The E-Coach technology-assisted care transition system: a pragmatic randomized trial.

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.

Regardless of age: Incorporating principles from geriatric medicine to improve care transitions for patients with complex needs.

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.

Determinants of health after hospital discharge: rationale and design of the Vanderbilt Inpatient Cohort Study (VICS).

BACKGROUND: The period following hospital discharge is a vulnerable time for patients when errors and poorly coordinated care are common. Suboptimal care transitions for patients admitted with cardiovascular conditions can contribute to readmission and other adverse health outcomes. Little research has examined the role of health literacy and other social determinants of health in predicting post-discharge outcomes. METHODS: The Vanderbilt Inpatient Cohort Study (VICS), funded by the National Institutes of Health, is a prospective longitudinal study of 3,000 patients hospitalized with acute coronary syndromes or acute decompensated heart failure. Enrollment began in October 2011 and is planned through October 2015. During hospitalization, a set of validated demographic, cognitive, psychological, social, behavioral, and functional measures are administered, and health status and comorbidities are assessed. Patients are interviewed by phone during the first week after discharge to assess the quality of hospital discharge, communication, and initial medication management. At approximately 30 and 90 days post-discharge, interviewers collect additional data on medication adherence, social support, functional status, quality of life, and health care utilization. Mortality will be determined with up to 3.5 years follow-up. Statistical models will examine hypothesized relationships of health literacy and other social determinants on medication management, functional status, quality of life, utilization, and mortality. In this paper, we describe recruitment, eligibility, follow-up, data collection, and analysis plans for VICS, as well as characteristics of the accruing patient cohort. DISCUSSION: This research will enhance understanding of how health literacy and other patient factors affect the quality of care transitions and outcomes after hospitalization. Findings will help inform the design of interventions to improve care transitions and post-discharge outcomes.

Measuring symptoms in community-dwelling older adults: the psychometric properties of a brief symptom screen.

BACKGROUND: With aging, the probability of experiencing multiple chronic conditions has increased, along with symptoms associated with these conditions. Symptoms form a central component of illness burden, and distress. To date, most symptom measures have focused on a particular disease population. OBJECTIVE: We aimed to develop and evaluate a simple symptom screen using data obtained from a representative sample of community-dwelling older adults. METHODS: Psychometric analyses were conducted on 10 self-reported dichotomous symptom indicators collected during in-person interviews from a sample of 1000 community-dwelling older adults. Symptoms included shortness of breath, feeling tired or fatigued, problems with balance or dizziness, perceived weakness in legs, constipation, daily pain, stiffness, poor appetite, anxiety, and anhedonia. RESULTS: Over one third of the individuals (37.4%) had 5 or more concurrent symptoms. Stiffness and feeling tired were the most common symptoms. Confirmatory factor analyses were performed on the 10 symptoms for single factor and bifactor (physical and affective) models of symptom reporting. Goodness-of-fit indices indicated better fit for the bifactor model (χdf=10=89.6; P<0.001), but the practical significance of the improvement in fit was negligible. Differential item functioning analyses showed some differences of relatively high magnitude in location parameters by race; however, because the differential item functioning was in different directions, the impact on the overall measure was most likely lessened. CONCLUSIONS: Among community-dwelling older adults, a large proportion experienced multiple co-occurring symptoms. This Brief Symptom Screen can be used to quickly measure the overall symptom load in older adult populations, including those with multiple chronic conditions.

Rationale and design of the Multicenter Medication Reconciliation Quality Improvement Study (MARQUIS).

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.

Quality of diabetes mellitus care by rural primary care physicians.

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.

Medication intensification in diabetes in rural primary care: a cluster-randomised effectiveness trial.

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.

Symptom burden predicts hospitalization independent of comorbidity in community-dwelling older adults.

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.

Using cognitive mapping to define key domains for successful attending rounds.

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.

Inflammatory biomarkers as predictors of hospitalization and death in community-dwelling older adults.

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.

Effect of patient- and medication-related factors on inpatient medication reconciliation errors.

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.

Estimating and reporting on the quality of inpatient stroke care by Veterans Health Administration Medical Centers.

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.

Risk prediction models for hospital readmission: a systematic review.

CONTEXT: Predicting hospital readmission risk is of great interest to identify which patients would benefit most from care transition interventions, as well as to risk-adjust readmission rates for the purposes of hospital comparison. OBJECTIVE: To summarize validated readmission risk prediction models, describe their performance, and assess suitability for clinical or administrative use. DATA SOURCES AND STUDY SELECTION: The databases of MEDLINE, CINAHL, and the Cochrane Library were searched from inception through March 2011, the EMBASE database was searched through August 2011, and hand searches were performed of the retrieved reference lists. Dual review was conducted to identify studies published in the English language of prediction models tested with medical patients in both derivation and validation cohorts. DATA EXTRACTION: Data were extracted on the population, setting, sample size, follow-up interval, readmission rate, model discrimination and calibration, type of data used, and timing of data collection. DATA SYNTHESIS: Of 7843 citations reviewed, 30 studies of 26 unique models met the inclusion criteria. The most common outcome used was 30-day readmission; only 1 model specifically addressed preventable readmissions. Fourteen models that relied on retrospective administrative data could be potentially used to risk-adjust readmission rates for hospital comparison; of these, 9 were tested in large US populations and had poor discriminative ability (c statistic range: 0.55-0.65). Seven models could potentially be used to identify high-risk patients for intervention early during a hospitalization (c statistic range: 0.56-0.72), and 5 could be used at hospital discharge (c statistic range: 0.68-0.83). Six studies compared different models in the same population and 2 of these found that functional and social variables improved model discrimination. Although most models incorporated variables for medical comorbidity and use of prior medical services, few examined variables associated with overall health and function, illness severity, or social determinants of health. CONCLUSIONS: Most current readmission risk prediction models that were designed for either comparative or clinical purposes perform poorly. Although in certain settings such models may prove useful, efforts to improve their performance are needed as use becomes more widespread.

A web-based diabetes intervention for physician: a cluster-randomized effectiveness trial.

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.

Patient complexity and diabetes quality of care in rural settings.

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

Preparing for oral scientific and clinical vignette presentations.

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.

Use of ecological momentary assessment to guide curricular change in graduate medical education.

PURPOSE: To assess whether a novel evaluation tool could guide curricular change in an internal medicine residency program. METHOD: The authors developed an 8-item Ecological Momentary Assessment tool and collected daily evaluations from residents of the relative educational value of 3 differing ambulatory morning report formats (scale: 8  =  best, 0  =  worst). From the evaluations, they made a targeted curricular change and used the tool to assess its impact. RESULTS: Residents completed 1388 evaluation cards for 223 sessions over 32 months, with a response rate of 75.3%. At baseline, there was a decline in perceived educational value with advancing postgraduate (PGY) year for the overall mean score (PGY-1, 7.4; PGY-2, 7.2; PGY-3, 7.0; P < .01) and for percentage reporting greater than 2 new things learned (PGY-1, 77%; PGY-2, 66%; PGY-3, 50%; P < .001). The authors replaced the format of a lower scoring session with one of higher cognitive content to target upper-level residents. The new session's mean score improved (7.1 to 7.4; P  =  .03); the adjusted odds ratios before and after the change for percentage answering, "Yes, definitely" to "Area I need to improve" was 2.53 (95% confidence interval [CI], 1.45-4.42; P  =  .001) and to "Would recommend to others," it was 2.08 (95% CI, 1.12-3.89; P  =  .05). CONCLUSIONS: The Ecological Momentary Assessment tool successfully guided ambulatory morning report curricular changes and confirmed successful curricular impact. Ecological Momentary Assessment concepts of multiple, frequent, timely evaluations can be successfully applied in residency curriculum redesign.