Association of Serious Hypoglycemic Events in Older Adults With Changes in Glycemic Performance Measures.

BACKGROUND: Reducing serious hypoglycemic events is a Federal-wide objective. Despite studies of trends for rates of serious hypoglycemia in existing literature, rigorous evaluation of links between the observed trends and changes in professional guidelines or performance measures for glycemic control is lacking. OBJECTIVE: To evaluate whether changes in professional society guidelines and performance measures for glycemic control correspond to changes in rates of serous hypoglycemia. RESEARCH DESIGN: This was a retrospective observational study. We merged Veterans Health Administration (VHA) and Medicare patient-level databases of VHA patients and identified those aged 65 years and above and receiving hypoglycemic agents. We derived age-adjusted and sex-adjusted annual rates and constructed piecewise Poisson regression models adjusting for age and sex to assess time trends of the rates. SUBJECTS: VHA patients, 2002-2015. MEASURES: The main outcome was the annual rates (2004-2015) of serious hypoglycemia, defined as hypoglycemia-related emergency department visits or hospitalizations. Secondary outcomes were annual rates of hemoglobin (Hb) A1c level <7% and >9%. Age and sex were additional variables. RESULTS: The annual rate for hypoglycemia decreased by 4.8% (rate ratio: 0.952; 95% confidence interval, 0.949-0.956) for 2008-2015 but did not change (1.001; 0.994-1.001) in 2004-2008. In 2008-2015, the annual rate for HbA1c <7% decreased by 5.0% (0.950; 0.949-0.951) but for HbA1c >9%, increased by 7.9% (1.079; 1.076-1.082). CONCLUSION: The cooccurrence of decreasing rates for HbA1c<7% and serious hypoglycemia since 2008 supports the possibility that withdrawal of a <7% HbA1c measure in 2008 impacted clinical practice and patient outcomes.

Balancing measures: identifying unintended consequences of diabetes quality performance measures in patients at high risk for hypoglycemia.

OBJECTIVE: To determine if changes in overtreatment rates were associated with changes in undertreatment rates. DESIGN: Pre-test/post-test study used cross-sectional administrative data from calendar years (CYs) 2013 and 2016. SETTING: The Veterans Health Administration. PARTICIPANTS: Patients with diabetes at risk for hypoglycemia (n = 171 875 and 166 703 in 2013 and 2016, respectively). INTERVENTION: Observational study of extant initiatives to reduce overtreatment. MAIN OUTCOME MEASURES: Overtreatment rate of diabetes defined at the proportion of patients in the group at high risk for hypoglycemia with A1c < 7.0%. Undertreatment defined as A1C > 9%. RESULTS: There was marked variation in overtreatment rates; for A1c < 7%, overtreatment rates ranged from 26.4% to 58.2% and 26.2% to 49.2% at the facility level in 2013 and 2016, respectively. The mean (±standard deviation (SD)) facility-level overtreatment rates fell from 40.3 (±5.3)% in 2013 to 37.75 (±4.70)% in 2016 (P < 0.001, paired t-test). Facility undertreatment rates ranged from 5.8% to 16.9% and 6.8% to 18.7% at the facility level in 2013 and 2016, respectively. The mean (±SD) undertreatment rate rose from 10.3 (±2.2)% in 2013 to 11.0 (±2.4)% in 2016 (P ≤ 0.001, paired t-test). However, change at individual facilities ranged from a decrease of 4.6% to an increase of 7.2%. Within year correlations were stronger than between year correlations. Overtreatment defined as A1c < 7 in this population inversely correlated strongly with undertreatment (r = -0.653, P < 0.001). CONCLUSIONS: Promotion of overtreatment reduction may be associated with an increase in undertreatment in patients with diabetes. Unintended consequence should be considered when implementing and evaluating quality measures and systems should include balancing measures to identify potential unintended harms.

Synopsis of the 2017 U.S. Department of Veterans Affairs/U.S. Department of Defense Clinical Practice Guideline: Management of Type 2 Diabetes Mellitus.

DESCRIPTION: In April 2017, the U.S. Department of Veterans Affairs (VA) and the U.S. Department of Defense (DoD) approved a joint clinical practice guideline for the management of type 2 diabetes mellitus. METHODS: The VA/DoD Evidence-Based Practice Work Group convened a joint VA/DoD guideline development effort that included a multidisciplinary panel of practicing clinician stakeholders and conformed to the Institute of Medicine's tenets for trustworthy clinical practice guidelines. The guideline panel developed key questions in collaboration with the ECRI Institute, which systematically searched and evaluated the literature through June 2016, developed an algorithm, and rated recommendations by using the GRADE (Grading of Recommendations Assessment, Development and Evaluation) system. RECOMMENDATIONS: This synopsis summarizes key features of the guideline in 7 areas: patient-centered care and shared decision making, glycemic biomarkers, hemoglobin A1c target ranges, individualized treatment plans, outpatient pharmacologic treatment, glucose targets for critically ill patients, and treatment of hospitalized patients.

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.

Using Shared Decision-Making to Address Possible Overtreatment in Patients at High Risk for Hypoglycemia: The Veterans Health Administration's Choosing Wisely Hypoglycemia Safety Initiative.

IN BRIEF Successful management of patients with diabetes requires individualizing A1C and treatment goals in conjunction with identifying and managing hypoglycemia risk. This article describes the Veterans Health Administration's Choosing Wisely Hypoglycemia Safety Initiative (CW-HSI), a voluntary program that aims to reduce the occurrence of hypoglycemia through shared decision-making about deintensifying diabetes treatment in a dynamic cohort of patients identified as being at high risk for hypoglycemia and potentially overtreated. The CW-HSI incorporates education for patients and clinicians, as well as clinical decision support tools, and has shown decreases in the proportions of high-risk patients potentially overtreated and impacts on the frequency of reported hypoglycemia.

Who Gets Testosterone? Patient Characteristics Associated with Testosterone Prescribing in the Veteran Affairs System: a Cross-Sectional Study.

BACKGROUND: There has been concern about the growing off-label use of testosterone. Understanding the context within which testosterone is prescribed may contribute to interventions to improve prescribing. OBJECTIVE: To evaluate patient characteristics associated with receipt of testosterone. DESIGN: Cross-sectional. SETTING: A national cohort of male patients, who had received at least one outpatient prescription within the Veterans Affairs (VA) system during Fiscal Year 2008- Fiscal Year 2012. PARTICIPANTS: The study sample consisted of 682,915 non-HIV male patients, of whom 132,764 had received testosterone and a random 10% sample, 550,151, had not. MAIN MEASURES: Conditions and medications associated with testosterone prescription. KEY RESULTS: Only 6.3% of men who received testosterone from the VA during the study period had a disorder of the testis, pituitary or hypothalamus associated with male hypogonadism. Among patients without a diagnosed disorder of hypogonadism, the use of opioids and obesity were the strongest predictors of testosterone prescription. Patients receiving >100 mg/equivalents of oral morphine daily (adjusted odds ratio = 5.75, p < 0.001) and those with body mass index (BMI) >40 kg/m2 (adjusted odds ratio = 3.01, p < 0.001) were more likely to receive testosterone than non-opioid users and men with BMI <25 kg/m2. Certain demographics (age 40-54, White race), comorbid conditions (sleep apnea, depression, and diabetes), and medications (antidepressants, systemic corticosteroids) also predicted a higher likelihood of testosterone receipt, all with an adjusted odds ratio less than 2 (p < 0.001). CONCLUSIONS: In the VA, 93.7% of men receiving testosterone did not have a diagnosed condition of the testes, pituitary, or hypothalamus. The strongest predictors of testosterone receipt (e.g., obesity, receipt of opioids), which though are associated with unapproved, off-label use, may be valid reasons for therapy. Interventions should aim to increase the proportion of testosterone recipients who have a valid indication.

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

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 < 6%, A1c < 6.5%, and A1c < 7%. There was little effect of facility complexity or regional Veterans Integrated Service Networks (VISNs) on outlier identification. Consistent high performing facilities for overtreatment had higher rates of undertreatment (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.

Variability in estimated glomerular filtration rate values is a risk factor in chronic kidney disease progression among patients with diabetes.

BACKGROUND: It is unknown whether variability of estimated Glomerular Filtration Rate (eGFR) is a risk factor for dialysis or death in patients with chronic kidney disease (CKD). This study aimed to evaluate variability of estimated Glomerular Filtration Rate (eGFR) as a risk factor for dialysis or death to facilitate optimum care among high risk patients. METHODS: A longitudinal retrospective cohort study of 70,598 Veterans Health Administration veteran patients with diabetes and CKD (stage 3-4) in 2000 with up to 5 years of follow-up. VHA and Medicare files were linked to derive study variables. We used Cox proportional hazards models to evaluate association between time to initial dialysis/death and key independent variables: time-varying eGFR variability (measured by standard deviation (SD)) and eGFR means and slopes while adjusting for prior hospitalizations, and comorbidities. RESULTS: There were 76.7% older than 65 years, 97.5% men, and 81.9% Whites. Patients were largely in early stage 3 (61.2%), followed by late stage 3 (28.9%), and stage 4 (9.9%); 29.1%, 46.8%, and 73.3%, respectively, died or had dialysis during the follow-up. eGFR SDs (median: 5.8, 5.1, and 4.0 ml/min/1.73 m(2)) and means (median: 54.1, 41.0, 27.2 ml/min/1.73 m(2)) from all two-year moving intervals decreased as CKD advanced; eGFR variability (relative to the mean) increased when CKD progressed (median coefficient of variation: 10.9, 12.8, and 15.4). Cox regressions revealed that one unit increase in a patient's standard deviation of eGFRs from prior two years was significantly associated with about 7% increase in risk of dialysis/death in the current year, similarly in all three CKD stages. This was after adjusting for concurrent means and slopes of eGFRs, demographics, prior hospitalization, and comorbidities. For example, the hazard of dialysis/death increased by 7.2% (hazard ratio:1.072; 95% CI = 1.067, 1.080) in early stage 3. CONCLUSION: eGFR variability was independently associated with elevated risk of dialysis/death even after controlling for eGFR means and slopes.

Mental illness and intensification of diabetes medications: an observational cohort study.

BACKGROUND: Mental health condition (MHC) comorbidity is associated with lower intensity care in multiple clinical scenarios. However, little is known about the effect of MHC upon clinicians' decisions about intensifying antiglycemic medications in diabetic patients with poor glycemic control. We examined whether delay in intensification of antiglycemic medications in response to an elevated Hemoglobin A1c (HbA1c) value is longer for patients with MHC than for those without MHC, and whether any such effect varies by specific MHC type. METHODS: In this observational study of diabetic Veterans Health Administration (VA) patients on oral antiglycemics with poor glycemic control (HbA1c ≥8) (N =52,526) identified from national VA databases, we applied Cox regression analysis to examine time to intensification of antiglycemics after an elevated HbA1c value in 2003-2004, by MHC status. RESULTS: Those with MHC were no less likely to receive intensification: adjusted Hazard Ratio [95% CI] 0.99 [0.96-1.03], 1.13 [1.04-1.23], and 1.12 [1.07-1.18] at 0-14, 15-30 and 31-180 days, respectively. However, patients with substance use disorders were less likely than those without substance use disorders to receive intensification in the first two weeks following a high HbA1c, adjusted Hazard Ratio 0.89 [0.81-0.97], controlling for sex, age, medical comorbidity, other specific MHCs, and index HbA1c value. CONCLUSIONS: For most MHCs, diabetic patients with MHC in the VA health care system do not appear to receive less aggressive antiglycemic management. However, the subgroup with substance use disorders does appear to have excess likelihood of non-intensification; interventions targeting this high risk subgroup merit attention.

Estimating utilities for chronic kidney disease, using SF-36 and SF-12-based measures: challenges in a population of veterans with diabetes.

PURPOSE: Using transformations of existing quality-of-life data to estimate utilities has the potential to efficiently provide investigators with utility information. We used within-method and across-method comparisons and estimated disutilities associated with increasing chronic kidney disease (CKD) severity. METHODS: In an observational cohort of veterans with diabetes (DM) and pre-existing SF-36/SF-12 responses, we used six transformation methods (SF-12 to EQ-5D, SF-36 to HUI2, SF-12 to SF-6D, SF-36 to SF-6D, SF-36 to SF-6D (Bayesian method), and SF-12 to VR-6D) to estimate unadjusted utilities. CKD severity was staged using glomerular filtration rate estimated from serum creatinines, with the modification of diet in renal disease formula. We then used multivariate regression to estimate disutilities specifically associated with CKD severity stage. RESULTS: Of 67,963 patients, 22,273 patients had recent-onset DM and 45,690 patients had prevalent DM. For the recent-onset group, the adjusted disutility associated with CKD derived from the six transformation methods ranged from 0.0029 to 0.0045 for stage 2; -0.004 to -0.0009 for early stage 3; -0.017 to -0.010 for late stage 3; -0.023 to -0.012 for stage 4; -0.078 to -0.033 for stage 5; and -0.012 to -0.001 for ESRD/dialysis. CONCLUSION: Disutility did not increase monotonically as CKD severity increased. Differences in disutilities estimated using the six different methods were found. Both findings have implications for using such estimates in economic analyses.

Eliminating Algorithmic Racial Bias in Clinical Decision Support Algorithms: Use Cases from the Veterans Health Administration.

The Veterans Health Administration uses equity- and evidence-based principles to examine, correct, and eliminate use of potentially biased clinical equations and predictive models. We discuss the processes, successes, challenges, and next steps in four examples. We detail elimination of the race modifier for estimated kidney function and discuss steps to achieve more equitable pulmonary function testing measurement. We detail the use of equity lenses in two predictive clinical modeling tools: Stratification Tool for Opioid Risk Mitigation (STORM) and Care Assessment Need (CAN) predictive models. We conclude with consideration of ways to advance racial health equity in clinical decision support algorithms.

Racial differences in trends of serious hypoglycemia among higher risk older adults in US Veterans Health Administration, 2004-2015: Relationship to comorbid conditions, insulin use, and hemoglobin A1c level.

AIMS: To evaluate temporal trends in racial/ethnic groups in rates of serious hypoglycemia among higher risk patients dually enrolled in Veterans Health Administration and Medicare fee-for-service and assess the relationship(s) between hypoglycemia rates, insulin/secretagogues and comorbid conditions. METHODS: Retrospective observational serial cross-sectional design. Patients were ≥65 years receiving insulin and/or secretagogues. The primary outcome was the annual (period prevalence) rates (2004-2015), per 1000 patient years, of serious hypoglycemic events, defined as hypoglycemic-related emergency department visits or hospitalizations. RESULTS: Subjects were 77-83% White, 7-10% Black, 4-5% Hispanic, <2% women; 38-58% were ≥75 years old; 72-75% had ≥1 comorbidity. In 2004-2015, rates declined from 63.2 to 33.6(-46.9%) in Blacks; 29.7 to 20.3 (-31.6%) in Whites; and 41.8 to 29.6 (-29.3%) in Hispanics. The Black-White rate differences narrowed regardless of insulin use, hemoglobin A1c level, and frequency and various combinations of comorbid conditions. Among insulin users, the Black-White contrast decreased from 34.7 (98.5 vs. 63.8) in 2004 to 13.2 (43.6 vs. 30.4) in 2015; in non-insulin users, the contrast was 25.7 (44.1 vs. 18.4) in 2004 and 10.1 (18.9 vs. 8.8) in 2015. CONCLUSION: Marked declines in serious hypoglycemia events occurred across race, medications, and comorbidities, suggesting significant changes in clinical practice.

CKD screening and management in the Veterans Health Administration: the impact of system organization and an innovative electronic record.

At the beginning of this decade, Healthy People 2010 issued a series of objectives to "reduce the incidence, morbidity, mortality and health care costs of chronic kidney disease." A necessary feature of any program to reduce the burden of kidney disease in the US population must include mechanisms to screen populations at risk and institute early the aspects of management, such as control of blood pressure, management of diabetes, and, in patients with advanced chronic kidney disease (CKD), preparation for dialysis therapy and proper vascular access management, that can retard CKD progression and improve long-term outcome. The Department of Veterans Affairs and the Veterans Health Administration is a broad-based national health care system that is almost uniquely situated to address these issues and has developed a number of effective approaches using evidence-based clinical practice guidelines, performance measures, innovative use of a robust electronic medical record system, and system oversight during the past decade. In this report, we describe the application of this systems approach to the prevention of CKD in veterans through the treatment of risk factors, identification of CKD in veterans, and oversight of predialysis and dialysis care. The lessons learned and applicability to the private sector are discussed.

Survival benefit of nephrologic care in patients with diabetes mellitus and chronic kidney disease.

BACKGROUND: The association of nephrologic care and survival in patients with diabetes mellitus and chronic kidney disease is unknown. METHODS: Using data from 1997 to 2000, we conducted a retrospective cohort study of Veterans Health Administration clinic users having diabetes mellitus and stage 3 or 4 chronic kidney disease. The baseline period was 12 months and median follow-up was 19.3 months. Degree of consistency of visits to a nephrologist, defined as the number of calendar quarters in which there was 1 visit or more (range, 0-4 quarters), and covariates were calculated from the baseline period. The outcome measure was dialysis-free death. RESULTS: Of 39,031 patients, 70.0%, 22.4%, and 7.6% had early stage 3, late stage 3, and stage 4 chronic kidney disease, respectively, and 3.1%, 9.5%, and 28.2%, respectively, visited a nephrologist. Dialysis-free mortality rates were 9.6, 14.1, and 19.4, respectively, per 100 person-years. More calendar quarters with visits to a nephrologist were associated with lower mortality: adjusted hazard ratios were 0.80 (95% confidence interval, 0.67-0.97), 0.68 (95% confidence interval, 0.55-0.86), and 0.45 (95% confidence interval, 0.32-0.63), respectively, when the groups having 2, 3, and 4 visits were compared with those who had no visits. One visit only was not associated with a difference in mortality when compared with no visits (adjusted hazard ratio,1.02; 95% confidence interval, 0.89-1.16). CONCLUSIONS: The consistency of outpatient nephrologic care was independently associated in a graded fashion with lower risk of deaths in patients with diabetes and moderately severe to severe chronic kidney disease. However, only a minority of patients had any visits to a nephrologist.

Risk of stroke, heart attack, and diabetes complications among veterans with spinal cord injury.

OBJECTIVES: To compare the rates of diabetes and macrovascular conditions in veterans with spinal cord injury (SCI) and to examine variations by patient-level demographic, socioeconomic, access, and health status factors. DESIGN: A retrospective analysis. Diabetes status was classified by merging with diabetes epidemiology cohort using a validated algorithm. Chi-square tests and logistic regressions used to compare rates in macro- and microvascular conditions in veterans with and without diabetes. SETTING: Veteran Health Administration clinic users in fiscal year (FY) 1999 to FY 2001. PARTICIPANTS: SCI patients (N=8769) with diabetes (n=1333), in FY 2000, identified through the SCI registry. INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: Macrovascular and microvascular conditions in the next year (February 2001). Derived from International Statistical Classification of Diseases, 9th Revision, Clinical Modification, codes in the patient treatment files. RESULTS: Overall, 15% of SCI veterans were identified with diabetes but this was an underestimate due to high mortality (8%). Among SCI veterans with diabetes, 49% had at least one macrovascular condition and 54% had microvascular conditions compared with 24% and 25% of those without diabetes (P<.001). CONCLUSIONS: Our study highlights the highly significant relationship between diabetes and macro- and microvascular conditions in veterans with SCI. Neurologic deficit combined with increased insulin resistance has a greater macrovascular impact on SCI veterans than on those who do not have diabetes. Increasing age and physical comorbidities compound the problem.

Impact of self-reported patient characteristics upon assessment of glycemic control in the Veterans Health Administration.

OBJECTIVE: The purpose of this article was to evaluate the impact of self-reported patient factors on quality assessment of Veterans Health Administration medical centers in achieving glycemic control. RESEARCH DESIGN AND METHODS: We linked survey data and administrative records for veterans who self-reported diabetes on a 1999 national weighted survey. Linear regression models were used to adjust A1C levels in fiscal year 2000 for socioeconomic status (education level, employment, and concerns of having enough food), social support (marital status and living alone), health behaviors (smoking, alcohol use, and exercise level), physical and mental health status, BMI, and diabetes duration. Medical centers were ranked by deciles, with and without adjustment for patient characteristics, on proportions of patients achieving A1C <7 or <8%. RESULTS: There was substantial medical center level variation in patient characteristics of the 56,740 individuals from 105 centers, e.g., grade school education (mean 15.3% [range 2.3-32.7%]), being retired (38.3% [19.9-59.7%]) or married (65.2% [43.7-77.8%]), food insufficiency (13.9% [7.2-24.6%]), and no reported exercise (43.2% [31.1-53.6%]). The final model had an R(2) of 7.8%. The Spearman rank coefficient comparing the thresholds adjusted only for age and sex to the full model was 0.71 for <7% and 0.64 for <8% (P < 0.0001). After risk adjustment, 4 of the 11 best-performing centers changed at least two deciles for the <7% threshold, and 2 of 11 changed two deciles for the <8% threshold. CONCLUSIONS: Adjustment for patient self-reported socioeconomic status and health impacts medical center rankings for glycemic control, suggesting the need for risk adjustment to assure valid inferences about quality.

Defining and measuring population health quality of outpatient diabetes care in Israel: lessons from the quality indicators in community health program.

In Israel, as in other Organization for Economic Co-operation and Development countries, performance measurement is a key public health strategy in monitoring and improving population health outcomes. The Israeli Quality Indicators in Community Healthcare (QICH) program has utilized electronic health records to monitor ambulatory care for the entire Israeli population since 2002. In 2006 the measures were updated to include laboratory values. They have been subsequently revised by stratifying by age, duration, adding medications, and changing frequency of testing for certain process measures. However, the QICH glycemic control measures do not address co-morbid conditions either thru exclusion criteria or higher target ranges. They also do not address potential over treatment in patients with complex medication conditions.In the United States there have also been changes in nationally endorsed diabetes specific performance measures since 2007. However, there have also been public disagreements among United States professional societies, government agencies, and performance measurement organizations as to whether the current glycemic dichotomous ("all or none") threshold measures, without exclusion criteria, are consistent with the most recent evidence. Specifically, most guidelines now recommend individualized target goals based upon co-morbid conditions, risk of harms from medications, and patient preferences.Concerns have been raised that the current glycemic performance measures have resulted in inappropriate care, such as medication over-treatment, and serious harms, such as hypoglycemia, especially in older adults. There currently are no national surveillance systems or measures that monitor these untoward outcomes.We recommend several actions that QICH could consider to advance diabetes specific performance measurement science and population health: Convene an international conference; implement technical modifications of current measures and surveillance systems; and, most importantly, acknowledge patient autonomy by developing measures that document individualization of target values using shared decision making.

An expanded prevention quality diabetes composite: Quantifying the burden of preventable hospitalizations for older adults with diabetes.

AIM: To expand the existing United States Agency for Health Research and Quality (AHRQ) Diabetes composite (AHRQ-DC) to include additional preventable hospitalizations specific or relevant to diabetes. METHODS: A cross-sectional analysis of 834,696 veteran patients with diabetes aged ≥65 years in 2012. An Expanded Diabetes Composite (Expanded-DC) was developed utilizing: (1) the diabetes-specific category: the AHRQ-DC (short-term and long-term complications, uncontrolled diabetes, lower extremity amputations) and two proposed conditions: hypoglycemia and lower extremity ulcers/inflammation/infections (LEU) and (2) the diabetes-relevant category: the AHRQ-Acute Composite (dehydration, pneumonia, urinary tract infections) and one proposed condition, acute kidney injury (AKI). RESULTS: The study population was 98% male, 80% White, 10% Black, and 5% Hispanic; 71% had complex comorbidities. There were 64,243 (77.0 admissions/1000 patients) hospitalizations in the Expanded-DC, compared to 13,523 (16.2) in the AHRQ-DC, a 4.7 fold increase. Hospitalizations from AHRQ-Acute Composite and the three proposed conditions added 79% to the Expanded-DC. LEU and hypoglycemia added 39% to the diabetes-specific category. AKI added 18% to the diabetes-relevant category. Blacks incurred more preventable hospitalizations (85.9) than Whites (74.7); as did patients with complex comorbidities (93.6) versus those without (34.6). CONCLUSION: The AHRQ-DC substantially underestimates rates of clinically important preventable hospitalizations in older diabetes patients.