Using the LACE index to predict hospital readmissions in congestive heart failure patients

Wang, Hao; Robinson, Richard D.; Johnson, Carlos; Zenarosa, Nestor R.; Jayswal, Rani; Keithley, Joshua; Delaney, Kathleen

doi:10.1186/1471-2261-14-97

Cited by 99 publications

(85 citation statements)

References 27 publications

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“…Although recent research [14] concludes that LACE (which is the base for LACE+) could not accurate predict unplanned readmission, the presented system will include more data than LACE. One of the reasons is that in the available data there can be found a set of variables different from the ones used in LACE+ validation.…”

mentioning

confidence: 93%

A Multiagent System Proposal for 30 Day Readmission Problem Management

Lemus

Montañana

Pons

et al. 2015

Agent and Multi-Agent Systems: Technologies and Applications

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Thirty day readmission rate is an important quality estimator for hospitals. Confident tools that forecast this risk for each patient before hospital discharge are needed by medical staff in order to delay the discharge and to plan additional home care interventions. This paper presents a proposal for a multi agent system that will evaluate this risk by integrating information from each patient and historical data from local and remote medical histories. This systems will not only help with the hospital discharge decision, but it will integrate a basic telecare system in order to reduce readmissions and increment patient quality of life by detecting problems arisen after hospital discharge.

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mentioning

confidence: 93%

A Multiagent System Proposal for 30 Day Readmission Problem Management

Lemus

Montañana

Pons

et al. 2015

Agent and Multi-Agent Systems: Technologies and Applications

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“…Findings demonstrated that the LACE index [9] may be useful in the identification of patients at risk for readmission to hospitals in Asian countries. [10] A retrospective study of 253 patients was conducted to externally validate the accuracy of using the LACE index [9] to predict 30 day readmissions in patients experiencing congestive heart failure [11] (CHF) exacerbation. Wang et al [11] found that the LACE index [9] may be more useful in predicting the incidence of visits to the emergency department during the post discharge period.…”

Section: Introductionmentioning

confidence: 99%

“…[10] A retrospective study of 253 patients was conducted to externally validate the accuracy of using the LACE index [9] to predict 30 day readmissions in patients experiencing congestive heart failure [11] (CHF) exacerbation. Wang et al [11] found that the LACE index [9] may be more useful in predicting the incidence of visits to the emergency department during the post discharge period. The ability to provide patients with valuable community health resources during the post discharge period may reduce the number of visits to the emergency department by this population.…”

Section: Introductionmentioning

confidence: 99%

The identification of post-acute patients at risk for hospital readmission: Clinical implications of the LACE index

Ritt

Taylor

2016

Clinical Nursing Studies

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Readmission to the hospital is stressful and disruptive for patients and accounts for billions of dollars in healthcare spending. The reduction of unplanned all-cause readmission to an acute care hospital is a major priority of the Centers for Medicare and Medicaid Services (CMS), policymakers, nurses, and all health care providers. Research studies have focused on patients discharged from an acute-care hospital to the home setting. The LACE index scoring tool has been used to predict the risk of death or unplanned readmission within 30 days after discharge from the hospital to the home setting. This descriptive, nonexperimental research study incorporated the LACE index in the record of patients admitted to two post-acute care facilities from surrounding acute care hospitals. Data were collected between September 2015 and February 2016. There were 164 participants in the study and ages ranged from 42-98 years of age with a mean age of 74.2. Of the 164 participants, a total of 19 participants, or 11.5%, were readmitted to the hospital within a 30-day period after discharge. The most commonly identified comorbidities of diabetes without complications, congestive heart failure (CHF), chronic pulmonary disease, dementia, and cerebrovascular disease point to the layers of clinical complexity and risk when caring for older adults. This study supports further implementation of the LACE index with other clinical assessment tools that identify patients at greatest risk for an unplanned all-cause readmission to the hospital within 30 days of discharge to the post-acute care facility.

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Section: Introductionmentioning

confidence: 99%

“…It calculates a score predictive of patient risk level based on length of stay (LOS), acuity of admission, medical comorbidities, and number of emergency visits in the 6 months leading up to admission [10]. The LACE index was first externally validated in congestive heart failure patients [10,11], and has also been validated in the general population of hospitalized patients [12]. Further, based on this scoring system, Bronstein et al [13] in a prospective, randomized fashion demonstrated that social work intervention for hospitalized patients based on a LACE score ≥ 7 decreased readmission likelihood by 22% compared to standard treatment.…”

Section: Introductionmentioning

confidence: 99%

The LACE Score as a Tool to Identify Radical Cystectomy Patients at Increased Risk of 90-Day Readmission and Mortality

Saluk¹,

Blackwell²,

Gange³

et al. 2018

Current Urology

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Introduction: Radical cystectomy for bladder cancer is associated with high rates of readmission. We investigated the LACE score, a validated prediction tool for readmission and mortality, in the radical cystectomy population. Materials & Methods: Patients who underwent radical cystectomy for bladder cancer were identified by ICD-9 codes from the Healthcare Cost and Utilization Project State Inpatient Database for California years 2007-2010. The LACE score was calculated as previously described, with components of L: length of stay, A: acuity of admission, C: comorbidity, and E: number of emergency department visits within 6 months preceding surgery. Results: Of 3,470 radical cystectomy patients, 638 (18.4%) experienced 90-day readmission, and 160 (4.6%) 90-day mortality. At a previously validated “high-risk” LACE score ≥ 10, patients experienced an increased risk of 90-day readmission (22.8 vs. 17.7%, p = 0.002) and mortality (9.1 vs. 3.5%, p < 0.001). On adjusted multivariable analysis, “high risk” patients by LACE score had increased 90-day odds of readmission (adjusted OR = 1.24, 95% CI: 0.99-1.54, p = 0.050) and mortality (adjusted OR = 2.09, 95% CI: 1.47-2.99, p < 0.001). Conclusion: The LACE score reasonably identifies patients at risk for 90-day mortality following radical cystectomy, but only poorly predicts readmission. Providers may use the LACE score to target high-risk patients for closer follow-up or intervention.

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Using the LACE index to predict hospital readmissions in congestive heart failure patients

Cited by 99 publications

References 27 publications

A Multiagent System Proposal for 30 Day Readmission Problem Management

A Multiagent System Proposal for 30 Day Readmission Problem Management

The identification of post-acute patients at risk for hospital readmission: Clinical implications of the LACE index

The LACE Score as a Tool to Identify Radical Cystectomy Patients at Increased Risk of 90-Day Readmission and Mortality

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