920 resultados para hospital admission


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Discrete Conditional Phase-type (DC-Ph) models are a family of models which represent skewed survival data conditioned on specific inter-related discrete variables. The survival data is modeled using a Coxian phase-type distribution which is associated with the inter-related variables using a range of possible data mining approaches such as Bayesian networks (BNs), the Naïve Bayes Classification method and classification regression trees. This paper utilizes the Discrete Conditional Phase-type model (DC-Ph) to explore the modeling of patient waiting times in an Accident and Emergency Department of a UK hospital. The resulting DC-Ph model takes on the form of the Coxian phase-type distribution conditioned on the outcome of a logistic regression model.

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Background: Admission hyperglycaemia is associated with mortality in patients with acute coronary syndrome (ACS), but controversy exists whether hyperglycaemia uniformly affects both genders. We evaluated coronary risk factors, gender, hyperglycaemia and their effect on hospital mortality. Methods: 959 ACS patients (363 women and 596 men) were grouped based on glycaemia >= or < 200 mg/dL and gender: men with glucose < 200 mg/dL (menG-); women with glucose < 200 mg/dL (womenG-); men with glucose >= 200 mg/dL (menG+); and women with glucose >= 200 mg/dL (womenG+). A logistic regression analysis compared the relation between gender and glycaemia groups and death, adjusted for coronary risk factors and laboratory data. Results group: menG- had lower mortality than menG+ (OR = 0.172, IC95% 0.062-0.478), and womenG+ (OR = 0.275, IC95% 0.090-0.841); womenG- mortality was lower than menG+ (OR = 0.230, IC95% 0.074-0.717). No difference was found between menG+ vs womenG+ (p = 0.461), or womenG- vs womenG+ (p = 0.110). Age (OR = 1.067, IC95% 1.031-1.104), EF (OR = 0.942, IC95% 0.915-0.968), and serum creatinine (OR = 1.329, IC95% 1.128-1.566) were other independent factors related to in-hospital death. Conclusions: Death was greater in hyperglycemic men compared to lower blood glucose men and women groups, but there was no differences between women groups in respect to glycaemia after adjustment for coronary risk factors.

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Objectives. Admission hyperglycemia and B-type natriuretic peptide (BNP) are associated with mortality in acute coronary syndromes, but no study compares their prediction in-hospital death. Methods. Patients with non-ST-elevation myocardial infarction (NSTEMI), in-hospital mortality and two-year mortality or readmission were compared for area under the curve (AUC), sensitivity (SEN), specificity (SPE), positive predictive value (PPV), negative predictive value (NPV), and accuracy (ACC) of glycemia and BNP. Results. Respectively, AUC, SEN, SPE, PPV, NPV, and ACC for prediction of in-hospital mortality were 0.815, 71.4%, 84.3%, 26.3%, 97.4%, and 83.3% for glycemia = 200 mg/dL and 0.748, 71.4%, 68.5%, 15.2%, 96.8% and 68.7% for BNP = 300 pg/mL. AUC of glycemia was similar to BNP (P = 0.411). In multivariate analysis we found glycemia >= 200mg/dL related to in-hospital death (P = 0.004). No difference was found in two-year mortality or readmission in BNP or hyperglycemic subgroups. Conclusion. Hyperglycemia was an independent risk factor for in-hospital mortality in NSTEMI and had a good ROC curve level. Hyperglycemia and BNP, although poor in-hospital predictors of unfavorable events, were independent risk factors for death or length of stay >10 days. No relation was found between hyperglycemia or BNP and long-term events.

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PURPOSE: The goal of this study was to analyse a possible association of admission blood glucose with hospital mortality of polytraumatised patients and to develop an outcome prediction model for this patient group. METHODS: The outcome of adult polytraumatised patients admitted to the University Hospital of Berne, Switzerland, between 2002 and 2004 with an ISS > or = 17, and more than one severely injured organ system was retrospectively analysed. RESULTS: The inclusion criteria were met by 555 patients, of which 108 (19.5%) died. Hyperglycaemia proved to be an independent predictor for hospital mortality (P < 0.0001), following multiple regression analysis. After inclusion of admission blood glucose, the calculated mortality prediction model performed better than currently described models (P < 0.0001, AUC 0.924). CONCLUSION: In this retrospective, single-centre study in polytraumatised patients, admission blood glucose proved to be an independent predictor of hospital mortality following regression analysis controlling for age, gender, injury severity and other laboratory parameters. A reliable admission blood glucose-based mortality prediction model for polytraumatised patients could be established. This observation may be helpful in improving the precision of future outcome prediction models for polytraumatised patients. These observations warrant further prospective evaluation.

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Objective: This dissertation evaluated three aspects of the Centers for Medicare and Medicaid Services' Hospital Acquired Conditions and Present on Admission Indicator Reporting program (HACPOA program) to produce three journal articles for publication. ^ Methods: All payer admission records from state inpatient databases from Arizona, New Jersey and Washington states were analyzed for the year 2008. However some analyses required a sample of adult only Medicare patients in the first two studies. California's inpatient data (2004 – 2010) was also analyzed in the third study to examine the reporting and non-payment program elements' impact on the incidence of hospital acquired conditions. ^ Results: Majority diagnoses reported in inpatient prospective payment systems hospitals were present on admission. However, some diagnoses are still coded as "not present on admission" and "insufficient documentation to determine whether or not conditions are present on admission or not". This is important because it reveals that hospital complications still occur in hospitals. Hospital fall and trauma injuries were the most common hospital acquired conditions observed in this study. Predictors of hospital fall injuries include age, gender, number of diagnoses, number of procedures, number of chronic conditions while predictors of hospital trauma injuries include number of e-codes, number of diagnoses and the presence of chronic conditions on a patient's admission records. Finally, the implementation of the present on admission reporting requirement increased reports of certain hospital acquired conditions while the non-payment policy element in the Hospital Acquired Conditions program reduced the incidence of hospital fall and trauma injuries in particular. ^ Conclusion: The implementation of the Hospital Acquired Conditions and Present on Admission Indicator Reporting program has made the state inpatient database a more useful source of data capable of now identifying hospital complications. The reporting and nonpayment program elements in the HACPOA program have also impacted the incidence of hospital acquired conditions. ^

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Background. The objective is to estimate the cost-effectiveness of an intervention that reduces hospital readmission among older people at high risk. A cost-effectiveness model to estimate the costs and health benefits of the intervention was implemented. Methodology/Principal Findings. The model used data from a randomised controlled trial conducted in an Australian tertiary metropolitan hospital. Participants were acute medical admissions aged >65 years with at least one risk factor for readmission: multiple comorbidities, impaired functionality, aged >75 years, 30 recent multiple admissions, poor social support, history of depression. The intervention was a comprehensive nursing and physiotherapy assessment and an individually tailored program of exercise strategies and nurse home visits with telephone follow-up; commencing in hospital and continuing following discharge for 24 weeks. The change to cost outcomes, including the costs of implementing the intervention and all subsequent use of health care services, and, the change to health benefits, represented by quality adjusted life years, were estimated for the intervention as compared to existing practice. The mean change to total costs and quality 38 adjusted life years for an average individual over 24 weeks participating in the intervention were: cost savings of $333 (95% Bayesian credible interval $-1,932:1,282) and 0.118 extra quality adjusted life years (95% Bayesian credible interval 0.1:0.136). The mean net41 monetary-benefit per individual for the intervention group compared to the usual care condition was $7,907 (95% Bayesian credible interval $5,959:$9,995) for the 24 week period. Conclusions/Significance. The estimation model that describes this intervention predicts cost savings and improved health outcomes. A decision to remain with existing practices causes unnecessary costs and reduced health. Decision makers should consider adopting this 46 program for elderly hospitalised patients.

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Aims: To describe a local data linkage project to match hospital data with the Australian Institute of Health and Welfare (AIHW) National Death Index (NDI) to assess longterm outcomes of intensive care unit patients. Methods: Data were obtained from hospital intensive care and cardiac surgery databases on all patients aged 18 years and over admitted to either of two intensive care units at a tertiary-referral hospital between 1 January 1994 and 31 December 2005. Date of death was obtained from the AIHW NDI by probabilistic software matching, in addition to manual checking through hospital databases and other sources. Survival was calculated from time of ICU admission, with a censoring date of 14 February 2007. Data for patients with multiple hospital admissions requiring intensive care were analysed only from the first admission. Summary and descriptive statistics were used for preliminary data analysis. Kaplan-Meier survival analysis was used to analyse factors determining long-term survival. Results: During the study period, 21 415 unique patients had 22 552 hospital admissions that included an ICU admission; 19 058 surgical procedures were performed with a total of 20 092 ICU admissions. There were 4936 deaths. Median follow-up was 6.2 years, totalling 134 203 patient years. The casemix was predominantly cardiac surgery (80%), followed by cardiac medical (6%), and other medical (4%). The unadjusted survival at 1, 5 and 10 years was 97%, 84% and 70%, respectively. The 1-year survival ranged from 97% for cardiac surgery to 36% for cardiac arrest. An APACHE II score was available for 16 877 patients. In those discharged alive from hospital, the 1, 5 and 10-year survival varied with discharge location. Conclusions: ICU-based linkage projects are feasible to determine long-term outcomes of ICU patients

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Objective: During hospitalisation older people often experience functional decline which impacts on their future independence. The objective of this study was to evaluate a multifaceted transitional care intervention including home-based exercise strategies for at-risk older people on functional status, independence in activities of daily living, and walking ability. Methods: A randomised controlled trial was undertaken in a metropolitan hospital in Australia with 128 patients (64 intervention, 64 control) aged over 65 years with an acute medical admission and at least one risk factor for hospital readmission. The intervention group received an individually tailored program for exercise and follow-up care which was commenced in hospital and included regular visits in hospital by a physiotherapist and a Registered Nurse, a home visit following discharge, and regular telephone follow-up for 24 weeks following discharge. The program was designed to improve health promoting behaviours, strength, stability, endurance and mobility. Data were collected at baseline, then 4, 12 and 24 weeks following discharge using the Index of Activities of Daily Living (ADL), Instrumental Index of Activities of Daily Living (IADL), and the Walking Impairment Questionnaire (Modified). Results: Significant improvements were found in the intervention group in IADL scores (p<.001), ADL scores (p<.001), and WIQ scale scores (p<.001) in comparison to the control group. The greatest improvements were found in the first four weeks following discharge. Conclusions: Early introduction of a transitional model of care incorporating a tailored exercise program and regular telephone follow-up for hospitalised at-risk older adults can improve independence and functional ability.

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Background: Assessments of change in subjective patient reported outcomes such as health-related quality of life (HRQoL) are a key component of many clinical and research evaluations. However, conventional longitudinal evaluation of change may not agree with patient perceived change if patients' understanding of the subjective construct under evaluation changes over time (response shift) or if patients' have inaccurate recollection (recall bias). This study examined whether older adults' perception of change is in agreement with conventional longitudinal evaluation of change in their HRQoL over the duration of their hospital stay. It also investigated this level of agreement after adjusting patient perceived change for recall bias that patients may have experienced. Methods: A prospective longitudinal cohort design nested within a larger randomised controlled trial was implemented. 103 hospitalised older adults participated in this investigation at a tertiary hospital facility. The EQ-5D utility and Visual Analogue Scale (VAS) scores were used to evaluate HRQoL. Participants completed EQ-5D reports as soon as they were medically stable (within three days of admission) then again immediately prior to discharge. Three methods of change score calculation were used (conventional change, patient perceived change and patient perceived change adjusted for recall bias). Agreement was primarily investigated using intraclass correlation coefficients (ICC) and limits of agreement. Results: Overall 101 (98%) participants completed both admission and discharge assessments. The mean (SD) age was 73.3 (11.2). The median (IQR) length of stay was 38 (20-60) days. For agreement between conventional longitudinal change and patient perceived change: ICCs were 0.34 and 0.40 for EQ-5D utility and VAS respectively. For agreement between conventional longitudinal change and patient perceived change adjusted for recall bias: ICCs were 0.98 and 0.90 respectively. Discrepancy between conventional longitudinal change and patient perceived change was considered clinically meaningful for 84 (83.2%) of participants, after adjusting for recall bias this reduced to 8 (7.9%). Conclusions: Agreement between conventional change and patient perceived change was not strong. A large proportion of this disagreement could be attributed to recall bias. To overcome the invalidating effect of response shift (on conventional change) and recall bias (on patient perceived change) a method of adjusting patient perceived change for recall bias has been described.

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In September 2009 an enormous dust storm swept across eastern Australia. Dust is potentially hazardous to health as it interferes with breathing, and previous dust storms have been linked to increased risks of asthma and even death. We examined whether the 2009 Australian dust storm changed the volume or characteristics of emergency admissions to hospital. We used an observational study design, using time series analyses to examine changes in the number of admissions, and case-only analyses to examine changes in the characteristics of admissions. The admission data were from the Prince Charles Hospital, Brisbane, between 1 January 2009 and 31 October 2009. There was a 39% increase in emergency admissions associated with the storm (95% confidence interval: 5, 81%), which lasted for just one day. The health effects of the storm could not be detected using particulate matter levels. We found no significant change in the characteristics of admissions during the storm, specifically there was no increase in respiratory admissions. The dust storm had a short-lived impact on emergency hospital admissions. This may be because the public took effective avoidance measures, or because the dust was simply not toxic, being mainly composed of soil. Emergency departments should be prepared for a short-term increase in admissions during dust storms.

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Objective: To investigate whether hospital utilisation and health outcomes in Victoria differ between people born in refugee-source countries and those born in Australia. Design and setting: Analysis of a statewide hospital discharge dataset for the 6 financial years from 1 July 1998 to 30 June 2004. Hospital admissions of people born in eight countries for which the majority of entrants to Australia arrived as refugees were included in the analysis. Main outcome measures: Age-standardised rates and rate ratios for: total hospital admissions; emergency admissions; surgical admissions; total days in hospital; discharge at own risk; hospital deaths; admissions due to infectious and parasitic diseases; and admissions due to mental and behavioural disorders. Results: In 2003–04, compared with the Australia-born Victorian population, people born in refugee-source countries had lower rates of surgical admission (rate ratio [RR], 0.85; 95% CI, 0.81–0.88), total days in hospital (RR, 0.74; 95% CI, 0.73–0.75), and admission due to mental and behavioural disorders (RR, 0.70; 95% CI, 0.65–0.76). Over the 6-year period, rates of total days in hospital and rates of admission due to mental and behavioural disorders for people born in refugee-source countries increased towards Australian-born averages, while rates of total admissions, emergency admissions, and admissions due to infectious and parasitic diseases increased above the Australian-born averages. Conclusions: Use of hospital services among people born in refugee-source countries is not higher than that of the Australian-born population and shows a trend towards Australian-born averages. Our findings indicate that the Refugee and Humanitarian Program does not currently place a burden on the Australian hospital system.

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Families of 52 first-admission patients diagnosed with a severe psychiatric disorder were videotaped interacting with the patient. Behavioral coding was used to derive several indices of interaction: base rates of positive and negative behavior by patients and relatives, cumulative affect of patients and relatives (the difference between the rates of positive and negative behaviors), and classification of families as affect-regulated or unregulated. Family-affect regulation reflects positive cumulative affect by both people in a given interaction. Six months after hospital discharge patients were assessed on occurrence of relapse, global functioning, severity of psychiatric symptoms, and quality of life. Relative to affect-unregulated family interaction, affect-regulated interaction predicted significantly fewer relapses, better global functioning, fewer positive and negative psychiatric symptoms, and higher patient quality of life. Most of the predictions by family-affect regulation were independent of