| Literature DB >> 33974661 |
Dawit T Zemedikun1, Jesse Kigozi1, Gwenllian Wynne-Jones2, Alessandra Guariglia3, Tracy Roberts1.
Abstract
BACKGROUND: Back pain is a common and costly health problem worldwide. There is yet a lack of consistent methodologies to estimate the economic burden of back pain to society.Entities:
Year: 2021 PMID: 33974661 PMCID: PMC8112645 DOI: 10.1371/journal.pone.0251406
Source DB: PubMed Journal: PLoS One ISSN: 1932-6203 Impact factor: 3.240
Categorisation process for selection of studies for review.
| A. The study reports primary or secondary research on the economic burden of back pain and provides substantial cost data. |
| B. The study discusses the cost of back pain and provides estimates of some aspects of COI or components of direct or indirect costs. |
| C. The study provides useful information on assessing the economic burden of back pain but does not entirely fall into either A or B. (e.g. methodological studies on COI without reporting direct or indirect costs estimates). |
| D. The study discusses general aspects of the economic impact of back pain but provides little or no data on direct or indirect costs (e.g. economic evaluations). |
| E. Full text of the study is not available (abstracts, conference proceedings). |
| F. The study does not have any relevance to the economic burden of back pain. |
| 1. Cost of illness (COI) analysis studies (direct or indirect cost) |
| 2. Other cost studies |
| 3. Description of methods used in assessing cost of back pain |
| 4. Private out of pocket expenditure |
| 5. Economic evaluations |
| 6. Review articles without new data |
| 7. Not relevant for economic burden of back pain. |
Fig 1PRISMA diagram of literature search and study selection.
Summary of the main characteristics of the included studies.
| Lead author, year | Country/perspective | Population | Study Design | Main data source, year of data | Back pain case definition | Direct cost estimation | Indirect cost approach |
|---|---|---|---|---|---|---|---|
| Walker, 2003 | Australia/Societal | National | R, PB | Australian adult LBP prevalence survey, 2001 | Diagnostic code | Top-down | Human capital & friction cost |
| van Zundert, 2005 | Belgium/Societal | National | R, PB | IDEWE (workers welfare body), 1999 | Other/non-specific | Top-down | n/s |
| Coyte, 1998 | Canada/Societal | National | R, PB | Ontario Health Survey data, 1990–94 | Diagnostic code | Top-down | Human capital |
| Hemmila, 2002 | Finland/Societal | Regional | R, PB | Social Insurance Institution files, and patient records, 1994 | Self-reported | Bottom-up | Human capital |
| Depont, 2010 | France/Healthcare provider | National | R, PB | Surveys/questionnaires, 2001 | Self-reported | Bottom-up | n/a |
| Muller-Schwefe, 2011 | Germany/Insurer | Health insurer ≈ 5.2 million members | R, IB | German statutory health insurance fund (DAK) claims data, 2006 | Diagnostic code | Bottom-up | n/a |
| Wenig, 2009 | Germany/Societal | National | R, PB | Postal survey by German Back Pain Research Network (GBPRN), 2003–06 | Self-reported | Bottom-up | Human capital |
| Becker, 2010 | Germany/Societal | Regional | P, PB | Cross sectional sample from an RCT, 2004 | Self-reported | Bottom-up | Human capital |
| Watson, 1998 | Isle of Jersey/Societal | National | P, PB | Social Security database, 1994 | Other/non-specific | n/a | n/s |
| Montgomery, 2017 | Japan/Societal | National | R, PB | Japan National Health & Wellbeing Survey (NHWS), 2011 | Self-reported & diagnosed | Bottom-up | Human capital |
| Itoh, 2013 | Japan/Societal | National | R, PB | Survey of Medical Care Activities in Public Health Insurance, 2011 | Diagnostic code | Bottom-up | n/a |
| Shinohara, 1998 | Japan/Insurer | National | R, PB | Labour Standards Inspection Office claims database, 1991–95 | Other/non-specific | Bottom-up | n/s |
| Kim, 2005 | Korea/Insurer | National | R, IB | Korea Labor Welfare Corporation, 1997 | Other/non-specific | n/s | n/a |
| Olafsson, 2018 | Sweden/Societal | Regional | R, PB | Administrative database VEGA, 2008–11 | Diagnostic code | Bottom-up | Human capital |
| Ekman, 2005 (b) | Sweden/Societal | Regional | R, PB | Surveys/questionnaires, 2002 | Self-reported | Bottom-up | Human capital |
| Ekman, 2005 (a) | Sweden/Societal | National | R, PB | Survey and registry data, 2001 | Diagnostic code | Top-down | human capital |
| Hansson, 2005 | Sweden/Societal | Regional | P, PB | Prospectively entered diaries and questionnaires, 1994–95 | Diagnostic code | Bottom-up | Human capital |
| Jonsson, 2000 | Sweden/Societal | National | R, PB, IB | National Board of Health and Welfare’s register, 1994 | Diagnostic code | Top-down | Human capital |
| Wieser, 2011 | Switzerland/Societal | Regional | R, PB | Large population-based survey, 2005 | Self-reported | Bottom-up | Human capital & friction cost |
| Lambeek, 2011 | Netherlands/Societal | National | R, PB | National registries and authorities, 2007 | Diagnostic code | Top-down | Human capital |
| Boonen, 2005 | Netherlands /Societal | National | P, IB | Cost diaries from three cohorts, 2002 | Self-reported | Bottom-up | Friction cost |
| van Tulder, 1995 | Netherlands/Societal | National | R, PB | Survey and registry data, 1991 | Diagnostic code | Top-down | Human capital |
| Hutubessy, 1999 | Netherlands/Societal | National | R, PB | Social Insurance Council data, 1991 | Diagnostic code | n/a | Human capital & friction cost |
| Alonso-Garcia, 2000 | Spain/Societal | National | R, PB | National Health Survey of 2017 (NHS 2017), 2017 | Self-reported | Bottom-up | Human capital |
| Yumusakhuylu, 2018 | Turkey/Societal | National | R, n/s | Surveys/questionnaires, 2011 | Other/non-specific | Bottom-up | Human capital |
| Icatasiotlu, 2015 | Turkey/Societal | National | R, PB | Surveys/questionnaires, 2013 | Self-reported | Bottom-up | Human capital |
| Hong, 2012 | UK/Health-care provider | National | CC, PB | UK General Practice Research Database (GPRD), 2007–09 | Diagnostic code | Bottom-up | n/a |
| Maniadakis, 2000 | UK/Societal | National | R, PB | Office of Population Censuses and Surveys (OPCS), 1997 | Diagnostic code | Top-down | Human capital & Friction cost |
| Kim, 2019 | USA/Insurer | Health insurer ≈ 75 million members | R, PB | MarketScan Commercial Claims Database, 2007–16 | Diagnostic code | Bottom-up | n/a |
| Smith, 2013 | USA/Societal | National | R, PB | Medical Expenditure Panel Survey (MEPS), 2000–07 | Diagnostic code | Bottom-up | n/a |
| Martin, 2008 | USA/Societal | National | CC, PB | Medical Expenditure Panel Survey (MEPS), 2005 | Diagnostic code | Bottom-up | n/a |
| Mehra, 2012 | USA/Insurer | Large regional health insurer | CC, PB | PharMetrics IMS LifeLink claims database, 2006–08 | Diagnostic code | Bottom-up | n/a |
| Gore, 2012 | USA/Insurer | Health insurer ≈ 62 million members | CC, IB | LifeLink Health Plan Claims Database, 2008 | Diagnostic code | Bottom-up | n/a |
| Ricci, 2006 | USA/Societal | National | R, PB | Caremark American Productivity Audit (telephone survey), 2003–04 | Self-reported | n/a | Human capital |
| Stewart, 2003 | USA/Societal | National | R, PB | American Productivity Audit (telephone survey), 2001–02 | Other/non-specific | n/a | Human capital |
| Lind, 2005 | USA/Insurer | Two Washington State companies | R, PB | Health insurance claims data from insurance companies, 2002 | Diagnostic code | Bottom-up | n/a |
| Mapel, 2004 | USA/Insurer | Health insurer with 240,000 members | CC, PB | Lovelace Health Plan (LHP) administrative databases, 2000–01 | Diagnostic code | Bottom-up | n/a |
| Vogt, 2005 | USA/Insurer | Health insurer with 255,958 members | R, PB | UPMC Health Plan claims database, 2001 | Diagnostic code | Bottom-up | n/a |
| Ritzwoller, 2006 | USA/Insurer | Health insurer with > 410,000 members | R, IB | Keiser Permanente Colorado (KPCO) claims database, 1996–2001 | Diagnostic code | Bottom-up | n/a |
| Luo, 2004 | USA/Societal | National | CC, PB | Medical Expenditure Panel Survey (MEPS), 1998 | Diagnostic code | Bottom-up | n/a |
| Rizzo, 1998 | USA/Societal | National | R, PB | National Medical Care Expenditure Survey (NMES), 1987 | self-reported | n/a | Human capital |
| Hashemi, 1998 | USA/Insurer | Insurer with 10% of WC market | R, IB | Claims data from a large insurer, 1996 | Self-reported | n/a | n/s |
| Guo, 1999 | USA/Employer | US industries | R, PB | National Health Interview Survey (NHIS), 1988 | Self-reported | n/a | n/s |
| Williams, 1998 | USA/Insurer | Regional WC insurer | R, n/s | Detailed Claim Information (DCI) database, 1988–92 | Diagnostic code | Bottom-up | n/s |
| Gustafson, 1995 | USA/Employer | Four participating hospitals | P, n/s | Employer records, 1991–92 | Self-reported | Bottom-up | n/s |
n/a = not applicable, n/s = non-specific, P = prospective, R = retrospective, PB = prevalence based, IB = incidence based, CC = matched case-control
LBP = low back pain, RCT = randomised controlled trial, WC = workers compensation, UPMC = University of Pittsburgh Medical Centre
Main concepts and approaches used in COI studies.
| Type of approaches/Concepts | Description |
|---|---|
| The perspective of the analysis indicates who bears the costs, which in turn determines which costs are to be included in the analysis. | |
Fig 2Allocation of direct costs in COI studies of back pain.
Legend: The figure illustrates the allocation of direct costs in studies that reported on all three major costs components (inpatient, outpatient, and pharmaceutical costs) of direct costs.
Fig 3Allocation of indirect costs in COI studies of back pain.
Legend: The figure illustrates the allocation of indirect costs in studies that reported on at least two of the three major costs components (absenteeism, presenteeism, and early retirement costs) of indirect costs.
National estimates of direct, indirect, and total costs of back pain.
| Ref. | Country | Population (million) | Direct costs | Indirect costs | Total costs | |||||
|---|---|---|---|---|---|---|---|---|---|---|
| National (million $) | % | Per capita | National (million $) | % | Per capita | National (million $) | Per capita | |||
| [ | Sweden | 8.9 | 42 | 16 | 4.7 | 217 | 84 | 24.4 | 259 | 29.1 |
| [ | Sweden | 8.9 | 61 | 15 | 6.9 | 346 | 85 | 38.9 | 407 | 45.7 |
| [ | Sweden | 9.4 | 261 | 33 | 27.7 | 527 | 67 | 56.0 | 788 | 83.7 |
| [ | Belgium | 10.2 | 302 | 16 | 29.5 | 1,603 | 84 | 156.7 | 1,905 | 186.2 |
| [ | Netherlands | 16.4 | 622 | 13 | 38.0 | 4,014 | 87 | 245.1 | 4,636 | 283.0 |
| [ | Spain | 46.5 | 3,380 | 25 | 72.6 | 9,878 | 75 | 212.3 | 13,257 | 284.9 |
| [ | Japan | 127.8 | 26,699 | 69 | 208.9 | 11,866 | 31 | 92.8 | 38,565 | 301.8 |
| [ | Canada | 29.1 | 832 | 8.3 | 28.6 | 9,209 | 92 | 316.4 | 10,041 | 344.9 |
| [ | UK | 58.5 | 3,363 | 13 | 57.5 | 22,015 | 87 | 86.7 | 25,378 | 433.9 |
| 58.5 | 3,363 | 25 | 57.5 | 75 | 177.1 | 13,721 | 234.6 | |||
| [ | Sweden | 8.8 | 130 | 3.3 | 14.8 | 3,799 | 97 | 432.7 | 3,929 | 447.5 |
| [ | Australia | 19.4 | 1,058 | 11 | 54.5 | 8,400 | 89 | 432.8 | 9,458 | 487.3 |
| 19.4 | 1,058 | 17 | 54.5 | 83 | 268.9 | 6,278 | 323.4 | |||
| [ | Netherlands | 15.1 | 586 | 7.4 | 38.9 | 7,319 | 93 | 485.7 | 7,905 | 524.6 |
| [ | Netherlands | 16.2 | 6,101 | 66 | 377.8 | 3,206 | 34 | 198.5 | 9,307 | 576.3 |
| [ | Switzerland | 7.4 | 2,109 | 39 | 283.5 | 3,326 | 61 | 447.0 | 5,435 | 730.5 |
| 7.4 | 2,109 | 54 | 283.5 | 46 | 239.9 | 3,894 | 523.4 | |||
| [ | Germany | 82.5 | 33,176 | 46 | 402.3 | 38,438 | 54 | 466.1 | 71,614 | 868.4 |
| [ | Japan | 127.8 | 791 | na | 6.2 | na | na | na | na | na |
| [ | Korea | 46.0 | 564 | na | 12.3 | na | na | na | na | na |
| [ | UK | 62.3 | 4,457 | na | 71.6 | na | na | na | na | na |
| [ | USA | 295.5 | 39,000 | na | 132.5 | na | na | na | na | na |
| 295.5 | na | 346.9 | na | na | na | na | na | |||
| [ | USA | 275.9 | 126,258 | na | 457.6 | na | na | na | na | na |
| [ | USA | 292.8 | na | na | na | 9,115 | na | 31.1 | na | na |
| [ | Jersey | 0.1 | na | na | na | 3 | na | 36.6 | na | na |
| [ | USA | 266.3 | na | na | na | 20,287 | na | 76.2 | na | na |
| [ | USA | 287.6 | na | na | na | 25,559 | na | 88.9 | na | na |
| [ | USA | 269.4 | na | na | na | 40,318 | na | 149.7 | na | na |
| [ | Netherlands | 15.1 | na | na | na | 7,339 | na | 487.0 | na | na |
| 15.1 | na | na | na | na | 158.0 | na | na | |||
* Estimated with alternative friction cost (fc) approach for the study above
~ Estimated with alternative incremental cost method for the study above
All costs are presented in 2015 USD.