Medical data formatting to improve physician interpretation speed in the Military Healthcare System.
Ontology highlight
ABSTRACT: Objective
The purpose of this project was to improve ease and speed of physician comprehension when interpreting daily laboratory data for patients admitted within the Military Healthcare System (MHS).Materials and methods
A JavaScript program was created to convert the laboratory data obtained via the outpatient electronic medical record (EMR) into a "fishbone diagram" format that is familiar to most physicians. Using a balanced crossover design, 35 internal medicine trainees and staff at Naval Medical Center Portsmouth were asked to complete timed comprehension tests for laboratory data sets formatted in the outpatient EMR's format and in fishbone diagram format. The number of responses per second and error rate per response were measured for each format. Participants were asked to rate relative ease of use for each format and indicate which format they preferred.Results
Comprehension speed increased 37% (6.28 seconds per interpretation) with the fishbone diagram format with no observed increase in errors. Using a Likert scale of 1-5 (1 being hard, 5 easy), participants indicated the new format was easier to use (4.14 for fishbone vs 2.14 for table) with 89% expressing preference for the new format.Discussion
The publically available web application that converts tabular lab data to fishbone diagram format is currently used 10 000-12 000 times per month across the MHS, delivering significant benefit to the enterprise in terms of time saved and improved physician experience.Conclusions
This study supports the use of fishbone diagram formatting for laboratory data for inpatients within the MHS.
SUBMITTER: Peterson JE
PROVIDER: S-EPMC9239313 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:ObjectivesTo explore physician satisfaction with an electronic medical records (EMR) system, to identify and explore the main limitations of the system and finally to submit recommendations to address these limitations.DesignA descriptive qualitative study that entailed three focus group interviews was performed among physicians using open-ended questions. The interviews were audiotaped, documented and transcribed verbatim. The themes were explored and analysed in different categories.SettingThe study was conducted in primary healthcare centres (PHC) in Al Ain, United Arab Emirates (UAE).ParticipantsA total of 23 physicians, all using the same EMR system, attended one of three focus groups held in PHC in Al Ain Medical District. Each focus group consisted of 7-9 physicians working in PHC as family medicine specialists, residents or general practitioners.Primary outcome measurePhysician satisfaction with the EMR system.ResultsKey themes emerged and were categorised as physician-dependent, patient-related and system-related factors. In general, physicians were satisfied with the EMR system in spite of initial difficulties with implementation. Most participants identified that the long time required to do the documentation affected their practice and patient communication. Many physicians expressed satisfaction with the orders and results of laboratory and radiology functions and they emphasised that this was the strongest point in the EMR. They were also satisfied with the electronic prescription function, stating that it reduced errors and saved time.ConclusionsPhysicians are satisfied with the EMR and have a positive perception regarding the application of the system. Several themes emerged during this study that need to be considered to enhance the EMR system. Further studies need to be conducted among other healthcare practitioners and patients to explore their attitude and perception about the EMR.
| S-EPMC4225459 | biostudies-literature
Project description:BackgroundLittle is known about how physicians interpret data displays that depict preliminary or exploratory clinical data in physician-targeted sales aids for oncology drugs. Using three factorial experiments, we examined whether disclosures of data limitations and clinical uncertainty adequately communicate the limitations and practical utility of this type of data.Subjects, materials, and methodsThe studies used a 2 (disclosure of data limitations: technical, nontechnical) × 2 (disclosure of clinical uncertainty: present, absent) + 1 (control: no disclosure) between-subjects experimental design to examine the impact of disclosures as they relate to presentations of preliminary or exploratory data in promotional communications for oncology products. In each experiment, we randomized oncologists and primary care physicians with oncology experience to view one version of a two-page sales aid. Following this exposure, physicians completed a web-based survey. The design was replicated in three concurrently conducted experiments using sales aids for different fictitious oncology drugs, each featuring one of three common data displays: a forest plot (n = 495), a Kaplan-Meier curve (n = 504), or a bar chart (n = 532).ResultsResults provide initial evidence that in some contexts disclosures can improve understanding of the clinical utility of certain information about a drug and the limitations of results presented in a data display. Disclosures can also temper perceptions of how much evidence is presented that supports a conclusion that the drug is an appropriate treatment. In terms of the language used in the disclosure of data limitations, physicians in all three experiments strongly preferred the nontechnical disclosures.ConclusionThe findings from the three experiments in this study suggest that disclosures have the potential to increase relevant knowledge, but more research is needed to establish best practice recommendations for using disclosures to convey contextual information relevant for interpreting data displays in promotional communications.Implications for practiceThis article reports the results from three large, online experimental studies that address a growing concern that drug companies often share favorable clinical trial results with physicians in promotional materials that lack important context for physicians to interpret the data. This series of studies investigates whether strategic use of two types of disclosures (disclosure of data limitations and a disclosure of clinical uncertainty) improves understanding and reduces misinterpretations among physicians. The results from these studies help identify communication factors that impact how physicians critically appraise preliminary or exploratory clinical trial data to inform policy and regulatory efforts.
| S-EPMC8649057 | biostudies-literature
Project description:BackgroundDiagnosing multiple sclerosis (MS) early is crucial to avoid future disability. However, potentially preventable delays in the diagnostic cascade from contact with a physician to definite diagnosis still occur and their causes are still unclear.ObjectiveTo identify the possible causes of delays in the diagnostic process.MethodsWe analyzed the data of the Swiss MS Registry. With logistic regression, we modeled the time from the first contact to the first consultation (contact-to-evaluation time, ⩽1 month/>1 month) and the evaluation-to-diagnosis time (⩽6 months/>6 months). Potential factors were health system characteristics, sociodemographic variables, first symptoms, and MS type.ResultsWe included 522 participants. Mostly, general practitioners (67%) were contacted first, without delaying the diagnosis. In contrast, first symptoms and MS type were the major contributors to delays: gait problems were associated with longer contact-to-evaluation times, depression as a concomitant symptom with longer evaluation-to-diagnosis times, and having primary progressive MS prolonged both phases. In addition, living in mountainous areas was associated with longer contact-to-evaluation times, whereas diagnosis after 2000 was associated with faster diagnoses.ConclusionFor a quicker diagnosis, awareness of MS as a differential diagnosis of gait disorders and the co-occurrence of depression at onset should be raised, and these symptoms should be attentively followed.
| S-EPMC7140343 | biostudies-literature
Project description:MOTIVATION:Over the past years, significant resources have been invested into formalizing biomedical ontologies. Formal axioms in ontologies have been developed and used to detect and ensure ontology consistency, find unsatisfiable classes, improve interoperability, guide ontology extension through the application of axiom-based design patterns and encode domain background knowledge. The domain knowledge of biomedical ontologies may have also the potential to provide background knowledge for machine learning and predictive modelling. RESULTS:We use ontology-based machine learning methods to evaluate the contribution of formal axioms and ontology meta-data to the prediction of protein-protein interactions and gene-disease associations. We find that the background knowledge provided by the Gene Ontology and other ontologies significantly improves the performance of ontology-based prediction models through provision of domain-specific background knowledge. Furthermore, we find that the labels, synonyms and definitions in ontologies can also provide background knowledge that may be exploited for prediction. The axioms and meta-data of different ontologies contribute to improving data analysis in a context-specific manner. Our results have implications on the further development of formal knowledge bases and ontologies in the life sciences, in particular as machine learning methods are more frequently being applied. Our findings motivate the need for further development, and the systematic, application-driven evaluation and improvement, of formal axioms in ontologies. AVAILABILITY AND IMPLEMENTATION:https://github.com/bio-ontology-research-group/tsoe. SUPPLEMENTARY INFORMATION:Supplementary data are available at Bioinformatics online.
| S-EPMC7141863 | biostudies-literature
Project description:This paper presents a healthcare information and medical resource management platform utilizing wearable devices, physiological sensors, and an indoor positioning system (IPS). This platform provides medical healthcare information management based on the physiological information collected by wearable devices and Bluetooth data collectors. The Internet of Things (IoT) is constructed for this medical care purpose. The collected data are classified and used to monitor the status of patients in real time with a Secure MQTT mechanism. The measured physiological signals are also used for developing an IPS. When the patient is out of the safety zone, the IPS will send an alert message instantly by pushing the server to remind the caretaker, easing the caretaker's burden and offering extra protection for the patient. The presented system also provides medical resource management with the help of IPS. The medical equipment and devices can be tracked by IPS to tackle some equipment rental problems, such as lost and found. A platform for the medical staff work coordination information exchange and transmission is also developed to expedite the maintenance of medical equipment, providing the shared medical information to healthcare and management staff in a timely and transparent manner. The presented system in this paper will finally reduce the loading of medical staff during the COVID-19 pandemic period.
| S-EPMC10302901 | biostudies-literature
Project description:BackgroundAlthough response rates for physician surveys have been decreasing, it is not clear whether this trend is associated with an increase in survey nonresponse bias. One means for assessing potential bias is to conduct a level-of-effort analysis that compares data estimates for respondents interviewed during the first recruitment contact to respondents interviewed at later recontact cycles.MethodsWe compared early and later responders within the Survey of Physician Attitudes Regarding the Care of Cancer Survivors with respect to both demographic characteristics and aggregate survey responses to items on survivor care knowledge, attitudes, and practices.ResultsAccumulating additional completions across each of 4 respondent contact attempts improved weighted response rates (35.0%, 46.9%, 52.3%, and 57.6%, respectively). However, the majority of estimates for analyzed variables remained relatively unchanged over additional cycles of recontact.ConclusionsWe conclude that additional respondent recontact attempts, especially beyond a single recontact, had little influence on key data distributions, suggesting that these were ineffective in reducing nonresponse bias. Further, the conduct of additional recruitment recontacts was an inefficient means for increasing statistical power. For the conduct of physician surveys, a practice that may in some cases be cost-effective, while also controlling total survey error, is to establish a larger initial sample; to either eliminate nonresponse follow-up or to limit this to one recontact; and to accept a somewhat lower final overall survey response rate.
| S-EPMC3784997 | biostudies-literature
Project description:We introduce a modeling approach for characterizing heterogeneity in healthcare utilization using massive medical claims data. We first translate the medical claims observed for a large study population and across five years into individual-level discrete events of care called utilization sequences. We model the utilization sequences using an exponential proportional hazards mixture model to capture heterogeneous behaviors in patients' healthcare utilization. The objective is to cluster patients according to their longitudinal utilization behaviors and to determine the main drivers of variation in healthcare utilization while controlling for the demographic, geographic, and health characteristics of the patients. Due to the computational infeasibility of fitting a parametric proportional hazards model for high-dimensional, large sample size data we use an iterative one-step procedure to estimate the model parameters and impute the cluster membership. The approach is used to draw inferences on utilization behaviors of children in the Medicaid system with persistent asthma across six states. We conclude with policy implications for targeted interventions to improve adherence to recommended care practices for pediatric asthma.
| S-EPMC6167939 | biostudies-literature
Project description:BACKGROUND:Genomic testing is increasingly performed in oncology, but concerns remain regarding the clinician's ability to interpret results. In the current study, the authors sought to determine the agreement between physicians and genomic annotators from the Precision Oncology Decision Support (PODS) team at The University of Texas MD Anderson Cancer Center in Houston regarding actionability and the clinical use of test results. METHODS:On a prospective protocol, patients underwent clinical genomic testing for hotspot mutations in 46 or 50 genes. Six months after sequencing, physicians received questionnaires for patients who demonstrated a variant in an actionable gene, investigating their perceptions regarding the actionability of alterations and clinical use of these findings. Genomic annotators independently classified these variants as actionable, potentially actionable, unknown, or not actionable. RESULTS:Physicians completed 250 of 288 questionnaires (87% response rate). Physicians considered 168 of 250 patients (67%) as having an actionable alteration; of these, 165 patients (98%) were considered to have an actionable alteration by the PODS team and 3 were of unknown significance. Physicians were aware of genotype-matched therapy available for 119 patients (71%) and 48 of these 119 patients (40%) received matched therapy. Approximately 46% of patients in whom physicians regarded alterations as not actionable (36 of 79 patients) were classified as having an actionable/potentially actionable mutation by the PODS team. However, many of these were only theoretically actionable due to limited trials and/or therapies (eg, KRAS). CONCLUSIONS:Physicians are aware of recurrent mutations in actionable genes on "hotspot" panels. As larger genomic panels are used, there may be a growing need for annotation of actionability. Decision support to increase awareness of genomically relevant trials and novel treatment options for recurrent mutations (eg, KRAS) also are needed. Cancer 2018;124:966-72. © 2017 American Cancer Society.
| S-EPMC5821595 | biostudies-literature
Project description:BackgroundSome experimental approaches in neuroscience research require the precise placement of a recording electrode, pipette or other tool into a specific brain area that can be quite small and/or located deep beneath the surface. This process is typically aided with stereotaxic methods but remains challenging due to a lack of advanced technology to aid the experimenter. Currently, procedures require a significant amount of skill, have a high failure rate, and take up a significant amount of time.New methodWe developed a next generation robotic stereotaxic platform for small rodents by combining a three-dimensional (3D) skull profiler sub-system and a full six degree-of-freedom (6DOF) robotic platform. The 3D skull profiler is based on structured illumination in which a series of horizontal and vertical line patterns are projected onto an animal skull. These patterns are captured by two two-dimensional (2D) CCD cameras which reconstruct an accurate 3D skull surface profile based on structured illumination and geometrical triangulation. Using the reconstructed 3D profile, the skull can be repositioned using a 6DOF robotic platform to accurately align a surgical tool.ResultsThe system was evaluated using mechanical measurement techniques, and the accuracy of the platform was demonstrated using agar brain phantoms and animal skulls. Additionally, a small and deep brain nucleus (the medial nucleus of the trapezoid body) were targeted in rodents to confirm the targeting accuracy.ConclusionsThe new stereotaxic system can accomplish "skull-flat" rapidly and precisely and with minimal user intervention, and thus reduces the failure rate of such experiments.
| S-EPMC8764742 | biostudies-literature
Project description:Introduction:Behavioral health conditions are a significant concern for the U.S. military and the Military Health System (MHS) because of decreased military readiness and increased health care utilization. Although MHS beneficiaries receive direct care in military treatment facilities, a disproportionate majority of behavioral health treatment is purchased care received in civilian facilities. Yet, limited evidence exists about purchased behavioral health care received by MHS beneficiaries. This longitudinal study (1) estimated the prevalence of purchased behavioral health care and (2) identified patient and visit characteristics predicting receipt of purchased behavioral health care in acute care facilities from 2000 to 2014. Materials and Methods:Medical claims with Major Diagnostic Code 19 (mental disorders/diseases) or 20 (alcohol/drug disorders) as primary diagnoses and TRICARE as the primary/secondary payer were analyzed for MHS beneficiaries (n = 17,943) receiving behavioral health care in civilian acute care facilities from January 1, 2000, to December 31, 2014. The primary dependent variable, receipt of purchased behavioral health care, was modeled for select mental health and substance use disorders from 2000 to 2014 using generalized estimating equations. Patient characteristics included time, age, sex, and race/ethnicity. Visit types included inpatient hospitalization and emergency department (ED). Time was measured in days and visits were assumed to be correlated over time. Behavioral health care was described by both frequency of patients and visit type. The University of South Carolina Institutional Review Board approved this study. Results:From 2000 to 2014, purchased care visits increased significantly for post-traumatic stress disorder, adjustment, anxiety, mood, bipolar, tobacco use, opioid/combination opioid dependence, nondependent cocaine abuse, psychosocial problems, and suicidal ideation among MHS beneficiaries. The majority of care was received for mental health disorders (78.8%) and care was most often received in EDs (56%). Most commonly treated diagnoses included mood, tobacco use, and alcohol use disorders. ED visits were associated with being treated for anxiety (excluding post-traumatic stress disorder; Adjusted odds ratio [AOR]: 9.14 [95% confidence interval (CI): 8.26, 10.12]), alcohol use disorders (AOR = 1.67 [95% CI: 1.53, 1.83]), tobacco use (AOR = 1.16 [95% CI: 1.06, 1.26]), nondependent cocaine abuse (AOR = 5.47 [95% CI: 3.28, 9.12]), nondependent mixed/unspecified drug abuse (AOR = 7.30 [95% CI: 5.11, 10.44]), and psychosis (AOR = 1.38 [95% CI: 1.20, 1.58]). Compared with adults age 60 yr and older, adolescents (ages 12-17 yr), and adults under age 60 yr were more likely to be treated for suicidal ideation, adjustment, mood, bipolar, post-traumatic stress disorder, nondependent cocaine, and mixed/unspecified drug abuse. Adults under age 60 yr also had increased odds of being treated for tobacco use disorders, alcohol use disorders, and opioid/combination opioid dependence compared with adults age 60 yr and older. Conclusions:Over the past 15 yr, purchased behavioral health care received by MHS beneficiaries in acute care facilities increased significantly. MHS beneficiaries received the majority of purchased behavioral health care for mental health disorders and were treated most often in the ED. Receiving behavioral health care in civilian EDs raises questions about access to outpatient behavioral health care and patient-centered care coordination between civilian and military facilities. Given the influx of new Veterans Health Administration users from the MHS, findings have implications for military, veteran, and civilian facilities providing behavioral health care to military and veteran populations.
| S-EPMC6027075 | biostudies-literature