Improving health determinants outside of the clinic does not mean outside of clinical science.

There has been steady and growing interest in addressing patient health beyond the traditional interactions with clinicians. Much attention has been given to the social determinants of health which are associated with many non-communicable diseases. A challenge to the healthcare delivery system is to incorporate these environmental circumstances into a coherent diagnosis and treatment framework. As clinicians are expected to help transform the healthcare delivery systems to consider these extra-clinical factors, they may benefit from better understanding of pathways to disease. Similarly, payment systems should incorporate health economics outcomes research to augment the healthcare utilization measures used frequently today.

Predictors of Change in Adherence Status from 1 Year to the Next Among Patients with Type 2 Diabetes Mellitus on Oral Antidiabetes Drugs.

BACKGROUND: Diabetes is a leading cause of morbidity, mortality, and medical resource utilization in the United States and worldwide. Treatment is aimed at keeping blood glucose levels close to normal and preventing or delaying medical complications. It has been estimated that only 50% of patients with diabetes in the United States achieve glycosylated hemoglobin A1c level < 7%. Nonadherence to antidiabetic medications has been identified as a major factor related to poor glycemic control. OBJECTIVES: To (a) assess adult patients with type 2 diabetes mellitus (T2DM) whose adherence status to oral antidiabetic drugs (OADs) changed from 1 year to the next and (b) identify predictors of change in adherence status. METHODS: This retrospective study of the Humana Medicare Advantage Database included patients with T2DM and continuous enrollment between 2010 and 2012. Proportion of days covered (PDC) by OADs was calculated for each of the 3 study years (2010, 2011, 2012). Patients were classified as adherent (PDC ≥ 80%) or nonadherent (PDC < 80%) during each year. Patient characteristics from the baseline period (2010) were used as covariates, and adherence status changes from baseline to follow-up year (2011) were used as response variables. Data from the subsequent study periods (2011 as baseline, 2012 as follow-up) were used to validate the model (final model). RESULTS: A total of 238,402 patients met inclusion criteria. Among them, 144,216 (60.5%) were adherent, and 94,186 (39.5%) were nonadherent during the baseline period. Change in adherence status from baseline to follow-up year was observed in 31,320 (21.7%) patients that were adherent and 39,284 (41.7%) patients that were nonadherent during the baseline year. The final model for baseline adherent patients had a receiver-operating characteristic (ROC) index of 73% and a misclassification rate of 39%. The predictors of highest importance were identified as total number of prescriptions filled with 90-day supply, diabetes-related pill burden, longest gap in OADs, total number of antidiabetic classes filled, and copay for the last OAD filled. The final model had a sensitivity value of 76.4%. The final model for baseline nonadherent patients had a ROC index of 68%, a misclassification rate of 36.4%, and sensitivity value of 52.9%. The predictors of highest importance were diabetes-related pill burden, longest gap in OADs, month-wise patient oscillation from adherent to nonadherent during baseline year, total number of prescriptions filled with a 90-day supply, and total pill burden during the baseline year. CONCLUSIONS: One third of the T2DM patients changed adherence status from 1 year to the next, and factors associated with adherence status changes were identified. Predictive models such as those used in this study can serve as useful and cost-effective tools for payers, helping to identify members that should be targeted for adherence enhancement programs and, ultimately, to improve patients' long-term outcomes. DISCLOSURES: Funding for this research was provided by Eli Lilly and Company. Comprehensive Health Insights, owned by Humana, completed this study. Peng, Fu, Ascher-Svanum, Ali, and Rodriguez are employees of Eli Lilly and Company. Saundankar and Louder are employed by Comprehensive Health Insights, and Slabaugh and Young are employed by Humana. Study concept and design were contributed by Peng, Ascher-Svanum, and Young. Saundankar and Louder took the lead in data collection, while Saundankar, Peng, Fu, and Louder interpreted the data. The manuscript was written by Saundankar, Peng, Fu, and Louder and revised by Saundankar, Rodriguez, Ali, and Louder.

Racial/ethnic and gender differences in severity of diabetes-related complications, health care resource use, and costs in a Medicare population.

This retrospective cohort study evaluated associations of race/ethnicity and gender with outcomes of diabetes complications severity, health care resource utilization (HRU), and costs among Medicare Advantage health plan members with type 2 diabetes (T2DM). Medical and pharmacy claims were evaluated for 333,576 members continuously enrolled from January 1, 2010, to December 31, 2011, aged 18-89 years, with ≥1 primary diagnosis medical claim, or ≥2 claims with a secondary diagnosis of T2DM (International Classification of Diseases, Ninth Revision, Clinical Modification code 250.x0 or 250.x2). Complications severity assessment by Diabetes Complications Severity Index ranged from 0 (no complications) to 5+. Mean (SD) all-cause medical, pharmacy, and total costs were reported alongside all-cause HRU by place of service (outpatient, inpatient, emergency room [ER]) and number of visits. Multivariate regression showed being Hispanic, black, or male was associated with higher prevalence of more severe complications. This racial/ethnic disparity was more pronounced among females, among whom odds of having more severe complications were higher for Hispanic and black as compared to white females [(Hispanic vs. white odds ratio [OR], 1.40; 95% confidence interval [CI], 1.32-1.48), and (black vs. white OR, 1.22; 95% CI, 1.19-1.25)]. Regardless of gender, blacks had more ER visits than whites. White females incurred the highest total health care costs (mean annual costs: $13,086; 95% CI, $12,935-$13,240, vs. Hispanic females: $10,732; 95% CI, $10,406-$11,067). These effects held regardless of other demographic and clinical attributes. These findings suggest racial/ethnic and gender differences exist in certain T2DM clinical and economic outcomes.

Relationship of diabetes complications severity to healthcare utilization and costs among Medicare Advantage beneficiaries.

OBJECTIVES: This study evaluated the usefulness of the Diabetes Complications Severity Index (DCSI) in assessing healthcare resource utilization (HRU) and costs among Medicare Advantage plan members diagnosed with type 2 diabetes mellitus (T2DM). STUDY DESIGN: A retrospective cohort study of medical and pharmacy claims of 333,576 Medicare members aged 18 to 89 years with ≥1 medical claim with primary diagnosis or ≥2 medical claims with secondary diagnosis, of T2DM (International Classification of Diseases, Ninth Revision, Clinical Modification code 250.x0 or 250.x2) during the period of January 1, 2010, to December 31, 2011. METHODS: DCSI was assessed concurrently with HRU and healthcare costs (total, medical, and pharmacy). The cohort was subdivided into 6 DCSI groups: DCSI = 0 (no complications) through DCSI = 5+ (≥5). Associations of complication severity with HRU and costs of care were summarized using regression models. RESULTS: A 1-point increase in DCSI was associated with a $2744 increase in total costs (a $2480 increase in medical costs plus a $264 increase in pharmacy costs). Increasing DCSI was associated with greater use of inpatient and emergency department (ED) services. Among the higher complications subgroups, there were greater representations of older patients, men, and cases of depressive disorders and hypoglycemia. CONCLUSIONS: DCSI is useful for identifying Medicare plan members with T2DM who should be targeted for clinical programs. HRU and costs increased with DCSI severity. Increases in high-cost HRU, driven by inpatient and ED visits, suggest that preventing or delaying utilization of these services are essential to driving down costs in the T2DM population. Furthermore, high rates of depression and hypoglycemia warrant early screening and necessary treatment to improve patient outcomes.