Inverse optimization on hierarchical networks: an application to breast cancer clinical pathways.
Breast cancer
Clinical pathway concordance
Hierarchical network
Inverse optimization
Operations research
Survival analysis
Journal
Health care management science
ISSN: 1572-9389
Titre abrégé: Health Care Manag Sci
Pays: Netherlands
ID NLM: 9815649
Informations de publication
Date de publication:
Dec 2022
Dec 2022
Historique:
received:
13
08
2021
accepted:
12
05
2022
pubmed:
9
7
2022
medline:
23
11
2022
entrez:
8
7
2022
Statut:
ppublish
Résumé
Clinical pathways are standardized processes that outline the steps required for managing a specific disease. However, patient pathways often deviate from clinical pathways. Measuring the concordance of patient pathways to clinical pathways is important for health system monitoring and informing quality improvement initiatives. In this paper, we develop an inverse optimization-based approach to measuring pathway concordance in breast cancer, a complex disease. We capture this complexity in a hierarchical network that models the patient's journey through the health system. A novel inverse shortest path model is formulated and solved on this hierarchical network to estimate arc costs, which are used to form a concordance metric to measure the distance between patient pathways and shortest paths (i.e., clinical pathways). Using real breast cancer patient data from Ontario, Canada, we demonstrate that our concordance metric has a statistically significant association with survival for all breast cancer patient subgroups. We also use it to quantify the extent of patient pathway discordances across all subgroups, finding that patients undertaking additional clinical activities constitute the primary driver of discordance in the population.
Identifiants
pubmed: 35802305
doi: 10.1007/s10729-022-09599-z
pii: 10.1007/s10729-022-09599-z
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
590-622Informations de copyright
© 2022. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.
Références
Ahuja RK, Orlin JB (2001) Inverse optimization. Oper Res 49(5):771–783
doi: 10.1287/opre.49.5.771.10607
Ahuja RK, Orlin JB (2002) Combinatorial algorithms for inverse network flow problems. Networks: Int J 40(4):181–187
doi: 10.1002/net.10048
American Cancer Society (2021) How common is breast cancer? https://www.cancer.org/cancer/breast-cancer/about/how-common-is-breast-cancer.html . Accessed: May 2022
Aswani A, Shen ZJ, Siddiq A (2018) Inverse optimization with noisy data. Oper Res 66 (3):870–892
doi: 10.1287/opre.2017.1705
Babier A, Chan TC, Lee T, Mahmood R, Terekhov D (2021) An ensemble learning framework for model fitting and evaluation in inverse linear optimization. Informs J Optim 3(2):119–138
doi: 10.1287/ijoo.2019.0045
Bergin RJ, Thomas RJ, Whitfield K, White V (2020) Concordance between optimal care pathways and colorectal cancer care: identifying opportunities to improve quality and reduce disparities. J Eval Clin Pract 26(3):918–926
doi: 10.1111/jep.13231
Bertsimas D, Gupta V, Paschalidis IC (2015) Data-driven estimation in equilibrium using inverse optimization. Math Program 153(2):595–633
doi: 10.1007/s10107-014-0819-4
Burton D, Toint PL (1992) On an instance of the inverse shortest paths problem. Math Program 53(1–3):45–61
doi: 10.1007/BF01585693
Burton D, Pulleyblank W, Toint PL (1997) The inverse shortest paths problem with upper bounds on shortest paths costs. In: Network optimization. Springer, pp 156–171
Campbell H, Hotchkiss R, Bradshaw N, Porteous M (1998) Integrated care pathways. Bmj 316(7125):133–137
doi: 10.1136/bmj.316.7125.133
Canadian Cancer Society (2021) Breast cancer in men. https://www.cancer.ca/en/cancer-information/cancer-type/breast/breast-cancer/breast-cancer-in-men/?region=on . Accessed: May 2022
Cancer Care Ontario (2021) About cancer care ontario. https://www.cancercareontario.ca/en/cancer-care-ontario/about-us , Accessed: May 2022
Cancer Care Ontario (2021) Breast cancer pathway map. https://www.cancercareontario.ca/en/pathway-maps/breast-cancer , Accessed: May 2022
Cancer Care Ontario (2021) Ontario breast screening program (obsp). https://www.cancercareontario.ca/en/cancer-care-ontario/programs/screening-programs/ontario-breast-obsp , Accessed: May 2022
Chan TC, Craig T, Lee T, Sharpe MB (2014) Generalized inverse multiobjective optimization with application to cancer therapy. Oper Res 62(3):680–695
doi: 10.1287/opre.2014.1267
Chan TC, Lee T, Terekhov D (2019) Inverse optimization: closed-form solutions, geometry, and goodness of fit. Manag Sci 65(3):1115–1135
doi: 10.1287/mnsc.2017.2992
Chan TC, Mahmood R, Zhu IY (2021) Inverse optimization: theory and applications. arXiv: 210903920
Chan TC, Eberg M, Forster K, Holloway C, Ieraci L, Shalaby Y, Yousefi N (2022) An inverse optimization approach to measuring clinical pathway concordance. Manag Sci 68(3):1882–1903
doi: 10.1287/mnsc.2021.4100
Charlson ME, Pompei P, Ales KL, MacKenzie CR (1987) A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Diseases 40(5):373–383
doi: 10.1016/0021-9681(87)90171-8
Cheng K, Chan C, Wong R, Leung K, Mui J, Chui W, Cheung E (2012) Integrated care pathway for the personalized care programme for patients with severe mental illness in hong kong. Int J Care Pathways 16(3):72–75
doi: 10.1258/jicp.2012.012006
Cox D (1971) Regression models and life-tables (with discussion). J R Stat Soc 34(2):187–220
van Dam PA, Verheyden G, Sugihara A, Trinh XB, Van Der Mussele H, Wuyts H, Verkinderen L, Hauspy J, Vermeulen P, Dirix L (2013) A dynamic clinical pathway for the treatment of patients with early breast cancer is a tool for better cancer care: implementation and prospective analysis between 2002–2010. World J Surg Oncol 11(1):70
doi: 10.1186/1477-7819-11-70
De Bleser L, Depreitere R, WAELE KD, Vanhaecht K, Vlayen J, Sermeus W (2006) Defining pathways. J Nurs Manag 14(7):553–563
doi: 10.1111/j.1365-2934.2006.00702.x
Esfahani PM, Shafieezadeh-Abadeh S, Hanasusanto GA, Kuhn D (2018) Data-driven inverse optimization with imperfect information. Math Program 167(1):191–234
doi: 10.1007/s10107-017-1216-6
Faragó A, Szentesi Á, Szviatovszki B (2003) Inverse optimization in high-speed networks. Discret Appl Math 129(1):83–98
doi: 10.1016/S0166-218X(02)00235-4
Forster K, Tsang K, Li S, Ieraci L, Murray P, Woltman K, Chmelnitsky D, Holloway C, Kennedy E (2020) Can concordance between actual care received and a pathway map be measured on a population level in ontario? A pilot study. Curr Oncol 27(1):e27
doi: 10.3747/co.27.5349
Heuberger C (2004) Inverse combinatorial optimization: a survey on problems, methods, and results. J Comb Optim 8(3):329–361
doi: 10.1023/B:JOCO.0000038914.26975.9b
Ishwaran H, Kogalur UB, Blackstone EH, Lauer MS et al (2008) Random survival forests. Annals Appl Stat 2(3):841–860
doi: 10.1214/08-AOAS169
Karunakaran M, Barreto SG, Singh MK, Kapoor D, Chaudhary A (2020) Deviations from a clinical pathway post pancreatoduodenectomy predict 90-day unplanned re-admission. Future Oncol 16 (24):1839–1849
doi: 10.2217/fon-2020-0120
Keshavarz A, Wang Y, Boyd S (2011) Imputing a convex objective function. In: 2011 IEEE International symposium on intelligent control (ISIC), IEEE, pp 613–619
van de Klundert J, Gorissen P, Zeemering S (2010) Measuring clinical pathway adherence. J Biomed Inform 43(6):861–872
doi: 10.1016/j.jbi.2010.08.002
Ontario Health (Cancer Care Ontario) (2017) Pathway Map Development Methodology. Tech. rep.
Panella M, Marchisio S, Di Stanislao F (2003) Reducing clinical variations with clinical pathways: do pathways work? Int J Qual Health Care 15(6):509–521
doi: 10.1093/intqhc/mzg057
Quan H, Sundararajan V, Halfon P, Fong A, Burnand B, Luthi JC, Saunders LD, Beck CA, Feasby TE, Ghali WA (2005) Coding algorithms for defining comorbidities in icd-9-cm and icd-10 administrative data. Med Care 43(11):1130–1139
doi: 10.1097/01.mlr.0000182534.19832.83
Rotter T, Kinsman L, James EL, Machotta A, Gothe H, Willis J, Snow P, Kugler J (2010) Clinical pathways: effects on professional practice, patient outcomes, length of stay and hospital costs. Cochrane database of systematic reviews (3)
Rotter T, Kinsman L, James E, Machotta A, Willis J, Snow P, Kugler J (2012) The effects of clinical pathways on professional practice, patient outcomes, length of stay, and hospital costs: Cochrane systematic review and meta-analysis. Eval Health Prof 35(1):3–27
doi: 10.1177/0163278711407313
Schmidt I, Thor J, Davidson T, Nilsson F, Carlsson C (2018) The national program on standardized cancer care pathways in Sweden: observations and findings halfway through. Health Policy 122(9):945–948
doi: 10.1016/j.healthpol.2018.07.012
Troutt MD, Pang WK, Hou SH (2006) Behavioral estimation of mathematical programming objective function coefficients. Manag Sci 52(3):422–434
doi: 10.1287/mnsc.1050.0445
Vanounou T, Pratt W, Fischer JE, Vollmer Jr CM, Callery MP (2007) Deviation-based cost modeling: a novel model to evaluate the clinical and economic impact of clinical pathways. J Am Coll Surg 204(4):570–579
doi: 10.1016/j.jamcollsurg.2007.01.025
Williams R, Buchan IE, Prosperi M, Ainsworth J (2014) Using string metrics to identify patient journeys through care pathways. In: AMIA Annual symposium proceedings, American medical informatics association, vol 2014, p 1208
World Health Organization (2021) Breast cancer now most common form of cancer: who taking action. https://www.who.int/news/item/03-02-2021-breast-cancer-now-most-common-form-of-cancer-who-taking-action . Accessed: May 2022
Xu S, Zhang J (1995) An inverse problem of the weighted shortest path problem. Japan J Ind Appl Math 12(1):47
doi: 10.1007/BF03167381
Yan H, Van Gorp P, Kaymak U, Lu X, Ji L, Chiau CC, Korsten HH, Duan H (2018) Aligning event logs to task-time matrix clinical pathways in bpmn for variance analysis. IEEE J Biomed Health Inform 22(2):311–317
doi: 10.1109/JBHI.2017.2753827
Yang C, Zhang J, Ma Z (1997) Inverse maximum flow and minimum cut problems. Optimization 40(2):147–170
doi: 10.1080/02331939708844306
Zhang J, Cai MC (1998) Inverse problem of minimum cuts. Math Methods Oper Res 47 (1):51–58
doi: 10.1007/BF01193836
Zhang J, Ma Z (1996) A network flow method for solving some inverse combinatorial optimization problems. Optimization 37(1):59–72
doi: 10.1080/02331939608844197
Zhang J, Ma Z, Yang C (1995) A column generation method for inverse shortest path problems. Zeitschrift für Oper Res 41(3):347–358
Zhao Q, Stettner A, Reznik E, Segrè D, Paschalidis IC (2015) Learning cellular objectives from fluxes by inverse optimization. In: 2015 IEEE 54th Annual conference on decision and control (CDC). IEEE, pp 1271–1276