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

Real-World Evidence of Aripiprazole Tablets with Sensor: Treatment Patterns and Impacts on Psychiatric Healthcare Resource Utilization

Purpose

Maintaining adherence to antipsychotic (AP) medication is often challenging. Aripiprazole tablets with sensor (AS) contain an ingestible event marker and communicate with wearable patches and a smartphone app to provide objective medication ingestion data. This study evaluated real-world treatment patterns of AS usage and its impact on psychiatric healthcare resource utilization (HCRU).

Patients and Methods

This retrospective, observational cohort study identified individuals who initiated AS between 1/1/2019 and 6/30/2020 with 3 months baseline and 6 months of follow-up data using a commercial medical and pharmacy claims database (Clarivate). Controls were propensity score-matched (4:1) to AS initiators based on age (±2 years), sex, diagnosis (major depressive disorder [MDD], schizophrenia, bipolar I disorder [BP-I], other), insurance, and baseline oral AP use (yes/no). Days of AP supply were evaluated using a general regression model. The frequency of psychiatric HCRU during follow-up was compared between groups using a zero-inflated regression model.

Results

Most AS initiators were diagnosed with MDD (61.2%) and were women (61.2%); mean age was 37.7 years (standard deviation: 14.1). Most AS initiators (53.1%) continued treatment for >60 days (mean days of supply = 77). After adjusting for covariates, AS initiators had 41% more days of AP supply during follow-up compared with controls (P <0.0001) and significantly lower adjusted odds ratios (ORs) for psychiatric outpatient visits (adjusted OR = 0.80; P <0.05), emergency department visits (adjusted OR = 0.11; P <0.05), inpatient visits (adjusted OR = 0.42; P <0.05), and other medical services (adjusted OR = 0.25; P <0.05).

Conclusion

Participants who implemented AS had significantly more days of AP supply and fewer psychiatric care visits. These preliminary results suggest AS usage can help build regular medication-taking habits and holds promise for reducing psychiatric HCRU. Additional studies with larger sample sizes are warranted to inform clinical practice and coverage decisions.

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.

A scoping review: Treatment attitudes and adherence for adults with schizophrenia

AIM AND OBJECTIVES

This scoping review presents an exploration of literature on the relationship between treatment attitudes and adherence in adults experiencing schizophrenia.

BACKGROUND

Strategies to address adherence and improve treatment outcomes are described in literature. However, adherence remains a challenge for people experiencing mental illness in practice. Transformational frameworks, evidence-based practice and patient-centred approaches have been established and implemented but non-adherence incidence rates continue to rise among people with schizophrenia. Moreover, the relationship between treatment attitudes and adherence in adults diagnosed with schizophrenia remains unclear.

DESIGN

A scoping review using the framework offered by Implementation Science, 5, 2010, 1. The PRISMA-ScR checklist was used to ensure integrity of the review.

METHODS

Four databases PsychINFO, Medline, Cochrane and CINAHL databases were searched for literature along with the reference lists of eligible sources. Original research, peer-reviewed articles published between 2010 and 2020 in English language were included. Articles were included if study participants were adults with a diagnosis of schizophrenia or related psychosis. Methodological quality was evaluated using a quality assessment checklist, the Critical Appraisal Skills Programme tool.

RESULTS

Ten articles were included in the study. Five main themes about treatment adherence emerged from the literature: (i) severity of symptoms, (ii) side effects, (iii) beliefs and attitudes, (iv) insight and (v) support and relationships.

CONCLUSIONS

This scoping review concluded that attitude influenced adherence to medication in people with schizophrenia. The five main themes reported directly influenced attitude, impacting on treatment adherence in people experiencing schizophrenia. This review makes recommendations for a person-centred and recovery framework that aims to improve adherence.

RELEVANCE TO CLINICAL PRACTICE

Nurses in all healthcare settings could use evidence-based strategies to enhance treatment adherence in people with a range of physical and mental health conditions.

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.

A Program to Increase the Appropriate Use of Long-Acting Injectable Antipsychotic Medications in Community Settings

OBJECTIVE

The Multilevel Facilitation of Long-Acting Antipsychotic Medication Program (MAP) is a novel intervention to increase the appropriate use of long-acting injectable (LAI) antipsychotics in community mental health clinics. The authors investigated the feasibility of MAP, facilitators and barriers to use, and preliminary impact on LAI medication use.

METHODS

Two clinics in Texas and two in Ohio serving 750 and 617 individuals with schizophrenia receiving oral antipsychotics, respectively, were asked to change clinical procedures for 1 year by using either the not receiving optimum benefit (NOB) checklist or the checklist plus MAP. Providers used the NOB checklist to identify individuals who could benefit from switching to LAI antipsychotics. MAP clinics used the NOB checklist plus nonbranded academic detailing for providers and a shared-decision-making video and tool for consumers. Use of MAP components was tracked, and barriers and facilitators were collected quarterly. Antipsychotic prescription counts were provided by participating clinics.

RESULTS

Barriers to use of MAP included loss of local champions and administrators, difficulty with provider buy-in, limited availability of peer specialists, and a lack of infrastructural support to integrate MAP into clinic flow. Higher scores on the NOB checklist were associated with more provider LAI medication offers and greater patient acceptance of LAI antipsychotics. LAI medication use increased in clinics over time, but it is unclear whether this increase was due to MAP.

CONCLUSIONS

Changing MAP components to fit local procedures and to circumvent unique barriers could aid implementation. Further research should investigate the potential impact of MAP components on LAI medication use.

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.

Prescriber Attitudes, Experiences, and Proclivities Toward Digital Medicine and How They Influence Adoption of Digital Medicine Platforms

BACKGROUND

Psychiatric prescribers (prescribers) typically assess medication adherence by patient or caregiver self-report. Despite likely clinical benefit of a new digital medicine technology, the role of specific prescriber attitudes, behaviors, and experiences in the likelihood of adoption is unclear.

OBJECTIVE

To identify prescriber characteristics that may affect adoption of the ingestible event marker (IEM) platform.

DESIGN

A survey of prescribers treating seriously mentally ill patients was conducted. Factor analysis was performed on 11 items representing prescriber characteristics believed to be related to endorsement of the IEM platform. Four factors were extracted. Regression analysis was used to test the strength of the relationships between the factors and likelihood of adoption of the IEM platform.

RESULTS

A total of 131 prescribers completed the survey. Most (84%) agreed that visits allow enough time to monitor adherence. Factor analysis revealed four underlying dimensions: 1) perspectives on the value of adherence; 2) concerns about measuring adherence; 3) views toward digital health technologies; and 4) views on payer role/reimbursement. Factors 1 and 3 were related to gender, the belief that computerization benefits prescribers, the presence of office support staff, and the belief that new digital medicine (DM) technology will be cost prohibitive. Willingness to adopt the IEM platform was related to gender (p < 0.05) and perspectives on the value of adherence (p < 0.05), with those scoring higher on that measure also being more likely to adopt.

CONCLUSION

Psychiatric prescribers are concerned about medication adherence, perceive current monitoring tools to be problematic, and are open to using digital technologies to improve accuracy of adherence assessment. Relationships among prescriber characteristics, beliefs, and experiences should be considered when developing educational materials, particularly when the goal is to encourage adoption and use of the IEM platform.

Using Information on Patient Adherence to Antipsychotic Medication to Understand Their Adherence to Other Medications

PURPOSE

To assess how patient adherence to atypical antipsychotic medications is associated with adherence to concurrently used medications that treat other serious mental illnesses (SMIs), type-2 diabetes, or hypertension.

METHODS

Among patients who had been diagnosed with an SMI (i.e., bipolar disorder, major depressive disorder, or schizophrenia) in the previous year, we used health-insurance claims data to measure adherence based on medication fills. Patients diagnosed with an SMI were required to have 1) a prescription for an atypical oral antipsychotic, and 2) another SMI therapy or oral anti-diabetic or antihypertensive agent in the same year. The patient's concurrent adherence to an antipsychotic and one of 23 other medications was measured by the proportion of days covered (PDC) over a one-year period. Patients were considered adherent when the PDC was ≥ 80%. The strength of the association between their atypical antipsychotic adherence and their concurrent medication adherence was evaluated using the following metrics: accuracy, positive predictive value (PPV), and negative predictive value (NPV).

RESULTS

The average (standard deviation) age of patients (N = 129,614) was 44.8 (14.8) years and 62.2% of patients were female. The median accuracy based on atypical antipsychotic adherence to the other 23 medications was 67% (range, 55-71%; statistically different from 50% accuracy in all cases, P < 0.001). Accuracy was higher than physician predictions of adherence from previous studies (53%). The negative predictive value of antipsychotic adherence (75%; range, 62-88%) was generally higher than the PPV (62%; range, 43-67%; all, P < 0.001).

CONCLUSION

Information on patient adherence to antipsychotics provides significant insight into adherence to other medications often used by patients with SMI. Because NPV is higher than PPV, adherence to antipsychotics is likely to be a necessary but not sufficient condition for patients with SMI regarding adherence to non-SMI medications.

Measuring adherence to antipsychotic medications for schizophrenia: Concordance and validity among a community sample in rural China

BACKGROUND

Despite the abundance of measures to assess medication adherence by persons suffering schizophrenia, few studies have evaluated their concordance and validity against a reference standard in resource-poor community settings. We explored the concordance and validity of several measures to assess antipsychotic medication adherence in a resource-poor community.

METHOD

Based on a random sample of 278 villagers diagnosed with schizophrenia from Liuyang, Hunan Province, China, we used a concordance correlation coefficient (rc) and Kappa statistic to assess agreement among pill counts, refill records, clinician rating, Drug Attitude Inventory (DAI), and the Brief Adherence Rating Scale (BARS). The validity of various measures was evaluated by their concordance and sensitivity/specificity to home-based unannounced pill count (UPC) as the reference standard.

RESULTS

The estimated proportion of adherent patients according to all measures (41% ~ 88%) was substantially higher than identified by UPC (35%). Concordance between any two measures was poor (rc/Kappa mostly <0.30). Validity of various measures also was poor against the UPC (rc < 0.20; Kappa <0.16), although refill records and the structured instruments (BARS) performed better than office-based pill counts and clinician impression. BARS, DAI and clinician rating were not sensitive to changes in adherence and would likely underestimate any program effect.

CONCLUSION

In resource-poor community settings, most measures assessed in this study should not be used alone as they overestimated adherence, underestimated program effect, and had poor validity. A combination of UPC and several other measures may provide more insight into clinical trials and programmatic management.

Does knowledge of patient non-compliance change prescribing behavior in the real world? A claims-based analysis of patients with serious mental illness

Background

New digital technologies offer providers the promise of more accurately tracking patients’ medication adherence. It is unclear, however, whether access to such information will affect provider treatment decisions in the real world.

Methods

Using prescriber-reported information on patient non-compliance from health insurance claims data between 2008 and 2014, we examined whether prescribers’ knowledge of non-compliance was associated with different prescribing patterns for patients with serious mental illness (SMI). We examined patients who initiated an oral atypical antipsychotic, but were later objectively non-adherent to this treatment, defined as proportion of days covered (PDC) <0.8. We examined how a physician’s awareness of patient non-compliance (ICD-9 diagnosis code: V15.81) was correlated with the physician’s real-world treatment decisions for that patient. Treatment decisions studied included the share of patients who increased antipsychotic dose, augmented treatment, switched their antipsychotic, or used a long-acting injectable (LAI).

Results

Among the 286,249 patients with SMI who initiated an antipsychotic and had PDC <0.8, 4,033 (1.4%) had documented non-compliance. When prescribers documented non-compliance, patients were more likely to be switched to another antipsychotic (32.8% vs 24.7%, P<0.001), have their dose increased (24.4% vs 22.1%, P=0.004), or receive an LAI (0.09% vs 0.04%, P=0.008), but were less likely to have augmented therapy with another antipsychotic (1.1% vs 1.3%, P=0.035) than patients without documented non-compliance.

Conclusion

Among SMI patients with documented non-compliance, the frequency of dose, medication switches, and LAI use were higher and augmentation was lower compared to patients without documented non-compliance. Access to adherence information may help prescribers more rapidly switch ineffective medications as well as avoid unnecessary medication augmentation.