An outcome study on average length of stay following total hip and knee replacement

2002 ◽  
Vol 6 (3) ◽  
pp. 161-169 ◽  
Author(s):  
Seamus O'Brien
2021 ◽  
Vol 2 (2) ◽  
pp. 30-34
Author(s):  
Jayme Bristol

Background: Total hip replacement surgeries are one of the most common orthopedic surgeries performed today1. This number continues to rise. One way to accommodate the growing need for inpatient orthopedic beds is through high hospital turnover. High turnover can possibly be accomplished through early ambulation. The goal of the study is to see if standing or walking before eight hours post-operative decreased overall length of hospital stay. Methods: This research study is a retrospective chart review that looked at 92 randomly selected general anesthesia total hip replacement patients from Nebraska Medicine in Omaha, NE from August 2017 to August 2018. This research study makes a clear definition of early ambulation after total hip replacement surgery: standing or walking within eight hours of surgery. Results: From the analyzed research the average length of stay for all 92 total hip replacement patients was 4.23 days. For those total hip replacement patients who were ambulated within eight hours of surgery completion the average length of stay was 2.83 days. For the total hip replacement patients who were ambulated after eight hours of surgery completion the average length of stay was 5.14 days. Conclusion: There is a statistically significant difference in length of hospital stay for total hip replacement patients at Nebraska Medicine who were ambulated within eight hours of surgery completion compared to those who were not.


2020 ◽  
Vol 41 (S1) ◽  
pp. s173-s174
Author(s):  
Keisha Gustave

Background: Methicillin-resistant Staphylococcus aureus(MRSA) and carbapenem-resistant Klebsiella pneumoniae (CRKP) are a growing public health concern in Barbados. Intensive care and critically ill patients are at a higher risk for MRSA and CRKP colonization and infection. MRSA and CRKP colonization and infection are associated with a high mortality and morbidly rate in the intensive care units (ICUs) and high-dependency units (HDUs). There is no concrete evidence in the literature regarding MRSA and CRKP colonization and infection in Barbados or the Caribbean. Objectives: We investigated the prevalence of MRSA and CRKP colonization and infection in the patients of the ICU and HDU units at the Queen Elizabeth Hospital from 2013 to 2017. Methods: We conducted a retrospective cohort analysis of patients admitted to the MICU, SICU, and HDU from January 2013 through December 2017. Data were collected as part of the surveillance program instituted by the IPC department. Admissions and weekly swabs for rectal, nasal, groin, and axilla were performed to screen for colonization with MRSA and CRKP. Follow-up was performed for positive cultures from sterile isolates, indicating infection. Positive MRSA and CRKP colonization or infection were identified, and patient notes were collected. Our exclusion criteria included patients with a of stay of <48 hours and patients with MRSA or CRKP before admission. Results: Of 3,641 of persons admitted 2,801 cases fit the study criteria. Overall, 161 (5.3%) were colonized or infected with MRSA alone, 215 (7.67%) were colonized or infected with CRKP alone, and 15 (0.53%) were colonized or infected with both MRSA and CRKP. In addition, 10 (66.6%) of patients colonized or infected with MRSA and CRKP died. Average length of stay of patients who died was 50 days. Conclusions: The results of this study demonstrate that MRSA and CRKP cocolonization and coinfection is associated with high mortality in patients within the ICU and HDU units. Patients admitted to the ICU and HDU with an average length of stay of 50 days are at a higher risk for cocolonization and coinfection with MRSA and CRKP. Stronger IPC measures must be implemented to reduce the spread and occurrence of MRSA and CRKP.Funding: NoneDisclosures: None


2020 ◽  
Vol 41 (S1) ◽  
pp. s403-s404
Author(s):  
Jonathan Edwards ◽  
Katherine Allen-Bridson ◽  
Daniel Pollock

Background: The CDC NHSN surveillance coverage includes central-line–associated bloodstream infections (CLABSIs) in acute-care hospital intensive care units (ICUs) and select patient-care wards across all 50 states. This surveillance enables the use of CLABSI data to measure time between events (TBE) as a potential metric to complement traditional incidence measures such as the standardized infection ratio and prevention progress. Methods: The TBEs were calculated using 37,705 CLABSI events reported to the NHSN during 2015–2018 from medical, medical-surgical, and surgical ICUs as well as patient-care wards. The CLABSI TBE data were combined into 2 separate pairs of consecutive years of data for comparison, namely, 2015–2016 (period 1) and 2017–2018 (period 2). To reduce the length bias, CLABSI TBEs were truncated for period 2 at the maximum for period 1; thereby, 1,292 CLABSI events were excluded. The medians of the CLABSI TBE distributions were compared over the 2 periods for each patient care location. Quantile regression models stratified by location were used to account for factors independently associated with CLABSI TBE, such as hospital bed size and average length of stay, and were used to measure the adjusted shift in median CLABSI TBE. Results: The unadjusted median CLABSI TBE shifted significantly from period 1 to period 2 for the patient care locations studied. The shift ranged from 20 to 75.5 days, all with 95% CIs ranging from 10.2 to 32.8, respectively, and P < .0001 (Fig. 1). Accounting for independent associations of CLABSI TBE with hospital bed size and average length of stay, the adjusted shift in median CLABSI TBE remained significant for each patient care location that was reduced by ∼15% (Table 1). Conclusions: Differences in the unadjusted median CLABSI TBE between period 1 and period 2 for all patient care locations demonstrate the feasibility of using TBE for setting benchmarks and tracking prevention progress. Furthermore, after adjusting for hospital bed size and average length of stay, a significant shift in the median CLABSI TBE persisted among all patient care locations, indicating that differences in patient populations alone likely do not account for differences in TBE. These findings regarding CLABSI TBEs warrant further exploration of potential shifts at additional quantiles, which would provide additional evidence that TBE is a metric that can be used for setting benchmarks and can serve as a signal of CLABSI prevention progress.Funding: NoneDisclosures: None


2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Nathanael Lapidus ◽  
Xianlong Zhou ◽  
Fabrice Carrat ◽  
Bruno Riou ◽  
Yan Zhao ◽  
...  

Abstract Background The average length of stay (LOS) in the intensive care unit (ICU_ALOS) is a helpful parameter summarizing critical bed occupancy. During the outbreak of a novel virus, estimating early a reliable ICU_ALOS estimate of infected patients is critical to accurately parameterize models examining mitigation and preparedness scenarios. Methods Two estimation methods of ICU_ALOS were compared: the average LOS of already discharged patients at the date of estimation (DPE), and a standard parametric method used for analyzing time-to-event data which fits a given distribution to observed data and includes the censored stays of patients still treated in the ICU at the date of estimation (CPE). Methods were compared on a series of all COVID-19 consecutive cases (n = 59) admitted in an ICU devoted to such patients. At the last follow-up date, 99 days after the first admission, all patients but one had been discharged. A simulation study investigated the generalizability of the methods' patterns. CPE and DPE estimates were also compared to COVID-19 estimates reported to date. Results LOS ≥ 30 days concerned 14 out of the 59 patients (24%), including 8 of the 21 deaths observed. Two months after the first admission, 38 (64%) patients had been discharged, with corresponding DPE and CPE estimates of ICU_ALOS (95% CI) at 13.0 days (10.4–15.6) and 23.1 days (18.1–29.7), respectively. Series' true ICU_ALOS was greater than 21 days, well above reported estimates to date. Conclusions Discharges of short stays are more likely observed earlier during the course of an outbreak. Cautious unbiased ICU_ALOS estimates suggest parameterizing a higher burden of ICU bed occupancy than that adopted to date in COVID-19 forecasting models. Funding Support by the National Natural Science Foundation of China (81900097 to Dr. Zhou) and the Emergency Response Project of Hubei Science and Technology Department (2020FCA023 to Pr. Zhao).


2020 ◽  
Vol 30 (Supplement_5) ◽  
Author(s):  
S V Valente de Almeida ◽  
H Ghattas ◽  
G Paolucci ◽  
A Seita

Abstract We measure the impact introducing a of 10% co-payment component on hospitalisation costs for Palestine refugees from Lebanon in public and private hospitals. This ex-post analysis provides a detailed insight on the direction and magnitude of the policy impact in terms of demand and supply for healthcare. The data was collected by the United Nations Relief and Works Agency for Palestine Refugees in the Near East and include episode level information from all public, private and Red Crescent Hospitals in Lebanon, between April 2016 and October 2017. This is a complete population episode level dataset with information from before and after the policy change. We use multinomial logit, negative binomial and linear models to estimate the policy impact on demand by type of hospital, average length of stay and treatment costs for the patient and the provider. After the new policy was implemented patients were 18% more likely to choose a (free-of-charge) PRCS hospital for secondary care, instead of a Private or Public hospital, where the co-payment was introduced. This impact was stronger for episodes with longer stays, which are also the more severe and more expensive cases. Average length of stay decreased in general for all hospitals and we could not find a statistically significant impact on costs for the provider nor the patient. We find evidence that the introduction of co-payments is hospital costs led to a shift in demand, but it is not clear to what extent the hospitals receiving this demand shift were prepared for having more patients than before, also because these are typically of less quality then the others. Regarding costs, there is no evidence that the provider managed to contain costs with the new policy, as the demand adapted to the changes. Our findings provide important information on hospitalisation expenses and the consequences of a policy change from a lessons learned perspective that should be taken into account for future policy decision making. Key messages We show that in a context of poverty, the introduction of payment for specific hospital types can be efficient for shifting demand, but has doubtable impact on costs containment for the provider. The co-payment policy can have a negative impact on patients' health since after its implementation demand increased at free-of-charge hospitals, which typically have less resources to treat patients.


BJS Open ◽  
2021 ◽  
Vol 5 (Supplement_1) ◽  
Author(s):  
Jacob Rapier ◽  
Steven Hornby ◽  
Jacob Rapier

Abstract Introduction Nationally 61,220 Laparoscopic Cholecystectomies are carried out annually. Those carried out as day-cases reduce providers’ costs and increase income through the best practice tariff. The system in our trust to record discharges is ‘Trakcare’. The aim of this audit was to accurately measure the discharge times of patients undergoing elective Laparoscopic Cholecystectomies, to try and reduce the number of patients recorded as having an overnight stay by accurate data collection. Methods Initial data was collected for all elective Laparoscopic Cholecystectomy discharge times on Trakcare, over a 1 month period. This data was then re-audited prospectively both from Trakcare and discharges reported by nurses/patients. A comparison was then made of Trakcare against reported discharge times. Results Initially 54 operations were recorded, with 30 completed as day cases (55.6%). The re-audited data (on Trakcare) recorded 47 operations, with 15 completed as day cases (37.91%). Of these discharges we were able to capture 26 (55.32%) manually, and 11 were completed as day cases (42.31%). Measuring these 26 with the same operations on Trakcare we were unable to show a difference in the number of cases completed as a day case (11 vs 11), with only a 33 minute decrease in the average length of stay. Conclusion Trakcare is a reliable tool for measuring the date of discharge for patients. The recommendations in are: scheduling surgery for a time pre-13:00 shows a higher proportion of patients discharged the same day, and continue to use Trakcare to record discharge times.


PEDIATRICS ◽  
1985 ◽  
Vol 75 (6) ◽  
pp. 993-996
Author(s):  
August L. Jung ◽  
Nan Sherman Streeter

In 1977, 7% of the 38,855 infants born in Utah were estimated to have required a total of 27,439 special-care hospital days. About half (53%) were mildly ill; their average length of stay was 4.6 days, or 24% of the total hospital-days. Another 20% of the infants had intermediate illness, with a 12-day average stay, or 23% of the total hospital-days. The remaining 27% of the infants required intensive care and used 53% of the total hospital-days; their average length of stay was 20 days. As a total population, the state's 38,855 births generated a need for two beds per 1,000 annual live births in special-care facilities. The estimated bed need was: mild illness (Level I), 0.5 beds per 1,000 annual live births; intermediate illness (Level II), 0.5 beds per 1,000 annual live births; and intense illness (Level III), one bed per 1,000 annual live births. Results are based on the assumption that nonstudy births, 30% of the total, have needs proportionate to study births. The following considerations are necessary to extrapolate these bed needs to other populations: (1) convalescence of intensely ill babies may require that up to 50% of their bed needs may be shifted to intermediate care; (2) compliance with criteria for transport to the next level of care may not be 100% as assumed in the study, thus redistributing bed needs; (3) census characteristically fluctuates in special-care nurseries (study results are reported for an unchanging daily census); and (4) the low birth rate of a population is intimately related to the bed needs.


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