1.Discharge Decision-Making by Intensivists on Readmission to the Intensive Care Unit.
Kyung Bong YOON ; Shin Ok KOH ; Dong Woo HAN ; One Chul KANG
Yonsei Medical Journal 2004;45(2):193-198
Patients readmitted to the intensive care unit (ICU) have a significantly higher mortality rate. The role of intensivists in judging when to discharge patients from the ICU is very important. We undertook this study to evaluate the effect of the intensivists' discharge decision-making on readmission to ICU. The intensivists actively participated in the discharge decision-making, with the discharge guideline taken into consideration, in respect of group 1 patients, but not in respect of group 2. The readmission rate in group 1 was lower than that in group 2. The readmission in patients in each group was associated with higher mortality rates and longer lengths of stay at the ICU. Respiratory failure was the major cause of readmission. In the non-survivors out of the readmitted patients, the Acute Physiology and Chronic Health Evaluation (APACHE) III scores on the initial discharge and readmission, the multiple organ dysfunction syndrome (MODS) scores on the initial admission, discharge and readmission were higher than the corresponding indices in the survivors. We conclude that the readmission rate was lower when intensivists participated in the discharge decision-making, and that APACHE III and MODS scores on the first discharge and readmission were significant prognostic factors in respect of the readmitted patients.
APACHE
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Acute Disease/*mortality/therapy
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Adult
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Aged
;
Decision Making
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Female
;
Human
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Intensive Care Units/*statistics & numerical data
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Male
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Middle Aged
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*Patient Discharge
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Patient Readmission/*statistics & numerical data
2.Construction and application of an ARIMA model for predicting the number of outpatient visits in general hospitals.
Journal of Southern Medical University 2009;29(5):1076-1078
OBJECTIVETo investigate the variation patterns of the number of outpatient visits in hospitals to provide references for more effective management of general hospitals.
METHODSThe forecasting model of ARIMA(1,0,1)(0,1,1)12 was established using residual error analysis and least squares method according to the sequence stability, long-term trend and seasonal effect after logarithm transformation and differencing.
RESULTSThe residual sum of squares was 2.790, AIC=-178.126, SBC=-170.080. The relative predictive error of the model for predicting the outpatient visits in a general hospital in the year 2008 was 6.11%, smaller than that of exponential smoothing (8.78%). This model predicted a number of outpatient visits of 1,501,200 in this hospital in the year 2009.
CONCLUSIONSThe ARIMA model provides a means for predicting the number of total outpatient visits, its long-term tendency and seasonal variation. The parameters p,d,q in the ARIMA model may vary between different hospitals, and the ACF and PACF charts of the original sequences are helpful for determining these parameters.
China ; Forecasting ; Humans ; Models, Statistical ; Outpatient Clinics, Hospital ; statistics & numerical data ; Outpatients ; statistics & numerical data ; Patient Readmission ; statistics & numerical data ; Seasons
3.Investigation of the Cause of Readmission to the Intensive Care Unit for Patients with Lung Edema or Atelectasis.
Yoshinori MATSUOKA ; Akinori ZAITSU ; Makoto HASHIZUME
Yonsei Medical Journal 2008;49(3):422-428
PURPOSE: For patients with acute respiratory failure due to lung edema or atelectasis, Surplus lung water that is not removed during an initial stay in the Intensive Care Unit (ICU) may be related to early ICU readmission. Therefore, we performed a retrospective study of patient management during the first ICU stay for such patients. MATERIALS AND METHODS: Of 1,835 patients who were admitted to the ICU in the 36 months from January, 2003 to December, 2005, 141 were patients readmitted, and the reason for readmission was lung edema or atelectasis in 21 patients. For these 21 patients, correlations were investigated between body weight gain at the time of initial ICU discharge (weight upon discharge from the ICU ÷ weight when entering the ICU) and the time to ICU readmission, between body weight gain and the P/F ratio at ICU readmission, between the R/E ratio (the period using a respirator (R) ÷ the length of the ICU stay after extubation (E)) and the time to ICU readmission, between the R/E ratio and body weight gain, and between body weight gain until extubation and the time to extubation. RESULTS: A negative linear relationship was found between body weight gain at the time of initial ICU discharge and the time to ICU readmission, and between body weight gain at the time of ICU discharge and the P/F ratio at ICU readmission. If body weight had increased by more than 10% at ICU discharge or the P/F ratio was below 150, readmission to the ICU within three days was likely. Patients with a large R/E ratio, a large body weight gain, and a worsening P/F ratio immediately after ICU discharge were likely to be readmitted soon to the ICU. Loss of body weight during the period of respirator support led to early extubation, since a positive correlation was found between the time to extubation and body weight gain. CONCLUSION: Fluid management failure during the first ICU stay might cause ICU readmission for patients who had lung edema or atelectasis. Therefore, a key to the prevention of ICU readmission is to ensure complete recovery from lung failure before the initial ICU discharge. Strict water management is crucial based on body weight measurement and removal of excess lung water is essential. In addition, an apparent improvement in respiratory state may be due to respiratory support, and such an improvement should be viewed cautiously. Loss of weight at the refilling stage of transfusion prevents ICU readmission and may decrease the length of the ICU stay.
Humans
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Intensive Care Units/*statistics & numerical data
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Patient Readmission/*statistics & numerical data
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Pulmonary Atelectasis/physiopathology/*therapy
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Pulmonary Edema/physiopathology/*therapy
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Retrospective Studies
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Time Factors
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Weight Gain
5.Multivariable analysis of factors associated with hospital readmission following pancreaticoduodenectomy for malignant diseases.
Zi-Yi ZHU ; Ji-Kai HE ; Yi-Fan WANG ; Xiao LIANG ; Hong YU ; Xian-Fa WANG ; Xiu-Jun CAI
Chinese Medical Journal 2011;124(7):1022-1025
BACKGROUNDReadmission rates after pancreaticoduodenectomy (PD) for malignant diseases have a significant impact on survival rate. Identification of risk factors for readmission may improve discharge plans and postoperative care. Data exist on the morbidity and mortality of patients undergoing PD, but there are few reports about hospital readmissions after this procedure. Our aims were to evaluate the proportion and reasons for readmissions after PD for malignant diseases, the factors influencing readmissions, and to analyze the relationship between readmission rate and survival rate.
METHODSFour hundred and thirty-six patients, who had undergone PD for malignant diseases in our centre from October 1999 to October 2009, a 10-year period, excluding perioperative (30-day) mortality, were identified. All readmissions within 1 year following PD were analyzed with respect to timing, location, reasons for readmission and outcome. We reviewed the hospitalization and readmissions for patients undergoing PD, and compared patients requiring readmission to patients that did not require readmission.
RESULTSOne hundred and forty-five patients (33.26%) were readmitted within 1 year following PD, for further treatment or complications. In those cases, diagnoses associated with high rates of readmission included radiation and/or chemotherapy (48.96%), progression of disease (11.72%), infection (11.72%), gastrointestinal dysfunction/obstruction (6.20%), surgery-related complications (2.76%) and pain (4.14%). The proportion of T4 in readmission group was lower than no readmission group (P < 0.05). The proportion of node positive cases in readmission group was much higher than no readmission group (P < 0.01). The number of readmission for complications reduced gradually in the first three months, and reached a second peak in the sixth and seventh month. Median survival was lower for the readmission group compared with the no readmission group (21 versus 46 months, P = 0.024).
CONCLUSIONThese results may assist in both anticipating and facilitating postoperative care as well as managing patient expectations.
Adult ; Aged ; Aged, 80 and over ; Female ; Humans ; Kaplan-Meier Estimate ; Male ; Middle Aged ; Pancreaticoduodenectomy ; adverse effects ; Patient Readmission ; statistics & numerical data ; Postoperative Complications
6.An Evaluation on the Effects of Inpatient Pulmonary Rehabilitation Following Acute Exacerbation of Chronic Obstructive Pulmonary Disease in a Singapore Hospital.
Rahizan ZAINULDIN ; Kieran M SASIADEK ; Nur Amirah Abdul RAUB ; Noel Wt TAY
Annals of the Academy of Medicine, Singapore 2016;45(4):169-171
7.Factors affecting unplanned readmissions from community hospitals to acute hospitals: a prospective observational study.
Ian Y O LEONG ; Siew-Pang CHAN ; Boon-Yeow TAN ; Yih-Yiow SITOH ; Yan-Hoon ANG ; Reshma MERCHANT ; Kala KANAGASABAI ; Patricia S Y LEE ; Weng-Sun PANG
Annals of the Academy of Medicine, Singapore 2009;38(2):113-120
INTRODUCTIONWhile the readmission rate from community hospitals is known, the factors affecting it are not. Our aim was to determine the factors predicting unplanned readmissions from community hospitals (CHs) to acute hospitals (AHs).
MATERIALS AND METHODSThis was an observational prospective cohort study, involving 842 patients requiring post-acute rehabilitation in 2 CHs admitted from 3 AHs in Singapore. We studied the role of the Cumulative Illness Rating Scale (CIRS) organ impairment scores, the Mini-mental State Examination (MMSE) score, the Shah modified Barthel Index (BI) score, and the triceps skin fold thickness (TSFT) in predicting the rate of unplanned readmissions (UR), early unplanned readmissions (EUPR) and late unplanned readmissions (LUPR). We developed a clinical prediction rule to determine the risk of UR and EUPR.
RESULTSThe rates of EUPR and LUPR were 7.6% and 10.3% respectively. The factors that predicted UR were the CIRS-heart score, the CIRS-haemopoietic score, the CIRS-endocrine / metabolic score and the BI on admission. The MMSE was predictive of EUPR. The TSFT and CIRS-liver score were predictive of LUPR. Upon receiver operator characteristics analysis, the clinical prediction rules for the prediction of EUPR and UR had areas under the curve of 0.745 and 0.733 respectively. The likelihood ratios of the clinical prediction rules for EUPR and UR ranged from 0.42 to 5.69 and 0.34 to 3.16 respectively.
CONCLUSIONSPatients who have UR can be identified by the admission BI, the MMSE, the TSFT and CIRS scores in the cardiac, haemopoietic, liver and endocrine/metabolic systems.
Acute Disease ; therapy ; Aged ; Female ; Follow-Up Studies ; Hospitals, Community ; statistics & numerical data ; Hospitals, Special ; statistics & numerical data ; Humans ; Intensive Care Units ; statistics & numerical data ; Male ; Patient Readmission ; trends ; Prospective Studies ; Risk Factors ; Severity of Illness Index ; Singapore
8.Readmission to Medical Intensive Care Units: Risk Factors and Prediction.
Yong Suk JO ; Yeon Joo LEE ; Jong Sun PARK ; Ho Il YOON ; Jae Ho LEE ; Choon Taek LEE ; Young Jae CHO
Yonsei Medical Journal 2015;56(2):543-549
PURPOSE: The objectives of this study were to find factors related to medical intensive care unit (ICU) readmission and to develop a prediction index for determining patients who are likely to be readmitted to medical ICUs. MATERIALS AND METHODS: We performed a retrospective cohort study of 343 consecutive patients who were admitted to the medical ICU of a single medical center from January 1, 2008 to December 31, 2012. We analyzed a broad range of patients' characteristics on the day of admission, extubation, and discharge from the ICU. RESULTS: Of the 343 patients discharged from the ICU alive, 33 (9.6%) were readmitted to the ICU unexpectedly. Using logistic regression analysis, the verified factors associated with increased risk of ICU readmission were male sex [odds ratio (OR) 3.17, 95% confidence interval (CI) 1.29-8.48], history of diabetes mellitus (OR 3.03, 95% CI 1.29-7.09), application of continuous renal replacement therapy during ICU stay (OR 2.78, 95% CI 0.85-9.09), white blood cell count on the day of extubation (OR 1.13, 95% CI 1.07-1.21), and heart rate just before ICU discharge (OR 1.03, 95% CI 1.01-1.06). We established a prediction index for ICU readmission using the five verified risk factors (area under the curve, 0.76, 95% CI 0.66-0.86). CONCLUSION: By using specific risk factors associated with increased readmission to the ICU, a numerical index could be established as an estimation tool to predict the risk of ICU readmission.
Aged
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Aged, 80 and over
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Cohort Studies
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Female
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Humans
;
Intensive Care Units/*statistics & numerical data
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Male
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Medical Records
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Middle Aged
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Odds Ratio
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Patient Readmission/*statistics & numerical data
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Predictive Value of Tests
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Regression Analysis
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Republic of Korea
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Retrospective Studies
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Risk Factors
9.Senior Managed Care System for Hip Fracture in the United States.
Hamed YAZDANSHENAS ; Eleby R WASHINGTON ; Arya Nick SHAMIE ; Firooz MADADI ; Eleby R WASHINGTON
Clinics in Orthopedic Surgery 2016;8(1):19-28
BACKGROUND: It is debatable whether a managed care model would affect the quality of care and length of hospital stay in the treatment of hip fractures in elderly patients. METHODS: This prospective study was undertaken to determine whether or not a managed care critical pathway tool shortened hospital stay in a group of 102 senior patients with fractures of the hip during follow-up. We compared our study findings with two equivalent populations of senior hip fracture patients not treated using a critical care pathway concerning specific markers of quality. RESULTS: The managed care group had a 9% mortality rate, 95% return to prefracture living and 63% return to ambulatory status. The rates compared favorably with previous studies. The quality of care provided before and after the critical pathway was equivalent, while the post-pathway length of stay dropped 30%. CONCLUSIONS: The proposed care protocol is recommended to shorten hospital stay in elderly patients with hip fractures.
Aged
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Aged, 80 and over
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Female
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Hip Fractures/*epidemiology/mortality/*therapy
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Humans
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Length of Stay/*statistics & numerical data
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Los Angeles/epidemiology
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Male
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Managed Care Programs/*statistics & numerical data
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Middle Aged
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Patient Readmission
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Postoperative Complications
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Prospective Studies
;
Quality of Health Care
10.Helicobacter pylori Eradication within 120 Days Is Associated with Decreased Complicated Recurrent Peptic Ulcers in Peptic Ulcer Bleeding Patients.
Shen Shong CHANG ; Hsiao Yun HU
Gut and Liver 2015;9(3):346-352
BACKGROUND/AIMS: The connection between Helicobacter pylori and complicated peptic ulcer disease in peptic ulcer bleeding (PUB) patients taking nonsteroidal anti-inflammatory drugs has not been established. In this study, we sought to determine whether delayed H. pylori eradication therapy in PUB patients increases complicated recurrent peptic ulcers. METHODS: We identified inpatient PUB patients using the Taiwan National Health Insurance Research Database. We categorized patients into early (time lag < or =120 days after peptic ulcer diagnosis) and late H. pylori eradication therapy groups. The Cox proportional hazards model was used. The primary outcome was rehospitalization for patients with complicated recurrent peptic ulcers. RESULTS: Our data indicated that the late H. pylori eradication therapy group had a higher rate of complicated recurrent peptic ulcers (hazard ratio [HR], 1.52; p=0.006), with time lags of more than 120 days. However, our results indicated a similar risk of complicated recurrent peptic ulcers (HR, 1.20; p=0.275) in time lags of more than 1 year and (HR, 1.10; p=0.621) more than 2 years. CONCLUSIONS: H. pylori eradication within 120 days was associated with decreased complicated recurrent peptic ulcers in patients with PUB. We recommend that H. pylori eradication should be conducted within 120 days in patients with PUB.
Adult
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Aged
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Female
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Helicobacter Infections/*drug therapy
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*Helicobacter pylori
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Humans
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Male
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Middle Aged
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Patient Readmission/*statistics & numerical data
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Peptic Ulcer/complications/*epidemiology/microbiology
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Peptic Ulcer Hemorrhage/complications
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Proportional Hazards Models
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Recurrence
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Time-to-Treatment/*statistics & numerical data
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Treatment Outcome
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Young Adult