Fecal microbiota transplantation and Clostridioides difficile infection among privately insured patients in the United States.

BACKGROUND: Clostridioides difficile infection (CDI) may be rising in severity in the US over the past decade and its treatment landscape is changing given the recent adoption of fecal microbiota transplantation (FMT) METHODS: We built a retrospective observational cohort using a database of a national care-plan containing medical claims of over 50 million individuals between 2008 and 2019. We used International Classification of Disease (ICD) and prescription data to identify patients with CDI. We estimated trends in disease burden and FMT use, and evaluated complications post FMT using a phenome-wide association approach. RESULTS: We identified 38,396 patients with CDI; the median age was 60 years (IQR 45-74) and 60% were female (n = 23,374). The rate of CDI increased from 33.4 to 69.46 cases per 100,000 person-years between 2008 and 2015, and stabilized from 2015 to 2019 (increase of 4.77 cases per 100,000 person-years per year, 95% CI 3.55-5.98 prior to 2015 vs. 2.01 95% CI - 10.16 to 14.18 after 2015). Of the 7715 patients with recurrent CDI, 407 patients (5%) underwent FMT. Gastrointestinal complications were increased within 1 month post FMT (OR 99.60, p < 0.001). Sepsis was identified in two individuals (0.49% 95% CI 0.05-1.7%) within the first month post FMT. The risk of CDI recurrence significantly decreased post FMT compared with anti-CDI antibiotics in the multivariable model (raw-recurrence rate 9.8% vs 36%, aOR = 0.21, 95% CI 0.12-0.53, p < 0.001). CONCLUSION: We show that FMT is strongly associated with a decrease in CDI recurrence compared with the usual care with generally mild complications for up to 2 years.

Dental services use before and after inpatient admission among privately insured adults in the United States.

BACKGROUND: Oral health has been connected to worse outcomes among hospitalized patients, but access to oral health care services in the hospital setting is limited. It is unknown how a hospital admission affects subsequent dental services use. METHODS: The authors conducted a retrospective analysis of insurance claims data from a national private insurer. Patients were included if they were admitted to the hospital and had visited a dentist at least once in the year before or after admission. Total number of dental visits, as well as Code on Dental Procedures and Nomenclature codes associated with these visits in the year before and after a hospital stay, patient demographic characteristics, hospital admission diagnosis, and length of stay were recorded. Differences in dental services use before and after the hospital stay were calculated. RESULTS: In total, 107,116 patients met inclusion criteria. There were fewer dental visits after admission (mean [standard deviation {SD}] 1.6 [1.7] than before admission (mean [SD] 1.9 [1.8]; P < .0001). Fewer procedures were recorded in the year after discharge (mean [SD] 7.0 [11.4] total Code on Dental Procedures and Nomenclature codes versus 8.5 [12.5] in the year before admission; P < .0001). The number of diagnostic and restorative services delivered was higher after admission, and the number of periodontic, endodontic, oral surgery, and prosthodontic services decreased (overall Pearson χ2, P < .0001). CONCLUSIONS: Patients are less likely to visit a dentist after a hospital stay, although impact on oral health is unknown. PRACTICAL IMPLICATIONS: Hospitalization may contribute to already existing oral health disparities. Hospital teams and dentists should work together to enhance access to oral health care after hospital admission.

Healthcare spending and utilization for pediatric Irritable Bowel Syndrome in a commercially insured population.

BACKGROUND: Pediatric Irritable Bowel Syndrome (IBS) is common and can be associated with disabling gastrointestinal symptoms. Comprehensive data regarding utilization and cost of pediatric IBS are lacking. Our aim was to determine the annual all-cause spending and healthcare utilization in pediatric IBS. METHODS: Cross-sectional cohort study using a national claims database of commercially insured individuals. 932,592 members, age 8-18 years, were included. Members were selected based on PheWas codes and continuous enrollment in 2014. Linear and binomial regression models were used to calculate healthcare spending and compare comorbidities between IBS subjects and controls. KEY RESULTS: 1215 members with claims for IBS (68.4% female) and 931,377 controls (55.7% female) were included. Mean age was 15.03 ± 2.83 (median 16) years in the IBS group and 13.14 ± 3.12 (median 13) years in controls. Mental health and chronic pain comorbidities were more prevalent in the IBS cohort. Healthcare spending: The mean annual all-cause incremental spending of members with IBS was $6,364.60 compared to controls when adjusting for age and gender. Healthcare utilization: Members with IBS had increased healthcare utilization including higher rates of inpatient, outpatient, and emergency room visits, and higher rates of health service utilization including medical care, radiology/laboratory services, surgery, anesthesia, mental health, and physical therapy. General pediatrics was more frequently consulted by controls. All subspecialty consultations, with the exception of dental medicine and endocrinology, were sought more frequently by IBS patients. CONCLUSION: Patients with IBS incur significant annual spending through increased healthcare utilization.

Measuring health-care delays among privately insured patients with tuberculosis in the USA: an observational cohort study.

BACKGROUND: A high index of suspicion is needed to initiate appropriate testing for tuberculosis due to its protean symptoms, yet health-care providers in low-incidence settings are becoming less familiar with the disease as rates decline. We aimed to estimate delays in tuberculosis diagnosis and treatment at the US national level between 2008 and 2016. METHODS: In this retrospective observational cohort study, we repurposed private insurance claims data provided by Aetna (Connecticut, USA), to measure health-care delays in tuberculosis diagnosis in the USA in 2008-16. Active tuberculosis was determined by diagnosis codes and the filling of anti-tuberculosis treatment prescriptions. Health-care delays were defined as the duration between the first health-care visit for a tuberculosis symptom and the initiation of anti-tuberculosis treatment. We assessed if delays varied over time, and by patient and system variables, using multivariable regression. We estimated household tuberculosis transmission and respiratory complications after treatment initiation. FINDINGS: We confirmed 738 active tuberculosis cases (incidence 1·45 per 100 000 person-years) with a median health-care delay of 24 days (IQR 10-45). Multivariable regression analysis showed that longer delays were associated with older age (8·4% per 10 year increase [95% CI 4·0 to 13·1]; p<0·0086) and non-HIV immunosuppression (19·2% [15·1 to 60·0]; p=0·0432). Presenting with three or more symptoms was associated with a shorter delay (-22·5% [-39·1 to -2·0]; p=0·0415), relative to presenting with one symptom, as did use of chest imaging (-24·9% [-37·9 to -8·9]; p<0·0098), tuberculosis nucleic acid amplification tests (-19·2% [-32·7 to -3·1]; p=0·0241), and care by a tuberculosis specialist provider (-17·2% [-33·1 to -22·3]; p<0·0087). Longer delays were associated with an increased rate of respiratory complications even after controlling for patient characteristics, and an increased rate of secondary tuberculosis among dependents. INTERPRETATION: In the USA, the median health-care delay for privately insured patients with tuberculosis exceeds WHO-recommended levels of 21 days (3 weeks). The results suggest the need for health-care provider education on best practices in tuberculosis diagnosis, including the use of molecular tests and the maintenance of a high index of suspicion for the disease. FUNDING: US National Institutes of Health.

Emergency department visits for dental problems among adults with private dental insurance: A national observational study.

OBJECTIVE: Dental insurance may be a protective factor in reducing unnecessary emergency department (ED) use for nontraumatic dental pain. The purpose of this study was to 1) characterize patient demographics and identify risk factors associated with ED utilization for dental problems among individuals dually enrolled in medical and dental insurance and 2) investigate antibiotic and opioid prescription patterns among these patients following discharge. Further study of this unique population may provide insight into other causes of unmet dental need beyond lack of dental insurance. METHODS: Claims data from a large national managed health care plan from 2015 to 2018 were used to evaluate ED use for dental problems in patients with synchronous medical and dental insurance. National counts for ED visits, total visit costs, primary diagnoses, and outpatient treatments for antibiotics and opioids were assessed. Multivariable regression was used to assess any associated demographic and health-related variables. RESULTS: 1492 unique patients were admitted to the ED for dental pain and 429,376 unique patients presented for other symptoms. Utilization rates for nontraumatic dental pain were estimated to be 0.4% of all ED visits, with an average cost of $1487 per visit. Within three days following discharge from the ED, 58% of patients filled an opioid prescription and 38% filled an antibiotic prescription. Patients who presented for dental ED pain were more likely to be younger, live in a ZIP code with a lower median household income, have more medical comorbidities, and receive fewer preventive dental procedures within the prior year. CONCLUSION: Our findings demonstrate a low rate of ED utilization for nontraumatic dental pain among dentally insured patients and highlight the protective value of prior dental visits for reducing ED use. Given high rates of antibiotic and opioid prescription fill following discharge, comprehensive ED guidelines regarding appropriate antibiotic and opioid treatment pathways may be helpful to provide more definitive care to patients with dental insurance.

A fast divide-and-conquer sparse Cox regression.

We propose a computationally and statistically efficient divide-and-conquer (DAC) algorithm to fit sparse Cox regression to massive datasets where the sample size $n_0$ is exceedingly large and the covariate dimension $p$ is not small but $n_0\gg p$. The proposed algorithm achieves computational efficiency through a one-step linear approximation followed by a least square approximation to the partial likelihood (PL). These sequences of linearization enable us to maximize the PL with only a small subset and perform penalized estimation via a fast approximation to the PL. The algorithm is applicable for the analysis of both time-independent and time-dependent survival data. Simulations suggest that the proposed DAC algorithm substantially outperforms the full sample-based estimators and the existing DAC algorithm with respect to the computational speed, while it achieves similar statistical efficiency as the full sample-based estimators. The proposed algorithm was applied to extraordinarily large survival datasets for the prediction of heart failure-specific readmission within 30 days among Medicare heart failure patients.

Variation in dental services by rurality among privately insured adults in the United States.

OBJECTIVES: Rurality is associated with reduced dental access and worse oral health outcomes. It is unknown whether there is variation in dental services received by rural adults who visit a dentist. METHODS: This was a retrospective analysis of claims data from a large private insurer. All individuals who had at least one dental visit in 2018 were included. Patient demographics, whether or not a patient's ZIP code was rural as defined by the Federal Office of Rural Health Policy, as well as ZIP code demographics were collected. Differences in the frequency of dental services received were evaluated using χ2 tests. Multilevel logistic regressions were used to evaluate the individual and ZIP code-level correlates of receiving a preventive dental procedure, a tooth extraction, or a denture-related dental procedure. RESULTS: Rates of preventive, oral and maxillofacial surgery, and denture-related procedures were higher among rural adults. Accounting for individual age and gender, and ZIP code average income and dentist density, rural dwellers were more likely to receive a preventive procedure [odds ratio (OR) 1.15, P < 0.0001] or tooth extraction (OR 1.08, P < 0.0001), and less likely to have a denture-related procedure (OR 0.94, P = 0.015) compared to nonrural dwellers. Female gender was the strongest predictor of receiving a preventive procedure (OR 1.30, P < 0.0001). CONCLUSIONS: Even among privately insured individuals with known access to dental care, rurality was associated with significant differences in the frequency of various dental procedures. Rural dental patients may have higher needs for oral surgical procedures, even when they have access to preventive care.

Dental Services Utilization by Rurality Among Privately Insured Children in the United States.

Purpose: The purpose of this study was to determine differences in dental services received between rural and urban residents in a national sample of children with private insurance. Methods: This was a retrospective study of deidentified claims data from a major national private insurer. Children younger than 18 years of age enrolled throughout 2018 and who had at least one visit to the dentist that year were included. Differences in the frequency of dental procedures received were determined by chi-square tests. Multilevel logistic regression was used to evaluate the effect of individual-level and ZIP Code-level covariates, including rurality, on the odds of receiving a preventive dental service or having a tooth extracted. Results: A total of 603,064 children, with an average age of 10.2±4.4 (standard deviation) years, visited a dentist, and 6.52 percent lived in a rural area. In a multilevel logistic regression correcting for patient age, patient gender, ZIP Code average income, and dental provider density, rurality was positively associated with receiving a tooth extraction (odds ratio [OR] equals 1.06; P<0.001) and negatively associated with receiving a preventive service (OR equals 0.85; P<0.001). Female gender was a negative predictor of preventive services and a predictor of having a tooth extracted. Conclusion: Children living in rural areas had reduced rates of preventive dental care and higher rates of tooth extraction than their nonrural counterparts.

Dental Practice Integration into Primary Care: A Microsimulation of Financial Implications for Practices.

Given the widespread lack of access to dental care for many vulnerable Americans, there is a growing realization that integrating dental and primary care may provide comprehensive care. We sought to model the financial impact of integrating dental care provision into a primary care practice. A microsimulation model was used to estimate changes in net revenue per practice by simulating patient visits to a primary dental practice within primary care practices, utilizing national survey and un-identified claims data from a nationwide health insurance plan. The impact of potential changes in utilization rates and payer distributions and hiring additional staff was also evaluated. When dental care services were provided in the primary care setting, annual net revenue changes per practice were -$92,053 (95% CI: -93,054, -91,052) in the first year and $104,626 (95% CI: 103,315, 105,316) in subsequent years. Net revenue per annum after the first year of integration remained positive as long as the overall utilization rates decreased by less than 25%. In settings with a high proportion of publicly insured patients, the net revenue change decreased but was still positive. Integrating primary dental and primary care providers would be financially viable, but this viability depends on demands of dental utilization and payer distributions.

Association of income inequality with orthodontic treatment use.

BACKGROUND: Income inequality has been associated with worse oral health outcomes and reduced dental care use. It is unknown whether income inequality may motivate people to seek orthodontic treatment. METHODS: This was a logistic mixed-effects model of deidentified claims from a private insurer in the United States with enrolled members having at least 1 orthodontic visit in the calendar year as the dependent variable. Total number of dental visits, age, and sex were individual-level covariates. Median household income, Gini coefficient, female population proportion, number of practicing dentists and orthodontists, population size, and population density were zip code-level covariates. RESULTS: A total of 1,860,709 people had at least 1 orthodontic claim. Adjusting for population demographics, the Gini index was significantly positively associated with orthodontic use for children but not for adults (odds ratio, 1.69 for children; P < .0001). Being female was the strongest predictor of orthodontic use for adults and was a significant predictor of use for children (odds ratio, 1.50 and 1.45, respectively; P < .0001). CONCLUSIONS: The Gini index is associated with orthodontic use in children in a privately insured population. Individual characteristics are more predictive of orthodontic use among privately insured adults. PRACTICAL IMPLICATIONS: Demographic and economic traits of communities can affect oral health care use; effects on orthodontic use may be more dramatic than on other forms of oral health care.

Estimates of healthcare spending for preterm and low-birthweight infants in a commercially insured population: 2008-2016.

The growth in healthcare spending is an important topic in the United States, and preterm and low-birthweight infants have some of the highest healthcare expenditures of any patient population. We performed a retrospective cohort study of spending in this population using a large, national claims database of commercially insured individuals. A total of 763,566 infants with insurance coverage through Aetna, Inc. for the first 6 months of post-natal life were included, and received approximately $8.4 billion (2016 USD) in healthcare services. Infants with billing codes indicating preterm status (<37 weeks, n = 50,511) incurred medical expenditures of $76,153 on average, while low-birthweight status (<2500 g) was associated with average spending of $114,437. Infants born at 24 weeks gestation (n = 418) had the highest per infant average expenditures of $603,778. Understanding the drivers of variation in costs within gestational age and birthweight bands is an important target for future studies.

Pre-existing autoimmune disease and the risk of immune-related adverse events among patients receiving checkpoint inhibitors for cancer.

INTRODUCTION: Patients with pre-existing autoimmune diseases have been excluded from clinical trials of immune checkpoint inhibitors (ICIs) for cancer. Real-world evidence is necessary to understand ICI safety in this population. METHODS: Patients treated with ICIs from 2011 to 2017 were identified using data from a large health insurer. Outcomes included time to (1) any hospitalization; (2) any hospitalization with an irAE diagnosis; and (3) outpatient corticosteroid treatment. The key exposure was pre-existing autoimmune disease, ascertained within 12 months before starting ICI treatment, and defined either by strict criteria (one inpatient or two outpatient claims at least 30 days apart) or relaxed criteria only (any claim, without meeting strict criteria). RESULTS: Of 4438 ICI-treated patients, pre-existing autoimmune disease was present among 179 (4%) by strict criteria, and another 283 (6%) by relaxed criteria only. In multivariable models, pre-existing autoimmune disease by strict criteria was not associated with all-cause hospitalization (HR 1.27, 95% CI 0.998-1.62), but it was associated with hospitalization with an irAE diagnosis (HR 1.81, 95% CI 1.21-2.71) and with corticosteroid treatment (HR 1.93, 95% CI 1.35-2.76). Similarly, pre-existing autoimmune disease by relaxed criteria only was not associated with all-cause hospitalization (HR 1.11, 95% CI 0.91-1.34), but was associated with hospitalization with an irAE diagnosis (HR 1.46, 95% CI 1.06-2.01) and corticosteroid treatment (HR 1.46, 95% CI 1.13-1.88). CONCLUSION: Pre-existing autoimmune disease was not associated with time to any hospitalization after initiating ICI therapy, but it was associated with a modest increase in hospitalizations with irAE diagnoses and with corticosteroid treatment.

Systemic nature of spinal muscular atrophy revealed by studying insurance claims.

OBJECTIVE: We investigated the presence of non-neuromuscular phenotypes in patients affected by Spinal Muscular Atrophy (SMA), a disorder caused by a mutation in the Survival of Motor Neuron (SMN) gene, and whether these phenotypes may be clinically detectable prior to clinical signs of neuromuscular degeneration and therefore independent of muscle weakness. METHODS: We utilized a de-identified database of insurance claims to explore the health of 1,038 SMA patients compared to controls. Two analyses were performed: (1) claims from the entire insurance coverage window; and (2) for SMA patients, claims prior to diagnosis of any neuromuscular disease or evidence of major neuromuscular degeneration to increase the chance that phenotypes could be attributed directly to reduced SMN levels. Logistic regression was used to determine whether phenotypes were diagnosed at significantly different rates between SMA patients and controls and to obtain covariate-adjusted odds ratios. RESULTS: Results from the entire coverage window revealed a broad spectrum of phenotypes that are differentially diagnosed in SMA subjects compared to controls. Moreover, data from SMA patients prior to their first clinical signs of neuromuscular degeneration revealed numerous non-neuromuscular phenotypes including defects within the cardiovascular, gastrointestinal, metabolic, reproductive, and skeletal systems. Furthermore, our data provide evidence of a potential ordering of disease progression beginning with these non-neuromuscular phenotypes. CONCLUSIONS: Our data point to a direct relationship between early, detectable non-neuromuscular symptoms and SMN deficiency. Our findings are particularly important for evaluating the efficacy of SMN-increasing therapies for SMA, comparing the effectiveness of local versus systemically delivered therapeutics, and determining the optimal therapeutic treatment window prior to irreversible neuromuscular damage.

Doubly robust matching estimators for high dimensional confounding adjustment.

Valid estimation of treatment effects from observational data requires proper control of confounding. If the number of covariates is large relative to the number of observations, then controlling for all available covariates is infeasible. In cases where a sparsity condition holds, variable selection or penalization can reduce the dimension of the covariate space in a manner that allows for valid estimation of treatment effects. In this article, we propose matching on both the estimated propensity score and the estimated prognostic scores when the number of covariates is large relative to the number of observations. We derive asymptotic results for the matching estimator and show that it is doubly robust in the sense that only one of the two score models need be correct to obtain a consistent estimator. We show via simulation its effectiveness in controlling for confounding and highlight its potential to address nonlinear confounding. Finally, we apply the proposed procedure to analyze the effect of gender on prescription opioid use using insurance claims data.

Patients Visiting Multiple Emergency Departments: Patterns, Costs, and Risk Factors.

OBJECTIVES: We sought to characterize the population of patients seeking care at multiple emergency departments (EDs) and to quantify the proportion of all ED visits and costs accounted for by these patients. METHODS: We performed a retrospective, cohort study of deidentified insurance claims for privately insured patients with one of more ED visits between 2010 and 2016. We measured the number of EDs visited by each patient and determined the overall proportion of all ED visits and ED costs accounted for by patients who visit multiple EDs. We identified factors associated with visiting multiple EDs. RESULTS: A total of 8,651,716 patients made 16,390,676 ED visits over the study period, accounting for $26,102,831,740 in ED costs. A significant minority (20.5%) of patients visited more than one ED over the study period. However, these patients accounted for a disproportionate amount of all ED visits (41.4%) and all ED costs (39.2%). A small proportion (0.4%) of patients visited five or more EDs but accounted for 2.8% of ED visits and costs. Among patients with two ED visits within 30 days, 32% were to different EDs. Having at least one ED visit for mental health or substance abuse-related diagnosis was associated with increased odds of visiting multiple EDs. CONCLUSIONS: A substantial minority of patients visit multiple EDs, but account for a disproportionate burden of overall ED utilization and costs. Future work should evaluate the impact of visiting multiple EDs on care utilization and outcomes and explore systems for improving access to patient records across care centers.

Predicting Falls in People Aged 65 Years and Older from Insurance Claims.

BACKGROUND: Accidental falls among people aged 65 years and older caused approximately 2,700,000 injuries, 27,000 deaths, and cost more than 34 billion dollars in the US annually in recent years. Here, we derive and validate a predictive model for falls based on a retrospective cohort of those 65 years and older. METHODS: Insurance claims from a 1-year observational period were used to predict a fall-related claim in the following 2 years. The predictive model takes into account a person's age, sex, prescriptions, and diagnoses. Through random assignment, half of the people had their claims used to derive the model, while the remaining people had their claims used to validate the model. RESULTS: Of 120,881 individuals with Aetna health insurance coverage, 12,431 (10.3%) members fell. During validation, people were risk stratified across 20 levels, where those in the highest risk stratum had 10.5 times the risk as those in the lowest stratum (33.1% vs 3.1%). CONCLUSIONS: Using only insurance claims, individuals in this large cohort at high risk of falls could be readily identified up to 2 years in advance. Although external validation is needed, the findings support the use of the model to better target interventions.

Prevalence of Inflammatory Bowel Disease Among Patients with Autism Spectrum Disorders.

BACKGROUND: The objective of this study was to measure the prevalence of inflammatory bowel disease (IBD) among patients with autism spectrum disorders (ASD), which has not been well described previously. METHODS: The rates of IBD among patients with and without ASD were measured in 4 study populations with distinct modes of ascertainment: a health care benefits company, 2 pediatric tertiary care centers, and a national ASD repository. The rates of IBD (established through International Classification of Diseases, Ninth Revision, Clinical Modification [ICD-9-CM] codes) were compared with respective controls and combined using a Stouffer meta-analysis. Clinical charts were also reviewed for IBD among patients with ICD-9-CM codes for both IBD and ASD at one of the pediatric tertiary care centers. This expert-verified rate was compared with the rate in the repository study population (where IBD diagnoses were established by expert review) and in nationally reported rates for pediatric IBD. RESULTS: In all of case-control study populations, the rates of IBD-related ICD-9-CM codes for patients with ASD were significantly higher than that of their respective controls (Stouffer meta-analysis, P < 0.001). Expert-verified rates of IBD among patients with ASD were 7 of 2728 patients in one study population and 16 of 7201 in a second study population. The age-adjusted prevalence of IBD among patients with ASD was higher than their respective controls and nationally reported rates of pediatric IBD. CONCLUSIONS: Across each population with different kinds of ascertainment, there was a consistent and statistically significant increased prevalance of IBD in patients with ASD than their respective controls and nationally reported rates for pediatric IBD.

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.