'All my co-workers are good people, but ': collaboration dynamics between frontline workers in rural Uttar Pradesh, India.

Multisectoral collaboration has been identified as a critical component in a wide variety of health and development initiatives. For India's Integrated Child Development Services (ICDS) scheme, which serves >100 million people annually across more than one million villages, a key point of multisectoral collaboration-or 'convergence', as it is often called in India-is between the three frontline worker cadres jointly responsible for delivering essential maternal and child health and nutritional services throughout the country: the Accredited Social Health Activist (ASHA), Anganwadi worker (AWW) and auxiliary nurse midwife (ANM) or 'AAA' workers. Despite the long-recognized importance of collaboration within this triad, there has been relatively little documentation of what this looks like in practice and what is needed in order to improve it. Informed by a conceptual framework of collaborative governance, this study applies inductive thematic analysis of in-depth interviews with 18 AAA workers and 6 medical officers from 6 villages across three administrative blocks in Hardoi district of Uttar Pradesh state to identify the key elements of collaboration. These are grouped into three broad categories: 'organizational' (including interdependence, role clarity, guidance/support and resource availability); 'relational' (interpersonal and conflict resolution) and 'personal' (flexibility, diligence and locus of control). These findings underscore the importance of 'personal' and 'relational' collaboration features, which are underemphasized in India's ICDS, the largest of its kind globally, and in the multisectoral collaboration literature more broadly-both of which place greater emphasis on 'organizational' aspects of collaboration. These findings are largely consistent with prior studies but are notably different in that they highlight the importance of flexibility, locus of control and conflict resolution in collaborative relationships, all of which relate to one's ability to adapt to unexpected obstacles and find mutually workable solutions with colleagues. From a policy perspective, supporting these key elements of collaboration may involve giving frontline workers more autonomy in how they get the work done, which may in some cases be impeded by additional training to reinforce worker role delineation, closer monitoring or other top-down efforts to push greater convergence. Given the essential role that frontline workers play in multisectoral initiatives in India and around the world, there is a clear need for policymakers and managers to understand the elements affecting collaboration between these workers when designing and implementing programmes.

Multilevel Interventions To Address Health Disparities Show Promise In Improving Population Health.

Multilevel interventions are those that affect at least two levels of influence-for example, the patient and the health care provider. They can be experimental designs or natural experiments caused by changes in policy, such as the implementation of the Affordable Care Act or local policies. Measuring the effects of multilevel interventions is challenging, because they allow for interaction among levels, and the impact of each intervention must be assessed and translated into practice. We discuss how two projects from the National Institutes of Health's Centers for Population Health and Health Disparities used multilevel interventions to reduce health disparities. The interventions, which focused on the uptake of the human papillomavirus vaccine and community-level dietary change, had mixed results. The design and implementation of multilevel interventions are facilitated by input from the community, and more advanced methods and measures are needed to evaluate the impact of the various levels and components of such interventions.

A matched-pair cluster-randomized trial of guided care for high-risk older patients.

BACKGROUND: Patients at risk for generating high health care expenditures often receive fragmented, low-quality, inefficient health care. Guided Care is designed to provide proactive, coordinated, comprehensive care for such patients. OBJECTIVE: We hypothesized that Guided Care, compared to usual care, produces better functional health and quality of care, while reducing the use of expensive health services. DESIGN: 32-month, single-blind, matched-pair, cluster-randomized controlled trial of Guided Care, conducted in eight community-based primary care practices. PATIENTS: The "Hierarchical Condition Category" (HCC) predictive model was used to identify high-risk older patients who were insured by fee-for-service Medicare, a Medicare Advantage plan or Tricare. Patients with HCC scores in the highest quartile (at risk for generating high health care expenditures during the coming year) were eligible to participate. INTERVENTION: A registered nurse collaborated with two to five primary care physicians in providing eight services to participants: comprehensive assessment, evidence-based care planning, proactive monitoring, care coordination, transitional care, coaching for self-management, caregiver support, and access to community-based services. MAIN MEASURES: Functional health was measured using the Short Form-36. Quality of care and health services utilization were measured using the Patient Assessment of Chronic Illness Care and health insurance claims, respectively. KEY RESULTS: Of the eligible patients, 904 (37.8 %) gave written consent to participate; of these, 477 (52.8 %) completed the final interview, and 848 (93.8 %) provided complete claims data. In intention-to-treat analyses, Guided Care did not significantly improve participants' functional health, but it was associated with significantly higher participant ratings of the quality of care (difference = 0.27, 95 % CI = 0.08-0.45) and 29 % lower use of home care (95 % CI = 3-48 %). CONCLUSIONS: Guided Care improves high-risk older patients' ratings of the quality of their care, and it reduces their use of home care, but it does not appear to improve their functional health.

The team checkup tool: evaluating QI team activities and giving feedback to senior leaders.

This tool can close the gap between hospital executives and frontline QI teams, improve knowledge of team activities, and help teams to identify and remedy barriers to progress.