Reduction of 30-day postdischarge hospital readmission or emergency department (ED) visit rates in high-risk elderly medical patients through delivery of a targeted care bundle

Inability of providers to predict unplanned readmissions

BACKGROUND

Readmissions cause significant distress to patients and considerable financial costs. Identifying hospitalized patients at high risk for readmission is an important strategy in reducing readmissions. We aimed to evaluate how well physicians, case managers, and nurses can predict whether their older patients will be readmitted and to compare their predictions to a standardized risk tool (Probability of Repeat Admission, or P(ra)).

METHODS

Patients aged ≥ 65 discharged from the general medical service at University of California, San Francisco Medical Center, a 550-bed tertiary care academic medical center, were eligible for enrollment over a 5-week period. At the time of discharge, the inpatient team members caring for each patient estimated the chance of unscheduled readmission within 30 days and predicted the reason for potential readmission. We also calculated the P(ra) for each patient. We identified readmissions through electronic medical record (EMR) review and phone calls with patients/caregivers. Discrimination was determined by creating ROC curves for each provider group and the P(ra).

RESULTS

One hundred sixty-four patients were eligible for enrollment. Of these patients, five died during the 30-day period post-discharge. Of the remaining 159 patients, 52 patients (32.7%) were readmitted. Mean readmission predictions for the physician providers were closest to the actual readmission rate, while case managers, nurses, and the P(ra) all overestimated readmissions. The ability to discriminate between readmissions and non-readmissions was poor for all provider groups and the P(ra) (AUC from 0.50 for case managers to 0.59 for interns, 0.56 for P(ra)). None of the provider groups predicted the reason for readmission with accuracy.

CONCLUSIONS

This study found (1) overall readmission rates were higher than previously reported, possibly because we employed a more thorough follow-up methodology, and (2) neither providers nor a published algorithm were able to accurately predict which patients were at highest risk of readmission. Amid increasing pressure to reduce readmission rates, hospitals do not have accurate predictive tools to guide their efforts.

Redefining readmission risk factors for general medicine patients

BACKGROUND

Readmissions are costly both financially for our healthcare system and emotionally for our patients. Identifying factors that increase risk for readmissions may be helpful to focus resources to optimize the discharge process and reduce avoidable readmissions.

OBJECTIVE

To identify factors associated with readmission within 30 days for general medicine patients.

METHODS

We performed a retrospective observational study of an administrative database at an urban 550-bed tertiary care academic medical center. Cohort patients were discharged from the general medicine service over a 2-year period from June 1, 2006, to May 31, 2008. Clinical, operational, and sociodemographic factors were evaluated for association with readmission.

RESULTS

Our cohort included 10,359 consecutive admissions (6805 patients) discharged from the general medicine service. The 30-day readmission rate was 17.0%. In multivariate analysis, factors associated with readmission included black race (odds ratio [OR], 1.43; 95% confidence interval [CI], 1.24-1.65), inpatient use of narcotics (1.33; 1.16-1.53) and corticosteroids (1.24; 1.09-1.42), and the disease states of cancer (with metastasis 1.61; 1.33-1.95; without metastasis 1.95; 1.54-2.47), renal failure (1.19; 1.05-1.36), congestive heart failure (1.30; 1.09-1.56), and weight loss (1.26; 1.09-1.47). Medicaid payer status (1.15; 0.97-1.36) had a trend toward readmission.

CONCLUSION

Readmission of general medicine patients within 30 days is common and associated with several easily identifiable clinical and nonclinical factors. Identification of these risk factors can allow providers to target interventions to reduce potentially avoidable readmissions.

Perceptions of hospital safety climate and incidence of readmission

OBJECTIVE

To define the relationship between hospital patient safety climate (a measure of hospitals' organizational culture as related to patient safety) and hospitals' rates of rehospitalization within 30 days of discharge.

DATA SOURCES

A safety climate survey administered to a random sample of hospital employees (n=36,375) in 2006-2007 and risk-standardized hospital readmission rates from 2008.

STUDY DESIGN

Cross-sectional study of 67 hospitals.

DATA COLLECTION

Robust multiple regressions used 30-day risk-standardized readmission rates as dependent variables in separate disease-specific models (acute myocardial infarction [AMI], heart failure [HF], pneumonia), and measures of safety climate as independent variables. We estimated separate models for all hospital staff as well as physicians, nurses, hospital senior managers, and frontline staff.

PRINCIPAL FINDINGS

There was a significant positive association between lower safety climate and higher readmission rates for AMI and HF (p ≤ .05 for both models). Frontline staff perceptions of safety climate were associated with readmission rates (p ≤ .01), but senior management perceptions were not. Physician and nurse perceptions related to AMI and HF readmissions, respectively.

CONCLUSIONS

Our findings indicate that hospital patient safety climate is associated with readmission outcomes for AMI and HF and those associations were management level and discipline specific.

Inpatient medication reconciliation at admission and discharge: A retrospective cohort study of age and other risk factors for medication discrepancies

BACKGROUND

Medication discrepancies are unintended differences between medication regimens (ie, between a patient's home regimen and medications prescribed on admission to the hospital).

OBJECTIVE

The goal of this study was to describe the incidence, drug classes, and probable importance of hospital admission medication discrepancies and discharge regimen differences, and to determine whether factors such as age and specific hospital services were associated with greater frequency of medication discrepancies and differences.

METHODS

This was a retrospective cohort study of a random sample of adult patients admitted to the general medicine, cardiology, or general surgery services of a tertiary care academic teaching hospital between July 1, 2006, and August 31, 2006. A chart review was performed to collect the following information: patient demographic characteristics, comorbid conditions, number of preadmission medications, discrepant medications identified by the hospital's reconciliation process, reasons for the discrepancies, and discharge medications that differed from the home regimen. Potentially high-risk discrepancies and differences were identified by determining if the medications were included on either the Institute for Safe Medication Practices high-alert list or the North Carolina Narrow Therapeutic Index list. Univariate and multivariate logistic regression analyses were used to identify factors associated with medication discrepancies and differences.

RESULTS

Of the 205 patients (mean age, 59.9 years; 116 men, 89 women; 60% white) included in the study, 27 did not have any medications recorded on admission. Of the 178 patients who did have medications listed, 41 had >or=1 discrepancy identified by the reconciliation process on admission (23%; 95% CI, 17-29); 19% (95% CI, 11-31) of these medications were considered to be potentially high risk. In the multivariate logistic regression model, age (odds ratio [OR] per 5-year increase = 1.16; 95% CI, 1.01-1.33; P = 0.035), presence of high-risk medications on admission (OR = 76.68; 95% CI, 9.13-643.76; P < 0.001), and general surgery service (OR = 3.31; 95% CI, 1.40-7.87; P < 0.007) were associated with a higher proportion of patients with discrepancies on admission. At discharge, 196 patients (96% [95% CI, 93<98]) had >or=1 medication change from their home regimen, with 1102 total differences for 205 patients. Less than half (44% [95% CI, 37-51]) of these patients were explicitly alerted at discharge to new medications or dose changes; 12% (95% CI, 7-18) were given written instructions to stop taking discontinued home medications. Cardiovascular drugs were the most frequent class involved at both admission (31%) and discharge (27%) in medication discrepancies or differences.

CONCLUSIONS

Medication discrepancies on admission and medication differences at discharge were prevalent for adult patients admitted to the general medicine, cardiology, and general surgery services in this academic teaching hospital. Medication reconciliation processes have a high potential to identify clinically important discrepancies for all patients.

The effect of the COACH program (Continuity Of Appropriate pharmacotherapy, patient Counselling and information transfer in Healthcare) on readmission rates in a multicultural population of internal medicine patients

Background

Medication errors occur frequently at points of transition in care. The key problems causing these medication errors are: incomplete and inappropriate medication reconciliation at hospital discharge (partly arising from inadequate medication reconciliation at admission), insufficient patient information (especially within a multicultural patient population) and insufficient communication to the next health care provider. Whether interventions aimed at the combination of these aspects indeed result in less discontinuity and associated harm is uncertain. Therefore the main objective of this study is to determine the effect of the COACH program (Continuity Of Appropriate pharmacotherapy, patient Counselling and information transfer in Healthcare) on readmission rates in patients discharged from the internal medicine department.

Methods/Design

An experimental study is performed at the internal medicine ward of a general teaching hospital in Amsterdam, which serves a multicultural population. In this study the effects of the COACH program is compared with usual care using a pre-post study design. All patients being admitted with at least one prescribed drug intended for chronic use are included in the study unless they meet one of the following exclusion criteria: no informed consent, no medication intended for chronic use prescribed at discharge, death, transfer to another ward or hospital, discharge within 24 hours or out of office hours, discharge to a nursing home and no possibility to counsel the patient.

The intervention consists of medication reconciliation, patient counselling and communication between the hospital and primary care healthcare providers.

The following outcomes are measured: the primary outcome readmissions within six months after discharge and the secondary outcomes number of interventions, adherence, patient's attitude towards medicines, patient's satisfaction with medication information, costs, quality of life and finally satisfaction of general practitioners and community pharmacists.

Interrupted time series analysis is used for data-analysis of the primary outcome. Descriptive statistics is performed for the secondary outcomes. An economic evaluation is performed according to the intention-to-treat principle.

Discussion

This study will be able to evaluate the clinical and cost impact of a comprehensive program on continuity of care and associated patient safety.

Trial registration

Dutch trial register: NTR1519

Preventing the rebound: improving care transition in hospital discharge processes

Background.Unplanned readmissions of recently discharged patients impose a significant burden on hospitals with limited bed capacity. Deficiencies in discharge processes contribute to such readmissions, which have prompted experimentation with multiple types of peridischarge interventions. Objective.To determine the relative efficacy of peridischarge interventions categorised into two groups: (1) single component interventions (sole or predominant) implemented either before or after discharge; and (2) integrated multicomponent interventions which have pre- and postdischarge elements. Design.Systematic metareview of controlled trials. Data collection.Search of four electronic databases for controlled trials or systematic reviews of trials published between January 1990 and April 2009 that reported effects on readmissions. Data synthesis.Among single-component interventions, only four (intense self-management and transition coaching of high-risk patients and nurse home visits and telephone support of patients with heart failure) were effective in reducing readmissions. Multicomponent interventions that featured early assessment of discharge needs, enhanced patient (and caregiver) education and counselling, and early postdischarge follow-up of high-risk patients were associated with evidence of benefit, especially in populations of older patients and those with heart failure. Conclusion.Peridischarge interventions are highly heterogenous and reported outcomes show considerable variation. However, multicomponent interventions targeted at high-risk populations that include pre- and postdischarge elements seem to be more effective in reducing readmissions than most single-component interventions, which do not span the hospital–community interface. What is known about this topic?Unplanned readmissions within 30 days of hospital discharge are common and may reflect deficiencies in discharge processes. Various peridischarge interventions have been evaluated, mostly single-component interventions that occur either before or after discharge, but failing to yield consistent evidence of benefit in reducing readmissions. More recent trials have assessed multicomponent interventions which involve pre- and postdischarge periods, but no formal review of such studies has been undertaken. What does this paper add?With the exception of intense self-management and transition coaching of high-risk patients, and nurse home visits and telephonic support for patients with heart failure, single-component interventions were ineffective in reducing readmissions. Multicomponent interventions demonstrated evidence of benefit in reducing readmissions by as much as 28%, with best results achieved in populations of older patients and those with heart failure. What are the implications for practitioners and managers?Hospital clinicians and managers should critically review and, where appropriate, modify their current discharge processes in accordance with these findings and negotiate the extra funding and personnel required to allow successful implementation of multicomponent discharge processes that transcend organisational boundaries.