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Care transitions from the hospital to home remain a vulnerable time for many patients, especially for those with heart failure (CHF) and chronic obstructive pulmonary disease (COPD). Despite regular use in chronic disease management, it remains unclear how technology can best support patients during their transition from the hospital. We sought to evaluate the impact of a technology-supported care transition support program on hospitalizations, days out of the community and mortality. Using a pragmatic randomized trial, we enrolled patients (511 enrolled, 478 analyzed) hospitalized with CHF/COPD to "E-Coach," an intervention with condition-specific customization and in-hospital and post-discharge support by a care transition nurse (CTN), interactive voice response post-discharge calls, and CTN follow-up versus usual post-discharge care (UC). The primary outcome was 30-day rehospitalization. Secondary outcomes included (1) rehospitalization and death and (2) days in the hospital and out of the community. E-Coach and UC groups were similar at baseline except for gender imbalance (p = 0.02). After adjustment for gender, our primary outcome, 30-day rehospitalization rates did not differ between the E-Coach and UC groups (15.0 vs. 16.3 %, adjusted hazard ratio [95 % confidence interval]: 0.94 [0.60, 1.49]). However, in the COPD subgroup, E-Coach was associated with significantly fewer days in the hospital (0.5 vs. 1.6, p = 0.03). E-Coach, an IVR-augmented care transition intervention did not reduce rehospitalization. The positive impact on our secondary outcome (days in hospital) among COPD patients, but not in CHF, may suggest that E-Coach may be more beneficial among patients with COPD.NIH trial registry number: NCT01135381Trial Protocol: http://dx.doi.org/ 10.1016/j.cct.2012.08.007.

With its focus on holistic approaches to patient care, caregiver support, and delivery system redesign, geriatrics has advanced our understanding of optimal care during transitions. This article provides a framework for incorporating geriatrics principles into care transition activities by discussing the following elements: (1) identifying factors that make transitions more complex, (2) engaging care "receivers" and tailoring home care to meet patient needs, (3) building "recovery plans" into transitional care, (4) predicting and avoiding preventable readmissions, and (5) adopting a palliative approach, when appropriate, that optimizes patient and family goals of care. The article concludes with a discussion of practical aspects of designing, implementing, and evaluating care transitions programs for those with complex care needs, as well as implications for public policy.

Background: Unresolved medication discrepancies during hospitalization can contribute to adverse drug events, resulting in patient harm. Discrepancies can be reduced by performing medication reconciliation; however, effective implementation of medication reconciliation has proven to be challenging. The goals of the Multi-Center Medication Reconciliation Quality Improvement Study (MARQUIS) are to operationalize best practices for inpatient medication reconciliation, test their effect on potentially harmful unintentional medication discrepancies, and understand barriers and facilitators of successful implementation., Methods: Six U.S. hospitals are participating in this quality improvement mentored implementation study. Each hospital has collected baseline data on the primary outcome: the number of potentially harmful unintentional medication discrepancies per patient, as determined by a trained on-site pharmacist taking a "gold standard" medication history. With the guidance of their mentors, each site has also begun to implement one or more of 11 best practices to improve medication reconciliation. To understand the effect of the implemented interventions on hospital staff and culture, we are performing mixed methods program evaluation including surveys, interviews, and focus groups of front line staff and hospital leaders., Discussion: At baseline the number of unintentional medication discrepancies in admission and discharge orders per patient varies by site from 2.35 to 4.67 (mean=3.35). Most discrepancies are due to history errors (mean 2.12 per patient) as opposed to reconciliation errors (mean 1.23 per patient). Potentially harmful medication discrepancies averages 0.45 per patient and varies by site from 0.13 to 0.82 per patient. We discuss several barriers to implementation encountered thus far. In the end, we anticipate that MARQUIS tools and lessons learned have the potential to decrease medication discrepancies and improve patient outcomes., Trial Registration: Clinicaltrials.gov identifier NCT01337063.

Background: Ward attending rounds are an integral part of internal medicine education. Being a good teacher is necessary, but not sufficient for successful rounds. Understanding perceptions of successful attending rounds (AR) may help define key areas of focus for enhancing learning, teaching and patient care., Objective: We sought to expand the conceptual framework of 30 previously identified attributes contributing to successful AR by: 1) identifying the most important attributes, 2) grouping similar attributes, and 3) creating a cognitive map to define dimensions and domains contributing to successful rounds., Design: Multi-institutional, cross-sectional study design., Participants: We recruited residents and medical students from a university-based internal medicine residency program and a community-based family medicine residency program. Faculty attending a regional general medicine conference, affiliated with multiple institutions, also participated., Main Measures: Participants performed an unforced card-sorting exercise, grouping attributes based on perceived similarity, then rated the importance of attributes on a 5-point Likert scale. We translated our data into a cognitive map through multi-dimensional scaling and hierarchical cluster analysis., Key Results: Thirty-six faculty, 49 residents and 40 students participated. The highest rated attributes (mean rating) were "Teach by example (bedside manner)" (4.50), "Sharing of attending's thought processes" (4.46), "Be approachable-not intimidating" (4.45), "Insist on respect for all team members" (4.43), "Conduct rounds in an organized, efficient & timely fashion" (4.39), and "State expectations for residents/students" (4.37). Attributes were plotted on a two-dimensional cognitive map, and adequate convergence was achieved. We identified five distinct domains of related attributes: 1) Learning Atmosphere, 2) Clinical Teaching, 3) Teaching Style, 4) Communicating Expectations, and 5) Team Management., Conclusions: We identified five domains of related attributes essential to the success of ward attending rounds.

Objective: To determine the effectiveness of a provider-based intervention to improve medication intensification among patients with diabetes., Design: Effectiveness cluster-randomised trial. Baseline and follow-up cross-sections of diabetes physicians' patients., Setting: Eleven U.S. Southeastern states, 2006-2008., Participants: 205 Rural primary care physicians, 95 completed the study., Intervention: Multicomponent interactive intervention including web-based continuing medical education (CME), performance feedback and quality improvement tools., Primary Outcome Measures: Medication intensification, a dose increase of an existing medication or the addition of a new class of medication for glucose, blood pressure and lipids control on any of the three most recent office visits., Results: Of 364 physicians attempting to register, 102 were randomised to the intervention and 103 to the control arms; 95 physicians (intervention, n=48; control, n=47) provided data on their 1182 of their patients at baseline (intervention, n=715; control, n=467) and 945 patients at follow-up (intervention, n=479; control, n=466). For A1c control, medication intensification increased in both groups (intervention, pre 26.4% vs post 32.6%, p=0.022; control, pre 24.8% vs post 31.1%, p=0.033) (intervention, adjusted OR (AOR) 1.37; 95% CI 1.06 to 1.76; control, AOR 1.41 (95% CI 1.06 to 1.89)); however, we observed no incremental benefit solely due to the intervention (group-by-time interaction, p=0.948). Among patients with the worst glucose control (A1c >9%), intensification increased in both groups (intervention, pre 34.8% vs post 62.5%, p=0.002; control, pre 35.7% vs post 61.4%, p=0.008)., Conclusions: A wide-reach, low-intensity, web-based interactive multicomponent intervention had no significant incremental effect on medication intensification for control of glucose, blood pressure or lipids for patients with diabetes of physicians practising in the rural Southeastern USA., Trial Registration: NCT00403091.

Purpose: To explore the relationship between degree of rurality and glucose (hemoglobin A1c), blood pressure (BP), and lipid (LDL) control among patients with diabetes., Methods: Descriptive study; 1,649 patients in 205 rural practices in the United States. Patients' residence ZIP codes defined degree of rurality (Rural-Urban Commuting Areas codes). Outcomes were measures of acceptable control (A1c < = 9%, BP < 140/90 mmHg, LDL < 130 mg/dL) and optimal control (A1c < 7%, BP < 130/80 mmHg, LDL < 100 mg/dL). Statistical significance was set at P < .008 (Bonferroni's correction)., Findings: Although the proportion of patients with reasonable A1c control worsened by increasing degree of rurality, the differences were not statistically significant (urban 90%, large rural 88%, small rural 85%, isolated rural 83%; P = .10); mean A1c values also increased by degree of rurality, although not statistically significant (urban 7.2 [SD 1.6], large rural 7.3 [SD 1.7], small rural 7.5 [SD 1.8], isolated rural 7.5 [SD 1.9]; P = .16). We observed no differences between degree of rural and reasonable BP or LDL control (P = .42, P = .23, respectively) or optimal A1c or BP control (P = .52, P = .65, respectively). Optimal and mean LDL values worsened as rurality increased (P = .08, P = .029, respectively)., Conclusions: In patients with diabetes who seek care in the rural Southern United States, we observed no relationship between degree of rurality of patients' residence and traditional measures of quality of care. Further examination of the trends and explanatory factors for relative worsening of metabolic control by increasing degree of rurality is warranted., (© 2012 National Rural Health Association.)

Objectives: To determine whether cumulative symptom burden predicts hospitalization or emergency department (ED) visits in a cohort of older adults., Design: Prospective, observational study with a baseline in-home assessment of symptom burden., Setting: Central Alabama., Participants: Nine hundred eighty community-dwelling adults aged 65 and older (mean 75.3 ± 6.7) recruited from a random sample of Medicare beneficiaries stratified according to sex, race, and urban/rural residence., Measurements: Symptom burden score (range 0-10). One point was given for each symptom reported: shortness of breath, tiredness or fatigue, problems with balance or dizziness, leg weakness, poor appetite, pain, stiffness, constipation, anxiety, and loss of interest in activities. Dependent variables were hospitalizations and ED visits, assessed every 6 months during the 8.5-year follow-up period. Using Cox proportional hazards models, time from the baseline in-home assessment to the first hospitalization and first hospitalization or ED visit was determined., Results: During the 8.5-year follow-up period, 545 (55.6%) participants were hospitalized or had an ED visit. Participants with greater symptom burden had higher risk of hospitalization (hazard ratio (HR) = 1.09, 95% confidence interval (CI) = 1.05-1.14) and hospitalization or ED visit (HR = 1.10, 95% CI = 1.06-1.14) than those with lower scores. Participants living in rural areas had significantly lower risk of hospitalization (HR = 0.83, 95% CI = 0.69-0.99) and hospitalization or ED visit (HR = 0.80, 95% CI = 0.70-0.95) than individuals in urban areas, independent of symptom burden and comorbidity., Conclusion: Greater symptom burden was associated with higher risk of hospitalization and ED visits in community-dwelling older adults. Healthcare providers treating older adults should consider symptom burden to be an additional risk factor for subsequent hospital utilization., (© 2012, Copyright the Authors Journal compilation © 2012, The American Geriatrics Society.)

Background: Little research has examined the incidence, clinical relevance, and predictors of medication reconciliation errors at hospital admission and discharge., Objective: To identify patient- and medication-related factors that contribute to pre-admission medication list (PAML) errors and admission order errors, and to test whether such errors persist in the discharge medication list., Design, Participants: We conducted a cross-sectional analysis of 423 adults with acute coronary syndromes or acute decompensated heart failure admitted to two academic hospitals who received pharmacist-assisted medication reconciliation during the Pharmacist Intervention for Low Literacy in Cardiovascular Disease (PILL-CVD) Study., Main Measures: Pharmacists assessed the number of total and clinically relevant errors in the PAML and admission and discharge medication orders. We used negative binomial regression and report incidence rate ratios (IRR) of predictors of reconciliation errors., Key Results: On admission, 174 of 413 patients (42%) had ≥1 PAML error, and 73 (18%) had ≥1 clinically relevant PAML error. At discharge, 158 of 405 patients (39%) had ≥1 discharge medication error, and 126 (31%) had ≥1 clinically relevant discharge medication error. Clinically relevant PAML errors were associated with older age (IRR = 1.46; 95% CI, 1.00- 2.12) and number of pre-admission medications (IRR = 1.17; 95% CI, 1.10-1.25), and were less likely when a recent medication list was present in the electronic medical record (EMR) (IRR = 0.54; 95% CI, 0.30-0.96). Clinically relevant admission order errors were also associated with older age and number of pre-admission medications. Clinically relevant discharge medication errors were more likely for every PAML error (IRR = 1.31; 95% CI, 1.19-1.45) and number of medications changed prior to discharge (IRR = 1.06; 95% CI, 1.01-1.11)., Conclusions: Medication reconciliation errors are common at hospital admission and discharge. Errors in preadmission medication histories are associated with older age and number of medications and lead to more discharge reconciliation errors. A recent medication list in the EMR is protective against medication reconciliation errors.

Individuals with multimorbidity may be at increased risk of hospitalization and death. Comorbidity indexes do not capture severity of illness or healthcare utilization; however, inflammation biomarkers that are not disease-specific may predict hospitalization and death in older adults. We sought to predict hospitalization and mortality of older adults using inflammation biomarkers. From a prospective, observational study, 370 community-dwelling adults 65 years or older from central Alabama participated in an in-home assessment and provided fasting blood samples for inflammation biomarker testing in 2004. We calculated an inflammation summary score (range 0-4), one point each for low albumin, high C-reactive protein, low cholesterol, and high interleukin-6. Utilizing Cox proportional hazards models, inflammation summary scores were used to predicted time to hospitalization and death during a 4-year follow up period. The mean age was 73.7 (±5.9 yrs), and 53 (14%) participants had summary scores of 3 or 4. The rates of dying were significantly increased for participants with inflammation summary scores of 2, 3, or 4 (hazard ratio (HR) 2.22, 2.78, and 7.55, respectively; p<0.05). An inflammation summary score of 4 significantly predicted hospitalization (HR 5.92, p<0.05). Community-dwelling older adults with biomarkers positive for inflammation had increased rates of being hospitalized or dying during the follow up period. Assessment of the individual contribution of particular inflammation biomarkers in the prediction of health outcomes in older populations and the development of validated summary scores to predict morbidity and mortality are needed., (Published by Elsevier Ireland Ltd.)

Background: Reporting of quality indicators (QIs) in Veterans Health Administration Medical Centers is complicated by estimation error caused by small numbers of eligible patients per facility. We applied multilevel modeling and empirical Bayes (EB) estimation in addressing this issue in performance reporting of stroke care quality in the Medical Centers., Methods and Results: We studied a retrospective cohort of 3812 veterans admitted to 106 Medical Centers with ischemic stroke during fiscal year 2007. The median number of study patients per facility was 34 (range, 12-105). Inpatient stroke care quality was measured with 13 evidence-based QIs. Eligible patients could either pass or fail each indicator. Multilevel modeling of a patient's pass/fail on individual QIs was used to produce facility-level EB-estimated QI pass rates and confidence intervals. The EB estimation reduced interfacility variation in QI rates. Small facilities and those with exceptionally high or low rates were most affected. We recommended 8 of the 13 QIs for performance reporting: dysphagia screening, National Institutes of Health Stroke Scale documentation, early ambulation, fall risk assessment, pressure ulcer risk assessment, Functional Independence Measure documentation, lipid management, and deep vein thrombosis prophylaxis. These QIs displayed sufficient variation across facilities, had room for improvement, and identified sites with performance that was significantly above or below the population average. The remaining 5 QIs were not recommended because of too few eligible patients or high pass rates with little variation., Conclusions: Considerations of statistical uncertainty should inform the choice of QIs and their application to performance reporting.

Background: Little is known about how faculty, residents, and fellows practice for oral presentations at academic meetings. We sought to categorize presenters' practice styles and the impact of feedback., Methods: We surveyed oral presenters at 5 annual academic general internal medicine meetings between 2008 and 2010, using a cross-sectional design. Main measures were frequency and settings of practice, most helpful practice setting, changes made in response to feedback, impact of feedback, and perceived quality of presentation., Results: The response rate was 63% (333/525 responders). Respondents represented 59 academic medical centers. Presenters reported practicing in a mean ± SD of 2.3 (±1.3) of 5 different settings. Of the 46% of presenters (152/333) who practiced in front of a group of more experienced colleagues, 80% of presenters (122/152) reported it was the most helpful setting. Eighty-one percent of presenters (268/333) practiced alone, and 25% of presenters (82/333) reported practicing alone was the most helpful setting. The mean numbers of change types reported by faculty were fewer than those reported by residents and fellows (mean 2.3 ± 1.8, and 3.1 ± 2.0, respectively; P < .001). Practicing alone was not associated with changes in content (P  =  .30), visual aids (P  =  .12), or delivery style (P  =  .53)., Conclusions: Practicing in front of a group of experienced colleagues was the most helpful setting in which to prepare for an oral academic meeting presentation, but it was not universally utilized. Feedback given at these sessions was more likely to result in changes made to the presentation; however, broader implementation of such sessions 5 require institutional support.

Objective: To determine the effectiveness of a provider-based education and implementation intervention for improving diabetes control., Design: Cluster-randomized trial with baseline and follow-up cross sections of diabetes patients in each participating physician's practice., Setting: Eleven US Southeastern states, 2006-08., Participants: Two hundred and five rural primary care physicians., Intervention: Multi-component interactive intervention including Web-based continuing medical education, performance feedback and quality improvement tools. Primary Outcome Measures 'Acceptable control' [hemoglobin A1c ≤9%, blood pressure (BP) <140/90 mmHg, low-density lipoprotein cholesterol (LDL) <130 mg/dl] and 'optimal control' (A1c <7%, BP <130/80 mmHg, LDL <100 mg/dl)., Results: Of 364 physicians attempting to register, 205 were randomized to the intervention (n= 102) or control arms (n= 103). Baseline and follow-up data were provided by 95 physicians (2127 patients). The proportion of patients with A1c ≤9% was similar at baseline and follow-up in both the control [adjusted odds ratio (AOR): 0.94; 95% confidence interval (CI): 0.61, 1.47] and intervention arms [AOR: 1.16 (95% CI: 0.80, 1.69)]; BP <140/90 mmHg and LDL <130 mg/dl were also similar at both measurement points (P= 0.66, P= 0.46; respectively). We observed no significant effect on diabetes control attributable to the intervention for any of the primary outcome measures. Intervention physicians engaged with the Website over a median of 64.7 weeks [interquartile range (IQR): 45.4-81.8) for a median total of 37 min (IQR: 16-66)., Conclusions: A wide-reach, low-intensity, Web-based interactive multi-component intervention did not improve control of glucose, BP or lipids for patients with diabetes of physicians practicing in the rural Southeastern US.

Purpose: Even though pay-for-performance programs are being rapidly implemented, little is known about how patient complexity affects practice-level performance assessment in rural settings. We sought to determine the association between patient complexity and practice-level performance in the rural United States., Basic Procedures: Using baseline data from a trial aimed at improving diabetes care, we determined factors associated with a practice's proportion of patients having controlled diabetes (hemoglobin A1c

Purpose: To investigate the association between physician participants' levels of engagement in a Web-based educational intervention and their patients' baseline diabetes measures., Method: The authors conducted a randomized trial of online CME activities designed to improve diabetes care provided by family, general, and internal medicine physicians in rural areas of 11 southeastern states between September 2006 and July 2008. Using incidence rate ratios derived from negative binomial models, the relationship between physicians' engagement with the study Web site and baseline proportion of their patients having controlled diabetes (hemoglobin A1c < or = 7%) was explored., Results: One hundred thirty-three participants (intervention = 64; control = 69) provided information for 1,637 patients with diabetes. In the intervention group, physicians in practices in the worst quartiles of A1c control were least engaged with the study Web site in nearly all dimensions. Total number of pages viewed decreased as quartile of A1c control worsened (137, 73, 68, 57; P = .007); similarly, for a given 10% increase in proportion of patients with controlled A1c, participants viewed 1.13 times more pages (95% CI: 1.02-1.26, P = .02). In the control group, engagement was neither correlated with A1c control nor different across quartiles of A1c control., Conclusions: Engagement in Web-based interventions is measurable and has important implications for research and education. Because physicians of patients with the greatest need for improvement in A1c control may not use online educational resources as intensely as others, other strategies may be necessary to engage these physicians in professional development activities.

Background: Multiple uncontrolled medical conditions may act as competing demands for clinical decision making. We hypothesized that multiple uncontrolled cardiovascular risk factors would decrease blood pressure (BP) medication intensification among uncontrolled hypertensive patients., Methods: We observed 946 encounters at two VA primary care clinics from May through August 2006. After each encounter, clinicians recorded BP medication intensification (BP medication was added or titrated). Demographic, clinical, and laboratory information were collected from the medical record. We examined BP medication intensification by presence and control of diabetes and/or hyperlipidemia. 'Uncontrolled' was defined as hemoglobin A1c >/= for diabetes, BP >/= 140/90 mmHg (>/= 130/80 mmHg if diabetes present) for hypertension, and low density lipoprotein cholesterol (LDL-c) >/= 130 mg/dl (>/= 100 mg/dl if diabetes present) for hyperlipidemia. Hierarchical regression models accounted for patient clustering and adjusted medication intensification for age, systolic BP, and number of medications., Results: Among 387 patients with uncontrolled hypertension, 51.4% had diabetes (25.3% were uncontrolled) and 73.4% had hyperlipidemia (22.7% were uncontrolled). The BP medication intensification rate was 34.9% overall, but higher in individuals with uncontrolled diabetes and uncontrolled hyperlipidemia: 52.8% overall and 70.6% if systolic BP >/= 10 mmHg above goal. Intensification rates were lowest if diabetes or hyperlipidemia were controlled, lower than if diabetes or hyperlipidemia were not present. Multivariable adjustment yielded similar results., Conclusions: The presence of uncontrolled diabetes and hyperlipidemia was associated with more guideline-concordant hypertension care, particularly if BP was far from goal. Efforts to understand and improve BP medication intensification in patients with controlled diabetes and/or hyperlipidemia are warranted.