all patients who were included in the
trial at baseline. Data to analyze the prediction of costs are drawn
from follow-up data at 6 and 12 months.
At the index visit, patients were asked to fill out 2 sets of
questionnaires, one while waiting and another one at home (socio-demographic and disease-related data). One baseline telephone interview (within 4 weeks) and 2 follow-up interviews (after 6 and 12 months) were performed by specially trained study
nurses. Data on disease-related health care resource use (Table 1)
were collected during all 3 interviews. Patients were explicitly
asked only to report health care utilization, which refers to their
LBP. To shorten interviews, we had to omit nonmedical costs such
as travel and time expenses or out-of-pocket costs.
Clinical Measures
For classification of the natural history of LBP, we dichotomized the sample into acute LBP (ⱕ90 days duration/6 months)
and chronic LBP (continuous or episodic LBP ⬎90 consecutive
d/6 mo). Pain chronicity was measured by von Korff⬘s severity
of chronic pain scale.26
We used the German version of the “Fear-AvoidanceBeliefs-Questionnaire” 27–29 to measure patients’ beliefs about
“physical activity as a cause of LBP” (subscale I), and about
“work as cause of pain” (subscale II) as well as patients’ assumptions of their “probable return to work” (subscale III).
Depression was studied by using the CES-D (German version30). A score of 23 or more (range, 0 – 60) was taken as
indicative of depressive disorder.31,32 To gain data on Quality
of life, we chose the EuroQol,33 which provides a single index
value on a visual analogue scale (0 –100).
Descriptive data are shown for pain and sociodemographic
characteristics. In addition, GPs evaluated each patient regarding the presence of complicating factors (red flags: being unwell, history of trauma, suspected cancer, major neurologic
deficits, signs of rheumatic disease, osteoporosis, fever, immune deficiency, or significant trauma).
Measurement of Health Care Utilization
Consultation with health care providers (GP, specialists), diagnostic and therapeutic procedures and auxiliaries were given in
Study Sample
All patients consulting for LBP were recruited consecutively.
Inclusion criteria were LBP on the day of inclusion, age above
19, ability to read and to understand German, and written
consent. Exclusion criteria were pregnancy and isolated thoracic or cervical pain.
Setting
The study was conducted in 2 German regions (Marburg, Göttingen) in 2003 to 2004. Overall, 118 practices (126 GPs) participated (883 GPs invited, 52% did not respond, 34% GPs
refused participation). GP characteristics are shown in Table 2.
For the prediction cohort, we refer to 1211 patients out of 1378
who completed follow-up (12.1% dropouts).
Table 2. Characteristics of Participating GP (n ⴝ 126)
Sex (males)
Age (mean ⫾ SD)
Type of practice
Single
Group practice
Practice size (practice attendees per
3-months’-period)
Less than 1000
1000–1500
More than 1500
Values are n (%), unless otherwise indicated.
73 (58)
48.73 years ⫾ 6.63
69 (55)
57 (45)
45 (36)
46 (37)
32 (25)
1716 Spine • Volume 35 • Number 18 • 2010
types and numbers. Pharmaceutical information was given in
free-text answers on type, doses, and package size of the medication. Data on hospital and rehabilitation were collected as
days of care and reason for admission (e.g., surgery, pain management).
Valuation of Direct and Indirect Costs
All costs were evaluated for the year 2004 from the societal
perspective. We postulated a 10% rate of privately insured
patients,25 which was drawn from the overall number of physician consultations, diagnostic and therapeutic procedures as
well as physiotherapy contacts and priced accordingly.
Direct Costs
Physician Consultations. To price of medical outpatient
consultations (general practitioners and specialists), the number of consultations was multiplied with provider specific
charges (“Einheitlicher Bewertungsmaßstab,” medical fee
schedule for physicians14 or the “Gebührenordnung für Ärzte,”15 for the privately insured patients). Charges (given in
points) were translated into Euros using an average point score
for 2004 depending on federal state (Hessen16 and Niedersachsen17). A copayment of €10 for the first physician consultation every 3 months was added allowing a 13.1% rate of patients freed from their own contribution (Verband der
Angestellten-Krankenkassen, VdAK e.V., personal information, 2008 – 04 –21). Contacts with nonmedical practitioners
(complementary practitioners) were valuated using provider
specific charges (Gebührenhandbuch für Heilpraktiker18).
Diagnostic and Therapeutic Procedures. Costs for diagnostic und therapeutic procedures (including physiotherapy)
were calculated by multiplying the number of procedures, with
the procedure-specific charges as drawn from the Einheitlicher
Bewertungsmaßstab14 or Gebührenordnung für Ärzte.15 In
case of provider specific charges, the reported procedures were
valued assuming the most likely provider. For physiotherapy,
we accounted for patient copayment.19
Drugs. The costs for drugs were based on package prices according to the official German price list of drugs (“Rote Liste”
200420). For missing values in doses and package sizes, we assumed a small package of medium dosage for patients with acute
LBP and a big package for patients with chronic LBP. Imprecise
information on type of drugs (like “pain killer”) at follow-up was
replaced by the previously prescribed medication.
Hospital and Rehabilitational Care. Expenditures for hospital care are based on diagnose related groups21 or on department specific daily charges,22 inflated for 2004 by the sector
and land specific inflation rate (adopted from classification of
individual consumption on purpose,23 Hessen: 21.4%, Niedersachsen: 24.3%). A daily €10 patient copayment for hospital
stay was added up to a maximum of 28 d/yr.
For costs of inpatient rehabilitation we used sector specific
charges (year 2000, information from regional rehabilitation
clinics) inflated for 2004.23 Again, a €10 daily patient copayment was added up to a maximum of 28 d/yr.
Auxiliaries. Cost estimations for auxiliaries, like walking
sticks or insoles, are based on average prices recommended by
Krauth et al22 (inflated for 2004) or by personal information
from medical supply stores.
Indirect Costs
Lost Productivity/Paid Work. For an estimation of indirect
costs, the number of missed working hours were multiplied by
the average daily labor cost in Germany (human capital approach, €108.38 per day, assuming 21 working d/mo).24 In
case of prolonged sick leave (⬎42 calendar days), patients receive sickness benefits from the statutory health insurance
(70% of the gross income). We then reduced the daily labor
costs by 30%.
Statistical Analysis
Statistical analysis was performed with SPSS 17.0 (SPSS, Inc.,
Chicago, IL). Nonparametric bootstrapping (99.999 replications) was applied to present means and confidence intervals of
cost data for subgroups of acute and chronic LPB.
Health care costs during 12-months follow-up were dichotomized into high and low health care costs by defining the
upper 25% of costs as “high health care costs” (ⱖ€1723 for
total costs, ⱖ€325 for indirect costs and ⱖ€983 for direct
costs). We used logistic regression analysis in 2 blocks to model
the influence of independent prediction variables on high
health care costs. Independent variables (block 1) were chosen
according to the results from univariate analysis (P ⬍ 0.05,
Table 5). A backward variable elimination process was performed (log likelihood ratio test, P ⬍ 0.10). To account for
potential confounders, we included variables on interventional
effects and work status (block 2). The Spearman correlation
coefficient between predictors remained below 0.5 for all variables. Logistic regression analysis for prediction of high indirect costs is based on a subgroup of wage and salary earners.
We used Nagelkerkes r2 as indicator of model fit.
For sensitivity analysis, we calculated costs for sick leave
based on a friction period of 72 days and 80% of the average
daily labor cost or the sickness benefits (as used for the human
capital approach). We performed a second sensitivity analysis
by replacing missing data for total health care costs (at 6- and
12-months follow-up), according to the “last observation carried forward” procedure.
Results
Study Sample
Our cross sectional analysis refers to 1094 patients of
1378 trial participants who reported relevant baseline
data to classify their pain in acute and chronic LBP. The
prediction cohort includes 1211 patients who completed
the 12 months follow-up (12.1% drop out). Dropouts
showed no relevant differences to trial participants.13
Logistic regression analysis only refers to the subgroup
of patients with complete data on all relevant predictors.
Baseline and socio-demographic characteristics of all patients are shown in Table 3.
Costs of Care
Distribution of costs, stratified for subgroups of acute
and chronic patients with LBP is shown in Table 4. Indirect cost account for approximately 54% of all health
care cost irrespective of disease duration.
LBP: Costs of Illness Study • Becker et al 1717
Table 3. Baseline Characteristics of the Study Sample
(n ⴝ 1378)
Demographic Characteristics
Age
Gender (males)
Employment status
Working full or part-time
Keeping house
Retired
Unemployed
Other
Net income
ⱕ1000€
1001–2000€
2001–3000€
⬎3000€
Characteristics of LBP
Functional capacity
Pain intensity (Numeric pain
scale: 0–10)
Days of pain in the previous year
Duration of the current episode
Quality of life (Visual analogue
scale: 0–100)
Chronic Pain grade* (n (%))
Low disability/low intensity
Low disability/high intensity
High disability/moderately
limiting
High disability/severely limiting
Red flags
Generally unwell
Neurological deficits
History of cancer
Chronic inflammatory disease
Osteoporosis with danger of
fracture
Fever
Immune deficiency
Severe trauma
Activity (Metabolic equivalent
hours/wk)†
Job satisfaction (Numeric pain
scale: 0–10)
Depression score
Fear avoidance beliefs score
Score I (physical activity ⫽
cause of pain)
Score II (work ⫽ cause of
pain)
Score III (prognostic job)
Mean
(Range. SD)
n (%)
n (%)
N (%)
48.85 (20–91. 13.7)
574 (41.65)
925 (67.1)
120 (8.7)
228 (16.6)
55 (4.0)
50 (3.6)
199 (14.4)
478 (34.7)
288 (20.9)
120 (8.7)
Mean (SD)
Mean (SD)
67.45 (21.43)
53.87 (17.03)
Mean (SD)
Mean (SD)
Mean (SD)
104.87 (128.83)
25.79 (62.93)
57.05 (19.27)
N (%)
N (%)
303 (22.0)
258 (18.7)
260 (18.9)
164 (11.9)
28 (2.0)
20 (1.5)
22 (1.6)
32 (2.3)
29 (2.1)
2 (0.1)
0
8 (0.6)
Mean (SD)
17.26 (20.25)
Mean (SD)
6.10 (2.46)
Mean (SD)
15.36 (9.38)
Mean (SD)
17.59 (6.80)
13.46 (8.60)
8.91 (8.38)
*More than 20% missing.
†Outlier corrected by “winsorizing”: values ⱖ98th percentile were equated to
this value.
SD indicates standard deviation; LBP, low back pain.
Health Care Utilization
Apart from the index visit, most patients had seen their
GP at least once during the 6 months before the day of
recruitment (n ⫽ 1266, 95.7%). The mean consultation
rate was 4.8 (s ⫽ 7.75). Patients who went to see their GP
at least 5 times (26% of all patients), account for 70% of
all GP consultations. Specialists were seen by 41% (n ⫽
548) of patients. Patients who went to see them at least
twice (26%) account for 92% of all specialist visits.
More use of radiologic procedures (ⱖ1 test) occurred in
32% of all patients. A third of all patients (n ⫽ 430,
32.5%) were on sick leave for 8 days on average (s ⫽
25.49); high utilizer (ⱖ5 days) accounted for 98% of all
days of sick leave (n ⫽ 9372 in total). About 20% of the
patients had been submitted to hospital care with a total
number of 457 days in hospital (range, 1– 41 days), 4%
of all patients (n ⫽ 54) participated in rehabilitative care
(in total 1320 days; range, 1– 42 days). NSAIDs were the
most frequently used drugs in patients with LBP (50.3%
of patients) followed by opioids (13%), muscle relaxants
(6.3%), and analgesics (6.8%).
Prediction of High Health Care Cost During the
Following Year
The distribution of cost during follow-up was similar to
their composition at baseline, with indirect cost accounting for 55% of total costs. Again therapeutic procedures
and hospital care had the highest share of direct cost.
Table 5 presents univariate associations of potential predictors and high cost of care during the following year.
Results from multivariate logistic regression analysis
are shown in Table 6. The models predicted 80% of high
total cost, 78% of high direct cost, and 68% of high
indirect cost.
Sensitivity Analysis
At baseline indirect cost valued by the friction cost approach amount to €410.98 per patient with acute LBP
(95% CI: 345.6 – 492.4) and to €577.44 (95% CI:
453.6 –731.8) per patient with chronic LBP. Logistic regression analysis on the prediction of high indirect cost
(ⱖ€606) revealed the same predictors as in the initial
model except for LBP severity grade III (high disability,
moderately limiting).
We found no effective changes in the logistic regression analysis for total costs after replacement of missing
values (LVCF, cut of for high total costs: ⱖ€1829).
Discussion
We performed a cost-of-illness study based on data from
a cluster randomized trial in primary care. Mean costs
for chronic LBP patients are about twice as high as for
acutely ill patients. Sick-leave accounts for about 52% to
54% of total costs. Almost 25% of direct costs refer to
therapeutic procedures and hospital or rehabilitational
care. Back pain severity and depression are the most important predictors for future costs, whereas fear avoidance beliefs and radiation of pain to the leg do add to
subsequent costs, but they are of minor importance.
To our knowledge, this is the first cost of illness study
in the field of LBP, which includes cohort data on pain,
patient characteristics, and a reasonable observation period in the context of German general practice. We found
one comparable German survey on the costs of LBP evaluated by a bottom up approach by Wenig et al.34 Valuation of costs in this study is based on the same recommendations as in our analysis.22 Similar to our study,
they found a proportion of indirect costs of 54% in a
sample of 5650 LBP patients. Total costs were estimated
to be €1322 per year, which is about twice the total costs
1718 Spine • Volume 35 • Number 18 • 2010
Table 4. Costs of Low Back Pain During 6 Month Classified by Duration of Pain (Baseline Data)
Direct costs
Physician consultations
Drugs
Diagnostic procedures
Therapeutic procedures
Auxiliaries
Hospital care
Rehabilitational care
Indirect costs
Total costs
Acute LBP
Chronic LBP
n ⫽ 643 (58%)
n ⫽ 451 (41%)
(Mean (95% Confidence
Interval))
% of Total
Costs
(Mean 关95% Confidence
Interval兴)
% of Total
Costs
456.49 (365.7–587.5)
58.85 (52.15–71.69)
16.74 (14.41–22.51)
59.41 (45.49–77.41)
123.74 (107.1–146.9)
10.14 (6.47–16.81)
120.38 (65.4–206.0)
67.23 (38.58–110.72)
545.49 (451.5–680.2)
1001.97 (847.0–1208.0)
45.6
5.9
1.7
5.9
12.4
1.0
12.0
6.7
54.4
100
853.81 (713.6–1044.7)
98.66 (81.75–130.40)
61.05 (46.66–85.82)
106.14 (81.6–141.1)
255.69 (223.2–297.0)
27.05 (19.65–37.13)
137.38 (72.1–245.5)
167.84 (111.6–246.3)
936.00 (708.1–1236.0)
1789.81 (1470.0–2202.0)
47.7
5.5
3.4
5.9
14.3
1.5
7.7
9.4
52.3
100
Means and 95%-confidence intervals are drawn from Bootstrap analysis.
LBP indicates low back pain.
estimated in our study and which is possibly due to the
different study settings.
A recent study by Martin et al35 found increased
spine-related per-user expenditures going back to increased expenditures for inpatient hospitalization, prescription medication, and emergency department visits.
The authors discuss the contribution of an increasing use
of imaging, surgical technology, etc., which is in line with
our findings. However, we were able to test for the influence of clinical data, which showed LBP severity and
depression to be the most important predictors for future
costs, which is different from Martin⬘s study. Similar
analyses based on cross sectional data underline this observed association (measured with von Korff chronic
pain grade or the Roland and Morris scale).6,34,36 In a
sample of consecutive LBP patients of an HMO primarycare clinic, Engel et al36 confirmed increasing chronic
pain grade to be the strongest predictor of high LBP
costs, followed by disc disorder/sciatica and increasing
pain persistence. Depression was the strongest predictor
of total health care costs which is why the authors hypothesize that physicians initiate expensive health services if they are confronted with dysfunction and chronicity or mood disorders.
None of the above-mentioned studies have so far examined the impact of high fear avoidance beliefs on subsequent health care costs. The patients’ own prognosis about
returning to work adds significantly to the prediction of
future costs. Obviously long-term consequences of catastrophic misinterpretations of pain initiate a vicious circle
Table 5. Univariate Association of Potential Predictors of High Health Care Costs Within the Following Year
(Follow-up Cost Data)
Crude OR (95% CI)
Predictor
Sex (0 ⫽ men, 1 ⫽ women)
Age
Paid work
Applying for pension
Quality of life (VAS: 1–100)
Depression (score ⬎23 ⫽ 1)
FABQ
Activity as cause of pain
Work as cause of pain
Prognosis for work
Severity of disease
Low disability-low intensity
Low disability-high intensity
High disability-moderately limiting
High disability-severely limiting
Days of pain in 12 mo
Radiation of pain
Duration of current episode
Red flags
High Total Costs (ⱖ1723€)
High Indirect Costs (ⱖ325€)
High Direct Costs (ⱖ983€)
1.060 (0.812–1.382)
1.00 (0.989–1.010)
1.201 (0.892–1.616)
2.070 (1.316–3.256)*
0.981 (0.974–0.988)*
1.041 (1.025–1.056)*
1.769 (1.374–2.278)*
0.960 (0.949–0.971)*
—
1.055 (0.652–1.706)*
0.990 (0.983–0.996)*
1.015 (1.001–1.030)*
0.613 (0.465–0.806)*
1.012 (1.001–1.022)*
0.65 (0.49–0.86)
1.847 (1.172–2.910)*
0.984 (0.977–0.991)*
1.038 (1.022–1.053)*
1.047 (1.024–1.071)*
1.069 (1.049–1.088)*
1.081 (1.062–1.101)*
1.040 (1.018–1.062)*
1.053 (1.035–1.071)*
1.057 (1.040–1.075)*
1.038 (1.016–1.061)*
1.045 (1.027–1.063)*
1.063 (1.045–1.081)*
—*
1.17 (0.71–1.92)*
3.18 (2.05–4.93)*
8.47 (5.21–13.76)*
1.002 (1.001–1.003)*
2.155 (1.584–2.932)*
1.003 (1.001–1.005)
1.448 (0.935–2.242)*
—*
1.66 (1.01–2.73)*
3.24 (2.01–5.24)*
8.30 (4.38–15.74)*
0.999 (0.998–1.000)*
1.21 (1.03–1.41)*
1.00 (1.00–1.00)
0.83 (0.43–1.61)*
—*
1.45 (0.90–2.34)*
3.18 (2.05–4.93)*
7.50 (4.62–12.16)*
1.003 (1.001–1.004)*
1.55 (1.35–1.78)*
1.00 (1.00–1.01)
1.88 (1.23–2.88)*
*Variables included in the logistic regression model block 1 with backward selection.
CI indicates confidence intervals; OR, odd ratio; FABQ, Fear-Avoidance-Beliefs-Questionnaire.
LBP: Costs of Illness Study • Becker et al 1719
Table 6. Results From Logistic Regression Analysis (Stepwise Selection, Follow-up Cost Data)
Adjusted OR (95% CI)
Predictor
Sex (female ⫽ 1, male ⫽ 2)
Radiation to the leg
Days of pain in 12 mo
Depression (score ⬎23)
FABQ–Prognosis for work
FABQ–Activity as cause of pain
Severity of disease
Low disability low intensity
Low disability-high intensity
High disability-moderately limiting
High disability-severely limiting
Paid work
Study arm
Nagelkerkes r2
High Total Costs (ⱖ1723€)
n ⫽ 577
High Indirect Costs (ⱖ325€)
n ⫽ 380
High Direct Costs (ⱖ983€)
n ⫽ 576
0.65 (0.42–1.01)
1.27 (1.03–1.58)
1.96 (1.18–3.24)
1.06 (1.03–1.09)
1.07 (1.03–1.10)
1.05 (1.01–1.09)
—
1.23 (0.65–2.34)
2.86 (1.57 ⫺ 5.23)
7.47 (3.66–15.25)
2.46 (1.48–4.08)
0.90 (0.69–1.17)
0.28
—
1.36 (0.78–2.38)
2.25 (1.27–4.01)
3.83 (1.71–8.57)
—
1.01 (0.79–1.38)
0.22
1.81 (1.11–2.98)
1.04 (1.01–1.07)
—
1.42 (0.76–2.66)
2.83 (1.54–5.19)
4.78 (2.36–9.69)
0.90 (0.58–1.40)
1.01 (0.78–1.31)
0.23
OR indicates odd ration; CI, confidence intervals FABQ, Fear-Avoidance-Beliefs-Questionnaire.
of pain-related fear, avoidance of physical activity and, finally, the emergence of a “disuse syndrome” as a consequence of long-lasting avoidance behavior.37,38 However,
their influence on subsequent cost development is rather
small and has to be validated in future studies.
Limitations
The results of our study are based on a secondary analysis of a randomized controlled trial. Even though trial
results are negative,13 we controlled for confounding by
study arm. However, a selection bias may be present,
because physicians participating in research studies may
be more interested in evidence-based care than nonparticipants. It remains unclear in which direction this bias
would change the observed associations. The overall inclusion rate of the RCT was 44%, which makes selection
bias on patient level likely as well. One of the key issues
of the implemented guideline is the early activation of
LBP patients. Trial participants may have felt less disabled by the pain, and may have had a higher level of
physical activity than LBP patients in general. This bias
would dilute the observed associations.
Another limitation of the study is its reliance on selfreport instruments. Recall bias, information bias (e.g., by
patients who are unable to distinguish between LBP-related
procedures and others) or social desirability bias cannot be
excluded. Under- or overestimation of costs are possible.
We included the Euroqol as a measurement of quality of
life. However, we did not adjust for potential confounding
by comorbidity which may lead to misclassification of LBP
related expenditures and—most likely— overestimation of
LBP-related health care utilization or which may influence
our logistic regression model.
We studied the costs of LBP in primary care from a
societal perspective. Total costs are most likely underestimated, because we had to restrict interviews to key
issues for practical reasons. For a valuation of physician
contacts, we followed the recommendations from
Krauth et al.22 These authors based their calculation on
assumptions about standard operating procedures instead of on detailed patient questioning which only allows an approximation of costs and may result in their
over- or underestimation.
Conclusion
Current studies underline the need for identification of
LBP subgroups in view of an efficient tailoring of cost
reduction strategies. As shown in our study severity of
LBP and depression are crucial variables for prediction
of future health care costs. Future studies will have to
corroborate these findings or to add further information
about determinants of increased cost. Increased knowledge will serve to assign resources to cost limiting procedures and to facilitate decisions on health care priorities.
Key Points
●
●
●
●
●
LBP is one of the most expensive illnesses in industrialized countries. Defining subgroups of patients who are likely to account for future high
health care costs is crucial.
We present a cost-of-illness estimate based on data
drawn from a randomized controlled trial in primary care. The aim is to study the pattern of health
care utilization and potential predictors of high
health care costs during a 12-months follow-up.
Mean direct and indirect costs for LBP care are
about twice as high for patients with chronic LBP
than for patients with acute LBP.
Severity (high disability and moderate to severe
limitations in daily living) and depression are the
most important predictors of future costs.
Prioritization efforts in LBP care, which aim to
achieve cost reduction, should focus on patients
suffering from severe back pain (von Korff III and
IV) as well as depressive comorbidity.
1720 Spine • Volume 35 • Number 18 • 2010
Acknowledgments
The authors thank all patients, practicing nurses, and
general practitioners who participated in the study as
well as the Scientific Institute of the local health care fund
(Wido) for their support in the valuation of costs.
References
1. Cassidy JD, Carroll LJ, Cote P. The Saskatchewan health and back pain
survey. The prevalence of low back pain and related disability in Saskatchewan adults. Spine 1998;23:1860 – 6.
2. Raspe HH, Kohlmann T. Die aktuelle Rückenschmerzepidemie [The current
backache epidemic]. Ther Umsch 1994;51:367–74.
3. Papageorgiou AC, Croft PR, Ferry S, et al. Estimating the prevalence of low
back pain in the general population. Evidence from the South Manchester
Back Pain Survey. Spine 1995;20:1889 –94.
4. Statistisches Bundesamt. Krankheitskosten je Einwohner in € (Costs of illness
per resident in €) [Statistisches Bundesamt web site]. 2008. Available at: http://
www.destatis.de/jetspeed/portal/cms/Sites/destatis/Internet/DE/Navigation/
Statistiken/Gesundheit/Krankheitskosten/Krankheitskosten.psml . Accessed
September 22, 2009.
5. Bolten W, Kempel-Waibel A, Pforringer W. Analyse der Krankheitskosten
bei Rückenschmerzen [Analysis of the cost of illness in backache]. Med Klin
1998;93:388 –93.
6. Ekman M, Johnell O, Lidgren L. The economic cost of low back pain in
Sweden in 2001. Acta Orthop 2005;76:275– 84.
7. Maniadakis N, Gray A. The economic burden of back pain in the United
Kingdom. Pain 2000;84:95–103.
8. Gandjour A, Telzerow A, Lauterbach KW. European comparison of costs
and quality in the treatment of acute back pain. Spine 2005;30:969 –75.
9. Tarricone R. Cost-of-illness analysis. What room in health economics?
Health Policy 2006;77:51– 63.
10. Deyo RA, Tsui-Wu YJ. Descriptive epidemiology of low-back pain and its
related medical care in the United States. Spine 1987;12:264 – 8.
11. van Tulder MW, Koes BW, Bouter LM. A cost-of-illness study of back pain
in The Netherlands. Pain 1995;62:233– 40.
12. Maetzel A, Li L. The economic burden of low back pain: a review of studies
published between 1996 and 2001. Best Pract Res Clin Rheumatol 2002;16:
23–30.
13. Becker A, Leonhardt C, Kochen MM, et al. Effects of two guideline implementation strategies on patient outcomes in primary care: a cluster randomized controlled trial. Spine 2008;33:473– 80.
14. Kassenärztliche Bundesvereinigung. Einheitlicher Bewertungsmaßstab
Stand 1 [Uniform Physicians⬘ Fee Scale]. Köln, Germany: Deutscher ÄrzteVerlag GmbH; 2005.
15. Bundesministerium für Gesundheit. Gebührenordnung für Ärzte (GOÄ)
[Physicians⬘ fee schedule] [Bundesministerium für Gesundheit web site].
2008. Available at: http://www.bmg.bund.de/cln_091/nn_1168248/Shared
Docs/Downloads/DE/Neu/Gesundheitsberufe__Geb_C3_BChrenordnung-_
C3_84rzte,templateId⫽raw,property⫽publicationFile.pdf/Gesundheitsberufe_
Geb%C3%BChrenordnung-%C3%84rzte.pdf. Accessed September 23, 2009.
16. Kassenärztliche Vereinigung Hessen. Info doc 2004, 2005 (Offizielle Mitteilungen der KV Hessen) [Official information of the KV Hessen] [Kassenärztliche Vereinigung Hessen web site]. 2008. Available at: https://
mitglieder.kvhessen.de/Mitglieder_intern-p-33673/Anmeldung.html.
Accessed September 23, 2009.
17. Kassenärztliche Vereinigung Niedersachsen. Honorarstatistik [Physicians⬘
fee statistics] [Kassenärztliche Vereinigung Niedersachsen web site]. 2008.
Available at: http://www.kvn.de/kvn/content/internet/kvs/hauptgeschaeftsstelle/
04/04/026/content_html?stelle⫽hauptgeschaeftsstelle&idd3⫽04&idd4⫽04&
idd5⫽026. Accessed September 23, 2009.
18. Die Deutschen Heilpraktikerverbände. Gebührenverzeichnis für Heilpraktiker (GebüH) [Complementary practitioners⬘ fees] [Verband Deutscher Heilpraktiker e.V. web site]. 2009. Available at: http://www.heilpraktiker-vdh.
de/assets/downloads/pdf/Gebuehren.pdf. Accessed September 23, 2009.
19. VDAK (Verband der Angestellten-Krankenkassen e.V.), AEV ArbeiterErsatzkassen-Verband e. V. Vergütungsliste für Krankengymnastische/
20.
21.
22.
23.
24.
25.
26.
27.
28.
29.
30.
31.
32.
33.
34.
35.
36.
37.
38.
physiotherapeutische Leistungen, Massagen und medizinische Bäder [Reimbursement list for physiotherapeutic services, massage and medical
washings] [VDAK web site]. 2006. Available at: http://www.vdak.de/LVen/
SAH/Vertragspartner/Sonstige_Vertragspartner/Physioth_Krankengym_
Masseure/Verguetungsliste_Physiotherapie_Ost__1.4.06.pdf. Accessed September 23, 2009.
Bundesverband der pharmazeutischen Industrie. Rote Liste [Red List].
Weinheim, Germany: Rote Liste Verlag; 2004.
AOK-Bundesverband. Landesbasisfallwerte [base rates according to the federal states] [AOK web site]. 2005. Available at: http://www.aok-gesundheits
partner.de/bundesverband/krankenhaus/budgetverhandlung/landesbasisfallwert/
2005/. Accessed September 23, 2009.
Krauth C, Hessel F, Hansmeier T, et al. Empirische Bewertungssätze in der
gesundheitsökonomischen Evaluation– ein Vorschlag der AG Methoden der
gesundheitsökonomischen Evaluation (AG MEG) [Empirical standard costs
for health economic evaluation in Germany—a proposal by the working
group on methods in health economic evaluation]. Gesundheitswesen 2005;
67:736 – 46.
Statistisches Bundesamt. Verbraucherpreisindices für Deutschland [Official
Price Index, Germany] Wiesbaden, Germany: Statistisches Bundesamt,
Fachserie; 2007:17(R7).
Boss A, Elendner T. Steuerreform und Lohnsteueraufkommen in Deutschland–Simulationen auf Basis der Lohnsteuerstatistik, Kieler Arbeitspapier
1185 [Tax reform and wage tax in Germany]. Die Weltwirtschaft 2003:
368 – 87.
Wissenschaftliches Institut der PKV. Leistungsausgaben und Häufigkeitsverteilung von Honorarziffern in der ambulanten ärztlichen Versorgung
2005/2006 [Costs and distribution of charges in primary care] [Verband der
privaten Krankenversicherung e.V. (PKV) web site]. 2008. Available at: http://
www.wip-pkv.de/uploads/tx_nppresscenter/Ambulant_Freq_Leistungen_05_06.
pdf. Accessed September 23, 2009.
Von Korff M, Ormel J, Keefe FJ, et al. Grading the severity of chronic pain.
Pain 1992;50:133– 49.
Pfingsten M, Kroner-Herwig B, Leibing E, et al. Validation of the German
version of the Fear-Avoidance Beliefs Questionnaire (FABQ). Eur J Pain
2000;4:259 – 66.
Pfingsten M. Angstvermeidungs-Überzeugungen bei Rückenschmerzen:
Gütekriterien und prognostische Relevanz des FABQ [Fear avoidance beliefs
in patients with back pain. Psychometric properties of the German version of
the FABQ]. Schmerz 2004;18:17–27.
Waddell G, Newton M, Henderson I, et al. A Fear-Avoidance Beliefs Questionnaire (FABQ) and the role of fear-avoidance beliefs in chronic low back
pain and disability. Pain 1993;52:157– 68.
Kohlmann T, Gerbershagen HU. CESD-D German version [DRK Krankenhausgesellschaft mbH Rheinland-Pfalz web site]. 2009. Available at: http://
www.drk-schmerz-zentrum.de/documents/infos/pdf/CES-D.pdf. Accessed
September 15, 2009.
Nagel B, Gerbershagen HU, Lindena G, et al. Entwicklung und empirische
Überprüfung des Deutschen Schmerzfragebogens der DGSS [Development
and evaluation of the multidimensional German pain questionnaire].
Schmerz 2002;16:263–70.
Geisser ME, Roth RS, Robinson ME. Assessing depression among persons
with chronic pain using the Center for Epidemiological Studies-Depression
Scale and the Beck Depression Inventory: a comparative analysis. Clin J Pain
1997;13:163–70.
Brooks R. EuroQol: The current state of play. Health Policy 1996;37:53–72.
Wenig CM, Schmidt CO, Kohlmann T, et al. Costs of back pain in Germany.
Eur J Pain 2009;13:280 – 6.
Martin BI, Turner JA, Mirza SK, et al. Trends in health care expenditures,
utilization, and health status among US adults with spine problems, 1997–
2006. Spine 2009;34:2077– 84.
Engel CC, Von Korff M, Katon WJ. Back pain in primary care: predictors of
high health-care costs. Pain 1996;65:197–204.
Verbunt JA, Seelen HA, Vlaeyen JW, et al. Disuse and deconditioning in
chronic low back pain: concepts and hypotheses on contributing mechanisms. Eur J Pain 2003;7:9 –21.
Leeuw M, Goossens ME, Linton SJ, et al. The fear-avoidance model of
musculoskeletal pain: current state of scientific evidence. J Behav Med 2007;
30:77–94.