Avoidable Hospital Readmissions Research Articles

Validation of the Potentially Avoidable Hospital Readmission Rate as a Routine Indicator of the Quality of Hospital Care

Validation of the Potentially Avoidable Hospital Readmission Rate as a Routine Indicator of the Quality of Hospital Care

Validation of the Potentially Avoidable Hospital Readmission Rate as a Routine Indicator of the Quality of Hospital Care

The hospital readmission rate has been proposed as an important outcome indicator computable from routine statistics. However, most commonly used measures raise conceptual issues. We sought to evaluate the usefulness of the computerized algorithm for identifying avoidable readmissions on the basis of minimum bias, criterion validity, and measurement precision. A total of 131,809 hospitalizations of patients discharged alive from 49 hospitals were used to compare the predictive performance of risk adjustment methods. A subset of a random sample of 570 medical records of discharge/readmission pairs in 12 hospitals were reviewed to estimate the predictive value of the screening of potentially avoidable readmissions. Potentially avoidable readmissions, defined as readmissions related to a condition of the previous hospitalization and not expected as part of a program of care and occurring within 30 days after the previous discharge, were identified by a computerized algorithm. Unavoidable readmissions were considered as censored events. A total of 5.2% of hospitalizations were followed by a potentially avoidable readmission, 17% of them in a different hospital. The predictive value of the screen was 78%; 27% of screened readmissions were judged clearly avoidable. The correlation between the hospital rate of clearly avoidable readmission and all readmissions rate, potentially avoidable readmissions rate or the ratio of observed to expected readmissions were respectively 0.42, 0.56 and 0.66. Adjustment models using clinical information performed better. Adjusted rates of potentially avoidable readmissions are scientifically sound enough to warrant their inclusion in hospital quality surveillance.

Old Age, New Technology, and Future Innovations in Disease Management and Home Health Care

The nation’s nearly 80 million baby boomers are about to enter their peak years of chronic disease and are set to become an unprecedented driver of health care costs. New technology, however, promises to enable a transformation in the delivery of care, putting patients at the center of care systems that engage and empower them and their families, directly connecting patients to care-givers, and personalizing services in response to patients’ unique needs, preferences, and values. Such care systems also offer the promise of strengthening an understaffed, underresourced home health care industry. Leveraging technology, disease management (DM), and home health have the opportunity to work together to more efficiently and effectively meet the needs of a rapidly aging society through better coordinated care that reduces avoidable hospital readmissions and other adverse events. This is achieved by positively affecting such things as home safety (e.g., falls), medication adherence, nutrition, and heart failure.

Überwachung multipler Herzkreislaufparameter mittels Telemonitoring bei Patienten mit chronischer Herzinsuffizienz

Progression of chronic heart failure depends on various additional pathophysiologic factors like blood pressure, arrhythmias, congestion. Early detection of any alteration using telemonitoring of multiple vital parameters may avoid severe decompensation requiring hospital admission. The feasibility and the clinical outcome using a new telemonitoring device for recording multiple vital parameters and allowing communication on individual state of health is investigated. Twenty-four patients with chronic heart failure (mean age 65 years, mean LV ejection fraction 35%) requiring at least one hospital admission during the past year were investigated. Twice a day, the vital-parameters were measured (weight, blood pressure, heart rate and rhythm, oxygen saturation, respiration rate) and patients information on well being, shortness of breath, medication, and request for contact were received. Intra-individual comparison was carried out between the 12 month before inclusion in this study and 12 month under telemonitoring surveillance (extrapolated, if necessary). Performing over 10 500 measurements during 5751 patient days, critical events were diagnosed for 55 events concerning relative weight gain (43 episodes), blood pressure (6), decrease in oxygen saturation (3), new onset of atrial fibrillation with tachyarrhymia (3). Of these, 45 events were controlled on an outpatient basis by changing medication or external cardioversion. Only 10 patients required re-admission. Thus, the number of admission to the hospital could be reduced by 62%, those of days spent in hospital by 69%. Non-invasive telemonitoring of multiple vital parameters combined with patients statements on their health condition and out-patient treatment on the basis of these findings is found to be an effective and reliable approach to avoid hospital readmission for patients with chronic heart failure.

HOME CARE OF THE HIGH-RISK INFANT

Increasingly, infants are discharged from the neonatal intensive care unit (NICU) with unresolved healthcare issues and ongoing technology needs. A well-planned discharge of a medically stable infant is important to assure safe and effective care in the home and to minimize avoidable hospital readmissions. This article addresses the discharge of and home care options for 3 groups of infants who have traditionally been cared for in the hospital. These include infants requiring palliative care, infants who are technology dependent, and those stable premature infants requiring intensive home support. Intermittent and continuous home nursing care options are defined, and the goals of home care nursing are outlined. The importance of objective discharge criteria and medical stability is discussed along with practical tips and strategies to assure success. A teaching tool to assist parents in choosing a home care provider is included.

Measuring performance in health care: case-mix adjustment by boosted decision trees

The purpose of this paper is to investigate the suitability of boosted decision trees for the case-mix adjustment involved in comparing the performance of various health care entities. First, we present logistic regression, decision trees, and boosted decision trees in a unified framework. Second, we study in detail their application for two common performance indicators, the mortality rate in intensive care and the rate of potentially avoidable hospital readmissions. For both examples the technique of boosting decision trees outperformed standard prognostic models, in particular linear logistic regression models, with regard to predictive power. On the other hand, boosting decision trees was computationally demanding and the resulting models were rather complex and needed additional tools for interpretation. Boosting decision trees represents a powerful tool for case-mix adjustment in health care performance measurement. Depending on the specific priorities set in each context, the gain in predictive power might compensate for the inconvenience in the use of boosted decision trees.

Using information technology to improve the management of chronic disease.

Information and communications technology (ICT) is increasingly being used in management of chronic illness to facilitate shared services (virtual health networks and electronic health records), knowledge management (care rules and protocols, scheduling, information directories), as well as consumer-based health education and evidence-based clinical protocols. Common applications of ICT include home monitoring of vital signs for patients with chronic disease, as well as replacing home visits by nurses in person with telemedicine videophone consultations. A patient-managed Home Telecare System with integrated clinical signs monitoring, automated scheduling and medication reminders, as well as access to health education and daily logs, is presented as an example of ICT use for chronic disease self-management. A clinical case study demonstrates how early identification of adverse trends in clinical signs recorded in the home can either avoid hospital readmission or reduce the length of hospital stay.

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.

New strategy for mentally ill in Wales.

Nurses working with the mentally ill have welcomed a new strategy launched in Wales by Secretary of State Peter Walker, but called for crisis prevention teams to avoid hospital re-admissions.