scholarly journals Measuring and Quantifying Collateral Information in Psychiatry: Feasibility study of the McLean Collateral Information and Clinical Actionability scale (M-CICAS) (Preprint)

2020 ◽  
Author(s):  
Praise Owoyemi ◽  
Sarah Salcone ◽  
Christopher King ◽  
Heejung Julie Kim ◽  
Kerry James Ressler ◽  
...  
Keyword(s):  
Decision Making ◽  
Medical Records ◽  
Interrater Reliability ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Collateral Information ◽  
Psychiatric Setting ◽  
Study Staff ◽  
Minimal Research ◽  
Made In

BACKGROUND The review of collateral information is an essential component of patient care. Though this is standard practice, minimal research has been devoted to quantifying collateral information collection and to understanding how collateral information translates to clinical decision-making. To address this, we developed and piloted a novel measure (the McLean collateral information and clinical actionability scale (M-CICAS)) to evaluate the types and number of collateral sources viewed and resulting actions made in a psychiatric setting. OBJECTIVE Study aims included: 1) feasibility testing of the M-CICAS measure, 2) validating this measure against clinician notes via medical records, and 3) evaluating whether reviewing a higher volume of collateral sources is associated with more clinical actions taken. METHODS For the M-CICAS measure, we developed a three-part instrument, focusing on measuring collateral sources reviewed, clinical actions taken, and shared decision-making between clinician and patient. We recruited clinicians providing psychotherapy services at McLean hospital (N = 7) to complete the M-CICAS measure after individual clinical sessions. We also independently completed the M-CICAS using only the clinician’s corresponding note from that session, in order to validate the reported measure against the electronic health record which served as the objective point of comparison. Based on this, we estimated inter-rater reliability, reporting validity and whether significant variance in clinical actions taken could be attributed to inter-clinician differences. RESULTS Study staff had high interrater reliability on the M-CICAS for the sources reviewed (r=0.98, P<.001) and actions taken (r=0.97, P <.001). Clinician and study staff ratings were moderately correlated and statistically significant on the M-CICAS summary scores for the sources viewed (r’s=0.24 and 0.25, P=.02202 and P=.0188, respectively). Univariate regression modelling demonstrated a significant association between collateral sources and clinical actions taken when clinicians completed the M-CICAS (B=.27, t=2.47, P =.015). Multilevel fixed slopes random intercepts model confirmed a significant association even when accounting for clinician differences (B=.23, t=2.13, P =.037). CONCLUSIONS This pilot study establishes feasibility and preliminary validity for the M-CICAS measure in assessing collateral sources and clinical decision-making in psychiatry. This study also indicated that reviewing more collateral sources may lead to an increased number of clinical actions following a session.

The Use of Artificial Intelligence Systems for Support of Medical Decision-Making

2011 ◽  
pp. 1017-1029
Author(s):  
William Claster ◽  
Nader Ghotbi ◽  
Subana Shanmuganathan
Keyword(s):  
Artificial Intelligence ◽  
Decision Making ◽  
Statistical Analysis ◽  
Medical Records ◽  
Clinical Decision Making ◽  
Ct Scanning ◽  
Clinical Decision ◽  
Radiology Department ◽  
Self Organizing Map ◽  
One Year

There is a treasure trove of hidden information in the textual and narrative data of medical records that can be deciphered by text-mining techniques. The information provided by these methods can provide a basis for medical artificial intelligence and help support or improve clinical decision making by medical doctors. In this paper we extend previous work in an effort to extract meaningful information from free text medical records. We discuss a methodology for the analysis of medical records using some statistical analysis and the Kohonen Self-Organizing Map (SOM). The medical data derive from about 700 pediatric patients’ radiology department records where CT (Computed Tomography) scanning was used as part of a diagnostic exploration. The patients underwent CT scanning (single and multiple) throughout a one-year period in 2004 at the Nagasaki University Medical Hospital. Our approach led to a model based on SOM clusters and statistical analysis which may suggest a strategy for limiting CT scan requests. This is important because radiation at levels ordinarily used for CT scanning may pose significant health risks especially to children.

Diagnostic conversations: Clinical Decision Making in surgery – Part 2

Diagnosis ◽  
2014 ◽  
Vol 1 (2) ◽  
pp. 189-193 ◽  
Author(s):  
David Allan Watters ◽  
Spencer Wynyard Beasley ◽  
Wendy Crebbin
Keyword(s):  
Decision Making ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Learning Opportunities ◽  
Clinical Decisions ◽  
Decision Making Processes ◽  
Royal Australasian College ◽  
Insight Into ◽  
Made In

AbstractProceduralists who fail to review their decision making are unlikely to learn from their experiences, irrespective of whether the operative outcome is successful or not. Teaching junior surgeons to develop ‘insight’ into their own decision making has long been a challenge. Surgeons and staff of the Royal Australasian College of Surgeons worked together to develop a model to help explain the processes around clinical decision making and incorporated this model into a Clinical Decision Making (CDM) training course. In this course, faculty apply the model to specific surgical cases, within the model’s framework of how clinical decisions are made; thus providing an opportunity to identify specific decision making processes as they occur and to highlight some of the learning opportunities they provide. The conversation in this paper illustrates the kinds of case-based interactions which typically occur in the development and teaching of the CDM course.The focus in this, the second of two papers, is on reviewing post-operative clinical decisions made in relation to one case, to improve the quality of subsequent decision making.

The assessment of bulging fontanel and splitting of sutures in premature infants: an interrater reliability study by the Hydrocephalus Clinical Research Network

2013 ◽  
Vol 11 (1) ◽  
pp. 12-14 ◽  
Author(s):  
John C. Wellons ◽  
Richard Holubkov ◽  
Samuel R. Browd ◽  
Jay Riva-Cambrin ◽  
William Whitehead ◽  
...  
Keyword(s):  
Decision Making ◽  
Clinical Research ◽  
Premature Infants ◽  
Interrater Reliability ◽  
Clinical Decision Making ◽  
Clinical Signs ◽  
Clinical Decision ◽  
Research Network ◽  
Posthemorrhagic Hydrocephalus ◽  
Clinical Research Network

Object Previous studies from the Hydrocephalus Clinical Research Network (HCRN) have shown a great degree of variation in surgical decision making for infants with posthemorrhagic hydrocephalus, such as when to temporize, when to shunt, or when to convert. Since much of this clinical decision making is dictated by clinical signs of increased intracranial pressure (including bulging fontanel and splitting of sutures), the authors investigated whether there was variability in how these signs were being assessed by neurosurgeons. They wanted to answer the following question: is there acceptable interrater reliability in the neurosurgical assessment of bulging fontanel and split sutures? Methods Explicit written definitions of “bulging fontanel” and “split sutures” were agreed upon with consensus across the HCRN. At 5 HCRN centers, pairs of neurosurgeons independently assessed premature infants in the first 3 months of life for the presence of a split suture and/or bulging fontanel, according to the a priori definitions. Interrater reliability was then calculated between pairs of observers using the Cohen simple kappa coefficient. Institutional board review approval was obtained at each center and at the University of Utah Data Coordinating Center. Results A total of 38 infants were assessed by 13 different raters (10 faculty, 2 fellows, and 1 resident). The kappa for bulging fontanel was 0.65 (95% CI 0.41–0.90), and the kappa for split sutures was 0.84 (95% CI 0.66–1.0). No complications from the study were encountered. Conclusions The authors have found a high degree of interrater reliability among neurosurgeons in their assessment of bulging fontanel and split sutures. While decision making may vary, the clinical assessment of this cohort appears to be consistent among these physicians, which is crucial for prospective studies moving forward.

scholarly journals Assessment of a laboratory critical risk result notification protocol in a tertiary care hospital and their use in clinical decision making

2019 ◽  
Vol 29 (3) ◽  
pp. 513-521
Author(s):  
Jose A. Delgado Rodríguez ◽  
Maria I. Pastor García ◽  
Cristina Gómez Cobo ◽  
Antonia R. Pons Más ◽  
Isabel Llompart Alabern ◽  
...  
Keyword(s):  
Decision Making ◽  
Medical Records ◽  
Clinical Decision Making ◽  
Tertiary Care Hospital ◽  
Tertiary Care ◽  
Clinical Decision ◽  
Care Hospital ◽  
Online Questionnaire ◽  
Risk Result ◽  
The Impact

Introduction: Communication of laboratory critical risk results is essential for patient safety, as it allows early decision making. Our aims were: 1) to retrospectively evaluate the current protocol for telephone notification of critical risk results in terms of rates, efficiency and recipient satisfaction, 2) to assess their use in clinical decision making and 3) to suggest alternative tools for a better assessment of notification protocols. Materials and methods: The biochemical critical risk result notifications reported during 12 months by routine and STAT laboratories in a tertiary care hospital were reviewed. Total number of reports, time for the notification and main magnitudes with critical risk results were calculated. The use of notifications in clinical decision making was assessed by reviewing medical records. Satisfaction with the notification protocol was assessed through an online questionnaire to requesting physicians and nurses. Results: Critical result was yielded by 0.1% of total laboratory tests. Median time for notification was 3.2 min (STAT) and 16.9 min (routine). The magnitudes with a greater number of critical results were glucose and potassium for routine analyses, and troponin, sodium for STAT. Most notifications were not reflected in the medical records. Overall mean satisfaction with the protocol was 4.2/5. Conclusion: The results obtained indicate that the current protocol is appropriate. Nevertheless, there are some limitations that hamper the evaluation of the impact on clinical decision making. Alternatives were proposed for a proper and precise evaluation.

Klinischer Nutzen der Flüssigkeitsbiopsie beim uvealen Melanom

2021 ◽  
pp. 1-3
Author(s):  
Ira Seibel
Keyword(s):  
Decision Making ◽  
Liquid Biopsy ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
High Rate ◽  
Precision Oncology ◽  
Noninvasive Biomarker ◽  
Biopsy Methods ◽  
Disease Understanding ◽  
Made In

In the era of precision oncology, major strides are being made to use individual tumor information for clinical decision-making. Differing from traditional biopsy methods, the emerging practice of liquid biopsy provides a minimally invasive way of obtaining tumor cells and derived molecules. Liquid biopsy provides a means to detect and monitor disease progression, recurrence, and treatment response in a noninvasive way, and to potentially complement classical biopsy. Uveal melanoma (UM) is a unique malignancy, with diagnosis heavily reliant on imaging, few repeat biopsies, and a high rate of metastasis, which occurs hematogenously and often many years after diagnosis. In this disease setting, a noninvasive biomarker to detect, monitor, and study the disease in real time could lead to better disease understanding and patient care. While advances have been made in the detection of tumor-disseminated components, sensitivity and specificity remain important challenges. Ambiguity remains in how to interpret current findings and in how liquid biopsy can have a place in clinical practice. Related publications in UM are few compared to other cancers, but with further studies we may be able to uncover more about the biology of disseminated molecules and the mechanisms involved in the progression to metastasis.

scholarly journals Health Care Expert’s Readiness to Implement National Unified Medical Records (Numr) System in the United Arab Emirates; A Qualitative Study

2020 ◽  
Author(s):  
Alya Harbi
Keyword(s):  
Decision Making ◽  
Medical Record ◽  
United Arab Emirates ◽  
Medical Records ◽  
Health Informatics ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Daily Basis ◽  
Structured Interviews ◽  
Healthcare Organizations

Abstract Background Electronic health records provide a valuable resource to improve health evaluation, surveillance and informs effective clinical decision making. Although electronic medical records (EMR) are introduced in many different settings, yet little is known about the readiness, effectiveness and progress of a centralized information system like NUMR across United Arab Emirates. This study aims to determine the readiness for national unified medical record (NUMR), barriers and challenges from the point of views of experts working in the field of health informatics on daily basis. Methods Semi-structured interviews were conducted with 10 experts using purposive sampling method from different healthcare organizations in the United Arab Emirates. Perceptions of interviewees regarding the readiness for national unified medical record were elicited. Thematic analysis was used to identify the different themes extracted from the interview transcripts. Results Overall, seven themes emerged after analyzing the transcripts obtained from the respondents. This study is expected to bring countless benefits for all countries that are moving forward toward nationwide and interoperable healthcare platforms. The support for NUMR will make a significant contribution to the health systems across UAE that will ultimately lead to safety, access to single shared records, improved care and coordination, better clinical and decision making, faster engagement, easy and secure access, safety and will save time for other tasks. Conclusion The future of implementation of NUMR in UAE is promising. Our findings offer beneficial guidelines for consideration in implementing NUMR system across UAE and also helps in the drive to improve healthcare systems nationally.

scholarly journals Improved preventive care clinical decision-making efficiency: leveraging a point-of-care clinical decision support system

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Scott Laing ◽  
Jay Mercer
Keyword(s):  
Decision Making ◽  
Electronic Medical Records ◽  
Preventive Care ◽  
Medical Records ◽  
Clinical Decision Making ◽  
Point Of Care ◽  
Clinical Decision ◽  
Ease Of Use ◽  
Perceived Usefulness ◽  
Digital Tools

Abstract Background Electronic medical records are widely used in family practices across Canada and can improve health outcomes. However, recent reports indicate that physicians using electronic medical records work longer and have less direct patient contact which may contribute to burnout. Therefore, new and innovative digital tools are essential to reduce physician workloads and improve patient-physician interaction to address physician burnout. The objective of this study was to assess the efficiency and accuracy of clinical decision-making when using a new preventive care point-of-care clinical decision support system (CDSS). An estimate of the potential annual time savings was also determined. This study also assessed physician reported perceived usefulness and ease of use of the CDSS. Methods Quantitative and qualitative data were collected during this study. Each participant evaluated two simulated patient charts and identified which preventive care metrics were due. The participants recorded their decisions and the time required to assess each chart. Participants then completed a Technology Acceptance Model survey regarding the perceived usefulness and ease of use of the CDSS, which included qualitative feedback. The amount of time saved was determined and participants’ clinical decision-making accuracy was scored against current Canadian preventive care guidelines. The number of preventive care specific visits completed per year was determined using clinic billing data. Results The preventive care CDSS saved an average of 195.7 s of chart review time (249.5 s vs 445.2 s; P < 0.001). A total of 1520 preventive visits were performed at Primrose and Bruyère Family Medicine Centres. Extrapolated across the organization, implementation of the new tool could save 82.6 h per year. Decision-making accuracy was not affected by the new tool (78.4% vs 80.9%, P > 0.05). Participants rated the perceived ease of use and usefulness to be very high. Conclusions New digital tools may reduce providers’ workload without impacting clinical decision-making accuracy. Participants indicated that the preventive care CDSS was useful and easy to use. Further software development and clinical studies are required to further improve and characterize the effect this new CDSS has when implemented in clinical practice.

scholarly journals The Influence of Personalised Sarcoma Care (PERSARC) Prediction Modelling on Clinical Decision Making in a Multidisciplinary Setting

Sarcoma ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-6
Author(s):  
H. S. Femke Hagenmaier ◽  
Annelies G. K. van Beeck ◽  
Rick L. Haas ◽  
Veroniek M. van Praag ◽  
Leti van Bodegom-Vos ◽  
...  
Keyword(s):  
Decision Making ◽  
Clinical Decision Making ◽  
Treatment Decision ◽  
Clinical Decision ◽  
Patient Centered ◽  
Treatment Protocols ◽  
Treatment Decision Making ◽  
Heterogenous Group ◽  
Centered Care ◽  
Made In

Background. With soft-tissue sarcoma of the extremity (ESTS) representing a heterogenous group of tumors, management decisions are often made in multidisciplinary team (MDT) meetings. To optimize outcome, nomograms are more commonly used to guide individualized treatment decision making. Purpose. To evaluate the influence of Personalised Sarcoma Care (PERSARC) on treatment decisions for patients with high-grade ESTS and the ability of the MDT to accurately predict overall survival (OS) and local recurrence (LR) rates. Methods. Two consecutive meetings were organised. During the first meeting, 36 cases were presented to the MDT. OS and LR rates without the use of PERSARC were estimated by consensus and preferred treatment was recorded for each case. During the second meeting, OS/LR rates calculated with PERSARC were presented to the MDT. Differences between estimated OS/LR rates and PERSARC OS/LR rates were calculated. Variations in preferred treatment protocols were noted. Results. The MDT underestimated OS when compared to PERSARC in 48.4% of cases. LR rates were overestimated in 41.9% of cases. With the use of PERSARC, the proposed treatment changed for 24 cases. Conclusion. PERSARC aids the MDT to optimize individualized predicted OS and LR rates, hereby guiding patient-centered care and shared decision making.

Choosing Wisely in the Era of Artificial Intelligence (Preprint)

2019 ◽  
Author(s):  
Nishila Mehta ◽  
Karen Born ◽  
Tai Huynh ◽  
Benjamin Fine
Keyword(s):  
Artificial Intelligence ◽  
Decision Making ◽  
Medical Records ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Choosing Wisely ◽  
Computing Power ◽  
Patient Resources ◽  
Patients Experience ◽  
Care Decision

UNSTRUCTURED Choosing Wisely campaigns have spread to more than 20 countries worldwide. Choosing Wisely is a clinician-led effort to produce clinician recommendations and patient resources around overused tests, procedures and medications. The digitization of medical records and workflows and growth in computing power has enabled artificial intelligence (AI) to be applied to augment health care decision-making. Overuse is an important problem for AI-enabled technologies to address. This commentary offers a roadmap of opportunities for AI-augmented efforts to reduce overuse which are presented according to a patient’s journey of care, beginning from when patients experience symptoms through clinical decision making and subsequent evaluation efforts. This roadmap can be used to guide the cross-discipline development and implementation of AI-enabled tools to reduce overuse and drive value.

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