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Background: Primary care practices are responding to calls to incorporate patients' social risk factors, such as housing, food, and economic insecurity, into clinical care. Healthcare likely relies on the expertise and resources of community-based organizations to improve patients' social conditions, yet little is known about the referral process.Objective: To characterize referrals to community-based organizations by primary care practices.Design: Qualitative study using semi-structured interviews with healthcare administrators responsible for social care efforts in their organization.Participants: Administrators at 50 diverse US healthcare organizations with efforts to address patients' social risks.Main Measures: Approaches used in primary care to implement social needs referral to community-based organizations.Results: Interviewed administrators reported that social needs referrals were an essential element in their social care activities. Administrators described the ideal referral programs as placing limited burden on care teams, providing patients with customized referrals, and facilitating closed-loop referrals. We identified three key challenges organizations experience when trying to implement the ideal referrals program: (1) developing and maintaining resources lists; (2) aligning referrals with patient needs; and (3) measuring the efficacy of referrals. Collectively, these challenges led to organizations relying on staff to manually develop and update resource lists and, in most cases, provide patients with generic referrals. Administrators not only hoped that referral platforms may help overcome some of these barriers, but also reported implementation challenges with platforms including inconsistent buy-in and use across staff; integration with electronic health records; management and prioritization of resources; and alignment with other organizations in their market.Conclusion and Relevance: Referrals to community-based organizations were used in primary care to improve patients' social conditions, but despite strong motivations, interviewees reported challenges providing tailored and up-to-date information to patients. [ABSTRACT FROM AUTHOR]

Racial-ethnic minorities receive lower quality and intensity of health care compared with whites across a wide range of preventive, diagnostic, and therapeutic services and disease entities. These disparities in health care contribute to continuing racial-ethnic disparities in the burden of illness and death. Several national medical organizations and the Institute of Medicine have issued position papers and recommendations for the elimination of health care disparities. However, physicians in practice are often at a loss for how to translate these principles and recommendations into specific interventions in their own clinical practices. This paper serves as a blueprint for translating principles for the elimination of racial-ethnic disparities in health care into specific actions that are relevant for individual clinical practices. We describe what is known about reducing racial-ethnic disparities in clinical practice and make recommendations for how clinician leaders can apply this evidence to transform their own practices. [ABSTRACT FROM AUTHOR]

Objectives: The objective of this paper was to describe primary care prescribers' perspectives on electronic prescribing drug alerts at the point of prescribing.Design: We used a mixed-method study which included clinician surveys (web-based and paper) and focus groups with prescribers and staff.Participants: Prescribers (n = 157) working in one of 64 practices using 1 of 6 e-prescribing technologies in 6 US states completed the quantitative survey and 276 prescribers and staff participated in focus groups.Measurements: The study measures self-reported frequency of overriding of drug alerts; open-ended responses to: "What do you think of the drug alerts your software generates for you?"Results: More than 40% of prescribers indicated they override drug-drug interactions most of the time or always (range by e-prescribing system, 25% to 50%). Participants indicated that the software and the interaction alerts were beneficial to patient safety and valued seeing drug-drug interactions for medications prescribed by others. However, they noted that alerts are too sensitive and often unnecessary. Participant suggestions included: (1) run drug alerts on an active medication list and (2) allow prescribers to set the threshold for severity of alerts.Conclusions: Primary care prescribers recognize the patient safety value of drug prescribing alerts embedded within electronic prescribing software. Improvements to increase specificity and reduce alert overload are needed. [ABSTRACT FROM AUTHOR]

Background: Patient complexity is often operationalized by counting multiple chronic conditions (MCC) without considering contextual factors that can affect patient risk for adverse outcomes.Objective: Our objective was to develop a conceptual model of complexity addressing gaps identified in a review of published conceptual models.Data Sources: We searched for English-language MEDLINE papers published between 1 January 2004 and 16 January 2014. Two reviewers independently evaluated abstracts and all authors contributed to the development of the conceptual model in an iterative process.Results: From 1606 identified abstracts, six conceptual models were selected. One additional model was identified through reference review. Each model had strengths, but several constructs were not fully considered: 1) contextual factors; 2) dynamics of complexity; 3) patients' preferences; 4) acute health shocks; and 5) resilience. Our Cycle of Complexity model illustrates relationships between acute shocks and medical events, healthcare access and utilization, workload and capacity, and patient preferences in the context of interpersonal, organizational, and community factors.Conclusions/implications: This model may inform studies on the etiology of and changes in complexity, the relationship between complexity and patient outcomes, and intervention development to improve modifiable elements of complex patients. [ABSTRACT FROM AUTHOR]

Personal autonomy is widely valued. Recognition of its vulnerability in health care contexts led to the inclusion of respect for autonomy as a key concern in biomedical ethics. The principle of respect for autonomy is usually associated with allowing or enabling patients to make their own decisions about which health care interventions they will or will not receive. In this paper, we suggest that a strong focus on decision situations is problematic, especially when combined with a tendency to stress the importance of patients' independence in choosing. It distracts attention from other important aspects of and challenges to autonomy in health care. Relational understandings of autonomy attempt to explain both the positive and negative implications of social relationships for individuals' autonomy. They suggest that many health care practices can affect autonomy by virtue of their effects not only on patients' treatment preferences and choices, but also on their self-identities, self-evaluations and capabilities for autonomy. Relational understandings de-emphasise independence and facilitate well-nuanced distinctions between forms of clinical communication that support and that undermine patients' autonomy. These understandings support recognition of the value of good patient-professional relationships and can enrich the specification of the principle of respect for autonomy. [ABSTRACT FROM AUTHOR]

Background: Failed referrals for specialty care are common and often represent medical errors. Technological structures and processes account for many failures. Scheduling appointments for subspecialty evaluation is a first step in outpatient referral and consultation.Objective: We determined whether moving from paper-based referrals to a Web-based system with automated tracking features was associated with greater scheduling of appointments among referred patients.Design: Staggered implementation of a quality-improvement project, with comparison of intervention and control groups.Participants: Patients 21 or more years of age referred from any of 11 primary-care clinics to any of 25 specialty clinics.Interventions: Faxed referrals were replaced by a Web-based application shared by generalists and specialists, with enhanced communications and automated notification to the specialty office.Measurements: We compared scheduling before and after implementation and time from referral to appointment. A logistic regression analysis adjusted for demographics.Main Results: Among 40,487 referrals, 54% led to scheduled specialty visits before intervention, compared to 83% with intervention. The median time to appointment was 168 days without intervention and 78 days with intervention. Scheduling increased more when duplicate referrals were not generated (54% for single orders, 24% for multiple orders). After adjustment, referrals with the intervention were more than twice as likely to have scheduled visits.Conclusions: With a new Web-based referrals system, referrals were more than twice as likely to lead to a scheduled visit. This system improves access to specialty medical services. [ABSTRACT FROM AUTHOR]