Computers in clinical practice: applying experience from child psychiatry.
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ABSTRACT:
SUBMITTER: Parkin A
PROVIDER: S-EPMC1118503 | biostudies-literature | 2000 Sep
REPOSITORIES: biostudies-literature
Publications
Computers in clinical practice: applying experience from child psychiatry.
BMJ (Clinical research ed.) 20000901 7261
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Project description:BackgroundMany healthcare professionals use smartphones and tablets to inform patient care. Contemporary research suggests that handheld computers may support aspects of clinical diagnosis and management. This systematic review was designed to synthesise high quality evidence to answer the question; Does healthcare professionals' use of handheld computers improve their access to information and support clinical decision making at the point of care?MethodsA detailed search was conducted using Cochrane, MEDLINE, EMBASE, PsycINFO, Science and Social Science Citation Indices since 2001. Interventions promoting healthcare professionals seeking information or making clinical decisions using handheld computers were included. Classroom learning and the use of laptop computers were excluded. Two authors independently selected studies, assessed quality using the Cochrane Risk of Bias tool and extracted data. High levels of data heterogeneity negated statistical synthesis. Instead, evidence for effectiveness was summarised narratively, according to each study's aim for assessing the impact of handheld computer use.ResultsWe included seven randomised trials investigating medical or nursing staffs' use of Personal Digital Assistants. Effectiveness was demonstrated across three distinct functions that emerged from the data: accessing information for clinical knowledge, adherence to guidelines and diagnostic decision making. When healthcare professionals used handheld computers to access clinical information, their knowledge improved significantly more than peers who used paper resources. When clinical guideline recommendations were presented on handheld computers, clinicians made significantly safer prescribing decisions and adhered more closely to recommendations than peers using paper resources. Finally, healthcare professionals made significantly more appropriate diagnostic decisions using clinical decision making tools on handheld computers compared to colleagues who did not have access to these tools. For these clinical decisions, the numbers need to test/screen were all less than 11.ConclusionHealthcare professionals' use of handheld computers may improve their information seeking, adherence to guidelines and clinical decision making. Handheld computers can provide real time access to and analysis of clinical information. The integration of clinical decision support systems within handheld computers offers clinicians the highest level of synthesised evidence at the point of care. Future research is needed to replicate these early results and to identify beneficial clinical outcomes.
| S-EPMC4099138 | biostudies-literature
Project description:To investigate the utility of dimensional psychopathologies of disruptive mood and behavior disorders (DBDs) by applying latent profile analysis (LPA) for characterization of youth referred to the tertiary outpatient clinic of child and adolescent psychiatry clinic and pharmacological treatment choices. One hundred fifty-eight children and adolescents with significant DBDs symptoms participated. Core dimensional psychopathologies of DBDs (irritability, callous-unemotional trait, and reactive-proactive aggressive behavior), DSM diagnoses, prescribed medications, and behavioral and emotional problems (Child Behavior Checklist, CBCL) were measured at baseline (clinic intake) and at 3-month follow-up. Latent Profile Analysis (LPA) was applied to characterize the study population based on the levels and interrelations among the core dimensional DBDs psychopathologies. Following LPA, the differences in clinical and treatment features between the latent classes were analyzed. LPA revealed two latent classes based on severity of DBDs symptoms. Class 1 (the moderate group) was characterized by relatively low scores on all trans-diagnostic indicators, whereas class 2 (the severe/critical group) showed higher levels of the dimensional psychopathologies and the majority of CBCL subscales. In addition, the severe/critical group was more often prescribed antipsychotic medications, and also experienced more frequent medication changes (addition, increasing the dose, and trial of different medications). Our findings suggested that application of LPA to a cluster of dimensional DBDs psychopathologies may provide valuable characterization of the youths referred to a tertiary outpatient child and adolescent psychiatric clinic, and offer insight into the providers' decision making on psychotropic medications, by overall severity of these psychopathologies rather than by single categorical diagnosis or single externalizing psychopathology.
| S-EPMC9020472 | biostudies-literature
Project description:Pharmacogenetic/pharmacogenomic (PGx) approaches to psychopharmacology aim to identify clinically meaningful predictors of drug efficacy and/or side-effect burden. To date, however, PGx studies in psychiatry have not yielded compelling results, and clinical utilization of PGx testing in psychiatry is extremely limited. In this review, the authors provide a brief overview on the status of PGx studies in psychiatry, review the commercialization process for PGx tests and then discuss methodological considerations that may enhance the potential for clinically applicable PGx tests in psychiatry. The authors focus on design considerations that include increased ascertainment of subjects in the earliest phases of illness, discuss the advantages of drug-induced adverse events as phenotypes for examination and emphasize the importance of maximizing adherence to treatment in pharmacogenetic studies. Finally, the authors discuss unique aspects of pharmacogenetic studies that may distinguish them from studies of other complex traits. Taken together, these data provide insights into the design and methodological considerations that may enhance the potential for clinical utility of PGx studies.
| S-EPMC3928114 | biostudies-literature
Project description:AimTo report experience with fingolimod in clinical practice.Design/methodsPatients in an academic medical center who were prescribed fingolimod from October 2010 to August 2011 were identified through the electronic medical record and followed for 12 months after fingolimod initiation. Adverse effects (AEs), clinical measures, MRI data, and quality of life measures were assessed.ResultsThree hundred seventeen patients started fingolimod. Eleven patients were treatment naïve (3.5%) and 76 (24.0%) had remote disease modifying therapy (DMT) use prior to fingolimod. One hundred fifty-one (47.6%) switched because of patient preference and 79 (24.9%) switched because of breakthrough disease. About 11.6% transitioned from natalizumab. Follow-up data were available for 306 patients (96.5%) with mean follow-up time 332 days. Fingolimod was discontinued in 76 of 306 patients (24.8%) at mean 248 days after fingolimod start. Discontinuation most often was due to AEs (n = 40) or breakthrough disease (n = 22). Among patients who started fingolimod with available 12 month follow-up data, 267 (87.3%) remained relapse free and 256 (83.7%) had no relapses or gadolinium enhancement. Time to first relapse occurred at mean 282 days after fingolimod initiation. Quality of life measures remained stable at follow-up.ConclusionsFingolimod was discontinued at a higher rate in clinical practice than in clinical trials. Discontinuation was primarily due to AEs or breakthrough disease. Disease activity was adequately controlled in most patients who started fingolimod. This clinical practice cohort is consistent with efficacy data from phase 3 trials and describes the most common tolerability issues in clinical practice.
| S-EPMC4414718 | biostudies-literature
Project description:Translational research on complex, multifactorial mental health disorders, such as bipolar disorder, major depressive disorder, schizophrenia, and substance use disorders requires databases with large-scale, harmonized, and integrated real-world and research data. The Munich Mental Health Biobank (MMHB) is a mental health-specific biobank that was established in 2019 to collect, store, connect, and supply such high-quality phenotypic data and biosamples from patients and study participants, including healthy controls, recruited at the Department of Psychiatry and Psychotherapy (DPP) and the Institute of Psychiatric Phenomics and Genomics (IPPG), University Hospital of the Ludwig-Maximilians-University (LMU), Munich, Germany. Participants are asked to complete a questionnaire that assesses sociodemographic and cross-diagnostic clinical information, provide blood samples, and grant access to their existing medical records. The generated data and biosamples are available to both academic and industry researchers. In this manuscript, we outline the workflow and infrastructure of the MMHB, describe the clinical characteristics and representativeness of the sample collected so far, and reveal future plans for expansion and application. As of 31 October 2021, the MMHB contains a continuously growing set of data from 578 patients and 104 healthy controls (46.37% women; median age, 38.31 years). The five most common mental health diagnoses in the MMHB are recurrent depressive disorder (38.78%; ICD-10: F33), alcohol-related disorders (19.88%; ICD-10: F10), schizophrenia (19.69%; ICD-10: F20), depressive episode (15.94%; ICD-10: F32), and personality disorders (13.78%; ICD-10: F60). Compared with the average patient treated at the recruiting hospitals, MMHB participants have significantly more mental health-related contacts, less severe symptoms, and a higher level of functioning. The distribution of diagnoses is also markedly different in MMHB participants compared with individuals who did not participate in the biobank. After establishing the necessary infrastructure and initiating recruitment, the major tasks for the next phase of the MMHB project are to improve the pace of participant enrollment, diversify the sociodemographic and diagnostic characteristics of the sample, and improve the utilization of real-world data generated in routine clinical practice.
| S-EPMC9353268 | biostudies-literature
Project description:ObjectiveTo place imaging-genetics research in the context of child psychiatry.MethodA conceptual overview is provided, followed by discussion of specific research examples.ResultsImaging-genetics research is described linking brain function to two specific genes, for the serotonin-reuptake-transporter protein and a monoamine oxidase enzyme. Work is then described on phenotype selection in imaging genetics.ConclusionsChild psychiatry applications of imaging genetics are only beginning to emerge. The approach holds promise for advancing understandings of pathophysiology and therapeutics.
| S-EPMC2997350 | biostudies-literature
Project description:BackgroundThe impact of precision psychiatry for clinical practice has not been systematically appraised. This study aims to provide a comprehensive review of validated prediction models to estimate the individual risk of being affected with a condition (diagnostic), developing outcomes (prognostic), or responding to treatments (predictive) in mental disorders.MethodsPRISMA/RIGHT/CHARMS-compliant systematic review of the Web of Science, Cochrane Central Register of Reviews, and Ovid/PsycINFO databases from inception until July 21, 2019 (PROSPERO CRD42019155713) to identify diagnostic/prognostic/predictive prediction studies that reported individualized estimates in psychiatry and that were internally or externally validated or implemented. Random effect meta-regression analyses addressed the impact of several factors on the accuracy of prediction models.FindingsLiterature search identified 584 prediction modeling studies, of which 89 were included. 10.4% of the total studies included prediction models internally validated (n = 61), 4.6% models externally validated (n = 27), and 0.2% (n = 1) models considered for implementation. Across validated prediction modeling studies (n = 88), 18.2% were diagnostic, 68.2% prognostic, and 13.6% predictive. The most frequently investigated condition was psychosis (36.4%), and the most frequently employed predictors clinical (69.5%). Unimodal compared to multimodal models (β = .29, P = .03) and diagnostic compared to prognostic (β = .84, p < .0001) and predictive (β = .87, P = .002) models were associated with increased accuracy.InterpretationTo date, several validated prediction models are available to support the diagnosis and prognosis of psychiatric conditions, in particular, psychosis, or to predict treatment response. Advancements of knowledge are limited by the lack of implementation research in real-world clinical practice. A new generation of implementation research is required to address this translational gap.
| S-EPMC7965077 | biostudies-literature
Project description: Not available
| S-EPMC359432 | biostudies-literature
Project description:The United States has a critical shortage of child and adolescent psychiatrists such that 70% of counties in the United States do not have any child and adolescent psychiatrists.1 Since 2014, the number of US and Canadian medical school applicants to psychiatry residencies has increased by 69%; however, the number of child and adolescent psychiatry fellowship applicants has increased by only 11%.2 Up to two-thirds of psychiatry residents report considering a career in child and adolescent psychiatry; however, only one-fourth of residents ultimately apply for a child and adolescent psychiatry subspecialty training.3,4 We surveyed child and adolescent psychiatry fellows across the country to understand the different pathways into child and adolescent psychiatry, with the hope of providing program directors' and faculty mentors' guidance on how to generate interest in child and adolescent psychiatry and to support residents in this pursuit.
| S-EPMC8120247 | biostudies-literature
Project description:The real world needs of the clinical community require a domain-specific solution to integrate disparate information available from various web-based resources for data, materials, and tools into routine clinical and clinical research setting. We present a child-psychiatry oriented portal as an effort to deliver a knowledge environment wrapper that provides organization and integration of multiple information and data sources. Organized semantically by resource context, the portal groups information sources by context type, and permits the user to interactively "narrow" or "broaden" the scope of the information resources that are available and relevant to the specific context. The overall objective of the portal is to bring information from multiple complex resources into a simple single uniform framework and present it to the user in a single window format.
| S-EPMC4012203 | biostudies-literature