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2000
Volume 18, Issue 2
  • ISSN: 1874-6098
  • E-ISSN: 1874-6128

Abstract

Several trends toward patient-centered multi-care models employing translational research strategies are currently emerging in orthopaedics. These align seamlessly with epigenetics discussions in pain, a clinical approach to pain management that prioritizes tailoring healthcare to individual needs, preferences, and circumstances. Recognizing the unique genetic and epigenetic factors influencing pain perception, healthcare providers can integrate personalized insights into their patient-centered approach, offering more targeted and effective pain management strategies tailored to each individual's experience. Custom 3D-printing technologies may also become increasingly relevant to more effectively and reliably treat painful degenerative structural abnormalities. They are expected to go hand-in-hand with the precision medicine redefinition of musculoskeletal care. More effective analysis of surgeons' clinical decision-making and patients' perception of high-value orthopaedic care is needed. Shared Decision Making (SDM) is critical to identifying the best solution for each patient and improving stakeholders' understanding of factors influencing the diverse prioritizing values of surgical or non-surgical treatments by payers, systems, and other providers. Identifying high-value orthopaedic surgeries effective SDM in orthopedic surgery requires more than just presenting patients with information. The Rasch analysis of patient expectations can provide this nuanced approach that involves understanding patient values, addressing misconceptions, and aligning surgical recommendations with patient-specific goals. Optimizing orthopaedic treatment within the patient-centered framework can drive innovation in reimbursement policies that support the field more broadly. Research on separating high-value from low-value orthopaedic procedures may likely impact healthcare decision-makers' resource allocation.

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2024-08-07
2025-10-02
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References

  1. Nirvanie-PersaudL. MillisR.M. Epigenetics and pain: New insights to an old problem.Cureus2022149e2935310.7759/cureus.2935336159345
    [Google Scholar]
  2. IkegamiN. Fee-for-service payment – an evil practice that must be stamped out?Int. J. Health Policy Manag.201542575910.15171/ijhpm.2015.2625674568
    [Google Scholar]
  3. OgundejiY.K. QuinnA. LunneyM. ChongC. ChewD. DansoG. DugganS. EdwardsA. HopkinG. SeniorP. SumnerG. WilliamsJ. MannsB. Factors that influence specialist physician preferences for fee-for-service and salary-based payment models: A qualitative study.Health Policy2021125444244910.1016/j.healthpol.2020.12.01433509635
    [Google Scholar]
  4. FernandopulleR. Breaking the fee-for-service addiction: Let’s move to a comprehensive primary care payment model.2015Available From: https://www.healthaffairs.org/content/forefront/breaking-fee-for-service-addiction-let-s-move-comprehensive-primary-care-payment-model
  5. FraktA.B. PizerS.D. FeldmanR. Payment reduction and Medicare private fee-for-service plans.Health Care Financ. Rev.2009303152419544932
    [Google Scholar]
  6. RutherfordB. BrockmanM. HuntS. HeltonJ. SchmidtR.N. Transitions from a FEE-FOR-SERVICE (FFS) payment model: Evolutionary triple to quadruple aim transformation, value-based care and decreased provider burnout.J. Bus. Educ. Leadersh.2022202212
    [Google Scholar]
  7. Van CittersA.D. FahlmanC. GoldmannD.A. LiebermanJ.R. KoenigK.M. DiGioiaA.M.III O’DonnellB. MartinJ. FedericoF.A. BankowitzR.A. NelsonE.C. BozicK.J. Developing a pathway for high-value, patient-centered total joint arthroplasty.Clin. Orthop. Relat. Res.201447251619163510.1007/s11999‑013‑3398‑424297106
    [Google Scholar]
  8. SalehK.J. ShafferW.O. Understanding value-based reimbursement models and trends in orthopaedic health policy: An introduction to the Medicare Access and CHIP Reauthorization Act (MACRA) of 2015.J. Am. Acad. Orthop. Surg.20162411e136e14710.5435/JAAOS‑D‑16‑0028327755264
    [Google Scholar]
  9. FinkelsteinA. JiY. MahoneyN. SkinnerJ. Mandatory Medicare bundled payment program for lower extremity joint replacement and discharge to institutional postacute care: Interim analysis of the first year of a 5-year randomized trial.JAMA2018320989290010.1001/jama.2018.1234630193277
    [Google Scholar]
  10. SorensonC. DrummondM. BurnsL.R. Evolving reimbursement and pricing policies for devices in Europe and the United States should encourage greater value.Health Aff.201332478879610.1377/hlthaff.2012.121023569060
    [Google Scholar]
  11. KimH MeathTH QuiñonesAR McConnellKJ IbrahimSA Association of medicare mandatory bundled payment program with the receipt of elective hip and knee replacement in white, black, and hispanic beneficiaries.JAMA Netw Open202143e211772
    [Google Scholar]
  12. KoH. MartinB.I. NelsonR.E. PeltC.E. How does the effect of the comprehensive care for joint replacement model vary based on surgical volume and costs of care?Med. Care2023611202610.1097/MLR.000000000000178536223537
    [Google Scholar]
  13. ThirukumaranCP KimY CaiX RicciardiBF LiY FiscellaKA MesfinA GlanceLG Association of the comprehensive care for joint replacement model with disparities in the use of total hip and total knee replacement.JAMA Netw Open202145e211185810.1001/jamanetworkopen.2021.11858
    [Google Scholar]
  14. CMSFindings at a Glance - Comprehensive Care for Joint Replacement (CJR) Model.2023Available From: https://www.cms.gov/priorities/innovation/data-and-reports/2023/cjr-py5-ar-findings-aag
  15. EricksonS.M. RockwernB. KoltovM. McLeanR.M. PracticeM. Physicians* QCotACo. Putting patients first by reducing administrative tasks in health care: A position paper of the American College of Physicians.Ann. Intern. Med.2017166965966110.7326/M16‑269728346948
    [Google Scholar]
  16. JostT.S. Racial and ethnic disparities in Medicare: What the Department of Health and Human Services and the Centers for Medicare and Medicaid Services can, and should, do.DePaul J. Health Care Law20059166771817061383
    [Google Scholar]
  17. LanskyD. NwachukwuB.U. BozicK.J. Using financial incentives to improve value in orthopaedics.Clin. Orthop. Relat. Res.201247041027103710.1007/s11999‑011‑2127‑022002826
    [Google Scholar]
  18. FountzilasE. TsimberidouA.M. VoH.H. KurzrockR. Clinical trial design in the era of precision medicine.Genome Med.202214110110.1186/s13073‑022‑01102‑136045401
    [Google Scholar]
  19. LewandrowskiK.U. AbrahamI. Ramírez LeónJ.F. TelfeianA.E. LorioM.P. HellingerS. KnightM. De CarvalhoP.S.T. RamosM.R.F. DowlingÁ. Rodriguez GarciaM. MuhammadF. HussainN. YamamotoV. KatebB. YeungA. A proposed personalized spine care protocol (spinescreen) to treat visualized pain generators: An illustrative study comparing clinical outcomes and postoperative reoperations between targeted endoscopic lumbar decompression surgery, minimally invasive TLIF and open laminectomy.J. Pers. Med.2022127106510.3390/jpm1207106535887562
    [Google Scholar]
  20. LewandrowskiK.U. ElfarJ.C. LiZ.M. BurkhardtB.W. LorioM.P. WinklerP.A. OertelJ.M. TelfeianA.E. DowlingÁ. VargasR.A.A. RaminaR. AbrahamI. AssefiM. YangH. ZhangX. Ramírez LeónJ.F. FiorelliR.K.A. PereiraM.G. de CarvalhoP.S.T. DefinoH. MoyanoJ. LimK.T. KimH.S. MontemurroN. YeungA. NovellinoP. The changing environment in postgraduate education in orthopedic surgery and neurosurgery and its impact on technology-driven targeted interventional and surgical pain management: Perspectives from Europe, Latin America, Asia, and The United States.J. Pers. Med.202313585210.3390/jpm1305085237241022
    [Google Scholar]
  21. LewandrowskiK.U. YeungA. LorioM.P. YangH. Ramírez LeónJ.F. SánchezJ.A.S. FiorelliR.K.A. LimK.T. MoyanoJ. DowlingÁ. Sea AramayoJ.M. ParkJ.Y. KimH.S. ZengJ. MengB. GómezF.A. RamirezC. De CarvalhoP.S.T. Rodriguez GarciaM. GarciaA. MartínezE.E. Gómez SilvaI.M. Valerio PascuaJ.E. Duchén RodríguezL.M. MevesR. MenezesC.M. CarelliL.E. CristanteA.F. AmaralR. de Sa CarneiroG. DefinoH. YamamotoV. KatebB. On Behalf OfT.O.I. Personalized interventional surgery of the lumbar spine: A perspective on minimally invasive and neuroendoscopic decompression for spinal stenosis.J. Pers. Med.202313571010.3390/jpm1305071037240880
    [Google Scholar]
  22. ToopN. DhaliwalJ. GrossbachA. GibbsD. ReddyN. KeisterA. MalloryN. XuD. ViljoenS. Subsidence rates associated with porous 3D-printed versus solid titanium cages in transforaminal lumbar interbody fusion.Global Spine J.202314710.1177/2192568223115776236786680
    [Google Scholar]
  23. McGilvrayK.C. EasleyJ. SeimH.B. ReganD. BervenS.H. HsuW.K. MrozT.E. PuttlitzC.M. Bony ingrowth potential of 3D-printed porous titanium alloy: A direct comparison of interbody cage materials in an in vivo ovine lumbar fusion model.Spine J.20181871250126010.1016/j.spinee.2018.02.01829496624
    [Google Scholar]
  24. LarattaJ.L. VivaceB.J. López-PeñaM. GuzónF.M. Gonzalez-CantalpeidraA. Jorge-MoraA. Villar-ListeR.M. Pino-LopezL. LukyanchukA. TaghizadehE.A. Pino-MinguezJ. 3D-printed titanium cages without bone graft outperform PEEK cages with autograft in an animal model.Spine J.20222261016102710.1016/j.spinee.2021.12.00434906741
    [Google Scholar]
  25. MaloneH. MundisG.M. CollierM. KidwellR.L. RiosF. JelousiM. GalliS. ShahidiB. AkbarniaB.A. EastlackR.K. Can a bioactive interbody device reduce the cost burden of achieving lateral lumbar fusion?J. Neurosurg. Spine202237564665310.3171/2022.4.SPINE21107036303478
    [Google Scholar]
  26. DengZ. ZouQ. WangL. WangL. XiuP. FengG. SongY. YangX. Comparison between Three‐Dimensional Printed Titanium and PEEK cages for cervical and lumbar interbody fusion: A prospective controlled trial.Orthop. Surg.202315112889290010.1111/os.1389637771127
    [Google Scholar]
  27. HamD.W. JungC.W. ChangD.G. YangJ.J. SongK.S. Feasibility of non-window three-dimensional–printed porous titanium cage in posterior lumbar interbody fusion: A pilot trial.Clin. Orthop. Surg.202315696096710.4055/cios2240438045587
    [Google Scholar]
  28. DuanY. FengD. LiT. WangY. JiangL. HuangY. Comparison of lumbar interbody fusion with 3D-printed porous titanium cage versus polyetheretherketone cage in treating lumbar degenerative disease: A systematic review and meta-analysis.World Neurosurg.202418314415610.1016/j.wneu.2023.12.11138145654
    [Google Scholar]
  29. OwensD.K. QaseemA. ChouR. ShekelleP. High-value, cost-conscious health care: Concepts for clinicians to evaluate the benefits, harms, and costs of medical interventions.Ann. Intern. Med.2011154317418010.7326/0003‑4819‑154‑3‑201102010‑0000721282697
    [Google Scholar]
  30. LewandrowskiK.U. de CarvalhoP.S.T. CalderaroA.L. SantosT.S. de Lima e SilvaM.S. de CarvalhoP.Jr YeungA. Outcomes with transforaminal endoscopic versus percutaneous laser decompression for contained lumbar herniated disc: A survival analysis of treatment benefit.J. Spine Surg.20206S1Suppl. 1S84S9910.21037/jss.2019.09.1332195418
    [Google Scholar]
  31. LewandrowskiK.U. RansomN.A. Five-year clinical outcomes with endoscopic transforaminal outside-in foraminoplasty techniques for symptomatic degenerative conditions of the lumbar spine.J. Spine Surg.20206S1Suppl. 1S54S6510.21037/jss.2019.07.0332195416
    [Google Scholar]
  32. YeungA. LewandrowskiK.U. Five-year clinical outcomes with endoscopic transforaminal foraminoplasty for symptomatic degenerative conditions of the lumbar spine: A comparative study of inside-out versus outside-in techniques.J. Spine Surg.20206S1Suppl. 1S66S8310.21037/jss.2019.06.0832195417
    [Google Scholar]
  33. RaadM. LópezW.O.C. SharafshahA. AssefiM. LewandrowskiK.U. Personalized medicine in cancer pain management.J. Pers. Med.2023138120110.3390/jpm1308120137623452
    [Google Scholar]
  34. RaschG. Probabilistic models for some intelligence and attainment tests.ChicagoThe University of Chicago Press1960/1980
    [Google Scholar]
  35. MastersG.N. A rasch model for partial credit scoring.Psychometrika198247214917410.1007/BF02296272
    [Google Scholar]
  36. AndrichD. An elaboration of Guttman scaling with Rasch models for measurement.Sociol. Methodol.198515338010.2307/270846
    [Google Scholar]
  37. BechtelG.G. Generalizing the Rasch model for consumer rating scales.Mark. Sci.198541627310.1287/mksc.4.1.62
    [Google Scholar]
  38. AndrichD. StylesI. Final report on the psychometric analysis of the Early Development Instrument (EDI) using the Rasch model: A technical paper commissioned for the development of the Australian Early Development Instrument (AEDI).2004Available From: https://www.semanticscholar.org/paper/Final-report-on-the- psychometric-analysis-of-the-A-Andrich-Styles/1469ba66cfdba1cf180d7af66e350ea0f74681d3
  39. DrahosG.L. WilliamsL. Addressing the emerging public health crisis of narcotic overdose.Gen. Dent.20176557928862579
    [Google Scholar]
  40. DasguptaN. BeletskyL. CiccaroneD. Opioid crisis: No easy fix to its social and economic determinants.Am. J. Public Health2018108218218610.2105/AJPH.2017.30418729267060
    [Google Scholar]
  41. CDCFrom 1999 to 2020, more than 263,000 people died in the United States from overdoses involving prescription opioids. Overdose deaths involving prescription opioids nearly increased by five times from 1999 to 2020.2023Available From: http://wonder.cdc.gov
  42. FriedmanS.R. KrawczykN. PerlmanD.C. Mateu-GelabertP. OmpadD.C. HamiltonL. NikolopoulosG. GuarinoH. CerdáM. The opioid/overdose crisis as a dialectics of pain, despair, and one-sided struggle.Front. Public Health2020854042310.3389/fpubh.2020.54042333251171
    [Google Scholar]
  43. WilsonN. KariisaM. SethP. SmithH.IV DavisN.L. Drug and opioid-involved overdose deaths — United States, 2017–2018.MMWR Morb. Mortal. Wkly. Rep.2020691129029710.15585/mmwr.mm6911a432191688
    [Google Scholar]
  44. BöttcherL. ChouT. D’OrsognaM.R. Forecasting drug overdose mortality by age in the United States at the national and county levels.medRxiv2023
    [Google Scholar]
  45. El IbrahimiS. HendricksM.A. LittleK. RitterG.A. FloresD. LoyB. WrightD. WeinerS.G. The association between community social vulnerability and prescription opioid availability with individual opioid overdose.Drug Alcohol Depend.202325211099110.1016/j.drugalcdep.2023.11099137862877
    [Google Scholar]
  46. WangL. HongP.J. JiangW. RehmanY. HongB.Y. CoubanR.J. WangC. HayesC.J. JuurlinkD.N. BusseJ.W. Predictors of fatal and nonfatal overdose after prescription of opioids for chronic pain: A systematic review and meta-analysis of observational studies.CMAJ202319541E1399E141110.1503/cmaj.23045937871953
    [Google Scholar]
  47. DennenA.C. BlumK. BravermanR.E. BowirratA. GoldM. ElmanI. ThanosK.P. BaronD. GuptaA. EdwardsD. BadgaiyanD.R. How to combat the global opioid crisis.CPQ Neurol Psychol. 2023545
    [Google Scholar]
  48. SadhasivamS. ChidambaranV. Pharmacogenomics of opioids and perioperative pain management.Pharmacogenomics201213151719174010.2217/pgs.12.15223171337
    [Google Scholar]
  49. ArokeE.N. KittelsrudJ.M. Pharmacogenetics of postoperative pain management: A review.AANA J.202088322923632442101
    [Google Scholar]
  50. ChaturvediR. AlexanderB. A’CourtA.M. WatermanR.S. BurtonB.N. UrmanR.D. GabrielR.A. Genomics testing and personalized medicine in the preoperative setting: Can it change outcomes in postoperative pain management?Baillieres. Best Pract. Res. Clin. Anaesthesiol.202034228329510.1016/j.bpa.2020.05.00832711834
    [Google Scholar]
  51. BatesJ. FudinJ. PatelJ.N. Integrating pharmacogenomics into precision pain management.Support. Care Cancer20223012104531045910.1007/s00520‑022‑07404‑936271058
    [Google Scholar]
  52. BlumK. HauserM. FratantonioJ. BadgaiyanR.D. Molecular genetic testing in pain and addiction: Facts, fiction and clinical utility.Addict. Genet.2015211510.1515/addge‑2015‑000126807291
    [Google Scholar]
  53. BlumK. ChenA.L.C. ThanosP.K. FeboM. DemetrovicsZ. DushajK. KovoorA. BaronD. SmithD.E. RoyA.K.III FriedL. ChenT.J.H. ChapmanE.Sr ModestinoE.J. SteinbergB. BadgaiyanR.D. Genetic addiction risk score GARS trade a predictor of vulnerability to opioid dependence.Front. Biosci.201810117519610.2741/e81628930612
    [Google Scholar]
  54. FlorinR.E. Rasch analysis in measurement of physician work.J. Outcome Meas.20004256457811272617
    [Google Scholar]
  55. YoungT. YangY. BrazierJ.E. TsuchiyaA. CoyneK. The first stage of developing preference-based measures: Constructing a health-state classification using Rasch analysis.Qual. Life Res.200918225326510.1007/s11136‑008‑9428‑019082759
    [Google Scholar]
  56. BooneW.J. StaverJ.R. YaleM.S. Rasch Analysis in the Human Sciences.ChamSpringer2013
    [Google Scholar]
  57. LorioM. MartinsonM. FerraraL. Paired comparison survey analyses utilizing rasch methodology of the relative difficulty and estimated work relative value units of CPT ® Code 27279.Int. J. Spine Surg.2016104010.14444/304028377854
    [Google Scholar]
  58. MundyL.R. MillerH.C. KlassenA.F. CanoS.J. PusicA.L. Patient-reported outcome instruments for surgical and traumatic scars: A systematic review of their development, content, and psychometric validation.Aesthetic Plast. Surg.201640579280010.1007/s00266‑016‑0642‑927357634
    [Google Scholar]
  59. TennantA. KüçükdeveciA.A. Application of the Rasch measurement model in rehabilitation research and practice: Early developments, current practice, and future challenges.Front Rehab Sci20234120867010.3389/fresc.2023.120867037529206
    [Google Scholar]
  60. CortigianoC. Why orthopedics could shift care models, per 3 leaders.2024Available From: https://www.beckersspine.com/featured-insights/58866-why-orthopedics-could-shift-care-models-per-3-leaders.html
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