Reporting and evaluating wait times for urgent hip fracture surgery in Ontario, Canada

BACKGROUND: Although a delay of 24 hours for hip fracture repair is associated with medical complications and costs, it is unknown how long patients wait for surgery for hip fracture. We describe novel methods for measuring exact urgent and emergent surgical wait times (in hours) and the factors that influence them. METHODS: Adults aged 45 years and older who underwent surgery for hip fracture (the most common urgently performed procedure) in Ontario, Canada, between 2009 and 2014 were eligible. Validated data from linked health administrative databases were used. The primary outcome was the time elapsed from hospital arrival recorded in the National Ambulatory Care Reporting System until the time of surgery recorded in the Discharge Abstract Database (in hours). The influence of patient, physician and hospital factors on wait times was investigated using 3-level, hierarchical linear regression models. RESULTS: Among 42 230 patients with hip fracture, the mean (SD) wait time for surgery was 38.76 (28.84) hours, and 14 174 (33.5%) patients underwent surgery within 24 hours. Variables strongly associated with delay included time for hospital transfer (adjusted increase of 26.23 h, 95% CI 25.38 to 27.01) and time for preoperative echocardiography (adjusted increase of 18.56 h, 95% CI 17.73 to 19.38). More than half of the hospitals (37 of 72, 51.4%), compared with 4.8% of surgeons and 0.2% of anesthesiologists, showed significant differences in the risk-adjusted likelihood of delayed surgery. INTERPRETATION: Exact wait times for urgent and emergent surgery can be measured using Canada’s administrative data. Only one-third of patients received surgery within the safe time frame (24 h). Wait times varied according to hospital and physician factors; however, hospital factors had a larger impact.

[1]  A. Nathens,et al.  Medical Costs of Delayed Hip Fracture Surgery , 2018, The Journal of bone and joint surgery. American volume.

[2]  A. Nathens,et al.  Association Between Wait Time and 30-Day Mortality in Adults Undergoing Hip Fracture Surgery , 2017, JAMA.

[3]  A. Jha.  Public Reporting of Surgical Outcomes: Surgeons, Hospitals, or Both? , 2017, JAMA.

[4]  P. Guy,et al.  Feasibility of using administrative data for identifying medical reasons to delay hip fracture surgery: a Canadian database study , 2017, BMJ Open.

[5]  M. Fu,et al.  Surgery for a fracture of the hip within 24 hours of admission is independently associated with reduced short‐term post‐operative complications , 2017, The bone & joint journal.

[6]  P. Guy,et al.  Patient and system factors of time to surgery after hip fracture: a scoping review , 2017, BMJ Open.

[7]  Alan J. Forster,et al.  Association of delay of urgent or emergency surgery with mortality and use of health care resources: a propensity score–matched observational cohort study , 2017, Canadian Medical Association Journal.

[8]  A. Nathens,et al.  Timing of femoral shaft fracture fixation following major trauma: A retrospective cohort study of United States trauma centers , 2017, PLoS medicine.

[9]  H. Kreder,et al.  Outcomes of After-Hours Hip Fracture Surgery , 2017, The Journal of bone and joint surgery. American volume.

[10]  M. Whitehouse,et al.  The association between the day of the week of milestones in the care pathway of patients with hip fracture and 30-day mortality: findings from a prospective national registry – The National Hip Fracture Database of England and Wales , 2017, BMC Medicine.

[11]  M. Zhan,et al.  Timing of Hip Fracture Surgery and 30-Day Outcomes. , 2016, Orthopedics.

[12]  L. Beaupre,et al.  In-hospital mortality after hip fracture by treatment setting , 2016, Canadian Medical Association Journal.

[13]  S. Jaglal,et al.  Post-acute pathways among hip fracture patients: a system-level analysis , 2016, BMC Health Services Research.

[14]  E. Livingston,et al.  Managing the Risks of Concurrent Surgeries. , 2016, JAMA.

[15]  A. Nathens,et al.  Redefining “dead on arrival”: Identifying the unsalvageable patient for the purpose of performance improvement , 2015, The journal of trauma and acute care surgery.

[16]  D. Juurlink,et al.  Outcomes of Daytime Procedures Performed by Attending Surgeons after Night Work. , 2015, The New England journal of medicine.

[17]  L. Lix,et al.  Reduced time to surgery improves mortality and length of stay following hip fracture: results from an intervention study in a Canadian health authority. , 2015, Canadian journal of surgery. Journal canadien de chirurgie.

[18]  J. Zuckerman,et al.  Delay in Hip Fracture Surgery: An Analysis of Patient-Specific and Hospital-Specific Risk Factors , 2015, Journal of orthopaedic trauma.

[19]  R. Mennicken,et al.  The volume-outcome relationship and minimum volume standards--empirical evidence for Germany. , 2015, Health economics.

[20]  M. Gardner,et al.  Factors Affecting Delay to Surgery and Length of Stay for Patients With Hip Fracture , 2015, Journal of orthopaedic trauma.

[21]  G. Guyatt,et al.  Accelerated care versus standard care among patients with hip fracture: the HIP ATTACK pilot trial , 2013, Canadian Medical Association Journal.

[22]  T. Gomes,et al.  A Population‐Based Assessment of the Drug Interaction Between Levothyroxine and Warfarin , 2012, Clinical pharmacology and therapeutics.

[23]  A. Liberati,et al.  Timing Matters in Hip Fracture Surgery: Patients Operated within 48 Hours Have Better Outcomes. A Meta-Analysis and Meta-Regression of over 190,000 Patients , 2012, PloS one.

[24]  W. Wodchis,et al.  Direct health-care costs attributed to hip fractures among seniors: a matched cohort study , 2012, Osteoporosis International.

[25]  Kazem Mohammad,et al.  Let Continuous Outcome Variables Remain Continuous , 2012, Comput. Math. Methods Medicine.

[26]  R. Weiss,et al.  Dichotomizing Continuous Variables in Statistical Analysis , 2012, Medical decision making : an international journal of the Society for Medical Decision Making.

[27]  P. Rucci,et al.  Determinants of surgical delay for hip fracture. , 2011, The surgeon : journal of the Royal Colleges of Surgeons of Edinburgh and Ireland.

[28]  G. Guyatt,et al.  Effect of early surgery after hip fracture on mortality and complications: systematic review and meta-analysis , 2010, Canadian Medical Association Journal.

[29]  J. Frood,et al.  Improving measures of hip fracture wait times: a focus on ontario. , 2010, Healthcare quarterly.

[30]  M. Pasquale,et al.  The Trauma Quality Improvement Program of the American College of Surgeons Committee on Trauma. , 2009, Journal of the American College of Surgeons.

[31]  T. To,et al.  Identifying Individuals with Physcian Diagnosed COPD in Health Administrative Databases , 2009, COPD.

[32]  James G Wright,et al.  Patient characteristics affecting the prognosis of total hip and knee joint arthroplasty: a systematic review. , 2008, Canadian journal of surgery. Journal canadien de chirurgie.

[33]  D. Redelmeier,et al.  Introducing a methodology for estimating duration of surgery in health services research. , 2008, Journal of clinical epidemiology.

[34]  Karen Tu,et al.  Accuracy of administrative databases in identifying patients with hypertension , 2007, Open medicine : a peer-reviewed, independent, open-access journal.

[35]  L. Bisanti,et al.  The influence of socioeconomic status on utilization and outcomes of elective total hip replacement: a multicity population-based longitudinal study. , 2007, International journal for quality in health care : journal of the International Society for Quality in Health Care.

[36]  Jean-Marie Bamvita,et al.  Is the delay to surgery for isolated hip fracture predictive of outcome in efficient systems? , 2005, The Journal of trauma.

[37]  S. Jaglal,et al.  The effect of hospital type and surgical delay on mortality after surgery for hip fracture. , 2005, The Journal of bone and joint surgery. British volume.

[38]  R. K. Peterson,et al.  The spinoglenoid ligament. Anatomy, morphology, and histological findings. , 2005, The Journal of bone and joint surgery. American volume.

[39]  J. Robins,et al.  A Structural Approach to Selection Bias , 2004, Epidemiology.

[40]  M. Mamdani,et al.  Lipid-lowering therapy with statins in high-risk elderly patients: the treatment-risk paradox. , 2004, JAMA.

[41]  C. Charalambous,et al.  Factors delaying surgical treatment of hip fractures in elderly patients. , 2003, Annals of the Royal College of Surgeons of England.

[42]  Janet E Hux,et al.  Diabetes in Ontario: determination of prevalence and incidence using a validated administrative data algorithm. , 2002, Diabetes care.

[43]  Harvey Goldstein,et al.  Multiple membership multiple classification (MMMC) models , 2001 .

[44]  Harvey Goldstein,et al.  Multilevel Cross-Classified Models , 1994 .

[45]  D. Ragland,et al.  Dichotomizing Continuous Outcome Variables: Dependence of the Magnitude of Association and Statistical Power on the Cutpoint , 1992, Epidemiology.

[46]  R. Deyo,et al.  Adapting a clinical comorbidity index for use with ICD-9-CM administrative databases. , 1992, Journal of clinical epidemiology.

[47]  P. Pronovost,et al.  A Methodological Critique of the ProPublica Surgeon Scorecard. , 2016, Rand health quarterly.

[48]  D. Juurlink,et al.  Enhancing the effectiveness of health care for Ontarians through research Canadian Institute for Health Information Discharge Abstract Database : A Validation Study , 2006 .