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Evaluating digital medicine ingestion data from seriously mentally ill patients with a Bayesian Hybrid Model.

ABSTRACT: The objective of this work was to adapt and evaluate the performance of a Bayesian hybrid model to characterize objective temporal medication ingestion parameters from two clinical studies in patients with serious mental illness (SMI) receiving treatment with a digital medicine system. This system provides a signal from an ingested sensor contained in the dosage form to a patient-worn patch and transmits this signal via the patient's mobile device. A previously developed hybrid Markov-von Mises model was used to obtain maximum-likelihood estimates for medication ingestion behavior parameters for individual patients. The individual parameter estimates were modeled to obtain distribution parameters of priors implemented in a Markov chain-Monte Carlo framework. Clinical and demographic covariates associated with model ingestion parameters were also assessed. We obtained individual estimates of overall observed ingestion percent (median:75.9%, range:18.2-98.3%, IQR:32.9%), rate of excess dosing events (median:0%, range:0-14.3%, IQR:3.0%) and observed ingestion duration. The modeling also provided estimates of the Markov-dependence probabilities of dosing success following a dosing success or failure. The ingestion-timing deviations were modeled with the von Mises distribution. A subset of 17 patients (22.1%) were identified as prompt correctors based on Markov-dependence probability of a dosing failure followed by a dosing success of unity. The prompt corrector sub-group had a better overall digital medicine ingestion parameter profile compared to those who were not prompt correctors. Our results demonstrate the potential utility of a Bayesian Hybrid Markov-von Mises model for characterizing digital medicine ingestion patterns in patients with SMI.

SUBMITTER: Knights J

PROVIDER: S-EPMC6550231 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Evaluating digital medicine ingestion data from seriously mentally ill patients with a Bayesian Hybrid Model.

Knights Jonathan J Heidary Zahra Z Peters-Strickland Timothy T Ramanathan Murali M

NPJ digital medicine 20190322

The objective of this work was to adapt and evaluate the performance of a Bayesian hybrid model to characterize objective temporal medication ingestion parameters from two clinical studies in patients with serious mental illness (SMI) receiving treatment with a digital medicine system. This system provides a signal from an ingested sensor contained in the dosage form to a patient-worn patch and transmits this signal via the patient's mobile device. A previously developed hybrid Markov-von Mises ...[more]

PMID: 31304367

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Project description:ObjectivesTo examine the association between the quality of care delivered to nursing home residents with and without a serious mental illness (SMI) and the proportion of nursing home residents with SMI.DesignInstrumental variable study. Relative distance to the nearest nursing home with a high proportion of SMI residents was used to account for potential selection of patients between high- and low-SMI facilities. Data were obtained from the 2006-2010 Minimum Data Set assessments linked with Medicare claims and nursing home information from the Online Survey, Certification, and Reporting database.SettingNursing homes with high (defined as at least 10% of a facility's population having an SMI diagnosis) and low proportions of SMI residents.ParticipantsA total of 58 571 Medicare nursing residents with an SMI diagnosis (ie, schizophrenia or bipolar disorder) and 558 699 individuals without an SMI diagnosis who were admitted to the same nursing homes.MeasurementsOutcomes were nursing home quality measures: (1) use of physical restraints, (2) any hospitalization in the last 3 months, (3) use of an indwelling catheter, (4) use of a feeding tube, and (5) presence of pressure ulcer(s).ResultsFor individuals with SMI, admission to a high-SMI facility was associated with a 3.7 percentage point (95% confidence interval [CI] = 1.4-6.0) increase in the probability of feeding tube use relative to individuals admitted to a low-SMI facility. Among individuals without SMI, admission to a high-SMI facility was associated with a 1.7 percentage point increase in the probability of catheter use (95 CI = .03-3.47), a 3.8 percentage point increase in the probability of being hospitalized (95% CI = 2.16-5.44), and a 2.1 percentage point increase in the probability of having a feeding tube (95% CI = .43-3.74).ConclusionAdmission to nursing homes with high concentrations of residents with SMI is associated with worse outcomes for both residents with and without SMI. J Am Geriatr Soc 67:2346-2352, 2019.

Project description:Background. In recent years, there has been an explosion in the number of technical and medical diagnostic platforms being developed. This has greatly improved our ability to more accurately, and more comprehensively, explore and characterize human biological systems on the individual level. Large quantities of biomedical data are now being generated and archived in many separate research and clinical activities, but there exists a paucity of studies that integrate the areas of clinical neuropsychiatry, personal genomics and brain-machine interfaces. Methods. A single person with severe mental illness was implanted with the Medtronic Reclaim(®) Deep Brain Stimulation (DBS) Therapy device for Obsessive Compulsive Disorder (OCD), targeting his nucleus accumbens/anterior limb of the internal capsule. Programming of the device and psychiatric assessments occurred in an outpatient setting for over two years. His genome was sequenced and variants were detected in the Illumina Whole Genome Sequencing Clinical Laboratory Improvement Amendments (CLIA)-certified laboratory. Results. We report here the detailed phenotypic characterization, clinical-grade whole genome sequencing (WGS), and two-year outcome of a man with severe OCD treated with DBS. Since implantation, this man has reported steady improvement, highlighted by a steady decline in his Yale-Brown Obsessive Compulsive Scale (YBOCS) score from ?38 to a score of ?25. A rechargeable Activa RC neurostimulator battery has been of major benefit in terms of facilitating a degree of stability and control over the stimulation. His psychiatric symptoms reliably worsen within hours of the battery becoming depleted, thus providing confirmatory evidence for the efficacy of DBS for OCD in this person. WGS revealed that he is a heterozygote for the p.Val66Met variant in BDNF, encoding a member of the nerve growth factor family, and which has been found to predispose carriers to various psychiatric illnesses. He carries the p.Glu429Ala allele in methylenetetrahydrofolate reductase (MTHFR) and the p.Asp7Asn allele in ChAT, encoding choline O-acetyltransferase, with both alleles having been shown to confer an elevated susceptibility to psychoses. We have found thousands of other variants in his genome, including pharmacogenetic and copy number variants. This information has been archived and offered to this person alongside the clinical sequencing data, so that he and others can re-analyze his genome for years to come. Conclusions. To our knowledge, this is the first study in the clinical neurosciences that integrates detailed neuropsychiatric phenotyping, deep brain stimulation for OCD and clinical-grade WGS with management of genetic results in the medical treatment of one person with severe mental illness. We offer this as an example of precision medicine in neuropsychiatry including brain-implantable devices and genomics-guided preventive health care.

Project description:BackgroundAccording to new Norwegian laws, mental healthcare for adults are obligated to assess all patients who are parents and to act on their children's needs. This article describes the study protocol of implementing the interventions Family Assessment and Child Talks for children of patients in the adult psychiatry of the University Hospital of Northern Norway. The project is designed to evaluate the process of changes in clinical practice due to the implementation of two interventions. The interventions to be implemented are a standardised Family Assessment Form and the intervention called Child Talks. The family assessment form is an intervention to identify children of mentally ill parents and their needs. The intervention Child Talks is a health-promoting and preventive intervention where the mental health workers talk with the family about the situation of the children and their needs.Methods/designThere are two groups of participants in this study: (1) mental health workers in the clinic (N=220) and (2) patients who are parents (N=200) receiving treatment in the clinic. (1) In the evaluation of clinical practice, the authors use a pre-test, post-test and 1-year follow-up design. At pre-test, the authors evaluate status quo among mental health workers in the clinic regarding knowledge, attitudes, collaborative routines and clinical practice related to families with parental mental illness. After the pre-test is finished, the project move on to implement the interventions Family Assessment Form and Child Talks in the clinic. At post-test and 1-year follow-up, the authors evaluate the impact of implementing the Family Assessment Form in terms of how many children were identified and offered Child Talks in the clinic or referred to other services for additional support. (2) In the evaluation of parents/patients experience with the interventions, the authors use a pre-test post-test design. To identify children of mentally ill patients, the authors collect data on demographical variables for the patient and the child at pre-measures, as well as data on parental competence (PSOC) and parental concerns (PEDS) about their children. At post-measures, the authors evaluate the impact of the intervention in terms of user satisfaction, as well as changes between pre- and post-measures on parental competence (PSOC) and parental concerns (PEDS) about their children.DiscussionThe implication of implementing new interventions to safeguard children of mentally ill patients and the limitation of not measuring child development directly are discussed.

Project description:BackgroundThe expectation to include patients as partners in research has steadily gained momentum. The vulnerability of frail and/or seriously ill patients provides additional complexity and may deter researchers from welcoming individuals from this patient population onto their teams. The aim was to synthesize the evidence on the engagement of frail and/or seriously ill patients as research partners across the research cycle.MethodsA systematic review was conducted using PRISMA guidelines. A search strategy included MEDLINE®, EMBASE®, Cumulative Index to Nursing and Allied Health Literature (CINAHL), and PsycINFO from database inception to April, 2019. Eligible studies were peer-reviewed qualitative, quantitative, and mixed methods research reporting on the engagement of frail and/or seriously ill patients as partners on research teams. The Mixed Methods Appraisal Tool was used to appraise study quality. Narrative analysis was conducted.ResultsOf 8763 citations, 30 were included. Most studies included individuals with cancer on the research team (60%). Barriers included: lack of time and resources (50%), discontinuity in contribution (37%), and concerns for well-being (33%). Facilitators included: trust and mutual respect (60%), structural accessibility (57%), flexibility in timing and methods of engagement (43%), and attention to care and comfort, (33%). Perceived impacts for patients included: renewed personal sense of agency (37%) and emotional/peer support (37%). Impacts for researchers included sensitization to the lived experience of disease (57%) and an increased appreciation of the benefits of patient engagement (23%). Research design, execution, and outcomes, developed with patients, were deemed more suitable, relevant and reflective of patients' priorities.ConclusionsThere is emerging evidence to suggest that research partnerships with frail and/or seriously ill patients can be achieved successfully. Patients mostly report benefit from partnering with research teams. Frailty and/or serious illness do present legitimate concerns for their well-being but appear to be successfully mitigated when researchers ensure that the purpose of engagement is well-defined, the timing and methods of engagement are flexible, and the practical and emotional needs of patient partners are addressed throughout the process.Systematic review registrationThe systematic review protocol was registered with the International Prospective Register of Systematic Reviews PROSPERO (CRD42019127994).

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Evaluating digital medicine ingestion data from seriously mentally ill patients with a Bayesian Hybrid Model.

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Evaluating digital medicine ingestion data from seriously mentally ill patients with a Bayesian Hybrid Model.

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