Health Information Resources and Clinical Core Skills as Predictors of Medical Doctors Clinical Decision Making in Obafemi Awolowo University Teaching Hospital, Ile-Ife, Nigeria

Author(s):  
Alarape A. A. ◽  
Adegboye M. O. ◽  
Ogunniran O. O ◽  
Omoba F. A
Author(s):  
Moyosore O. Adegboye ◽  
Samuel Adeyoyin

The study evaluates health information resources as predictors for clinical decision- making among medical doctors in Obafemi Awolowo University Teaching Hospital Ile-Ife. A survey research design was adopted by the study and random sampling technique was used to select 265 medical doctors from a population of 822. Primary data were obtained on socioeconomic characteristics of the respondents, level of accessibility, frequency and various core skills of health information resources using a structured questionnaire and focus group discussion (FGD). Data were analyzed using frequency counts, percentage and mean. Results revealed that 59.8% of the respondents were male while 51.1% were female. Findings, however, showed that pattern recognition from experience ( &#x0304 = 3.32), critical thinking without emotion (&#x0304 = 3.16), hypothesis updating (&#x0304 = 3.607) and perception based confidence (&#x0304 = 2.97) were the core skills used by the medical doctors in clinical decision making. The focus group discussion emphasized that medical doctors should possess critical thinking without emotions and good time pressure balance in order to make accurate clinical decisions. The study concludes that medical doctors have quality access to health information resources to make clinical decisions. The study, therefore recommended regular trainings of medical personnel on health information resources to ensure accurate and sound decision making in order to enhance optimal performance. Keywords Information sharing, Job satisfaction, Librarians, Private Universities


Author(s):  
Maria Ehioghae ◽  
Ezinwanyi Madukoma

The study interrogates health information use by resident doctors in Lagos State University Teaching hospital (LASUTH), Lagos State. Health information has been variously described as the “foundation” for better health, as the “glue” holding the health systems together and as the “oil” keeping the health systems running. It is important for making the right clinical decisions and enhancing professionalism. A survey research design was adopted by the study and the enumeration technique was used to cover all 115 resident doctors that constituted the population. Out of the 115 questionnaire copies administered, 94 copies were returned for data analysis, making the response rate to be 81.7%. The data collected were analyzed using frequency counts and percentages. Findings revealed that the majority of resident doctors in LASUTH have access and use, to a large extent, health information for clinical decision-making. It is, however, recommended that to improve on health information sharing, workshops and seminars on health information should be regularly conducted for resident doctors in LASUTH. This, expectedly, will expose them to new health information trends that will enhance their clinical experience. Keywords: Health Information, Information Use, Resident Doctors, Clinical Decision-making


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Steven A. Hicks ◽  
Jonas L. Isaksen ◽  
Vajira Thambawita ◽  
Jonas Ghouse ◽  
Gustav Ahlberg ◽  
...  

AbstractDeep learning-based tools may annotate and interpret medical data more quickly, consistently, and accurately than medical doctors. However, as medical doctors are ultimately responsible for clinical decision-making, any deep learning-based prediction should be accompanied by an explanation that a human can understand. We present an approach called electrocardiogram gradient class activation map (ECGradCAM), which is used to generate attention maps and explain the reasoning behind deep learning-based decision-making in ECG analysis. Attention maps may be used in the clinic to aid diagnosis, discover new medical knowledge, and identify novel features and characteristics of medical tests. In this paper, we showcase how ECGradCAM attention maps can unmask how a novel deep learning model measures both amplitudes and intervals in 12-lead electrocardiograms, and we show an example of how attention maps may be used to develop novel ECG features.


2020 ◽  
Author(s):  
Philip Scott ◽  
Elisavet Andrikopoulou ◽  
Haythem Nakkas ◽  
Paul Roderick

Background: The overall evidence for the impact of electronic information systems on cost, quality and safety of healthcare remains contested. Whilst it seems intuitively obvious that having more data about a patient will improve care, the mechanisms by which information availability is translated into better decision-making are not well understood. Furthermore, there is the risk of data overload creating a negative outcome. There are situations where a key information summary can be more useful than a rich record. The Care and Health Information Exchange (CHIE) is a shared electronic health record for Hampshire and the Isle of Wight that combines key information from hospital, general practice, community care and social services. Its purpose is to provide clinical and care professionals with complete, accurate and up-to-date information when caring for patients. CHIE is used by GP out-of-hours services, acute hospital doctors, ambulance service, GPs and others in caring for patients. Research questions: The fundamental question was How does awareness of CHIE or usage of CHIE affect clinical decision-making? The secondary questions were What are the latent benefits of CHIE in frontline NHS operations? and What is the potential of CHIE to have an impact on major NHS cost pressures? The NHS funders decided to focus on acute medical inpatient admissions as the initial scope, given the high costs associated with hospital stays and the patient complexities (and therefore information requirements) often associated with unscheduled admissions. Methods: Semi-structured interviews with healthcare professionals to explore their experience about the utility of CHIE in their clinical scenario, whether and how it has affected their decision-making practices and the barriers and facilitators for their use of CHIE. The Framework Method was used for qualitative analysis, supported by the software tool Atlas.ti. Results: 21 healthcare professionals were interviewed. Three main functions were identified as useful: extensive medication prescribing history, information sharing between primary, secondary and social care and access to laboratory test results. We inferred two positive cognitive mechanisms: knowledge confidence and collaboration assurance, and three negative ones: consent anxiety, search anxiety and data mistrust. Conclusions: CHIE gives clinicians the bigger picture to understand the patient's health and social care history and circumstances so as to make confident and informed decisions. CHIE is very beneficial for medicines reconciliation on admission, especially for patients that are unable to speak or act for themselves or who cannot remember their precise medication or allergies. We found no clear evidence that CHIE has a significant impact on admission or discharge decisions. We propose the use of recommender systems to help clinicians navigate such large volumes of patient data, which will only grow as additional data is collected.


BMJ Open ◽  
2021 ◽  
Vol 11 (5) ◽  
pp. e044510
Author(s):  
Edmond Li ◽  
Juan Emmanuel Dewez ◽  
Queena Luu ◽  
Marieke Emonts ◽  
Ian Maconochie ◽  
...  

ObjectivesThe use of rapid point-of-care tests (POCTs) has been advocated for improving patient management and outcomes and for optimising antibiotic prescribing. However, few studies have explored healthcare workers’ views about their use in febrile children. The aim of this study was to explore the perceptions of hospital-based doctors and nurses regarding the use of POCTs in England.Study designQualitative in-depth interviews with purposively selected hospital doctors and nurses. Data were analysed thematically.SettingTwo university teaching hospitals in London and Newcastle.Participants24 participants (paediatricians, emergency department doctors, trainee paediatricians and nurses).ResultsThere were diverse views about the use of POCTs in febrile children. The reported advantages included their ease of use and the rapid availability of results. They were seen to contribute to faster clinical decision-making; the targeting of antibiotic use; improvements in patient care, flow and monitoring; cohorting (ie, the physical clustering of hospitalised patients with the same infection to limit spread) and enhancing communication with parents. These advantages were less evident when the turnaround for results of laboratory tests was 1–2 hours. Factors such as clinical experience and specialty, as well as the availability of guidelines recommending POCT use, were also perceived as influential. However, in addition to their perceived inaccuracy, participants were concerned about POCTs not resolving diagnostic uncertainty or altering clinical management, leading to a commonly expressed preference for relying on clinical skills rather than test results solely.ConclusionIn this study conducted at two university teaching hospitals in England, participants expressed mixed opinions about the utility of current POCTs in the management of febrile children. Understanding the current clinical decision-making process and the specific needs and preferences of clinicians in different settings will be critical in ensuring the optimal design and deployment of current and future tests.


2021 ◽  
Author(s):  
Steven Hicks ◽  
Jonas Isaksen ◽  
Vajira Thambawita ◽  
Jonas Ghouse ◽  
Gustav Ahlberg ◽  
...  

Deep learning-based tools may annotate and interpret medical tests more quickly, consistently, and accurately than medical doctors. However, as medical doctors remain ultimately responsible for clinical decision-making, any deep learning-based prediction must necessarily be accompanied by an explanation that can be interpreted by a human. In this study, we present an approach, called ECGradCAM, which uses attention maps to explain the reasoning behind AI decision-making and how interpreting these explanations can be used to discover new medical knowledge. Attention maps are visualizations of how a deep learning network makes, which may be used in the clinic to aid diagnosis, and in research to identify novel features and characteristics of diagnostic medical tests. Here, we showcase the use of ECGradCAM attention maps using a novel deep learning model capable of measuring both amplitudes and intervals in 12-lead electrocardiograms.


Author(s):  
Christoph U. Lehmann ◽  
Karl E. Misulis ◽  
Mark E. Frisse

Decision support is a broad technique that seeks to bring information to bear at the time a clinician is taking actions that are driven by other data. Clinical decision-making methodology depends on the complexity of the patient’s case, the certainty of a diagnosis, available treatment and diagnostic resources, reliability of information resources, training of the clinician, and psychological makeup of the clinician. Most clinical decision support efforts seek to improve workflow, enforce best clinical practices, or mitigate adverse drug events. Clinical decision support can reduce medical errors, improve nutrition, prevent orders on the wrong patient, and reduce costs. Clinical and administrative decision support can lead to more effective outcomes, improved quality, and lower costs.


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