Integrating E-Prescribing and Pharmacy Claims Data for Predictive Modeling: Comparing Costs and Utilization of Health Plan Members Who Fill Their Initial Medications with Those Who Do Not.

BACKGROUND: Nonfilling of prescribed medications is a worldwide problem of serious concern. Studies of health care costs and utilization associated with medication nonadherence frequently rely on claims data and usually focus on patients with specific conditions. Past studies also have little agreement on whether higher medication costs associated with higher adherence can reduce downstream health care consumption. OBJECTIVES: To (a) compare the characteristics between people with and without complete medication initiations from a general population and (b) quantify the effect of medication initiation on health care utilization and expenditures with propensity score weighting. METHODS: We conducted a retrospective cohort study using 2012 and 2013 electronic health records (EHR) and insurance claims data from an integrated health care delivery network. We included 43,097 eligible primary care patients in the study. Annual medication fill rates of initial prescriptions in 2012 were defined as the number of filled prescriptions from claims divided by the number of e-prescriptions from EHRs, while excluding all refills. A claim was considered filled if (a) EHR and claims records were from the same drug class; (b) claims occurred between the date of a current EHR order and that of the next EHR order of the same class; and (c) the maximum fill rate was 100%. The 6 annual outcomes included total costs, medical costs, pharmacy costs, being a high-cost "outlier" (in top 5%), having 1 or more hospitalizations, and having 1 or more emergency department (ED) visits. Individuals were classified as either having completed all medication initiations (100% annual filling rate for initiations) or not. We used propensity score weighting to control for baseline differences between complete and incomplete initial fillers. We adopted linear and logistic regressions to model costs and binary utilization indicators for the same year (concurrently) and next year (prospectively). RESULTS: Approximately 42% of the study sample had complete medication initiations (100% filling rate), while the remaining 58% had incomplete initiations. Individuals who fully filled initial prescriptions had lower comorbidity burden and consumed fewer health care resources. After applying propensity score weighting and controlling for variables such as the number of prescription orders, patients with complete medication initiations had lower overall and medical costs, concurrently and prospectively (e.g., $751 and $252 less for annual total costs). Complete medication initiation fillers were also less likely to have concurrent health care utilization (OR = 0.78, 95% CI = 0.68-0.90 for hospitalization; OR = 0.77, 95% CI = 0.72-0.82 for ED admissions) but no difference in prospective utilization other than for ED visits (OR = 0.93, 95% CI = 0.87-0.99). CONCLUSIONS: Identifying the subpopulation of patients with incomplete medication initiations (i.e., filling less than 100% of initial prescriptions) is a pragmatic approach for population health management programs to align resources and potentially contain cost and utilization. DISCLOSURES: No outside funding supported this study. This study applied the Adjusted Clinical Group (ACG) case-mix/risk adjustment methodology, developed at Johns Hopkins Bloomberg School of Public Health. Although ACGs are an important aspect of this study, the goal of the study was not to directly assess or evaluate the methodology. The Johns Hopkins University receives royalties for nonacademic use of software based on the ACG methodology. Chang, Kharrazi, and Weiner receive a portion of their salary support from this revenue. Chang is also a part-time consultant for Monument Analytics, a health care consultancy whose clients include the life sciences industry, as well as plaintiffs in opioid litigation. Alexander is past Chair of FDA's Peripheral and Central Nervous System Advisory Committee; has served as a paid advisor to IQVIA; is a co-founding Principal and equity holder in Monument Analytics; and is a member of OptumRx's National P&T Committee. These arrangements have been reviewed and approved by Johns Hopkins University in accordance with its conflict of interest policies. The other authors have nothing to disclose.

Comparing Survey-Based Frailty Assessment to Medicare Claims in Predicting Health Outcomes and Utilization in Medicare Beneficiaries.

Objectives: To assess two models for the prediction of health utilization and functions using standardized in-person assessments of frailty and administrative claims-based geriatric risk measures among Medicare fee-for-service beneficiaries aged 65 years and above. Methods: Outcomes of hospitalizations, death, and functional help were investigated for participants in the 2011 National Health and Aging Trends Study. For each outcome, multivariable logistic regression model was used to investigate claims-based geriatric risk and survey-based frailty. Results: Both claims-based and survey-based models showed moderate discrimination. The c-statistic of the standardized frailty models ranged from 0.67 (for any hospitalization) to 0.84 (for any IADL [instrumental activities of daily living] help). Models using administrative data ranged from 0.71 (for any hospitalization) to 0.81 (for any IADL help). Discussion: Models based on existing administrative data appear to be as discriminate as survey-based models. Health care providers and insurance plans can effectively apply existing data resources to help identify high-risk individuals for potential care management interventions.

Exploring the use of machine learning for risk adjustment: A comparison of standard and penalized linear regression models in predicting health care costs in older adults.

BACKGROUND: Payers and providers still primarily use ordinary least squares (OLS) to estimate expected economic and clinical outcomes for risk adjustment purposes. Penalized linear regression represents a practical and incremental step forward that provides transparency and interpretability within the familiar regression framework. This study conducted an in-depth comparison of prediction performance of standard and penalized linear regression in predicting future health care costs in older adults. METHODS AND FINDINGS: This retrospective cohort study included 81,106 Medicare Advantage patients with 5 years of continuous medical and pharmacy insurance from 2009 to 2013. Total health care costs in 2013 were predicted with comorbidity indicators from 2009 to 2012. Using 2012 predictors only, OLS performed poorly (e.g., R2 = 16.3%) compared to penalized linear regression models (R2 ranging from 16.8 to 16.9%); using 2009-2012 predictors, the gap in prediction performance increased (R2:15.0% versus 18.0-18.2%). OLS with a reduced set of predictors selected by lasso showed improved performance (R2 = 16.6% with 2012 predictors, 17.4% with 2009-2012 predictors) relative to OLS without variable selection but still lagged behind the prediction performance of penalized regression. Lasso regression consistently generated prediction ratios closer to 1 across different levels of predicted risk compared to other models. CONCLUSIONS: This study demonstrated the advantages of using transparent and easy-to-interpret penalized linear regression for predicting future health care costs in older adults relative to standard linear regression. Penalized regression showed better performance than OLS in predicting health care costs. Applying penalized regression to longitudinal data increased prediction accuracy. Lasso regression in particular showed superior prediction ratios across low and high levels of predicted risk. Health care insurers, providers and policy makers may benefit from adopting penalized regression such as lasso regression for cost prediction to improve risk adjustment and population health management and thus better address the underlying needs and risk of the populations they serve.

Burden of systemic lupus erythematosus on employment and work productivity: data from a large cohort in the southeastern United States.

OBJECTIVE: To examine the burden of systemic lupus erythematosus (SLE) on work loss, unemployment, and work productivity impairment in an SLE cohort from the southeastern US. METHODS: We examined 689 SLE patients ages 18-64 years from the Georgians Organized Against Lupus (GOAL) cohort. GOAL is a longitudinal cohort predominantly derived from the Georgia Lupus Registry, a population-based registry established in metropolitan Atlanta. We used the Kaplan-Meier method to assess the proportion of patients who self-reported work loss since diagnosis. We compared unemployment between SLE patients and the general population from the same geographic area, calculating the standardized unemployment ratio (SUR) within demographic and disease strata. We also calculated the percentage of work productivity impairment by disease outcomes. RESULTS: Of 511 patients employed at diagnosis, 249 (49%) experienced work loss within an average disease duration of 13 years. The proportion of patients who lost their jobs since diagnosis was almost twice for African Americans than for whites. However, the SURs were similar across demographic characteristics, including race. Patients with severe disease activity and severe organ damage had the highest SUR at 4.4 and 5.6, respectively. Among those that remained employed, patients with severe fatigue, neurocognitive symptoms, and musculoskeletal symptoms had the highest impairment of work productivity. CONCLUSION: SLE imposes a substantial toll on individuals and burden on society. Major factors that negatively impact work outcomes are fatigue, disease activity, and organ damage. More effective treatments along with coping strategies at the workplace are needed to reduce the burden of SLE on work outcomes.

Cumulative burden of oral corticosteroid adverse effects and the economic implications of corticosteroid use in patients with systemic lupus erythematosus.

BACKGROUND: Corticosteroids (CSs) are used to treat patients with systemic lupus erythematosus (SLE) and are associated with potential adverse events (AEs). However, few data are currently available on the risk of AEs in CS users in an SLE population. OBJECTIVE: To examine AEs related to CS use and costs of treating CS-related AEs in patients with SLE. METHODS: In a retrospective cohort study using claims data (study period: January 1, 2000-June 30, 2010), patients aged ≥18 years having ≥2 SLE-related (International Classification of Diseases, Ninth Revision, Clinical Modification code 710.0x) outpatient or ≥1 inpatient/emergency department claim were identified with an index diagnosis date deemed as the date of first SLE diagnosis. Receipt of CS therapy was assessed within 6 months of the index diagnosis date. Cox models were used to evaluate risk of AEs in CS users and nonusers. Associated costs were computed for AEs where risk was significantly different among the cohorts. RESULTS: Of 2717 patients with SLE, 989 received CSs and 1728 did not. Users of CSs were ~1.5 times more likely to develop chronic AEs (sleep disturbances, migraines, cataracts, hypertension, and type 2 diabetes mellitus) and ~2 times more likely to develop acute AEs (pneumonia, herpes zoster, fungal infections, and nausea/vomiting) compared with CS nonusers. The mean annual cost for managing AEs was $4607 and was highest for diabetes mellitus ($9764), hypertension ($8773), and sleep disturbances ($5599). Applying differences in 1-year event rates (CS user: 58.1%; CS nonuser: 75.1%) to cost estimates yielded an additional $784 per year per CS user to manage known CS-related AEs compared with CS nonusers. CONCLUSIONS: Although CSs are prescribed to control SLE symptoms, these results highlight potential risks and costs associated with their use, which providers/payers should consider when making treatment decisions.

Healthcare utilization and costs of systemic lupus erythematosus in Medicaid.

Objective. Healthcare utilization and costs associated with systemic lupus erythematosus (SLE) in a US Medicaid population were examined. Methods. Patients ≥ 18 years old with SLE diagnosis (ICD-9-CM 710.0x) were extracted from a large Medicaid database 2002-2009. Index date was date of the first SLE diagnosis. Patients with and without SLE were matched. All patients had a variable length of followup with a minimum of 12 months. Annualized healthcare utilization and costs associated with SLE and costs of SLE flares were assessed during the followup period. Multivariate regressions were conducted to estimate incremental healthcare utilization and costs associated with SLE. Results. A total of 14,777 SLE patients met the study criteria, and 14,262 were matched to non-SLE patients. SLE patients had significantly higher healthcare utilization per year than their matched controls. The estimated incremental annual cost associated with SLE was $10,984, with the highest increase in inpatient costs (P < 0.001). Cost per flare was $11,716 for severe flares, $562 for moderate flares, and $129 for mild flares. Annual total costs for patients with severe flares were $49,754. Conclusions. SLE patients had significantly higher healthcare resource utilization and costs than non-SLE patients. Patients with severe flares had the highest costs.

Comparative utility of aripiprazole and haloperidol in schizophrenia: post hoc analysis of two 52-week, randomized, controlled trials.

BACKGROUND: Since their introduction, second-generation antipsychotics (SGAs) have become the drugs of choice for the treatment of schizophrenia. However, recent findings have questioned the benefits of SGAs over first-generation antipsychotics (FGAs). OBJECTIVE: This post hoc analysis sought to compare the utility of the SGA aripiprazole with the FGA haloperidol in patients with early-phase schizophrenia (ES) or chronic schizophrenia (CS). METHOD: Data were pooled from two identical 52-week, randomized, active comparator trials (31-98-217 and 31-98-304) of aripiprazole 20-30 mg/day versus haloperidol 7-10 mg/day. Patients in the efficacy sample were classified as having ES if they were

Incidence and costs of treatment-related complications among patients with advanced squamous cell carcinoma of the head and neck.

OBJECTIVE: To evaluate the incidence and costs of complications due to radiotherapy alone vs platinum-based chemoradiotherapy among patients diagnosed as having advanced squamous cell carcinoma of the head and neck (ASCCHN) from a payer perspective. DESIGN: Retrospective cohort study. SETTING: Data from the PharMetrics Patient-Centric Database from June 2000 through June 2006. PATIENTS: The study included patients with ASCCHN and an indication of a secondary malignant neoplasm (both identified based on International Classification of Diseases, Ninth Revision, Clinical Modification, diagnosis codes), 124 of whom were treated with radiotherapy alone and 77 of whom were treated with chemoradiotherapy (including 53 with cisplatin plus radiotherapy, 26 with carboplatin plus radiotherapy, and 2 with cisplatin and carboplatin plus radiotherapy). The patients were assigned to 1 of 2 cohorts based on treatment type-radiotherapy only and platinum-based chemoradiotherapy-and were followed up for 6 months. MAIN OUTCOME MEASURES: Incidence and costs of treatment-related complications associated with chemotherapy in ASCCHN. RESULTS: We found significantly (P < .001) higher rates of treatment-related complications among patients receiving chemoradiotherapy (86%) than among patients receiving only radiotherapy (51%). The mean per-patient costs associated with treatment-related complications were approximately $10 000 higher among patients who received chemoradiotherapy than among those treated with radiotherapy alone (P < .001). These costs represented 17% of the total costs during follow-up for patients who received chemoradiotherapy and 11% of costs for those who received radiotherapy. The most expensive complications were dehydration and/or electrolyte imbalance and oral complications. CONCLUSIONS: Our study results suggest that the attributable incidence and costs of treatment-related complications associated with chemotherapy in ASCCHN are substantial. The emergence of safer treatments may have the advantage of alleviating this cost burden.

Prevalence and the associated burden of illness of symptoms of diabetic peripheral neuropathy and diabetic retinopathy.

BACKGROUND: We estimated the prevalence and the associated burden of illness of symptoms of diabetic peripheral neuropathy (SDPN), diabetic retinopathy (DR), and comorbid SDPN and DR among people with diabetes in the United States aged > or =40 years. METHODS: Analyses were conducted on 850 respondents aged > or =40 years with diagnosed diabetes from the combined 1999-2000 and 2001-2002 National Health and Nutrition Examination Surveys. Sampling weights were used to estimate the number of people with diabetes who have SDPN, DR, or comorbid SDPN and DR. Multivariate regression models were used to assess the effects of SDPN, DR, and comorbid SDPN and DR on burden-of-illness measures. RESULTS: Approximately 11.9 million adults in the United States aged > or =40 years have diagnosed diabetes. Of those, 3.9 million (32.7%) have SDPN, 3.3 million (27.4%) have DR, and 1.6 million (13.1%) have comorbid SDPN and DR. Among our sample, those with SDPN [odds ratio (OR)=2.25; 95% confidence interval (95% CI)=1.32-3.83], DR (OR=1.68; 95% CI=1.08-2.61), or comorbid SDPN and DR (OR=2.84; 95% CI=1.26-6.41) were more likely than those without the corresponding condition to have four or more health care visits in the past year. Those of working age (40-65 years) with SDPN (OR=3.23; 95% CI=1.60-6.52), DR (OR=2.94; 95% CI=1.45-5.97), or comorbid SDPN and DR (OR=4.32; 95% CI=2.17-8.63) were more likely unable to work due to physical limitations. CONCLUSIONS: SDPN, DR, and comorbid SDPN and DR are prevalent among people with diabetes in the United States aged > or =40 years; each of these complications appears to significantly increase the burden of illness.