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

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

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

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.

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

2019 ◽  
Vol 29 ◽  
pp. S237-S238
Author(s):  
Emily Morris ◽  
Rolan Batallones ◽  
Jane Ryan ◽  
Caitlin Slomp ◽  
Prescilla Carrion ◽  
...  
Keyword(s):  
Mental Illness ◽  
Genetic Counseling ◽  
Medication Adherence ◽  
Serious Mental Illness ◽  
Psychotropic Medication

scholarly journals Patient experience with healthcare services among older adults with serious mental illness compared to the general older population

2017 ◽  
Vol 52 (4-6) ◽  
pp. 381-398 ◽  
Author(s):  
Karen L Fortuna ◽  
Matthew C Lohman ◽  
John A Batsis ◽  
Elizabeth A DiNapoli ◽  
Peter R DiMilia ◽  
...  
Keyword(s):  
Older Adults ◽  
Decision Making ◽  
Mental Illness ◽  
Patient Experience ◽  
Serious Mental Illness ◽  
Healthcare Services ◽  
Provider Communication ◽  
Shared Decision ◽  
Schizophrenia Spectrum Disorder ◽  
Schizophrenia Spectrum

Objective To compare patient experience with healthcare services and providers among older patients (≥50 years old) with and without serious mental illness. Methods Using secondary data from the Medical Expenditures Panel Survey from 2003 through 2013, we compared adults aged 50 years and older with schizophrenia spectrum disorder ( n = 106), mood disorders (i.e., major depressive disorder and bipolar disorder) ( n = 419), and no serious mental illness ( n = 34,921). Results Older adults with schizophrenia spectrum disorder reported significantly worse provider communication than older adults without serious mental illness. Older adults with mood disorders reported the greatest barriers to shared decision-making and the greatest difficulty accessing services. Conclusions Our results highlight the need to improve the patient experience of older adults with serious mental illness. Addressing provider communication, shared decision-making, and access to care among this vulnerable group of older adults may impact clinical outcomes and costs. Future research examining the extent to which improving the patient experience may improve health outcomes and enhance treatment for this highly vulnerable older group is warranted.

scholarly journals Glucose Control and Medication Adherence Among Veterans With Diabetes and Serious Mental Illness: Does Collocation of Primary Care and Mental Health Care Matter?

Diabetes Care ◽  
2014 ◽  
Vol 37 (8) ◽  
pp. 2261-2267 ◽  
Author(s):  
Judith A. Long ◽  
Andrew Wang ◽  
Elina L. Medvedeva ◽  
Susan V. Eisen ◽  
Adam J. Gordon ◽  
...  
Keyword(s):  
Mental Health ◽  
Primary Care ◽  
Health Care ◽  
Mental Illness ◽  
Medication Adherence ◽  
Mental Health Care ◽  
Serious Mental Illness ◽  
Glucose Control

scholarly journals Association of Patients Reading Clinical Notes With Perception of Medication Adherence Among Persons With Serious Mental Illness

2021 ◽  
Vol 4 (3) ◽  
pp. e212823 ◽  
Author(s):  
Charlotte Blease ◽  
Zhiyong Dong ◽  
John Torous ◽  
Jan Walker ◽  
Maria Hägglund ◽  
...  
Keyword(s):  
Mental Illness ◽  
Medication Adherence ◽  
Serious Mental Illness ◽  
Clinical Notes

scholarly journals Detection of Behavioral Anomalies in Medication Adherence Patterns Among Patients With Serious Mental Illness Engaged With a Digital Medicine System (Preprint)

2020 ◽  
Author(s):  
Jonathan Knights ◽  
Zahra Heidary ◽  
Jeffrey M Cochran
Keyword(s):  
Clinical Trial ◽  
Mental Illness ◽  
Medication Adherence ◽  
Anomaly Detection ◽  
Serious Mental Illness ◽  
Clinical Trial Data ◽  
Trial Data ◽  
Reference Sequence ◽  
Sequence Of Events ◽  
Digital Medicine

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 <i>adherence volatility</i> as <i>“the degree to which medication ingestion behavior fits expected behavior based on historically observed data”</i> 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 <i>adherence volatility</i> and develops a new type of contextual anomaly detection, which does not require an a priori definition of <i>normal</i> 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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