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Low serum albumin and total lymphocyte count as predictors of 30 day hospital readmission in patients 65 years of age or older.

ABSTRACT: Introduction. Hospital readmission within 30 days of discharge is a target for health care cost savings through the medicare Value Based Purchasing initiative. Because of this focus, hospitals and health systems are investing considerable resources into the identification of patients at risk of hospital readmission and designing interventions to reduce the rate of hospital readmission. Malnutrition is a known risk factor for hospital readmission. Materials and Methods. All medical patients 65 years of age or older discharged from Memorial Medical Center from January 1, 2012 to March 31, 2012 who had a determination of serum albumin level and total lymphocyte count on hospital admission were studied retrospectively. Admission serum albumin levels and total lymphocyte counts were used to classify the nutritional status of all patients in the study. Patients with a serum albumin less than 3.5 grams/dL and/or a TLC less than 1,500 cells per mm3 were classified as having protein energy malnutrition. The primary outcome investigated in this study was hospital readmission for any reason within 30 days of discharge. Results. The study population included 1,683 hospital discharges with an average age of 79 years. The majority of the patients were female (55.9%) and had a DRG weight of 1.22 (0.68). 219 patients (13%) were readmitted within 30 days of hospital discharge. Protein energy malnutrition was common in this population. Low albumin was found in 973 (58%) patients and a low TLC was found in 1,152 (68%) patients. Low albumin and low TLC was found in 709 (42%) of patients. Kaplan-Meier analysis shows any laboratory evidence of PEM is a significant (p < 0.001) predictor of hospital readmission. Low serum albumin (p < 0.001) and TLC (p = 0.018) show similar trends. Cox proportional-hazards regression analysis showed low serum albumin (Hazard Ratio 3.27, 95% CI [2.30-4.63]) and higher DRG weight (Hazard Ratio 1.19, 95% CI [1.03-1.38]) to be significant independent predictors of hospital readmission within 30 days. Discussion. This study investigated the relationship of PEM to the rate of hospital readmission within 30 days of discharge in patients 65 years of age or older. These results indicate that laboratory markers of PEM can identify patients at risk of hospital readmission within 30 days of discharge. This risk determination is simple and identifies a potentially modifiable risk factor for readmission: protein energy malnutrition.

SUBMITTER: Robinson R

PROVIDER: S-EPMC4558061 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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Low serum albumin and total lymphocyte count as predictors of 30 day hospital readmission in patients 65 years of age or older.

Robinson Robert R

PeerJ 20150813

Introduction. Hospital readmission within 30 days of discharge is a target for health care cost savings through the medicare Value Based Purchasing initiative. Because of this focus, hospitals and health systems are investing considerable resources into the identification of patients at risk of hospital readmission and designing interventions to reduce the rate of hospital readmission. Malnutrition is a known risk factor for hospital readmission. Materials and Methods. All medical patients 65 ye ...[more]

PMID: 26339558

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Project description:Importance:Falls are common among older adults, particularly those with previous falls and cognitive impairment and in the postdischarge period. Hospitals have financial incentives to reduce both inpatient falls and hospital readmissions, yet little is known about whether fall-related injuries (FRIs) are common diagnoses for 30-day hospital readmissions. Objective:To compare fall-related readmissions with other leading rehospitalization diagnoses, including for patients at greatest risk of readmission. Design, Setting, and Participants:Retrospective cohort study of the Hospital Cost and Utilization Project's Nationwide Readmissions Database of nationally representative US hospital discharges among Medicare beneficiaries aged 65 years and older from January 1, 2013, to November 30, 2014. The prevalence and ranking of FRIs compared with other diagnostic factors for 30-day unplanned hospital-wide readmissions were determined, overall and for 2 acute geriatric cohorts, classified by fall injury or cognitive impairment diagnoses observed at the index admission. Analyses were also stratified by patient discharge disposition (home, home health care, skilled nursing facility). Analyses were conducted from February 1, 2018, to February 26, 2018. Main Outcomes and Measures:Unplanned hospital-wide readmission within 30 days of discharge. Results:From the database, 8?382?074 eligible index admissions were identified, including 746?397 (8.9%) in the FRI cohort and 1?367?759 (16.3%) in the cognitive impairment cohort. Among the entire 8 382 074-discharge cohort, mean (SD) age was 77.7 (7.8) years and 4?736?281 (56.5%) were female. Overall, 1?205?962 (14.4%) of index admissions resulted in readmission, with readmission rates of 12.9% for those with a previous fall and 16.0% for patients with cognitive impairment. Overall, FRIs ranked as the third-leading readmission diagnosis, accounting for 60?954 (5.1%) of all readmission diagnoses. Within the novel acute geriatric cohorts, FRIs were the second-leading diagnosis for readmission both for patients with an FRI at index admission (10.3% of all readmission diagnoses) and those with cognitive impairment (7.0% of all readmission diagnoses). For those with an FRI at index admission and discharged home or to home health care, FRIs were the leading readmission diagnosis. Conclusions and Relevance:This study found that posthospital FRIs were a leading readmission diagnosis, particularly for patients originally admitted with a FRI or cognitive impairment. Targeting at-risk hospitalized older adults, particularly those discharged to home or home health care, is an underexplored, cost-effective mechanism with potential to reduce readmissions and improve patient care.

Project description:The 30-day readmission rate after hospitalization for a sickle cell crisis (SCC) is extremely high. Accurate information on readmission diagnoses, total readmission costs and factors associated with readmission is required to effectively plan resource allocation and to plan interventions to reduce readmission rates. The present study aimed to examine readmission diagnoses and factors associated with all-cause 30-day readmission after hospitalization for SCC. We analyzed 2016 nationwide readmission database (NRD) to identify patterns of 30-day readmission by patient demographic characteristics and time after hospitalization for SCC. We estimated the percentage and most common readmission diagnoses for 30-day and 7-day readmissions after discharge. We studied the relationship between risk factors and readmission and the impact of readmission on patient outcomes and resulting financial burden on health care in dollars. In 2016, of 67,887 discharges after index hospitalizations, 18099 (26.9%) were readmitted within 30-days. Of all readmissions, 5166 (7.6%) were readmitted within 7 days. The spectrum of readmission diagnoses was largely similar in both 30-day and 7-day readmission with more than 80% patients in both time periods readmitted with diagnoses related to SCC. The mean length of stay for readmitted patients was significantly longer than the index hospitalization (5.3 days (5.1-5.5) vs 4.9 days (CI 4.8-5.1, p?<?0.01). Also, the mean cost of hospitalization in readmitted patients $8485 was significantly higher than the index hospitalization $8064 p?<?0.01. In 2016, readmission among patients with SCC incurred an additional 95,445 hospitalization days resulting a total charge of $609 million and a total cost of $152 million in the US. On Multivariate analysis, age group 18-30 years, discharge against medical advice, higher Charlson comorbidity index, low socioeconomic status and admission at high volume centers were associated with a higher likelihood of 30-day readmission. Among patients hospitalized for SCC, 30-day readmissions were frequent throughout the month post hospitalization and resulted in an enormous financial burden on the United States healthcare system.

Project description:BACKGROUND:Hospital readmission is considered an adverse health outcome in older people, adding additional pressure on clinical resources within health care services. Despite numerous studies on risk factors for readmissions, studies find different strengths of respective determinants and there is a need to explore and identify patterns of risk factors in larger cohorts. OBJECTIVE:Exploring and identifying patterns of risk factors for acute, all-cause 30-day readmission in a Danish cohort of patients aged 65+. DESIGN:Register-based cohort study using individual-level linkable information on demographics, social determinants, clinical conditions, health care utilization, and provider determinants obtained from primary and secondary health care. PARTICIPANTS:Historic cohort of 1,267,752 admissions in 479,854 patients, aged 65+, discharged from Danish public hospitals from January 2007 to September 2010. MAIN MEASURES:We included patient-level variables and admission-level variables. Outcome was acute, all-cause 30-day readmission. Data was analyzed by univariable and multivariable logistic regression. Strength of associations was analyzed using Wald test statistics. Receiver operating characteristic (ROC) analysis was used for quantification of predictive ability. For validation, we used split-sample design. KEY RESULTS:Acute admission and number of days since previous hospital discharge were factors strongly associated with readmission. Patients at risk of future readmission suffered from comorbidity, consumed more drugs, and were frequent users of in- and outpatient health care services in the year prior to the index admission. Factors related to index admission were only weakly associated with readmission. The predictive ability was 0.709 (0.707-0.711) for acute readmission. CONCLUSIONS:In a general population of older people, we found that pre-hospital factors rather than hospital factors account for increased risk of readmission and are dominant contributors to predict acute all-cause 30-day readmission. Therefore, risk for excess readmission should be shared across sectors and focus the care trajectory over time rather than distinct care episodes.

Project description:RESEARCH OBJECTIVE:Pharmacists are an expensive and limited resource in the hospital and outpatient setting. A pharmacist can spend up to 25% of their day planning. Time spent planning is time not spent delivering an intervention. A readmission risk adjustment model has potential to be used as a universal outcome-based prioritization tool to help pharmacists plan their interventions more efficiently. Pharmacy-specific predictors have not been used in the constructs of current readmission risk models. We assessed the impact of adding pharmacy-specific predictors on performance of readmission risk prediction models. STUDY DESIGN:We used an observational retrospective cohort study design to assess whether pharmacy-specific predictors such as an aggregate pharmacy score and drug classes would improve the prediction of 30-day readmission. A model of age, sex, length of stay, and admission category predictors was used as the reference model. We added predictor variables in sequential models to evaluate the incremental effect of additional predictors on the performance of the reference. We used logistic regression to regress the outcomes on predictors in our derivation dataset. We derived and internally validated our models through a 50:50 split validation of our dataset. POPULATION STUDIED:Our study population (n=350,810) was of adult admissions at hospitals in a large integrated health care delivery system. PRINCIPAL FINDINGS:Individually, the aggregate pharmacy score and drug classes caused a nearly identical but moderate increase in model performance over the reference. As a single predictor, the comorbidity burden score caused the greatest increase in model performance when added to the reference. Adding the severity of illness score, comorbidity burden score and the aggregate pharmacy score to the reference caused a cumulative increase in model performance with good discrimination (c statistic, 0.712; Nagelkerke R, 0.112). The best performing model included all predictors: severity of illness score, comorbidity burden score, aggregate pharmacy score, diagnosis groupings, and drug subgroups. CONCLUSIONS:Adding the aggregate pharmacy score to the reference model significantly increased the c statistic but was out-performed by the comorbidity burden score model in predicting readmission. The need for a universal prioritization tool for pharmacists may therefore be potentially met with the comorbidity burden score model. However, the aggregate pharmacy score and drug class models still out-performed current Medicare readmission risk adjustment models. IMPLICATIONS FOR POLICY OR PRACTICE:Pharmacists have a great role in preventing readmission, and therefore can potentially use one of our models: comorbidity burden score model, aggregate pharmacy score model, drug class model or complex model (a combination of all 5 major predictors) to prioritize their interventions while exceeding Medicare performance measures on readmission. The choice of model to use should be based on the availability of these predictors in the health care system.

Project description:BackgroundLowering hospital readmission rates has become a primary target for the Centers for Medicare & Medicaid Services, but studies of the relationship between adherence to the recommended hospital care processes and readmission rates have provided inconsistent and inconclusive results.ObjectiveTo examine the association between hospital performance on Medicare's Hospital Compare process quality measures and 30-day readmission rates for patients with acute myocardial infarction (AMI), heart failure and pneumonia, and for those undergoing major surgery.Design, setting and participantsWe assessed hospital performance on process measures using the 2007 Hospital Inpatient Quality Reporting Program. The process measures for each condition were aggregated in two separate measures: Overall Measure (OM) and Appropriate Care Measure (ACM) scores. Readmission rates were calculated using Medicare claims.Main outcome measureRisk-standardized 30-day all-cause readmission rate was calculated as the ratio of predicted to expected rate standardized by the overall mean readmission rate. We calculated predicted readmission rate using hierarchical generalized linear models and adjusting for patient-level factors.ResultsAmong patients aged ≥ 66 years, the median OM score ranged from 79.4 % for abdominal surgery to 95.7 % for AMI, and the median ACM scores ranged from 45.8 % for abdominal surgery to 87.9 % for AMI. We observed a statistically significant, but weak, correlation between performance scores and readmission rates for pneumonia (correlation coefficient R = 0.07), AMI (R = 0.10), and orthopedic surgery (R = 0.06). The difference in the mean readmission rate between hospitals in the 1st and 4th quartiles of process measure performance was statistically significant only for AMI (0.25 percentage points) and pneumonia (0.31 percentage points). Performance on process measures explained less than 1 % of hospital-level variation in readmission rates.ConclusionsHospitals with greater adherence to recommended care processes did not achieve meaningfully better 30-day hospital readmission rates compared to those with lower levels of performance.

Dataset Information

Low serum albumin and total lymphocyte count as predictors of 30 day hospital readmission in patients 65 years of age or older.

Publications

Low serum albumin and total lymphocyte count as predictors of 30 day hospital readmission in patients 65 years of age or older.

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