Time trends in hospital stay after hip fracture in Canada, 2004–2012: database study
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Changes in bed management and access policy aimed to shorten Canadian hip fracture hospital stay. Secular trends in hip fracture total, preoperative, and postoperative stay are unknown. Hip fracture stay shortened from 2004 to 2012, mostly from shortening postoperative stay. This may reflect changes in bed management rather than access policy.
To compare the probability of discharge by time after patient admission to hospital with first-time hip fracture over a period of nine calendar years.
We retrieved acute hospitalization records for 169,595 patients 65 years and older, who were admitted to an acute care hospital with hip fracture between 2004 and 2012 in Canada (outside of Quebec). The main outcome measure was cumulative incidence of discharge by inpatient day, accounting for competing events that end hospital stay.
The probability of surgical discharge within 30 days of admission increased from 57.2 % in 2004 to 67.3 % in 2012. The probability of undergoing surgery on day of admission or day after fluctuated around 58.5 % over the study period. For postoperative stay, the discharge probability increased from 6.8 to 12.2 % at day 4 after surgery and from 57.2 to 66.6 % at day 21 after surgery, between 2004 and 2012. The differences across years persisted after adjustment for characteristics of patients, fracture, comorbidity, treatment, type and timing of surgery, and access to care.
Hospital stay following hip fracture shortened substantially between 2004 and 2012 in Canada, mostly due to shortening of postoperative stays. Shorter hospital stays may reflect changes in bed management protocols rather than in access policy.
KeywordsHip fracture Length of stay Postoperative stay Time trends Cumulative incidence Competing risks
We gratefully acknowledge the guidance from the CIHI experts in understanding the discharge abstracts.
Compliance with ethical standards
This research was funded by the Canadian Institute for Health Research. This funder had no role in the design of this study, execution, analyses, data interpretation, or decision to submit results for publication.
Conflicts of interest
The following competing interests are declared: (1) PG has received grants from the Canadian Institutes of Health Research related to this work. PG also receives funding from the Natural Sciences and Engineering Research Council of Canada, the Canadian Foundation for Innovation, and the British Columbia Specialists Services Committee for work around hip fracture care not related to this manuscript. He has also received fees from the BC Specialists Services Committee (for a provincial quality improvement project on redesign of hip fracture care) and from Stryker Orthopedics (as a product development consultant). He is a board member and shareholder in Traumis Surgical Systems Inc. and a board member for the Canadian Orthopedic Foundation. He also serves on the speakers’ bureaus of AO Trauma North America and Stryker Canada. (2) SNM reports grants from Amgen Canada, grants from Merck, personal fees from Amgen Canada, and personal fees from Eli Lilly outside the submitted work. (3) KS is a postdoctoral fellow whose salary is paid by Canadian Institutes of Health Research funding related to this work. (4) BS, LK, EB, LB, JMS, MD, DG, EH declare that they have no conflicts of interest.
- 4.Barrett J, Doyle W, Higgins D (2008) Corporate patient flow: “changing a culture through strategic planning and Accreditation Canada”. http://www.healthcarecan.ca/wp-content/uploads/2014/07/Changing-a-culture-though-strategic-planning-and-Accreditation-Canad.pdf Accessed 24 July 2015
- 5.Waddell J, McMullan J, Lo N, OConnor M, Sheppard L, Mensour M, Palda V, McGlasson R (2010) Improving time to surgery—emergency room, preoperative and immediate postoperative clinical practice guidelines for the management of hip fracture patients. Bone & Joint Health Network. http://boneandjointcanada.com/wp-content/uploads/2014/05/ER-Pre-op-Clinical-Practice-Guidelines-20101101_Final.pdf Accessed 24 July 2015
- 6.Ontario Ministry of Health and Long-Term Care (2005) First ever common benchmarks will allow canadians to measure progress in reducing wait times. www.health.gov.on.ca/english/media/news_releases/archives/nr_05/nr_121205.html Accessed 24 July 2015
- 12.Canadian Institute for Health Information (2007) Health Indicators 2007. CIHI, OttawaGoogle Scholar
- 13.Canadian Institute for Health Information (2011) Data quality documentation for external users: Discharge Abstract Database, 2010–2011. CIHI, OttawaGoogle Scholar
- 17.Kaboli PJ, Go JT, Hockenberry J, Glasgow JM, Johnson SR, Rosenthal GE, Jones MP, Vaughan-Sarrazin M (2012) Associations between reduced hospital length of stay and 30-day readmission rate and mortality: 14-year experience in 129 Veterans Affairs hospitals. Ann Intern Med 157:837–845CrossRefPubMedGoogle Scholar
- 19.Pintilie M (2006) Competing risks, a practical perspective. John Wiley & SonsGoogle Scholar
- 21.Bland JM, Altman DG (1998) Survival probabilities (the Kaplan-Meier method). BMJ 317:572Google Scholar
- 22.Gray B (2014) cmprsk: Subdistribution analysis of competing risks. http://CRAN.R-project.org/package=cmprsk Accessed 24 July 2015
- 23.Gerds T (2014) prodlim: Product-limit estimation for censored event history analysis. http://CRAN.R-project.org/package=prodlim Accessed 24 July 2015
- 24.Hojsgaard S, Halekoh U, Yan J (2006) The R package geepack for generalized estimating equations. J Stat Softw 15:1–11Google Scholar
- 25.R core team (2015) R: a language and environment for statistical computingGoogle Scholar
- 34.Canadian Institute for Health Information (2005) Inpatient hospitalizations and average length od stay trends in Canada, 2003–2004 and 2004–2005. CIHI, OttawaGoogle Scholar
- 35.Canadian Institute for Health Information (2005) Hospital trends in Canada—results of a project to create a historical series of statistical and financial data for Canadian hospitals over twenty-seven years. CIHI, OttawaGoogle Scholar
- 36.Kralj B, Kantarevic J (2012) Primary care model enrolment and hospital length of stay in Ontario: patient rostering associated with reduced length of stay, significant health system savings. Ontario Medical Review. 16–19Google Scholar
- 37.OECD (2011) Average length of stay in hospitals. In: Health at a Glance 2011: OECD Indicators. OECD PublishingGoogle Scholar
- 42.Miani C, Ball S, Pitchforth E, Exley J, King S, Roland M, Fuld J, Nolte E (2014) Organisational interventions to reduce length of stay in hospital: a rapid evidence assessment. health services and delivery researchGoogle Scholar
- 43.Neuburger J, Currie C, Wakeman R, Tsang C, Plant F, De SB, Cromwell DA, van der Meulen J (2015) The impact of a national clinician-led audit initiative on care and mortality after hip fracture in England: an external evaluation using time trends in non-audit data. Med Care 53:686–691CrossRefPubMedPubMedCentralGoogle Scholar