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      Predictive Value of LACE Scores for Pediatric Readmissions

      research-article
      , MD 1 , , , MD 2 , , MD 2 , , MBA, RN, RRT 1 , , PhD 1 , , MS 1 , , MD 1
      The Permanente Journal
      The Permanente Press
      readmission rates, LACE score, decreasing readmission rates

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          Abstract

          Introduction

          Hospital readmissions are recognized as a prevalent, yet potentially preventable, personal and economic burden. Length of stay, Acuity of admission, Comorbidities, and number of Emergency Department visits in the preceding 6 months can be quantified into one score, the LACE score. LACE scores have previously been identified to correlate with hospital readmissions within 30 days of discharge, but research specific to the pediatric population is scant. The objective of the present study was to investigate if LACE scores, in addition to other factors, can be utilized to create a predictive pediatric hospital readmission model that may ultimately be used to decrease readmission rates.

          Methods

          This study included 25,616 hospitalizations of patients under the age of 18 years. Data were extracted from a hospital network electronic medical record. Demographics included LACE scores, age, gender, race/ethnicity, median household income, and medical centers. The primary exposure variable was LACE score. The main outcome measures were readmissions within 7, 14, and 30 days. The area under the curve (AUC) was used to assess the predictive capability of the regression model on patient 30-day admission.

          Results

          LACE scores, age, gender, race/ethnicity, median household income, and medical centers were examined in a multivariable model to assess patient risk of a 30-day readmission. Only age and LACE score were observed to be statistically significant. The AUC for the combined model was 0.69.

          Discussion

          As only age and LACE score were observed to be statistically significant and the AUC for the combined model was 0.69, this model is considered to have poor predictive capability.

          Conclusions

          In this study, LACE scores, as well the other factors, had a poor predictive capability for pediatric readmissions.

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          Most cited references34

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          Pediatric complex chronic conditions classification system version 2: updated for ICD-10 and complex medical technology dependence and transplantation

          Background The pediatric complex chronic conditions (CCC) classification system, developed in 2000, requires revision to accommodate the International Classification of Disease 10th Revision (ICD-10). To update the CCC classification system, we incorporated ICD-9 diagnostic codes that had been either omitted or incorrectly specified in the original system, and then translated between ICD-9 and ICD-10 using General Equivalence Mappings (GEMs). We further reviewed all codes in the ICD-9 and ICD-10 systems to include both diagnostic and procedural codes indicative of technology dependence or organ transplantation. We applied the provisional CCC version 2 (v2) system to death certificate information and 2 databases of health utilization, reviewed the resulting CCC classifications, and corrected any misclassifications. Finally, we evaluated performance of the CCC v2 system by assessing: 1) the stability of the system between ICD-9 and ICD-10 codes using data which included both ICD-9 codes and ICD-10 codes; 2) the year-to-year stability before and after ICD-10 implementation; and 3) the proportions of patients classified as having a CCC in both the v1 and v2 systems. Results The CCC v2 classification system consists of diagnostic and procedural codes that incorporate a new neonatal CCC category as well as domains of complexity arising from technology dependence or organ transplantation. CCC v2 demonstrated close comparability between ICD-9 and ICD-10 and did not detect significant discontinuity in temporal trends of death in the United States. Compared to the original system, CCC v2 resulted in a 1.0% absolute (10% relative) increase in the number of patients identified as having a CCC in national hospitalization dataset, and a 0.4% absolute (24% relative) increase in a national emergency department dataset. Conclusions The updated CCC v2 system is comprehensive and multidimensional, and provides a necessary update to accommodate widespread implementation of ICD-10.
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            Derivation and validation of an index to predict early death or unplanned readmission after discharge from hospital to the community.

            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. 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. 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 mnemonic "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. 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.
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              Interventions to reduce 30-day rehospitalization: a systematic review.

              About 1 in 5 Medicare fee-for-service patients discharged from the hospital is rehospitalized within 30 days. Beginning in 2013, hospitals with high risk-standardized readmission rates will be subject to a Medicare reimbursement penalty. To describe interventions evaluated in studies aimed at reducing rehospitalization within 30 days of discharge. MEDLINE, EMBASE, Web of Science, and the Cochrane Library were searched for reports published between January 1975 and January 2011. English-language randomized, controlled trials; cohort studies; or noncontrolled before-after studies of interventions to reduce rehospitalization that reported rehospitalization rates within 30 days. 2 reviewers independently identified candidate articles from the results of the initial search on the basis of title and abstract. Two 2-physician reviewer teams reviewed the full text of candidate articles to identify interventions and assess study quality. 43 articles were identified, and a taxonomy was developed to categorize interventions into 3 domains that encompassed 12 distinct activities. Predischarge interventions included patient education, medication reconciliation, discharge planning, and scheduling of a follow-up appointment before discharge. Postdischarge interventions included follow-up telephone calls, patient-activated hotlines, timely communication with ambulatory providers, timely ambulatory provider follow-up, and postdischarge home visits. Bridging interventions included transition coaches, physician continuity across the inpatient and outpatient setting, and patient-centered discharge instruction. Inadequate description of individual studies' interventions precluded meta-analysis of effects. Many studies identified in the review were single-institution assessments of quality improvement activities rather than those with experimental designs. Several common interventions have not been studied outside of multicomponent "discharge bundles." No single intervention implemented alone was regularly associated with reduced risk for 30-day rehospitalization. None.
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                Author and article information

                Journal
                Perm J
                tpj
                tpj
                The Permanente Journal
                The Permanente Press
                1552-5767
                1552-5775
                2024
                23 February 2024
                : 28
                : 2
                : 9-15
                Affiliations
                [1] 1 Southern California Permanente Medical Group , Los Angeles, CA, USA
                [2] 2 Kaiser Foundation Hospital , Los Angeles, CA, USA
                Author notes
                Jelena Douillard, MD jelena.douillard@ 123456kp.org

                Supplementary Materials: Supplemental Material is available at: www.thepermanentejournal.org/files/2024/23.114supp.pdf

                Author information
                https://orcid.org/0000-0002-1362-3229
                Article
                TPJ-23-114
                10.7812/TPP/23.114
                11232907
                38389442
                6cb1299f-4e6c-4f15-a119-c78ab93e97ed
                © 2024 The Authors.

                Published by The Permanente Federation LLC under the terms of the CC BY-NC-ND 4.0 license https://creativecommons.org/licenses/by-nc-nd/4.0/.

                History
                : 19 August 2023
                : 23 November 2023
                : 04 December 2023
                Page count
                Figures: 2, Tables: 3, References: 34, Pages: 7
                Funding
                Funded by: Regional Research Committee of Kaiser Permanente Southern California
                Award ID: KP-RRC-20211004
                Categories
                Original Research

                readmission rates,lace score,decreasing readmission rates

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