Untitled

El‐Darzi, Elia; Vasilakis, Christos; Chaussalet, Thierry J.; Millard, Peter

doi:10.1023/a:1019054921219

Cited by 140 publications

(17 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Delays from hospital admission to hip fracture surgery is one factor that has been implicated as being associated with increased risk of medical complications(1–5). Length of hospital stay (LOS) is an important factor that determines resource utilization and costs(6, 7). Identifying and modifying factors associated with delays to surgery (DTS) and LOS have the potential to impact medical expenditures and quality of care for hip fracture patients.…”

Section: Introductionmentioning

confidence: 99%

Factors Affecting Delay to Surgery and Length of Stay for Patients With Hip Fracture

Ricci

Brandt

McAndrew

et al. 2015

Journal of Orthopaedic Trauma

108

View full text Add to dashboard Cite

Purpose The purpose of this study was to determine factors, including day of week of hospital admission, associated with delay to surgery (DTS) and increased length of stay (LOS) in patients with hip fractures. Design Retrospective Setting Level I Trauma Center Patients and Methods Six hundred and thirty five consecutive patients admitted to a single hospital between January 1999 and July 2006 age 65 or older with a hip fracture (OTA 31) were identified retrospectively from an orthopaedic database. Demographic data, ASA score, hospital admission and discharge dates, the date of surgery, and details of any pre-operative cardiac testing were extracted from the hospital record. These data were used to identify the day of week for hospital admission and to calculate days for DTS and hospital LOS. Linear regression was used to identify independent variables associated with DTS and increased LOS. Intervention All patients underwent surgical treatment of a hip fracture (OTA 31) Main Outcome Measures Factors effecting DTS and LOS. Results Independent factors associated with DTS included the day of week for hospital admission, ASA score, and the need for pre-operative cardiac testing. Patients admitted Thursday through Saturday had longer DTS (mean 2.2 to 2.7 days) than did patients admitted other days (mean 1.7 – 1.8). Delay to surgery increased for increasing ASA: 1.4 days for ASA 2; 2.0 days for ASA 3; and 3.0 days for ASA 4. Those requiring pre-operative cardiac testing had an increased number of days to surgery (mean 3.2 days) than those without (1.7 days). Independent factors associated with increasing hospital LOS included ASA, the need for pre-operative cardiac testing, male gender, and day of admission. Length of stay increased for increasing ASA: 6.3 days for ASA 2; 8.1 days for ASA 3; and 10.1 days for ASA 4. Those requiring pre-operative cardiac testing had an increased LOS (mean 9.4 days) than those without (7.3 days). Male patients had a longer LOS (mean 9.8 days) than did females (mean 7.3 days). Patients admitted on Thursday or Friday (mean 8.5 – 9.1 days) had longer LOS than those admitted on other days (mean 7.3 – 7.9 days). Conclusions This is the first study to consider and identify day of admission and need for pre-operative cardiac tests as determinants of DTS and LOS for geriatric hip fracture patients. Relative scarcity of weekend hospital resources, when present, may be responsible for these delays. This study also confirms that patient medical condition as measured by ASA affects both DTS and LOS.

show abstract

Section: Introductionmentioning

confidence: 99%

Factors Affecting Delay to Surgery and Length of Stay for Patients With Hip Fracture

Ricci

Brandt

McAndrew

et al. 2015

Journal of Orthopaedic Trauma

108

View full text Add to dashboard Cite

show abstract

“…Constraint (2) and (3) balances the estimated/actual time for surgeries scheduled with opening hours at the operating theatre included overtime in constraint (3). Constraint (4) and (5) connects patients scheduled for surgery from one simulation step to the next simulation step and keeps track of possible cancellations.…”

Section: Discussionmentioning

confidence: 99%

“…We compose a queuing system which includes an optimization model as further described below and the three characteristics earlier expressed by E. El-Darzi et al [3]:…”

Section: Queuing Systemmentioning

confidence: 99%

“…The literature reports on several studies which analyse the performance of medical clinics, i.e. emergency departments, operating room department, geriatric departments and outpatient clinics which use simulation and/or optimization techniques [3][4][5][6]. Marshal et al [7] emphasize the importance of modelling the patient-flow when analysing the complexity of healthcare activities.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Analysing management policies for operating room planning using simulation

Persson

2009

Health Care Manag Sci

View full text Add to dashboard Cite

In this paper we analyse the operating room planning at a department of orthopaedic surgery in Sweden. We focus on the problem of meeting the uncertainty in demand of patient arrival and surgery duration and at the same time maximizing the utilization of operating room (OR) time. With a discrete-event model we simulate how different management polices affect different performance metrics such as patient waiting time, cancellations and the utilization of OR time. The experiments show that the performance of the operating room department can be improved significantly by applying a different policy in reserving OR-capacity for emergency cases together with a policy to increase staff in stand-by. Moreover, the developed simulation model provides estimates for a what-if situation related to the prognosis of an increasing number of hip-joint replacements.

show abstract

“…[18] Simulation modeling has been shown to be an effective tool used in the healthcare setting in reducing wait times, optimizing patient flow, and decreasing bottlenecks. [19,20] While many studies indicate observation units have positive implications for hospitals, further research is needed to test the effectiveness of a COU at an AMC, through simulation modeling. It is important to assess the optimal patient-type mix in an observation unit.…”

Section: Introductionmentioning

confidence: 99%

A new look at observation units: evidence-based approach

Shah

Subbarao

Noonan

et al. 2015

JHA

View full text Add to dashboard Cite

Background: Observation patient classification and billing are an important focus area for recovery audit contractors (RACs) and creation of a centralized observation unit (COU) could be a good strategy for Academic Medical Centers (AMCs) to improve care and fiscal management of a growing observation/patient volume. Objective: To define and investigate the feasibility of a dual purpose COU at an AMC. Methods: Retrospective data analysis and domain expertise were utilized to define potential observation patients. A pre/post study design was used to test the effects of three strategies. These strategies included: 1) all observation patients; 2) all observation patients except Emergency Department (ED) sourced patients; and 3) only post-procedural and post-surgical observation patients measured on unit efficiency metrics (i.e., bed placement wait time and occupancy rate), through simulation modeling. In addition, domain experts determined operational feasibility of each strategy based on multiple criteria. Results:Results of the simulation model demonstrated two feasible strategies that included COUs focusing on non-ED sourced observation patients on inpatient units (wait time ≤ 1 minute; occupancy rate = 8.26 ± 3.8 beds) and post-surgical and postprocedural observation patients only (wait time ≤ 1 minute; occupancy rate = 5.15 ± 3.04 beds). Conclusions: A multi-purpose COU with clear definitions and patient care protocols for observation patients allows efficient medical care to be delivered, facilitates correct documentation and billing to third-party payers, and frees capacity on inpatient care units. Additional hospital revenue and reimbursement with modest investment given clinical feasibility bolster financial viability of a COU.

show abstract

Untitled

Cited by 140 publications

References 12 publications

Factors Affecting Delay to Surgery and Length of Stay for Patients With Hip Fracture

Factors Affecting Delay to Surgery and Length of Stay for Patients With Hip Fracture

Analysing management policies for operating room planning using simulation

A new look at observation units: evidence-based approach

Contact Info

Product

Resources

About