Aetna's Compassionate Care Program: Sustained Value for Our Members with Advanced Illness.

Background: In 2004, Aetna, a national health insurer, launched the Aetna Compassionate Care Program (ACCP) targeting members diagnosed with an advanced illness with a view to increase access to palliative care and hospice services. Objective: The objective of this study is to evaluate the impact of ACCP on health care utilization and hospice enrollment among enrolled members. Methods: This was a retrospective cohort study comparing participants in ACCP to a matched control group using a propensity score method. The study group consisted of Aetna Medicare Advantage members who participated in the ACCP between January 2014 and June 2015. Potential control group members were those who were not identified by the predictive model nor were referred to the ACCP program through other means. The primary outcomes of interest were hospice use measured as percent of members electing hospice and median number of days in hospice; health care utilization and medical costs measured as rates and medical costs associated with acute inpatient admissions, emergency room, primary care, and specialty visits in the 30 and 90 days before death. Results: Participants in the ACCP program were 36% more likely to enroll in hospice (79% vs. 58%, p < 0.0001) and had reduced acute inpatient medical costs ($4169 vs. $5863, p < 0.0001) driven primarily by fewer inpatient admissions (860 vs. 1017, p < 0.0001) in the last 90 days of life. Conclusions: Advanced illness case management programs such as ACCP can improve access to hospice and improve patient outcomes while reducing unnecessary admissions in the last 90 days of life.

Utilization Patterns of Oral Disease-Modifying Drugs in Commercially Insured Patients with Multiple Sclerosis.

BACKGROUND: The approval of new oral disease-modifying drugs (DMDs), such as fingolimod, dimethyl fumarate (DMF), and teriflunamide, has considerably expanded treatment options for relapsing forms of multiple sclerosis (MS). However, data describing the use of these agents in routine clinical practice are limited. OBJECTIVE: To describe time trends and identify factors associated with oral DMD treatment initiation and switching among individuals with MS. METHODS: Using data from a large sample of commercially insured patients, we evaluated changes over time in the proportion of MS patients who initiated treatment with an oral DMD and who switched from an injectable DMD to an oral DMD between 2009 and 2014 in the United States. We evaluated predictors of oral DMD use using conditional logistic regression in 2 groups matched on calendar time: oral DMD initiators matched to injectable DMDs initiators and oral DMD switchers matched to those who switched to a second injectable DMD. RESULTS: Our cohort included 7,576 individuals who initiated a DMD and 1,342 who switched DMDs, of which oral DMDs accounted for 6% and 39%, respectively. Oral DMD initiation and switching steadily increased from 5% to 16% and 35% to 84%, respectively, between 2011 and 2014, with DMF being the most commonly used agent. Of the potential predictors with clinical significance, a recent neurologist consultation (OR = 1.60; 95% CI = 1.20-2.15) and emergency department visit (OR = 1.43; 95% CI = 1.01-2.01) were significantly associated with oral DMD initiation. History of depression was noted to be a potential predictor of oral DMD initiation; however, the estimate for this predictor did not reach statistical significance (OR = 1.35; 95% CI = 0.99-1.84). No clinically relevant factors measured in our data were associated with switching to an oral DMD. CONCLUSIONS: Oral DMDs were found to be routinely used as second-line treatment. However, we identified few factors predictive of oral DMD initiation or switching, which implies that their selection is driven by patient and/or physician preferences. DISCLOSURES: This study was funded by CVS Caremark through an unrestricted research grant to Brigham and Women's Hospital. Shrank and Matlin were employees of, and shareholders in, CVS Health at the time of the study; they report no financial interests in products or services that are related to the subject of this study. Spettell is an employee of, and shareholder in, Aetna. Chitnis serves on clinical trial advisory boards for Novartis and Genzyme-Sanofi; has consulted for Bayer, Biogen Idec, Celgene, Novartis, Merck-Serono, and Genentech-Roche; and has received research support from NIH, National Multiple Sclerosis Society, Peabody Foundation, Consortium for MS Centers, Guthy Jackson Charitable Foundation, EMD-Serono, Novartis Biogen, and Verily. Desai reports receiving a research grant from Merck for unrelated work. Gagne is principal investigator of a research grant from Novartis Pharmaceuticals Corporation to the Brigham and Women's Hospital and has received grant support from Eli Lilly, all for unrelated work. He is also a consultant to Aetion and Optum. Minden reports grants from Biogen and other fees from Genentech, EMD Serano, Avanir, and Novartis, unrelated to this study. The other authors have no conflicts to report. This study was presented as a poster at the International Society for Pharmacoepidemiology 32nd Annual Meeting; August 25-28, 2016; Dublin, Ireland.

Predicting Adherence to Chronic Disease Medications in Patients with Long-term Initial Medication Fills Using Indicators of Clinical Events and Health Behaviors.

BACKGROUND: Efforts at predicting long-term adherence to medications have been focused on patients filling typical month-long supplies of medication. However, prediction remains difficult for patients filling longer initial supplies, a practice that is becoming increasingly common as a method to enhance medication adherence. OBJECTIVES: To (a) extend methods involving short-term filling behaviors and (b) develop novel variables to predict adherence in a cohort of patients receiving longer initial prescriptions. METHODS: In this retrospective cohort study, we used claims from a large national insurer to identify patients initiating a 90-day supply of oral medications for diabetes, hypertension, and hyperlipidemia (i.e., statins). Patients were included in the cohort if they had continuous database enrollment in the 180 days before and 365 days after medication initiation. Adherence was measured in the subsequent 12 months using the proportion of days covered metric. In total, 125 demographic, clinical, and medication characteristics at baseline and in the first 30-120 days after initiation were used to predict adherence using logistic regression models. We used 10-fold cross-validation to assess predictive accuracy by discrimination (c-statistic) measures. RESULTS: In total, 32,249 patients met the inclusion criteria, including 14,930 patients initiating statins, 12,887 patients initiating antihypertensives, and 4,432 patients initiating oral hypoglycemics. Prediction using only baseline variables was relatively poor (cross-validated c-statistic = 0.644). Including indicators of acute clinical conditions, health resource utilization, and short-term medication filling in the first 120 days greatly improved predictive ability (0.823). A model that incorporated all baseline characteristics and predictors within the first 120 days after medication initiation more accurately predicted future adherence (0.832). The best performing model that included all 125 baseline and postbaseline characteristics had strong predictive ability (0.837), suggesting the utility of measuring these novel postbaseline variables in this population. CONCLUSIONS: We demonstrate that long-term, 12-month adherence in patients filling longer supplies of medication can be strongly predicted using a combination of clinical, health resource utilization, and medication filling characteristics before and after treatment initiation. DISCLOSURES: This work was supported by an unrestricted grant from CVS Health to Brigham and Women's Hospital. Shrank and Matlin were employees and shareholders at CVS Health at the time of this study; they report no financial interests in products or services that are related to this subject. Spettell is an employee of, and shareholder in, Aetna. This research was previously presented at the 2016 Annual Conference of the International Society for Pharmacoepidemiology; August 25-28, 2016; Dublin, Ireland.

Effect of Electronic Reminders, Financial Incentives, and Social Support on Outcomes After Myocardial Infarction: The HeartStrong Randomized Clinical Trial.

Importance: Adherence to medications prescribed after acute myocardial infarction (AMI) is low. Wireless technology and behavioral economic approaches have shown promise in improving health behaviors. Objective: To determine whether a system of medication reminders using financial incentives and social support delays subsequent vascular events in patients following AMI compared with usual care. Design, Setting, and Participants: Two-arm, randomized clinical trial with a 12-month intervention conducted from 2013 through 2016. Investigators were blinded to study group, but participants were not. Design was a health plan-intermediated intervention for members of several health plans. We recruited 1509 participants from 7179 contacted AMI survivors (insured with 5 large US insurers nationally or with Medicare fee-for-service at the University of Pennsylvania Health System). Patients aged 18 to 80 years were eligible if currently prescribed at least 2 of 4 study medications (statin, aspirin, ß-blocker, antiplatelet agent), and were hospital inpatients for 1 to 180 days and discharged home with a principal diagnosis of AMI. Interventions: Patients were randomized 2:1 to an intervention using electronic pill bottles combined with lottery incentives and social support for medication adherence (1003 patients), or to usual care (506 patients). Main Outcomes and Measures: Primary outcome was time to first vascular rehospitalization or death. Secondary outcomes were time to first all-cause rehospitalization, total number of repeated hospitalizations, medication adherence, and total medical costs. Results: A total of 35.5% of participants were female (n = 536); mean (SD) age was 61.0 (10.3) years. There were no statistically significant differences between study arms in time to first rehospitalization for a vascular event or death (hazard ratio, 1.04; 95% CI, 0.71 to 1.52; P = .84), time to first all-cause rehospitalization (hazard ratio, 0.89; 95% CI, 0.73 to 1.09; P = .27), or total number of repeated hospitalizations (hazard ratio, 0.94; 95% CI, 0.60 to 1.48; P = .79). Mean (SD) medication adherence did not differ between control (0.42 [0.39]) and intervention (0.46 [0.39]) (difference, 0.04; 95% CI, -0.01 to 0.09; P = .10). Mean (SD) medical costs in 12 months following enrollment did not differ between control ($29 811 [$74 850]) and intervention ($24 038 [$66 915]) (difference, -$5773; 95% CI, -$13 682 to $2137; P = .15). Conclusions and Relevance: A compound intervention integrating wireless pill bottles, lottery-based incentives, and social support did not significantly improve medication adherence or vascular readmission outcomes for AMI survivors. Trial Registration: clinicaltrials.gov Identifier: NCT01800201.

Predicting 1-Year Statin Adherence Among Prevalent Users: A Retrospective Cohort Study.

BACKGROUND: Attempts to predict who is at risk of future nonadherence have largely focused on predictions at the time of therapy initiation; however, these users are only a small proportion of all patients on therapy at any point in time. Methods to predict nonadherence for established medication users, which have not been previously described in the literature, would be helpful to guide efforts to enhance the use of evidence-based therapies. OBJECTIVE: To test approaches for adherence prediction among prevalent statin users, namely the use of short-term filling behavior, investigator-specified predictors from medical and pharmacy administrative claims, and the empirical selection of potential predictors using the high-dimensional propensity score variable selection algorithm. METHODS: Medical and prescription claims data from a large national health insurer were used to create a cohort of patients who filled statin medication prescriptions in January 2012. We defined 6 groups of adherence predictors and estimated 10 main models to predict medication adherence in the full cohort. The same was done for the population stratified based on the days supply of the index statin prescription (≤ 30 days vs. > 30 days). RESULTS: The study cohort consisted of 93,777 individuals, 58.4% of which were adherent to statins during follow-up. The use of 3 pre-index adherence predictors alone achieved a c-statistic of 0.70. Investigator-specified and empirically selected pharmacy, medical, and demographic variables did substantially worse (0.57-0.60). The use of 3 indicators of post-index adherence achieved a higher c-statistic than the best-performing model using pre-index information (0.74 vs. 0.72). The addition of 3 pre-index adherence predictors further improved discrimination (0.78). CONCLUSIONS: This analysis demonstrated the ability to predict adherence among medication users using filling behavior before and immediately after an index prescription fill. DISCLOSURES: This work was supported by an unrestricted grant from CVS Health to Brigham and Women's Hospital. Shrank, Brennan, and Matlin were employees and shareholders at CVS Health at the time of this manuscript preparation; they report no financial interests in products or services that are related to the subject of the manuscript. Franklin has received consulting fees from Aetion. Chourdry has received grants from the National Heart, Lung, and Blood Institute, PhRMA Foundation, Merck, Sanofi, AstraZeneca, and MediSafe. Spettell is an employee of, and shareholder in, Aetna. The other authors have nothing to disclose. Krumme, Choudhry, Tong, and Franklin contributed to the study design, interpretation of results, and manuscript drafting. Tong prepared and analyzed the data. Isaman, Spettell, Shrank, Brennan, and Matlin provided interpretation of results and critical manuscript revisions.

Association Between Patient-Centered Medical Homes and Adherence to Chronic Disease Medications: A Cohort Study.

BACKGROUND: Despite the widespread adoption of patient-centered medical homes into primary care practice, the evidence supporting their effect on health care outcomes has come primarily from geographically localized and well-integrated health systems. OBJECTIVE: To assess the association between medication adherence and medical homes in a national patient and provider population, given the strong ties between adherence to chronic disease medications and health care quality and spending. DESIGN: Retrospective cohort study. SETTING: Claims from a large national health insurer. PATIENTS: Patients initiating therapy with common medications for chronic diseases (diabetes, hypertension, and hyperlipidemia) between 2011 and 2013. MEASUREMENTS: Medication adherence in the 12 months after treatment initiation was compared among patients cared for by providers practicing in National Committee for Quality Assurance-recognized patient-centered medical homes and propensity score-matched control practices in the same Primary Care Service Areas. Linear mixed models were used to examine the association between medical homes and adherence. RESULTS: Of 313 765 patients meeting study criteria, 18 611 (5.9%) received care in patient-centered medical homes. Mean rates of adherence were 64% among medical home patients and 59% among control patients. Among 4660 matched control and medical home practices, medication adherence was significantly higher in medical homes (2.2% [95% CI, 1.5% to 2.9%]). The association between medical homes and better adherence did not differ significantly by disease state (diabetes, 3.0% [CI, 1.5% to 4.6%]; hypertension, 3.2% [CI, 2.2% to 4.2%]; hyperlipidemia, 1.5% [CI, 0.6% to 2.5%]). LIMITATION: Clinical outcomes related to medication adherence were not assessed. CONCLUSION: Receipt of care in a patient-centered medical home is associated with better adherence, a vital measure of health care quality, among patients initiating treatment with medications for common high-cost chronic diseases. PRIMARY FUNDING SOURCE: CVS Health.

Longitudinal Patterns of Spending Enhance the Ability to Predict Costly Patients: A Novel Approach to Identify Patients for Cost Containment.

BACKGROUND: With rising health spending, predicting costs is essential to identify patients for interventions. Many of the existing approaches have moderate predictive ability, which may result, in part, from not considering potentially meaningful changes in spending over time. Group-based trajectory modeling could be used to classify patients into dynamic long-term spending patterns. OBJECTIVES: To classify patients by their spending patterns over a 1-year period and to assess the ability of models to predict patients in the highest spending trajectory and the top 5% of annual spending using prior-year predictors. SUBJECTS: We identified all fully insured adult members enrolled in a large US nationwide insurer and used medical and prescription data from 2009 to 2011. RESEARCH DESIGN: Group-based trajectory modeling was used to classify patients by their spending patterns over a 1-year period. We assessed the predictive ability of models that categorized patients in the top fifth percentile of annual spending and in the highest spending trajectory, using logistic regression and split-sample validation. Models were estimated using investigator-specified variables and a proprietary risk-adjustment method. RESULTS: Among 998,651 patients, in the best-performing model, prediction was strong for patients in the highest trajectory group (C-statistic: 0.86; R: 0.47). The C-statistic of being in the top fifth percentile of spending in the best-performing model was 0.82 (R: 0.26). Approaches using nonproprietary investigator-specified methods performed almost as well as other risk-adjustment methods (C-statistic: 0.81 vs. 0.82). CONCLUSIONS: Trajectory modeling may be a useful way to predict costly patients that could be implementable by payers to improve cost-containment efforts.

Evaluating Cardiovascular Health Disparities Using Estimated Race/Ethnicity: A Validation Study.

BACKGROUND: Methods of estimating race/ethnicity using administrative data are increasingly used to examine and target disparities; however, there has been no validation of these methods using clinically relevant outcomes. OBJECTIVE: To evaluate the validity of the indirect method of race/ethnicity identification based on place of residence and surname for assessing clinically relevant outcomes. DATA SOURCES: A total of 2387 participants in the Post-MI Free Rx Event and Economic Evaluation (MI FREEE) trial who had both self-reported and Bayesian Improved Surname Geocoding method (BISG)-estimated race/ethnicity information available. STUDY DESIGN: We used tests of interaction to compare differences in the effect of providing full drug coverage for post-MI medications on adherence and rates of major vascular events or revascularization for white and nonwhite patients based upon self-reported and indirect racial/ethnic assignment. RESULTS: The impact of full coverage on clinical events differed substantially when based upon self-identified race (HR=0.97 for whites, HR=0.65 for nonwhites; interaction P-value=0.05); however, it did not differ among race/ethnicity groups classified using indirect methods (HR=0.87 for white and nonwhites; interaction P-value=0.83). The impact on adherence was the same for self-reported and BISG-estimated race/ethnicity for 2 of the 3 medication classes studied. CONCLUSIONS: Quantitatively and qualitatively different results were obtained when indirectly estimated race/ethnicity was used, suggesting that these techniques may not accurately describe aspects of race/ethnicity related to actual health behaviors.

Leveraging remote behavioral health interventions to improve medical outcomes and reduce costs.

OBJECTIVE: The dramatic rise in healthcare expenditures calls for innovative and scalable strategies to achieve measurable, near-term improvements in health. Our objective was to determine whether a remotely delivered behavioral health intervention could improve medical health, reduce hospital admissions, and lower cost of care for individuals with a recent cardiovascular event. STUDY DESIGN: This retrospective observational cohort study included members of a commercial health plan referred to participate in AbilTo's Cardiac Health Program. AbilTo is a national provider of telehealth, behavioral change programs for high risk medical populations. METHODS: The program is an 8-week behavioral health intervention delivered by a licensed clinical social worker and a behavioral coach via phone or secure video. RESULTS: Among the 201 intervention and 180 comparison subjects, the study found that program participants had significantly fewer all-cause hospital admissions in 6 months (293 per 1000 persons/year vs 493 per 1000 persons/year in the comparison group) resulting in an adjusted percent reduction of 31% (P = .03), and significantly fewer total hospital days (1455 days per 1000 persons/year vs 3933 per 1000 persons/year) with an adjusted percent decline of 48% (P = .01). This resulted in an overall savings in the cost of care even after accounting for total program costs. CONCLUSIONS: Successful patient engagement in a national, remotely delivered behavioral health intervention can reduce medical utilization in a targeted cardiac population. A restored focus on tackling barriers to behavior change in order to improve medical health is an effective, achievable population health strategy for reducing health costs in the United States.

Quality of care at retail clinics for 3 common conditions.

OBJECTIVES: Evaluation of quality of care across retail clinics in a geographically diverse population has not been undertaken to date. We sought to evaluate and compare the quality of care for otitis media, pharyngitis, and urinary tract infection received in retail medical clinics in CVS pharmacies ("MinuteClinics" [MCs]), ambulatory care facilities (ACFs), and emergency departments (EDs). METHODS: We used 14 measures constructed from RAND Corporation's Quality Assurance Tools and guidelines from the American Academy of Pediatrics, the American Academy of Family Physicians, and the Infectious Diseases Society of America. Our cohort was drawn from Aetna medical and prescription claims, 2009-2012. Members were matched on visit date, condition, and propensity score. Generalized estimating equations were used to compare quality across clinic type, overall, and by index condition. RESULTS: We matched 75,886 episodes of care, of which 20,153 were eligible for at least 1 quality measure. MCs performed better than EDs and ACFs in 7 measures. In a multivariable model, MCs performed better than ACFs and EDs across all quality measures ([OR 0.42; 95% CI, 0.40-0.45; P < .0001; ACF vs MC] [OR 0.29; 95% CI, 0.27-0.31; P < .0001; ED vs MC]). Results for each condition were significant at P < .0001. CONCLUSIONS: Quality of care for these conditions based on widely accepted objective measures was superior in MinuteClinics compared with ACFs and EDs.

Initial choice of oral glucose-lowering medication for diabetes mellitus: a patient-centered comparative effectiveness study.

IMPORTANCE: Although many classes of oral glucose-lowering medications have been approved for use, little comparative effectiveness evidence exists to guide initial selection of therapy for diabetes mellitus. OBJECTIVE: To determine the effect of initial oral glucose-lowering agent class on subsequent need for treatment intensification and 4 short-term adverse clinical events. DESIGN, SETTING, AND PARTICIPANTS: This study was a retrospective cohort study of patients who were fully insured members of Aetna (a large national health insurer) who had been prescribed an oral glucose-lowering medication from July 1, 2009, through June 30, 2013. Individuals newly prescribed an oral glucose-lowering agent who filled a second prescription for a medication in the same class and with a dosage at or above the World Health Organization's defined daily dose within 90 days of the end-of-day's supply of the first prescription were studied. Individuals with interim prescriptions for other oral glucose-lowering medications were excluded. EXPOSURES: Initiation of treatment with metformin, a sulfonylurea, a thiazolidinedione, or a dipeptidyl peptidase 4 inhibitor. MAIN OUTCOMES AND MEASURES: Time to addition of a second oral agent or insulin, each component separately, hypoglycemia, other diabetes-related emergency department visits, and cardiovascular events. RESULTS: A total of 15 516 patients met the inclusion criteria, of whom 8964 (57.8%) started therapy with metformin. In unadjusted analyses, use of medications other than metformin was significantly associated with an increased risk of adding a second oral agent only, insulin only, and a second agent or insulin (P < .001 for all). In propensity score and multivariable-adjusted Cox proportional hazards models, initiation of therapy with sulfonylureas (hazard ratio [HR], 1.68; 95% CI, 1.57-1.79), thiazolidinediones (HR, 1.61; 95% CI, 1.43-1.80), and dipeptidyl peptidase 4 inhibitors (HR, 1.62; 95% CI, 1.47-1.79) was associated with an increased hazard of intensification. Alternatives to metformin were not associated with a reduced risk of hypoglycemia, emergency department visits, or cardiovascular events. CONCLUSIONS AND RELEVANCE: Despite guidelines, only 57.8% of individuals began diabetes treatment with metformin. Beginning treatment with metformin was associated with reduced subsequent treatment intensification, without differences in rates of hypoglycemia or other adverse clinical events. These findings have significant implications for quality of life and medication costs.

Patterns of initiation of oral anticoagulants in patients with atrial fibrillation- quality and cost implications.

BACKGROUND: Dabigatran, rivaroxaban, and apixaban have been approved for use in patients with atrial fibrillation based upon randomized trials demonstrating their comparable or superior efficacy and safety relative to warfarin. Little is known about their adoption into clinical practice, whether utilization is consistent with the controlled trials on which their approval was based, and how their use has affected health spending for patients and insurers. METHODS: We used medical and prescription claims data from a large insurer to identify patients with nonvalvular atrial fibrillation who were prescribed an oral anticoagulant in 2010-2013. We plotted trends in medication initiation over time, assessed corresponding insurer and patient out-of-pocket spending, and evaluated the cumulative number and cost of anticoagulants. We identified predictors of novel anticoagulant initiation using multivariable logistic models. Finally, we estimated the difference in total drug expenditures over 6 months for patients initiating warfarin versus a novel anticoagulant. RESULTS: There were 6893 patients with atrial fibrillation that initiated an oral anticoagulant during the study period. By the end of the study period, novel anticoagulants accounted for 62% of new prescriptions and 98% of anticoagulant-related drug costs. Female sex, lower household income, and higher CHADS2, CHA2DS2-VASC, and HAS-BLED scores were significantly associated with lower odds of receiving a novel anticoagulant (P <.001 for each). Average combined patient and insurer anticoagulant spending in the first 6 months after initiation was more than $900 greater for patients initiating a novel anticoagulant. CONCLUSIONS: This study demonstrates rapid adoption of novel anticoagulants into clinical practice, particularly among patients with lower CHADS2 and HAS-BLED scores, and high health care cost consequences. These findings provide important directions for future comparative and cost-effectiveness research.

Early detection of poor adherers to statins: applying individualized surveillance to pay for performance.

BACKGROUND: Medication nonadherence costs $300 billion annually in the US. Medicare Advantage plans have a financial incentive to increase medication adherence among members because the Centers for Medicare and Medicaid Services (CMS) now awards substantive bonus payments to such plans, based in part on population adherence to chronic medications. We sought to build an individualized surveillance model that detects early which beneficiaries will fall below the CMS adherence threshold. METHODS: This was a retrospective study of over 210,000 beneficiaries initiating statins, in a database of private insurance claims, from 2008-2011. A logistic regression model was constructed to use statin adherence from initiation to day 90 to predict beneficiaries who would not meet the CMS measure of proportion of days covered 0.8 or above, from day 91 to 365. The model controlled for 15 additional characteristics. In a sensitivity analysis, we varied the number of days of adherence data used for prediction. RESULTS: Lower adherence in the first 90 days was the strongest predictor of one-year nonadherence, with an odds ratio of 25.0 (95% confidence interval 23.7-26.5) for poor adherence at one year. The model had an area under the receiver operating characteristic curve of 0.80. Sensitivity analysis revealed that predictions of comparable accuracy could be made only 40 days after statin initiation. When members with 30-day supplies for their first statin fill had predictions made at 40 days, and members with 90-day supplies for their first fill had predictions made at 100 days, poor adherence could be predicted with 86% positive predictive value. CONCLUSIONS: To preserve their Medicare Star ratings, plan managers should identify or develop effective programs to improve adherence. An individualized surveillance approach can be used to target members who would most benefit, recognizing the tradeoff between improved model performance over time and the advantage of earlier detection.

Risk of Guillain-Barré syndrome after meningococcal conjugate vaccination.

PURPOSE: A new meningococcal conjugate vaccine (MCV4) was introduced in 2005. Shortly after, case reports of Guillain-Barré syndrome (GBS), a serious demyelinating disease, began to be reported to the Vaccine Adverse Event Reporting System. In 2006, the Centers for Disease Control and Prevention and the Food and Drug Administration requested the evaluation of GBS risk after MCV4 vaccination. We conducted a study to assess the risk of GBS after MCV4 vaccination using health plan administrative and claims data together with the review of primary medical records of potential cases. METHODS: Retrospective cohort study among 12.6 million 11- to 21-year-old members of five US health plans with a total membership of 50 million. Automated enrollment and medical claims data from March 2005 through August 2008 were used to identify the population, the vaccinations administered, and the medical services associated with possible GBS. Medical records were reviewed and adjudicated by a neurologist panel to confirm cases of GBS. The study used distributed data analysis methods that minimized sharing of protected health information. RESULTS: We confirmed 99 GBS cases during 18,322,800 person-years (5.4/1,000,000 person-years). More than 1.4 million MCV4 vaccinations were observed. No confirmed cases of GBS occurred within 6 weeks after vaccination. The upper 95% CI for the attributable risk of GBS associated with MCV4 is estimated as 1.5 cases per 1,000,000 doses. CONCLUSIONS: Among members of five US health plans, MCV4 vaccination was not associated with increased GBS risk.

Use and overuse of left ventriculography.

BACKGROUND: Left ventriculography provided the first imaging of left ventricular function and was historically performed as part of coronary angiography despite a small but significant risk of complications. Because modern noninvasive imaging techniques are more accurate and carry smaller risks, the routine use of left ventriculography is of questionable utility. We sought to analyze the frequency that left ventriculography was performed during coronary angiography in patients with and without a recent alternative assessment of left ventricular function. METHODS: We performed a retrospective analysis of insurance claims data from the Aetna health care benefits database including all adults who underwent coronary angiography in 2007. The primary outcome was the concomitant use of left ventriculography during coronary angiography. RESULTS: Of 96,235 patients who underwent coronary angiography, left ventriculography was performed in 78,705 (81.8%). Use of left ventriculography was high in all subgroups, with greatest use in younger patients, those with a diagnosis of coronary disease, and those in the Southern United States. In the population who had undergone a very recent ejection fraction assessment by another modality (within 30 days) and who had had no intervening diagnosis of new heart failure, myocardial infarction, hypotension, or shock (37,149 patients), left ventriculography was performed in 32,798 patients (88%)-a rate higher than in the overall cohort. CONCLUSIONS: Left ventriculography was performed in most coronary angiography cases and often when an alternative imaging modality had been recently completed. New clinical practice guidelines should be considered to decrease the overuse of this invasive test.

Telemonitoring with case management for seniors with heart failure.

OBJECTIVE: To assess the impact of supplementing nurse case management with Internet-connected telemonitoring on clinical outcomes in an elderly heart failure (HF) population. STUDY DESIGN: Randomized clinical trial allocating high-risk HF subjects to the telehealth system with case management (THCM) versus case management (CM) alone. METHODS: Medicare Advantage members with HF and recent hospitalization were randomized to THCM or CM. Consenting participants received THCM for 6 months or the health plan's usual Medicare specialized CM as long as deemed necessary. The primary outcome measure was a composite of all-cause hospitalization, ED visit, or death. Because only a subset of those who were randomized consented and participated, the strategies were evaluated as-treated rather than by intention-to-treat, with multivariate adjustment in logistic regression models for confounding introduced by postrandomization exclusions. RESULTS: The treated sample size was 164 subjects in THCM and 152 in CM. Treatment arms did not differ significantly for the primary composite outcome (45% for THCM vs 40% for CM, relative risk 1.18; P = .22). Telehealth alerts prompted frequent telephonic contact, increasing THCM case managers' workload. The participant population overall had 42% fewer inpatient days during the intervention period compared with the previous year. CONCLUSIONS: Despite effective implementation of an Internet-based telehealth intervention in an elderly HF population, there was no discernible impact on overall morbidity or mortality. Notably, limited postrandomization participation decreased power to detect a difference. The reduction in days hospitalized for trial participants overall underscores the benefit of CM for such HF patients.

Opportunities to improve the quality of care for advanced illness.

Many studies describe a sizable chasm between the care Americans consider optimal for advanced illness and what we actually experience. Aggressive or curative measures may be pursued to the exclusion of comfort, pain relief, and psychosocial support. We briefly describe a care management program that gives people culturally sensitive supportive information, to make informed choices and obtain palliative services in a timely manner. In the sample population, more members chose hospice care; acute care utilization declined. It is possible to assist Americans with advanced illness and remove barriers to selecting hospice care, if that is their choice, without adverse financial impact.

A comprehensive case management program to improve palliative care.

OBJECTIVE: The objective of this study was to evaluate the impact of comprehensive case management (CM) and expanded insurance benefits on use of hospice and acute health care services among enrollees in a national health plan. STUDY DESIGN: Retrospective cohort design with three intervention groups, each matched to a historical control group. METHODS: Intervention groups were health plan enrollees who died after 2004: 3491 commercial enrollees with CM; 387 commercial enrollees with CM and expanded hospice benefits; and 447 Medicare enrollees with CM. Control groups consisted of enrollees who died in 2004 prior to the start of the palliative care CM program. The main outcomes measured were the proportion using hospice, mean number of hospice days, and number of inpatient days measured through medical claims. RESULTS: Hospice use increased for all groups receiving CM compared to the respective control groups: from 30.8% to 71.7% (p < 0.0001) for commercial members with CM and from 27.9% to 69.8% (p < 0.0001) for Commercial members with CM and enhanced hospice benefits. Mean hospice days increased from 15.9 to 28.6 days (p < .0001) and from 21.4 to 36.7 days (p < 0.0001) for these groups, respectively. Inpatient stays were lower for all groups receiving CM services compared to their respective control groups. CONCLUSIONS: Comprehensive health plan CM and more liberal hospice benefit design may help to break down barriers to hospice use; benefits might be liberalized within the context of such case management programs without adverse impact on total costs.

A distributed research network model for post-marketing safety studies: the Meningococcal Vaccine Study.

PURPOSE: We describe a multi-center post-marketing safety study that uses distributed data methods to minimize the need for covered entities to share protected health information (PHI). Implementation has addressed several issues relevant to creation of a large scale post-marketing drug safety surveillance system envisioned by the FDA's Sentinel Initiative. METHODS: This retrospective cohort study of Guillain-Barré syndrome (GBS) following meningococcal conjugate vaccination incorporates the data and analytic expertise of five research organizations closely affiliated with US health insurers. The study uses administrative claims data, plus review of full text medical records to adjudicate the status of individuals with a diagnosis code for GBS (ICD9 357.0). A distributed network approach is used to create the analysis files and to perform most aspects of the analysis, allowing nearly all of the data to remain behind institutional firewalls. Pooled analysis files transferred to a central site will contain one record per person for approximately 0.2% of the study population, and contain PHI limited to the month and year of GBS onset for cases or the index date for matched controls. RESULTS: The first planned data extraction identified over 9 million eligible adolescents in the target age range of 11-21 years. They contributed an average of 14 months of eligible time on study over 27 months of calendar time. MCV4 vaccination coverage levels exceeded 20% among 17-18-year olds and 16% among 11-13 and 14-16-year-old age groups by the second quarter of 2007. CONCLUSION: This study demonstrates the feasibility of using a distributed data network approach to perform large scale post-marketing safety analyses and is scalable to include additional organizations and data sources. We believe these results can inform the development of a large national surveillance system.

Do managed care plans' tiered networks lead to inequities in care for minority patients?

This study examined whether specialists designated as meeting efficiency thresholds in an insurance company's performance network were less likely than non-designated specialists to treat minority patients insured by that company. Claims data were used to identify patients treated by specialists. Claimants' race/ethnicity status was self-reported to the insurer at enrollment. In large part, minority patients appeared to be evenly distributed across the performance network, with the exception of Asian/Pacific Islanders, who appeared to be more likely to be treated by nondesignated physicians than by designated "good-performing" specialists.