Identification of outliers and positive deviants for healthcare improvement: looking for high performers in hypoglycemia safety in patients with diabetes

Abstract Background The study objectives were to determine: (1) how statistical outliers exhibiting low rates of diabetes overtreatment performed on a reciprocal measure – rates of diabetes undertreatment; and (2) the impact of different criteria on high performing outlier status. Methods The design was serial cross-sectional, using yearly Veterans Health Administration (VHA) administrative data (2009–2013). Our primary outcome measure was facility rate of HbA1c overtreatment of diabetes in patients at risk for hypoglycemia. Outlier status was assessed by using two approaches: calculating a facility outlier value within year, comparator group, and A1c threshold while incorporating at risk population sizes; and examining standardized model residuals across year and A1c threshold. Facilities with outlier values in the lowest decile for all years of data using more than one threshold and comparator or with time-averaged model residuals in the lowest decile for all A1c thresholds were considered high performing outliers. Results Using outlier values, three of the 27 high performers from 2009 were also identified in 2010–2013 and considered outliers. There was only modest overlap between facilities identified as top performers based on three thresholds: A1c  9%) than VA average in the population of patients at high risk for hypoglycemia. Conclusions Statistical identification of positive deviants for diabetes overtreatment was dependent upon the specific measures and approaches used. Moreover, because two facilities may arrive at the same results via very different pathways, it is important to consider that a “best” practice may actually reflect a separate “worst” practice

State-Level Variability in Veteran Reliance on Veterans Health Administration and Potentially Preventable Hospitalizations: A Geospatial Analysis

Most Veterans who use the Veterans Health Administration (VHA) also utilize private-sector health care providers. To better inform local and regional health care planning, we assessed the association between reliance on VHA ambulatory care and total and system-specific preventable hospitalization rates (PHRs) at the state level. We conducted a retrospective dynamic cohort study using Veterans with diabetes mellitus, aged 66 years or older, and dually enrolled in VHA and Medicare parts A and B from 2004 to 2010. While controlling for median age and proportion of males, we measured the association between reliance on VHA ambulatory care and PHRs at the state level using multivariable ordinary least square regression, geographically weighted regression, and generalized additive models. We measured geospatial patterns in PHRs using global Moran’s I and univariate local indicator spatial analysis. Approximately 30% of hospitalized Veterans experienced a preventable hospitalization. Reliance on VHA ambulatory care at the state level ranged from 13.92% to 67.78% and was generally not associated with PHRs. Geospatial analysis consistently identified a cluster of western states with low PHRs from 2006 to 2010. Given the generally low reliance on VHA ambulatory care and lack of association between this reliance and PHRs, policy changes to improve Veterans’ health care outcomes should address private-sector care in addition to VHA care

State-Level Variability in Veteran Reliance on Veterans Health Administration and Potentially Preventable Hospitalizations: A Geospatial Analysis

Most Veterans who use the Veterans Health Administration (VHA) also utilize private-sector health care providers. To better inform local and regional health care planning, we assessed the association between reliance on VHA ambulatory care and total and system-specific preventable hospitalization rates (PHRs) at the state level. We conducted a retrospective dynamic cohort study using Veterans with diabetes mellitus, aged 66 years or older, and dually enrolled in VHA and Medicare parts A and B from 2004 to 2010. While controlling for median age and proportion of males, we measured the association between reliance on VHA ambulatory care and PHRs at the state level using multivariable ordinary least square regression, geographically weighted regression, and generalized additive models. We measured geospatial patterns in PHRs using global Moran’s I and univariate local indicator spatial analysis. Approximately 30% of hospitalized Veterans experienced a preventable hospitalization. Reliance on VHA ambulatory care at the state level ranged from 13.92% to 67.78% and was generally not associated with PHRs. Geospatial analysis consistently identified a cluster of western states with low PHRs from 2006 to 2010. Given the generally low reliance on VHA ambulatory care and lack of association between this reliance and PHRs, policy changes to improve Veterans’ health care outcomes should address private-sector care in addition to VHA care

Recruitment and retention of primary care practices in the Southeastern Collaboration to Improve Blood Pressure Control

Background: Racial disparities related to hypertension prevalence and control persist, with Black persons continuing to have both high prevalence and suboptimal control. The Black Belt region of the US Southeast is characterized by multiple critical priority populations: rural, low-income, and minority (Black). Methods: In a cluster-randomized, controlled, pragmatic implementation trial, the Southeastern Collaboration to Improve Blood Pressure Control evaluated two multi-component, multi-level functional interventions – peer coaching (PC) and practice facilitation (PF) (separately and combined) – as adjuncts to usual care to improve blood pressure control in the Black Belt. The overall goal was to randomize 80 primary care practices (later reduced to 69 practices) in Alabama and North Carolina to one of four interventions: 1) enhanced usual care (EUC); 2) EUC plus PC; 3) EUC plus PF; or 4) EUC plus both PC and PF. Several measures to facilitate recruitment and retention of practices were employed, including practice readiness assessment. Results: Contact was initiated with 248 practices during the study enrollment period. Of these, 99 declined participation, 39 were ineligible, and 41 were being evaluated for inclusion when the target number of practices was reached. The remaining 69 practices eventually were enrolled, with 18 practices randomized to EUC, 19 to PC, 16 to PF, and 16 to PC plus PF. Only two practices (2.9%) were withdrawn during the study. Several facilitators of and barriers to practice recruitment and retention were identified. Conclusion: Our findings underscore the importance of a structured approach to recruiting primary care practices in a pragmatic implementation trial.ClinicalTrials.gov registration number NCT0286666

State-Level Variability in Veteran Reliance on Veterans Health Administration and Potentially Preventable Hospitalizations: A Geospatial Analysis

Most Veterans who use the Veterans Health Administration (VHA) also utilize private-sector health care providers. To better inform local and regional health care planning, we assessed the association between reliance on VHA ambulatory care and total and system-specific preventable hospitalization rates (PHRs) at the state level. We conducted a retrospective dynamic cohort study using Veterans with diabetes mellitus, aged 66 years or older, and dually enrolled in VHA and Medicare parts A and B from 2004 to 2010. While controlling for median age and proportion of males, we measured the association between reliance on VHA ambulatory care and PHRs at the state level using multivariable ordinary least square regression, geographically weighted regression, and generalized additive models. We measured geospatial patterns in PHRs using global Moran’s I and univariate local indicator spatial analysis. Approximately 30% of hospitalized Veterans experienced a preventable hospitalization. Reliance on VHA ambulatory care at the state level ranged from 13.92% to 67.78% and was generally not associated with PHRs. Geospatial analysis consistently identified a cluster of western states with low PHRs from 2006 to 2010. Given the generally low reliance on VHA ambulatory care and lack of association between this reliance and PHRs, policy changes to improve Veterans’ health care outcomes should address private-sector care in addition to VHA care