Home-based digital exercise versus hospital physiotherapy for plantar fasciitis: a propensity-score-matched retrospective cohort study with dual-perspective cost-utility evaluation
DOI:
https://doi.org/10.2340/jrm.v58.45974Keywords:
plantar fasciitis, digital therapeutics, telerehabilitation, propensity-score matching, cost-utility analysisAbstract
Objective: To compare the clinical effectiveness and cost-effectiveness of a 12-week home-based digital exercise programme with 12-week hospital-supervised physiotherapy for plantar fasciitis in routine Chinese tertiary-hospital care.
Design: Single-centre retrospective cohort study with 1:2 propensity-score matching on 13 baseline covariates.
Subjects/Patients: 587 adults with a clinician-confirmed diagnosis of plantar fasciitis treated in 2022–2024 were matched.
Methods: The primary outcome was first-step morning pain at 3 months on a 0–10 numeric rating scale (non-inferiority margin 1.3 points; sensitivity margins 0.9 and 1.9). A 12-month cost–utility analysis took payer and societal perspectives.
Results: The adjusted mean difference was −0.63 points (95% confidence interval −0.92 to −0.35; p < 0.001), non-inferior against all 3 margins (E-value 2.84). Incremental payer cost was −¥4,920 (−US$684), incremental societal cost −¥7,008 (−US$974), and incremental quality-adjusted life-years +0.011, with dominance in 96.7% of bootstrap replications.
Conclusion: Home-based digital exercise was non-inferior for 3-month first-step pain and less costly from both perspectives. Matching left 12 of 13 covariates imbalanced and only 6.3% of screened patients were eligible, so residual confounding and selection bias are likely. These observational findings are provisional and require confirmation in a pragmatic multicentre randomized controlled trial before informing reimbursement.
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References
Nahin RL. Prevalence and pharmaceutical treatment of plantar fasciitis in United States adults. J Pain 2018; 19: 885–896. DOI: https://doi.org/10.1016/j.jpain.2018.03.003
Thomas MJ, Whittle R, Menz HB, Rathod-Mistry T, Marshall M, Roddy E. Plantar heel pain in middle-aged and older adults: population prevalence, associations with health status and lifestyle factors, and frequency of healthcare use. BMC Musculoskelet Disord 2019; 20: 337. DOI: https://doi.org/10.1186/s12891-019-2718-6
Buchbinder R. Clinical practice. Plantar fasciitis. N Engl J Med 2004; 350: 2159–2166. DOI: https://doi.org/10.1056/NEJMcp032745
Riddle DL, Schappert SM. Volume of ambulatory care visits and patterns of care for patients diagnosed with plantar fasciitis: a national study of medical doctors. Foot Ankle Int 2004; 25: 303–310. DOI: https://doi.org/10.1177/107110070402500505
Tong KB, Furia J. Economic burden of plantar fasciitis treatment in the United States. Am J Orthop (Belle Mead NJ) 2010; 39: 227–231.
Ahn J, Yeo J, Lee SH, Lee YJ, Park Y, Goo B, et al. Healthcare usage and cost for plantar fasciitis: a retrospective observational analysis of the 2010–2018 Health Insurance Review and Assessment Service national patient sample data. BMC Health Serv Res 2023; 23: 546. DOI: https://doi.org/10.1186/s12913-023-09443-2
Meng Q, Xu J, Shi V, Liu X, Guo Y, Sun X, et al. Needs for rehabilitation in China: estimates based on the Global Burden of Disease Study 2019. Chin Med J (Engl) 2025; 138: 66–75.
Liu X, Zhu Y, Gao L, Meng Q. Integrated medical rehabilitation delivery in China. Chronic Dis Transl Med 2017; 3: 75–81. DOI: https://doi.org/10.1016/j.cdtm.2017.02.003
Koc TA Jr, Bise CG, Neville C, Carreira D, Martin RL, McDonough CM. Heel pain-plantar fasciitis: revision 2023. J Orthop Sports Phys Ther 2023; 53: CPG1-CPG39. DOI: https://doi.org/10.2519/jospt.2023.0303
Martin RL, Davenport TE, Reischl SF, McPoil TG, Matheson JW, Wukich DK, et al. Heel pain-plantar fasciitis: revision 2014. J Orthop Sports Phys Ther 2014; 44: A1–A33. DOI: https://doi.org/10.2519/jospt.2014.0303
China Internet Network Information Center. The 55th Statistical Report on China’s Internet Development. Beijing: CNNIC; 2025.
Chen X, Xu Q, Lin H, Zhu J, Chen Y, Zhao Q, et al. Applications of digital health approaches for cardiometabolic disease prevention and management in the Western Pacific region. Lancet Reg Health West Pac 2023; 43: 100817. DOI: https://doi.org/10.1016/j.lanwpc.2023.100817
Cottrell MA, Galea OA, O’Leary SP, Hill AJ, Russell TG. Real-time telerehabilitation for the treatment of musculoskeletal conditions is effective and comparable to standard practice: a systematic review and meta-analysis. Clin Rehabil 2017; 31: 625–638. DOI: https://doi.org/10.1177/0269215516645148
Seron P, Oliveros MJ, Gutierrez-Arias R, Fuentes-Aspe R, Torres-Castro RC, Merino-Osorio C, et al. Effectiveness of telerehabilitation in physical therapy: a rapid overview. Phys Ther 2021; 101: pzab053. DOI: https://doi.org/10.1093/ptj/pzab053
Hinman RS, Campbell PK, Kimp AJ, Russell T, Foster NE, Kasza J, et al. Telerehabilitation consultations with a physiotherapist for chronic knee pain versus in-person consultations in Australia: the PEAK non-inferiority randomised controlled trial. Lancet 2024; 403: 1267–1278. DOI: https://doi.org/10.1016/S0140-6736(23)02630-2
Nelligan RK, Hinman RS, Kasza J, Crofts SJC, Bennell KL. Effects of a self-directed web-based strengthening exercise and physical activity program supported by automated text messages for people with knee osteoarthritis: a randomized clinical trial. JAMA Intern Med 2021; 181: 776–785. DOI: https://doi.org/10.1001/jamainternmed.2021.0991
Bennell KL, Nelligan R, Dobson F, Rini C, Keefe F, Kasza J, et al. Effectiveness of an internet-delivered exercise and pain-coping skills training intervention for persons with chronic knee pain: a randomized trial. Ann Intern Med 2017; 166: 453–462. DOI: https://doi.org/10.7326/M16-1714
von Elm E, Altman DG, Egger M, Pocock SJ, Gøtzsche PC, Vandenbroucke JP; STROBE Initiative. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. Lancet 2007; 370: 1453–1457. DOI: https://doi.org/10.1016/S0140-6736(07)61602-X
Husereau D, Drummond M, Augustovski F, de Bekker-Grob E, Briggs AH, Carswell C, et al. Consolidated Health Economic Evaluation Reporting Standards 2022 (CHEERS 2022) statement: updated reporting guidance for health economic evaluations. BMJ 2022; 376: e067975. DOI: https://doi.org/10.1136/bmj-2021-067975
General Administration of Quality Supervision, Inspection and Quarantine of the People’s Republic of China; Standardization Administration of China. Classification and codes of diseases: GB/T 14396–2016. Beijing: Standards Press of China; 2016.
McMillan AM, Landorf KB, Barrett JT, Menz HB, Bird AR. Diagnostic imaging for chronic plantar heel pain: a systematic review and meta-analysis. J Foot Ankle Res 2009; 2: 32. DOI: https://doi.org/10.1186/1757-1146-2-32
Wearing SC, Smeathers JE, Sullivan PM, Yates B, Urry SR, Dubois P. Plantar fasciitis: are pain and fascial thickness associated with arch shape and loading? Phys Ther 2007; 87: 1002–1008. DOI: https://doi.org/10.2522/ptj.20060136
Li Z, Zhang X, Ding L, Du K, Yan J, Chan MTV, et al. Association between remote resistance exercises programs delivered by a smartphone application and skeletal muscle mass among elderly patients with type 2 diabetes: a retrospective real-world study. Front Endocrinol (Lausanne) 2024; 15: 1407408. DOI: https://doi.org/10.3389/fendo.2024.1407408
DiGiovanni BF, Nawoczenski DA, Lintal ME, Moore EA, Murray JC, Wilding GE, et al. Tissue-specific plantar fascia-stretching exercise enhances outcomes in patients with chronic heel pain: a prospective, randomized study. J Bone Joint Surg Am 2003; 85: 1270–1277. DOI: https://doi.org/10.2106/00004623-200307000-00013
DiGiovanni BF, Nawoczenski DA, Malay DP, Graci PA,Williams TT, Wilding GE, et al. Plantar fascia-specific stretching exercise improves outcomes in patients with chronic plantar fasciitis: a prospective clinical trial with two-year follow-up. J Bone Joint Surg Am 2006; 88: 1775–1781. DOI: https://doi.org/10.2106/JBJS.E.01281
Rathleff MS, Mølgaard CM, Fredberg U, Kaalund S, Andersen KB, Jensen TT, et al. High-load strength training improves outcome in patients with plantar fasciitis: a randomized controlled trial with 12-month follow-up. Scand J Med Sci Sports 2015; 25: e292–300. DOI: https://doi.org/10.1111/sms.12313
Celik D, Kuş G, Sırma SÖ. Joint mobilization and stretching exercise vs steroid injection in the treatment of plantar fasciitis: a randomized controlled study. Foot Ankle Int 2016; 37: 150–156. DOI: https://doi.org/10.1177/1071100715607619
Landorf KB, Radford JA, Hudson S. Minimal Important Difference (MID) of two commonly used outcome measures for foot problems. J Foot Ankle Res 2010; 3: 7. DOI: https://doi.org/10.1186/1757-1146-3-7
Martin RL, Irrgang JJ, Burdett RG, Conti SF, Van Swearingen JM. Evidence of validity for the Foot and Ankle Ability Measure (FAAM). Foot Ankle Int 2005; 26: 968–983. DOI: https://doi.org/10.1177/107110070502601113
Luo N, Liu G, Li M, Guan H, Jin X, Rand-Hendriksen K. Estimating an EQ-5D-5L value set for China. Value Health 2017; 20: 662–669. DOI: https://doi.org/10.1016/j.jval.2016.11.016
Rosenbaum PR, Rubin DB. The central role of the propensity score in observational studies for causal effects. Biometrika 1983; 70: 41–55. DOI: https://doi.org/10.1093/biomet/70.1.41
Austin PC. A comparison of 12 algorithms for matching on the propensity score. Stat Med 2014; 33: 1057–1069. DOI: https://doi.org/10.1002/sim.6004
Austin PC. An introduction to propensity score methods for reducing the effects of confounding in observational studies. Multivariate Behav Res 2011; 46: 399–424. DOI: https://doi.org/10.1080/00273171.2011.568786
Austin PC. Balance diagnostics for comparing the distribution of baseline covariates between treatment groups in propensity-score matched samples. Stat Med 2009; 28: 3083–3107. DOI: https://doi.org/10.1002/sim.3697
Rubin DB. Multiple imputation for nonresponse in surveys. New York: Wiley; 1987. DOI: https://doi.org/10.1002/9780470316696
Leurent B, Gomes M, Faria R, Morris S, Grieve R, Carpenter JR. Sensitivity analysis for not-at-random missing data in trial-based cost-effectiveness analysis: a tutorial. Pharmacoeconomics 2018; 36: 889–901. DOI: https://doi.org/10.1007/s40273-018-0650-5
VanderWeele TJ, Ding P. Sensitivity analysis in observational research: introducing the E-value. Ann Intern Med 2017; 167: 268–74. DOI: https://doi.org/10.7326/M16-2607
Xu L, Chen M, Angell B, Jiang Y, Howard K, Jan S, et al. Establishing cost-effectiveness threshold in China: a community survey of willingness to pay for a healthy life year. BMJ Glob Health 2024; 9: e013070. DOI: https://doi.org/10.1136/bmjgh-2023-013070
Kyriacou DN, Lewis RJ. Confounding by indication in clinical research. JAMA 2016; 316: 1818–1819. DOI: https://doi.org/10.1001/jama.2016.16435
Hernán MA, Robins JM. Using big data to emulate a target trial when a randomized trial is not available. Am J Epidemiol 2016; 183: 758–764. DOI: https://doi.org/10.1093/aje/kwv254
VanderWeele TJ. Principles of confounder selection. Eur J Epidemiol 2019; 34: 211–219. DOI: https://doi.org/10.1007/s10654-019-00494-6
Rothwell PM. External validity of randomised controlled trials: “to whom do the results of this trial apply?” Lancet 2005; 365: 82–93. DOI: https://doi.org/10.1016/S0140-6736(04)17670-8
Fan M, Chen J, Luo Y, Xu S, Zhang L, Wang M, et al. Digital therapeutics in China: a comprehensive review. J Med Internet Res 2025; 27: e70955. DOI: https://doi.org/10.2196/70955
Ford I, Norrie J. Pragmatic trials. N Engl J Med 2016; 375: 454–463. DOI: https://doi.org/10.1056/NEJMra1510059
Sherman RE, Anderson SA, Dal Pan GJ, Gray GW, Gross T, Hunter NL, et al. Real-world evidence, what is it and what can it tell us? N Engl J Med 2016; 375: 2293–2297. DOI: https://doi.org/10.1056/NEJMsb1609216
Hernán MA, Hernández-Díaz S, Robins JM. A structural approach to selection bias. Epidemiology 2004; 15: 615–625. DOI: https://doi.org/10.1097/01.ede.0000135174.63482.43
Stuart EA. Matching methods for causal inference: a review and a look forward. Stat Sci 2010; 25: 1–21. DOI: https://doi.org/10.1214/09-STS313
Nguyen TL, Collins GS, Spence J, Daurès JP, Devereaux PJ, Landais P, et al. Double-adjustment in propensity score matching analysis: choosing a threshold for considering residual imbalance. BMC Med Res Methodol 2017; 17: 78. DOI: https://doi.org/10.1186/s12874-017-0338-0
Julious SA. Sample sizes for clinical trials with normal data. Stat Med 2004; 23: 1921–1986. DOI: https://doi.org/10.1002/sim.1783
Chow SC, Shao J, Wang H. Sample size calculations in clinical research. 2nd ed. Boca Raton, FL: Chapman & Hall/CRC; 2008.
Cnaan A, Laird NM, Slasor P. Using the general linear mixed model to analyse unbalanced repeated measures and longitudinal data. Stat Med 1997; 16: 2349–2380. DOI: https://doi.org/10.1002/(SICI)1097-0258(19971030)16:20<2349::AID-SIM667>3.0.CO;2-E
Fitzmaurice GM, Laird NM, Ware JH. Applied longitudinal analysis. 2nd ed. Hoboken, NJ: Wiley; 2011. DOI: https://doi.org/10.1002/9781119513469
Wan F. Matched or unmatched analyses with propensity-score-matched data? Stat Med 2019; 38: 289–300. DOI: https://doi.org/10.1002/sim.7976
Kenward MG, Roger JH. Small sample inference for fixed effects from restricted maximum likelihood. Biometrics 1997; 53: 983–997. DOI: https://doi.org/10.2307/2533558
Vickers AJ, Altman DG. Statistics notes: analysing controlled trials with baseline and follow up measurements. BMJ 2001; 323: 1123–1124. DOI: https://doi.org/10.1136/bmj.323.7321.1123
Grimes DA, Schulz KF. Bias and causal associations in observational research. Lancet 2002; 359: 248–252. DOI: https://doi.org/10.1016/S0140-6736(02)07451-2
Piaggio G, Elbourne DR, Pocock SJ, Evans SJW, Altman DG; CONSORT Group. Reporting of noninferiority and equivalence randomized trials: extension of the CONSORT 2010 statement. JAMA 2012; 308: 2594–2604. DOI: https://doi.org/10.1001/jama.2012.87802
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