Dashboard to Support the Decision-Making within a Chronic Disease

2012 ◽  
pp. 160-171 ◽  
Author(s):  
Leonor Teixeira ◽  
Vasco Saavedra ◽  
João Pedro Simões
Keyword(s):  
Decision Making ◽  
Chronic Disease ◽  
Real Time ◽  
Clinical Decision Making ◽  
Healthcare Providers ◽  
Clinical Decision ◽  
Heterogeneous Data ◽  
Information And Communications Technologies ◽  
The Right ◽  
Real Time Information

This chapter describes a monitoring system based on alerts and Key Performance Indicators (KPIs), applied in clinical context, within a chronic disease (haemophilia). This kind of disease follows the patient through his/her life, and its treatment requires an almost permanent exchange of data/information with healthcare professional (HCPs), with the information and communications technologies (ICTs) a key contribution in this process. However, most applications based on those ICTs do not allow the analysis of heterogeneous data in real-time, requiring the availability of clinicians to check the data and analyze the information to support the clinical decision process. Since time is a scarce resource in the context of healthcare providers, and information a crucial resource in the decision support process, real-time monitoring systems can help finding the right balance between those two resources, presenting the key information in an appropriate format, through alerts and KPIs. The system described in this chapter, named hemo@care_dashboard, aims to support clinical decision-making of healthcare professionals of a specific chronic disease, providing real-time information in a push-logic through alerts and KPIs, displayed on a dashboard.

scholarly journals Factors Influencing Physicians' Clinical Decision-making at Upazila Health Complexes in Bangladesh

2020 ◽  
Vol 3 (4) ◽  
pp. 125-133
Author(s):  
M. Aminul Islam ◽  
M. Abdul Awal
Keyword(s):  
Decision Making ◽  
Social Networks ◽  
Clinical Decision Making ◽  
Average Length ◽  
Clinical Decision ◽  
Primary Data ◽  
Decision Making Process ◽  
Cross Sectional ◽  
The Right ◽  
Consultation Session

ABSTRACT Introduction Selecting the most appropriate treatment for each patient is the key activity in patient-physician encounters and providing healthcare services. Achieving desirable clinical goals mostly depends on making the right decision at the right time in any healthcare setting. But little is known about physicians' clinical decision-making in the primary care setting in Bangladesh. Therefore, this study explored the factors that influence decisions about prescribing medications, ordering pathologic tests, counseling patients, average length of patient visits in a consultation session, and referral of patients to other physicians or hospitals by physicians at Upazila Health Complexes (UHCs) in the country. It also explored the structure of physicians' social networks and their association with the decision-making process. Methods This was a cross-sectional descriptive study that used primary data collected from 85 physicians. The respondents, who work at UHCs in the Rajshahi Division, were selected purposively. The collected data were analyzed with descriptive statistics including frequency, percentage, one-way analysis of variance, and linear regression to understand relationships among the variables. Results The results of the study reveal that multiple factors influence physicians' decisions about prescribing medications, ordering pathologic tests, length of visits, counseling patients, and referring patients to other physicians or hospitals at the UHCs. Most physicians prescribe drugs to their patients, keeping in mind their purchasing capacity. Risk of violence by patients' relatives and better management are the two key factors that influence physicians' referral decisions. The physicians' professional and personal social networks also play an influential role in the decision-making process. It was found that physicians dedicate on average 16.17 minutes to a patient in a consultation session. The length of visits is influenced by various factors including the distance between the physicians' residence and their workplace, their level of education, and the number of colleagues with whom they have regular contact and from whom they can seek help. Conclusion The results of the study have yielded some novel insights about the complexity of physicians' everyday tasks at the UHCs in Bangladesh. The results would be of interest to public health researchers and policy makers.

scholarly journals Complexity of Clinical Decision Making: Consent, Capacity, and Ethics

2019 ◽  
Vol 40 (03) ◽  
pp. 162-169 ◽  
Author(s):  
Annette Askren ◽  
Paula Leslie
Keyword(s):  
Decision Making ◽  
Clinical Decision Making ◽  
Negative Charge ◽  
Clinical Decision ◽  
Informed Consent Process ◽  
Thickened Liquids ◽  
Medical Decisions ◽  
Social Media Platforms ◽  
The Right ◽  
Right To Refuse

AbstractSpeech–language pathologists (SLPs), and really their patients, are often faced with challenging clinical decisions to be made. Patients may decline interventions recommended by the SLP and are often inappropriately labeled “noncompliant.” The inappropriateness of this label extends beyond the negative charge; the patient's right to refuse is, in fact, protected by law. Anecdotal exchanges, social media platforms, and American Speech-Language-Hearing Association forums have recently revealed that many SLPs are struggling with the patient's right to decline. Many are not comfortable with the informed consent process and what entails patients' capacity to make their own medical decisions. Here, we discuss the basics of clinical decision-making ethics with intent to minimize the clinician's discomfort with the right to refuse those thickened liquids and eliminate the practice of defensive medicine.

scholarly journals Value-impregnated factual claims may undermine medical decision-making

2018 ◽  
Vol 13 (3) ◽  
pp. 151-158 ◽  
Author(s):  
Niels Lynøe ◽  
Gert Helgesson ◽  
Niklas Juth
Keyword(s):  
Decision Making ◽  
Medical Decision Making ◽  
Clinical Decision Making ◽  
Negative Impact ◽  
Personal Values ◽  
Healthcare Providers ◽  
Clinical Decision ◽  
Medical Decision ◽  
Clinical Decisions ◽  
Soft Laws

Clinical decisions are expected to be based on factual evidence and official values derived from healthcare law and soft laws such as regulations and guidelines. But sometimes personal values instead influence clinical decisions. One way in which personal values may influence medical decision-making is by their affecting factual claims or assumptions made by healthcare providers. Such influence, which we call ‘value-impregnation,’ may be concealed to all concerned stakeholders. We suggest as a hypothesis that healthcare providers’ decision making is sometimes affected by value-impregnated factual claims or assumptions. If such claims influence e.g. doctor–patient encounters, this will likely have a negative impact on the provision of correct information to patients and on patients’ influence on decision making regarding their own care. In this paper, we explore the idea that value-impregnated factual claims influence healthcare decisions through a series of medical examples. We suggest that more research is needed to further examine whether healthcare staff’s personal values influence clinical decision-making.

scholarly journals Utility and Acceptability of Influenza Surveillance amongst Emergency Providers

2015 ◽  
Vol 7 (1) ◽  
Author(s):  
Andrea F. Dugas ◽  
Howard Burkom ◽  
Anna L. DuVal ◽  
Richard Rothman
Keyword(s):  
Decision Making ◽  
Emergency Department ◽  
Real Time ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Surveillance Data ◽  
Influenza Surveillance ◽  
Additional Information ◽  
Provider Surveys

We provided emergency department providers with a real-time laboratory-based influenza surveillance tool, and evaluated the utility and acceptability of the surveillance information using provider surveys. The majority of emergency department providers found the surveillance data useful and indicated the additional information impacted their clinical decision making regarding influenza testing and treatment.

scholarly journals Comparison of Cortisol, Androstenedione and Metanephrines to Assess Selectivity and Lateralization of Adrenal Vein Sampling in Primary Aldosteronism

2021 ◽  
Vol 10 (20) ◽  
pp. 4755
Author(s):  
Giulio Ceolotto ◽  
Giorgia Antonelli ◽  
Brasilina Caroccia ◽  
Michele Battistel ◽  
Giulio Barbiero ◽  
...  
Keyword(s):  
Decision Making ◽  
Primary Aldosteronism ◽  
Inferior Vena ◽  
Clinical Decision Making ◽  
Vena Cava ◽  
Clinical Decision ◽  
Selectivity Index ◽  
Adrenal Vein ◽  
Adrenal Vein Sampling ◽  
The Right

Success of adrenal vein sampling (AVS) is verified by the selectivity index (SI), i.e., by a step-up of cortisol levels between the adrenal vein and the infrarenal inferior vena cava samples, beyond a given cut-off. We tested the hypothesis that androstenedione, metanephrine, and normetanephrine, which have higher gradients than cortisol, could increase the rate of AVS studies judged to be bilaterally successful and usable for the clinical decision making. We prospectively compared within-patient, head-to-head, the selectivity index of androstenedione (SIA), metanephrine (SIM), and normetanephrine (SINM), and cortisol (SIC) in consecutive hypertensive patients with primary aldosteronism submitted to AVS. Main outcome measures were rate of bilateral success, SI values, and identification of unilateral PA. We recruited 136 patients (55 + 10 years, 35% women). Compared to the SIC, the SIA values were 3.5-fold higher bilaterally, and the SIM values were 7-fold and 4.4-fold higher on the right and the left side, respectively. With the SIA and the SIM the rate of bilaterally successful AVS increased by 14% and 15%, respectively without impairing the identification of unilateral PA. We concluded that androstenedione and metanephrine outperformed cortisol for ascertaining AVS success, thus increasing the AVS studies useable for the clinical decision making.

scholarly journals “I can guess the month … but beyond that, I can’t tell” an exploratory qualitative study of health care provider perspectives on gestational age estimation in Rajasthan, India

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
K. Scott ◽  
S. Gupta ◽  
E. Williams ◽  
M. Arthur ◽  
U. V. Somayajulu ◽  
...  
Keyword(s):  
Health Care ◽  
Decision Making ◽  
Gestational Age ◽  
Age Estimation ◽  
Clinical Decision Making ◽  
Healthcare Providers ◽  
Clinical Decision ◽  
Provider Perspectives ◽  
Gestational Age Estimation ◽  
Age Estimates

Abstract Background Accurately estimating gestational age is essential to the provision of time-sensitive maternal and neonatal interventions, including lifesaving measures for imminent preterm birth and trimester-specific health messaging. Methods We explored healthcare provider perspectives on gestational age estimation in the state of Rajasthan, India, including the methods they use (last menstrual period [LMP] dating, ultrasound, or fundal height measurement); barriers to making accurate estimates; how gestational age estimates are documented and used for clinical decision-making; and what could help improve the accuracy and use of these estimates. We interviewed 20 frontline healthcare providers and 10 key informants. Thematic network analysis guided our coding and synthesis of findings. Results Health care providers reported that they determined gestational age using some combination of LMP, fundal height, and ultrasound. Their description of their practices showed a lack of standard protocol, varying levels of confidence in their capacity to make accurate estimates, and differing strategies for managing inconsistencies between estimates derived from different methods. Many frontline healthcare providers valued gestational age estimation more to help women prepare for childbirth than as a tool for clinical decision making. Feedback on accuracy was rare. The providers sampled could not offer ultrasound directly, and instead could only refer women to ultrasound at higher level facilities, and usually only in the second or third trimesters because of late antenatal care-seeking. Low recall among pregnant women limited the accuracy of LMP. Fundal height was heavily relied upon, despite its lack of precision. Conclusion The accuracy of gestational age estimates is influenced by factors at four levels: 1. health system (protocols to guide frontline workers, interventions that make use of gestational age, work environment, and equipment); 2. healthcare provider (technical understanding of and capacity to apply the gestational age estimation methods, communication and rapport with clients, and value assessment of gestational age); 3. client (time of first antenatal care, migration status, language, education, cognitive approach to recalling dates, and experience with biomedical services); and, 4. the inherent limitations and ease of application of the methods themselves.

Cancer patient management: role of multidisciplinary teams

2021 ◽  
pp. bmjspcare-2021-003039
Author(s):  
Tuan Trong Luu
Keyword(s):  
Decision Making ◽  
Human Resources ◽  
Clinical Decision Making ◽  
Health Care Systems ◽  
Healthcare Providers ◽  
Clinical Decision ◽  
Care Quality ◽  
Multidisciplinary Teams ◽  
Patient Centeredness ◽  
Care Systems

ObjectivesAs a cancer model recommended by numerous governments and health care systems, multidisciplinary teams (MDTs) can improve clinical decision-making and overall patient care quality. This paper aims to discuss key elements and resources, as well as contingencies for effectiveness MDTs and their meetings.MethodsWe derived elements, resources, and contingencies for effective MDTs by analyzing articles on the themes of MDTs and MDT meetings.ResultsThis paper identifies key elements comprising MDT characteristics, team governance, infrastructure for MDM, MDM organization, MDM logistics, and clinical decision-making in light of patient-centeredness. Resources that facilitate an MDM functioning consist of human resources and non-human resources. The paper further detects barriers to the sustainable performance of MDTs and provide suggestions for improving their functioning in light of patients’ and healthcare providers’ perspectives.ConclusionsMDTs are vital to cancer care through enabling healthcare professionals with diversity of clinical specialties to collaborate and formulate optimal treatment recommendations for patients with suspected or confirmed cancer.

scholarly journals Machine Learning for Clinical Decision-Making: Challenges and Opportunities

2019 ◽  
Author(s):  
Sergio Sanchez-Martinez ◽  
Oscar Camara ◽  
Gemma Piella ◽  
Maja Cikes ◽  
Miguel Angel Gonzalez Ballester ◽  
...  
Keyword(s):  
Machine Learning ◽  
Decision Making ◽  
Clinical Decision Making ◽  
Clinical Status ◽  
Clinical Decision ◽  
Heterogeneous Data ◽  
Response To Treatment ◽  
Classical Pathway ◽  
Challenges And Opportunities ◽  
Four Levels

The use of machine learning (ML) approaches to target clinical problems is called to revolutionize clinical decision-making. The success of these tools is subjected to the understanding of the intrinsic processes being used during the classical pathway by which clinicians make decisions. In a parallelism with this pathway, ML can have an impact at four levels: for data acquisition, predominantly by extracting standardized, high-quality information with the smallest possible learning curve; for feature extraction, by discharging healthcare practitioners from performing tedious measurements on raw data; for interpretation, by digesting complex, heterogeneous data in order to augment the understanding of the patient status; and for decision support, by leveraging the previous step to predict clinical outcomes, response to treatment or to recommend a specific intervention. This paper discusses the state-of-the-art, as well as the current clinical status and challenges associated with each of these tasks, together with the challenges related to the learning process, the auditability/traceability, the system infrastructure and the integration within clinical processes.

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