Cost-effectiveness analysis of CYP3A5 genotype-guided tacrolimus dosing in solid organ transplantation using real-world data.

The objective of this study was to estimate the cost-effectiveness of CYP3A5 genotype-guided tacrolimus dosing in kidney, liver, heart, and lung transplant recipients relative to standard of care (SOC) tacrolimus dosing, from a US healthcare payer perspective. We developed decision-tree models to compare economic and clinical outcomes between CYP3A5 genotype-guided and SOC tacrolimus therapy in the first six months post-transplant. We derived inputs for CYP3A5 phenotype frequencies and physician use of genotype test results to inform clinical care from literature; tacrolimus exposure [high vs low tacrolimus time in therapeutic range using the Rosendaal algorithm (TAC TTR-Rosendaal)] and outcomes (incidences of acute tacrolimus nephrotoxicity, acute cellular rejection, and death) from real-world data; and costs from the Medicare Fee Schedule and literature. We calculated cost per avoided event and performed sensitivity analyses to evaluate the robustness of the results to changes in inputs. Incremental costs per avoided event for CYP3A5 genotype-guided vs SOC tacrolimus dosing were $176,667 for kidney recipients, $364,000 for liver recipients, $12,982 for heart recipients, and $93,333 for lung recipients. The likelihood of CYP3A5 genotype-guided tacrolimus dosing leading to cost-savings was 19.8% in kidney, 32.3% in liver, 51.8% in heart, and 54.1% in lung transplant recipients. Physician use of genotype results to guide clinical care and the proportion of patients with a high TAC TTR-Rosendaal were key parameters driving the cost-effectiveness of CYP3A5 genotype-guided tacrolimus therapy. Relative to SOC, CYP3A5 genotype-guided tacrolimus dosing resulted in a slightly greater benefit at a higher cost. Further economic evaluations examining intermediary outcomes (e.g., dose modifications) are needed, particularly in populations with higher frequencies of CYP3A5 expressers.

Evaluation of an opioid pain teleconsultation service to address the opioid overdose epidemic in Colorado: A Health First Colorado demonstration project.

BACKGROUND: Since the mid-1990s, more than 500,000 deaths have been attributed to the opioid overdose epidemic, which has created a serious national crisis affecting public health and social and economic welfare. To mitigate these opioid-related overdoses and deaths, interventions targeted at both the patient and community level are needed. OBJECTIVE: This demonstration project sought to determine whether implementation of a provider-to-provider opioid pain teleconsultation service with a pain specialist was correlated with a reduction in inappropriate opioid use and improve health outcomes. METHODS: Individual-level claims data for Health First Colorado Medicaid members were collected between March 1, 2017, and September 30, 2021, for individuals who triggered a provider-to-provider pain management teleconsultation based on receipt of a prescription for an opioid where the member was receiving a high-dose opioid (n = 125) or was opioid-naive (n = 819). The primary outcome measures were a patient's opioid dose less than 200 morphine milligram equivalent (MME) by 6 months after the consult if consult was triggered for high-dose use or discontinuation of an opioid by 12 weeks after consult if the consult was triggered for opioid naivety. Secondary opioid-related health outcomes were also assessed. RESULTS: In the high-dose opioid cohort, 87% of the members had their monthly average MME reduced to less than 200 by 180 days after their consult. More than half of the opioid-naive group had discontinued their opioid by 90 days after their consult. CONCLUSION: Results indicate that provider-to-provider teleconsultation services with a pain specialist can be an effective intervention at reducing total inappropriate opioid use.

The landscape of pharmacogenetic testing in a US managed care population.

PURPOSE: Little is known about how many insured patients receive pharmacogenetic testing. We describe trends of single-gene pharmacogenetic testing in a US managed care population, and demographic and clinical characteristics of patients who received a test. METHODS: We leveraged a random sample of nearly 11 million patients from a data set of paid medical and pharmacy claims to identify patients with at least one claim indicating receipt of at least one of these single-gene pharmacogenetic tests: CYP2C19, CYP2D6, CYP2C9, VKORC1, UGT1A1, and HLA class 1 typing. RESULTS: From 1 January 2013 to 30 September 2017, 5712 patients received at least one pharmacogenetic test (55% female; mean age = 43 years). The median number of tests per patient was 3 (mean = 2.7, max = 12); 54% were processed through Managed Medicare/Medicaid, while 45% were processed through commercial insurance. The total number of pharmacogenetic tests received more than doubled from 2013 (n = 1955) to 2015 (n = 4192), then decreased slightly in 2016 (n = 3946). The most common test was CYP2C19 (n = 4719), and "long-term (current) use of other medications" was the most common diagnosis. CONCLUSION: Pharmacogenetic testing through patients' insurance was low, but more than doubled from 2013 to 2016. This study highlights the need to better understand utilization patterns and insurance coverage for pharmacogenetic tests.

Increased Odds of Ventricular Arrhythmias Associated with Selective Serotonin Reuptake Inhibitor Use among the Pediatric and Young Adult Population: A Case-Control Study.

OBJECTIVE: To measure the association between selective serotonin reuptake inhibitor (SSRI) use and out-of-hospital ventricular arrhythmia among the pediatric and young adult population. STUDY DESIGN: Case-control study using US claims data from 2007 to 2018. Cases were subjects with at least 1 event between ages 2 and 24 years. Controls (matched 10:1 on index date, age, sex, and continuous enrollment) had no events during study period. Independent association between current SSRI use (prescription fill with continuous exposure ending on, or after, the index date) and incident out-of-hospital ventricular arrhythmia (hospitalization or emergency room encounter with primary diagnostic code for ventricular arrhythmia) was estimated using multivariable conditional logistic regression. Separate analyses were performed for pediatric (2-17 years of age) vs young adult (18-24 years of age) subjects and between citalopram/escitalopram vs other SSRIs. RESULTS: During the study period, 237 eligible cases were identified with 2370 matched controls. Cases were more likely to have government insurance and have a mental health, cardiac, or other complex chronic condition. Thirteen cases (5%) and 15 controls (<1%) had current SSRI exposure. After adjustment for mental health and chronic conditions, there was an increased odds of current SSRI use among cases compared with controls (OR 5.11, 95% CI 1.22-21.37). No difference was observed between pediatric and young adult ages, nor between citalopram/escitalopram and other SSRIs. CONCLUSIONS: These findings demonstrate increased odds of out-of-hospital ventricular arrhythmia associated with SSRI use in the pediatric and young adult population, suggesting a need for heightened awareness and ongoing monitoring of this potential adverse effect.

A Quasi-Experimental Analysis of Lethal Means Assessment and Risk for Subsequent Suicide Attempts and Deaths.

BACKGROUND: Counseling on access to lethal means is highly recommended for patients with suicide risk, but there are no formal evaluations of its impact in real-world settings. OBJECTIVE: Evaluate whether lethal means assessment reduces the likelihood of suicide attempt and death outcomes. DESIGN: Quasi-experimental design using an instrumental variable to overcome confounding due to unmeasured patient characteristics that could influence provider decisions to deliver lethal means assessment. SETTING: Kaiser Permanente Colorado, an integrated health system serving over 600,000 members, with comprehensive capture of all electronic health records, medical claims, and death information. PARTICIPANTS: Adult patients who endorsed suicide ideation on the Patient Health Questionnaire-9 (PHQ-9) depression screener administered in behavioral health and primary care settings from 2010 to 2016. INTERVENTIONS: Provider documentation of lethal means assessment in the text of clinical notes, collected using a validated Natural Language Processing program. MEASUREMENTS: Main outcome was ICD-9 or ICD-10 codes for self-inflicted injury or suicide death within 180 days of index PHQ-9 event. RESULTS: We found 33% of patients with suicide ideation reported on the PHQ-9 received lethal means assessment in the 30 days following identification. Lethal means assessment reduced the risk of a suicide attempt or death within 180 days from 3.3 to 0.83% (p = .034, 95% CI = .069-.9). LIMITATIONS: Unmeasured suicide prevention practices that co-occur with lethal means assessment may contribute to the effects observed. CONCLUSIONS: Clinicians should expand the use of counseling on access to lethal means, along with co-occurring suicide prevention practices, to all patients who report suicide ideation.

Validity of administrative claims-based algorithms for ventricular arrhythmia and cardiac arrest in the pediatric population.

PURPOSE: Identify administrative claims-based algorithms for capturing out-of-hospital ventricular arrhythmias (VA) and cardiac arrests (CA) due to cardiac causes in the pediatric population with high positive-predictive value (PPV). METHODS: Within a single pediatric center, a retrospective cohort of patients hospitalized or seen in the emergency room for VA or CA were identified from the electronic health records. Eligible encounters were blindly reviewed and linked to administrative data, including ICD-9/ICD-10 codes. Test characteristics, including PPV, for different diagnostic and procedure codes were generated using a 50% training sample. The gold standard was definite or suspected out-of-hospital VA or CA due to cardiac cause verified based on clinical criteria. Algorithms with the highest PPV were then applied to a 50% validation sample to validate performance. RESULTS: From 2004-2017, 598 encounters met eligibility criteria. 174 (29%) had an outcome of interest, with remainder being an inpatient event or CA due to other cause. Within the training sample (n = 263), VA codes in primary position had a PPV 94% (95%CI 81%-99%) with low sensitivity (44%, 95%CI 33%-56%). CA codes in any position or VA codes in nonprimary positions had low PPV (18%-19%, 31% respectively). Applying the top three performing algorithms to the validation sample (n = 252) yielded similar PPV values. CONCLUSIONS: Contrary to adults, algorithms including a CA code do not perform well for identifying out-of-hospital VA and CA due to cardiac cause in the pediatric populations. Researchers should be aware of the potential implications for future pediatric drug safety studies for these outcomes.

Comparison of antidepressant classes and the risk and time course of suicide attempts in adults: propensity matched, retrospective cohort study.

BACKGROUND: Placebo-controlled clinical trials have led to concern over possible increased risk of suicide-related events in some populations exposed to antidepressants. AIMS: To evaluate the risk of suicide attempts by antidepressant drug class and the presence or absence of depression. METHOD: A retrospective propensity-matched new-user cohort study was used to compare participants with incident depression classified by antidepressant treatment with each other and with the general population. RESULTS: Among the treated group, the suicide attempt rate peaked in the month prior to diagnosis then decreased steadily over the next 6 months. Among the pharmacologically untreated group, the highest rate was seen in the second month after diagnosis. Cohorts with depression had significantly higher suicide attempt risk than the general population, but the treated group did not differ significantly from the untreated group. CONCLUSIONS: Patients on antidepressants did not have significantly higher risk compared with untreated patients. No significant differences were observed for patients treated with individual serotonin-noradrenaline reuptake inhibitors (SNRIs) or selective serotonin reuptake inhibitors (SSRIs) or by class (SSRI v. SNRI cohorts).

Dynamic medication adherence modeling in primary prevention of cardiovascular disease: a Markov microsimulation methods application.

BACKGROUND: Real-world patients' medication adherence is lower than that of clinical trial patients. Hence, the effectiveness of medications in routine practice may differ. OBJECTIVES: The study objective was to compare the outcomes of an adherence-naive versus a dynamic adherence modeling framework using the case of statins for the primary prevention of cardiovascular (CV) disease. METHODS: Statin adherence was categorized into three state-transition groups on the basis of an epidemiological cohort study. Yearly adherence transitions were incorporated into a Markov microsimulation using TreeAge software. Tracker variables were used to store adherence transitions, which were used to adjust probabilities of CV events over the patient's lifetime. Microsimulation loops "random walks" estimated the average accrued quality-adjusted life-years (QALYs) and CV events. For each 1,000-patient microsimulations, 10,000 outer loops were performed to reflect second-order uncertainty. RESULTS: The adherence-naive model estimated 0.14 CV events avoided per person, whereas the dynamic adherence model estimated 0.08 CV events avoided per person. Using the adherence-naive model, we found that statin therapy resulted in 0.40 QALYs gained over the lifetime horizon on average per person while the dynamic adherence model estimated 0.22 incremental QALYs gained. Subgroup analysis revealed that maintaining high adherence in year 2 resulted in 0.23 incremental QALYs gained as compared with 0.16 incremental QALYs gained when adherence dropped to the lowest level. CONCLUSIONS: A dynamic adherence Markov microsimulation model reveals risk reduction and effectiveness that are lower than with an adherence-naive model, and reflective of real-world practice. Such a model may highlight the value of improving or maintaining good adherence.

Frequency of Continuous Glucose Monitoring Use and Change in Hemoglobin A1C for Adults with Type 1 Diabetes in a Clinical Practice Setting.

OBJECTIVE: To estimate the frequency of continuous glucose monitoring (CGM) use and change in hemoglobin A1c (HbA1c) compared to self-monitoring of blood glucose (SMBG) alone in adults with type 1 diabetes in a clinical practice setting. METHODS: We retrospectively identified 66 adult type 1 diabetes patients at the Barbara Davis Center for Diabetes (BDC) who first initiated CGM between 2006 and 2011 and 67 controls using SMBG. The frequency of CGM use was estimated from survey recall and defined as the mean number of days/month of CGM use during a maximum follow-up of 10 months. Change in HbA1c was calculated as the difference between the baseline value and the lowest follow-up value. RESULTS: The mean change in HbA1c for CGM users was -0.48% (95% confidence interval [CI]: -0.67, -0.28) and for SMBG users was -0.37% (95% CI: -0.56, -0.18). The between-group mean difference in change in HbA1c, adjusted for patient characteristics, was -0.11% (95% CI: -0.38, 0.16), whereas the subgroup with a baseline HbA1c ≥7.0% and users of CGM ≥21 days/month was -0.36% (95% CI: -0.78, 0.05). Nearly half (n = 32, 48%) used CGM <21 days/month. The reasons for low frequency of CGM use or discontinuation included sensor costs, frequency of alarms, inaccuracy, and discomfort. CONCLUSIONS: These CGM data from clinical practice suggest a trend toward decreasing HbA1c for adults with type 1 diabetes, especially in patients with higher baseline HbA1c and higher frequency of CGM use. Future studies are needed to assess the use of CGM in larger populations of clinical practice adult type 1 diabetes patients.

Pharmacy student use of ChatGPT: A survey of students at a U.S. School of Pharmacy.

OBJECTIVE: To learn how students in an accredited PharmD program in the United States are using ChatGPT for personal, academic, and clinical reasons, and whether students think ChatGPT training should be incorporated into their program's curriculum. METHODS: In August 2023, an 18-item survey was developed, pilot tested, and sent to all students who were enrolled during the Spring 2023 semester in the entry-level PharmD program at the University of Colorado. E-mail addresses were separated from survey responses to maintain anonymity. Responses were described using descriptive statistics. RESULTS: 206 pharmacy students responded to the survey for a 49% response rate. Nearly one-half (48.5%) indicated they had used ChatGPT for personal reasons; 30.2% had used it for academic reasons; and 7.5% had used it for clinical reasons. The most common personal use for ChatGPT was answering questions and looking-up information (67.0%). The top academic reason for using ChatGPT was summarizing information or a body of text (42.6%), while the top clinical reason was simplifying a complex topic (53.3%). Most respondents (61.8%) indicated they would be interested in learning about how ChatGPT could help them in pharmacy school, and 28.1% thought ChatGPT training should be incorporated into their pharmacy curriculum. CONCLUSION: At the time of the survey, ChatGPT was being used by approximately one-half of our pharmacy student respondents for personal, academic, or clinical reasons. Overall, many students indicated they want to learn how to use ChatGPT to help them with their education and think ChatGPT training should be integrated into their curriculum.

Perceptions and Utility of Course Evaluations in US Pharmacy Schools.

OBJECTIVE: This study aimed to describe the purpose, implementation, and perceived utility of course evaluations in pharmacy programs. METHODS: After a literature review, a 34-item survey was developed, pretested, and sent to assessment administrators at accredited pharmacy programs (N = 139) with at least 3 follow-ups. Descriptive and inferential statistics were performed in IBM SPSS Statistics software. RESULTS: A total of 90 programs responded (64.7% response rate). Most students (94%) were offered the opportunity to complete course evaluations. Some students completed evaluations during the course (47%), while others did so within 1 week of completion of the course (49%). Whether or not class time was given for students to complete the survey was often dependent on faculty choice (52.2%). Results were typically released after final grades were posted (92%), in time to use for the next semester of teaching (77%). Faculty were chosen to be evaluated by the number of teaching hours (50%) followed by all instructors (45.6%). Programs used the results for performance reviews by chairs (91%), course coordinator reviews (84%), and committee continuous quality improvement efforts (72%). Most programs did not provide faculty guidance on using evaluations (78%) nor development/mentoring (57%); only 22% of programs offered student development in completing evaluations. CONCLUSION: While most programs invite feedback from all students via evaluations, most did not provide guidance to faculty on how to use this feedback for faculty or course development purposes. A more robust process to optimize the use of course evaluations should be developed.

Comparative safety of selective serotonin reuptake inhibitors among pediatric users with respect to adverse cardiac events.

PURPOSE: This study aims to perform a comparative safety study assessing the risk of ventricular arrhythmia, cardiac arrest, or sudden death among pediatric selective serotonin reuptake inhibitor (SSRI) users. METHODS: Using US claims data from 1997 to 2009, new pediatric (age < 18 years) users of SSRI monotherapy were identified. Adverse cardiac outcomes occurring within 12 months of SSRI initiation were identified using a previously validated International Classification of Disease, ninth edition algorithm. Cox proportional hazard analysis was used to estimate the risk for each SSRI, using fluoxetine as the referent group, adjusting for the propensity to receive an individual SSRI, demographics, and exposure covariates. RESULTS: Over the study period, 113,714 subjects met the inclusion criteria and contributed 40,639 person-years of SSRI exposure time. Sertraline (33%) and fluoxetine (29%) were the most commonly prescribed SSRIs. Forty events occurred within 12 months of SSRI initiation. The crude incidence rate was highest for escitalopram (19.5/10,000 person-years) and lowest for fluoxetine (4.2/10,000 person-years). The median time to event ranged from 45 to 86 days. The adjusted risk of adverse event, relative to fluoxetine, was highest for citalopram Hazard Ratio (HR) = 3.53, 95% confidence interval [CI] = 1.09­11.46) and escitalopram (HR = 3.30, 95%CI = 1.08­10.14) and lowest for paroxetine (HR = 1.34, 95%CI = 0.30­5.99) and sertraline (HR = 2.14, 95%CI = 0.75­6.16). CONCLUSIONS: The incidence of adverse cardiac events among pediatric SSRI users was low. However, the risk of an adverse outcome was higher for citalopram and escitalopram users as compared with fluoxetine users. Future studies should focus on confirming these findings and identifying modifying risk factors to optimize medication selection for this population.

Patient-Level Exposure to Actionable Pharmacogenomic Medications in a Nationally Representative Insurance Claims Database.

BACKGROUND: The prevalence of exposure to pharmacogenomic medications is well established but little is known about how long patients are exposed to these medications. AIM: Our objective was to describe the amount of exposure to actionable pharmacogenomic medications using patient-level measures among a large nationally representative population using an insurance claims database. METHODS: Our retrospective cohort study included adults (18+ years) from the IQVIA PharMetrics® Plus for Academics claims database with incident fills of 72 Clinical Pharmacogenetics Implementation Consortium level A, A/B, or B medications from January 2012 through September 2018. Patient-level outcomes included the proportion of days covered (PDC), number of fills, and average days supplied per fill over a 12-month period. RESULTS: Over 1 million fills of pharmacogenetic medications were identified for 605,355 unique patients. The mean PDC for all medications was 0.21 (SD 0.3), suggesting patients were exposed 21% (77 days) of the year. Medications with the highest PDC (0.55-0.89) included ivacaftor, tamoxifen, clopidogrel, HIV medications, transplant medications, and statins; with the exception of statins, these medications were initiated by fewer patients. Pharmacogenomic medications were filled an average of 2.8 times (SD 3.0, range 1-81) during the year following the medication's initiation, and the average days supplied for each fill was 22.3 days (SD 22.4, range 1-180 days). CONCLUSION: Patient characteristics associated with more medication exposure were male sex, older age, and comorbid chronic conditions. Prescription fill data provide patient-level exposure metrics that can further our understanding of pharmacogenomic medication utilization and help inform opportunities for pharmacogenomic testing.

Evaluating the Effect of COVID-19 on Outpatient Opioid Utilization Among Health First Colorado Members and a National Non-Medicaid Cohort: An Interrupted Time Series Analysis.

Objective: COVID-19, coinciding with the opioid epidemic in the United States, has had significant impacts on health-care utilization. While mixed, early analyses signaled a potential resurgence in opioid use following the pandemic. The primary study objective was to assess the association of the COVID-19 pandemic with opioid utilization among Health First Colorado (Colorado's Medicaid Program) members and a non-Medicaid managed care cohort who did not have a diagnosis of cancer or sickle cell disease. Patients and Methods: Using an interrupted time series and segmented regression analysis, this population-level study assessed the association of the COVID-19 pandemic on prescribed utilization of long- and short-acting opioid analgesics among Health First Colorado members and a random sample of non-Medicaid managed care members. Pharmacy claims data for both cohorts were assessed between October 1, 2018, and September 30, 2021, with April 2020 identified as the interruption of interest. We evaluated the following monthly opioid use measures separately for short-acting and long-acting opioids: number of members filling an opioid, total fills, and total days supplied. Results: Short- and long-acting opioid utilization was significantly decreasing among Health First Colorado members in the 18 months prior to the start of COVID-19. After the onset of the pandemic, utilization stabilized and slopes were not significantly different from zero. Among the non-Medicaid managed care cohort, short- and long-acting opioid utilization significantly decreased in the 18 months leading up to the onset of the pandemic. After the onset of the pandemic, utilization of long-acting opioids stabilized, while utilization of short-acting opioids significantly increased. Conclusion: While we observed an increase in opioid utilization measures post-pandemic in the non-Medicaid managed care cohort, a similar increase was not observed in Health First Colorado members suggesting that thoughtful opioid policies put in place pre-pandemic may have been effective at controlling potential inappropriate opioid utilization.

A machine learning evaluation of patient characteristics associated with prescribing of guideline-directed medical therapy for heart failure.

Introduction/background: Patients with heart failure and reduced ejection fraction (HFrEF) are consistently underprescribed guideline-directed medications. Although many barriers to prescribing are known, identification of these barriers has relied on traditional a priori hypotheses or qualitative methods. Machine learning can overcome many limitations of traditional methods to capture complex relationships in data and lead to a more comprehensive understanding of the underpinnings driving underprescribing. Here, we used machine learning methods and routinely available electronic health record data to identify predictors of prescribing. Methods: We evaluated the predictive performance of machine learning algorithms to predict prescription of four types of medications for adults with HFrEF: angiotensin converting enzyme inhibitor/angiotensin receptor blocker (ACE/ARB), angiotensin receptor-neprilysin inhibitor (ARNI), evidence-based beta blocker (BB), or mineralocorticoid receptor antagonist (MRA). The models with the best predictive performance were used to identify the top 20 characteristics associated with prescribing each medication type. Shapley values were used to provide insight into the importance and direction of the predictor relationships with medication prescribing. Results: For 3,832 patients meeting the inclusion criteria, 70% were prescribed an ACE/ARB, 8% an ARNI, 75% a BB, and 40% an MRA. The best-predicting model for each medication type was a random forest (area under the curve: 0.788-0.821; Brier score: 0.063-0.185). Across all medications, top predictors of prescribing included prescription of other evidence-based medications and younger age. Unique to prescribing an ARNI, the top predictors included lack of diagnoses of chronic kidney disease, chronic obstructive pulmonary disease, or hypotension, as well as being in a relationship, nontobacco use, and alcohol use. Discussion/conclusions: We identified multiple predictors of prescribing for HFrEF medications that are being used to strategically design interventions to address barriers to prescribing and to inform further investigations. The machine learning approach used in this study to identify predictors of suboptimal prescribing can also be used by other health systems to identify and address locally relevant gaps and solutions to prescribing.

Pharmacogenetic testing among patients with depression in a US managed care population.

Actionable drug-gene pairs relevant to depression treatment include CYP2D6 and CYP2C19 with specific antidepressants. While clinical use of pharmacogenetic testing is growing, little is known about pharmacogenetic testing for depression treatment in managed care. We determined the incidence of single-gene CYP2D6 and CYP2C19 testing following a new depression episode among US managed care patients, and described characteristics and antidepressant use of patients receiving tests. We used paid medical and pharmacy claims for patients from commercial health plans in the US. For adult patients with a new depression episode from January 1, 2013 to June 30, 2018, we identified covered claims for single-gene CYP2D6 and CYP2C19 pharmacogenetic tests and antidepressant fills. Fewer than 1% (n = 1795) of the depressed cohort (n = 438,534) received a single-gene CYP2D6 or CYP2C19 test through their insurance within 365 days of their earliest depression episode. The percentage of patients who received a test nearly tripled from 0.2% in 2013 to 0.5% in 2014 before plateauing at 0.4% from 2014 to 2017. Among the patients who received a single-gene CYP2D6 or CYP2C19 test and filled an antidepressant within 365 days of their depression diagnosis, up to 30% may have had their initial antidepressant informed by the test result. Our findings describe the use of antidepressants before and after pharmacogenetic testing, which is clinically relevant as pharmacogenomic testing becomes more common in clinical practice. Our study also emphasizes the need for procedure and billing codes that capture multiple-gene panel tests to be more widely implemented in administrative databases.

Suicide ideation, depressive symptoms, and out-of-home placement among youth in the U.S. child welfare system.

The objectives of this study were to describe the association between type of placement, depressive symptoms, and suicide ideation among a sample of youth (7 years and older) as they entered the child welfare system and to examine the longitudinal effect of prior out-of-home placements and prior depressive symptoms on subsequent suicide ideation among these at-risk youth. Results supported a statistically significant association between prior depressive symptoms and subsequent suicide ideation, after adjusting for prior suicide ideation and prior out-of-home placements. Tests of mediation supported the role of prior depressive symptoms as a mediator between prior out-of-home placements and subsequent suicide ideation. These results suggest that youth who enter the child welfare system and are put in an out-of home placement may be at an increased risk for depressive symptoms, which in turn may increase their risk for suicide ideation.

Longitudinal Association of a Medication Risk Score With Mortality Among Ambulatory Patients Acquired Through Electronic Health Record Data.

The use of electronic health records allows for the application of a novel medication risk score for the rapid identification of ambulatory patients at risk of adverse drug events. We sought to examine the longitudinal association of medication risk score with mortality. This retrospective cohort study included patients whose data were available through electronic health records from multiple health care organizations in the United States that provided data as part of a Patient Safety Organization. Patients were included if they had ≥1 visit and ≥1 medication in their record between January 1, 2011, to June 30, 2017. Cox proportional hazards regression was used to examine the association between continuous and categorized medication risk score with all-cause mortality. Among 427,103 patients, the median age was 50 years (interquartile range, 29-64 years); 61% were female; 50% were White, 11% were Black, and 38% were Hispanic; and 6873 had a death date recorded. Patients 30 to 49 years old had the highest hazard ratios (HRs), followed by the 50- to 64-year-olds and lastly those 65 years or older. Controlling for all covariates, 30- to 49-year-olds with a score of 20 to 30 (versus <10) had a 604% increase in the hazard of death (HR, 7.04; 95% confidence interval [CI], 3.86-12.85), 50- to 64-year-olds had a 254% increase (HR, 3.54; 95% CI, 2.71-4.63), and ≥65-year-olds had an 87% increase (HR, 1.87; 95% CI, 1.67-2.09). The medication risk score was independently associated with death, adjusting for multimorbidities and other conditions. Risk was found to vary by age group and score. Results suggest that pharmaceutical interventions among those with elevated scores could improve medication safety for patients taking multiple medications.

Economic Impact of Coverage Expansion for Non-invasive Prenatal Testing Through a Performance-Based Risk-Sharing Agreement.

BACKGROUND: Harvard Pilgrim Health Care expanded coverage for non-invasive prenatal testing (NIPT) to include all pregnant, single-gestation women aged < 35 years, through a performance-based risk-sharing (PBRS) agreement with Illumina to offset costs from coverage expansion. NIPT analyzes cell-free DNA fragments from a maternal blood sample to screen for fetal aneuploidies and is considered a more accurate screening method than conventional serum biochemical screening and nuchal translucency ultrasound-based approaches. OBJECTIVE: This study assessed the impact of NIPT coverage expansion on prenatal screening strategies and payer expenditures. METHODS: This was a real-world comparison of utilization and expenditures of prenatal screening and diagnostic testing in pregnant women aged < 35 years pre- (1 March 2016-28 February 2018) and post- (1 March 2018-30 September 2019) coverage expansion. Incidence rate ratios (IRRs) with 95% confidence intervals (CIs) were estimated to compare changes in utilization of conventional and NIPT-based prenatal screening methods. Change in per member per month (PMPM) expenditures in $US year 2020 were assessed post-coverage expansion using a budget impact model. RESULTS: A total of 5041 and 4109 distinct pregnancies were identified in pre- and post-coverage expansion periods, respectively. Mean ± standard deviation maternal age was consistent between pre- and post-coverage expansion periods (30.35 ± 3.35 and 30.33 ± 3.28, respectively). Screening orders for conventional methods decreased, with an adjusted IRR in the post-expansion period of 0.87 (95% CI 0.85-0.90) times the rate in the pre-expansion period; orders for NIPT increased, with an adjusted IRR in the post-expansion period of 1.41 (95% CI 1.32-1.51) times the rate in the pre-expansion period. Invasive diagnostic testing was low at baseline (1.0%) and did not change post-coverage expansion. The change in PMPM is estimated at $US0.026 post-coverage expansion. CONCLUSION: The PBRS agreement to expand NIPT coverage for women aged < 35 years was associated with an increase in NIPT utilization, decreases in conventional screening methods, and a modest increase in PMPM expenditures.

Association between suicide death and concordance with benzodiazepine treatment guidelines for anxiety and sleep disorders.

OBJECTIVE: Guidelines for management of anxiety and sleep disorders emphasize antidepressant medications and/or psychotherapy as first/second-line and benzodiazepines as third-line treatments. We evaluated the association between suicide death and concordance with benzodiazepine guidelines. METHODS: Retrospective case-control study of patients with anxiety and/or sleep disorders from health systems across 8 U.S. states within the Mental Health Research Network. Suicide death cases were matched to controls on year and health system. Appropriate benzodiazepine prescribing defined as: no monotherapy, no long duration, and/or age < 65 years. The association between guideline concordance and suicide death was evaluated, adjusting for diagnostic and treatment covariates. RESULTS: Sample included 6960 patients with anxiety disorders (2363 filled benzodiazepine) and 6215 with sleep disorders (1237 filled benzodiazepine). Benzodiazepine guideline concordance was associated with reduced odds for suicide in patients with anxiety disorders (OR = 0.611, 95% CI = 0.392-0.953, p = 0.03) and was driven by shorter duration of benzodiazepine use with concomitant psychotherapy or antidepressant medication. The association of benzodiazepine guideline concordance with suicide death did not meet statistical significance in the sleep disorder group (OR = 0.413, 95% CI = 0.154-1.11, p = 0.08). CONCLUSIONS: We found reduced odds for suicide in those with anxiety disorders who filled benzodiazepines in short-moderate duration with concomitant psychotherapy or antidepressant treatment.