Are diagnosis specific outcome indicators based on administrative data useful in assessing quality of hospital care?

Background: Hospital performance reports based on administrative data should distinguish differences in quality of care between hospitals from case mix related variation and random error effects. A study was undertaken to determine which of 12 diagnosis-outcome indicators measured across all hospitals in one state had significant risk adjusted systematic (or special cause) variation (SV) suggesting differences in quality of care. For those that did, we determined whether SV persists within hospital peer groups, whether indicator results correlate at the individual hospital level, and how many adverse outcomes would be avoided if all hospitals achieved indicator values equal to the best performing 20% of hospitals.

Methods: All patients admitted during a 12 month period to 180 acute care hospitals in Queensland, Australia with heart failure (n = 5745), acute myocardial infarction (AMI) (n = 3427), or stroke (n = 2955) were entered into the study. Outcomes comprised in-hospital deaths, long hospital stays, and 30 day readmissions. Regression models produced standardised, risk adjusted diagnosis specific outcome event ratios for each hospital. Systematic and random variation in ratio distributions for each indicator were then apportioned using hierarchical statistical models.

Results: Only five of 12 (42%) diagnosis-outcome indicators showed significant SV across all hospitals (long stays and same diagnosis readmissions for heart failure; in-hospital deaths and same diagnosis readmissions for AMI; and in-hospital deaths for stroke). Significant SV was only seen for two indicators within hospital peer groups (same diagnosis readmissions for heart failure in tertiary hospitals and inhospital mortality for AMI in community hospitals). Only two pairs of indicators showed significant correlation. If all hospitals emulated the best performers, at least 20% of AMI and stroke deaths, heart failure long stays, and heart failure and AMI readmissions could be avoided.

Conclusions: Diagnosis-outcome indicators based on administrative data require validation as markers of significant risk adjusted SV. Validated indicators allow quantification of realisable outcome benefits if all hospitals achieved best performer levels. The overall level of quality of care within single institutions cannot be inferred from the results of one or a few indicators.

     

Comparison between planned and unplanned readmissions to a department of internal medicine

The objective of this study was to assess the respective frequency of planned and unplanned early readmissions after discharge from an internal medicine department, and to identify and compare risk factors for these two types of readmissions. Readmissions within 31 days of discharge were identified as planned or unplanned based on analysis of discharge summaries. Time-failure methods were used to describe the risk of readmissions over time and to assess relationships between patient and index stay characteristics and risk of readmission. Of 5828 patients discharged alive, 730 (12.5%) were readmitted within 31 days. There were slightly more planned than unplanned readmissions (393 vs. 337). The difference in time-to-event functions was significant (P=0.04). The risk of planned readmission was increased for men, younger patients, and for patients discharged with a diagnosis of coronary heart disease, cardiac arrhythmia, and neoplastic disease. Increased risk of unplanned readmission was associated with index length of stay longer than 3 days, an increased number of comorbidities, and with a diagnosis of neoplastic disease. Planned readmissions constitute more than half of early readmissions to our internal medicine department. Therefore, a crude readmission rate is unlikely to be a useful indicator of quality of care. Several patient characteristics influence the risk of unplanned readmission, suggesting that case-mix adjustments are necessary when readmission rates are compared between institutions or tracked over time.     

Impact of physician training level on emergency readmission within internal medicine

OBJECTIVES: The research question was whether training level of admitting physicians and referrals from practitioners in primary health care (PHC) are risk factors for emergency readmission within 30 days to internal medicine. METHODS: This report is a prospective multicenter study carried out during 1 month in 1997 in seven departments of internal medicine in the County of Stockholm, Sweden. Two of the units were at university hospitals, three at county hospitals and two in district hospitals. The study area is metropolitan-suburban with 1,762,924 residents. Data were analyzed by multiple logistic regression. RESULTS: A total of 5,131 admissions, thereby 408 unplanned readmissions (8 percent) were registered (69.8 percent of 7348 true inpatient episodes). The risk of emergency readmission increased with patient's age and independently 1.40 times (95 percent confidence interval [CI], 1.13-1.74) when residents decided on hospitalization. Congestive heart failure as primary or comorbid condition was the main reason for unplanned readmission. Referrals from PHC were associated with risk decrease (odds ratio, 0.53; 95 percent CI, 0.38-0.73). CONCLUSION: The causes of unplanned hospital readmissions are mixed. Patient contact with primary health care appears to reduce the recurrence. In addition to the diagnoses of cardiac failure, training level of admitting physicians in emergency departments was an independent risk factor for early readmission. Our conclusion is that it is cost-effective to have all decisions on admission to hospital care confirmed by senior doctors. Inappropriate selection of patients to inpatient care contributes to poor patient outcomes and reduces cost-effectiveness and quality of care.     

Do Hospital Length of Stay and Staffing Ratio Affect Elderly Patients' Risk of Readmission? A Nation‐wide Study of Norwegian Hospitals

OBJECTIVE: To test whether there is an association between hospital operating conditions such as average length of stays (LOS) and staffing ratio, and elderly patients' risk of readmission. DATA SOURCES: The main data source was a national patient database of admissions to all acute-care Norwegian hospitals during the year of 1996. STUDY DESIGN: It is a cross-sectional study, where Cox' regression analysis was used to test the factors acting on the probability of early unplanned readmission (within 30 days), and later occuring ones. The principal hospital variables included average hospital LOS and staffing ratio (discharges per man-years of personnel). Adjusting patient variables in the model included age, gender, and cost-weights of the Diagnosis Related Groups (DRGs). DATA EXTRACTION METHODS: The selected material included discharges from 59 hospitals, and 113,055 elderly patients (> or = 67 years). Multiple admissions to the same hospital were linked together chronologically, and additional hospital data were matched on. To maximize the association between the index stay and the defined outcome (unplanned readmission), no intervening planned admission was accepted. PRINCIPAL FINDINGS: Being admitted to a hospital with relatively short average LOS increased the patient's risk of early readmission significantly. In addition it was found that more intensive care (more staff) could have a compensatory effect. Furthermore, the predictive factors were shown to be time dependent, as hospital variables had much less impact on readmissions occurring late (within 90-180 days). CONCLUSIONS: The results give support to the assumption of a link between hospital operating conditions and patient outcome.     

The Association between Oral Nutritional Supplements and 30-Day Hospital Readmissions of Malnourished Patients at a US Academic Medical Center

BackgroundMalnutrition affects up to 50% of hospitalized patients and contributes to adverse health and economic outcomes, but often remains unrecognized or undertreated.ObjectiveThis study assessed the utilization of oral nutritional supplements (ONS) and its association with the number of 30-day unplanned hospital readmissions of adult malnourished patients in comparison with the readmissions rates of their malnourished counterparts who did not receive ONS.DesignThis was a retrospective cohort study.Participants/settingOf 153,161 inpatient encounters analyzed, a total of 8,713 (5.7%) malnourished adults admitted to an academic medical center hospital in the United States between October 1, 2016, and September 30, 2017 were included in the analyses. The study utilized records of patients at risk of malnutrition on admission and subsequently diagnosed as malnourished by a registered dietitian following established criteria.Main outcomes measuresONS utilization rate, hospital length of stay (LOS), and 30-day unplanned hospital readmissions data were obtained from electronic medical records.Statistical analyses performedThe associations between the number of 30-day unplanned hospital readmissions and ONS use were analyzed using mixed-effects negative binomial regression models, with coefficients and 95% CIs reported. Important covariates such as age, sex, and the severity of illness index were included in the regression models.ResultsOnly 3.1% of malnourished patients received ONS. ONS users had 38.8% fewer readmissions compared with non-ONS counterparts (P=0.017). The reduction in hospital readmissions by ONS was even greater for oncology patients (46.1%, P<0.001). A 50% reduction in time from hospital admission to ONS provision was associated with a 10.2% (P<0.01), 10.2% (P=0.014), and 16.6% (P<0.01) decrease in LOS for overall, oncology, and intensive care unit encounters, respectively.ConclusionsIn a large cohort of malnourished adult inpatient encounters, ONS provision rate was low, but when used, ONS intervention was associated with 38.8% fewer 30-day readmissions. This association was more pronounced for oncology encounters. Shorter LOS was observed when the interval between admission and ONS initiation was shorter. Reduced LOS and readmissions rates could result in financial benefits for health care systems prioritizing hospital nutrition care, in addition to informing significant medical benefits for their patients.     

Measuring potentially avoidable hospital readmissions

The objectives of this study were to develop a computerized method to screen for potentially avoidable hospital readmissions using routinely collected data and a prediction model to adjust rates for case mix. We studied hospital information system data of a random sample of 3,474 inpatients discharged alive in 1997 from a university hospital and medical records of those (1,115) readmitted within 1 year. The gold standard was set on the basis of the hospital data and medical records: all readmissions were classified as foreseen readmissions, unforeseen readmissions for a new affection, or unforeseen readmissions for a previously known affection. The latter category was submitted to a systematic medical record review to identify the main cause of readmission. Potentially avoidable readmissions were defined as a subgroup of unforeseen readmissions for a previously known affection occurring within an appropriate interval, set to maximize the chance of detecting avoidable readmissions. The computerized screening algorithm was strictly based on routine statistics: diagnosis and procedures coding and admission mode. The prediction was based on a Poisson regression model. There were 454 (13.1%) unforeseen readmissions for a previously known affection within 1 year. Fifty-nine readmissions (1.7%) were judged avoidable, most of them occurring within 1 month, which was the interval used to define potentially avoidable readmissions (n = 174, 5.0%). The intra-sample sensitivity and specificity of the screening algorithm both reached approximately 96%. Higher risk for potentially avoidable readmission was associated with previous hospitalizations, high comorbidity index, and long length of stay; lower risk was associated with surgery and delivery. The model offers satisfactory predictive performance and a good medical plausibility. The proposed measure could be used as an indicator of inpatient care outcome. However, the instrument should be validated using other sets of data from various hospitals.     

Stability over time of the “hospital effect” on 30-day unplanned readmissions: Evidence from administrative data

Past studies showed that hospital characteristics affect hospital performance in terms of 30-day unplanned readmissions, proving the existence of a “hospital effect”. However, the stability over time of this effect has been under-investigated. This study offers new evidence about the stability over time of the hospital effect on 30-day unplanned readmissions.Using 78,907 heart failure (HF) records collected from 116 hospitals in the Lombardy Region (Northern Italy) over three years (2010-2012), this study analysed hospital performance in terms of 30-day unplanned readmissions. Hospitals with unusually high and low readmission rates were identified through multi-level regression that combined both patient and hospital covariates in each year.Our results confirm that although hospital covariates – and the connected managerial choices – affect the 30-day unplanned readmissions of a specific year, their effect is not stable in the short-term (3 years). This has important implications for pay-for-performance schemes and quality improvement initiatives.     

Outcomes and the quality of care for patients hospitalized with heart failure.

OBJECTIVE: The purpose of this study was to determine whether process quality indicators derived from evidence-based guidelines for heart failure patients were associated with outcome indicators (hospital mortality and readmissions). DESIGN: A retrospective cohort-study among patients discharged with a primary or secondary International Classification of Disease, 10th revision (ICD-10) heart failure code from 1 January to 31 December 1999. SETTING: The study was implemented in three Swiss academic medical centers. STUDY PARTICIPANTS: Records of 1634 patients hospitalized with heart failure were abstracted. Demographic characteristics, risk factors, symptoms and findings at admission, and discharge characteristics were recorded. Main outcome measure. Process quality indicators were derived from evidence-based guidelines, related to appropriate management and treatment of heart failure patients. Hospital mortality was measured in a chart abstraction process. Thirty-day readmissions were calculated using administrative data from hospitals. RESULTS: Among the three hospitals, 1153 patients with heart failure were eligible for this study. Mean age was 75.3 years (standard deviation 12.7) and 45.7% of patients were female. Ventricular function (VF) was determined in 69% of patients. The adjusted odds-ratios (OR) for the VF not determined were 1.74 [95% confidence interval (CI) 1.06-2.84] for hospital mortality and 0.75 (95% CI 0.47-1.18) for 30-day readmissions. Among patients with left ventricular systolic dysfunction and no contraindication to angiotensin-converting enzyme inhibitor (ACEI), 54% were prescribed target-dose ACEI or angiotensin receptor blockers at discharge, 32% received ACEI at less then target dose, and 14% received no ACEI at discharge. Adjusted ORs (95% CI) for readmissions were 0.89 (0.28-2.84) for no ACEI and 1.17 (0.56-2.43) for less than target ACEI compared with target dose. CONCLUSIONS: Among patients with heart failure, the determination of VF was associated with hospital mortality. However, process indicators derived from evidence-based guidelines were not related to early readmissions in three Swiss university hospitals.     

What do we conclude from re-admissions about quality of inpatient care?

Quality assurance in hospital care increasingly focuses on evaluation of outcome. Problems arise with displaying results of medical care beyond discharge. In this context hospital readmissions are often used as outcome variable. But it is unclear whether readmissions are meaningful indices of quality of hospital care and if so, where to get valid data on readmissions. We used claims data of the regional health insurance fund in Saxony-Anhalt (AOK Saxony-Anhalt) from 2002 and 2003 (850,000 insured; nearly 300,000 cases per year). All hospital admissions of a insured person are identified by an anonymous id-number independent of the admitting hospital. By this way we can analyze readmissions individually. Readmission are frequent events in hospital care. Nearly one third of all patients were admitted at least a second time in 2003. 18 % of all hospital cases are readmissions within 30 days after discharge. Readmissions concentrated on chronically ill, oncological, or multimorbid patients. Many of the readmissions take place in the context of planned therapies or post-operative treatment. 'Revolving-door patients' with multiple readmissions point to problems in cooperation of ambulatory and hospital care. By defining tracer diagnoses and specific causes of readmissions unplanned readmissions may be identified as a quality indicator of suboptimal care. Readmissions don't express suboptimal care per se. But taking into account methodological aspects a tracer approach with defining specific unplanned readmissions may provide meaningful outcome indicators. These can be derived from claims data fast, routinely, and with low costs. Further validation of the approach is needed.     

Understanding the large heterogeneity in hospital readmissions and mortality for acute myocardial infarction

This study aims to investigate the variation in two acute myocardial infarction (AMI) outcomes across public hospitals in Portugal. In-hospital mortality and 30-day unplanned readmissions were studied using two distinct AMI cohorts of adults discharged from all acute care public hospital centers in Portugal from 2012−2015. Hierarchical generalized linear models were used to assess the association between patient and hospital characteristics and hospital variability in the two outcomes.Our findings indicate that hospitals are not performing homogeneously—the risk of adverse events tends to be consistently larger in some hospitals and consistently lower in other hospitals. While patient characteristics accounted for a larger share of the explained between-hospital variance, hospital characteristics explain an additional 8% and 10% of hospital heterogeneity in the mortality and the readmission cohorts respectively. Admissions to hospitals with low AMI caseloads or located in Alentejo/Algarve and Lisbon had a higher risk of mortality. Discharges from larger-sized hospitals were associated with increased risk of readmissions. Future health policies should incorporate these findings in order to incentivize more consistent health care outcomes across hospitals. Further investigation addressing geographical disparities, hospital caseload and practices is needed to direct actions of improvement to specific hospitals.     

Unplanned admissions to inpatient psychiatric treatment and services received prior to admission

BackgroundInpatient bed numbers are continually being reduced but are not being replaced with adequate alternatives in primary health care. There is a considerable risk that eventually all inpatient treatment will be unplanned, because planned or elective treatments are superseded by urgent needs when capacity is reduced.Aims of the studyTo estimate the rate of unplanned admissions to inpatient psychiatric treatment facilities in Norway and analyse the difference between patients with unplanned and planned admissions regarding services received during the three months prior to admission as well as clinical, demographical and socioeconomic characteristics of patients.MethodUnplanned admissions were defined as all urgent and involuntary admissions including unplanned readmissions. National mapping of inpatients was conducted in all inpatient treatment psychiatric wards in Norway on a specific date in 2012. Binary logit regressions were performed to compare patients who had unplanned admissions with patients who had planned admissions (i.e., the analyses were conditioned on admission to inpatient psychiatric treatment).ResultsPatients with high risk of unplanned admission are suffering from severe mental illness, have low functional level indicated by the need for housing services, high risk for suicide attempt and of being violent, low education and born outside Norway.ConclusionSpecialist mental health services should support the local services in their efforts to prevent unplanned admissions by providing counselling, short inpatient stays, outpatient treatment and ambulatory outpatient psychiatry services.Implications for health policiesThis paper suggests the rate of unplanned admissions as a quality indicator and considers the introduction of economic incentives in the income models at both service levels.     

Development of claims‐based measures of unplanned acute care with superior power for assessing the effectiveness of interventions following acute care

ObjectiveTo develop outcome measures that are more sensitive than current measures for evaluating primary or transitional care after hospitalizations, emergency department (ED) visits, or observation stays.Data SourcesMedicare claims data from January 1, 2015, to October 31, 2017, for 1 261 707 Medicare fee‐for‐service beneficiaries served by (a) primary care practices participating in Track 1 of the Comprehensive Primary Care Plus (CPC+) initiative, and (b) their matched comparison practices.Study DesignGiven the poor statistical power in many studies to detect effects on readmissions, we developed two novel claims‐based measures of unplanned acute care (UAC) following an index acute care event. The first measure assesses the proportion of hospitalizations followed by an unplanned readmission, ED visit, or observation stay within 30 days of discharge; the second assesses the proportion of ED visits and observation stays followed by a hospitalization, ED visit, or observation stay within 30 days. We calculate minimum detectable effects (MDEs) for both measures and for a conventional measure of 30‐day unplanned readmissions, using CPC+ data.Principal FindingsRepeat UAC events are common among Medicare beneficiaries served by the CPC+ practices. In 2017, 22% of discharges and 21% of ED visits and observation stays had a UAC event within 30 days. Readmissions were the most common UAC event following discharge, whereas ED visits were most common following index ED visits or observation stays. MDEs are 25%‐40% lower for the new measures than for the standard 30‐day readmissions measure, indicating better statistical power to detect impacts of primary or transitional care interventions.ConclusionsThis study introduces two new claims‐based measures to assess quality of care during a patient''s vulnerable period following acute care. The new measures complement existing measures, covering a broader range of UAC events than the standard 30‐day readmissions measure, and yielding greater statistical power.     

Using administrative data to assess the impact of length of stay on readmissions: study of two procedures in surgery and obstetrics

BackgroundThe prospective payment system for the French short-stay hospitals creates a financial incentive to reduce length of stay. The potential impact of the resulting decrease in length of stay on the quality of healthcare is unknown. Readmission rates are valid outcome indicators for some clinical procedures.MethodsRetrospective study of the association between length of stay and unplanned readmissions related to the initial stay, for two procedures: cholecystectomy and vaginal delivery.DataAdministrative diagnosis-related groups database of “Assistance publique–Hôpitaux de Paris”, a large teaching hospital, for years 2002 to 2005.ResultsThe risk of readmission according to length of stay, taking age, sex, comorbidity, hospital and year of admission into account, followed a J-shaped curve for both procedures. The probability of readmission was higher for very short stays, with odds ratios and 95% confidence intervals of 6.03 [2.67–13.59] for cholecystectomies (1- versus 3-night stays), and of 1.74 [1.05–2.91] for vaginal deliveries (2- versus 3-night stays).ConclusionFor both procedures, the shortest lengths of stay are associated with a higher readmission probability. Suitable indicators derived from administrative databases would enable monitoring of the association between length of stay and readmissions.     

Readmission rate as an indicator of hospital performance: the case of Spain

OBJECTIVES: Hospital readmission rate is currently used as a quality of care indicator, although its validity has not been established. Our aims were to identify the frequency and characteristics of potential avoidable readmissions and to compare the assessment of quality of care derived from readmission rate with other measure of quality (judgment of experts). METHODS: Design: cross-sectional observational study; Setting: acute care hospital located in Marbella, South of Spain; Study participants: random sample of patients readmitted at the hospital within six months from discharge (n = 363); Interventions: review of clinical records by a pair of observers to assess the causes of readmissions and their potential avoidability; Main measures: logistic regression analysis to identify the variables from the databases of hospital discharges which are related to avoidability of readmissions. Determination of sensitivity and specificity of different definitions of readmission rate to detect avoidable situations. RESULTS: Nineteen percent of readmissions were considered potentially avoidable. Variables related to readmission avoidability were (i) time elapsed between index admission and readmission and (ii) difference in diagnoses of both episodes. None of the definitions of readmission rate used in this study provided adequate values of sensitivity and specificity in the identification of potentially avoidable readmissions. CONCLUSIONS: Most readmissions in our hospital were unavoidable. Thus, readmission rate might not be considered a valid indicator of quality of care.     

Impact of UK Primary Care Policy Reforms on Short-Stay Unplanned Hospital Admissions for Children With Primary Care–Sensitive Conditions

PURPOSEWe aimed to assess the impact of UK primary care policy reforms implemented in April 2004 on potentially avoidable unplanned short-stay hospital admissions for children with primary care–sensitive conditions.METHODSWe conducted an interrupted time series analysis of hospital admissions for all children aged younger than 15 years in England between April 2000 and March 2012 using data from National Health Service public hospitals in England. The main outcomes were annual short-stay (<2-day) unplanned hospital admission rates for primary care–sensitive infectious and chronic conditions.RESULTSThere were 7.8 million unplanned admissions over the study period. More than one-half (4,144,729 of 7,831,633) were short-stay admissions for potentially avoidable infectious and chronic conditions. The primary care policy reforms of April 2004 were associated with an 8% increase in short-stay admission rates for chronic conditions, equivalent to 8,500 additional admissions, above the 3% annual increasing trend. Policy reforms were not associated with an increase in short-stay admission rates for infectious illness, which were increasing by 5% annually before April 2004. The proportion of primary care–referred admissions was falling before the reforms, and there were further sharp reductions in 2004.CONCLUSIONSThe introduction of primary care policy reforms coincided with an increase in short-stay admission rates for children with primary care–sensitive chronic conditions, and with more children being admitted through emergency departments. Short-stay admission rates for primary care–sensitive infectious illness increased more steadily and could be related to lowered thresholds for hospital admission.     

Evaluating integrative medicine acute stroke inpatient care in South Korea

High demand for traditional Korean medicine led to a policy change in 2010 allowing hospitals to provide Integrative medicine care that combines Western medicine and Korean medicine. This study evaluated the effects of Integrative medicine compared to Western medicine-only for managing acute stroke in South Korean hospitals.A retrospective matched case-control observational study was conducted for acute stroke patients admitted nationwide in 2012 and 2013. Propensity score matching was used to adjust for the likelihood of selecting Integrative medicine. Hierarchical generalized linear models were used to control for patient characteristics at the episode of care (level 1) and cluster effects from the hospitals (level 2).A total of 1182 patients and 65 hospitals were matched and analyzed. Receiving Integrative medicine significantly increased the average length of stay (OR 1.27; 95% CI 1.13–1.42), total cost of inpatient care (OR 1.93; 95% CI 1.62–2.31), and per-day cost (OR 1.34; 95% CI 1.21–1.47). Receiving Integrative medicine did not affect all-cause 3-month emergency readmissions (OR 1.36; 95% CI 0.92–2.02). However, Integrative medicine was associated with a reduced risk of all-cause mortality at 3 months (OR 0.36; 90% CI 0.13–0.99) and 12 months (OR 0.34; 95% CI 0.15–0.75) after admission.Receiving Integrative medicine was associated with improved 3-month and 12-month survival, greater healthcare utilization and higher costs. Further economic evaluations are needed to guide policy for efficient integration of Korean medicine and Western medicine.     

Predictors of Rehospitalization Among Elderly Patients Admitted to a Rehabilitation Hospital: The Role of Polypharmacy,Functional Status,and Length of Stay

Objectives

Rehospitalizations for elderly patients are an increasing health care burden. Nonetheless, we have limited information on unplanned rehospitalizations and the related risk factors in elderly patients admitted to in-hospital rehabilitation facilities after an acute hospitalization.

Setting

In-hospital rehabilitation and aged care unit.

Design

Retrospective cohort study.

Participants

Elderly patients 65 years or older admitted to an in-hospital rehabilitation hospital after an acute hospitalization between January 2004 and June 2011.

Measurements

The rate of 30-day unplanned rehospitalization to hospitals was recorded. Risk factors for unplanned rehospitalization were evaluated at rehabilitation admission: age, comorbidity, serum albumin, number of drugs, decline in functional status, delirium, Mini Mental State Examination score, and length of stay in the acute hospital. A multivariable Cox proportional regression model was used to identify the effect of these risk factors for time to event within the 30-day follow-up.

Results

Among 2735 patients, with a median age of 80 years (interquartile range 74–85), 98 (4%) were rehospitalized within 30 days. Independent predictors of 30-day unplanned rehospitalization were the use of 7 or more drugs (hazard ratio [HR], 3.94; 95% confidence interval, 1.62–9.54; P = .002) and a significant decline in functional status (56 points or more at the Barthel Index) compared with the month before hospital admission (HR 2.67, 95% CI: 1.35–5.27; P = .005). Additionally, a length of stay in the acute hospital of 13 days or more carried a twofold higher risk of rehospitalization (HR 2.67, 95% CI: 1.39–5.10); P = .003).

Conclusions

The rate of unplanned rehospitalization was low in this study. Polypharmacy, a significant worsening of functional status compared with the month before acute hospital admission, and hospital length of stay are important risk factors.     

女性乳腺癌术后复发风险的时间分布规律

目的 探讨女性乳腺癌术后复发风险的时间分布规律.方法 对1996年1月1日～2008年12月31日期间在某市四家“三甲”医院手术治疗的女性乳腺癌患者进行随访,并应用生存分析的方法分析术后复发风险.结果 单因素和多因素生存分析均提示,腋下淋巴结转移和肿瘤直径较大是乳腺癌术后复发的危险因素(P＜0.05).复发风险时间曲线呈现双峰型,分别出现在术后第2年和第5年,在有腋下淋巴结转移及肿瘤直径较大的患者中叠加效应更为明显.结论 根据患者的特征制定个性化的术后随访和辅助治疗策略,将有助于预防乳腺癌的术后复发.     

Health Care Costs and Utilization Predictions by the Skilled Nursing Facility Readmission Risk Instrument

ObjectivesHealth care providers at hospitals and skilled nursing facilities (SNFs) are increasingly expected to optimize care of post-acute patients to reduce hospital readmissions and contain costs. To achieve these goals, providers need to understand their patients’ risk of hospital readmission and how this risk is associated with health care costs. A previously developed risk prediction model identifies patients’ probability of 30-day hospital readmission at the time of discharge to an SNF. With a computerized algorithm, we translated this model as the Skilled Nursing Facility Readmission Risk (SNFRR) instrument. Our objective was to evaluate the relationship between 30-day health care costs and hospital readmissions according to the level of risk calculated by this model.DesignThis retrospective cohort study used SNFRR scores to evaluate patient data.Setting and ParticipantsThe patients were discharged from Mayo Clinic Rochester hospitals to 11 area SNFs.MethodsWe compared the outcomes of all-cause 30-day standardized direct medical costs and hospital readmissions between risk quartiles based on the distribution of SNFRR scores for patients discharged to SNFs for post-acute care from April 1 through November 30, 2017.ResultsMean 30-day all-cause standardized costs were positively associated with SNFRR score quartiles and ranged from $9199 in the fourth quartile (probability of readmission, 0.27-0.66) to $2679 in the first quartile (probability of readmission, 0.07-0.13) (P ≤ .05). Patients in the fourth SNFRR score quartile had 5.68 times the odds of 30-day hospital readmission compared with those in the first quartile.Conclusions and ImplicationsThe SNFRR instrument accurately predicted standardized direct health care costs for patients on discharge to an SNF and their risk for 30-day hospital readmission. Therefore, it could be used to help categorize patients for preemptive interventions. Further studies are needed to confirm its validity in other institutions and geographic areas.     

Do Older Rural and Urban Veterans Experience Different Rates of Unplanned Readmission to VA and Non‐VA Hospitals?

ABSTRACT:  Context: Unplanned readmission within 30 days of discharge is an indicator of hospital quality. Purpose: We wanted to determine whether older rural veterans who were enrolled in the VA had different rates of unplanned readmission to VA or non-VA hospitals than their urban counterparts. Methods: We used the combined VA/Medicare dataset to examine 3,513,912 hospital admissions for older veterans that occurred in VA or non-VA hospitals between 1997 and 2004. We calculated 30-day readmission rates and odds ratios for rural and urban veterans, and we performed a logistic regression analysis to determine whether living in a rural setting or initially using the VA for hospitalization were independent risk factors for unplanned 30-day readmission, after adjusting for age, sex, length of stay of the index admission, and morbidity. Findings: Overall, rural veterans had slightly higher 30-day readmission rates than their urban counterparts (17.96% vs 17.86%; OR 1.006, 95% CI: 1.0004, 1.013). For both rural- and urban-dwelling veterans, readmission after using a VA hospital was more common than after using a non-VA hospital (20.7% vs 16.8% for rural veterans, 21.2% vs 16.1% for urban veterans). After adjusting for other variables, readmission was more likely for rural veterans and following admission to a VA hospital. Conclusions: Our findings suggest that VA should consider using the unplanned readmission rate as a performance metric, using the non-VA experience of veterans as a performance benchmark, and helping rural veterans select higher performing non-VA hospitals.