Disparities in neurosurgical care: Using length of stay to evaluate efficiency of care in New York City hospitals

Abstract

Objective: We sought to analyze public and private hospital patient cohorts in New York City (NYC) to assess differences in hospital access and outcomes from 2009-2022.
Methods: Inpatient neurosurgical discharges, as determined by APR-DRG codes, from 2009-2022 were aggregated for seven NYC hospitals, four private and three public, via the Statewide Planning and Research Cooperative System (SPARCS). Statistical analyses (Z-tests) were performed in Python.
Results: 325,351 patients were identified, 223,361 private and 101,990 public. Private hospitals had lower high-severity to low-severity and higher high-mortality to low-mortality risk ratios relative to public hospitals (p <.001). Public hospitals treated a higher proportion of stroke and trauma (p <.001). Average length of stay (LOS) was shorter at private hospitals compared to public (5.3 vs. 7.1 days, p <.001). Statistical significance remained when stratifying for illness severity and elective versus non-elective surgery status. Interestingly, cranial trauma cases were associated with a longer LOS in private hospitals relative to public (7.9 vs. 5.7 days, p <.001).
Conclusions: While many factors influence outcomes in private versus public hospitals, LOS can mark the efficiency of care. LOS was shorter at private hospitals in all instances except with cranial trauma. Care efficiency is important for hospital reimbursement, which can directly impact available resources for patient care. These findings emphasize the need to further analyze patient accessibility to neurosurgical care at private hospitals and the resources necessary to support neurosurgical practices within public hospitals.

Keywords

Neurosurgery / New York City / Health disparities / Hospital efficiency

ACKNOWLEDGEMENTS

All data were obtained from the Statewide Planning and Research Cooperative System (SPARCS) as collected by the New York State Department of Health.

AUTHORS CONTRIBUTIONS

Alexander N. Eremiev: submission of final manuscript, manuscript writing, formulation of project; Cordelia Orillac, Camiren Carter, Eric Grin, Derek Huell, Sophie Yagoda: manuscript writing; Karl Sangwon: data analysis, figure production; David B. Kurland: manuscript writing, figure production; David H. Harter: supervision of project, review of manuscript.

FUNDING

NA.

CONFLICTS OF INTEREST DISCLOSURE

The authors declare they have no conflicts of interest.

INFORMED CONSENT

Obtained.

ETHICS APPROVAL

The Publication Ethics Committee of the Sciedu Press. The journal’s policies adhere to the Core Practices established by the Committee on Publication Ethics (COPE).

PROVENANCE AND PEER REVIEW

Not commissioned; externally double-blind peer reviewed.

DATA AVAILABILITY STATEMENT

This publication was produced publicly available data reports from the New York Department of Health. Reports from 2009 to 2021 titled “Hospital Inpatient Discharges (SPARCS De-Identified): Year” were utilized. Data are publicly accessible at the following website: https://health.data.ny.gov/browse. The New York State Department of Health makes no representation, warranty or guarantee relating to the data or analyses derived from these data.[42-55]

DATA SHARING STATEMENT

No additional data are available.

OPEN ACCESS

This is an open-access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/4.0/).

COPYRIGHTS

Copyright for this article is retained by the author(s), with first publication rights granted to the journal.

References

[1] Owolo E, Seas A, Bishop B, et al. Scoping review on the state of racial disparities literature in the treatment of neurosurgical disease: a call for action. 2023; 55(5): E3. https://doi.org/10.3171/2023.8.FOCUS23466E3.

[2] Pugazenthi S, Barpujari A, Patel S, et al. A Systematic Review of the State of Neurosurgical Disparities Research: Past, Present, and Future. World Neurosurg. 2024; 182: 193-199.e4. https://doi.org/10.1016/j.wneu.2023.11.127

[3] Rana RH, Alam K, Gow J. Selection of private or public hospital care: examining the care-seeking behaviour of patients with private health insurance. BMC Health Serv. Res. 2020; 20: 380. https://doi.org/10.1186/s12913-020-05253-y

[4] Lucifora C. Management practices in hospitals: A public-private comparison. PLoS One. 2023; 18: e0282313. https://doi.org/10.1371/journal.pone.0282313

[5] Anesi GL, Kerlin MP. The impact of resource limitations on care delivery and outcomes: routine variation, the coronavirus disease 2019 pandemic, and persistent shortage. Curr. Opin. Crit. Care. 2021; 27: 513-519. https://doi.org/10.1097/MCC.0000000000000859

[6] Mbau R, Musiega A, Nyawira L, et al. Analysing the Efficiency of Health Systems: A Systematic Review of the Literature. Appl. Health Econ. Health Policy. 2023; 21: 205-224. https://doi.org/10.1007/s40258-022-00785-2

[7] Asbu EZ, Masri MD, Al Naboulsi M. Determinants of hospital efficiency: A literature review. Int. J. Healthc. Inf. Syst. Inform. 2020; 6: 44. https://doi.org/10.5430/ijh.v6n2p44

[8] Dehouche N, Viravan S, Santawat U, et al. Hospital length of stay: A cross-specialty analysis and Beta-geometric model. PLoS One. 2023; 18: e0288239. https://doi.org/10.1371/journal.pone.0288239e0288239.

[9] Buttigieg SC, Abela L, Pace A. Variables affecting hospital length of stay: a scoping review. J. Health Organ. Manag. 2018; 32: 463-493. https://doi.org/10.1108/JHOM-10-2017-0275

[10] PLOS ONE Staff. Correction: Risk factors associated with prolonged hospital length-of-stay: 18-year retrospective study of hospitalizations in a tertiary healthcare center in Mexico. PLoS One. 2018; 13: e0209944. https://doi.org/10.1371/journal.pone.0209944e0209944.

[11] Besa JJV, Masamayor EMI, Tamondong-Lachica DR, et al. Prevalence and predictors of prolonged length of stay among patients admitted under general internal medicine in a tertiary government hospital in Manila, Philippines: a retrospective cross-sectional study. BMC Health Serv. Res. 2023; 23: 50. https://doi.org/10.118 6/s12913-022-08885-4

[12] Garba DL, Fadalla T, Sarpong K, et al. Access to training in neurosurgery (Part 2): The costs of pursuing neurosurgical training. Brain Spine. 2022; 2: 100927. https://doi.org/10.1016/j.bas.20 22.100927

[13] New York NY. Available from: https://datausa.io/profile/geo/new-york-ny

[14] Yancy CW. COVID-19 and African Americans. JAMA. 2020; 323: 1891-1892. https://doi.org/10.1001/jama.2020.6548

[15] New York city health indicators by race/ethnicity, 2018-2020. Available from: https://www.health.ny.gov/statistics/commu nity/minority/county/newyorkcity.htm

[16] Haider A. H, Weygandt PL, Bentley JM, et al. Disparities in trauma care and outcomes in the United States: a systematic review and meta-analysis. J. Trauma Acute Care Surg. 2013; 74(5): 1195-205. https://doi.org/10.1097/01586154-201305000-00002

[17] Chavez MA, Bogert JN, Soe-Lin H, et al. Length of stay and trauma center finances: A disparity of payer source at a Level I trauma center. J. Trauma Acute Care Surg. 2022; 92(4): 683-690. https://doi.org/10.1097/TA.0000000000003529

[18] Stocker B, Weiss HK, Weingarten N, et al. Predicting length of stay for trauma and emergency general surgery patients. Am. J. Surg. 2020; 220(3): 757-764. https://doi.org/10.1016/j.amjsurg.2020.01.055

[19] Rapoport J, Teres D, Zhao Y, et al. Length of stay data as a guide to hospital economic performance for ICU patients. Med. Care. 2003; 41: 386-397. https://doi.org/10.1097/01.MLR.0000053021.93198.96

[20] Di Fusco M, Shea KM, Lin J, et al. Health outcomes and economic burden of hospitalized COVID-19 patients in the United States. J. Med. Econ. 2021; 24(1): 308-317. https://doi.org/10.1080/13696998.2021.1886109

[21] Brasel KJ, Lim HJ, Nirula R, et al. Length of stay: an appropriate quality measure? Arch. Surg. 2007; 142: 461-5; discussion 465-6. https://doi.org/10.1001/archsurg.142.5.461

[22] Rapoport J, Teres D, Lemeshow S, et al. Explaining variability of cost using a severity-of-illness measure for ICU patients. Med. Care. 1990; 28: 338-348. https://doi.org/10.1097/00005650-199004000-00005

[23] Oye RK, Bellamy PE. Patterns of resource consumption in medical intensive care. Chest. 1991; 99: 685-689. https://doi.org/10.1378/chest.99.3.685

[24] Detsky AS, Stricker SC, Mulley AG, et al. Prognosis, survival, and the expenditure of hospital resources for patients in an intensive-care unit. N. Engl. J. Med. 1981; 305: 667-672. https://doi.org/10.1056/NEJM198109173051204

[25] Danielsen E, Mjåset C, Ingebrigtsen T, et al. A nationwide study of patients operated for cervical degenerative disorders in public and private hospitals. Sci. Rep. 2022; 12: 1-8. https://doi.org/10.1038/s41598-022-17194-z

[26] Zheng J, Tisdale RL, Heidenreich PA, et al. Disparities in Hospital Length of Stay Across Race and Ethnicity Among Patients With Heart Failure. Circ. Heart Fail. 2022; 15. https://doi.org/10.1161/CIRCHEARTFAILURE.121.009362

[27] Parra RS, Feitosa MR, Valerio FP, et al. Laparoscopic bowel resection of deep infiltrating endometriosis. Comparative outcomes of a public teaching hospital and a referral private hospital. Acta Cir. Bras. 2020; 35. https://doi.org/10.1590/s0102-865020200090000008

[28] Linzey JR, Foshee R, Moriguchi F, et al. Length of Stay Beyond Medical Readiness in a Neurosurgical Patient Population and Associated Healthcare Costs. Neurosurgery. 2021; 88(3): E259-E264. https://doi.org/10.1093/neuros/nyaa535

[29] Lubelski D, Ehresman J, Feghali J, et al. Prediction calculator for nonroutine discharge and length of stay after spine surgery. Spine J. 2020; 20(7): 1154-1158. https://doi.org/10.1016/j.spinee.2020.02.022

[30] Akbari SHA, Rizvi AA, CreveCoeur TS, et al. Socioeconomic and demographic factors in the diagnosis and treatment of Chiari malformation type I and syringomyelia. J. Neurosurg. Pediatr. 2021; 29(3): 288-297.

[31] Krell RW, Girotti ME, Dimick JB. Extended length of stay after surgery: complications, inefficient practice, or sick patients? JAMA Surg. 2014; 149: 815-820. https://doi.org/10.1001/jamasurg.2014.629

[32] Murphy ME, Noetscher CM. Reducing hospital inpatient lengths of stay. J. Nurs. Care Qual. 1999; Spec No: 40-54. https://doi.or g/10.1097/00001786-199911000-00006

[33] Han TS, Murray P, Robin J, et al. Evaluation of the association of length of stay in hospital and outcomes. Int. J. Qual. Health Care. 2022; 34(2): mzab160. https://doi.org/10.1093/intqhc/mzab160

[34] Singh R, Zamanian C, Bcharah G, et al. High-Value Epilepsy Care in the United States: Predictors of Increased Costs and Complications from the National Inpatient Sample Database 2016-2019. World Neurosurg. 2024; 185: e1230-e1243. https://doi.org/10.1016/j.wneu.2024.03.061

[35] Hines K, Mouchtouris N, Getz C, et al. Bundled Payment Models in Spine Surgery. Global Spine J. 2021; 11(1_suppl): 7S-13S. https://doi.org/10.1177/2192568220974977

[36] Joynt Maddox KE, Orav EJ, Zheng J, et al. Evaluation of Medicare’s Bundled Payments Initiative for Medical Conditions. N. Engl. J. Med. 2018; 379: 260-269. https://doi.org/10.1056/NEJMsa1801569

[37] Medress Z, Ugiliweneza B, Parker J, et al. Simulating Episode-Based Bundled Payments for Cranial Neurosurgical Procedures. Neurosurgery. 2020; 87: 86-95. https://doi.org/10.1093/neuros/nyz353

[38] Khan HA, Hill TC, Suryadevara CM, et al. Development and implementation of an Enhanced Recovery After Cranial Surgery pathway following supratentorial tumor resection at a tertiary care center. Neurosurg. Focus. 2023; 55(6): E4. https://doi.org/10.3171/2023.9.FOCUS23552E4.

[39] Debono B, Wainwright TW, Wang MY, et al. Consensus statement for perioperative care in lumbar spinal fusion: Enhanced Recovery After Surgery (ERASR ) Society recommendations. Spine J. 2021; 21(5): 729-752. https://doi.org/10.1016/j.spinee.2021.01.001

[40] Dietz N, Sharma M, Adams S, et al. Enhanced Recovery After Surgery (ERAS) for Spine Surgery: A Systematic Review. World Neurosurg. 2019; 130: 415-426. https://doi.org/10.1016/j.wneu.2019.06.181

[41] Howard SD, Aysola J, Montgomery CT, et al. Post-operative neurosurgery outcomes by race/ethnicity among enhanced recovery after surgery (ERAS) participants. Clin. Neurol. Neurosurg. 2023; 24: 107561. https://doi.org/10.1016/j.clineuro.2022.107561

[42] New York State Department of Health. Hospital inpatient discharges (SPARCS DE-identified): 2019. 2022.

[43] New York State Department of Health. Hospital inpatient discharges (SPARCS DE-identified): 2009. 2013.

[44] New York State Department of Health. Hospital inpatient discharges (SPARCS DE-identified): 2010. 2013.

[45] New York State Department of Health. Hospital inpatient discharges (SPARCS DE-identified): 2011. 2013.

[46] New York State Department of Health. Hospital inpatient discharges (SPARCS DE-Identified): 2012. 2013.

[47] New York State Department of Health. Hospital inpatient discharges (SPARCS DE-identified): 2013. 2014.

[48] New York State Department of Health. Hospital inpatient discharges (SPARCS DE-identified): 2014. 2016.

[49] New York State Department of Health. Hospital inpatient discharges (SPARCS DE-identified): 2015. 2017.

[50] New York State Department of Health. Hospital inpatient discharges (SPARCS DE-identified): 2016. 2018.

[51] New York State Department of Health. Hospital inpatient discharges (SPARCS DE-identified): 2017. 2019.

[52] New York State Department of Health. Hospital inpatient discharges (SPARCS DE-identified): 2018. 2022.

[53] New York State Department of Health. Hospital inpatient discharges (SPARCS DE-identified): 2021. 2022.

[54] New York State Department of Health. Hospital inpatient discharges (SPARCS DE-identified): 2020. 2022.

[55] New York State Department of Health. Hospital inpatient discharges (SPARCS DE-identified): 2022. 2024.