Patient, Caregiver, and Physician Work in Heart Failure Disease Management: A Qualitative Study of Issues That Undermine Wellness.

OBJECTIVE: To identify factors underlying heart failure hospitalization. METHODS: Between January 1, 2012, and May 31, 2012, we combined medical record reviews and cross-sectional qualitative interviews of multiple patients with heart failure, their clinicians, and their caregivers from a large academic medical center in the Midwestern United States. The interview data were analyzed using a 3-step grounded theory-informed process and constant comparative methods. Qualitative data were compared and contrasted with results from the medical record review. RESULTS: Patient nonadherence to the care plan was the most important contributor to hospital admission; however, reasons for nonadherence were complex and multifactorial. The data highlight the importance of patient education for the purposes of condition management, timeliness of care, and effective communication between providers and patients. CONCLUSION: To improve the consistency and quality of care for patients with heart failure, more effective relationships among patients, providers, and caregivers are needed. Providers must be pragmatic when educating patients and their caregivers about heart failure, its treatment, and its prognosis.

Survey of Provider Transfusion Practices for Oncology Patients in an Academic Medical Center.

OBJECTIVES: Hospitalized oncology patients receive care from a variety of professionals, each of whom plays a role in decisions related to blood transfusions. We sought to examine differences in transfusion practices based on professional role, years of experience, and patient clinical scenario. METHODS: We surveyed general medicine residents, hospitalists, and oncologists caring for inpatients at a large academic medical center between August 2013 and June 2014. Respondents reported transfusion practices in three different patient scenarios: a generally healthy patient, a patient with solid tumor malignancy, and a patient with hematologic malignancy. We also assessed rationale for transfusion practices. Bivariate comparisons of respondent characteristics and transfusion threshold were conducted using the Fisher exact test. Multivariate logistic regression was performed to assess the relative relations among professional role, years in practice, clinical scenario, and transfusion threshold <7 g/dL. RESULTS: Of 158 physicians surveyed, 97 responded (61.4%). In bivariate analyses, fewer oncologists than residents or hospitalists used a threshold of <7 g/dL, but the result was significant for only one of three scenarios. The multivariate odds of transfusing at a threshold <7 g/dL were significantly higher among nononcologists (odds ratio [OR] 2.10, 95% confidence interval [CI] 1.03-4.28). Residents and practitioners in practice for <4 years also were more likely to use a threshold <7 g/dL (OR 1.82, 95% CI 0.99-3.33). Providers were less likely to use a restrictive threshold when an underlying malignancy was present (solid tumor OR 0.31, 95% CI 0.15-0.64; hematologic malignancy OR 0.34, 95% CI 0.16-0.70). CONCLUSIONS: Transfusion thresholds differed based on professional role, years in practice, and patient scenario. Further research is needed to determine the optimal transfusion threshold for oncology patients.

Association of hospital admission service structure with early transfer to critical care, hospital readmission, and length of stay.

BACKGROUND: Hospital medical groups use various staffing models that may systematically affect care continuity during the admission process. OBJECTIVE: To compare the effect of 2 hospitalist admission service models ("general" and "admitter-rounder") on patient disposition and length of stay. DESIGN: Retrospective observational cohort study with difference-in-difference analysis. SETTING: Large tertiary academic medical center in the United States. PARTICIPANTS: Patients (n = 19,270) admitted from the emergency department to hospital medicine and medicine teaching services from July 2010 to June 2013. INTERVENTIONS: Admissions to hospital medicine staffed by 2 different service models, compared to teaching service admissions. MEASUREMENTS: Incidence of transfer to critical care within the first 24 hours of hospitalization, hospital and emergency department length of stay, and hospital readmission rates ≤30 days postdischarge. RESULTS: The change of hospitalist services to an admitter-rounder model was associated with no significant change in transfer to critical care or hospital length of stay compared to the teaching service (difference-in-difference P = 0.32 and P = 0.87, respectively). The admitter-rounder model was associated with decreased readmissions compared to the teaching service on difference-in-difference analysis (odds ratio difference: -0.21, P = 0.01). Adoption of the hospitalist admitter-rounder model was associated with an increased emergency department length of stay compared to the teaching service (difference of +0.49 hours, P < 0.001). CONCLUSIONS: Rates of transfer to intensive care and overall hospital length of stay between the hospitalist admission models did not differ significantly. The hospitalist admitter-rounder admission service structure was associated with extended emergency department length of stay and a decrease in readmissions. Journal of Hospital Medicine 2016;11:669-674. © 2016 Society of Hospital Medicine.

Impact of pharmacist involvement in the transitional care of high-risk patients through medication reconciliation, medication education, and postdischarge call-backs (IPITCH Study).

BACKGROUND: Previous data suggest that direct pharmacist interaction with patients through medication reconciliation, discharge counseling, and postdischarge phone calls decreases the number of adverse drug events (ADEs) and plays an overall positive role in transitional care. Previous studies have evaluated pharmacist involvement in improving transitional care, but these studies did not include multiple postdischarge follow-up phone calls. OBJECTIVES: The objectives of this study were to assess the impact of pharmacist involvement in transitions of care as measured by decreased medication errors (MEs) and ADEs, patients' knowledge related to communication about their medications as measured by improvement in the Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) scores, and 30-day all-cause inpatient readmissions and emergency department (ED) visits. METHODS: This was a prospective, randomized, single-period longitudinal study that occurred from November 2012 through June 2013 at an urban, tertiary, academic medical center. Patients admitted to 2 designated internal medicine units on high-risk medications or with greater than 3 prescription medications upon discharge were included for randomization. The control group received the usual hospital standard of care. The study group received face-to-face medication reconciliation, a patient-specific pharmaceutical care plan, discharge counseling, and postdischarge phone calls on days 3, 14, and 30 to provide education and assess study endpoints. RESULTS: A total of 278 patients were included in the final analysis, with 141 in the control group and 137 in the study group. Fifty-five patients (39%) in the control arm experienced an inpatient readmission or ED visit within 30-days postdischarge compared to 34 patients (24.8%) in the study arm (P = 0.01). Eighteen patients (12.8%) in the control group experienced an ADEs or MEs compared to 11 patients (8%) in the study group (P > 0.05). The HCAHPS scores during the study period showed a 9% improvement for the assessed questionnaire domain (P > 0.05). CONCLUSIONS: This study demonstrated that pharmacist involvement in hospital discharge transitions of care had a positive impact on decreasing composite inpatient readmissions and ED visits. Statistically significant difference in medication-related events and HCAHPS scores were not observed. Patients with moderately complex medication regimens benefited from a continuity of care involving a pharmacy team during transitions in care.

Effect of patient-centred bedside rounds on hospitalised patients' decision control, activation and satisfaction with care.

IMPORTANCE: Though interprofessional bedside rounds have been promoted to enhance patient-centred care for hospitalised patients, few studies have been conducted in adult hospital settings and evidence of impact is lacking. OBJECTIVE: To evaluate the effect of patient-centred bedside rounds (PCBRs) on measures of patient-centred care. DESIGN AND SETTING: Cluster randomised controlled trial involving four similar non-teaching hospitalist service units in a large urban hospital. PARTICIPANTS: Hospitalised general medical patients. INTERVENTION: We assembled working groups on two intervention units, consisting of professionals and patient/family members, to determine the optimal timing, duration and format for PCBR. Nurses and hospitalists rounded together in PCBR using a communication tool to provide a framework for discussion and unit leaders joined PCBR to provide coaching during initial weeks of implementation. MAIN OUTCOMES: Using patient interviews, we assessed preferred and experienced roles in medical decision-making using the Control Preferences Scale, activation using the Short Form of the Patient Activation Measure, and satisfaction. We also compared postdischarge patient satisfaction survey items related to teamwork, involvement in decisions and overall care. We assessed nurses', physicians' and advanced practice providers' (APP) perceptions of PCBR using a survey developed for this study. RESULTS: Overall, 650 patients were approached for structured interview during hospitalisation: 284 were excluded because of disorientation, 54 were excluded because of non-English language, 72 declined to participate and 4 withdrew from the study after enrolment. Interview data were available for 236 (122 control and 114 intervention unit) patients, and postdischarge satisfaction survey data were available for 493 (274 control and 219 intervention unit) patients. We found no significant differences in patients' perceptions of shared decision-making, activation or satisfaction with care. Results were similar in analyses based on whether PCBR had been performed (ie, per protocol). We also found no difference in postdischarge patient satisfaction items. Results were similar in multivariate analyses controlling for patient characteristics and clustering of patients within study units. A majority of nurses (78.6%), but only about half of hospitalist physicians and APPs felt that PCBR improved communication with patients (47.4%). A minority of nurses (46.4%) and physicians and APPs (36.8%) agreed that PCBR had improved the efficiency of their workday. CONCLUSIONS: PCBR had no impact on patients' perceptions of shared decision-making, activation or satisfaction with care. Additional research is needed to identify optimal approaches that can be reliably implemented in hospital settings to improve patient-centred care.

The physician mentored implementation model: a promising quality improvement framework for health care change.

Quality improvement (QI) efforts hold great promise for improving care delivery. However, hospitals often struggle with QI implementation and fail to sustain improvement in either process changes or patient outcomes. Physician mentored implementation (PMI) is a novel approach that promotes the success and sustainability of QI initiatives at hospitals. It leverages the expertise of external physician mentors who coach QI teams to implement interventions at their local hospitals. The PMI model includes five core components: (1) a hospital self-assessment tool, (2) a face-to-face training session including direct interaction with a physician mentor, (3) a guided continuous quality improvement and systems approach, (4) yearlong individual physician mentoring, and (5) a learning community supported by a resource center, listserv, and webinars. Mentors provide content and process expertise, rather than offering "one-size-fits-all" technical assistance that might not be sustained after the mentoring year ends. Mentors support and motivate QI teams throughout the planning and implementation phases of their interventions, help to engage hospital leadership, garner local physician buy-in, and address institutional barriers. Mentors also guide hospitals to identify opportunities for the adaptation and customization of original evidence-based models of care while ensuring the fidelity of those models. More than 350 hospitals have used the PMI model to implement successful national and statewide QI initiatives. Academic medical centers are charged with improving the health of patients and reengineering care delivery; thus, they serve as the ideal source for physician mentors and can act as leaders in implementing QI projects using the PMI model.

The effect of hospitalist discontinuity on adverse events.

BACKGROUND: Patient-physician continuity is difficult to achieve in hospital settings because of the need to provide care continuously. The impact of hospital physician discontinuity on patient safety is unknown. OBJECTIVE: To determine the association between hospital physician continuity and the incidence of adverse events (AEs). DESIGN: Retrospective observational study using multivariable models to adjust for patient characteristics. PARTICIPANTS: Patients admitted to a nonteaching hospitalist service in a large academic hospital between March 1, 2009 and December 31, 2011. MAIN MEASURE(S): Two measures of continuity were used. The Number of Physicians Index (NPI) was the total number of unique hospitalists caring for a patient. The Usual Provider of Care (UPC) Index was the proportion of encounters with the most frequently encountered hospitalist. Outcome measures were AEs detected by automated queries of information systems and confirmed by 2 physician researchers. KEY RESULTS: Our analysis included data from 474 hospitalizations. In unadjusted models, each 1-unit increase in the NPI (ie, less continuity) was significantly associated with the incidence of 1 or more AEs (odds ratio = 1.75; P < 0.001). However, UPC was not associated with incidence of AEs. Across all adjusted models, neither NPI nor UPC was significantly associated with the incidence of AEs. The direction of the effect of discontinuity on AEs was also inconsistent across models. CONCLUSIONS: Hospitalist physician continuity does not appear to be associated with the incidence of AEs. Because hospital care is provided by teams of clinicians, future research should evaluate the impact of team complexity and dynamics on patient outcomes.

Project BOOST implementation: lessons learned.

OBJECTIVES: Enhancing care coordination and reducing hospital readmissions have been a focus of multiple quality improvement (QI) initiatives. Project BOOST (Better Outcomes by Optimizing Safe Transitions) aims to enhance the discharge transition from hospital to home. Previous research indicates that QI initiatives originating externally often face difficulties gaining momentum or effecting lasting change in a hospital. We performed a qualitative evaluation of Project BOOST implementation by examining the successes and failures experienced by six pilot sites. We also evaluated the unique physician mentoring component of this program. Finally, we examined the impact of intensification of the physician mentoring model on adoption of BOOST interventions in two later Illinois cohorts (27 hospitals). METHODS: Qualitative analysis of six pilot hospitals used a process of methodological triangulation and analysis of the BOOST enrollment applications, the listserv, and content from telephone interviews. Evaluation of BOOST implementation at Illinois hospitals occurred via mid-year and year-end surveys. RESULTS: The identified common barriers included inadequate understanding of the current discharge process, insufficient administrative support, lack of protected time or dedicated resources, and lack of frontline staff buy-in. Facilitators of implementation included the mentor, a small beginning, teamwork, and proactive engagement of the patient. Notably, hospitals viewed their mentors as essential facilitators of change. Sites consistently commented that the individualized mentoring was extremely helpful and provided significant accountability and stimulated creativity. In the Illinois cohorts, the improved mentoring model showed more complete implementation of BOOST interventions. CONCLUSIONS: The implementation of Project BOOST was well received by hospitals, although sites faced substantial barriers consistent with other QI research reports. The unique mentorship element of Project BOOST proved extremely valuable in helping sites overcome their distinctive challenges and identify facilitators for success. The findings from this qualitative study should contribute to future BOOST implementation success and others' efforts to optimize hospital discharge transitions.

"You get caught up": youth decision-making and violence.

Violence is a major cause of morbidity and mortality among adolescents. We conducted serial focus groups with 30 youth from a violence prevention program to discuss violence in their community. We identified four recurrent themes characterizing participant experiences regarding peer decision-making related to violence: (1) youth pursue respect, among other typical tasks of adolescence; (2) youth pursue respect as a means to achieve personal safety; (3) youth recognize pervasive risks to their safety, frequently focusing on the prevalence of firearms; and (4) as youth balance achieving respect in an unsafe setting with limited opportunities, they express conflict and frustration. Participants recognize that peers achieve peer-group respect through involvement in unsafe or unhealthy behavior including violence; however they perceive limited alternative opportunities to gain respect. These findings suggest that even very high risk youth may elect safe and healthy alternatives to violence if these opportunities are associated with respect and other adolescent tasks of development.

Project BOOST: effectiveness of a multihospital effort to reduce rehospitalization.

BACKGROUND: Rehospitalization is a prominent target for healthcare quality improvement and performance-based reimbursement. The generalizability of existing evidence on best practices is unknown. OBJECTIVE: To determine the effect of Project BOOST (Better Outcomes for Older adults through Safe Transitions) on rehospitalization rates and length of stay. DESIGN: Semicontrolled pre-post study. SETTING/PARTICIPANTS: Volunteer sample of 11 hospitals varying in geography, size, and academic affiliation. INTERVENTION: Hospitals implemented Project BOOST-recommended tools supported by an external quality improvement physician mentor. METHODS: Pre-post changes in readmission rates and length of stay within BOOST units, and between BOOST units and site-designated control units. RESULTS: The average rate of 30-day rehospitalization in BOOST units was 14.7% prior to implementation and 12.7% 12 months later (P = 0.010), reflecting an absolute reduction of 2% and a relative reduction of 13.6%. Rehospitalization rates for matched control units were 14.0% in the preintervention period and 14.1% in the postintervention period (P = 0.831). The mean absolute reduction in readmission rates in BOOST units compared to control units was 2.0% (P = 0.054 for signed rank test comparing differences in readmission rate reduction in BOOST units compared to site-matched control units). CONCLUSIONS: Participation in Project BOOST appeared to be associated with a decrease in readmission rates.

Interventions to reduce 30-day rehospitalization: a systematic review.

BACKGROUND: About 1 in 5 Medicare fee-for-service patients discharged from the hospital is rehospitalized within 30 days. Beginning in 2013, hospitals with high risk-standardized readmission rates will be subject to a Medicare reimbursement penalty. PURPOSE: To describe interventions evaluated in studies aimed at reducing rehospitalization within 30 days of discharge. DATA SOURCES: MEDLINE, EMBASE, Web of Science, and the Cochrane Library were searched for reports published between January 1975 and January 2011. STUDY SELECTION: English-language randomized, controlled trials; cohort studies; or noncontrolled before-after studies of interventions to reduce rehospitalization that reported rehospitalization rates within 30 days. DATA EXTRACTION: 2 reviewers independently identified candidate articles from the results of the initial search on the basis of title and abstract. Two 2-physician reviewer teams reviewed the full text of candidate articles to identify interventions and assess study quality. DATA SYNTHESIS: 43 articles were identified, and a taxonomy was developed to categorize interventions into 3 domains that encompassed 12 distinct activities. Predischarge interventions included patient education, medication reconciliation, discharge planning, and scheduling of a follow-up appointment before discharge. Postdischarge interventions included follow-up telephone calls, patient-activated hotlines, timely communication with ambulatory providers, timely ambulatory provider follow-up, and postdischarge home visits. Bridging interventions included transition coaches, physician continuity across the inpatient and outpatient setting, and patient-centered discharge instruction. LIMITATIONS: Inadequate description of individual studies' interventions precluded meta-analysis of effects. Many studies identified in the review were single-institution assessments of quality improvement activities rather than those with experimental designs. Several common interventions have not been studied outside of multicomponent "discharge bundles." CONCLUSION: No single intervention implemented alone was regularly associated with reduced risk for 30-day rehospitalization. PRIMARY FUNDING SOURCE: None.

Hospital discharge documentation and risk of rehospitalisation.

BACKGROUND Avoidable hospital readmission is a focus of quality improvement efforts. The effectiveness of individual elements of the standard discharge process in reducing rehospitalisation is unknown. METHODS The authors conducted a case-control study of 1039 patients experiencing rehospitalisation within 30 days of discharge and 981 non-rehospitalised patients matched on admission diagnosis, discharge disposition, and severity of illness. In separate models for each discharge process component, the authors measured the relationship between readmission and discharge summary completion, contents of discharge summary, completion of discharge instructions, contents of discharge instructions, presence of caregiver for discharge instruction, completion of medication reconciliation, and arrangement of ambulatory follow-up prior to discharge. RESULTS Adjusting for patient and hospital characteristics, including severity of illness and discharge disposition, the study failed to find an association between readmission and most components of the discharge process. There was no association between readmission and medication reconciliation, transmission of discharge summary to an outpatient physician, or documentation of any specific aspect of discharge instruction. Associations were found between readmission and discharge with followup arranged (adjusted odds ratio (OR) 1.21; 95% CI 1.05 to 1.37) and increasing number of medicines (adjusted OR 1.02; 95% CI 1.01 to 1.04). CONCLUSIONS Documentation of discharge process components in the medical record may not reflect actual discharge process activities. Alternatively, mandated discharge processes are ineffective in preventing readmission. The observed absence of an association between discharge documentation and readmission indicates that discharge quality improvement initiatives should target metrics of discharge process quality beyond improving rates of documentation.

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.

National quality campaigns: who benefits?

BACKGROUND: The use of national quality campaigns to foster evidence-based hospital practices is increasing. Because campaigns typically do not limit access to their resources, they may influence non-enrolled hospitals as well. OBJECTIVE: To examine the relative impact of a national campaign, the Door-to-Balloon (D2B) Alliance, on enrolled and non-enrolled hospitals. METHODS: In this prospective cohort study, we compared the use of D2B Alliance resources (eg, webinars, online community, mentor network), changes in the use of strategies recommended by the D2B Alliance, and perceived impact of the D2B Alliance between hospitals that enrolled in the D2B Alliance (n=264) and hospitals that declined enrolment (n=101). RESULTS: More than half (53.2%) of non-enrolled hospitals reported using at least some of the resources made available by the D2B Alliance to improve door-to-balloon times. This compared with 83.5% of enrolled hospitals reporting that they used D2B Alliance resources (p<0.01). Both enrolled and non-enrolled hospitals significantly increased their use of recommended hospital strategies between 2005 and 2008, although the use of strategies remained incomplete (35.5-91.5% use). There was no significant difference between the use of these strategies between enrolled and non-enrolled hospitals at follow-up (p > or = 0.51), adjusted for baseline use. About half of all hospitals reported that door-to-balloon times would have been worse at their hospital without the existence of the D2B Alliance. CONCLUSIONS: This research suggests that national quality campaigns with open access to campaign resources may have substantial spillover effects on non-enrolled hospitals.