T40PSYCHIATRIC GENETIC COUNSELING: IMPACT ON PSYCHOTROPIC MEDICATION ADHERENCE IN PEOPLE WITH SERIOUS MENTAL ILLNESS

BACKGROUND Adherence to medication is often represented in the form of a success percentage over a period of time. Although noticeable changes to aggregate adherence levels may be indicative of unstable medication behavior, a lack of noticeable changes in aggregate levels over time does not necessarily indicate stability. The ability to detect developing changes in medication-taking behavior under such conditions in real time would allow patients and care teams to make more timely and informed decisions. OBJECTIVE This study aims to develop a method capable of identifying shifts in behavioral (medication) patterns at the individual level and subsequently assess the presence of such shifts in retrospective clinical trial data from patients with serious mental illness. METHODS We defined the term adherence volatility as “the degree to which medication ingestion behavior fits expected behavior based on historically observed data” and defined a contextual anomaly system around this concept, leveraging the empirical entropy rate of a stochastic process as the basis for formulating anomaly detection. For the presented methodology, each patient’s evolving behavior is used to dynamically construct the expectation bounds for each future interval, eliminating the need to rely on model training or a static reference sequence. RESULTS Simulations demonstrated that the presented methodology identifies anomalous behavior patterns even when aggregate adherence levels remain constant and highlight the temporal dependence inherent in these anomalies. Although a given sequence of events may present as anomalous during one period, that sequence should subsequently contribute to future expectations and may not be considered anomalous at a later period—this feature was demonstrated in retrospective clinical trial data. In the same clinical trial data, anomalous behavioral shifts were identified at both high- and low-adherence levels and were spread across the whole treatment regimen, with 77.1% (81/105) of the population demonstrating at least one behavioral anomaly at some point in their treatment. CONCLUSIONS Digital medicine systems offer new opportunities to inform treatment decisions and provide complementary information about medication adherence. This paper introduces the concept of adherence volatility and develops a new type of contextual anomaly detection, which does not require an a priori definition of normal and allows expectations to evolve with shifting behavior, removing the need to rely on training data or static reference sequences. Retrospective analysis from clinical trial data highlights that such an approach could provide new opportunities to meaningfully engage patients about potential shifts in their ingestion behavior; however, this framework is not intended to replace clinical judgment, rather to highlight elements of data that warrant attention. The evidence provided here identifies new areas for research and seems to justify additional explorations in this area.

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Factors contributing to antihypertensive medication adherence among adults with intellectual and developmental disability

Journal of Intellectual Disabilities ◽

10.1177/1744629520961958 ◽

2020 ◽

pp. 174462952096195

Author(s):

Nicholas V Resciniti ◽

Yuan Hong ◽

Suzanne McDermott

Keyword(s):

Mental Illness ◽

Medication Adherence ◽

Developmental Disabilities ◽

Direct Effect ◽

Developmental Disability ◽

Psychotropic Medication ◽

Indirect Effect ◽

Antihypertensive Medication ◽

Total Effect ◽

Intellectual And Developmental Disability

Adults with intellectual or developmental disabilities often have hypertension and mental illness, and are prescribed medications for treatment. This study examined psychotropic medication adherence as a mediator between the association of residence type and antihypertensive medication adherence for adults with intellectual or developmental disabilities. We used Medicaid data of adults with intellectual or developmental disabilities who had hypertension and prescribed antihypertensive medication (N = 1,201) to measure the direct effect, indirect effect, and total effect of residence type (home vs. supervised setting) and antihypertensive medication adherence, with a mediator of psychotropic medication adherence. The indirect effect of psychotropic medication adherence on antihypertensive medication adherence was 1.26 (OR = 1.26, CI: 1.08–1.52), holding residency constant. The direct effect of residential type on antihypertensive medication adherence was 3.75 (OR = 3.75, CI: 1.61–8.75). This association may be due to some features of having a mental illness or maybe the result of being prescribed more than one medication.

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

ClinicoEconomics and Outcomes Research ◽

10.2147/ceor.s231000 ◽

2020 ◽

Vol Volume 12 ◽

pp. 123-132

Author(s):

Felicia Forma ◽

Teresa Green ◽

Seung Kim ◽

Christie Teigland

Keyword(s):

Mental Illness ◽

Medication Adherence ◽

Serious Mental Illness ◽

Antipsychotic Medication ◽

Healthcare Services ◽

Services Utilization

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Characterization of activity behavior using a digital medicine system and comparison to medication ingestion in patients with serious mental illness

npj Digital Medicine ◽

10.1038/s41746-021-00436-1 ◽

2021 ◽

Vol 4 (1) ◽

Author(s):

Jeffrey M. Cochran ◽

Zahra Heidary ◽

Jonathan Knights

Keyword(s):

Mental Illness ◽

Medication Adherence ◽

Serious Mental Illness ◽

Activity Rhythm ◽

Activity Patterns ◽

Improve Medication Adherence ◽

Ingestion Rates ◽

Patient Level ◽

Activity Intensity ◽

Digital Medicine

AbstractActivity patterns can be important indicators in patients with serious mental illness. Here, we utilized an accelerometer and electrocardiogram incorporated within a digital medicine system, which also provides objective medication ingestion records, to explore markers of patient activity and investigate whether these markers of behavioral change are related to medication adherence. We developed an activity rhythm score to measure the consistency of step count patterns across the treatment regimen and explored the intensity of activity during active intervals. We then compared these activity features to ingestion behavior, both on a daily basis, using daily features and single-day ingestion behavior, and at the patient-level, using aggregate features and overall ingestion rates. Higher values of the single-day features for both the activity rhythm and activity intensity scores were associated with higher rates of ingestion on the following day. Patients with a mean activity rhythm score greater than the patient-level median were also shown to have higher overall ingestion rates than patients with lower activity rhythm scores (p = 0.004). These initial insights demonstrate the ability of digital medicine to enable the development of digital behavioral markers that can be compared to previously unavailable objective ingestion information to improve medication adherence.

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Antipsychotic medication adherence and preventive diabetes screening in Medicaid enrollees with serious mental illness: an analysis of real-world administrative data

BMC Health Services Research ◽

10.1186/s12913-020-06045-0 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Erica L. Stockbridge ◽

Nathaniel J. Webb ◽

Eleena Dhakal ◽

Manasa Garg ◽

Abiah D. Loethen ◽

...

Keyword(s):

Bipolar Disorder ◽

Mental Illness ◽

Medication Adherence ◽

Serious Mental Illness ◽

Antipsychotic Medication ◽

Clinical Characteristics ◽

Care Quality ◽

System Reform ◽

Diabetes Screening

Abstract Background There is excess amenable mortality risk and evidence of healthcare quality deficits for persons with serious mental illness (SMI). We sought to identify sociodemographic and clinical characteristics associated with variations in two 2015 Healthcare Effectiveness Data and Information Set (HEDIS) measures, antipsychotic medication adherence and preventive diabetes screening, among Medicaid enrollees with serious mental illness (SMI). Methods We retrospectively analyzed claims data from September 2014 to December 2015 from enrollees in a Medicaid specialty health plan in Florida. All plan enrollees had SMI; analyses included continuously enrolled adults with antipsychotic medication prescriptions and schizophrenia or bipolar disorder. Associations were identified using mixed effects logistic regression models. Results Data for 5502 enrollees were analyzed. Substance use disorders, depression, and having both schizophrenia and bipolar disorder diagnoses were associated with both HEDIS measures but the direction of the associations differed; each was significantly associated with antipsychotic medication non-adherence (a marker of suboptimal care quality) but an increased likelihood of diabetes screening (a marker of quality care). Compared to whites, blacks and Hispanics had a significantly greater risk of medication non-adherence. Increasing age was significantly associated with increasing medication adherence, but the association between age and diabetes screening varied by sex. Other characteristics significantly associated with quality variations according to one or both measures were education (associated with antipsychotic medication adherence), urbanization (relative to urban locales, residing in suburban areas was associated with both adherence and diabetes screening), obesity (associated with both adherence and diabetes screening), language (non-English speakers had a greater likelihood of diabetes screening), and anxiety, asthma, and hypertension (each positively associated with diabetes screening). Conclusions The characteristics associated with variations in the quality of care provided to Medicaid enrollees with SMI as gauged by two HEDIS measures often differed, and at times associations were directionally opposite. The variations in the quality of healthcare received by persons with SMI that were identified in this study can guide quality improvement and delivery system reform efforts; however, given the sociodemographic and clinical characteristics’ differing associations with different measures of care quality, multidimensional approaches are warranted.

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