scholarly journals Mobile Clinical Decision Support System for the Management of Diabetic Patients With Kidney Complications in UK Primary Care Settings: Mixed Methods Feasibility Study (Preprint)

2020 ◽  
Author(s):  
Hala Ibrahim Alhodaib ◽  
Christina Antza ◽  
Joht Singh Chandan ◽  
Wasim Hanif ◽  
Sailesh Sankaranarayanan ◽  
...  
Keyword(s):  
Health Care ◽  
Clinical Practice ◽  
Decision Support ◽  
Health Care Providers ◽  
Clinical Decision Support System ◽  
Intervention Group ◽  
Clinical Decision ◽  
Control Group ◽  
Care Providers ◽  
Specialist Nurses

BACKGROUND Attempts to utilize eHealth in diabetes mellitus (DM) management have shown promising outcomes, mostly targeted at patients; however, few solutions have been designed for health care providers. OBJECTIVE The purpose of this study was to conduct a feasibility project developing and evaluating a mobile clinical decision support system (CDSS) tool exclusively for health care providers to manage chronic kidney disease (CKD) in patients with DM. METHODS The design process was based on the 3 key stages of the user-centered design framework. First, an exploratory qualitative study collected the experiences and views of DM specialist nurses regarding the use of mobile apps in clinical practice. Second, a CDSS tool was developed for the management of patients with DM and CKD. Finally, a randomized controlled trial examined the acceptability and impact of the tool. RESULTS We interviewed 15 DM specialist nurses. DM specialist nurses were not currently using eHealth solutions in their clinical practice, while most nurses were not even aware of existing medical apps. However, they appreciated the potential benefits that apps may bring to their clinical practice. Taking into consideration the needs and preferences of end users, a new mobile CDSS app, “Diabetes &amp; CKD,” was developed based on guidelines. We recruited 39 junior foundation year 1 doctors (44% male) to evaluate the app. Of them, 44% (17/39) were allocated to the intervention group, and 56% (22/39) were allocated to the control group. There was no significant difference in scores (maximum score=13) assessing the management decisions between the app and paper-based version of the app’s algorithm (intervention group: mean 7.24 points, SD 2.46 points; control group: mean 7.39, SD 2.56; t<sub>37</sub>=–0.19, <i>P</i>=.85). However, 82% (14/17) of the participants were satisfied with using the app. CONCLUSIONS The findings will guide the design of future CDSS apps for the management of DM, aiming to help health care providers with a personalized approach depending on patients’ comorbidities, specifically CKD, in accordance with guidelines.

scholarly journals Mobile Clinical Decision Support System for the Management of Diabetic Patients With Kidney Complications in UK Primary Care Settings: Mixed Methods Feasibility Study

JMIR Diabetes ◽  
10.2196/19650 ◽  
2020 ◽  
Vol 5 (4) ◽  
pp. e19650
Author(s):  
Hala Ibrahim Alhodaib ◽  
Christina Antza ◽  
Joht Singh Chandan ◽  
Wasim Hanif ◽  
Sailesh Sankaranarayanan ◽  
...  
Keyword(s):  
Health Care ◽  
Clinical Practice ◽  
Decision Support ◽  
Health Care Providers ◽  
Clinical Decision Support System ◽  
Intervention Group ◽  
Clinical Decision ◽  
Control Group ◽  
Care Providers ◽  
Specialist Nurses

Background Attempts to utilize eHealth in diabetes mellitus (DM) management have shown promising outcomes, mostly targeted at patients; however, few solutions have been designed for health care providers. Objective The purpose of this study was to conduct a feasibility project developing and evaluating a mobile clinical decision support system (CDSS) tool exclusively for health care providers to manage chronic kidney disease (CKD) in patients with DM. Methods The design process was based on the 3 key stages of the user-centered design framework. First, an exploratory qualitative study collected the experiences and views of DM specialist nurses regarding the use of mobile apps in clinical practice. Second, a CDSS tool was developed for the management of patients with DM and CKD. Finally, a randomized controlled trial examined the acceptability and impact of the tool. Results We interviewed 15 DM specialist nurses. DM specialist nurses were not currently using eHealth solutions in their clinical practice, while most nurses were not even aware of existing medical apps. However, they appreciated the potential benefits that apps may bring to their clinical practice. Taking into consideration the needs and preferences of end users, a new mobile CDSS app, “Diabetes & CKD,” was developed based on guidelines. We recruited 39 junior foundation year 1 doctors (44% male) to evaluate the app. Of them, 44% (17/39) were allocated to the intervention group, and 56% (22/39) were allocated to the control group. There was no significant difference in scores (maximum score=13) assessing the management decisions between the app and paper-based version of the app’s algorithm (intervention group: mean 7.24 points, SD 2.46 points; control group: mean 7.39, SD 2.56; t37=–0.19, P=.85). However, 82% (14/17) of the participants were satisfied with using the app. Conclusions The findings will guide the design of future CDSS apps for the management of DM, aiming to help health care providers with a personalized approach depending on patients’ comorbidities, specifically CKD, in accordance with guidelines.

Consent, Refusal, and Waivers in Patient-Centered Dysphagia Care: Using Law, Ethics, and Evidence to Guide Clinical Practice

2016 ◽  
Vol 25 (4) ◽  
pp. 453-469 ◽  
Author(s):  
Jennifer Horner ◽  
Maria Modayil ◽  
Laura Roche Chapman ◽  
An Dinh
Keyword(s):  
Health Care ◽  
Public Policy ◽  
Clinical Practice ◽  
Health Care Providers ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Care Providers ◽  
Patient Centered ◽  
Legal Advice ◽  
Medical Context

PurposeWhen patients refuse medical or rehabilitation procedures, waivers of liability have been used to bar future lawsuits. The purpose of this tutorial is to review the myriad issues surrounding consent, refusal, and waivers. The larger goal is to invigorate clinical practice by providing clinicians with knowledge of ethics and law. This tutorial is for educational purposes only and does not constitute legal advice.MethodThe authors use a hypothetical case of a “noncompliant” individual under the care of an interdisciplinary neurorehabilitation team to illuminate the ethical and legal features of the patient–practitioner relationship; the elements of clinical decision-making capacity; the duty of disclosure and the right of informed consent or informed refusal; and the relationship among noncompliance, defensive practices, and iatrogenic harm. We explore the legal question of whether waivers of liability in the medical context are enforceable or unenforceable as a matter of public policy.ConclusionsSpeech-language pathologists, among other health care providers, have fiduciary and other ethical and legal obligations to patients. Because waivers try to shift liability for substandard care from health care providers to patients, courts usually find waivers of liability in the medical context unenforceable as a matter of public policy.

scholarly journals Evaluation of User-Interface Alert Displays for Clinical Decision Support Systems for Sepsis

2018 ◽  
Vol 38 (4) ◽  
pp. 46-54 ◽  
Author(s):  
Devida Long ◽  
Muge Capan ◽  
Susan Mascioli ◽  
Danielle Weldon ◽  
Ryan Arnold ◽  
...  
Keyword(s):  
Health Care ◽  
Decision Support ◽  
User Interface ◽  
Decision Support Systems ◽  
Clinical Decision Support ◽  
Health Care Providers ◽  
Support Systems ◽  
Clinical Decision Support Systems ◽  
Clinical Decision ◽  
Care Providers

BACKGROUND Hospitals are increasingly turning to clinical decision support systems for sepsis, a life-threatening illness, to provide patient-specific assessments and recommendations to aid in evidence-based clinical decision-making. Lack of guidelines on how to present alerts has impeded optimization of alerts, specifically, effective ways to differentiate alerts while highlighting important pieces of information to create a universal standard for health care providers. OBJECTIVE To gain insight into clinical decision support systems–based alerts, specifically targeting nursing interventions for sepsis, with a focus on behaviors associated with and perceptions of alerts, as well as visual preferences. METHODS An interactive survey to display a novel user interface for clinical decision support systems for sepsis was developed and then administered to members of the nursing staff. RESULTS A total of 43 nurses participated in 2 interactive survey sessions. Participants preferred alerts that were based on an established treatment protocol, were presented in a pop-up format, and addressed the patient’s clinical condition rather than regulatory guidelines. CONCLUSIONS The results can be used in future research to optimize electronic medical record alerting and clinical practice workflow to support the efficient, effective, and timely delivery of high-quality care to patients with sepsis. The research also may advance the knowledge base of what information health care providers want and need to improve the health and safety of their patients.

scholarly journals Economic Value of Data and Analytics for Health Care Providers: Hermeneutic Systematic Literature Review

10.2196/23315 ◽  
2020 ◽  
Vol 22 (11) ◽  
pp. e23315
Author(s):  
Philip von Wedel ◽  
Christian Hagist
Keyword(s):  
Health Care ◽  
Decision Support ◽  
Economic Impact ◽  
Clinical Decision Support ◽  
Health Care Providers ◽  
Clinical Decision ◽  
Economic Benefits ◽  
Economic Effects ◽  
Care Providers ◽  
Advanced Analytics

Background The benefits of data and analytics for health care systems and single providers is an increasingly investigated field in digital health literature. Electronic health records (EHR), for example, can improve quality of care. Emerging analytics tools based on artificial intelligence show the potential to assist physicians in day-to-day workflows. Yet, single health care providers also need information regarding the economic impact when deciding on potential adoption of these tools. Objective This paper examines the question of whether data and analytics provide economic advantages or disadvantages for health care providers. The goal is to provide a comprehensive overview including a variety of technologies beyond computer-based patient records. Ultimately, findings are also intended to determine whether economic barriers for adoption by providers could exist. Methods A systematic literature search of the PubMed and Google Scholar online databases was conducted, following the hermeneutic methodology that encourages iterative search and interpretation cycles. After applying inclusion and exclusion criteria to 165 initially identified studies, 50 were included for qualitative synthesis and topic-based clustering. Results The review identified 5 major technology categories, namely EHRs (n=30), computerized clinical decision support (n=8), advanced analytics (n=5), business analytics (n=5), and telemedicine (n=2). Overall, 62% (31/50) of the reviewed studies indicated a positive economic impact for providers either via direct cost or revenue effects or via indirect efficiency or productivity improvements. When differentiating between categories, however, an ambiguous picture emerged for EHR, whereas analytics technologies like computerized clinical decision support and advanced analytics predominantly showed economic benefits. Conclusions The research question of whether data and analytics create economic benefits for health care providers cannot be answered uniformly. The results indicate ambiguous effects for EHRs, here representing data, and mainly positive effects for the significantly less studied analytics field. The mixed results regarding EHRs can create an economic barrier for adoption by providers. This barrier can translate into a bottleneck to positive economic effects of analytics technologies relying on EHR data. Ultimately, more research on economic effects of technologies other than EHRs is needed to generate a more reliable evidence base.

The Effects of the Medical Pause on Physiological Stress Markers among Health Care Providers: A Pilot Randomized Controlled Trial

2021 ◽  
pp. 019394592110276
Author(s):  
Ebru Cayir ◽  
Tim Cunningham ◽  
Ryne Ackard ◽  
Julie Haizlip ◽  
Jeongok Logan ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Health Care ◽  
Heart Rate ◽  
Heart Rate Variability ◽  
Health Care Providers ◽  
Physiological Stress ◽  
Intervention Group ◽  
Control Group ◽  
Care Providers ◽  
The Impact

Contemplative practices promote well-being, work engagement and resilience among health care providers. We examined the impact of The Pause, a brief contemplative intervention, on health care providers’ physiological stress response. Participants were randomly assigned to either The Pause or the control group. They participated in a high-fidelity, stressful medical simulation. Following the simulation, intervention group practiced The Pause. Outcome measures were heart rate variability, heart rate, and blood pressure. We adjusted for baseline physiological variables, sociodemographic variables, self-care practices, and perceived stress. Participants in the intervention group had a standard deviation of the normal-to-normal RR intervals (heart rate variability indicator) that was 13.8 (95% CI 4.0, 23.5; p < .01) points higher than those in the control group. There were no significant effects of The Pause on heart rate or blood pressure. The Pause may reduce stress reactivity, increase heart rate variability, and enhance resilience in health care providers.

scholarly journals Effectiveness of an educational intervention on complementary feeding practices and growth in rural China: a cluster randomised controlled trial

2009 ◽  
Vol 13 (4) ◽  
pp. 556-565 ◽  
Author(s):  
Ling Shi ◽  
Jingxu Zhang ◽  
Yan Wang ◽  
Laura E Caulfield ◽  
Bernard Guyer
Keyword(s):  
Health Care ◽  
Health Care Providers ◽  
Educational Intervention ◽  
Complementary Feeding ◽  
Intervention Group ◽  
Feeding Practices ◽  
Control Group ◽  
Local Health ◽  
Care Providers ◽  
Local Health Care

AbstractObjectiveInappropriate complementary feeding is one of the major causes of malnutrition in young children in developing countries. We developed an educational intervention, delivered by local health-care providers, aimed at improving complementary feeding practices and child nutrition.DesignEight townships in Laishui, a rural area in China, were randomly assigned to the educational intervention or control group. A total of 599 healthy infants were enrolled at age 2–4 months and followed up until 1 year of age. In the intervention group, educational messages and enhanced home-prepared recipes were disseminated to caregivers through group trainings and home visits. Questionnaire surveys and anthropometric measurements were taken at baseline and ages 6, 9 and 12 months. Analysis was by intention to treat.ResultsIt was found that food diversity, meal frequency and hygiene practices were improved in the intervention group. Infants in the intervention group gained 0·22 kg more weight (95 % CI 0·003, 0·45 kg, P = 0·047) and gained 0·66 cm more length (95 % CI 0·03, 1·29 cm, P = 0·04) than did controls over the study period.ConclusionsFindings from the study suggest that an educational intervention delivered through local health-care providers can lead to substantial behavioural changes of caregivers and improve infant growth.

Clinical Decision Support in the Management of Patients With Suspected Ebola Infection

2015 ◽  
Vol 9 (5) ◽  
pp. 591-594 ◽  
Author(s):  
Adam B. Landman ◽  
Eric Goralnick ◽  
Jonathan M. Teich
Keyword(s):  
Public Health ◽  
Health Care ◽  
Decision Support ◽  
Clinical Decision Support ◽  
Health Care Providers ◽  
Clinical Decision ◽  
Health Care Facilities ◽  
Care Providers ◽  
Clinical Workflow ◽  
Health Threats

AbstractPatients with suspected public health threats, such as Ebola, must be quickly identified and isolated on presentation to health care facilities. Patients can be screened by intake staff or other health care providers; however, perfect compliance is difficult to achieve. Well-designed, carefully placed clinical decision support (CDS) within the electronic health record can be a reliable partner in helping to rapidly identify, isolate, and care for patients with suspected Ebola infection and other emerging public health threats. We describe how different types of CDS can be applied in the clinical workflow and share how we implemented CDS to force Ebola screening upon patient presentation to our emergency department. (Disaster Med Public Health Preparedness. 2015;9:591–594)

scholarly journals Economic Value of Data and Analytics for Health Care Providers: Hermeneutic Systematic Literature Review (Preprint)

2020 ◽  
Author(s):  
Philip von Wedel ◽  
Christian Hagist
Keyword(s):  
Health Care ◽  
Decision Support ◽  
Economic Impact ◽  
Clinical Decision Support ◽  
Health Care Providers ◽  
Clinical Decision ◽  
Economic Benefits ◽  
Economic Effects ◽  
Care Providers ◽  
Advanced Analytics

BACKGROUND The benefits of data and analytics for health care systems and single providers is an increasingly investigated field in digital health literature. Electronic health records (EHR), for example, can improve quality of care. Emerging analytics tools based on artificial intelligence show the potential to assist physicians in day-to-day workflows. Yet, single health care providers also need information regarding the economic impact when deciding on potential adoption of these tools. OBJECTIVE This paper examines the question of whether data and analytics provide economic advantages or disadvantages for health care providers. The goal is to provide a comprehensive overview including a variety of technologies beyond computer-based patient records. Ultimately, findings are also intended to determine whether economic barriers for adoption by providers could exist. METHODS A systematic literature search of the PubMed and Google Scholar online databases was conducted, following the hermeneutic methodology that encourages iterative search and interpretation cycles. After applying inclusion and exclusion criteria to 165 initially identified studies, 50 were included for qualitative synthesis and topic-based clustering. RESULTS The review identified 5 major technology categories, namely EHRs (n=30), computerized clinical decision support (n=8), advanced analytics (n=5), business analytics (n=5), and telemedicine (n=2). Overall, 62% (31/50) of the reviewed studies indicated a positive economic impact for providers either via direct cost or revenue effects or via indirect efficiency or productivity improvements. When differentiating between categories, however, an ambiguous picture emerged for EHR, whereas analytics technologies like computerized clinical decision support and advanced analytics predominantly showed economic benefits. CONCLUSIONS The research question of whether data and analytics create economic benefits for health care providers cannot be answered uniformly. The results indicate ambiguous effects for EHRs, here representing data, and mainly positive effects for the significantly less studied analytics field. The mixed results regarding EHRs can create an economic barrier for adoption by providers. This barrier can translate into a bottleneck to positive economic effects of analytics technologies relying on EHR data. Ultimately, more research on economic effects of technologies other than EHRs is needed to generate a more reliable evidence base.

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