Validation of claims-based algorithms to identify patients with psoriasis.

PURPOSE: Accurately identifying patients with psoriasis (PsO) is crucial for generating real-world evidence on PsO disease course and treatment utilization. METHODS: We developed nine claims-based algorithms for PsO using a combination of the International Classification of Diseases (ICD)-9 codes, specialist visit, and medication dispensing using Medicare linked to electronic health records data (2013-2014) in two healthcare provider networks in Boston, Massachusetts. We calculated positive predictive value (PPV) and 95% confidence interval (CI) for each algorithm using the treating physician's diagnosis of PsO via chart review as the gold standard. Among the confirmed PsO cases, we assessed their PsO disease activity. RESULTS: The nine claims-based algorithms identified 990 unique patient records. Of those, 918 (92.7%) with adequate information were reviewed. The PPV of the algorithms ranged from 65.1 to 82.9%. An algorithm defined as ≥1 ICD-9 diagnosis code for PsO and ≥1 prescription claim for topical vitamin D agents showed the highest PPV (82.9%). The PPV of the algorithm requiring ≥2 ICD-9 diagnosis codes and ≥1 prescription claim for PsO treatment excluding topical steroids was 81.1% but higher (82.5%) when ≥1 diagnosis was from a dermatologist. Among 411 PsO patients with adequate information on PsO disease activity in EHRs, 1.5-5.8% had no disease activity, 31.3-36.8% mild, and 26.9-35.1% moderate-to-severe across the algorithms. CONCLUSIONS: Claims-based algorithms based on a combination of PsO diagnosis codes and dispensing for PsO-specific treatments had a moderate-to-high PPV. These algorithms can serve as a useful tool to identify patients with PsO in future real-world data pharmacoepidemiologic studies.

Validation of claims-based algorithms for psoriatic arthritis.

PURPOSE: An increasing number of new medications are being developed and approved for psoriatic arthritis (PsA). To generate real-world evidence on comparative safety and effectiveness of these drugs, a claims-based algorithm that can accurately identify PsA is greatly needed. METHODS: To identify patients with PsA, we developed seven claims-based algorithms based on a combination of diagnosis codes and medication dispensing using the claims data from Medicare parts A/B/D linked to electronic medical records (2012-2014). Two physicians independently conducted a chart review using the treating physician's diagnosis of PsA as the gold standard. We calculated the positive predictive value (PPV) and 95% confidence intervals of each algorithm. RESULTS: Of the total 2157 records identified by the seven algorithms, 45% of the records had relevant clinical data to determine the presence of PsA. The PPV of the algorithms ranged from 75.2% (algorithm 1: ≥2 diagnosis codes for PsA and ≥1 diagnosis code for psoriasis) to 88.6% (algorithm 7: ≥2 diagnosis codes for PsA with ≥1 code by rheumatologist and ≥1 dispensing for PsA medication). Having ≥2 diagnosis codes and ≥1 dispensing for PsA medications (algorithm 6) also had PPV of 82.4%. CONCLUSIONS: All seven claims-based algorithms demonstrated a moderately high PPV of 75% to 89% in identifying PsA. The use of ≥2 diagnosis codes plus ≥1 prescription claim for PsA appears to be a valid and efficient tool in identifying PsA patients in the claims data, while broader algorithms based on diagnoses without a prescription claim also have reasonably good PPVs.

Association between trajectories of statin adherence and subsequent cardiovascular events.

PURPOSE: Trajectory models have been shown to (1) identify groups of patients with similar patterns of medication filling behavior and (2) summarize the trajectory, the average adherence in each group over time. However, the association between adherence trajectories and clinical outcomes remains unclear. This study investigated the association between 12-month statin trajectories and subsequent cardiovascular events. METHODS: We identified patients with insurance coverage from a large national insurer who initiated a statin during January 1, 2007 to December 31, 2010. We assessed medication adherence during the 360 days following initiation and grouped patients based on the proportion of days covered (PDC) and trajectory models. We then measured cardiovascular events during the year after adherence assessment. Cox proportional hazards models were used to evaluate the association between adherence measures and cardiovascular outcomes; strength of association was quantified by the hazard ratio, the increase in model C-statistic, and the net reclassification index (NRI). RESULTS: Among 519 842 statin initiators, 8777 (1.7%) had a cardiovascular event during follow-up. More consistent medication use was associated with a lower likelihood of clinical events, whether adherence was measured through trajectory groups or PDC. When evaluating the prediction of future cardiovascular events by including a measure of adherence in the model, the best model reclassification was observed when adherence was measured using three or four trajectory groups (NRI = 0.189; 95% confidence interval: [0.171, 0.210]). CONCLUSIONS: Statin adherence trajectory predicted future cardiovascular events better than measures categorizing PDC. Thus, adherence trajectories may be useful for targeting adherence interventions.

Did HEDIS get it right? Evaluating the quality of a quality measure: adherence to ß-blockers and cardiovascular outcomes after myocardial infarction.

BACKGROUND: As an example of the process that could be used to evaluate and optimize the performance of quality measures in routine practice, we evaluated whether the Healthcare Effectiveness Data and Information Set (HEDIS) measure assessing the "persistence of ß-blocker treatment after a heart attack" correlates with post-myocardial infarction (MI) outcomes and whether or not there are alternative specifications of this construct which are better predictors and/or may be more easily applied. RESEARCH DESIGN: The study included a retrospective cohort of 8672 post-MI patients 18 years old and above. We assessed the strength of the association between the different adherence measures and the composite clinical outcome using multivariable Cox models. We compared the predictive capacity of each adherence definition model to one that did not contain adherence by computing the change in C-statistics and the continuous net reclassification improvement indices (NRIs). RESULTS: Adherence was associated with clinical outcome reductions, with hazard ratios ranging from 0.48 (95% CI, 0.27-0.85) to 0.81 (95% CI, 0.67-0.99). None of the adherence measures, including the HEDIS definition, significantly changed the C-statistic relative to a model that did not include adherence. However, the short-term adherence measure (having 72 d covered during the first 90 d postdischarge) showed a large change in NRI (correctly reclassifying 12% of cases and 16% of noncases; NRI: 28%; 95% CI, 22%-38%), although did not significantly differ from the change in NRI with the HEDIS measure. CONCLUSIONS: We identified an adherence measure that showed a predictive ability as good as that of the HEDIS definition to measure ß-blocker use after MI, halving the time of assessment required, and thus, allowing for the implementation of quality improvement interventions in a more timely manner.

Association of Sodium-Glucose Cotransporter-2 Inhibitors With Fracture Risk in Older Adults With Type 2 Diabetes.

Importance: Whether sodium-glucose cotransporter-2 inhibitors (SGLT-2i) are associated with an increased risk of fractures in older adults with type 2 diabetes (T2D) outside of clinical trials remains unknown. Objective: To examine the association of incident fracture among older adults with T2D with initiating an SGLT-2i compared with initiating a dipeptidyl peptidase 4 inhibitor (DPP-4i) or a glucagon-like peptide 1 receptor agonist (GLP-1RA). Design, Setting, and Participants: This is a population-based, new-user cohort study including older adults (aged ≥65 years) with T2D enrolled in Medicare fee-for-service from April 2013 to December 2017. Data analysis was performed from October 2020 to April 2021. Exposures: New users of an SGLT-2i, DPP-4i, or GLP-1RA without a previous fracture were matched in a 1:1:1 ratio using 3-way propensity score matching. Main Outcomes and Measures: The primary outcome was a composite end point of nontraumatic pelvic fracture, hip fracture requiring surgery, or humerus, radius, or ulna fracture requiring intervention within 30 days. After 3-way 1:1:1 propensity score matching, multivariable Cox proportional hazards regression models were used to generate hazard ratios (HRs) for SGLT-2i compared with DPP-4i and GLP-1RA and Kaplan-Meier curves to visualize fracture risk over time across groups. Results: Of 466 933 new initiators of study drugs, 62 454 patients were new SGLT-2i users. After 3-way matching, 45 889 (73%) new SGLT-2i users were matched to new users of DPP-4i and GLP-1RA, yielding a cohort of 137 667 patients (mean [SD] age, 72 [5] years; 64 126 men [47%]) matched 1:1:1 for analyses. There was no difference in the risk of fracture in SGLT-2i users compared with DPP-4i users (HR, 0.90; 95% CI, 0.73-1.11) or GLP-1RA users (HR, 1.00; 95% CI, 0.80-1.25). Results were consistent across categories of sex, frailty (nonfrail, prefrail, and frail), age (<75 and ≥75 years), and insulin use (baseline users and nonusers). Conclusions and Relevance: In this nationwide Medicare cohort, initiating an SGLT-2i was not associated with an increased risk of fracture in older adults with T2D compared with initiating a DPP-4i or GLP-1RA, with consistent results across categories of frailty, age, and insulin use. These findings add to the evidence base evaluating the potential risks associated with SGLT-2i use for older adults outside of randomized clinical trials.

Risk of Serious Infection Among Initiators of Tumor Necrosis Factor Inhibitors Plus Methotrexate Versus Triple Therapy for Rheumatoid Arthritis: A Cohort Study.

OBJECTIVE: To compare the risk of serious infections between the use of tumor necrosis factor inhibitors (TNFi) plus methotrexate (MTX) versus triple therapy among rheumatoid arthritis (RA) patients in a real-world setting. METHODS: Using claims data from Truven MarketScan (2003-2014), we conducted a cohort study to compare RA patients receiving MTX who added a TNFi (TNFi plus MTX group) versus MTX plus hydroxychloroquine and sulfasalazine (triple therapy group). The primary outcome was any serious infection (i.e., a composite end point of hospitalized bacterial and opportunistic infections or herpes zoster). Secondary outcomes were individual components of the composite end point. To adjust for baseline confounding, we used propensity score (PS)-based fine stratification and weighting. A weighted Cox proportional hazards model estimated the hazard ratio (HR) and 95% confidence interval (95% CI) of the outcomes. RESULTS: After PS stratification (PSS) and weighting, we included a total of 45,208 TNFi plus MTX initiators and 1,387 triple therapy initiators. Mean age was 53 years and 70% were female. The incidence rate of any serious infection per 100 person-years was 2.46 in the TNFi plus MTX group and 2.03 in the triple therapy group. The PSS-weighted HR for any serious infection comparing TNFi plus MTX versus triple therapy was 1.23 (95% CI 0.87-1.74). For the secondary outcomes, the PSS-weighted HR was 1.41 (95% CI 0.85-2.34) for bacterial infection and 0.80 (95% CI 0.55-1.18) for herpes zoster. CONCLUSION: In this real-world cohort of RA patients, we noted no substantially different risk of any serious infection, bacterial infection, or herpes zoster after initiating TNFi plus MTX versus triple therapy, although CIs were wide.

Validation of claims-based algorithms to identify interstitial lung disease in patients with rheumatoid arthritis.

OBJECTIVE: To develop and validate claims-based algorithms to identify interstitial lung disease (ILD) in patients with rheumatoid arthritis (RA) METHODS: Using Medicare claims data linked with the electronic medical records (2012-2014), we first selected RA patients based on ≥2 diagnostic codes for RA and ≥1 disease-modifying antirheumatic drugs.Then, to identify ILD in RA, we developed eight claims-based algorithms using a combination of ICD-9 diagnosis codes and procedure codes related to the diagnosis or management of ILD. We assessed the positive predictive value (PPV) for each of the eight algorithms relative to confirmed ILD cases using chest computerized tomography or lung biopsy as the gold standard. RESULTS: A total of 5,214 RA patients were included in the study, and the ILD cases identified by each algorithm ranged from 181 to 993. The PPV of the diagnosis code-based algorithms ranged from 43.4% (≥1 diagnosis code by any physician) to 52.0% (≥2 diagnosis codes by any physician). When the algorithms further required ≥1 procedure code (e.g., imaging, bronchoscopy), the PPV did not improve. However, the algorithms that required ILD diagnosis codes by specialists (i.e., pulmonologist or rheumatologist) had PPVs of 61.5% with ≥1 code; 72.4% with ≥2 codes. CONCLUSIONS: In a cohort of RA patients, our algorithm that required ≥2 ILD diagnosis codes by specialists demonstrated a PPV of 72.4% in ascertaining ILD. Our results support the utility of the claims-based algorithm to identify a population-based cohort of RA patients with ILD using large administrative claims data.

Defining Exposure in Observational Studies Comparing Outcomes of Treatment Discontinuation.

BACKGROUND: Continuation of antiplatelet therapy beyond 12 months after a drug-eluting stent procedure reduced the risk of a major adverse cardiovascular and cerebrovascular event (MACCE) in the DAPT trial (Dual Antiplatelet Therapy). Observational studies have evaluated outcomes related to different durations of therapy but are susceptible to bias. METHODS AND RESULTS: Using deidentified claims from commercially insured and Medicare populations in the United States, we compared how increasingly stringent definitions of exposure affect associations between antiplatelet continuation versus discontinuation and MACCE, myocardial infarction, and intracerebral hemorrhage or gastrointestinal bleeding in patients meeting DAPT trial inclusion criteria between 2004 and 2013. Therapy continuation at 12 months was defined as (1) having antiplatelet supply on hand versus not (landmark time); (2) refilling within 30 days versus not among individuals with antiplatelet supply; (3) criteria 2 plus continuous prior antiplatelet use; and (4) criteria 2 and 3 plus a cardiologist visit in months 10 to 12. Propensity score-adjusted hazard ratios were compared. Cohort sizes were 53 679, 27 524, 16 971, and 7948, respectively, of which 20% were discontinuers on average. Increasing restriction led to progressively larger associations with continued treatment: cohort 1 MACCE hazard ratio, 0.79 (0.73, 0.87); myocardial infarction, 0.74 (0.65, 0.83); bleed, 1.03 (0.96, 1.11) versus cohort 4 MACCE hazard ratio, 0.66 (0.48, 0.91); myocardial infarction, 0.56 (0.37, 0.86); bleed, 1.24 (0.95, 1.61). Estimates trended toward DAPT trial estimates and were associated with reduced levels of exposure misclassification. CONCLUSIONS: In an example of long-term antiplatelet use, increasing restrictions on the definition of therapy continuation yielded results consistent with trial estimates by reducing exposure misclassification.

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.

Effect of Reminder Devices on Medication Adherence: The REMIND Randomized Clinical Trial.

Importance: Forgetfulness is a major contributor to nonadherence to chronic disease medications and could be addressed with medication reminder devices. Objective: To compare the effect of 3 low-cost reminder devices on medication adherence. Design, Setting, and Participants: This 4-arm, block-randomized clinical trial involved 53 480 enrollees of CVS Caremark, a pharmacy benefit manager, across the United States. Eligible participants were aged 18 to 64 years and taking 1 to 3 oral medications for long-term use. Participants had to be suboptimally adherent to all of their prescribed therapies (with a medication possession ratio of 30% to 80%) in the 12 months before randomization. Participants were stratified on the basis of the medications they were using at randomization: medications for cardiovascular or other nondepression chronic conditions (the chronic disease stratum) and antidepressants (the antidepressant stratum). In each stratum, randomization occurred within blocks defined by whether all of the patient's targeted medications were dosed once daily. Patients were randomized to receive in the mail a pill bottle strip with toggles, digital timer cap, or standard pillbox. The control group received neither notification nor a device. Data were collected from February 12, 2013, through March 21, 2015, and data analyses were on the intention-to-treat population. Main Outcomes and Measures: The primary outcome was optimal adherence (medication possession ratio ≥80%) to all eligible medications among patients in the chronic disease stratum during 12 months of follow-up, ascertained using pharmacy claims data. Secondary outcomes included optimal adherence to cardiovascular medications among patients in the chronic disease stratum as well as optimal adherence to antidepressants. Results: Of the 53 480 participants, mean (SD) age was 45 (12) years and 56% were female. In the primary analysis, 15.5% of patients in the chronic disease stratum assigned to the standard pillbox, 15.1% assigned to the digital timer cap, 16.3% assigned to the pill bottle strip with toggles, and 15.1% assigned to the control arm were optimally adherent to their prescribed treatments during follow-up. There was no statistically significant difference in the odds of optimal adherence between the control and any of the devices (standard pillbox: odds ratio [OR], 1.03 [95% CI, 0.95-1.13]; digital timer cap: OR, 1.00 [95% CI, 0.92-1.09]; and pill bottle strip with toggles: OR, 0.94 [95% CI, 0.85-1.04]). In direct comparisons, the odds of optimal adherence were higher with a standard pillbox than with the pill bottle strip (OR, 1.10 [95% CI, 1.00-1.21]). Secondary analyses yielded similar results. Conclusions and Relevance: Low-cost reminder devices did not improve adherence among nonadherent patients who were taking up to 3 medications to treat common chronic conditions. The devices may have been more effective if coupled with interventions to ensure consistent use or if targeted to individuals with an even higher risk of nonadherence. Trial Registration: clinicaltrials.gov Identifier: NCT02015806.

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.

Time series analyses of the effect of FDA communications on use of prescription weight loss medications.

OBJECTIVE: To determine the impact of FDA safety communications regarding the weight loss medications sibutramine and orlistat. METHODS: The 2008 to 2011 pharmacy claims data from CVS Caremark were used to determine the effect of the relevant FDA warnings on (1) use of sibutramine and orlistat, (2) their rates of discontinuation, and (3) substitution to an alternate weight loss medication in the 3-month period following discontinuation. RESULTS: The use of sibutramine, orlistat, or phentermine declined from 45 users per 100,000 Caremark enrollees in May 2008 to 24 users per 100,000 enrollees in December 2010. In the time series analyses of overall use of medications, a very small decline in the trend of use of sibutramine after the FDA communication (0.000002% per month decline after the communication; P < 0.001) was found. However, rates of discontinuation of sibutramine and orlistat were similar before and after relevant FDA communications (all P values >0.1 for both level and trend changes post-warning). Patients discontinuing sibutramine post-communication increased use of phentermine at a rate of 0.004% per month after discontinuation (P = 0.01). CONCLUSION: From 2008 to 2010, use of prescription weight loss medications was low and declined over time. FDA communications regarding the safety of these medications had limited effect on use.