scholarly journals Reducing Alert Fatigue by Sharing Low-Level Alerts With Patients and Enhancing Collaborative Decision Making Using Blockchain Technology: Scoping Review and Proposed Framework (MedAlert) (Preprint)

2020 ◽  
Author(s):  
Paul Kengfai Wan ◽  
Abylay Satybaldy ◽  
Lizhen Huang ◽  
Halvor Holtskog ◽  
Mariusz Nowostawski
Keyword(s):  
Health Care ◽  
Decision Making ◽  
Scoping Review ◽  
Health Care Quality ◽  
Research Question ◽  
Clinical Decision ◽  
Care Quality ◽  
Alert Fatigue ◽  
Low Level ◽  
Future Work

BACKGROUND Clinical decision support (CDS) is a tool that helps clinicians in decision making by generating clinical alerts to supplement their previous knowledge and experience. However, CDS generates a high volume of irrelevant alerts, resulting in alert fatigue among clinicians. Alert fatigue is the mental state of alerts consuming too much time and mental energy, which often results in relevant alerts being overridden unjustifiably, along with clinically irrelevant ones. Consequently, clinicians become less responsive to important alerts, which opens the door to medication errors. OBJECTIVE This study aims to explore how a blockchain-based solution can reduce alert fatigue through collaborative alert sharing in the health sector, thus improving overall health care quality for both patients and clinicians. METHODS We have designed a 4-step approach to answer this research question. First, we identified five potential challenges based on the published literature through a scoping review. Second, a framework is designed to reduce alert fatigue by addressing the identified challenges with different digital components. Third, an evaluation is made by comparing MedAlert with other proposed solutions. Finally, the limitations and future work are also discussed. RESULTS Of the 341 academic papers collected, 8 were selected and analyzed. MedAlert securely distributes low-level (nonlife-threatening) clinical alerts to patients, enabling a collaborative clinical decision. Among the solutions in our framework, Hyperledger (private permissioned blockchain) and BankID (federated digital identity management) have been selected to overcome challenges such as data integrity, user identity, and privacy issues. CONCLUSIONS MedAlert can reduce alert fatigue by attracting the attention of patients and clinicians, instead of solely reducing the total number of alerts. MedAlert offers other advantages, such as ensuring a higher degree of patient privacy and faster transaction times compared with other frameworks. This framework may not be suitable for elderly patients who are not technology savvy or in-patients. Future work in validating this framework based on real health care scenarios is needed to provide the performance evaluations of MedAlert and thus gain support for the better development of this idea. CLINICALTRIAL

scholarly journals Reducing Alert Fatigue by Sharing Low-Level Alerts With Patients and Enhancing Collaborative Decision Making Using Blockchain Technology: Scoping Review and Proposed Framework (MedAlert)

10.2196/22013 ◽  
2020 ◽  
Vol 22 (10) ◽  
pp. e22013
Author(s):  
Paul Kengfai Wan ◽  
Abylay Satybaldy ◽  
Lizhen Huang ◽  
Halvor Holtskog ◽  
Mariusz Nowostawski
Keyword(s):  
Health Care ◽  
Decision Making ◽  
Scoping Review ◽  
Health Care Quality ◽  
Research Question ◽  
Clinical Decision ◽  
Care Quality ◽  
Alert Fatigue ◽  
Low Level ◽  
Future Work

Background Clinical decision support (CDS) is a tool that helps clinicians in decision making by generating clinical alerts to supplement their previous knowledge and experience. However, CDS generates a high volume of irrelevant alerts, resulting in alert fatigue among clinicians. Alert fatigue is the mental state of alerts consuming too much time and mental energy, which often results in relevant alerts being overridden unjustifiably, along with clinically irrelevant ones. Consequently, clinicians become less responsive to important alerts, which opens the door to medication errors. Objective This study aims to explore how a blockchain-based solution can reduce alert fatigue through collaborative alert sharing in the health sector, thus improving overall health care quality for both patients and clinicians. Methods We have designed a 4-step approach to answer this research question. First, we identified five potential challenges based on the published literature through a scoping review. Second, a framework is designed to reduce alert fatigue by addressing the identified challenges with different digital components. Third, an evaluation is made by comparing MedAlert with other proposed solutions. Finally, the limitations and future work are also discussed. Results Of the 341 academic papers collected, 8 were selected and analyzed. MedAlert securely distributes low-level (nonlife-threatening) clinical alerts to patients, enabling a collaborative clinical decision. Among the solutions in our framework, Hyperledger (private permissioned blockchain) and BankID (federated digital identity management) have been selected to overcome challenges such as data integrity, user identity, and privacy issues. Conclusions MedAlert can reduce alert fatigue by attracting the attention of patients and clinicians, instead of solely reducing the total number of alerts. MedAlert offers other advantages, such as ensuring a higher degree of patient privacy and faster transaction times compared with other frameworks. This framework may not be suitable for elderly patients who are not technology savvy or in-patients. Future work in validating this framework based on real health care scenarios is needed to provide the performance evaluations of MedAlert and thus gain support for the better development of this idea.

scholarly journals Hearing Loss and Help-Seeking Behavior

2020 ◽  
Vol 4 (Supplement_1) ◽  
pp. 797-797
Author(s):  
Nicholas Reed
Keyword(s):  
Health Care ◽  
Hearing Loss ◽  
Help Seeking ◽  
Health Care Quality ◽  
Medicare Beneficiary ◽  
Care Quality ◽  
The Past ◽  
Help Seeking Behaviour ◽  
Seeking Behavior ◽  
Future Work

Abstract Hearing Loss (HL) is common among older adults and is associated with poor health care quality outcomes include 30-day readmissions, length of stay, poorer satisfaction, and increased medical expenditures. These associations may manifest in changes in help-seeking behaviour. In the 2015 Current Medicare Beneficiary Study (MCBS) (n=10848; weighted sample=46.3 million), participants reported whether they knowingly had avoided seeking care in the past year and self-reported HL was measured as degree of trouble (none, a little, or a lot) hearing when using a hearing aid if applicable. In a model adjusted for demographic, socioeconomic, and health factors, those with a little trouble (OR= 1.612; 95% CI= 1.334-1.947; P<0.001) and a lot of trouble hearing (OR= 2.011; 95% CI= 1.443-2.801; P<0.001) had 61.2% and 101.1% higher odds of avoiding health care over the past year relative to participants with no trouble hearing. Future work should examine whether hearing care modifies this association.

scholarly journals Reaching those most in need: A scoping review of interventions to improve health care quality for disadvantaged populations with osteoarthritis

2010 ◽  
Vol 63 (1) ◽  
pp. 39-52 ◽  
Author(s):  
Cornelia M. Borkhoff ◽  
Mark L. Wieland ◽  
Elena Myasoedova ◽  
Zareen Ahmad ◽  
Vivian Welch ◽  
...  
Keyword(s):  
Health Care ◽  
Scoping Review ◽  
Health Care Quality ◽  
Care Quality ◽  
Improve Health Care ◽  
Disadvantaged Populations ◽  
Improve Health Care Quality ◽  
Improve Health

scholarly journals Use of EHR-Based Pediatric Quality Measures: Views of Health System Leaders and Parents

2019 ◽  
Vol 35 (2) ◽  
pp. 177-185
Author(s):  
David M. Hartley ◽  
Susannah Jonas ◽  
Daniel Grossoehme ◽  
Amy Kelly ◽  
Cassandra Dodds ◽  
...  
Keyword(s):  
Health Care ◽  
Decision Making ◽  
Health System ◽  
Health Care Quality ◽  
Quality Measures ◽  
Care Quality ◽  
Quality Data ◽  
High Confidence ◽  
System Leaders ◽  
Using Data

Measures of health care quality are produced from a variety of data sources, but often, physicians do not believe these measures reflect the quality of provided care. The aim was to assess the value to health system leaders (HSLs) and parents of benchmarking on health care quality measures using data mined from the electronic health record (EHR). Using in-context interviews with HSLs and parents, the authors investigated what new decisions and actions benchmarking using data mined from the EHR may enable and how benchmarking information should be presented to be most informative. Results demonstrate that although parents may have little experience using data on health care quality for decision making, they affirmed its potential value. HSLs expressed the need for high-confidence, validated metrics. They also perceived barriers to achieving meaningful metrics but recognized that mining data directly from the EHR could overcome those barriers. Parents and HSLs need high-confidence health care quality data to support decision making.

Patient registries from the view of health policy

2014 ◽  
Vol 155 (19) ◽  
pp. 729-731 ◽  
Author(s):  
Ildikó Kissné Horváth
Keyword(s):  
Health Care ◽  
Decision Making ◽  
Health Policy ◽  
Health Care Providers ◽  
Health Care Quality ◽  
Health Data ◽  
Care Quality ◽  
Care Providers ◽  
Critical Importance ◽  
Disease Registries

Integrated health data management and disease registries which are able to support evidence-based decision making are of critical importance for health policy. Data provided by disease registries are used for the development of health strategy, planning of preventive activities, capacity-building in health care provision, improving health care quality, and planning clinical trials. Disease registries monitoring epidemiology, natural history of diseases, treatment outcomes and the detection of adverse reactions are requested not only by policy-makers, but public health authorities and health care providers, too. Registries for rare diseases are of critical importance for developing network between reference centres and developing and evaluating new drugs. Data and information need for decision-making in public services and the protection of health data of individuals require a careful balance that needs to be taken into account when considering disease registries. Orv. Hetil., 2014, 155(19), 729–731.

scholarly journals The Impact of Artificial Intelligence on Quality and Safety

2020 ◽  
Vol 10 (1_suppl) ◽  
pp. 99S-103S
Author(s):  
Michelle S. Lee ◽  
Matthew M. Grabowski ◽  
Ghaith Habboub ◽  
Thomas E. Mroz
Keyword(s):  
Artificial Intelligence ◽  
Health Care ◽  
Health Care Quality ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Care Quality ◽  
Cost Of Care ◽  
Quality And Safety ◽  
Future Outcomes ◽  
The Impact

As exponential expansion of computing capacity converges with unsustainable health care spending, a hopeful opportunity has emerged: the use of artificial intelligence to enhance health care quality and safety. These computer-based algorithms can perform the intricate and extremely complex mathematical operations of classification or regression on immense amounts of data to detect intricate and potentially previously unknown patterns in that data, with the end result of creating predictive models that can be utilized in clinical practice. Such models are designed to distinguish relevant from irrelevant data regarding a particular patient; choose appropriate perioperative care, intervention or surgery; predict cost of care and reimbursement; and predict future outcomes on a variety of anchored measures. If and when one is brought to fruition, an artificial intelligence platform could serve as the first legitimate clinical decision-making tool in spine care, delivering on the value equation while serving as a source for improving physician performance and promoting appropriate, efficient care in this era of financial uncertainty in health care.

scholarly journals Research on the Quality of Abdominal Surgical Nursing Care: A Scoping Review

Medicina ◽  
2011 ◽  
Vol 47 (5) ◽  
pp. 35 ◽  
Author(s):  
Natalja Istomina ◽  
Tarja Suominen ◽  
Artūras Razbadauskas ◽  
Helena Leino-Kilpi
Keyword(s):  
Health Care ◽  
Abdominal Surgery ◽  
Nursing Care ◽  
Scoping Review ◽  
Health Care Quality ◽  
Care Quality ◽  
Care Needs ◽  
Measurement And Evaluation ◽  
Quality Of Nursing

Various health care measures have been identified over the years as indicators of health care quality. However, studies evaluating the quality of nursing care among different patient groups are scarce. Patients undergoing abdominal surgery may be a group that has different views, needs, expectations, and evaluation of the quality of nursing care. Literature search was conducted using the following key words in various combinations in the MEDLINE, PsycInfo, CINAHL, and Cochrane databases: quality of nursing, surgical or perioperative, abdominal or abdomen. The studies that focused on the evaluation of surgical nursing care with a study sample of patients undergoing abdominal surgery and nurses taking care of these patients were included in this scoping review. In total, 17 research articles were analyzed. The analysis revealed that the quality of nursing care was usually rated as high according to the perceptions of patients and/or nurses. The following factors associated with the quality of nursing care were identified: nurse staffing, organizational characteristics, patients’ characteristics, nurses’ characteristics, nursing care needs, and nursing documentation. Further research should be focused on the measurement and evaluation of the quality of abdominal surgical nursing care from nurses’, patients’ and their relatives’ perceptions by using nonexperimental and experimental study designs for gaining the knowledge how to improve the quality in practice.

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