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Patient-reported outcome measures (PROMs) have great promise, but evidence of success is mixed. This study uses data from Dartmouth-Hitchcock Medical Center and Kaiser-Permanente Colorado to evaluate providing PROMs directly to the primary care physician. We compared changes over time in urinary incontinence, falls, and mental and physical health between clinics providing augmented PROMs (N = 202 patients) and control clinics (N = 102 patients). Both the control and treatment groups exhibited improvements, but there was no significant difference in outcomes over time. These results suggest that measuring and printing out PROMs for primary care physicians will not result in better patient outcomes without physician clinical engagement.

Large scale collection and analysis of data on patients’ experiences and outcomes have become staples of successful health systems worldwide. The systems go by various names—including registries, quality registries, clinical databases, clinical audits, and quality improvement programmes—but all collect standardised information on patients’ diagnoses, care processes, and outcomes, enabling systematic comparison and analysis across multiple sites. Hundreds of what we will term, for simplicity, “registries,” now exist around the world. The United Kingdom is home to over 50 clinical audit programmes, the United States has over 110 federally qualified registries certified to report quality metrics, and Sweden, perhaps the registry epicentre, has over 100, covering conditions from birth to frail old age. These registries have had far reaching effects. They facilitate public reporting, retrospective and prospective research, professional development, and service improvement. They reveal variations in practices, processes, and outcomes, and identify targets for improvement. In the UK, they have been associated with many notable successes, including improvements in management of cardiovascular disease and stroke, cancer, and joint replacement.

It is widely hoped that accountable care organizations (ACOs) will improve health care quality and reduce costs by fostering integration among diverse provider groups. But how do implementers actually envision integration, and what will integration mean in terms of managing the many social identities that ACOs bring together?Using the lens of the social identity approach, this qualitative study examined how four nascent ACOs engaged with the concept of integration. During multiday site visits, we conducted interviews (114 managers and physicians), observations, and document reviews.In no case was the ACO interpreted as a new, overarching entity uniting disparate groups; rather, each site offered a unique interpretation that flowed from its existing strategies for social-identity management: An independent practice association preserved members' cherished value of autonomy by emphasizing coordination, not "integration"; a medical group promoted integration within its employed core, but not with affiliates; a hospital, engaging community physicians who mistrusted integrated systems, reimagined integration as an equal partnership; an integrated delivery system advanced its careful journey towards intergroup consensus by presenting the ACO as a cultural, not structural, change.The ACO appears to be a model flexible enough to work in synchrony with whatever social strategies are most context appropriate, with the potential to promote alignment and functional integration without demanding common identification with a superordinate group. "Soft integration" may be a promising alternative to the vertically integrated model that, though widely assumed to be ideal, has remained unattainable for most organizations.

External groups requiring measures now include public and private payers, regulators, accreditors and others that certify performance levels for consumers, patients and payers. Although benefits have accrued from the growth in quality measurement, the recent explosion in the number of measures threatens to shift resources from improving quality to cover a plethora of quality-performance metrics that may have a limited impact on the things that patients and payers want and need (ie, better outcomes, better care, and lower per capita costs). Here we propose a policy that quality measurement should be: balanced to meet the need of end users to judge quality and cost performance and the need of providers to continuously improve the quality, outcomes and costs of their services; and parsimonious to measure quality, outcomes and costs with appropriate metrics that are selected based on end-user needs.

BACKGROUND Bringing new therapies to patients with rare diseases depends in part on optimizing clinical trial conduct through efficient study start-up processes and rapid enrollment. Suboptimal execution of clinical trials in academic medical centers not only results in high cost to institutions and sponsors, but also delays the availability of new therapies. Addressing the factors that contribute to poor outcomes requires novel, systematic approaches tailored to the institution and disease under study. OBJECTIVE To use clinical trial performance metrics data analysis to select high-performing cystic fibrosis (CF) clinical research teams and then identify factors contributing to their success. DESIGN Mixed-methods research, including semi-structured qualitative interviews of high-performing research teams. PARTICIPANTS CF research teams at nine clinical centers from the CF Foundation Therapeutics Development Network. APPROACH Survey of site characteristics, direct observation of team meetings and facilities, and semi-structured interviews with clinical research team members and institutional program managers and leaders in clinical research. KEY RESULTS Critical success factors noted at all nine high-performing centers were: 1) strong leadership, 2) established and effective communication within the research team and with the clinical care team, and 3) adequate staff. Other frequent characteristics included a mature culture of research, customer service orientation in interactions with study participants, shared efficient processes, continuous process improvement activities, and a businesslike approach to clinical research. CONCLUSIONS Clinical research metrics allowed identification of high-performing clinical research teams. Site visits identified several critical factors leading to highly successful teams that may help other clinical research teams improve clinical trial performance.