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Original article

Vol. 148 No. 4546 (2018)

Rationale and methods of an observational study to support the design of a nationwide surgical registry: the MIDAS study

  • Werner Vach
  • Franziska Saxer
  • Anders Holsgaard-Larsen
  • Søren Overgaard
  • Erik Farin-Glattacker
  • Nicolas Bless
  • Heiner C. Bucher
  • Marcel Jakob
DOI
https://doi.org/10.4414/smw.2018.14680
Cite this as:
Swiss Med Wkly. 2018;148:w14680
Published
18.11.2018

Summary

BACKGROUND

Surgical registries are becoming increasingly popular. In addition, Swiss legislation requires data on therapeutic outcome quality. The Swiss Association of Surgeons (Schweizerische Gesellschaft Chirurgie, SGC-SCC) has already agreed on a first minimum data set. However, in the long run the scope and content of the registry should be evidence-based and not only accepted by professional stakeholders. The MIDAS study aims at providing such evidence for the example population of patients undergoing emergency or elective hip surgery. Five relevant aspects are considered: (1) choice of instruments for assessing health related quality of life (HRQoL); (2) optimal time-point for assessment; (3) use of proxy assessments; (4) choice of pre-surgery risk factors; and (5) assessment of peri- and postoperative variables.

METHODS

MIDAS is a longitudinal observational multicentre study. All patients suffering from a femoral neck fracture or from arthritis of the hip joint with an indication for prosthetic joint replacement surgery will be offered participation. The study is based on a combination of routine data from clinical standard practice with specifically documented data to be reported by the treating clinician and data to be collected in cooperation with the patient – in particular patient-reported outcome measures (PROMs). The latter include the Health Utility Index Mark 3 (HUI3) and Euro-Qol-5D (EQ-5D) as generic instruments, Hip Disability and Osteoarthritis Outcome Score (HOOS) as a disease specific instrument for the assessment of HRQoL, and two performance-based functional tests. Data will be collected at baseline, during hospitalisation/at discharge and at three routine follow-up visits. All patients will be asked to name a person for assessing proxy-perceived HRQoL.

DISCUSSION

To the best of our knowledge, this is the first study explicitly addressing questions about the design of a national surgical registry in an empirical manner. The study aims at providing a scientific base for decisions regarding scope and content of a potential national Swiss surgical registry. We designed a pragmatic study to envision data collection in a national registry with the option of specifying isolated research questions of interest. One focus of the study is the use of PROMs, and we hope that our study and their results will inspire also other surgical registries to take this important step forward.

Trial registration

Registered at the “Deutsches Register Klinischer Studien (DRKS)”, the German Clinical Trials Registry, since this registry meets the scope and methodology of the proposed study. Registration no.: DRKS00012991

References

  1. Delaunay C. Registries in orthopaedics. Orthop Traumatol Surg Res. 2015;101(1, Suppl):S69–75. doi:.https://doi.org/10.1016/j.otsr.2014.06.029
  2. Niederländer C, Wahlster P, Kriza C, Kolominsky-Rabas P. Registries of implantable medical devices in Europe. Health Policy. 2013;113(1-2):20–37. doi:.https://doi.org/10.1016/j.healthpol.2013.08.008
  3. Pugely AJ, Martin CT, Harwood J, Ong KL, Bozic KJ, Callaghan JJ. Database and Registry Research in Orthopaedic Surgery: Part 2: Clinical Registry Data. J Bone Joint Surg Am. 2015;97(21):1799–808. doi:.https://doi.org/10.2106/JBJS.O.00134
  4. Alluri RK, Leland H, Heckmann N. Surgical research using national databases. Ann Transl Med. 2016;4(20):393. doi:.https://doi.org/10.21037/atm.2016.10.49
  5. Dy CJ, Bumpass DB, Makhni EC, Bozic KJ ; AAOS Washington Health Policy Fellowship. The Evolving Role of Clinical Registries: Existing Practices and Opportunities for Orthopaedic Surgeons. J Bone Joint Surg Am. 2016;98(2):e7. doi:.https://doi.org/10.2106/JBJS.O.00494
  6. Sebastian AS. Database Research in Spine Surgery. Clin Spine Surg. 2016;29(10):427–9. doi:.https://doi.org/10.1097/BSD.0000000000000464
  7. Inacio MCS, Paxton EW, Dillon MT. Understanding Orthopaedic Registry Studies: A Comparison with Clinical Studies. J Bone Joint Surg Am. 2016;98(1):e3. doi:.https://doi.org/10.2106/JBJS.N.01332
  8. Stey AM, Russell MM, Ko CY, Sacks GD, Dawes AJ, Gibbons MM. Clinical registries and quality measurement in surgery: a systematic review. Surgery. 2015;157(2):381–95. doi:.https://doi.org/10.1016/j.surg.2014.08.097
  9. Hoffman RL, Bartlett EK, Medbery RL, Sakran JV, Morris JB, Kelz RR. Outcomes registries: an untapped resource for use in surgical education. J Surg Educ. 2015;72(2):264–70. doi:.https://doi.org/10.1016/j.jsurg.2014.08.014
  10. Mandavia R, Knight A, Phillips J, Mossialos E, Littlejohns P, Schilder A. What are the essential features of a successful surgical registry? a systematic review. BMJ Open. 2017;7(9):e017373. doi:.https://doi.org/10.1136/bmjopen-2017-017373
  11. International Conference on Harmonisation of Technical Requirements for Registration of Pharmaceuticals for Human Use. ICH Harmonised Tripartite Guideline. Guideline for good clinical practice E6(R1).
  12. Dindo D, Demartines N, Clavien P-A. Classification of surgical complications: a new proposal with evaluation in a cohort of 6336 patients and results of a survey. Ann Surg. 2004;240(2):205–13. doi:.https://doi.org/10.1097/01.sla.0000133083.54934.ae
  13. World Health Organisation. ICD-10 Version: 2016. http://apps.who.int/classifications/icd10/browse/2016. Accessed Nov 14, 2017
  14. Brooks RG. 28 Years of the EuroQol Group : An Overview. EuroQol Working Paper Series 15003. 2015. Available from: https://euroqol.org/wp-content/uploads/working_paper_series/EuroQol_Working_Paper_Series_Manuscript_15003_-_Richard_Brooks.pdf.
  15. Herdman M, Gudex C, Lloyd A, Janssen M, Kind P, Parkin D, et al. Development and preliminary testing of the new five-level version of EQ-5D (EQ-5D-5L). Qual Life Res. 2011;20(10):1727–36. doi:.https://doi.org/10.1007/s11136-011-9903-x
  16. EQ-5D-5L user guide. Basic Information on how to use EQ-5D-5L Instrumemnts. 2015. https://euroqol.org/wp-content/uploads/2016/09/EQ-5D-5L_UserGuide_2015.pdf. Accessed November 14, 2017.
  17. Eidgenössisches Department des Inneren - Bundesamt für Statistik. Schweizerische Operationsklassifikation (CHOP). Systematisches Verzeichnis 2017.
  18. Patientenzufriedenheit ANQ. http://www.anq.ch/akutsomatik/patientenbefragung/. Accessed August 27, 2017.
  19. Horsman J, Furlong W, Feeny D, Torrance G. The Health Utilities Index (HUI): concepts, measurement properties and applications. Health Qual Life Outcomes. 2003;1(1):54. doi:.https://doi.org/10.1186/1477-7525-1-54
  20. Van Beeck EF, Larsen CF, Lyons RA, Meerding WJ, Mulder S, Essink-Bot ML. Guidelines for the conduction of follow-up studies measuring injury-related disability. J Trauma. 2007;62(2):534–50. doi:.https://doi.org/10.1097/TA.0b013e31802e70c7
  21. Shaw FE. Falls in cognitive impairment and dementia. Clin Geriatr Med. 2002;18(2):159–73. doi:.https://doi.org/10.1016/S0749-0690(02)00003-4
  22. Muir SW, Gopaul K, Montero Odasso MM. The role of cognitive impairment in fall risk among older adults: a systematic review and meta-analysis. Age Ageing. 2012;41(3):299–308. doi:.https://doi.org/10.1093/ageing/afs012
  23. Liu-Ambrose TY, Ashe MC, Graf P, Beattie BL, Khan KM. Increased risk of falling in older community-dwelling women with mild cognitive impairment. Phys Ther. 2008;88(12):1482–91. doi:.https://doi.org/10.2522/ptj.20080117
  24. Segev-Jacubovski O, Herman T, Yogev-Seligmann G, Mirelman A, Giladi N, Hausdorff JM. The interplay between gait, falls and cognition: can cognitive therapy reduce fall risk? Expert Rev Neurother. 2011;11(7):1057–75. doi:.https://doi.org/10.1586/ern.11.69
  25. Pickard AS, Knight SJ. Proxy evaluation of health-related quality of life: a conceptual framework for understanding multiple proxy perspectives. Med Care. 2005;43(5):493–9. doi:.https://doi.org/10.1097/01.mlr.0000160419.27642.a8
  26. Magaziner J, Simonsick EM, Kashner TM, Hebel JR. Patient-proxy response comparability on measures of patient health and functional status. J Clin Epidemiol. 1988;41(11):1065–74. doi:.https://doi.org/10.1016/0895-4356(88)90076-5
  27. Mathew RO, Hsu W-H, Young Y. Effect of comorbidity on functional recovery after hip fracture in the elderly. Am J Phys Med Rehabil. 2013;92(8):686–96. doi:.https://doi.org/10.1097/PHM.0b013e318282bc67
  28. Kabboord AD, van Eijk M, Fiocco M, van Balen R, Achterberg WP. Assessment of Comorbidity Burden and its Association With Functional Rehabilitation Outcome After Stroke or Hip Fracture: A Systematic Review and Meta-Analysis. J Am Med Dir Assoc. 2016;17(11):1066.e13–21. doi:.https://doi.org/10.1016/j.jamda.2016.07.028
  29. Peter WF, Dekker J, Tilbury C, Tordoir RL, Verdegaal SH, Onstenk R, et al. The association between comorbidities and pain, physical function and quality of life following hip and knee arthroplasty. Rheumatol Int. 2015;35(7):1233–41. doi:.https://doi.org/10.1007/s00296-015-3211-7
  30. Günther KP, Haase E, Lange T, Kopkow C, Schmitt J, Jeszenszky C, et al. Persönlichkeitsprofil und Komorbidität: Gibt es den “schwierigen Patienten” in der primären Hüftendoprothetik? [Personality and comorbidity: are there “difficult patients” in hip arthroplasty?]. Orthopade. 2015;44(7):555–65.https://doi.org/10.1007/s00132-015-3097-9
  31. Charlson ME, Pompei P, Ales KL, MacKenzie CR. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis. 1987;40(5):373–83. doi:.https://doi.org/10.1016/0021-9681(87)90171-8
  32. Charlson M, Szatrowski TP, Peterson J, Gold J. Validation of a combined comorbidity index. J Clin Epidemiol. 1994;47(11):1245–51. doi:.https://doi.org/10.1016/0895-4356(94)90129-5
  33. Elixhauser A, Steiner C, Harris DR, Coffey RM. Comorbidity measures for use with administrative data. Med Care. 1998;36(1):8–27. doi:.https://doi.org/10.1097/00005650-199801000-00004
  34. Clark DO, Von Korff M, Saunders K, Baluch WM, Simon GE. A chronic disease score with empirically derived weights. Med Care. 1995;33(8):783–95. doi:.https://doi.org/10.1097/00005650-199508000-00004
  35. Perkins AJ, Kroenke K, Unützer J, Katon W, Williams JW, Jr, Hope C, et al. Common comorbidity scales were similar in their ability to predict health care costs and mortality. J Clin Epidemiol. 2004;57(10):1040–8. doi:.https://doi.org/10.1016/j.jclinepi.2004.03.002
  36. Schneeweiss S, Maclure M. Use of comorbidity scores for control of confounding in studies using administrative databases. Int J Epidemiol. 2000;29(5):891–8. doi:.https://doi.org/10.1093/ije/29.5.891
  37. Nilsdotter A, Bremander A. Measures of hip function and symptoms: Harris Hip Score (HHS), Hip Disability and Osteoarthritis Outcome Score (HOOS), Oxford Hip Score (OHS), Lequesne Index of Severity for Osteoarthritis of the Hip (LISOH), and American Academy of Orthopedic Surgeons (AAOS) Hip and Knee Questionnaire. Arthritis Care Res (Hoboken). 2011;63(S11, Suppl 11):S200–7. doi:.https://doi.org/10.1002/acr.20549
  38. Kennedy DM, Stratford PW, Wessel J, Gollish JD, Penney D. Assessing stability and change of four performance measures: a longitudinal study evaluating outcome following total hip and knee arthroplasty. BMC Musculoskelet Disord. 2005;6(1):3. doi:.https://doi.org/10.1186/1471-2474-6-3
  39. Roos EM. HOOS. http://www.koos.nu. Accessed Nov 14, 2017.
  40. Blasimann A, Dauphinee SW, Staal JB. Translation, cross-cultural adaptation, and psychometric properties of the German version of the hip disability and osteoarthritis outcome score. J Orthop Sports Phys Ther. 2014;44(12):989–97. doi:.https://doi.org/10.2519/jospt.2014.4994
  41. ICHOM. http://www.ichom.org. Accessed August 28, 2017.
  42. Dobson F, Hinman RS, Roos EM, Abbott JH, Stratford P, Davis AM, et al. OARSI recommended performance-based tests to assess physical function in people diagnosed with hip or knee osteoarthritis. Osteoarthritis Cartilage. 2013;21(8):1042–52. doi:.https://doi.org/10.1016/j.joca.2013.05.002
  43. Dobson F, Hinman RS, Hall M, Terwee CB, Roos EM, Bennell KL. Measurement properties of performance-based measures to assess physical function in hip and knee osteoarthritis: a systematic review. Osteoarthritis Cartilage. 2012;20(12):1548–62. doi:.https://doi.org/10.1016/j.joca.2012.08.015
  44. Bennell K, Dobson F, Hinman R. Measures of physical performance assessments: Self-Paced Walk Test (SPWT), Stair Climb Test (SCT), Six-Minute Walk Test (6MWT), Chair Stand Test (CST), Timed Up & Go (TUG), Sock Test, Lift and Carry Test (LCT), and Car Task. Arthritis Care Res (Hoboken). 2011;63(S11, Suppl 11):S350–70. doi:.https://doi.org/10.1002/acr.20538
  45. Steffen TM, Hacker TA, Mollinger L. Age- and gender-related test performance in community-dwelling elderly people: Six-Minute Walk Test, Berg Balance Scale, Timed Up & Go Test, and gait speeds. Phys Ther. 2002;82(2):128–37. doi:.https://doi.org/10.1093/ptj/82.2.128
  46. Jones CJ, Rikli RE, Beam WCA. A 30-s chair-stand test as a measure of lower body strength in community-residing older adults. Res Q Exerc Sport. 1999;70(2):113–9. doi:.https://doi.org/10.1080/02701367.1999.10608028
  47. Millor N, Lecumberri P, Gómez M, Martínez-Ramírez A, Izquierdo M. An evaluation of the 30-s chair stand test in older adults: frailty detection based on kinematic parameters from a single inertial unit. J Neuroeng Rehabil. 2013;10(1):86. doi:.https://doi.org/10.1186/1743-0003-10-86
  48. Gill S, McBurney H. Reliability of performance‐based measures in people awaiting joint replacement surgery of the hip or knee. Physiother Res Int. 2008;13:141–52.
  49. Unver B, Kahraman T, Kalkan S, Yuksel E, Karatosun V, Gunal I. Test-retest reliability of the 50-foot timed walk and 30-second chair stand test in patients with total hip arthroplasty. Acta Orthop Belg. 2015;81(3):435–41.
  50. Kennedy D, Stratford PW, Pagura SM, Walsh M, Woodhouse LJ. Comparison of gender and group differences in self-report and physical performance measures in total hip and knee arthroplasty candidates. J Arthroplasty. 2002;17(1):70–7. doi:.https://doi.org/10.1054/arth.2002.29324
  51. Kahn RL, Goldfarb AI, Pollack M, Peck A. Brief objective measures for the determination of mental status in the aged. Am J Psychiatry. 1960;117(4):326–8. doi:.https://doi.org/10.1176/ajp.117.4.326
  52. Rosenthal R, Hoffmann H, Clavien PA, Bucher HC, Dell-Kuster S. Definition and classification of intraoperative complications (CLASSIC): Delphi study and pilot evaluation. World J Surg. 2015;39(7):1663–71. doi:.https://doi.org/10.1007/s00268-015-3003-y
  53. Altman R, Alarcón G, Appelrouth D, Bloch D, Borenstein D, Brandt K, et al. The American College of Rheumatology criteria for the classification and reporting of osteoarthritis of the hip. Arthritis Rheum. 1991;34(5):505–14. doi:.https://doi.org/10.1002/art.1780340502
  54. Bundesversammlung der Schweizer Eidgenossenschaft: Schweizerisches Zivilgesetzbuch. (Stand 1.9.2017).
  55. Saklad M. Grading for Patients for Surgical Procedures. Anesthesiology. 1941;2(3):281–4. doi:.https://doi.org/10.1097/00000542-194105000-00004
  56. Codes ATC. http://www.atccode.com/. Accessed November 14, 2017.
  57. Hamilton DF, Lane JV, Gaston P, Patton JT, Macdonald DJ, Simpson AH, et al. Assessing treatment outcomes using a single question: the net promoter score. Bone Joint J. 2014;96-B(5):622–8. doi:.https://doi.org/10.1302/0301-620X.96B5.32434
  58. Luo N, Johnson J, Coons SJ. Using instrument-defined health state transitions to estimate minimally important differences for four preference-based health-related quality of life instruments. Med Care. 2010;48(4):365–71. doi:.https://doi.org/10.1097/MLR.0b013e3181c162a2
  59. Paulsen A, Roos EM, Pedersen AB, Overgaard S. Minimal clinically important improvement (MCII) and patient-acceptable symptom state (PASS) in total hip arthroplasty (THA) patients 1 year postoperatively. Acta Orthop. 2014;85(1):39–48. doi:.https://doi.org/10.3109/17453674.2013.867782
  60. Farin E. Integration of patient and provider assessments of mobility and self-care resulted in unidimensional item-response theory scales. J Clin Epidemiol. 2009;62(10):1075–84. doi:.https://doi.org/10.1016/j.jclinepi.2008.11.014
  61. Tibshirani R. Regression Selection and Shrinkage via the Lasso. J R Stat Soc B. 1996;58(1):267–88. doi:.https://doi.org/10.2307/2346178
  62. Marufu TC, Mannings A, Moppett IK. Risk scoring models for predicting peri-operative morbidity and mortality in people with fragility hip fractures: Qualitative systematic review. Injury. 2015;46(12):2325–34. doi:.https://doi.org/10.1016/j.injury.2015.10.025
  63. Huber CA, Szucs TD, Rapold R, Reich O. Identifying patients with chronic conditions using pharmacy data in Switzerland: an updated mapping approach to the classification of medications. BMC Public Health. 2013;13(1):1030. doi:.https://doi.org/10.1186/1471-2458-13-1030
  64. Cortaredona S, Pambrun E, Verdoux H, Verger P. Comparison of pharmacy-based and diagnosis-based comorbidity measures from medical administrative data. Pharmacoepidemiol Drug Saf. 2017;26(4):402–11. doi:.https://doi.org/10.1002/pds.4146
  65. Cook JA, McCulloch P, Blazeby JM, Beard DJ, Marinac-Dabic D, Sedrakyan A ; IDEAL Group. IDEAL framework for surgical innovation 3: randomised controlled trials in the assessment stage and evaluations in the long term study stage. BMJ. 2013;346(jun18 3):f2820. doi:.https://doi.org/10.1136/bmj.f2820
  66. Van Balen R, Essink-Bot ML, Steyerberg E, Cools H, Habbema DF. Quality of life after hip fracture: a comparison of four health status measures in 208 patients. Disabil Rehabil. 2003;25(10):507–19. doi:.https://doi.org/10.1080/0963828031000090443

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