Adherence to augmentation therapy for the treatment of major depressive disorder

BACKGROUND

Inadequate response to antidepressant medication is common. Often, adjunctive pharmacotherapy or psychotherapy is recommended.

OBJECTIVE

To measure adherence to adjunctive pharmacotherapy and psychotherapy among individuals with major depressive disorder (MDD).

METHODS

Retrospective cohort study of individuals with MDD on antidepressant monotherapy who added adjunctive pharmacotherapy and/or psychotherapy. Medication adherence was measured by proportion of days covered (PDC) with optimal adherence defined as PDC≥0.80 and psychotherapy adherence defined by count of visits (optimal 8+ visits). Factors associated with optimal adherence were assessed by logistic regression.

RESULTS

Among 218,192 individuals with adjunctive therapy, 185,349 added pharmacotherapy and 32,843 added psychotherapy. In the subsequent 12 months, 36.2% and 54.9% achieved optimal adherence to adjunctive pharmacotherapy and psychotherapy, respectively. Adherence to adjunctive pharmacotherapy was associated with adding psychotherapy, index antidepressant adherence, medical comorbidities, and MDD severity codes. Adherence to adjunctive psychotherapy was associated with adding another medication, previous psychiatry visit and psychiatric comorbidities.

CONCLUSION

Adjunctive psychotherapy appears under-utilized and adherence to adjunctive therapy was low. Low adherence to adjunctive therapy reinforces challenges in managing MDD. That a second adjunctive therapy enhanced adherence to the initial adjunctive therapy indicates an opportunity to explore alternative adjunctive therapies.

Network meta-analysis comparing the effectiveness of a prescription digital therapeutic for chronic insomnia to medications and face-to-face cognitive behavioral therapy in adults

OBJECTIVE

The purpose of this study was to compare the effectiveness of the only Food and Drug Administration-authorized prescription digital therapeutic (PDT) Somryst versus face-to-face cognitive behavioral therapy for insomnia (CBT-I), or FDA-approved prescription medications for insomnia.

METHODS

A systematic literature review was undertaken to identify relevant studies. A Bayesian network meta-analysis (NMA) was conducted to examine (1) mean change in insomnia severity index (ISI); (2) proportional change in ISI remitters; (3) mean change in wake after sleep onset (WASO); and (4) mean change in sleep onset latency (SOL).

RESULTS

Twenty studies provided data on the PDT, CBT-I, CBT-I in combination with self-help (SH), or two prescription medications (eszopiclone and zolpidem). The PDT was associated with significant mean change in ISI (-5.77, 95% Credible Interval [CrI] - 8.53, -3.07) and ISI remitters (OR 12.33; 95% CrI 2.28, 155.91) compared to placebo, and had the highest probability of being the most effective treatment overall for ISI mean change (56%), and ISI remitters (64%). All evaluated interventions significantly outperformed placebo for WASO but no significant differences were observed for SOL (five interventions). Sensitivity analyses excluding medications and meta-regression (assessing type, duration, delivery method for CBT-I) did not affect NMA results.

CONCLUSIONS

This network meta-analysis demonstrated that a PDT delivering CBT-I had the highest probability of being most effective compared to face-to-face CBT-I, prescription sleep medications, or placebo, as measured by reductions in mean ISI score from baseline and ISI-determined remittance.

Real-World Evaluation of Clinical Response and Long-Term Healthcare Resource Utilization Patterns Following Treatment with a Digital Therapeutic for Chronic Insomnia

Background and Objectives

This analysis evaluated insomnia severity and long-term impact on healthcare resource utilization (HCRU) and costs after treatment with Somryst^® (previously called SHUTi), a digital therapeutic delivering cognitive behavioral therapy for insomnia (CBT-I).

Methods

Change from baseline in insomnia severity index (ISI) score was assessed using last observed ISI score. A pre/post analysis of claims data was conducted, comparing HCRU in patients with self-identified sleep problems who successfully initiated the therapeutic (index date) between June 1, 2016 and December 31, 2018.

Results

A total of 248 patients were analyzed (median age 56.5 years, 57.3% female, mean ISI score 19.13, 52.4% treated with sleep aid medications pre-index). After 9 weeks, mean ISI score declined by 37.2% from baseline (19.1 vs 12.0), 58.8% of patients achieved ISI responder status (ISI score improved by =>7; NNT: 1.7), and 26.6% of patients achieved insomnia remission (ISI score <8; NNT for remission: 3.8). After two-year follow-up, post-index events were reduced (compared to 2 years pre-index) for emergency department visits (-53%; IRR: 0.47; 95% CI 0.27, 0.82; P=0.008), hospiatizations (-21%; IRR: 0.79; 95% CI 0.46, 1.35; P=0.389) and hospital outpatient visits (-13%; IRR: 0.87; 95% CI 0.66, 1.14; P=0.315). Slightly increased rates were observed for ambulatory surgical center visits (2%; IRR: 1.02; 95% CI 0.73, 1.44; P=0.903) and office visits (2%; IRR: 1.02; 95% CI 0.92, 1.14; P=0.672). The number of patients treated with sleep aid medications dropped 18.5% (52.4% pre-index vs 42.7% post-index). Average number of prescriptions decreased from 3.98 pre-index to 3.73 post-index (P= 0.552). Total two-year cost reduction post-index vs pre-index was $510,678, or -$2059 per patient.

Conclusion

In a real-world cohort of patients with chronic insomnia, treatment with a digital therapeutic delivering CBT-I was associated with reductions in insomnia severity, emergency department visits, and net costs.

0481 Effectiveness of a digital therapeutic compared to medications and cognitive behavioral therapy for treating chronic insomnia in adults

Introduction

Limitations on the availability of guideline-recommended cognitive behavioral therapy for insomnia (CBT-I) constrain its use and create an unmet need for innovative ways to expand access. Digital therapeutics offer a potential solution. This study compared a digital intervention, traditional face-to-face CBT-I, and prescription medications for insomnia.

Methods

Of 184 articles identified in a systematic literature review, 13 studies reported ISI mean change from baseline data: 1 using the digital therapeutic (DT) SHUTi (now known as the prescription digital therapeutic Somryst), 1 on the medication eszopiclone, and 11 on traditional CBT. A Bayesian network meta-analysis (NMA) was performed on the mean change from baseline and the proportion of remitters using the insomnia severity index (ISI) endpoint with follow-up timepoints between 6-12 weeks. Mean change in ISI score from baseline was analyzed as a continuous endpoint while comparisons of the proportion of remitters was performed using odds ratios. The analysis used a random-effects model for the base case analysis. A surface under the cumulative ranking curve (SUCRA) analysis was performed to rank the treatments on each endpoint.

Results

Only the DT and CBT-I were significantly different than placebo. The DT had the greatest mean change from baseline in ISI from placebo (-5.77 points, 95% Credible Interval (CrI) [-8.53, -3.07]), followed by CBT-I (-4.3 points, 95% CrI [-6.32, -2.39]). In the SUCRA analysis, the DT had the highest probability (56%) of being the most effective treatment based on ISI mean change from baseline. 8 studies reported the proportion of ISI remitters. Only the DT showed a statistically significant difference in remission vs. placebo, and the DT had the highest odds ratio for remission vs. placebo (OR 12.33; 95%CrI [2.28, 155.91]). The DT had the highest probability (64%), of being the most effective treatment for inducing remission using ISI definitions.

Conclusion

The DT in this study was projected to be the most effective therapy on both mean change in ISI and ISI remission within 6-12 weeks of treatment start vs. either traditional CBT-I or medications.

Support (If Any)

This analysis was funded by Pear Therapeutics, Inc.

0480 Reduction in health care-related costs after initiation of treatment with a prescription digital therapeutic for chronic insomnia: two-year follow up analysis of health care claims data

Introduction

The objective of this study was to evaluate the effectiveness of the first FDA-authorized prescription digital therapeutic (PDT) for adults with chronic insomnia that delivers evidence-based treatment (Somryst, previously called SHUTi). FDA considers PDTs to be prescription-only neurobehavioral devices that provide a computerized version of condition-specific behavioral therapy as an adjunct to clinician supervised outpatient treatment.

Methods

A pre/post multi-payer analysis of claims data was conducted, comparing two-year pre- and post-index healthcare resource utilization (HCRU) in an all-comer population of patients with self-identified sleep problems across the United States who activated the PDT between February 1, 2012 and December 31, 2018 (Index). HCRU categories assessed were: hospitalizations, treat-and-release emergency department (ED) visits, ambulatory surgical center (ASC) visits, hospital outpatient department (HOPD) visits, office visits, number of sleep medication prescriptions, and associated health care costs. Costs were estimated by multiplying HCRU by published average costs for each medical resource.

Results

252 patients initiating the PDT were analyzed (mean age 54.2 years, 57.5% female). Compared to the pre-index period, post-index events were reduced for ED (-56.2%; P=0.001), hospitalizations (-20.9%; P=0.4), sleep medication use (-8.9%; P=0. 0.377), HOPD (-8.3%; P=0.522), and ASC (-6.7%; P=0.695). Post-index events were slightly increased for office visits (+0.7%; P=0.891). Total estimated two-year cost savings associated with the reduced rates of all services except office visits was $494,634, or $1,963 per patient.

Conclusion

In a real-world cohort of patients with self-identified sleep problems, treatment with a PDT delivering digital CBT-I was associated with clinically meaningful net reductions in health-related services and associated costs.

Support (If Any)

This analysis was funded by Pear Therapeutics, Inc.

Mental Health Care Provider's Perspectives Toward Adopting a Novel Technology to Improve Medication Adherence

Objective

To understand perspectives of mental health care providers regarding barriers and drivers of adopting a medication ingestible event monitoring (IEM) system in clinical practice.

Methods

Between April and October 2019, a cross‐sectional, online survey was conducted among 131 prescribing clinicians and 119 non‐prescribing clinicians providing care to patients with major depressive disorder, bipolar disorder, and schizophrenia.

Results

Most prescribing clinicians were physicians (79.4%) while most non‐prescribing clinicians (52.9%) were licensed clinical social workers, followed by counselors (30.8%), clinical psychologists (13.4%), and case managers (2.5%). Most respondents (93.2%) reported that clinicians can influence adherence, that the IEM technology was in their patients' best interest (63.6%), and a willingness to beta test the technology (54.8%). Support was positively associated with prescribing clinicians (OR: 2.2; 95% CI: 1.1, 4.5), belief that antipsychotics reduce the health, social, or financial consequences of the condition (OR: 3.8; 95% CI: 1.3, 11.0), concern for patients' well‐being without monitoring (OR: 3.3; 95% CI: 1.2, 8.7), and belief the technology will enhance clinical alliance (OR: 3.1; 95% CI: 1.5, 6.3) or improve patient engagement (OR: 3.0; 95% CI: 1.5, 6.2). Support was inversely related to concerns about appropriate follow‐up actions (OR: 0.4; 95% CI: 0.2, 0.9) and responsibilities (OR: 0.3; 95% CI: 0.1, 0.8) when using the technology.

Conclusions

Our results suggest that IEM sensor technology adoption will depend upon additional evidence that patients will actively engage in the use of the technology, will benefit from the technology through improved outcomes, and that the additional burden placed upon providers is minimal compared to the potential benefit.

Among clinicians with prescribing authority, 91.6% are concerned about the quality of self‐reported medication adherence and 75.6% reported that the IEM sensor technology would be in their patients' “best interest”.

Most prescribing (85.5%) and non‐prescribing (74.0%) clinicians believe that the IEM sensor technology will either improve patient outcomes or practice efficiency.

A key barrier to adoption appears to be concern about how to incorporate these data into practice.

Measuring Response to Adjunctive Therapy Among Individuals with Major Depressive Disorder

BACKGROUND

Incomplete or inadequate response to first-line antidepressant therapy (ADT) for major depressive disorder (MDD) is common. Response to adjunctive therapy is less understood.

OBJECTIVE

To estimate response to adjunctive pharmacotherapy or psychotherapy among individuals with MDD on an antidepressant using the PHQ-9 questionnaire.

METHODS

This was a retrospective cohort analysis using medical and pharmacy insurance claims among individuals with MDD or ADT who initiated adjunctive pharmacotherapy, psychotherapy, or both (dual). Eligible individuals initiated adjunctive therapy between 7/1/2014-12/31/2018. Symptom severity was measured by PHQ-9 score in the 6-month baseline and 12-month follow up. Multivariate logistic regression identified factors associated with improved symptom severity.

RESULTS

Most (81.8%) of the 2389 participants initiated adjunctive pharmacotherapy, followed by psychotherapy (12.7%) and dual adjunctive (5.5%). Only 30.2% had both a baseline and follow-up PHQ-9 score. Among those with mild or more severe PHQ-9 baseline scores, 36.7% had the same or worse MDD severity during follow-up. Among those with moderate or more severe baseline scores, 28.1% had the same or worse MDD severity during follow-up.

CONCLUSION

Most individuals with moderate-to-severe MDD did not receive a follow-up questionnaire, suggesting incomplete monitoring of treatment response. Among those with a PHQ-9 following initiation of adjunctive therapy, many continued to report impactful symptoms. Future studies should explore alternate treatment approaches and methods to support the utilization of the PHQ-9 for monitoring treatment response.

Are caregivers ready for digital? Caregiver preferences for health technology tools to monitor medication adherence among patients with serious mental illness

Background

Adherence to antipsychotic medication is critical for bipolar disorder (BPD), major depression (MDD) and schizophrenia (SCZ) patients. Digital tools have emerged to monitor medication adherence along with tracking general health. Evidence on physician or patient preferences for such tools exists but is limited among caregivers. The study objective was to assess preferences and willingness-to-pay (WTP) for medication adherence monitoring tools among caregivers of SMI patients.

Methods

A web-based survey was administered to caregivers of adult SMI patients. Twelve discrete choice questions comparing adherence monitoring tools that varied across two attribute bundles: (1) tool attributes including source of medication adherence information, frequency of information updates, access to adherence information, and physical activity, mood, and rest tracking, and (2) caregiver monthly out-of-pocket cost attribute were administered to caregiver respondents. Attributes were parameterized for both digital and non-digital tools. Random utility models were used to estimate caregivers’ preferences and WTP.

Results

Among 184 study-eligible caregivers, 57, 61 and 66 participants cared for BPD, MDD, and SCZ patients, respectively. Caregivers highly preferred (odds ratio (OR): 7.34, 95% confidence interval (CI): 5.00–10.79) a tool that tracked medication ingestion using a pill embedded with an ingestible event market (IEM) sensor and tracked patients’ physical activity, mood, and rest than a non-digital pill organizer. Additionally, caregivers were willing to pay $255 per month (95% CI: $123–$387) more for this tool compared to a pill organizer.

Conclusion

Caregivers of SMI patients highly preferred and were willing to pay more for digital tools that not only measures medication ingestion but also tracks general health.

Impact of the COVID-19 Pandemic on Healthcare Resource Utilization in Individuals with Major Depressive Disorder

Objective

To estimate the impact COVID-19 pandemic on healthcare resource utilization (HCRU) among individuals with major depressive disorder (MDD).

Method

A retrospective cohort study was conducted to compare HCRU in the twelve months prior to and six months following pandemic onset among 1,318,709 individuals with MDD and propensity-score matched controls. Outcomes were monthly rates of all-cause and MDD-specific outpatient, inpatient, and prescription medication HCRU. Piecewise random effects models were used to adjust for patient-level clustering, trends over time, and pre-pandemic factors.

Results

In the first month following onset, outpatient HCRU declined with primary care visits down 25.1%. Following this initial decline, outpatient HCRU increased, exceeding pre-pandemic rates within three months. By April 2020, three quarters of all psychotherapy sessions were delivered by telehealth, followed by psychiatry (62.3%), and primary care visits (30.1%). The use of telehealth remained highest for psychotherapy and psychiatry (representing 67.6% and 54.2% of visits, respectively, in September 2020). All-cause partial-day hospitalizations declined 50.5% and remained depressed through July 2020 (down 18.3%). Beginning in the first month post-onset, prescription medication HCRU increased for all antidepressant and antipsychotic medication classes: serotonin modulators ( + 11.8%), bupropion ( + 10.4%), SSRIs ( + 9.0%), SNRIs ( + 8.6%), and atypical antipsychotics ( + 7.5%).

Conclusions

Following pandemic onset, individuals with MDD realized an immediate, but short-lived, reduction in primary care HCRU. Telehealth use remained elevated through the first six months. The most significant and sustained reduction in HCRU was noted for partial-day hospitalizations and all-cause ED visits.

Impact of treatment-related discussions on healthcare resource use and costs among patients with severe mental illness

OBJECTIVE

Serious mental illnesses (SMIs), including schizophrenia, bipolar disorder, and major depressive disorder (MDD), are often treated with antipsychotic medications. Unfortunately, medication non-adherence is widespread and is associated with serious adverse outcomes. However, little real-world data are available describing adherence, compliance, or other medication-taking-related discussions between providers and patients. This study described these communications in ambulatory care.

METHODS

Commercially insured patients having acute (emergency or inpatient) behavioral health (BH) events were included by specific criteria: age 18-65 years; diagnoses of schizophrenia, bipolar disorder, or MDD; continuous health insurance coverage 6 months before to 12 months after the first claim (index) date during 01/01/2014‒12/31/2015; and prescribed antipsychotic medication. Medical charts were abstracted for ambulatory visits with a BH diagnosis through 12 months after the acute event, describing any treatment compliance discussions that occurred. BH-related healthcare utilization and costs were measured via insurance claims. Results were analyzed by observation of an antipsychotic medication taking-related (i.e. compliance or adherence) discussion at the initial abstracted visit.

RESULTS

Ninety patients were included: 62% female, mean age 41 years. Only 58% had antipsychotic compliance discussions during the first abstracted ambulatory visit. A total of 680 BH-related visits were abstracted for the 90 patients. Providers frequently discussed any psychotropic medication use (97% of all visits abstracted); however, discussion of compliance with BH talk therapies was less common (49% of visits among patients with a first visit antipsychotic discussion and 23% without, p < .001). Follow-up BH-related healthcare utilization and costs were not significantly different by cohort. Patients with ≥2 compliance discussions had a significantly lower risk of follow-up acute events, which are the costliest components of healthcare for SMI (p = .023).

CONCLUSION

Increasing the frequency of antipsychotic treatment-related adherence/compliance discussions may represent an opportunity to improve the quality of care for these vulnerable patients and reduce the overall economic burden associated with the treatment of SMI diagnosis.

Treatment Compliance Communications Between Patients with Severe Mental Illness and Treating Healthcare Providers: A Retrospective Study of Documentation Using Healthcare Reimbursement Claims and Medical Chart Abstraction

Introduction

Successful treatment for serious mental illnesses (SMIs) requires a good therapeutic alliance with healthcare providers and compliance with prescribed therapies such as antipsychotic medications. This retrospective study, which utilized administrative claims linked with abstracted medical chart data, addressed a data gap regarding compliance-related discussions between providers and patients.

Methods

Commercially insured patients in ambulatory care post-acute (emergency or inpatient) event were eligible. Criteria included age 18–65 years; schizophrenia, bipolar disorder, or major depressive disorder diagnoses; continuous enrollment 6 months before to 12 months after the first acute event claim dated 01/01/2014 to 12/31/2015; and antipsychotic medication prescription. Demographic and clinical data, and patient–provider discussions about treatment compliance were characterized from claims and abstracted medical charts.

Results

Ninety patients (62% female, mean age 41 years) were included and 680 visits were abstracted; only 58% had first-visit antipsychotic compliance discussions. Notably, 18% of patients had discussions using the specific terms “compliance,” “persistence,” or “adherence,” whereas half were identified by more general terms. Compliance discussions were observed least often among the patients with schizophrenia, as compared with bipolar or major depressive disorders—a counterintuitive finding.

Discussion

Compliance discussions may represent intervention opportunities to optimize treatment, yet their study is a complex endeavor. The results of this study show an opportunity to improve this valuable treatment step.

Adoption of Digital Health Technologies in the Practice of Behavioral Health: Qualitative Case Study of Glucose Monitoring Technology

Background

Evaluation of patients with serious mental illness (SMI) relies largely on patient or caregiver self-reported symptoms. New digital technologies are being developed to better quantify the longitudinal symptomology of patients with SMI and facilitate disease management. However, as these new technologies become more widely available, psychiatrists may be uncertain about how to integrate them into daily practice. To better understand how digital tools might be integrated into the treatment of patients with SMI, this study examines a case study of a successful technology adoption by physicians: endocrinologists’ adoption of digital glucometers.

Objective

This study aims to understand the key facilitators of and barriers to clinician and patient adoption of digital glucose monitoring technologies to identify lessons that may be applicable across other chronic diseases, including SMIs.

Methods

We conducted focus groups with practicing endocrinologists from 2 large metropolitan areas using a semistructured discussion guide designed to elicit perspectives of and experiences with technology adoption. The thematic analysis identified barriers to and facilitators of integrating digital glucometers into clinical practice. Participants also provided recommendations for integrating digital health technologies into clinical practice more broadly.

Results

A total of 10 endocrinologists were enrolled: 60% (6/10) male; a mean of 18.4 years in practice (SD 5.6); and 80% (8/10) working in a group practice setting. Participants stated that digital glucometers represented a significant change in the treatment paradigm for diabetes care and facilitated more effective care delivery and patient engagement. Barriers to the adoption of digital glucometers included lack of coverage, provider reimbursement, and data management support, as well as patient heterogeneity. Participant recommendations to increase the use of digital health technologies included expanding reimbursement for clinician time, streamlining data management processes, and customizing the technologies to patient needs.

Conclusions

Digital glucose monitoring technologies have facilitated more effective, individualized care delivery and have improved patient engagement and health outcomes. However, key challenges faced by the endocrinologists included lack of reimbursement for clinician time and nonstandardized data management across devices. Key recommendations that may be relevant for other diseases include improved data analytics to quickly and accurately synthesize data for patient care management, streamlined software, and standardized metrics.

Antipsychotic Medication Adherence and Healthcare Services Utilization in Two Cohorts of Patients with Serious Mental Illness

Objective

To evaluate differences in patient characteristics and real-world outcomes in two distinct high-risk cohorts of patients with serious mental illness (SMI).

Methods

Retrospective cross-sectional analysis using a national multi-payer claims database. Two SMI cohorts identified by a technical expert panel—patients recently discharged (RD) from an SMI-related hospitalization and early episode (EE) patients—were evaluated for antipsychotic medication adherence, healthcare utilization, and spending patterns.

Results

The analysis included 51,705 patients with bipolar disorder, major depressive disorder, and schizophrenia. More than half were over age 46 and >60% were female. Adherence to psychiatric medications was low (52.5% RD and 16.1% EE). More than half of RD and 100% of EE patients switched medications at least once annually, but 19% of RD patients switched ≥2 times compared to 14% of EE. The RD cohort (generally older and sicker) had higher psychiatric related utilization and higher annual costs (US$21,171 versus US$15,398). In both cohorts, women were more likely to have an emergency department (ED) and primary care provider (PCP) visit, but less likely to be hospitalized. Patients age <46 were less likely to have a PCP visit and more likely to have an ED visit, but younger patients age 18–24 were less likely to be hospitalized.

Conclusion

Efforts to manage SMI are confounded by heterogeneity and low adherence to treatment. By better understanding which patients are at higher risk for specific adverse outcomes, clinicians can target interventions more appropriately to reduce the significant burden of SMI.

Digital health technology for use in patients with serious mental illness: a systematic review of the literature

BACKGROUND

As the capabilities and reach of technology have expanded, there is an accompanying proliferation of digital technologies developed for use in the care of patients with mental illness. The objective of this review was to systematically search published literature to identify currently available health technologies and their intended uses for patients with serious mental illness.

MATERIALS AND METHODS

The Medline, Embase, and BIOSIS Previews electronic databases were searched to identify peer-reviewed English language articles that reported the use of digital, mobile, and other advanced technology in patients with schizophrenia/schizoaffective disorder, bipolar disorder, and major depressive disorder. Eligible studies were systematically reviewed based on Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines.

RESULTS

Eighteen studies that met the inclusion criteria were identified. Digital health technologies (DHTs) assessed in the selected studies included mobile applications (apps), digital medicine, digital personal health records, and an electronic pill container. Smartphone apps accounted for the largest share of DHTs. The intended uses of DHTs could be broadly classified as monitoring to gain a better understanding of illness, clinical assessment, and intervention. Overall, studies indicated high usability/feasibility and efficacy/effectiveness, with several reporting validity against established clinical scales. Users were generally engaged with the DHT, and mobile assessments were deemed helpful in monitoring disease symptoms.

CONCLUSION

Rapidly proliferating digital technologies seem to be feasible for short-term use in patients with serious mental illness; nevertheless, long-term effectiveness data from naturalistic studies will help demonstrate their usefulness and facilitate their adoption and integration into the mental health-care system.

The cost of adherence mismeasurement in serious mental illness: a claims-based analysis

OBJECTIVES

To quantify how adherence mismeasurement affects the estimated impact of adherence on inpatient costs among patients with serious mental illness (SMI).

STUDY DESIGN

Proportion of days covered (PDC) is a common claims-based measure of medication adherence. Because PDC does not measure medication ingestion, however, it may inaccurately measure adherence. We derived a formula to correct the bias that occurs in adherence-utilization studies resulting from errors in claims-based measures of adherence.

METHODS

We conducted a literature review to identify the correlation between gold-standard and claims-based adherence measures. We derived a bias-correction methodology to address claims-based medication adherence measurement error. We then applied this methodology to a case study of patients with SMI who initiated atypical antipsychotics in 2 large claims databases.

RESULTS

Our literature review identified 6 studies of interest. The 4 most relevant ones measured correlations between 0.38 and 0.91. Our preferred estimate implies that the effect of adherence on inpatient spending estimated from claims data would understate the true effect by a factor of 5.3, if there were no other sources of bias. Although our procedure corrects for measurement error, such error also may amplify or mitigate other potential biases. For instance, if adherent patients are healthier than nonadherent ones, measurement error makes the resulting bias worse. On the other hand, if adherent patients are sicker, measurement error mitigates the other bias.

CONCLUSIONS

Measurement error due to claims-based adherence measures is worth addressing, alongside other more widely emphasized sources of bias in inference.

Access to credible information on schizophrenia patients' medication adherence by prescribers can change their treatment strategies: evidence from an online survey of providers

OBJECTIVE

Overestimating patients' medication adherence diminishes the ability of psychiatric care providers to prescribe the most effective treatment and to identify the root causes of treatment resistance in schizophrenia. This study was conducted to determine how credible patient drug adherence information (PDAI) might change prescribers' treatment decisions.

METHODS

In an online survey containing 8 clinical case vignettes describing patients with schizophrenia, health care practitioners who prescribe antipsychotics to patients with schizophrenia were instructed to choose a preferred treatment recommendation from a set of predefined pharmacologic and non-pharmacologic options. The prescribers were randomly assigned to an experimental or a control group, with only the experimental group receiving PDAI. The primary outcome was the prescribers' treatment choice for each case. Between-group differences were analyzed using multinomial logistic regression.

RESULTS

A convenience sample (n=219) of prescribers completed the survey. For 3 nonadherent patient vignettes, respondents in the experimental group were more likely to choose a long-acting injectable antipsychotic compared with those in the control group (77.7% experimental vs 25.8% control; P<0.001). For 2 adherent but poorly controlled patient vignettes, prescribers who received PDAI were more likely to increase the antipsychotic dose compared with the control group (49.1% vs 39.1%; P<0.001). For the adherent and well-controlled patient vignette, respondents in both groups made similar treatment recommendations across all choices (P=0.099), but respondents in the experimental arm were more likely to recommend monitoring clinical stability (87.2% experimental vs 75.5% control, reference group).

CONCLUSION

The results illustrate how credible PDAI can facilitate more appropriate clinical decisions for patients with schizophrenia.

Cost sharing, adherence, and health outcomes in patients with diabetes

OBJECTIVES

To assess the relationship between cost sharing and adherence to antidiabetic medications in patients with type 2 diabetes and to examine the relationship between medication adherence and outcomes, including complication rates, medical service utilization, and workplace productivity measures.

STUDY DESIGN

A retrospective, cross-sectional study analyzing the healthcare experience of patients with type 2 diabetes on oral antidiabetic medication (OAD) with or without insulin (n = 96,734) and patients on OAD only (n = 55,356) with employer-sponsored insurance in the 2003-2006 MarketScan Database.

METHODS

Using a 2-stage residual inclusion model, the first stage estimated the effects of cost sharing on adherence to antidiabetic medications in an 18-month time frame (January 2003 through June 2004). Adherence was determined from the percentage of days covered. The second stage estimated the effects of adherence on complication rates (eg, retinopathy, neuropathy, peripheral vascular disease), medical service utilization rates, and measures of productivity (absence days and short-term disability days) in the subsequent 2 years (July 2004 through June 2006).

RESULTS

A $10 increase in the patient cost-sharing index resulted in a 5.4% reduction in adherence to antidiabetic medications for patients on OAD only and a 6.2% reduction in adherence for patients on OAD with or without insulin. Adherence was associated with lower rates of complications (eg, amputation/ulcers, retinopathy) and also was associated with fewer emergency department visits and short-term disability days.

CONCLUSIONS

Medical plans, employers, and policy makers should consider implementing interventions targeted to improve antidiabetic medication adherence, which may translate to better outcomes.

A comparison of insulin use, glycemic control, and health care costs with insulin detemir and insulin glargine in insulin-naive patients with type 2 diabetes

OBJECTIVES

The goal of this study was to compare daily insulin use, glycemic control, and health care costs in insulin-naive patients with type 2 diabetes who initiated treatment with either insulin detemir or insulin glargine.

METHODS

This was a retrospective cohort analysis of health care claims data and laboratory results for adult, insulin-naive patients with type 2 diabetes who were enrolled in a large US managed care organization and initiated basal therapy with insulin detemir or insulin glargine between May 1, 2006, and December 31, 2006. The daily average consumption (DACON) of insulin was calculated as the total number of units dispensed (excluding the last fill) divided by the number of days between the index date and the date of the last fill of the index insulin. Glycemic control was evaluated by comparing mean glycosylated hemoglobin (HbA(1c)) values in the preindex period (the 180 days before the index date) and the follow-up period (the 180 days after the index date). Mean all-cause and diabetes-related health care costs in the preindex and follow-up periods were calculated and compared.

RESULTS

The analysis included 48 patients initiating therapy with insulin detemir and 258 initiating therapy with insulin glargine. The mean age of the 2 cohorts was approximately 54 years, and most patients in each cohort were male (52.1% and 59.7%, respectively). Few patients in either cohort had a baseline HbA(1c) value <7% (13% and 10%), suggesting poor glycemic control at the time of insulin initiation. After adjustment for confounders (eg, preindex diabetes medication), the DACON of insulin was comparable between cohorts (29.3 and 29.6 U/d; P = NS), as were follow-up HbA(1c) values (8.2% and 7.9%). Insulin detemir and insulin glargine also were associated with comparable mean adjusted all-cause pharmacy costs ($3074 and $2899), medical costs ($2319 and $3704), and total health care costs ($6014 and $7023). However, insulin glargine was associated with significantly higher mean adjusted diabetes-related medical costs compared with insulin detemir ($1510 vs $707, respectively; P = 0.03), as well as significantly higher mean adjusted total diabetes-related health care costs ($3408 vs $2261; P = 0.03).

CONCLUSIONS

In this managed care population of insulin-naive patients who initiated therapy with insulin detemir or insulin glargine, the daily insulin dose and glycemic control did not differ significantly between the 2 insulins. However, patients receiving insulin detemir incurred lower diabetes-related medical and total health care costs.

Effect of drug therapy on HEDIS measurements of HbA1c control in diabetes patients

The purpose of this study was to corroborate an earlier study that explored the relationship between a health plan's Health Plan Employer Data and Information Set (HEDIS) score for glycolated hemoglobin (HbA1c) control in diabetes patients and its utilization of insulin and oral diabetes products. Prescription volumes were tracked for four categories of diabetes drug therapy: analog insulin, human insulin, single-source brand oral products, and multisource generic oral products, for calendar years 2005 and 2006. The prescription shares of each of the four drug categories for each health plan were matched to the health plan's HEDIS measurements of HbA1c control for each year. Univariate and multivariate regression analysis was performed between the health plan's HbA1c -based HEDIS score and its prescription share of each drug category. A favorable and statistically significant (p < 0.01) relationship was found between plan HbA1c HEDIS score and plan prescription share of analog insulin in both 2005 and 2006. The correlation between HEDIS scores and human insulin was not statistically significant. Unfavorable relationships were found between HEDIS scores and both the single-source brand (statistically significant) and the multisource generic oral category prescription shares (not significant). These results corroborate the relationships found in our earlier study, although a cause and effect relationship cannot be confirmed.

Correlation of HEDIS diabetes health plan score with utilization of diabetes medications

This study sought to determine the correlation between a health plan's Health Plan Employer Data and Information Set (HEDIS) score for glycated hemoglobin (HbA1c) control in patients with diabetes and its utilization of analog insulin, human insulin, and oral drug therapy as determined by the share of prescriptions of each therapy. Prescription volumes were tracked for four categories of diabetes drug therapy: (1) analog insulin, (2) human insulin, (3) single-source brand oral products, and (4) multisource generic oral products, for the three months ending January 2005 and January 2006 and matched to the 2004 and 2005 HEDIS scores. A correlation analysis conducted between the HbA1c-based HEDIS score and the prescription share of each drug category found a favorable and statistically significant (P < .0001) correlation between plan HbA1c HEDIS score and plan prescription share of analog insulin in both 2004 and 2005. The correlation between HEDIS scores and human insulin was not statistically significant. Unfavorable correlations were found between HEDIS scores and both the single-source brand and the multisource generic oral category prescription shares, although these correlations were found to be significant only for the single-source products in 2005.