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ObjectiveDisagreement exists between rheumatology and primary care societies regarding gout management. This paper describes a formal process for gathering input from stakeholders in the planning of a trial to compare gout management strategies.MethodsWe recruited patients, nurses, physician assistants, primary care clinicians, and rheumatologists to participate in a modified Delphi panel (mDP) to provide input on design of a trial focused on optimal management for primary care patients with gout. The 16 panelists received a plain-language briefing document that discussed the rationale for the trial, key clinical issues in gout, and aspects of trial design. The panelists also received information and considerations on nine voting questions (VQs), judged to be the key design questions. Cognitive interviews with panelists ensured that the VQs were understood by the range of panelists involved in the mDP. Panelists were asked to score all VQs from 1 (definitely no) to 9 (definitely yes). Two voting rounds were conducted-round 1 by email and round 2 by video conference.ResultsThe VQs were modified through the cognitive interviews. The round 1 voting resulted in consensus on eight items, with consensus defined as median voting score in the same tercile (1-3, 4-6 or 7-9). Re-voting at the meeting (round 2) reached consensus on the remaining item.ConclusionAn mDP with various stakeholders facilitated consensus on the design of a trial of different management strategies for chronic gout. This method may be useful for designing trials of clinical questions with substantial disagreement across stakeholders.

Objective: To identify organizational service features associated with positive patient ratings of primary care within primary care clinics tailored to accommodate persons with ongoing and recent experiences of homelessness (PEH). Data Sources and Study Setting: PEH receiving primary care in 29 United States Veterans Health Administration homeless‐tailored clinics were surveyed about their primary care experience using the validated Primary Care Quality‐Homeless (PCQ‐H) survey. Characteristics of the clinics were assessed through surveys of clinic staff using a new organizational survey developed through literature review, site visits, statistical analysis, and consensus deliberation. Study Design: Cross‐sectional examination of patients' ratings of care based on surveys of patients, and of clinic characteristics, analyzed with Classification and Regression Tree (CART) analysis, a form of machine learning. Data Collection Methods: Patient surveys (n = 3394) were obtained from a random sample of enrolled patients by both mail and telephone by an external survey contractor. Staff (n = 52 from 29 clinics) were interviewed by telephone. Principal Findings: This analysis identified service features that impact patient experience favorably, including aspects of patient‐centeredness, team identity, strong external leadership support, and service that reach beyond traditional primary care clinic confines. Results varied according to the patient experience scale analyzed. Individual characteristics of PEH, such as degree of social support, general health, and unsheltered status, were also correlated with how they rate care. Conclusions: Organizational characteristics correlate with ratings of primary care from patients with recent and ongoing homelessness. Primary care programs serving homeless individuals can assure better care based on who they hire, how they foster team identity, what services they provide, and the strength of leadership support to protect a homeless‐focused mission. [ABSTRACT FROM AUTHOR]

OBJECTIVES: Continuity of care measures are widely used to evaluate the quality of health care delivery, but which visits are included vary across studies. Our objective was to determine how the provider specialties included affect continuity values, year-to-year stability, and association with emergency department (ED) visits. STUDY DESIGN: Retrospective study of Alabama Medicaid administrative data. METHODS: We included beneficiaries with diabetes who had at least 3 outpatient visits in each of 2018 and 2019 (N = 9578). We defined 3 provider groupings: all providers, diabetes-broad (primary care, cardiology, neurology, endocrinology, ophthalmology, nephrology, and psychiatry), and diabetes-narrow (primary care and endocrinology). Continuity of care was calculated using the Continuity of Care Index (COCI) for each provider grouping. We compared correlation between measures and from year to year using Spearman correlations, and we used multivariable logistic regression to determine association with ED visits. RESULTS: The mean COCI was 0.54 using visits with all providers, 0.64 with diabetes-broad providers, and 0.83 with diabetes-narrow providers. COCI with diabetes-narrow providers was moderately correlated with the broader sets of providers (Spearman ρ, 0.52-0.65). Comparing each participant's COCI in 2018 with that in 2019, the mean intraperson difference was similar (0.16-0.22), and correlation was moderate (Spearman ρ, 0.41-0.47) for each measure. COCI had similar weak association with ED visits using each provider grouping (odds ratio, 0.99; 95% CI, 0.98-0.99 for each 0.1-unit difference in COCI). CONCLUSIONS: Continuity values differed substantially depending on which provider specialties were included. The importance of this variation is uncertain, as continuity was weakly associated with ED visits using each of the measures. [ABSTRACT FROM AUTHOR]

Objective: To describe patterns of care use for adult Medicaid beneficiaries with diabetes and the association between primary care utilization and Ambulatory Care Sensitive (ACS) diabetes hospitalizations. Methods: This retrospective cohort study analyzes Alabama Medicaid claims data from January 2010 to April 2018 for 52,549 covered adults ages 19 to 64 with diabetes. Individuals were characterized by demographics, comorbidities, and health care use including primary, specialty, mental health, pharmaceutical, laboratory and hospital care. Characteristics of those with and without any ACS diabetes hospitalization are reported. A set of 118,758 observations was created, pairing information on primary care use in one year with ACS hospitalizations in the following year. Logistic regression analysis was used to assess the impact of primary care use in one year on the occurrence of an ACS hospitalization in the following year. Results: One third of the cohort had at least one ACS diabetes hospitalization over their observed periods; hospital users tended to have multiple ACS hospitalizations. Hospital users had more comorbidities and pharmaceutical and other types of care use than those with no ACS hospitalizations. Controlling for other types of care use, comorbidities and demographics, having a primary care visit in one year was significantly associated with a reduced likelihood of ACS hospitalization in the following year (adjusted odds ratio comparing 1-2 primary care visits versus none 0.79, 95% confidence interval 0.73-0.85). Conclusions: Program and population health interventions that increase access to primary care can have a beneficial effect of reducing excess inpatient hospital use for Medicaid covered adults with diabetes. Disclosure: J.M. Bronstein: None. L. Huang: None. A.A. Agne: None. F.L. Mondesir: None. C.A. Presley: None. K.R. Riggs: None. M. Pisu: None. E.B. Levitan: Consultant; Self; Novartis Pharmaceuticals Corporation. Research Support; Self; Amgen Inc. A. Cherrington: None. Funding: National Institute of Diabetes and Digestive and Kidney Diseases [ABSTRACT FROM AUTHOR]