Prolonged Length of Stay and Risk of Unplanned 30-Day Readmission After Elective Spine Surgery: Propensity Score-Matched Analysis of 33,840 Patients.
Adult
Aged
Databases, Factual
/ trends
Elective Surgical Procedures
/ adverse effects
Female
Humans
Length of Stay
/ trends
Male
Middle Aged
Patient Readmission
/ trends
Postoperative Complications
/ diagnosis
Propensity Score
Prospective Studies
Retrospective Studies
Risk Factors
Spinal Diseases
/ diagnosis
Journal
Spine
ISSN: 1528-1159
Titre abrégé: Spine (Phila Pa 1976)
Pays: United States
ID NLM: 7610646
Informations de publication
Date de publication:
15 Sep 2020
15 Sep 2020
Historique:
pubmed:
29
4
2020
medline:
15
12
2020
entrez:
29
4
2020
Statut:
ppublish
Résumé
Retrospective database study. To assess the association between prolonged length of hospital stay (pLOS) (≥4 d) and unplanned readmission in patients undergoing elective spine surgery by controlling the clinical and statistical confounders. pLOS has previously been cited as a risk factor for unplanned hospital readmission. This potentially modifiable risk factor has not been distinguished as an independent risk factor in a large-scale, multi-institutional, risk-adjusted study. Data were collected from the American College of Surgeons National Surgical Quality Improvement Program database. A retrospective propensity score-matched analysis was used to reduce baseline differences between the cohorts. Univariate and multivariate analyses were performed to assess the degree of association between pLOS and unplanned readmission. From the 99,575 patients that fit the inclusion criteria, propensity score matching yielded 16,920 well-matched pairs (mean standard propensity score difference = 0.017). The overall 30-day unplanned readmission rate of these 33,840 patients was 5.5%. The mean length of stay was 2.0 ± 0.9 days and 6.0 ± 4.5 days (P ≤ 0.001) for the control and pLOS groups, respectively. In our univariate analysis, pLOS was associated with postoperative complications, especially medical complications (22.7% vs. 8.3%, P < 0.001). Multivariate analysis of the propensity score-matched population, which adjusted identified confounders (P < 0.02 and ≥10 occurrences), showed pLOS was associated with an increased risk of 30-day unplanned readmission (odds ratio [OR] 1.423, 95% confidence interval [CI] 1.290-1.570, P < 0.001). Patients who undergo elective spine procedures who have any-cause pLOS (≥4 d) are at greater risk of having unplanned 30-day readmission compared with patients with shorter hospital stays. 4.
Sections du résumé
STUDY DESIGN
METHODS
Retrospective database study.
OBJECTIVE
OBJECTIVE
To assess the association between prolonged length of hospital stay (pLOS) (≥4 d) and unplanned readmission in patients undergoing elective spine surgery by controlling the clinical and statistical confounders.
SUMMARY OF BACKGROUND DATA
BACKGROUND
pLOS has previously been cited as a risk factor for unplanned hospital readmission. This potentially modifiable risk factor has not been distinguished as an independent risk factor in a large-scale, multi-institutional, risk-adjusted study.
METHODS
METHODS
Data were collected from the American College of Surgeons National Surgical Quality Improvement Program database. A retrospective propensity score-matched analysis was used to reduce baseline differences between the cohorts. Univariate and multivariate analyses were performed to assess the degree of association between pLOS and unplanned readmission.
RESULTS
RESULTS
From the 99,575 patients that fit the inclusion criteria, propensity score matching yielded 16,920 well-matched pairs (mean standard propensity score difference = 0.017). The overall 30-day unplanned readmission rate of these 33,840 patients was 5.5%. The mean length of stay was 2.0 ± 0.9 days and 6.0 ± 4.5 days (P ≤ 0.001) for the control and pLOS groups, respectively. In our univariate analysis, pLOS was associated with postoperative complications, especially medical complications (22.7% vs. 8.3%, P < 0.001). Multivariate analysis of the propensity score-matched population, which adjusted identified confounders (P < 0.02 and ≥10 occurrences), showed pLOS was associated with an increased risk of 30-day unplanned readmission (odds ratio [OR] 1.423, 95% confidence interval [CI] 1.290-1.570, P < 0.001).
CONCLUSION
CONCLUSIONS
Patients who undergo elective spine procedures who have any-cause pLOS (≥4 d) are at greater risk of having unplanned 30-day readmission compared with patients with shorter hospital stays.
LEVEL OF EVIDENCE
METHODS
4.
Identifiants
pubmed: 32341301
doi: 10.1097/BRS.0000000000003520
pii: 00007632-202009150-00006
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
1260-1268Références
Hines AL, Barrett ML, Jiang HJ, et al. Conditions with the largest number of adult hospital readmissions by payer, 2011: statistical brief #172. Healthcare Cost and Utilization Project (HCUP) Statistical Briefs. Rockville, MD: Agency for Healthcare Research and Quality; 2006.
Henke RM, Karaca Z, Jackson P, et al. Discharge planning and hospital readmissions. Med Care Res Rev 2017; 74:345–368.
Zuckerman RB, Sheingold SH, Orav EJ, et al. Readmissions, observation, and the hospital readmissions reduction program. New Engl J Med 2016; 374:1543–1551.
Kim BD, Smith TR, Lim S, et al. Predictors of unplanned readmission in patients undergoing lumbar decompression: multi-institutional analysis of 7016 patients. J Neurosurg Spine 2014; 20:606–616.
Akins PT, Harris J, Alvarez JL, et al. Risk factors associated with 30-day readmissions after instrumented spine surgery in 14,939 patients: 30-day readmissions after instrumented spine surgery. Spine (Phila Pa 1976) 2015; 40:1022–1032.
Hills J, Sivaganesan A, Khan I, et al. Causes and timing of unplanned 90-day readmissions following spine surgery. Spine (Phila Pa 1976) 2018; 43:991–998.
McCormack RA, Hunter T, Ramos N, et al. An analysis of causes of readmission after spine surgery. Spine (Phila Pa 1976) 2012; 37:1260–1266.
Garg SK, Campbell JP, Anugwom C, et al. Incidence and predictors of readmissions in acute pancreatitis: a nationwide analysis. Pancreas 2018; 47:46–54.
Rinne ST, Graves MC, Bastian LA, et al. Association between length of stay and readmission for COPD. Am J Manag Care 2017; 23:e253–e258.
Pugely AJ, Martin CT, Gao Y, et al. Causes and risk factors for 30-day unplanned readmissions after lumbar spine surgery. Spine (Phila Pa 1976) 2014; 39:761–768.
Akamnonu C, Cheriyan T, Goldstein JA, et al. Unplanned hospital readmission after surgical treatment of common lumbar pathologies: rates and causes. Spine (Phila Pa 1976) 2015; 40:423–428.
Khuri SF, Daley J, Henderson W, et al. Risk adjustment of the postoperative mortality rate for the comparative assessment of the quality of surgical care: results of the National Veterans Affairs Surgical Risk Study. J Am Coll Surg 1997; 185:315–327.
Khuri SF, Henderson WG, Daley J, et al. Successful implementation of the Department of Veterans Affairs’ National Surgical Quality Improvement Program in the private sector: the Patient Safety in Surgery study. Ann Surg 2008; 248:329–336.
Birkmeyer JD, Shahian DM, Dimick JB, et al. Blueprint for a new American College of Surgeons: national surgical quality improvement program. J Am Coll Surg 2008; 207:777–782.
Shiloach M, Frencher SK Jr, Steeger JE, et al. Toward robust information: data quality and inter-rater reliability in the American College of Surgeons National Surgical Quality Improvement Program. J Am Coll Surg 2010; 210:6–16.
Sellers MM, Merkow RP, Halverson A, et al. Validation of new readmission data in the American College of Surgeons National Surgical Quality Improvement Program. J Am Coll Surg 2013; 216:420–427.
Rosenbaum PR, Rubin DB. Constructing a control group using multivariate matched sampling methods that incorporate the propensity score. Am Stat 1985; 39:33–38.
Thoemmes FJ, Kim ES. A systematic review of propensity score methods in the social sciences. Multivariate Behav Res 2011; 46:90–118.
Stukel TA, Fisher ES, Wennberg DE, et al. Analysis of observational studies in the presence of treatment selection bias: effects of invasive cardiac management on AMI survival using propensity score and instrumental variable methods. JAMA 2007; 297:278–285.
Kim RB, Garcia RM, Smith ZA, et al. Impact of resident participation on outcomes after single-level anterior cervical diskectomy and fusion: an analysis of 3265 patients from the American College of Surgeons National Surgical Quality Improvement Program Database. Spine (Phila Pa 1976) 2016; 41:E289–E296.
Austin PC. Optimal caliper widths for propensity-score matching when estimating differences in means and differences in proportions in observational studies. Pharm Stat 2011; 10:150–161.
Piper K, DeAndrea-Lazarus I, Algattas H, et al. Risk factors associated with readmission and reoperation in patients undergoing spine surgery. World Neurosurg 2018; 110:e627–e635.
Cusimano MD, Pshonyak I, Lee MY, et al. Causes of 30-day readmission after neurosurgery of the spine. J Neurosurg Spine 2016; 24:281–290.
Rumalla K, Smith KA, Arnold PM. National rates, causes, risk factors, and outcomes associated with 30-day and 90-day readmissions following degenerative posterior cervical spine surgery utilizing the Nationwide Readmissions Database. Neurosurgery 2017; 81:740–751.
Phan K, Lee NJ, Kothari P, et al. Risk factors for readmissions following anterior lumbar interbody fusion. Spine (Phila Pa 1976) 2018; 43:364–369.
Singh S, Sparapani R, Wang MC. Variations in 30-day readmissions and length of stay among spine surgeons: a national study of elective spine surgery among US Medicare beneficiaries. J Neurosurg Spine 2018; 29:286–291.
Kim BD, Hsu WK, De Oliveira GS Jr, et al. Operative duration as an independent risk factor for postoperative complications in single-level lumbar fusion: an analysis of 4588 surgical cases. Spine (Phila Pa 1976) 2014; 39:510–520.
Bernstein DN, Thirukumaran C, Saleh A, et al. Complications and readmission after cervical spine surgery in elderly patients: an analysis of 1786 patients. World Neurosurg 2017; 103:859.e8–868.e8.
Guan J, Karsy M, Schmidt M, et al. Multivariable analysis of factors affecting length of stay and hospital charges after atlantoaxial fusion. Cureus 2017; 9:e1173.
McGirt MJ, Parker SL, Chotai S, et al. Predictors of extended length of stay, discharge to inpatient rehab, and hospital readmission following elective lumbar spine surgery: introduction of the Carolina-Semmes Grading Scale. J Neurosurg Spine 2017; 27:382–390.
Passias PG, Jalai CM, Worley N, et al. Predictors of hospital length of stay and 30-day readmission in cervical spondylotic myelopathy patients: an analysis of 3057 patients using the ACS-NSQIP Database. World Neurosurg 2018; 110:e450–e458.
Wolkewitz M, Zortel M, Palomar-Martinez M, et al. Landmark prediction of nosocomial infection risk to disentangle short- and long-stay patients. J Hosp Infect 2017; 96:81–84.
Amin AN, Girard F, Samama MM. Does ambulation modify venous thromboembolism risk in acutely ill medical patients? Thromb Haemost 2010; 104:955–961.
Slover J, Mullaly K, Karia R, et al. The use of the risk assessment and prediction tool in surgical patients in a bundled payment program. Int J Surg 2017; 38:119–122.
Ali ZS, Ma TS, Ozturk AK, et al. Pre-optimization of spinal surgery patients: development of a neurosurgical enhanced recovery after surgery (ERAS) protocol. Clin Neurol Neurosurg 2018; 164:142–153.