Justin K. Benzer

The Relationship between Organizational Climate and Quality of Chronic Disease Management

OBJECTIVE To test the utility of a two-dimensional model of organizational climate for explaining variation in diabetes care between primary care clinics. DATA SOURCES/STUDY SETTING Secondary data were obtained from 223 primary care clinics in the Department of Veterans Affairs health care system. STUDY DESIGN Organizational climate was defined using the dimensions of task and relational climate. The association between primary care organizational climate and diabetes processes and intermediate outcomes were estimated for 4,539 patients in a cross-sectional study. DATA COLLECTION/EXTRACTION METHODS All data were collected from administrative datasets. The climate data were drawn from the 2007 VA All Employee Survey, and the outcomes data were collected as part of the VA External Peer Review Program. Climate data were aggregated to the facility level of analysis and merged with patient-level data. PRINCIPAL FINDINGS Relational climate was related to an increased likelihood of diabetes care process adherence, with significant but small effects for adherence to intermediate outcomes. Task climate was generally not shown to be related to adherence. CONCLUSIONS The role of relational climate in predicting the quality of chronic care was supported. Future research should examine the mediators and moderators of relational climate and further investigate task climate.

Provider workload and quality of care in primary care settings: moderating role of relational climate.

Primary care providers are increasingly under pressure to do more with fewer resources. We examined the effect of workload on patients’ experiences of quality of care, measured through approximately 44,000 patient experience surveys in a sample of 222 primary care clinics in the Veterans Health Administration. We tested the extent to which relational climate, a measure of teamwork, moderated the relationship between workload and patient ratings of quality of care. Our outcome measures included patient complaints, time spent with provider, and overall visit quality. Workload was negatively associated with patients’ quality of care ratings and relational climate moderated the relation between workload and quality of care ratings. Patients seen in clinics with higher workload and greater relational climate reported better care compared with patients in clinics with higher workload but lower relational climate. Findings highlight the importance of relational climate as an important teamwork factor when managing and developing clinic policies, practices, and procedures in resource-constrained settings.

Grounded Theory of Barriers and Facilitators to Mandated Implementation of Mental Health Care in the Primary Care Setting

Objective. There is limited theory regarding the real-world implementation of mental health care in the primary care setting: a type of organizational coordination intervention. The purpose of this study was to develop a theory to conceptualize the potential causes of barriers and facilitators to how local sites responded to this mandated intervention to achieve coordinated mental health care. Methods. Data from 65 primary care and mental health staff interviews across 16 sites were analyzed to identify how coordination was perceived one year after an organizational mandate to provide integrated mental health care in the primary care setting. Results. Standardized referral procedures and communication practices between primary care and mental health were influenced by the organizational factors of resources, training, and work design, as well as provider-experienced organizational boundaries between primary care and mental health, time pressures, and staff participation. Organizational factors and provider experiences were in turn influenced by leadership. Conclusions. Our emergent theory describes how leadership, organizational factors, and provider experiences affect the implementation of a mandated mental health coordination intervention. This framework provides a nuanced understanding of the potential barriers and facilitators to implementing interventions designed to improve coordination between professional groups.

Multilevel Interventions: Measurement and Measures

BACKGROUND Multilevel intervention research holds the promise of more accurately representing real-life situations and, thus, with proper research design and measurement approaches, facilitating effective and efficient resolution of health-care system challenges. However, taking a multilevel approach to cancer care interventions creates both measurement challenges and opportunities. METHODS One-thousand seventy two cancer care articles from 2005 to 2010 were reviewed to examine the state of measurement in the multilevel intervention cancer care literature. Ultimately, 234 multilevel articles, 40 involving cancer care interventions, were identified. Additionally, literature from health services, social psychology, and organizational behavior was reviewed to identify measures that might be useful in multilevel intervention research. RESULTS The vast majority of measures used in multilevel cancer intervention studies were individual level measures. Group-, organization-, and community-level measures were rarely used. Discussion of the independence, validity, and reliability of measures was scant. DISCUSSION Measurement issues may be especially complex when conducting multilevel intervention research. Measurement considerations that are associated with multilevel intervention research include those related to independence, reliability, validity, sample size, and power. Furthermore, multilevel intervention research requires identification of key constructs and measures by level and consideration of interactions within and across levels. Thus, multilevel intervention research benefits from thoughtful theory-driven planning and design, an interdisciplinary approach, and mixed methods measurement and analysis.

Sustainability of quality improvement following removal of pay-for-performance incentives.

ABSTRACTBACKGROUNDAlthough pay-for-performance (P4P) has become a central strategy for improving quality in US healthcare, questions persist about the effectiveness of these programs. A key question is whether quality improvement that occurs as a result of P4P programs is sustainable, particularly if incentives are removed.OBJECTIVETo investigate sustainability of performance levels following removal of performance-based incentives.DESIGN, SETTING, AND PARTICIPANTSObservational cohort study that capitalized on a P4P program within the Veterans Health Administration (VA) that included adoption and subsequent removal of performance-based incentives for selected inpatient quality measures. The study sample comprised 128 acute care VA hospitals where performance was assessed between 2004 and 2010.INTERVENTIONVA system managers set annual performance goals in consultation with clinical leaders, and report performance scores to medical centers on a quarterly basis. These scores inform performance-based incentives for facilities and their managers. Bonuses are distributed based on the attainment of these performance goals.MEASUREMENTSSeven quality of care measures for acute coronary syndrome, heart failure, and pneumonia linked to performance-based incentives.RESULTSSignificant improvements in performance were observed for six of seven quality of care measures following adoption of performance-based incentives and were maintained up to the removal of the incentive; subsequently, the observed performance levels were sustained.LIMITATIONSThis is a quasi-experimental study without a comparison group; causal conclusions are limited.CONCLUSIONThe maintenance of performance levels after removal of a performance-based incentive has implications for the implementation of Medicare’s value-based purchasing initiative and other P4P programs. Additional research is needed to better understand human and system-level factors that mediate sustainability of performance-based incentives.

Nurse practitioner and physician assistant scope of practice in 118 acute care hospitals

BACKGROUND Advanced practice providers (APPs), including nurse practitioners (NPs) and physician assistants (PAs) are cost-effective substitutes for physicians, with similar outcomes in primary care and surgery. However, little is understood about APP roles in inpatient medicine. OBJECTIVE Describe APPs role in inpatient medicine. DESIGN Observational cross-sectional cohort study. SETTING One hundred twenty-four Veterans Health Administration (VHA) hospitals. PARTICIPANTS Chiefs of medicine (COMs) and nurse managers. MEASUREMENTS Surveys included inpatient medicine scope of practice for APPs and perceived healthcare quality. We conducted bivariate unadjusted and multivariable adjusted analyses. RESULTS One hundred eighteen COMs (95.2%) and 198 nurse managers (75.0%) completed surveys. Of 118 medicine services, 56 (47.5%) employed APPs; 27 (48.2%) used NPs only, 15 (26.8%) PAs only, and 14 (25.0%) used both. Full-time equivalents for NPs was 0.5 to 7 (mean = 2.22) and PAs was 1 to 9 (mean = 2.23). Daily caseload was similar at 4 to 10 patients (mean = 6.5 patients). There were few significant differences between tasks. The presence of APPs was not associated with patient or nurse manager satisfaction. Presence of NPs was associated with greater overall inpatient and discharge coordination ratings by COMs and nurse managers, respectively; the presence of PAs was associated with lower overall inpatient coordination ratings by nurse managers. CONCLUSIONS NPs and PAs work on half of VHA inpatient medicine services with broad, yet similar, scopes of practice. There were few differences between their roles and perceptions of care. Given their very different background, regulation, and reimbursement, this has implications for inpatient medicine services that plan to hire NPs or PAs.

Between and within-site variation in qualitative implementation research

BackgroundMultisite qualitative studies are challenging in part because decisions regarding within-site and between-site sampling must be made to reduce the complexity of data collection, but these decisions may have serious implications for analyses. There is not yet consensus on how to account for within-site and between-site variations in qualitative perceptions of the organizational context of interventions. The purpose of this study was to analyze variation in perceptions among key informants in order to demonstrate the importance of broad sampling for identifying both within-site and between-site implementation themes.MethodsCase studies of four sites were compared to identify differences in how Department of Veterans Affairs (VA) medical centers implemented a Primary Care/Mental Health Integration (PC/MHI) intervention. Qualitative analyses focused on between-profession variation in reported referral and implementation processes within and between sites.ResultsKey informants identified co-location, the consultation-liaison service, space, access, and referral processes as important topics. Within-site themes revealed the importance of coordination, communication, and collaboration for implementing PC/MHI. The between-site theme indicated that the preexisting structure of mental healthcare influenced how PC/MHI was implemented at each site and that collaboration among both leaders and providers was critical to overcoming structural barriers.ConclusionsWithin- and between-site variation in perceptions among key informants within different professions revealed barriers and facilitators to the implementation not available from a single source. Examples provide insight into implementation barriers for PC/MHI. Multisite implementation studies may benefit from intentionally eliciting and analyzing variation within and between sites. Suggestions for implementation research design are presented.

Accounting for Variation in Technical Quality and Patient Satisfaction The Contribution of Patient, Provider, Team, and Medical Center

Background:The delivery of healthcare depends on individual providers, coordination within teams, and the structure of the work setting. We analyzed the amount of variation in technical quality and patient satisfaction accounted for at the patient, provider, team, and medical center level. Methods:Data abstracted from Veterans Health Administration patient medical records for 2007 were used to calculate measures of technical quality based on adherence to best practice guidelines in 5 domains. Outpatient satisfaction was obtained from a 2007 standardized national mail survey. Hierarchical linear models that accounted for the clustering of patients within providers, providers within teams, and teams within medical centers were used to partition the variation in technical quality and satisfaction across patients and components of the system (ie, providers, teams, and medical centers). Results:Providers accounted for the largest percent of system-level variance for all technical quality domains, ranging from 46.5% to 71.9%. For the single-item measure of patient satisfaction, medical centers, teams, and providers accounted for about the same percent of system-level variance (31%–34%). For the doctor/patient interaction scale providers explained 59.9% of system-level variance, more than double that of teams and medical centers. For all the measures, the residual variance (composed of patient-level and random error) explained the largest proportion of the total variance. Conclusions:Providers explained the greatest amount of system-level variation in technical quality and patient satisfaction. However, in both of these domains, differences between patients were the predominant source of nonrandom variance.

Impact of Coping Style and PTSD on Family Functioning After Deployment in Operation Desert Shield/Storm Returnees

The relationship between military combat and postdeployment family functioning difficulties has been frequently investigated in the literature, as has the relationship between types of coping and posttraumatic stress disorder (PTSD). Few studies, however, have examined these variables together, and no studies of which we are aware have examined the effect of coping on family functioning after combat exposure. This study examined coping style measured immediately after return from deployment, and PTSD symptoms and family functioning 18-24 months after return from deployment in a sample of Operation Desert Shield/Storm veterans (N = 2,949). Structural equation models suggested that the relationships between distinct coping styles on family functioning were differentially mediated by postdeployment PTSD symptoms. Results are consistent with full mediation for avoidant coping (βdirect = -.09, p = .07; βindirect = -.17, p < .001) and partial mediation for approach coping (βdirect = .16, p < .001; βindirect = .09, p < .001). Results suggest that the strategies used to cope with a combat stress event may impact both PTSD and family functioning outcomes, and highlight the potential utility of pre- and postdeployment coping skills training.

One-Year Cost Implications of Using Mental Health Care After Discharge From a General Medical Hospitalization

OBJECTIVE The purpose of this study was to direct attention to mental health issues that may occur around discharge of patients hospitalized for general medical issues. This study provides a methodology and tested whether postdischarge mental health care moderates the effect of the length of the medical inpatient stay on costs one year later. METHODS Veterans Health Administration administrative data were drawn from four time periods: one year before admission, an inpatient stay, 30 days postdischarge, and the year after discharge. The cohort included 21,716 patients actively engaged in primary care with and without reliably established mental health diagnoses and who were hospitalized for a general medical issue but had no inpatient utilization in the prior year. Generalized linear models were estimated to determine the impact of administrative measures on postdischarge costs. RESULTS Postdischarge mental health care in the 30 days after discharge was found to interact with length of stay, as hypothesized. Postdischarge mental health care was most important for patients with moderate utilization costs in the year after discharge (a proxy for disease severity). Length of stay was negatively related to costs for patients with postdischarge mental health care and positively related to costs for patients with mental health diagnoses who did not receive postdischarge mental health care. CONCLUSIONS Results provide initial support to the hypothesis that postdischarge mental health care is an important factor after inpatient general medical care. Results suggest that hospitals should screen all general medical patients for psychiatric problems and ensure that postdischarge mental health care is available. Implications for future research on mental health in primary care and possibly preventable readmission are discussed.