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.

The Use of Simulation Training in Teaching Health Care Quality and Safety: An Annotated Bibliography

2011 ◽  
Vol 26 (3) ◽  
pp. 229-238 ◽  
Author(s):  
Justin Abraham ◽  
Dina M. Wade ◽  
Katherine A. O'Connell ◽  
Susan Desharnais ◽  
Richard Jacoby
Keyword(s):  
Health Care ◽  
Health Care Quality ◽  
Simulation Training ◽  
Care Quality ◽  
Annotated Bibliography ◽  
Quality And Safety

scholarly journals Komunitas Masyarakat Dan Perawatan Kesehatan Dalam Peningkatan Kualitas Hidup

2020 ◽  
Vol 10 (1) ◽  
pp. 11-24
Author(s):  
Agustinus Hermino
Keyword(s):  
Quality Of Life ◽  
Health Care ◽  
Health Care Quality ◽  
Health Sector ◽  
Well Being ◽  
Individual Variability ◽  
Care Quality ◽  
Global Era ◽  
The Impact

Latar belakang: Seiring dengan perkembangan jaman, dalam beberapa tahun terakhir ini banyak perhatian yang difokuskan pada eksplorasi dampak penyakit fisik dan mental pada kualitas hidup seseorang baik secara individu maupun masyarakat secara keseluruhan. Sifat subyektif dari 'kualitas hidup' individu, merupakan konsep yang dinamis untuk diukur dan didefinisikan, tetapi bahwa secara umum dapat dipandang sebagai konsep multidimensi yang menekankan pada persepsi diri dari keadaan pikiran seseorang saat iniTujuan: penulisan ini bertujuan untuk memberikan pemahaman tentang peran masyarakat dalam memahani pentingnya kesehatan di era global ditinjau dari perspektif akademis. Pada sektor kesehatan pemahaman kesehatan menjadi sangat pentingnya karena akan menunjukkan pada kualitas hidup seseorang, tetapi hal ini tidak cukup secara individu karena diperlukan pemahaman secara menyeluruh terhadap masyarakat tentang makna kesehatan dan perawatan kesehatan.Metode: penulisan ilmiah ini adalah dengan melakukan analisa akademis dari dari berbagai sumber rujukan relevan sehingga menemukan makna teoritis baru dalam rangka menjawab tantangan yang terjadi di masyarakat.Hasil: Berdasarkan berbagai sumber rujukan yang ada, dapat disimpulkan bahwa kesehatan merupakan gaya hidup yang bertujuan untuk mencapai kesejahteraan fisik, emosional, intelektual, spiritual, dan lingkungan. Penggunaan langkah-langkah kesehatan dapat meningkatkan stamina, energi, dan harga diri, kemudian meningkatkan kualitas hidup. Dengan demikian maka konsep kesehatan memungkinkan adanya variabilitas individu. Kesehatan dapat dianggap sebagai keseimbangan aspek fisik, emosional, psikologis, sosial dan spiritual dari kehidupan seseorang. Kata kunci: masyarakat, perawatan kesehatan, kualitas hidup Society Community and Health Care in Improving Quality of LifeAbstract Background: Along with the development of the era, in recent years there has been a lot of attention focused on exploring the impact of physical and mental illness on the quality of life of a person both individually and as a whole. The subjective nature of an individual's 'quality of life' is a dynamic concept to measure and define, but that in general can be seen as a multidimensional concept that emphasizes self-perception of one's current state of mindAim: purpose of this study is to provide an understanding the role of community in understanding the importance of health in the global era from an academic perspective. In the health sector understanding of health is very important because it will show the quality of life of a person, but this is not enough individually because a comprehensive understanding of the meaning of health and health care is needed. Method: The method of scientific writing is to carry out academic analysis from various relevant reference sources, and find new theoretical meanings in order to answer the challenges that occur in society. Keyword: Community, Society,Health Care, Quality oflife Resullt : Based on various academic reference, it can be concluded that health is a lifestyle that aims to achieve physical, emotional, intellectual, spiritual, and environmental well-being. The use of health measures can increase stamina, energy, and self-esteem, then improve the quality of life. Thus the concept of health allows for individual variability. Health can be considered as a balance of physical, emotional, psychological, social and spiritual aspects of one's life. Keywords: community, health care, quality of life 

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

Medical Errors

2017 ◽  
pp. 33-60
Author(s):  
Jayita Poduval
Keyword(s):  
Health Care ◽  
Medical Errors ◽  
Health Care Professionals ◽  
Health Care Quality ◽  
Service Providers ◽  
Care Quality ◽  
System Failures ◽  
Root Cause ◽  
The Impact ◽  
Improving Health Care

The impact of medical errors on the delivery of health care is massive, and it significantly reduces health care quality. They could be largely attributed to system failures and not human weakness. Therefore improving health care quality and ensuring quality control in health care would mean making systems function in a better manner. In order to achieve this all sections of society as well as industry must be involved. Reporting of medical error needs to be encouraged and this may be ensured if health care professionals as well as administrators and health consumers come forward without fear of being blamed. To get to the root of the problem- literally and metaphorically- a root cause analysis and audit must be carried out whenever feasible. Persons outside the medical care establishment also need to work with medical service providers to set standards of performance, competence and excellence.

scholarly journals The Impact of Discharge Decisions on Health Care Quality

1998 ◽  
Vol 44 (3) ◽  
pp. 400-415 ◽  
Author(s):  
Emre Berk ◽  
Kamran Moinzadeh
Keyword(s):  
Health Care ◽  
Health Care Quality ◽  
Care Quality ◽  
The Impact

The impact of new technologies on clinical decision-making in health care

Science ◽  
2015 ◽  
Vol 350 (6266) ◽  
pp. 1397-1397
Author(s):  
R. Rosenquist Brandell ◽  
O. Kallioniemi ◽  
A. Wedell
Keyword(s):  
Health Care ◽  
Decision Making ◽  
Clinical Decision Making ◽  
New Technologies ◽  
Clinical Decision ◽  
The Impact

scholarly journals A Quality Improvement Initiative to Decrease Platelet Ordering Errors and a Proposed Model for Evaluating Clinical Decision Support Effectiveness

2019 ◽  
Vol 10 (03) ◽  
pp. 505-512
Author(s):  
Julia Whitlow Yarahuan ◽  
Amy Billet ◽  
Jonathan D. Hron
Keyword(s):  
Decision Support ◽  
Clinical Decision Support ◽  
Health Care Quality ◽  
Platelet Transfusion ◽  
Tertiary Care ◽  
Clinical Decision ◽  
Care Quality ◽  
Inpatient Service ◽  
The Impact ◽  
Order Set

Background and Objectives Clinical decision support (CDS) and computerized provider order entry have been shown to improve health care quality and safety, but may also generate previously unanticipated errors. We identified multiple CDS tools for platelet transfusion orders. In this study, we sought to evaluate and improve the effectiveness of those CDS tools while creating and testing a framework for future evaluation of other CDS tools. Methods Using a query of an enterprise data warehouse at a tertiary care pediatric hospital, we conducted a retrospective analysis to assess baseline use and performance of existing CDS for platelet transfusion orders. Our outcome measure was the percentage of platelet undertransfusion ordering errors. Errors were defined as platelet transfusion volumes ordered which were less than the amount recommended by the order set used. We then redesigned our CDS and measured the impact of our intervention prospectively using statistical process control methodology. Results We identified that 62% of all platelet transfusion orders were placed with one of two order sets (Inpatient Service 1 and Inpatient Service 2). The Inpatient Service 1 order set had a significantly higher occurrence of ordering errors (3.10% compared with 1.20%). After our interventions, platelet transfusion order error occurrence on Inpatient Service 1 decreased from 3.10 to 0.33%. Conclusion We successfully reduced platelet transfusion ordering errors by redesigning our CDS tools. We suggest that the use of collections of clinical data may help identify patterns in erroneous ordering, which could otherwise go undetected. We have created a framework which can be used to evaluate the effectiveness of other similar CDS tools.

scholarly journals MINIMAR (MINimum Information for Medical AI Reporting): Developing reporting standards for artificial intelligence in health care

2020 ◽  
Vol 27 (12) ◽  
pp. 2011-2015 ◽  
Author(s):  
Tina Hernandez-Boussard ◽  
Selen Bozkurt ◽  
John P A Ioannidis ◽  
Nigam H Shah
Keyword(s):  
Artificial Intelligence ◽  
Health Care ◽  
Clinical Decision Making ◽  
Prediction Models ◽  
Clinical Decision ◽  
Digital Data ◽  
Reporting Standards ◽  
Minimum Information ◽  
Support Tools ◽  
Hidden Biases

Abstract The rise of digital data and computing power have contributed to significant advancements in artificial intelligence (AI), leading to the use of classification and prediction models in health care to enhance clinical decision-making for diagnosis, treatment and prognosis. However, such advances are limited by the lack of reporting standards for the data used to develop those models, the model architecture, and the model evaluation and validation processes. Here, we present MINIMAR (MINimum Information for Medical AI Reporting), a proposal describing the minimum information necessary to understand intended predictions, target populations, and hidden biases, and the ability to generalize these emerging technologies. We call for a standard to accurately and responsibly report on AI in health care. This will facilitate the design and implementation of these models and promote the development and use of associated clinical decision support tools, as well as manage concerns regarding accuracy and bias.

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