***TASK*** the task is to summarize an input biomedical literature in six sentences 
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    Input: BACKGROUND Previous studies found that medication errors result from lack of sufficient information during the prescribing step . Therefore , it is proposed that having a pharmacist available when patients are evaluated during the rounding process may reduce the likelihood of preventable adverse drug events ( ADEs ) . The objectives of this study were to evaluate the impact of having a pharmacist participate with a physician rounding team on preventable ADEs in general medicine units and to document pharmacist interventions made during the rounding process . METHODS A single-blind , st and ard care-controlled study design was used to compare  patients receiving care from a rounding team including a pharmacist with patients receiving st and ard care ( no pharmacist on rounding team ) . Patients admitted to and discharged from the same general medicine unit were included in the study . The main outcome measure of this study was preventable ADEs . Patient records were r and omly selected and evaluated by a blinded process involving independent senior pharmacist specialists and a senior staff physician . Interventions made by the pharmacists in the treatment group were documented . RESULTS The rate of preventable ADEs was reduced by 78 % , from 26.5 per 1000 hospital days to 5.7 per 1000 hospital days . There were 150 documented interventions recommended during the rounding process , 147 of which were accepted by the team . The most common interventions were ( 1 ) dosing-related changes and ( 2 ) recommendations to add a drug to therapy . CONCLUSION Pharmacist participation with the medical rounding team on a general medicine unit contributes to a significant reduction in preventable ADEs OBJECTIVES To study the feasibility and effectiveness of a  discharge planning intervention . DESIGN Quasi-experimental pre-post study design . SETTING General medicine wards at three hospitals : an academic medical center , a community teaching hospital , and a community-based nonteaching hospital . PARTICIPANTS All patients aged 65 and older admitted to the hospitalist services . INTERVENTION The intervention toolkit had five core elements : admission form with geriatric cues , facsimile to the primary care provider , interdisciplinary worksheet to identify barriers to discharge , pharmacist-physician collaborative medication reconciliation , and predischarge planning appointments . MEASUREMENTS Thirty-day readmission and return to emergency department rates and patient satisfaction with discharge . Odds ratios were determined , and site effects were examined accordig to interaction terms and Breslow Day statistics . RESULTS Two hundred thirty-seven patients were followed during the preintervention period , and 185 were exposed to the intervention . Patients characteristics were similar across the two time periods . The proportion of patients with high- quality transitions home , measured according to Coleman 's Care Transition Measures , increased from 68 % to 89 % ( odds ratio (OR)=3.49 , 95 % confidence interval (CI)=2.06 - 5.92 ) . Return to the emergency department within 3 days of discharge was lower in the intervention period ( 10 % vs 3 % , OR=0.25 , 95 % CI=0.10 - 0.62 ) . At 30 days , there was a lower rate of readmission ( 22 % vs 14 % , OR=0.59 , 95 % CI=0.34 - 0.97 ) and fewer visits to the emergency department ( 21 % vs 14 % , OR=0.61 , 95 % CI=0.36 - 1.03 ) ( P=.06 ) . CONCLUSION When hospitalized elderly patients are treated with consideration of their specific needs , healthcare outcomes can be improved OBJECTIVE : To describe the incidence of adverse drug events ( ADEs ) , preventable ADEs , and ameliorable ADEs occurring after hospital discharge and their associated risk factors . DESIGN : Prospect i ve cohort study . SETTING : Urban academic health sciences center . PATIENTS : Consecutive patients discharged home from the general medical service . INTERVENTIONS : We determined posthospital outcomes approximately 24 days following discharge by performing a chart review and telephone interview . Using the telephone interview , we identified new or worsening symptoms , the patient ’s health system use , and re collection of processes of care . Posthospital outcomes were judged by 2 internists independently . RESULTS : Four hundred of 581 potentially eligible patients were evaluated . Of the 400 patients , 45 developed an ADE ( incidence , 11 % ; 95 % confidence interval [ CI ] , 8 % to 14 % ) . Of these , 27 % were preventable and 33 % were ameliorable . Injuries were significant in 32 patients , serious in 6 , and life threatening in 7 . Patients were less likely to experience an ADE if they recalled having side effects of prescribed medications explained ( OR , 0.4 ; 95 % CI , 0.2 to 0.8 ) . The risk of ADE per prescription was highest for corticosteroids , anticoagulants , antibiotics , analgesics , and cardiovascular medications . Risk increased with prescription number . Failure to monitor was an especially common cause of preventable and ameliorable ADEs . CONCLUSION : Following discharge , ADEs were common and many were preventable or ameliorable . Medication side effects should be discussed , and interventions should include better monitoring and target patients receiving specific drug classes or multiple medications BACKGROUND Hospitalization and subsequent discharge home often involve discontinuity of care , multiple changes in medication regimens , and inadequate patient education , which can lead to adverse drug events ( ADEs ) and avoidable health care utilization . Our objectives were to identify drug-related problems during and after hospitalization and to determine the effect of patient counseling and follow-up by pharmacists on preventable ADEs . METHODS We conducted a r and omized trial of 178 patients being discharged home from the general medicine service at a large teaching hospital . Patients in the intervention group received pharmacist counseling at discharge and a follow-up telephone call 3 to 5 days later . Interventions focused on clarifying medication regimens ; review ing indications , directions , and potential side effects of medications ; screening for barriers to adherence and early side effects ; and providing patient counseling and /or physician feedback when appropriate . The primary outcome was rate of preventable ADEs . RESULTS Pharmacists observed the following drug-related problems in the intervention group : unexplained discrepancies between patients ' preadmission medication regimens and discharge medication orders in 49 % of patients , unexplained discrepancies between discharge medication lists and postdischarge regimens in 29 % of patients , and medication nonadherence in 23 % . Comparing trial outcomes 30 days after discharge , preventable ADEs were detected in 11 % of patients in the control group and 1 % of patients in the intervention group ( P = .01 ) . No differences were found between groups in total ADEs or total health care utilization . CONCLUSIONS Pharmacist medication review , patient counseling , and telephone follow-up were associated with a lower rate of preventable ADEs 30 days after hospital discharge . Medication discrepancies before and after discharge were common targets of intervention Background There is a paucity of literature on a well-defined role of a pharmacist in different aspects of transition of care service ( TCS ) . Although health care institutions have specific details on the discharge process , there is a need for a sustainable TCS with a well-defined role of pharmacists . Objective To describe the impact of a pharmacist-led TCS on acute health care utilization , clinic quality indicators , and identification and resolution of medication-related problems ( MRPs ) . Methods A  pharmacist-managed TCS service , referred to as the Pharmacist Advancement of Transitions of Care to Home ( PATCH ) service , was established at an academic medical center , where high-risk patients received a postdischarge phone call from a pharmacist  followed by a face-to-face meeting with the pharmacist and the patient 's primary care provider ( PCP ) . In a prospect i ve transitions of care group ( n = 74 ) , outcomes of patients such as acute health care utilization ( an emergency department visit or an inpatient readmission , within 30 days post discharge ) , clinic quality indicators , and identification and resolution of MRPs were compared to a retrospective control group ( n = 87 ) who received the st and ard of care . Results Utilization of acute health care services was significantly lower in the prospect i ve group compared to the retrospective control group ( 23 % vs 41.4 % ; P = .013 ) . A total of 49 MRPs were discovered in patients who received the TCS . Conclusions Pharmacists play an integral role in improving the transitions of care to reduce acute health care utilization . In addition , they may improve care transitions by optimizing clinic quality indicators and by identifying and resolving MRPs Background Despite growing emphasis on transitional care to reduce costs and improve quality , few studies have examined transitional care improvements in socioeconomically disadvantaged adults . It is important to consider these patients separately as many are high-utilizers , have different needs , and may have different responses to interventions . Objective To evaluate the impact of a multicomponent transitional care improvement program on 30-day readmissions , emergency department ( ED ) use , transitional care quality , and mortality . Design Clustered r and omized controlled trial conducted at a single urban academic medical center in Portl and , Oregon . Participants Three hundred eighty-two hospitalized low-income adults admitted to general medicine or cardiology who were uninsured or had public insurance . InterventionMulticomponent intervention including ( 1 ) transitional nurse coaching and education , including home visits for highest risk patients ; ( 2 ) pharmacy care , including provision of 30 days of medications after discharge for those without prescription drug coverage ; ( 3 ) post-hospital primary care linkages ; ( 4 ) systems integration and continuous quality improvement . Measurements Primary outcomes included 30-day inpatient readmission and ED use . Readmission data were obtained using state-wide administrative data for all participants ( insured and uninsured ) . Secondary outcomes included quality ( 3-item Care Transitions Measure ) and mortality . Research staff administering question naires and assessing outcomes were blinded . Results There was no significant difference in 30-day readmission between C-TraIn ( 30/209 , 14.4 % ) and control patients ( 27/173 , 16.1 % ) , p = 0.644 , or in ED visits between C-TraIn ( 51/209 , 24.4 % ) and control ( 33/173 , 19.6 % ) , p = 0.271 . C-TraIn was associated with improved transitional care quality ; 47.3 % ( 71/150 ) of C-TraIn patients reported a high quality transition compared to 30.3 % ( 36/119 ) control patients , odds ratio 2.17 ( 95 % CI 1.30–3.64 ) . Zero C-TraIn patients died in the 30-day post-discharge period compared with five in the control group ( unadjusted p = 0.02 ) . Conclusions C-TraIn did not reduce 30-day inpatient readmissions or ED use ; however , it improved transitional care quality Context Research on patient safety has focused on adverse events in hospitalized patients .  Adverse events following hospitalization have received little attention . Contribution Among 400 consecutive patients discharged from the general medical service of an academic hospital , 76 had adverse events during the 2 weeks following hospital discharge . Of the adverse events , the research ers categorized 23 as preventable , 24 as ameliorable , and the remainder as neither . Adverse drug events were the most frequent occurrence . Implication s Interventions to maximize patient safety should consider the vulnerable transition from hospital to home . The Editors Patient safety is a public concern that has received substantial attention , especially since the release of two reports from the U.S. Institute of Medicine . The first of these , To Err Is Human , review ed the literature on adverse events , or injuries result ing from medical care ( 1 ) . On the basis of data from two large population -based chart review studies , the report estimated that adverse events occur in 2.9 % ( 2 ) to 3.7 % ( 3 ) of hospitalizations . The first of these studies ( 2 ) found that although most injuries are minor , approximately 1 in 10 results in death . The research ers determined that approximately half of the adverse events were caused by errors ( 1 , 3 , 4 ) . The second report , Crossing the Quality Chasm , which proposes strategies for improving the health system , declared patient safety a fundamental component of care quality ( 5 ) . However , the estimated incidence of adverse events quoted in To Err Is Human may underestimate the overall safety problem , since injuries occurring after discharge were not included in the evaluation . Patients may be especially vulnerable to injuries during this period because they may still have functional impairments and because discontinuities may occur at the interface of acute and ambulatory care ( 6 ) . These discontinuities may be worsened by the current health care environment , in which patients are leaving the hospital quicker and sicker ( 7 ) and may receive care from hospitalists rather than their primary care physicians ( 8) . Despite these theoretical concerns , few studies are available to estimate the extent of the problem . Several studies have determined the risk for postdischarge wound infections in surgical patients ( 9 , 10 ) , but this is a specific type of safety problem and the risk can not be generalized . Other studies have used readmission rates to identify poor- quality hospital care ( 11 ) . However , this outcome is an insensitive and nonspecific marker of quality in general ( 11 ) and safety in particular . Information on the incidence and type of adverse events is vital for improving postdischarge safety . We wanted to determine the incidence and severity of adverse events affecting patients after discharge from the hospital to home . In addition , 
    Output:
    
Conclusions : Pharmacy-supported TOC programs were associated with a significant reduction in the odds of 30-day readmissions