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1.
Aida Bianco Antonio Molè Carmelo G. A. Nobile Gabriella Di Giuseppe Claudia Pileggi Italo F. Angelillo 《PloS one》2012,7(11)
Background
One quality indicator of hospital care, which can be used to judge the process of care, is the prevalence of hospital readmission because it reflects the impact of hospital care on the patient’s condition after discharge. The purposes of the study were to measure the prevalence of hospital readmissions, to identify possible factors that influence such readmission and to measure the prevalence of readmissions potentially avoidable in Italy.Methods
A sample of 2289 medical records of patients aged 18 and over admitted for medical or surgical illness at one 502-bed community non-teaching hospital were randomly selected.Results
A total of 2252 patients were included in the final analysis, equaling a response rate of 98.4%. The overall hospital readmission prevalence within 30 days of discharge was 10.2%. Multivariate logistic regression analysis revealed that the proportion of patients readmitted within 30 days of discharge significantly increased regardless of Charlson et al. comorbidity score, among unemployed or retired patients, and in patients in general surgery. A total of 43.7% hospital readmissions were judged to be potentially avoidable. Multivariate logistic regression analysis showed that potentially avoidable readmissions were significantly higher in general surgery, in patients referred to hospital by an emergency department physician, and in those with a shortened time between discharge and readmission.Conclusion
Additional research on intervention or bundle of interventions applicable to acute inpatient populations that aim to reduce potentially avoidable readmissions is strongly needed, and health care providers are urged to implement evidence-based programs for more cost-effective delivery of health care. 相似文献2.
Background
Many studies have evaluated methicillin-resistant Staphylococcus aureus (MRSA) infections during single hospitalizations and subsequent readmissions to the same institution. None have assessed the comprehensive burden of MRSA infection in the period after hospital discharge while accounting for healthcare utilization across institutions.Methodology/Principal Findings
We conducted a retrospective cohort study of adult patients insured by Harvard Pilgrim Health Care who were newly-detected to harbor MRSA between January 1991 and December 2003 at a tertiary care medical center. We evaluated all MRSA-attributable infections associated with hospitalization in the year following new detection, regardless of hospital location. Data were collected on comorbidities, healthcare utilization, mortality and MRSA outcomes. Of 591 newly-detected MRSA carriers, 23% were colonized and 77% were infected upon detection. In the year following detection, 196 (33%) patients developed 317 discrete and unrelated MRSA infections. The most common infections were pneumonia (34%), soft tissue (27%), and primary bloodstream (18%) infections. Infections occurred a median of 56 days post-detection. Of all infections, 26% involved bacteremia, and 17% caused MRSA-attributable death. During the admission where MRSA was newly-detected, 14% (82/576) developed subsequent infection. Of those surviving to discharge, 24% (114/482) developed post-discharge infections in the year following detection. Half (99/185, 54%) of post-discharge infections caused readmission, and most (104/185, 55%) occurred over 90 days post-discharge.Conclusions/Significance
In high-risk tertiary care patients, newly-detected MRSA carriage confers large risks of infection and substantial attributable mortality in the year following acquisition. Most infections occur post-discharge, and 18% of infections associated with readmission occurred in hospitals other than the one where MRSA was newly-detected. Despite gains in reducing MRSA infections during hospitalization, the risk of MRSA infection among critically and chronically ill carriers persists after discharge and warrants targeted prevention strategies. 相似文献3.
Carl van Walraven Alison Jennings Monica Taljaard Irfan Dhalla Shane English Sunita Mulpuru Saul Blecker Alan J. Forster 《CMAJ》2011,183(14):e1067-e1072
Background:
Urgent, unplanned hospital readmissions are increasingly being used to gauge the quality of care. We reviewed urgent readmissions to determine which were potentially avoidable and compared rates of all-cause and avoidable readmissions.Methods:
In a multicentre, prospective cohort study, we reviewed all urgent readmissions that occurred within six months among patients discharged to the community from 11 teaching and community hospitals between October 2002 and July 2006. Summaries of the readmissions were reviewed by at least four practising physicians using standardized methods to judge whether the readmission was an adverse event (poor clinical outcome due to medical care) and whether the adverse event could have been avoided. We used a latent class model to determine whether the probability that each readmission was truly avoidable exceeded 50%.Results:
Of the 4812 patients included in the study, 649 (13.5%, 95% confidence interval [CI] 12.5%–14.5%) had an urgent readmission within six months after discharge. We considered 104 of them (16.0% of those readmitted, 95% CI 13.3%–19.1%; 2.2% of those discharged, 95% CI 1.8%–2.6%) to have had a potentially avoidable readmission. The proportion of patients who had an urgent readmission varied significantly by hospital (range 7.5%–22.5%; χ2 = 92.9, p < 0.001); the proportion of readmissions deemed avoidable did not show significant variation by hospital (range 1.2%–3.7%; χ2 = 12.5, p < 0.25). We found no association between the proportion of patients who had an urgent readmission and the proportion of patients who had an avoidable readmission (Pearson correlation 0.294; p = 0.38). In addition, we found no association between hospital rankings by proportion of patients readmitted and rankings by proportion of patients with an avoidable readmission (Spearman correlation coefficient 0.28, p = 0.41).Interpretation:
Urgent readmissions deemed potentially avoidable were relatively uncommon, comprising less than 20% of all urgent readmissions following hospital discharge. Hospital-specific proportions of patients who were readmitted were not related to proportions with a potentially avoidable readmission.Urgent, unplanned hospital readmissions are increasingly being used to measure institutional or regional quality of care.1–4 The public reporting of readmissions and their use in considerations for funding suggest a belief that readmissions indicate the quality of care provided by particular institutions. However, urgent readmissions are an informative metric only if we know what proportion of them are avoidable. If they are rarely avoidable, they would be a poor gauge of the quality of patient care.Current estimates of the proportion of urgent readmissions that are avoidable are unreliable. In a systematic review of 34 studies that reviewed how many readmissions were avoidable, 3 of the studies relied solely on combinations of administrative diagnostic codes, and most used undefined or subjective criteria.5 In addition, most of the studies were conducted at a single centre and used only one reviewer. The proportion of readmissions deemed avoidable varied widely, from 5.1%6 to 78.9%,7 which reflected in part the lack of standardized and reliable methods to identify avoidable readmissions.We conducted a multicentre prospective cohort study to elicit judgments from multiple practising physicians who used standard implicit review methods to determine whether urgent readmissions were potentially avoidable. We analyzed these judgments using a latent class analysis. We also measured the proportion of readmissions deemed avoidable and compared hospital-specific proportions of all-cause and avoidable readmissions. 相似文献4.
Carl van Walraven Carol Bennett Alison Jennings Peter C. Austin Alan J. Forster 《CMAJ》2011,183(7):E391-E402
Background
Readmissions to hospital are increasingly being used as an indicator of quality of care. However, this approach is valid only when we know what proportion of readmissions are avoidable. We conducted a systematic review of studies that measured the proportion of readmissions deemed avoidable. We examined how such readmissions were measured and estimated their prevalence.Methods
We searched the MEDLINE and EMBASE databases to identify all studies published from 1966 to July 2010 that reviewed hospital readmissions and that specified how many were classified as avoidable.Results
Our search strategy identified 34 studies. Three of the studies used combinations of administrative diagnostic codes to determine whether readmissions were avoidable. Criteria used in the remaining studies were subjective. Most of the studies were conducted at single teaching hospitals, did not consider information from the community or treating physicians, and used only one reviewer to decide whether readmissions were avoidable. The median proportion of readmissions deemed avoidable was 27.1% but varied from 5% to 79%. Three study-level factors (teaching status of hospital, whether all diagnoses or only some were considered, and length of follow-up) were significantly associated with the proportion of admissions deemed to be avoidable and explained some, but not all, of the heterogeneity between the studies.Interpretation
All but three of the studies used subjective criteria to determine whether readmissions were avoidable. Study methods had notable deficits and varied extensively, as did the proportion of readmissions deemed avoidable. The true proportion of hospital readmissions that are potentially avoidable remains unclear.In most instances, unplanned readmissions to hospital indicate bad health outcomes for patients. Sometimes they are due to a medical error or the provision of suboptimal patient care. Other times, they are unavoidable because they are due to the development of new conditions or the deterioration of refractory, severe chronic conditions.Hospital readmissions are frequently used to gauge patient care. Many organizations use them as a metric for institutional or regional quality of care.1 The widespread public reporting of hospital readmissions and their use in considerations for funding implicitly suggest a belief that readmissions indicate the quality of care provided by particular physicians and institutions.The validity of hospital readmissions as an indicator of quality of care depends on the extent that readmissions are avoidable. As the proportion of readmissions deemed to be avoidable decreases, the effort and expense required to avoid one readmission will increase. This decrease in avoidable admissions will also dilute the relation between the overall readmission rate and quality of care. Therefore, it is important to know the proportion of hospital readmissions that are avoidable.We conducted a systematic review of studies that measured the proportion of readmissions that were avoidable. We examined how such readmissions were measured and estimated their prevalence. 相似文献5.
Introduction
Early discharge from the ICU is desirable because it shortens time in the ICU and reduces care costs, but can also increase the likelihood of ICU readmission and post-discharge unanticipated death if patients are discharged before they are stable. We postulated that, using eICU® Research Institute (eRI) data from >400 ICUs, we could develop robust models predictive of post-discharge death and readmission that may be incorporated into future clinical information systems (CIS) to assist ICU discharge planning.Methods
Retrospective, multi-center, exploratory cohort study of ICU survivors within the eRI database between 1/1/2007 and 3/31/2011. Exclusion criteria: DNR or care limitations at ICU discharge and discharge to location external to hospital. Patients were randomized (2∶1) to development and validation cohorts. Multivariable logistic regression was performed on a broad range of variables including: patient demographics, ICU admission diagnosis, admission severity of illness, laboratory values and physiologic variables present during the last 24 hours of the ICU stay. Multiple imputation was used to address missing data. The primary outcomes were the area under the receiver operator characteristic curves (auROC) in the validation cohorts for the models predicting readmission and death within 48 hours of ICU discharge.Results
469,976 and 234,987 patients representing 219 hospitals were in the development and validation cohorts. Early ICU readmission and death was experienced by 2.54% and 0.92% of all patients, respectively. The relationship between predictors and outcomes (death vs readmission) differed, justifying the need for separate models. The models for early readmission and death produced auROCs of 0.71 and 0.92, respectively. Both models calibrated well across risk groups.Conclusions
Our models for death and readmission after ICU discharge showed good to excellent discrimination and good calibration. Although prospective validation is warranted, we speculate that these models may have value in assisting clinicians with ICU discharge planning. 相似文献6.
Matthew O. Wiens Shane Pawluk Niranjan Kissoon Elias Kumbakumba J. Mark Ansermino Joel Singer Andrew Ndamira Charles Larson 《PloS one》2013,8(6)
Objectives
Mortality following hospital discharge is an important and under-recognized contributor to overall child mortality in developing countries. The primary objective of this systematic review was to identify all studies reporting post-discharge mortality in children, estimate likelihood of death, and determine the most important risk factors for death.Search Strategy
MEDLINE and EMBASE were systematically searched using MeSH terms and keywords from the inception date to October, 2012. Key word searches using Google Scholar™ and hand searching of references of retrieved articles was also performed. Studies from developing countries reporting mortality following hospital discharge among a pediatric population were considered for inclusion.Results
Thirteen studies that reported mortality rates following discharge were identified. Studies varied significantly according to design, underlying characteristics of study population and duration of follow-up. Mortality rates following discharge varied significantly between studies (1%–18%). When reported, post-discharge mortality rates often exceeded in-hospital mortality rates. The most important baseline variables associated with post-discharge mortality were young age, malnutrition, multiple previous hospitalizations, HIV infection and pneumonia. Most post-discharge deaths occurred early during the post-discharge period. Follow-up care was examined in only one study examining malaria prophylaxis in children discharged following an admission secondary to malaria, which showed no significant benefit on post-discharge mortality.Conclusions
The months following hospital discharge carry significant risk for morbidity and mortality. While several characteristics are strongly associated with post-discharge mortality, no validated tools are available to aid health workers or policy makers in the systematic identification of children at high risk of post-discharge mortality. Future research must focus on both the creation of tools to aid in defining groups of children most likely to benefit from post-discharge interventions, and formal assessment of the effectiveness of such interventions in reducing morbidity and mortality in the first few months following hospital discharge. 相似文献7.
Isuru Ranasinghe Yongfei Wang Kumar Dharmarajan Angela F. Hsieh Susannah M. Bernheim Harlan M. Krumholz 《PLoS medicine》2014,11(9)
Background
Patients aged ≥65 years are vulnerable to readmissions due to a transient period of generalized risk after hospitalization. However, whether young and middle-aged adults share a similar risk pattern is uncertain. We compared the rate, timing, and readmission diagnoses following hospitalization for heart failure (HF), acute myocardial infarction (AMI), and pneumonia among patients aged 18–64 years with patients aged ≥65 years.Methods and Findings
We used an all-payer administrative dataset from California consisting of all hospitalizations for HF (n = 206,141), AMI (n = 107,256), and pneumonia (n = 199,620) from 2007–2009. The primary outcomes were unplanned 30-day readmission rate, timing of readmission, and readmission diagnoses. Our findings show that the readmission rate among patients aged 18–64 years exceeded the readmission rate in patients aged ≥65 years in the HF cohort (23.4% vs. 22.0%, p<0.001), but was lower in the AMI (11.2% vs. 17.5%, p<0.001) and pneumonia (14.4% vs. 17.3%, p<0.001) cohorts. When adjusted for sex, race, comorbidities, and payer status, the 30-day readmission risk in patients aged 18–64 years was similar to patients ≥65 years in the HF (HR 0.99; 95%CI 0.97–1.02) and pneumonia (HR 0.97; 95%CI 0.94–1.01) cohorts and was marginally lower in the AMI cohort (HR 0.92; 95%CI 0.87–0.96). For all cohorts, the timing of readmission was similar; readmission risks were highest between days 2 and 5 and declined thereafter across all age groups. Diagnoses other than the index admission diagnosis accounted for a substantial proportion of readmissions among age groups <65 years; a non-cardiac diagnosis represented 39–44% of readmissions in the HF cohort and 37–45% of readmissions in the AMI cohort, while a non-pulmonary diagnosis represented 61–64% of patients in the pneumonia cohort.Conclusion
When adjusted for differences in patient characteristics, young and middle-aged adults have 30-day readmission rates that are similar to elderly patients for HF, AMI, and pneumonia. A generalized risk after hospitalization is present regardless of age. Please see later in the article for the Editors'' Summary 相似文献8.
Dorman RB Miller CJ Leslie DB Serrot FJ Slusarek B Buchwald H Connett JE Ikramuddin S 《PloS one》2012,7(3):e32506
Background and Objectives
Complications resulting in hospital readmission are important concerns for those considering bariatric surgery, yet present understanding of the risk for these events is limited to a small number of patient factors. We sought to identify demographic characteristics, concomitant morbidities, and perioperative factors associated with hospital readmission following bariatric surgery.Methods
We report on a prospective observational study of 24,662 patients undergoing primary RYGB and 26,002 patients undergoing primary AGB at 249 and 317 Bariatric Surgery Centers of Excellence (BSCOE), respectively, in the United States from January 2007 to August 2009.Data were collected using standardized assessments of demographic factors and comorbidities, as well as longitudinal records of hospital readmissions, complications, and mortality.Results
The readmission rate was 5.8% for RYGB and 1.2% for AGB patients 30 days after discharge. The greatest predictors for readmission following RYGB were prolonged length of stay (adjusted odds ratio [OR], 2.3; 95% confidence interval [CI], 2.0–2.7), open surgery (OR, 1.8; CI, 1.4–2.2), and pseudotumor cerebri (OR, 1.6; CI, 1.1–2.4). Prolonged length of stay (OR, 2.3; CI, 1.6–3.3), history of deep venous thrombosis or pulmonary embolism (OR, 2.1; CI, 1.3–3.3), asthma (OR, 1.5; CI, 1.1–2.1), and obstructive sleep apnea (OR, 1.5; CI, 1.1–1.9) were associated with the greatest increases in readmission risk for AGB. The 30-day mortality rate was 0.14% for RYGB and 0.02% for AGB.Conclusion
Readmission rates are low and mortality is very rare following bariatric surgery, but risk for both is significantly higher after RYGB. Predictors of readmission were disparate for the two procedures. Results do not support excluding patients with certain comorbidities since any reductions in overall readmission rates would be very small on the absolute risk scale. Future research should evaluate the efficacy of post-surgical managed care plans for patients at higher risk for readmission and adverse events. 相似文献9.
Aims
To determine whether the additional interventions to standard care are cost-effective in addressing cocaine and alcohol abuse at 4 months (4 M) and 12 months (12 M) from baseline.Method
We conducted a cost-effectiveness analysis of a randomized controlled trial with three arms: (1) NIDA''s Standard intervention (SI); (2) SI plus a Well Woman Exam (WWE); and, (3) SI, WWE, plus four Educational Sessions (4ES).Results
To obtain an additional cocaine abstainer, WWE compared to SI cost $7,223 at 4 M and $3,611 at 12 M. Per additional alcohol abstainer, WWE compared to SI cost $3,611 and $7,223 at 4 M and 12 M, respectively. At 12 M, 4ES was dominated (more costly and less effective) by WWE for abstinence outcomes.Conclusions
To our knowledge, this is the first cost-effectiveness analysis simultaneously examining cocaine and alcohol abuse in women. Depending on primary outcomes sought and priorities of policy makers, peer-delivered interventions can be a cost-effective way to address the needs of this growing, underserved population.Trial Registration
ClinicalTrials.gov NCT01235091 相似文献10.
Background
Epidemiological interventions aim to control the spread of infectious disease through various mechanisms, each carrying a different associated cost.Methodology
We describe a flexible statistical framework for generating optimal epidemiological interventions that are designed to minimize the total expected cost of an emerging epidemic while simultaneously propagating uncertainty regarding the underlying disease model parameters through to the decision process. The strategies produced through this framework are adaptive: vaccination schedules are iteratively adjusted to reflect the anticipated trajectory of the epidemic given the current population state and updated parameter estimates.Conclusions
Using simulation studies based on a classic influenza outbreak, we demonstrate the advantages of adaptive interventions over non-adaptive ones, in terms of cost and resource efficiency, and robustness to model misspecification. 相似文献11.
Marie-Anne Durand Lewis Carpenter Hayley Dolan Paulina Bravo Mala Mann Frances Bunn Glyn Elwyn 《PloS one》2014,9(4)
Background
Increasing patient engagement in healthcare has become a health policy priority. However, there has been concern that promoting supported shared decision-making could increase health inequalities.Objective
To evaluate the impact of SDM interventions on disadvantaged groups and health inequalities.Design
Systematic review and meta-analysis of randomised controlled trials and observational studies.Data Sources
CINAHL, the Cochrane Register of Controlled Trials, the Cochrane Database of Systematic Reviews, EMBASE, HMIC, MEDLINE, the NHS Economic Evaluation Database, Open SIGLE, PsycINFO and Web of Knowledge were searched from inception until June 2012.Study Eligibility Criteria
We included all studies, without language restriction, that met the following two criteria: (1) assess the effect of shared decision-making interventions on disadvantaged groups and/or health inequalities, (2) include at least 50% of people from disadvantaged groups, except if a separate analysis was conducted for this group.Results
We included 19 studies and pooled 10 in a meta-analysis. The meta-analyses showed a moderate positive effect of shared decision-making interventions on disadvantaged patients. The narrative synthesis suggested that, overall, SDM interventions increased knowledge, informed choice, participation in decision-making, decision self-efficacy, preference for collaborative decision making and reduced decisional conflict among disadvantaged patients. Further, 7 out of 19 studies compared the intervention''s effect between high and low literacy groups. Overall, SDM interventions seemed to benefit disadvantaged groups (e.g. lower literacy) more than those with higher literacy, education and socioeconomic status. Interventions that were tailored to disadvantaged groups'' needs appeared most effective.Conclusion
Results indicate that shared decision-making interventions significantly improve outcomes for disadvantaged patients. According to the narrative synthesis, SDM interventions may be more beneficial to disadvantaged groups than higher literacy/socioeconomic status patients. However, given the small sample sizes and variety in the intervention types, study design and quality, those findings should be interpreted with caution. 相似文献12.
Paul E. Sax Alexis Sypek Bethany K. Berkowitz Bethany L. Morris Elena Losina A. David Paltiel Kathleen A. Kelly George R. Seage III Rochelle P. Walensky Milton C. Weinstein Joseph Eron Kenneth A. Freedberg 《PloS one》2014,9(11)
Background
We examined efficacy, toxicity, relapse, cost, and quality-of-life thresholds of hypothetical HIV cure interventions that would make them cost-effective compared to life-long antiretroviral therapy (ART).Methods
We used a computer simulation model to assess three HIV cure strategies: Gene Therapy, Chemotherapy, and Stem Cell Transplantation (SCT), each compared to ART. Efficacy and cost parameters were varied widely in sensitivity analysis. Outcomes included quality-adjusted life expectancy, lifetime cost, and cost-effectiveness in dollars/quality-adjusted life year ($/QALY) gained. Strategies were deemed cost-effective with incremental cost-effectiveness ratios <$100,000/QALY.Results
For patients on ART, discounted quality-adjusted life expectancy was 16.4 years and lifetime costs were $591,400. Gene Therapy was cost-effective with efficacy of 10%, relapse rate 0.5%/month, and cost $54,000. Chemotherapy was cost-effective with efficacy of 88%, relapse rate 0.5%/month, and cost $12,400/month for 24 months. At $150,000/procedure, SCT was cost-effective with efficacy of 79% and relapse rate 0.5%/month. Moderate efficacy increases and cost reductions made Gene Therapy cost-saving, but substantial efficacy/cost changes were needed to make Chemotherapy or SCT cost-saving.Conclusions
Depending on efficacy, relapse rate, and cost, cure strategies could be cost-effective compared to current ART and potentially cost-saving. These results may help provide performance targets for developing cure strategies for HIV. 相似文献13.
Background
Hospital readmission rates are being used to evaluate performance. A survey of the present rates is needed before policies can be developed to decrease incidence of readmission. We address three questions: What is the present rate of 30-day readmission in orthopedics? How do factors such as orthopedic specialty, data source, patient insurance, and time of data collection affect the 30-day readmission rate? What are the causes and risk factors for 30-day readmissions?Methods/Findings
A review was first registered with Prospero (CRD42014010293, 6/17/2014) and a meta-analysis was performed to assess the current 30-day readmission rate in orthopedics. Studies published after 2006 were retrieved, and 24 studies met the inclusion criteria. The 30-day readmission rate was extrapolated from each study along with the orthopedic subspecialty, data source, patient insurance, time of collection, patient demographics, and cause of readmission. A sensitivity analysis was completed on the stratified groups. The overall 30-day readmission rate across all orthopedics was 5.4 percent (95% confidence interval: 4.8,6.0). There was no significant difference between subspecialties. Studies that retrieved data from a multicenter registry had a lower 30-day readmission rate than those reporting data from a single hospital or a large national database. Patient populations that only included Medicare patients had a higher 30-day readmission rate than populations of all insurance. The 30-day readmission rate has decreased in the past ten years. Age, length of stay, discharge to skilled nursing facility, increased BMI, ASA score greater than 3, and Medicare/Medicaid insurance showed statistically positive correlation with increased 30-day readmissions in greater than 75 percent of studies. Surgical site complications accounted for 46 percent of 30-day readmissions.Conclusions
This meta-analysis shows the present rate of 30-day readmissions in orthopedics. Demonstrable heterogeneity between studies underlines the importance of uniform collection and reporting of readmission rates for hospital evaluation and reimbursement. 相似文献14.
Background
In Western Europe, low back pain has the greatest burden of all diseases. When back pain persists, different medical specialists are involved and a lack of consensus exists among these specialists for medical decision-making in Chronic Low Back Pain (CLBP).Objective
To develop a decision tool for secondary or tertiary spine care specialists to decide which patients with CLBP should be seen by a spine surgeon or by other non-surgical medical specialists.Methods
A Delphi study was performed to identify indicators predicting the outcome of interventions. In the preparatory stage evidence from international guidelines and literature were summarized. Eligible studies were reviews and longitudinal studies. Inclusion criteria: surgical or non-surgical interventions and persistence of complaints, CLBP-patients aged 18–65 years, reported baseline measures of predictive indicators, and one or more reported outcomes had to assess functional status, quality of life, pain intensity, employment status or a composite score. Subsequently, a three-round Delphi procedure, to reach consensus on candidate indicators, was performed among a multidisciplinary panel of 29 CLBP-professionals (>five years CLBP-experience). The pre-set threshold for general agreement was ≥70%. The final indicator set was used to develop a clinical decision tool.Results
A draft list with 53 candidate indicators (38 with conclusive evidence and 15 with inconclusive evidence) was included for the Delphi study. Consensus was reached to include 47 indicators. A first version of the decision tool was developed, consisting of a web-based screening questionnaire and a provisional decision algorithm.Conclusions
This is the first clinical decision tool based on current scientific evidence and formal multidisciplinary consensus that helps referring the patient for consultation to a spine surgeon or a non-surgical spine care specialist. We expect that this tool considerably helps in clinical decision-making spine care, thereby improving efficient use of scarce sources and the outcomes of spinal interventions. 相似文献15.
Samuel L. Aitken Tiby B. Joseph Dhara N. Shah Todd M. Lasco Hannah R. Palmer Herbert L. DuPont Yang Xie Kevin W. Garey 《PloS one》2014,9(7)
Background
There are limited data examining healthcare resource utilization in patients with recurrent Clostridium difficile infection (CDI).Methods
Patients with CDI at a tertiary-care hospital in Houston, TX, were prospectively enrolled into an observational cohort study. Recurrence was assessed via follow-up phone calls. Patients with one or more recurrence were included in this study. The location at which healthcare was obtained by patients with recurrent CDI was identified along with hospital length of stay. CDI-attributable readmissions, defined as a positive toxin test within 48 hours of admission and a primary CDI diagnosis, were also assessed.Results
372 primary cases of CDI were identified of whom 64 (17.2%) experienced at least one CDI recurrence. Twelve of 64 patients experienced 18 further episodes of CDI recurrence. Of these 64 patients, 33 (50.8%) patients with recurrent CDI were readmitted of which 6 (18.2%) required ICU care, 29 (45.3%) had outpatient care only, and 2 (3.1%) had an ED visit. Nineteen (55.9%) readmissions were defined as CDI-attributable. For patients with CDI-attributable readmission, the average length of stay was 6±6 days.Conclusion
Recurrent CDI leads to significant healthcare resource utilization. Methods of reducing the burden of recurrent CDI should be further studied. 相似文献16.
Carl van Walraven Irfan A. Dhalla Chaim Bell Edward Etchells Ian G. Stiell Kelly Zarnke Peter C. Austin Alan J. Forster 《CMAJ》2010,182(6):551-557
Background
Readmissions to hospital are common, costly and often preventable. An easy-to-use index to quantify the risk of readmission or death after discharge from hospital would help clinicians identify patients who might benefit from more intensive post-discharge care. We sought to derive and validate an index to predict the risk of death or unplanned readmission within 30 days after discharge from hospital to the community.Methods
In a prospective cohort study, 48 patient-level and admission-level variables were collected for 4812 medical and surgical patients who were discharged to the community from 11 hospitals in Ontario. We used a split-sample design to derive and validate an index to predict the risk of death or nonelective readmission within 30 days after discharge. This index was externally validated using administrative data in a random selection of 1 000 000 Ontarians discharged from hospital between 2004 and 2008.Results
Of the 4812 participating patients, 385 (8.0%) died or were readmitted on an unplanned basis within 30 days after discharge. Variables independently associated with this outcome (from which we derived the nmemonic “LACE”) included length of stay (“L”); acuity of the admission (“A”); comorbidity of the patient (measured with the Charlson comorbidity index score) (“C”); and emergency department use (measured as the number of visits in the six months before admission) (“E”). Scores using the LACE index ranged from 0 (2.0% expected risk of death or urgent readmission within 30 days) to 19 (43.7% expected risk). The LACE index was discriminative (C statistic 0.684) and very accurate (Hosmer–Lemeshow goodness-of-fit statistic 14.1, p = 0.59) at predicting outcome risk.Interpretation
The LACE index can be used to quantify risk of death or unplanned readmission within 30 days after discharge from hospital. This index can be used with both primary and administrative data. Further research is required to determine whether such quantification changes patient care or outcomes.Readmission to hospital and death are adverse patient outcomes that are serious, common and costly.1,2 Several studies suggest that focused care after discharge can improve post-discharge outcomes.3–7 Being able to accurately predict the risk of poor outcomes after hospital discharge would allow health care workers to focus post-discharge interventions on patients who are at highest risk of poor post-discharge outcomes. Further, policy-makers have expressed interest in either penalizing hospitals with relatively high rates of readmission or rewarding hospitals with relatively low expected rates.8 To implement this approach, a validated method of standardizing readmission rates is needed.9Two validated models for predicting risk of readmission after hospital discharge have been published.10,11 However, these models are impractical to clinicians. Both require area-level information (e.g., neighbourhood socio-economic status and community-specific rates of admission) that is not readily available. Getting this information requires access to detailed tables, thereby making the model impractical. Second, both models are so complex that risk estimates cannot be attained from them without the aid of special software. Although these models have been used by health-system planners in the United Kingdom, we are unaware of any clinicians who use them when preparing patients for hospital discharge.Our primary objective was to derive and validate a clinically useful index to quantify the risk of early death or unplanned readmission among patients discharged from hospital to the community. 相似文献17.
Li-Fu Chen Hsu-Chueh Ho Yu-Chieh Su Moon-Sing Lee Shih-Kai Hung Pesus Chou Ching-Chieh J. Lee Li-Chu Lin Ching-Chih Lee 《PloS one》2013,8(6)
Background
Oral cancer requires considerable utilization of healthcare services. Wide resection of the tumor and reconstruction with free flap are widely used. Due to high recurrence rate, close follow-up is mandatory. This study was conducted to explore the relationship between the healthcare expenditure of oncological surgery and one-year follow up and provider volume.Methods
From the National Health Insurance Research Database published by the Taiwanese National Health Research Institute, the authors selected a total of 1300 oral cancer patients who underwent tumor resection and free flap reconstruction in 2008. Hierarchical linear regression analysis was subsequently performed to explore the relationship between provider volume and expenditures of oncological surgery and one-year follow-up period. Emergency department (ED) visits and 30-day readmission rates were also analyzed.Results
The mean expenditure for oncological surgery was $11080±4645 (all costs are given in U.S. dollars) and $10129±9248 for one-year follow up. For oncological surgery expenditure, oral cancer patients treated by low-volume surgeons had an additional $845 than those in high-volume surgeons in mixed model. For one-year follow-up expenditure, patients in low-volume hospitals had an additional $3439 than those in high-volume hospitals; patient in low-volume surgeons and medium-volume surgeons incurred an additional expenditure of $2065 and $1811 than those in high-volume surgeons. Oral cancer patients treated in low-volume hospitals incurred higher risk of 30-day readmission rate (odds ratio, 6.6; 95% confidence interval, 1.6–27).Conclusions
After adjusting for physician, hospital, and patient characteristics, low-volume provider performing wide excision with reconstructive surgery in oral cancer patients incurred significantly higher expenditure for oncological surgery and one-year healthcare per patient than did others with higher volumes. Treatment strategies adapted by high-volume providers should be further analyzed. 相似文献18.
Kahn JG Muraguri N Harris B Lugada E Clasen T Grabowsky M Mermin J Shariff S 《PloS one》2012,7(2):e31316
Background
Efficiently delivered interventions to reduce HIV, malaria, and diarrhea are essential to accelerating global health efforts. A 2008 community integrated prevention campaign in Western Province, Kenya, reached 47,000 individuals over 7 days, providing HIV testing and counseling, water filters, insecticide-treated bed nets, condoms, and for HIV-infected individuals cotrimoxazole prophylaxis and referral for ongoing care. We modeled the potential cost-effectiveness of a scaled-up integrated prevention campaign.Methods
We estimated averted deaths and disability-adjusted life years (DALYs) based on published data on baseline mortality and morbidity and on the protective effect of interventions, including antiretroviral therapy. We incorporate a previously estimated scaled-up campaign cost. We used published costs of medical care to estimate savings from averted illness (for all three diseases) and the added costs of initiating treatment earlier in the course of HIV disease.Results
Per 1000 participants, projected reductions in cases of diarrhea, malaria, and HIV infection avert an estimated 16.3 deaths, 359 DALYs and $85,113 in medical care costs. Earlier care for HIV-infected persons adds an estimated 82 DALYs averted (to a total of 442), at a cost of $37,097 (reducing total averted costs to $48,015). Accounting for the estimated campaign cost of $32,000, the campaign saves an estimated $16,015 per 1000 participants. In multivariate sensitivity analyses, 83% of simulations result in net savings, and 93% in a cost per DALY averted of less than $20.Discussion
A mass, rapidly implemented campaign for HIV testing, safe water, and malaria control appears economically attractive. 相似文献19.
Objective
We compared the readmission rates and the pattern of readmission among patients discharged against medical advice (AMA) to control patients discharged with approval over a one-year follow-up period.Methods
A retrospective matched-cohort study of 656 patients(328 were discharged AMA) who were followed for one year after their initial hospitalization at an urban university-affiliated teaching hospital in Vancouver, Canada that serves a population with high prevalence of addiction and psychiatric disorders. Multivariate conditional logistic regression was used to examine the independent association of discharge AMA on 14-day related diagnosis hospital readmission. We fit a multivariate conditional negative binomial regression model to examine the readmission frequency ratio between the AMA and non-AMA group.Principal Findings
AMA patients were more likely to be homeless (32.3% vs. 11%) and have co-morbid conditions such as psychiatric illnesses, injection drug use, HIV, hepatitis C and previous gastrointestinal bleeding. Patients discharged AMA were more likely to be readmitted: 25.6% vs. 3.4%, p<0.001 by day 14. The AMA group were more likely to be readmitted within 14 days with a related diagnosis than the non-AMA group (Adjusted Odds Ratio 12.0; 95% Confidence Interval [CI]: 3.7–38.9). Patients who left AMA were more likely to be readmitted multiple times at one year compared to the non-AMA group (adjusted frequency ratio 1.6; 95% CI: 1.3–2.0). There was also higher all-cause in-hospital mortality during the 12-month follow-up in the AMA group compared to non-AMA group (6.7% vs. 2.4%, p = 0.01).Conclusions
Patients discharged AMA were more likely to be homeless and have multiple co-morbid conditions. At one year follow-up, the AMA group had higher readmission rates, were predisposed to multiple readmissions and had a higher in-hospital mortality. Interventions to reduce discharges AMA in high-risk groups need to be developed and tested. 相似文献20.
Benjamin P. Linas Devra M. Barter Jared A. Leff Sabrina A. Assoumou Joshua A. Salomon Milton C. Weinstein Arthur Y. Kim Bruce R. Schackman 《PloS one》2014,9(5)