Clinical consensus on treatments for transplant-ineligible newly diagnosed multiple myeloma: double-blinded Delphi panel.

Aim: Obtain clinical consensus on factors impacting first-line prescribing for transplant-ineligible (TIE) patients with newly diagnosed multiple myeloma (NDMM). Materials & methods: A double-blinded, modified Delphi panel was employed. USA-based hematologists/oncologists who treat TIE patients with NDMM were selected as expert panelists. Results: Consensus was reached that patient frailty, performance status, comorbidities, treatment efficacy, and adverse event profile affect first-line prescribing. All panelists agreed it is important to use the most efficacious treatment first; 88% of panelists considered daratumumab-containing regimens the most efficacious. Panelists agreed treatment should be continued until progression while benefits outweigh risk. Conclusion: Findings reinforce the importance of using the most efficacious regimen upfront for TIE NDMM, and nearly all panelists considered daratumumab-containing regimens the most efficacious treatment.

The purpose of this study was to determine the latest clinician preferences and opinions on factors affecting initial treatment selection for people recently diagnosed with multiple myeloma and unable to receive a bone marrow transplant, and to understand challenges with current treatments used in clinical practice. A panel of doctors with an average of two decades of experience treating blood disorders and cancers were recruited as expert panelists. Experts discussed treatment options by completing two rounds of surveys on treatment and one round of discussion. All experts agreed that the most effective treatment should be used first. Most experts considered treatment containing the drug daratumumab to be the most effective. Experts agreed that treatment should be continued until the cancer worsens if the treatment offers more benefits than side effects.

A Choice-Based Conjoint Analysis of the Psychiatrist Decision-Making Process Used in Determining When to Discharge Adults With Major Depressive Disorder Hospitalized for Active Suicidal Ideation With Intent.

ABSTRACT: To ascertain the relative importance of attributes considered when deciding to discharge patients hospitalized with major depressive disorder (MDD) and active suicidal ideation with intent, a choice-based conjoint analysis was conducted via online survey among US-based psychiatrists actively managing such patients. Potential attributes and attribute levels were identified. Attribute importance in decision to discharge and the discharge time frame were assessed. One hundred psychiatrists completed the survey. The relative importance of attributes were current MDD severity (relative importance weight [out of 100] 24.8 [95% confidence interval, 23.3-26.3]), clinician assessment of current suicidal ideation (20.8 [18.5-23.0]), previous history of suicide attempts (16.7 [15.9-17.6]), psychosocial support at discharge (13.0 [11.7-14.4]), postdischarge outpatient follow-up (9.8 [8.8-10.8]), current length of hospital stay (9.2 [8.1-10.3]), and suicidal ideation at admission (5.7 [4.8-6.6]). Thus, current clinical symptoms were considered the most important attributes by psychiatrists when discharging patients initially hospitalized with MDD and active suicidal ideation with intent.

Association of depression symptom severity with short-term risk of an initial hospital encounter in adults with major depressive disorder.

BACKGROUND: Despite the availability of pharmacologic and nonpharmacologic treatment options, depression continues to be one of the leading causes of disability worldwide. This study evaluated whether depression symptom severity, as measured by PHQ-9 score, of patients diagnosed with MDD is associated with short-term risk of a hospital encounter (ER visit or inpatient stay). METHODS: Adults with ≥1 PHQ-9 assessment in an outpatient setting (index date) and ≥ 1 MDD diagnosis within 6 months prior were included from the de-identified Optum Electronic Health Record database (April 2016-June 2019). Patients were categorized by depression symptom severity based on PHQ-9 scores obtained by natural language processing. Crude rates, adjusted absolute risks, and adjusted relative risks of all-cause and MDD-related hospital encounters within 30 days following assessment of depression severity were determined. RESULTS: The study population consisted of 280,145 patients with MDD and ≥ 1 PHQ-9 assessment in an outpatient setting. Based on PHQ-9 scores, 26.9% of patients were categorized as having none/minimal depression symptom severity, 16.4% as mild, 24.7% as moderate, 19.6% as moderately severe, and 12.5% as severe. Among patients with none/minimal, mild, moderate, moderately severe, and severe depression, the adjusted absolute short-term risks of an initial all-cause hospital encounter were 4.1, 4.4, 4.8, 5.6, and 6.5%, respectively; MDD-related hospital encounter adjusted absolute risks were 0.8, 1.0, 1.3, 1.6, and 2.1%, respectively. Compared to patients with none/minimal depression symptom severity, the adjusted relative risks of an all-cause hospital encounter were 1.60 (95% CI 1.50-1.70) for those with severe, 1.36 (1.29-1.44) for those with moderately severe, 1.18 (1.12-1.25) for those with moderate, and 1.07 (1.00-1.13) for those with mild depression symptom severity. CONCLUSIONS: These study findings indicate that depression symptom severity is a key driver of short-term risk of hospital encounters, emphasizing the need for timely interventions that can ameliorate depression symptom severity.

Unmet need in major depressive disorder and acute suicidal ideation or behavior: findings from a longitudinal electronic health record data analysis.

AIMS: Using a national electronic health records (EHR) database, the current study describes treatments, depression severity, and health care resource utilization (HRU) among patients with major depressive disorder (MDD) and acute suicidal ideation or behavior (MDSI) prior to, during, and following a suicide-related event in the United States. MATERIALS AND METHODS: This retrospective matched cohort study used data collected from the Optum EHR de-identified database for patients with diagnosis codes for MDD and acute suicidal ideation or behavior and a propensity score-matched cohort of patients without MDD or a suicide-related event. The study period was 31 October 2015-30 September 2019. MDD-related treatments and 9-item Patient Health Questionnaire (PHQ-9) scores, when available, were assessed at the first health care encounter for a suicide-related event (index period), 12 months before (pre-period), and 6 months after (post-period). All-cause and MDD-related HRU were assessed during the post-period. RESULTS: The mean (standard deviation) age of patients with MDSI was 39 (16) years; 55.0% were female. Index events occurred as follows: inpatient stay, 38.9%; observation unit stay, 4.6%; emergency department (ED) visit, 46.5%; and outpatient visit, 10.1%. Antidepressants and psychotherapy were the most common pharmacologic and nonpharmacologic treatments, respectively, prescribed during the pre- (31.3%, 9.5%, respectively) and index (41.2%, 18.7%, respectively) periods. Post-period data (n = 40,261) revealed only 43.4% received an antidepressant and 20.5% had psychotherapy after the suicide-related event. Few patients had PHQ-9 scores recorded during the pre- (4.4%), index (1.3%), and post- (7.6%) periods. During the post-period, 11.8%, 5.0%, and 33.1% of patients had ≥1 all-cause inpatient stay, observation unit stay, and ED visit, respectively; 61.0% had ≥1 all-cause and 33.4% ≥1 MDD-related outpatient visit. Most patients with MDSI and an inpatient encounter or ED visit were discharged to home or self-care (65.4%). Odds of an all-cause hospital encounter during the post-period were higher for patients with versus without MDSI (by 30.1, 33.5, and 33.9 times for inpatient stay, ED visit, and observation unit stay, respectively). CONCLUSION: This analysis highlights an opportunity to improve outcomes for this vulnerable population. More complete data on patient outcomes is needed to inform strategies designed to optimize screening and treatment.

Clinical and economic burden of major depressive disorder with acute suicidal ideation or behavior in a US Veterans Health Affairs database.

OBJECTIVE: Although a high incidence of major depressive disorder (MDD) and an increased risk of suicide are observed among the veteran population, there are yet limited real-world data characterizing patients with MDD with acute suicidal ideation/behavior (MDSI) in the Veterans Health Administration (VHA) system. We assessed the clinical and economic burden, including comorbidities, treatment patterns, health care resource utilization, and health care costs, among veterans and their family members with MDSI within the VHA system. METHODS: This retrospective, longitudinal analysis of VHA datasets (10/1/2015-3/31/2018) evaluated the clinical and economic burden associated with MDSI and compared this population with matched MDD alone (i.e. MDD diagnosis without acute suicidal ideation/behavior) and non-MDD (i.e. neither MDD nor acute suicidal ideation/behavior) cohorts. RESULTS: Among 11,203 patients with MDSI, the proportions of patients who filled a prescription for ≥1 antidepressant during the 12-month pre- and 6-month post-periods were significantly higher compared with patients with MDD alone (53.7% vs 28.8%, p < .05; and 72.3% vs 44.1%, p < .05; respectively). During the 12-month pre-period, the MDSI cohort had the highest proportion of patients with ≥1 mental health-related inpatient visit compared with the MDD alone and non-MDD cohorts (13.2% vs 2.3% vs 1.4%, respectively; p < .05), and the highest mental health-related costs per patient ($8853 vs $1913 vs $1079, respectively). For the 6-month post-period, the MDSI cohort had the highest proportion of patients with ≥1 mental health-related inpatient visit compared with the MDD alone and non-MDD cohorts (60.4% vs 7.9% vs 0.8%, respectively; p < .05), and had the highest mental health-related costs per patient ($20,334 vs $4803 vs $545, respectively). CONCLUSIONS: Findings demonstrate significant clinical and economic burden for those in the VHA system diagnosed with MDSI and highlight unmet needs and opportunities for improving the care of this vulnerable group.

There are limited real-world data regarding patients diagnosed with major depressive disorder and having suicidal thoughts/behavior (MDSI) in the Veterans Health Administration (VHA) system. We examined data on 11,203 patients with MDSI from the VHA between October 1, 2015 and March 31, 2018. We compared patients with MDSI with patients with major depressive disorder alone (MDD) and patients with no depression (non-MDD). Our results showed that patients with MDSI were treated with more antidepressant therapy, had more hospital stays (inpatient visits), and incurred greater costs than the MDD and non-MDD patients. These results highlight the unmet need and potential opportunity to improve patient care among veterans and their families with MDSI.

US budget impact analysis of esketamine nasal spray in major depressive disorder with acute suicidal ideation/behavior.

Background: Esketamine nasal spray plus an oral antidepressant is approved in adults with major depressive disorder with acute suicidal ideation or behavior (MDSI). Methods: A budget impact analysis from a US payer perspective was performed with a hypothetical 1-million-member plan, using pharmacy and medical costs associated with adding esketamine plus an oral antidepressant to usual care. Results: Estimated annual total healthcare costs of managing patients with MDSI increased from $32,988,247 without esketamine to $34,161,188 in Year 3 with esketamine (primarily due to medical costs). The per-member-per-month incremental costs were $0.02, $0.06 and $0.10 in Years 1, 2 and 3, respectively. Conclusion: Incorporation of esketamine results in a modest estimated impact on the annual budget over a 3-year time horizon.

Excess healthcare resource utilization and healthcare costs among privately and publicly insured patients with major depressive disorder and acute suicidal ideation or behavior in the United States.

BACKGROUND: This study assessed the healthcare resource utilization (HRU) and cost burden of patients with major depressive disorder (MDD) and acute suicidal ideation or behavior (SIB; MDSI) versus those with MDD without SIB and those without MDD. METHODS: Adults were selected from the MarketScan® Databases (10/2015-02/2020). The MDSI cohort received an MDD diagnosis within 6 months of a claim for acute SIB (index date). The index date was a random MDD claim in the MDD without SIB cohort and a random date in the non-MDD cohort. Patients had continuous eligibility ≥12 months pre- and ≥1 month post-index. HRU and costs were compared during 1- and 12-month post-index periods between MDSI and control cohorts matched 1:1 on demographics. RESULTS: The MDSI cohort included 73,242 patients (mean age 35 years, 60.6% female, 37.2% Medicaid coverage). At 1 month post-index, the MDSI cohort versus the MDD without SIB/non-MDD cohorts had 12.8/67.2 times more inpatient admissions and 3.3/8.9 times more emergency department visits; they had 2.9 times more outpatient visits versus the non-MDD cohort (all p < 0.001). The MDSI cohort had incremental mean healthcare costs of $5255 and $6674 per-patient-month versus the MDD without SIB and non-MDD cohorts (all p < 0.001); inpatient costs drove up to 89.5% of incremental costs. At 12 months post-index, HRU and costs remained higher in MDSI versus control cohorts. LIMITATIONS: SIB are underreported in claims; unobserved confounders may cause bias. CONCLUSIONS: MDSI is associated with substantial excess healthcare costs driven by inpatient costs, concentrated in the first month post-index, and persisting during the following year.

Characteristics of hospital encounters and associated economic burden of patients with major depressive disorder and acute suicidal ideation or behavior.

OBJECTIVES: Relatively little is known about the hospital experience among patients with major depressive disorder (MDD) and acute suicidal ideation or behavior (MDSI). The objectives of this study were to examine hospital encounter characteristics, including the associated economic burden and risk of subsequent hospital encounters of patients with MDSI in the US. METHODS: In this retrospective analysis, patients ≥18 years of age with a hospital encounter (emergency department [ED] visit or inpatient admission) were selected from the de-identified Premier Hospital database between 1 January 2017 and 30 September 2018. Patients were required to have MDD as the primary and acute suicidal ideation or behavior as a secondary discharge diagnosis or vice versa. Patient demographics and characteristics of hospital encounters were examined. Rates and costs of subsequent all-cause and MDD-related hospital encounters 6 months following initial discharge were also evaluated. RESULTS: The study population consisted of 123,179 patients with a hospital encounter for MDSI (mean age: 38 years, 50.9% female, 74.6% White); 50.2% were treated in the ED only (mean ± standard deviation cost: $693±$630), while 49.8% were admitted as inpatients ($6,478±$7,001). Among those with ED visits, very few (7.0%) received an antidepressant (AD). Among those with an inpatient admission, 87.2% received ≥1 AD and 39.0% received AD augmentation. Overall rates and costs of subsequent all-cause and MDD-related hospital encounters were 22.3% ($5,136±$11,791) and 12.0% ($3,722±$9,621), respectively; nearly half of subsequent encounters (41.3% and 44.3%, respectively) occurred in the first month following initial discharge. CONCLUSIONS: This analysis of patients with MDSI presenting to US hospitals shows heterogeneity in treatment and a concentration of costly subsequent hospital encounters within 1-month post discharge, suggesting that healthcare systems may benefit from examination of current care pathways for this vulnerable patient population.

How well do clinical and demographic characteristics predict Patient Health Questionnaire-9 scores among patients with treatment-resistant major depressive disorder in a real-world setting?

OBJECTIVES: To create and validate a model to predict depression symptom severity among patients with treatment-resistant depression (TRD) using commonly recorded variables within medical claims databases. METHODS: Adults with TRD (here defined as > 2 antidepressant treatments in an episode, suggestive of nonresponse) and ≥ 1 Patient Health Questionnaire (PHQ)-9 record on or after the index TRD date were identified (2013-2018) in Decision Resource Group's Real World Data Repository, which links an electronic health record database to a medical claims database. A total of 116 clinical/demographic variables were utilized as predictors of the study outcome of depression symptom severity, which was measured by PHQ-9 total score category (score: 0-9 = none to mild, 10-14 = moderate, 15-27 = moderately severe to severe). A random forest approach was applied to develop and validate the predictive model. RESULTS: Among 5,356 PHQ-9 scores in the study population, the mean (standard deviation) PHQ-9 score was 10.1 (7.2). The model yielded an accuracy of 62.7%. For each predicted depression symptom severity category, the mean observed scores (8.0, 12.2, and 16.2) fell within the appropriate range. CONCLUSIONS: While there is room for improvement in its accuracy, the use of a machine learning tool that predicts depression symptom severity of patients with TRD can potentially have wide population-level applications. Healthcare systems and payers can build upon this groundwork and use the variables identified and the predictive modeling approach to create an algorithm specific to their population.

Mental Health Care Resource Utilization and Barriers to Receiving Mental Health Services Among US Adults With a Major Depressive Episode and Suicidal Ideation or Behavior With Intent.

Objective: To examine the incremental mental health care resource utilization (MHRU) and barriers to receiving mental health services among adults with a major depressive episode (MDE) and suicidal ideation or behavior with intent.Methods: Data from adult participants in the 2017 National Survey on Drug Use and Health were used to identify 3 cohorts: MDE (determined by Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition [DSM-5] criteria) with suicidal ideation or behavior with intent (MDSI), MDE, and non-MDE. MHRU and barriers to receiving mental health services were compared among cohorts using logistic regression models.Results: The MDSI cohort had significantly higher odds (adjusted odds ratio [95% confidence interval]) of receiving mental health-related inpatient care, outpatient care, prescription medications, and any treatment versus the MDE cohort (10.2 [7.1-14.6], 2.4 [1.7-3.4], 2.4 [1.8-3.3], and 2.6 [1.8-3.7], respectively) and the non-MDE cohort (40.3 [27.3-59.5], 20.0 [14.5-27.7], 17.2 [12.9-22.9], and 19.6 [14.1-27.1], respectively). Compared to the MDE cohort, the MDSI cohort was significantly more likely to report barriers to receiving mental health services (2.6 [2.0-3.4]), with the largest differences between cohorts related to fear of negative impact (3.9 [2.8-5.4]). Additionally, 30.6% of the MDSI cohort and 47.0% of the MDE cohort did not receive any mental health treatment in the past year.Conclusions: Although respondents in the MDSI cohort reported substantially higher MHRU across all categories, they also reported greater barriers to receiving care than those in the MDE cohort. This study documents the extensive burden and unmet need in the MDSI population.

Cluster Analysis of Care Pathways in Adults with Major Depressive Disorder with Acute Suicidal Ideation or Behavior in the USA.

BACKGROUND AND OBJECTIVE: Suicidal ideation or behavior are core symptoms of major depressive disorder (MDD). This study aimed to understand heterogeneity among patients with MDD and acute suicidal ideation or behavior. METHODS: Adults with a diagnosis of MDD on the same day or 6 months before a claim for suicidal ideation or behavior (index date) were identified in the MarketScan® Databases (10/01/2014-04/30/2019). A mathematical algorithm was used to cluster patients on characteristics of care measured pre-index. Patient care pathways were described by cluster during the 12-month pre-index period and up to 12 months post-index. RESULTS: Among 38,876 patients with MDD and acute suicidal ideation or behavior, three clusters were identified. Across clusters, pre-index exposure to mental healthcare was revealed as a key differentiator: Cluster 1 (N = 16,025) was least exposed, Cluster 2 (N = 5640) moderately exposed, and Cluster 3 (N = 17,211) most exposed. Patients whose MDD diagnosis was first observed during their index event comprised 86.0% and 72.8% of Clusters 1 and 2, respectively; in Cluster 3, all patients had an MDD diagnosis pre-index. Within 30 days post-index, in Clusters 1, 2, and 3, respectively, 79.3%, 85.2%, and 88.2% used mental health services, including outpatient visits for MDD. Within 12 months post-index, 61.5%, 91.5%, and 84.6% had one or more antidepressant claim, respectively. Per-patient index event costs averaged $5614, $6645, and $5853, respectively. CONCLUSIONS: Patients with MDD and acute suicidal ideation or behavior least exposed to the healthcare system pre-index similarly received the least care post-index. An opportunity exists to optimize treatment and follow-up with mental health services.

Cardiovascular Health After Preeclampsia: Patient and Provider Perspective.

Background: Preeclampsia predicts future cardiovascular disease (CVD) yet few programs exist for post-preeclampsia care. Methods: The Health after Preeclampsia Patient and Provider Engagement Network workshop was convened at the Radcliffe Institute for Advanced Study in June 2018. The workshop sought to identify: 1) patient perspectives on barriers and facilitators to CVD risk reduction; 2) clinical programs specialized in post-preeclampsia care; 3) recommendations by national organizations for risk reduction; and 4) next steps. Stakeholders included the Preeclampsia Foundation, patients, clinicians who had initiated CVD risk reduction programs for women with prior preeclampsia, researchers, and national task force members. Results: Participants agreed there is insufficient awareness and action to prevent CVD after preeclampsia. Patients suggested a clinician checklist to ensure communication of CVD risks, enhanced training for clinicians on the link between preeclampsia and CVD, and a post-delivery appointment with a clinician knowledgeable about this link. Clinical programs primarily served patients in the first postpartum year, bridging obstetrical and primary care. They recommended CVD risk modification with periodic blood pressure, weight, lipid and diabetes screening. Barriers included the paucity of programs designed for this population and gaps in insurance coverage after delivery. The American Heart Association, the American College of Obstetricians and Gynecologists, and the Preeclampsia Foundation have developed guidelines and materials for patients and providers to guide management of women with prior preeclampsia. Conclusions: Integrated efforts of patients, caregivers, researchers, and national organizations are needed to improve CVD prevention after preeclampsia. This meeting's recommendations can serve as a resource and catalyst for this effort.

Real-world comparison of hospitalization costs for heart failure in type 2 diabetes mellitus patients with established cardiovascular disease treated with canagliflozin versus other antihyperglycemic agents.

Aims: This real-world study compared hospitalization for heart failure (HHF) costs and all-cause healthcare costs in patients with type 2 diabetes mellitus (T2DM) and established cardiovascular disease treated with the sodium glucose co-transporter 2 inhibitor (SGLT2i) canagliflozin and non-SGLT2i antihyperglycemic agents (AHAs).Materials and methods: Propensity score-matched cohorts from a retrospective observational study (OBSERVE-4D) using the Truven MarketScan Commercial Claims and Encounters and Optum Clinformatics databases were analyzed. HHF and all-cause healthcare costs per-patient-per-month (PPPM) were compared for patients initiated on canagliflozin and non-SGLT2i AHAs in the on-treatment analysis.Results: Baseline characteristics were well balanced between matched cohorts that included new users of canagliflozin or non-SGLT2i AHAs in the Truven (13,954 and 45,101, respectively) and Optum (11,490 and 53,360, respectively) databases. The mean (95% CI) PPPM cost of HHF was lower for canagliflozin than for non-SGLT2i AHAs in analyses of both the Truven ($21.31 [$21.25, $21.37]) and Optum ($30.43 [$30.41, $30.45]) databases. The mean (95% CI) PPPM all-cause healthcare cost was also lower for canagliflozin than for non-SGLT2i AHAs in analyses of both the Truven ($321 [$280, $361]) and Optum ($449 [$402, $495]) databases.Limitations: This study is subject to the limitations inherent to observational research including potential for coding errors and biases and unobserved confounding. Because all patients were in commercially administered health plans, these findings cannot be easily generalized to uninsured or Medicaid populations. Patient costs were evaluated up to and including their first HHF event. Post-discharge costs such as the costs of subsequent rehospitalizations were not included in this analysis.Conclusions: For patients with T2DM and established cardiovascular disease in this real-world study, treatment with canagliflozin was associated with lower HHF costs and all-cause healthcare costs compared with treatment with non-SGLT2i AHAs.

Communication of Medication Nonmedical Switching Policies and Procedures by Insurance Companies: Results of an E-Survey.

PURPOSE: Nonmedical switching is defined as a change in a stable patient's prescribed medication to a clinically distinct, nongeneric alternative for reasons other than lack of clinical response, adverse effects, or poor adherence. Nonmedical switching often results from formulary changes implemented by insurers to lower medication costs. We sought to survey randomly sampled physicians to elicit their opinions regarding insurers' communication about nonmedical switching. METHODS: We performed an online, cross-sectional survey of licensed, practicing physicians who were >2 years but <30 years out of residency and/or fellowship, who practiced in an internal medicine, family medicine, or specialist setting, spent ≥10% of their work time providing direct patient care, and had received at least 1 request for a nonmedical switch for ≥1 patient in the prior 12 months. The survey was fielded from November to December 2018. We report weighted percent responses categorized from 5- or 7-point Likert scale questions. FINDINGS: E-mail invitations were sent to 13,117 randomly sampled physicians, and 1818 opened the e-mail and followed the embedded survey link to participate. Of these, 1010 total physicians (55.5%), 606 primary care and 404 specialists, who treated patients experiencing nonmedical switching in the prior 12 months completed the survey. A few physicians were notified about nonmedical switches by insurers; more frequently physicians learned about them from pharmacies serving their patients. Notification frequently occurred at or after a refill came due. Notification via electronic medical record or insurer letter was less frequent. Few thought that insurers clearly communicated information about alternative medications when a nonmedical switch was required, and most disagreed that insurers provided clear procedures, timelines, and methods to track challenges. Nearly all agreed that insurers should provide supporting documentation or rationale for nonmedical switches and specifics on alternatives. Respondents overwhelmingly agreed that steps to improve communication and physicians' and patients' ability to navigate nonmedical switches or challenge procedures should be implemented. IMPLICATIONS: This survey of primary care and speciality physicians suggests that physicians believe that insurers' current level of communication regarding nonmedical switching is suboptimal. Respondents suggested that insurers did not optimally communicate information about alternative medications when a nonmedical switch was required and did not provide clear procedures, timelines, and methods to track challenges. A preponderance of physicians agreed that steps to improve physician-insurer communication to aid in the navigation of nonmedical switch and to challenge procedures should be implemented. If not addressed, these identified nonmedical switch communication issues may have a negative effect on achieving the quadruple aim of enhancing patient experience, improving population health, reducing costs, and improving the work life of health care practitioners and their staff.

Impact of non-medical switching of prescription medications on health outcomes: an e-survey of high-volume medicare and medicaid physician providers.

BACKGROUND: Non-medical switching refers to a change in a stable patient's prescribed medication to a clinically distinct, non-generic, alternative for reasons other than poor clinical response, side-effects or non-adherence. OBJECTIVE: To assess the perceptions of high-volume Medicare and/or Medicaid physician providers regarding the impact non-medical switching has on their patients' medication-related outcomes and health-care utilization. METHODS: We performed an e-survey of high-volume Medicare and/or Medicaid physicians (spending >50% of their time caring for Medicare and/or Medicaid patients), practicing for >2 years but <30 years post-residency and/or fellowship; working in a general, internal, family medicine or specialist setting; spending ≥40% of their time providing direct care and having received ≥1 request for a non-medical switch in the past 12 months. Physicians were queried on 15-items to assess perceptions regarding the impact non-medical switching on medication-related outcomes and health-care utilization. RESULTS: Three-hundred and fifty physicians were included. Respondents reported they felt non-medical switching, to some degree, increased side-effects (54.0%), medication errors (56.0%) and medication abandonment (60.3%), and ~50% believed it increased patients' out-of-pocket costs. Few physicians (≤13.4% for each) felt non-medical switching had a positive impact on effectiveness, adherence or patients' or physicians' confidence in the quality-of-care provided. Non-office visit and prescriber-pharmacy contact were most frequently thought to increase due to non-medical switching. One-third of physicians felt office visits were very frequently/frequently increased, and ~ 1-in-5 respondents believed laboratory testing and additional medication use very frequently/frequently increased following a non-medical switch. About 1-in-10 physicians felt non-medical switching very frequently/frequently increased the utilization of emergency department or in-hospital care. CONCLUSION: This study suggests high-volume Medicare and/or Medicaid physician providers perceive multiple negative influences of non-medical switching on medication-related outcomes and health-care utilization.

Long-term direct and indirect costs of ulcerative colitis in a privately-insured United States population.

Objective: Prior evaluations of ulcerative colitis (UC)-related costs are dated or encompassed limited follow-up. This study assessed the incremental direct and indirect work loss-related costs of privately-insured patients with UC in the United States, overall and in specific subgroups.Methods: In this retrospective matched cohort study, the OptumHealth Care Solutions, Inc (formerly Optum Health Reporting and Insights employer) database (01 January 1999-31 March 2017) was used to identify adult patients with ≥2 claims for UC, who were matched 1:5 to patients with no claims for inflammatory bowel disease (IBD). UC subgroups were identified based on indicators during the observation period (i.e. use of biologics, opioids, or corticosteroids; UC-related surgery; moderate-to-severe disease; UC-related comorbidities). Healthcare resource utilization (HRU), work loss days, and direct and work loss-related costs were compared between matched cohorts. Descriptive analyses of direct and work loss-related costs were conducted within each UC subgroup.Results: Compared to the non-IBD cohort (n = 46,765), the UC cohort (n = 9353) incurred higher HRU, including 128% more inpatients visits, resulting in $11,029 higher direct costs per patient per year (PPPY; $7170 vs. $18,198; p < .001). Patients in the UC cohort also incurred more work loss days, resulting in $2142 higher work loss-related costs PPPY ($3165 vs. $5307; p < .001). Direct and work loss-related costs were particularly high in the UC subgroups, with patients undergoing UC-related surgery incurring the highest costs.Conclusions: Over ∼5 years follow-up, patients with UC had significantly higher all-cause direct healthcare and indirect work loss-related costs compared to matched patients without IBD.

Specialist physician perspectives on non-medical switching of prescription medications.

Introduction: A non-medical switch is a change to a patient's medication regimen for reasons other than lack of clinical response, side-effects or poor adherence. Specialist physicians treat complex patients who may be vulnerable to non-medical switching. Objectives: To evaluate specialist physicians' perceptions regarding the frequency of non-medical switch requests, and the impact on their patients' outcomes and healthcare utilization. Methods: An online survey of randomly sampled physicians spending ≥10% of time providing patient care and having received ≥1 non-medical switch request during the prior 12-months. Results: Among 404 specialist physicians surveyed, non-medical switch requests were reported as very frequent or frequent by 35.0% of oncologists (for injectable cancer agents) and up to 80.3% of endocrinologists (for injectable anti-hyperglycemics). Respondents reported decreased medication effectiveness (25.0% of oncologists to 75.0% of dermatologists) and increased side-effects (32.5% of oncologists to 66.7% of psychiatrists). Most specialists reported very frequent or frequent increases in non-office visits (52.5% of oncologists to 75.3% of endocrinologists) and calls with pharmacies (57.5% of oncologists to 80.5% of rheumatologists) due to non-medical switching. Conclusions: Receipt of non-medical switching requests were common among specialist physicians. Non-medical switching may lead to negative effects on patient care and require increased healthcare utilization.

Burden of Crohn's disease in the United States: long-term healthcare and work-loss related costs.

AIMS: To quantify the long-term direct and indirect costs among patients with Crohn's disease (CD) and specific subgroups of these patients in the United States from the private payer's perspective. MATERIALS AND METHODS: This retrospective study used the OptumHealth Care Solutions, Inc database (01 January 1999-31 March 2017) to match (1:5) adult patients with ≥2 claims for CD to patients without inflammatory bowel disease (IBD). Patterns observed during follow-up (i.e. biologics, opioids, or steroids; CD-related surgery; moderate-to-severe disease; and comorbidities) were used to identify CD subgroups. Comparisons of healthcare resource utilization, work loss days, and direct and indirect work loss-related costs were made between matched cohorts. Descriptive analyses of costs were conducted within each CD subgroup. RESULTS: There were 6,715 and 33,575 patients in the CD and non-IBD cohorts, respectively. The direct burden was significantly higher in the CD cohort compared to the non-IBD cohort, with 0.34 inpatient admissions per patient per year (PPPY) versus 0.12 (217% increase; p < .001), and $24,500 direct healthcare costs PPPY versus $7,037 ($17,463 increase; p < .001). The trend was similar for the indirect burden, with work loss-related costs PPPY of $5,490 in the CD cohort versus $3,322 in the non-IBD cohort ($2,168 increase; p < .001). The burden was numerically higher in the CD subgroups, with direct healthcare costs reaching $101,013 PPPY in the surgery subgroup. LIMITATIONS: Severity of CD was determined based on claims-based algorithms due to the lack of access to medical files. Absenteeism was imputed based on claims data, and presenteeism was not assessed. CONCLUSIONS: The direct healthcare and indirect work loss-related costs of patients with CD was significantly higher compared to patients without IBD over an average follow-up of 5 years.

Physicians' perspectives regarding non-medical switching of prescription medications: Results of an internet e-survey.

BACKGROUND: Physicians are in an ideal position to describe the impact of medication non-medical switching (switching commonly due to formulary changes by insurer for reasons unrelated to patient health) on their practice dynamics and patient care. We sought to examine physicians' openness to requests for non-medical switching and their experiences and opinions regarding the impact of non-medical switching on their practice, staff and patients. METHODS: An online survey of randomly-sampled physicians spending ≥10% of time providing patient care and having received ≥1 non-medical switch request during the prior 12-months. The impact of non-medical switching on clinical decision-making process; professional experience with clinical practice, patient-physician relationship, insurance process; and perceived impact on practice, staff and patients were assessed. Weighted percent responses were calculated. RESULTS: We sampled 1,010 physicians (response rate = 55.5%). Many responded being frequently not amenable (26.0%) or had reservations (41.8%) to non-medical switch requests; with >50% indicating patient stability on current therapy and suboptimal alternatives as factors frequently influencing amenability. Physicians agreed non-medical switching can create ethical concerns (clinical judgement, autonomy, ability to treat per guidelines; 74.8%, 82.3%, 53.5%, respectively), while forcing them to take responsibility for insurers' decisions (81.1%) and diverting their clinical time (84.3%). Most indicated non-medical switching increased practice burden (administrative, non-billable interactions, additional staffing, non-office patient contact, calls to/from the pharmacy; 85.0%, 72.5%, 62.2%, 64.2%, 69.5%, respectively). Physicians felt insurer processes discouraged non-medical switch challenges (76.7%) and required inconvenient lengths-of-time (76.1%) speaking to insurer representatives without proper expertise (62.0%). They believed non-medical switching negatively impacted aspects of care (effectiveness, side-effects, medication adherence and abandonment, out-of-pocket costs, medication errors; 46.5%, 53.2%, 50.6%, 49.4%, 59.6%, 54.5%, respectively). CONCLUSIONS: Physicians were frequently not amenable or had reservations regarding non-medical switching. They noted ethical concerns due to non-medical switching. Most felt non-medical switches burdened their practice and negatively impacted care.

Antihyperlipidemic Medication Treatment Patterns and Statin Adherence Among Patients with ASCVD in a Managed Care Plan After Release of the 2013 ACC/AHA Guideline on the Treatment of Blood Cholesterol.

BACKGROUND: The American College of Cardiology (ACC) and American Heart Association (AHA) released a new blood cholesterol treatment guideline in November 2013. It is unknown how the new recommendations have affected cholesterol medication use and adherence in a commercial health plan. OBJECTIVE: To evaluate the effect of the 2013 guideline release on antihyperlipidemic treatment patterns and statin adherence in patients with atherosclerotic cardiovascular disease (ASCVD) compared with a historical control group. METHODS: This study was a historical cohort analysis of adult patients (aged 21-75 years) with clinical ASCVD enrolled in a SelectHealth commercial health plan. Patients were included in the guideline implementation cohort if they had a medical claim with an ICD-9-CM diagnosis of ASCVD in the year before the November 2013 ACC/AHA guideline release. The index date was defined as the first outpatient medical claim with an ICD-9-CM for ASCVD in the first 6 months after the guideline was released. Patients were required to have continuous enrollment for ≥ 1 year before and after the index date. These same criteria were applied to patients exactly 4 years earlier to identify a historical control group. Patients meeting these criteria formed the antihyperlipidemic treatment patterns cohort. Of these, patients who also had ≥1 pharmacy claim for a statin in the 1-year pre- and post-index periods were included in the statin adherence cohort. Antihyperlipidemic treatment patterns were assessed using pharmacy claims for antihyperlipidemic medications in the 1-year pre- and post-index periods. Antihyperlipidemic medication claims were classified as a nonstatin cholesterol medication, low-intensity statin, moderate-intensity statin, or high-intensity statin. To address differences in pre-index antihyperlipidemic medications between the guideline implementation and historical control groups, patients were randomly matched 1:1 based on pre-index classification in a post hoc analysis. Post-index antihyperlipidemic classifications were compared between groups using a Stuart-Maxwell test. The change in mean statin adherence (proportion of days covered [PDC]) was compared within and between groups using paired and independent t-tests, respectively. The proportion of adherent patients (PDC ≥ 0.80) in the pre- and post-index periods was compared between groups using a chi-square test. A multivariable logistic regression was used to compare the likelihood of being adherent in the post-index period while controlling for pre-index adherence and other potential confounders. RESULTS: A total of 7,818 adult members with ASCVD in the index period and 1 year before the index period were identified. Of those, 1,841 patients met the criteria to be included in the analysis, and 1,526 patients were matched on antihyperlipidemic classification and included in the antihyperlipidemic treatment patterns analysis. Baseline characteristics were similar, although the guideline implementation group was younger (58.3 vs. 60.5 years, P < 0.001), and more were male (74.8% vs. 71.3%, P = 0.106) than the historical control group. In the matched cohort, there was a significant difference in the post-index antihyperlipidemic classification (P < 0.001), which appeared to be a result of the difference in nonstatin cholesterol medications (guideline 6.9% vs. historical 13.0%) and high-intensity statins (guideline 23.7% vs. historical 16.3%). Of the 1,841 patients in the antihyperlipidemic treatment patterns cohort, 919 patients met inclusion criteria for the statin adherence analysis. Although PDC decreased over time in both groups, significantly more patients in the guideline implementation group were adherent in the post-index period than the historical control group (66.5% vs. 57.3%, respectively; P = 0.005). Additionally, patients in the guideline implementation group were more likely than the historical control to be adherent in the post-index period when adjusting for potential confounders (OR = 1.49, 95% CI = 1.10-2.03; P = 0.011). CONCLUSIONS: Since the release of the updated ACC/AHA treatment guideline, more commercial health plan patients with ASCVD used high-intensity statins and fewer used nonstatin cholesterol medications than historical controls. Additionally, since the guideline release, more patients are adherent to statin therapy than historical controls. This study provides managed care organizations with valuable information regarding the effect of the 2013 ACC/AHA guideline. DISCLOSURES: No outside funding or services were received for this work. Outside of the current study, Bellows has received research funding from Biogen Idec, Regeneron Pharmaceuticals, Myriad Genetic Laboratories, Shire Development, and Bristol-Myers Squibb and an honorariam from Avanir Pharmaceuticals. Voelker received summer intern support from Pfizer and the AMCP Foundation during the time of this study. The remaining authors have nothing to disclose. All authors contributed to study concept and design and to the revision of the manuscript. Bellows, Olsen, and Voelker collected the data, assisted by Wander; data interpretation was performed primarily by Bellows, along with Olsen and Voelker and assisted by Wander. The manuscript was primarily written by Bellows, along with the other authors.