The Role for Knowledge Management in Modern Healthcare Delivery

2010 ◽  
Vol 2 (2) ◽  
pp. 1-9 ◽  
Author(s):  
Nilmini Wickramasinghe
Keyword(s):  
Knowledge Management ◽  
Medical Science ◽  
Healthcare Delivery ◽  
Healthcare Providers ◽  
Healthcare Setting ◽  
Full Potential ◽  
Information And Communications Technologies ◽  
Healthcare Operations ◽  
Knowledge Assets ◽  
Tools And Techniques

As medical science advances and the applications of information and communications technologies (ICTs) to healthcare operations diffuse more data, information begins to permeate healthcare databases and repositories. However, given the voluminous nature of these disparate data assets, it is no longer possible for healthcare providers to process these data without the aid of sophisticated tools and technologies. The goal of knowledge management is to provide the decision maker with appropriate tools, technologies, strategies and processes to turn data and information into valuable knowledge assets. This paper discusses the benefits of incorporating these tools and techniques to the healthcare arena in order to make healthcare delivery more effective and efficient. To ensure a successful knowledge management initiative in a healthcare setting, the paper proffers the knowledge management infrastructure (KMI) framework and intelligence continuum (IC) model. The benefits of these techniques lie not only in the ability of making explicit the elements of these knowledge assets, and in so doing enable their full potential to be realized, but also to provide a systematic and robust approach to structuring the conceptualization of knowledge assets.

Key Considerations for the Adoption and Implementation of Knowledge Management in Healthcare Operations

2010 ◽  
pp. 125-142 ◽  
Author(s):  
Nilmini Wickramasinghe ◽  
Elie Geisler
Keyword(s):  
Knowledge Management ◽  
Healthcare System ◽  
Healthcare Costs ◽  
Cost Effective ◽  
Healthcare Setting ◽  
Healthcare Systems ◽  
Healthcare Operations ◽  
Healthcare Settings ◽  
Adoption And Implementation ◽  
The U.S

The importance of knowledge management (KM) to organizations in today’s competitive environment is being recognized as paramount and significant. This is particularly evident for healthcare both globally and in the U.S. The U.S. healthcare system is facing numerous challenges in trying to deliver cost effective, high quality treatments and is turning to KM techniques and technologies for solutions in an attempt to achieve this goal. While the challenges facing the U.S. healthcare are not dissimilar to those facing healthcare systems in other nations, the U.S. healthcare system leads the field with healthcare costs more than 15% of GDP and rising exponentially. What is becoming of particular interest when trying to find a solution is the adoption and implementation of KM and associated KM technologies in the healthcare setting, an arena that has to date been notoriously slow to adopt technologies and new approaches for the practice management side of healthcare. We examine this issue by studying the barriers encountered in the adoption and implementation of specific KM technologies in healthcare settings. We then develop a model based on empirical data and using this model draw some conclusions and implications for orthopaedics.

Realizing Knowledge Assets in the Medical Sciences with Data Mining

2008 ◽  
pp. 3662-3674
Author(s):  
Adam Fadlalla ◽  
Nilmini Wickramasinghe
Keyword(s):  
Data Mining ◽  
Medical Science ◽  
Diagnostic Methods ◽  
Full Potential ◽  
Medical Sciences ◽  
Medical Field ◽  
Medical Specialties ◽  
Knowledge Assets ◽  
Data Mining Techniques ◽  
The Right

This chapter provides insight into various areas within the medical field that strive to take advantage of different data mining techniques in order to realize the full potential of their knowledge assets. Specifically, this is done by discussing many of the limitations associated with conventional methods of diagnosis and showing how data mining can be used to improve these methods. Comparative analyses of different techniques associated with various areas within the medical field are outlined in order to identify the right technique for particular medical specialties. Furthermore, suggestions are provided to appropriately utilize the various data mining techniques thereby leading to effective and efficient knowledge management and knowledge utilization. In this chapter we highlight the potential of data mining in improving the exploratory as well as the predictive capabilities of conventional diagnostic methods in medical science.

Realizing Knowledge Assets in the Medical Sciences with Data Mining

2005 ◽  
pp. 164-178 ◽  
Author(s):  
Adam Fadlalla ◽  
Nilmini Wickramasinghe
Keyword(s):  
Data Mining ◽  
Medical Science ◽  
Diagnostic Methods ◽  
Full Potential ◽  
Medical Sciences ◽  
Medical Field ◽  
Medical Specialties ◽  
Knowledge Assets ◽  
Data Mining Techniques ◽  
The Right

This chapter provides insight into various areas within the medical field that strive to take advantage of different data mining techniques in order to realize the full potential of their knowledge assets. Specifically, this is done by discussing many of the limitations associated with conventional methods of diagnosis and showing how data mining can be used to improve these methods. Comparative analyses of different techniques associated with various areas within the medical field are outlined in order to identify the right technique for particular medical specialties. Furthermore, suggestions are provided to appropriately utilize the various data mining techniques thereby leading to effective and efficient knowledge management and knowledge utilization. In this chapter we highlight the potential of data mining in improving the exploratory as well as the predictive capabilities of conventional diagnostic methods in medical science.

The Need for Developing Learning Healthcare Organisations

2020 ◽  
pp. 1-15
Author(s):  
Nilmini Wickramasinghe
Keyword(s):  
Big Data ◽  
Knowledge Management ◽  
Digital Health ◽  
Medical Science ◽  
Healthcare Delivery ◽  
Healthcare Systems ◽  
Organisational Learning ◽  
Sequencing Data ◽  
Healthcare Environments ◽  
Data Analytic

As the volumes of data generated in healthcare delivery grows, the need for embracing big data strategies and data analytic techniques to better navigate dynamic and complex healthcare environments becomes more and more pressing. This focus has been further fuelled by the advances in technologies and medical science and the incorporation of digital health solutions that enable us to isolate genome sequencing data. However, it is the thesis of this chapter that unless healthcare organisations become learning organisations and incorporate the techniques of knowledge management and organisational learning, these large and essentially raw data assets will become a burden and not a benefit. Thus, healthcare systems need to be redesigned into intelligent health systems that maximise technology and utilise valuable knowledge assets. To do this, it is imperative to understand the link between the principles of organisational learning and knowledge management (KM) to facilitate the building of learning healthcare organisations.

Realizing Knowledge Assets in the Medical Sciences with Data Mining

2011 ◽  
pp. 322-333
Author(s):  
Adam Fadlalla
Keyword(s):  
Data Mining ◽  
Medical Science ◽  
Diagnostic Methods ◽  
Full Potential ◽  
Medical Sciences ◽  
Medical Field ◽  
Medical Specialties ◽  
Knowledge Assets ◽  
Data Mining Techniques ◽  
The Right

This chapter provides insight into various areas within the medical field that strive to take advantage of different data mining techniques in order to realize the full potential of their knowledge assets. Specifically, this is done by discussing many of the limitations associated with conventional methods of diagnosis and showing how data mining can be used to improve these methods. Comparative analyses of different techniques associated with various areas within the medical field are outlined in order to identify the right technique for particular medical specialties. Furthermore, suggestions are provided to appropriately utilize the various data mining techniques thereby leading to effective and efficient knowledge management and knowledge utilization. In this chapter we highlight the potential of data mining in improving the exploratory as well as the predictive capabilities of conventional diagnostic methods in medical science.

Knowledge and Communication of the National Core Standards Tool

2018 ◽  
Vol 20 (2) ◽  
Author(s):  
Winnie Thembisile Maphumulo ◽  
Busisiwe Bhengu
Keyword(s):  
Pearson Correlation ◽  
Healthcare Delivery ◽  
Healthcare Providers ◽  
Sampling Technique ◽  
Quality Of Healthcare ◽  
Survey Study ◽  
Public Healthcare ◽  
Cross Sectional Survey ◽  
Cross Sectional ◽  
Professional Nurses

The National Department of Health in South Africa has introduced the National Core Standards (NCS) tool to improve the quality of healthcare delivery in all public healthcare institutions. Knowledge of the NCS tool is essential among healthcare providers. This study investigated the level of knowledge on NCS and how the NCS tool was communicated among professional nurses. This was a cross-sectional survey study. Purposive sampling technique was used to select hospitals that only offered tertiary services in KwaZulu-Natal. Six strata of departments were selected using simple stratified sampling. The population of professional nurses in the selected hospitals was 3 050. Systematic random sampling was used to recruit 543 participants. The collected data were analysed using SPSS version 25. The study showed that only 16 (3.7%) respondents had knowledge about NCS, using McDonald’s standard of learning outcome measured criteria regarding the NCS tool. The Pearson correlation coefficient between the communication and knowledge was r = 0.055. The results revealed that although the communication scores for the respondents were high their knowledge scores remained low. This study concluded that there is a lack of knowledge regarding the NCS tool and therefore healthcare institutions need to commit themselves to the training of professional nurses regarding the NCS tool. The findings suggest that healthcare institutions implement the allocation of incentives for nurses that attend the workshops for NCS.

scholarly journals Emergency cricothyrotomy during the COVID-19 pandemic: how to suppress aerosolization

2020 ◽  
Vol 5 (1) ◽  
pp. e000542
Author(s):  
Nabil Issa ◽  
Whitney E Liddy ◽  
Sandeep Samant ◽  
David B Conley ◽  
Robert C Kern ◽  
...  
Keyword(s):  
Potential Risk ◽  
Healthcare Providers ◽  
Healthcare Setting ◽  
Healthcare Systems ◽  
Financial Resources ◽  
Risk Of Infection ◽  
X Ray ◽  
General Surgeons ◽  
Fluorescein Dye ◽  
Nose And Throat

BackgroundCricothyrotomy is associated with significant aerosolization that increases the potential risk of infection among healthcare providers. It is important to identify simple yet effective methods to suppress aerosolization and improve the safety of healthcare providers.Methods5 ear, nose and throat and general surgeons used a locally developed hybrid cricothyrotomy simulator with a porcine trachea to test three draping methods to suppress aerosolization during the procedure: an X-ray cassette drape, dry operating room (OR) towels and wet OR towels. The three methods were judged based on three categories: effectiveness of suppression, availability in all healthcare systems and ease of handling.ResultsAll five surgeons performed the procedure independently using each of the three suppression methods. The wet OR towel drape was found to be an effective method to suppress aerosolization, and it did not hinder the surgeons from performing the procedure accurately. This finding was confirmed by using an atomized fluorescein dye injection into the porcine trachea, representing aerosolized material while performing the procedure.ConclusionsWe present a novel intervention using wet towels to suppress aerosolization during cricothyrotomy. Wet towels are cheap and readily available within any healthcare setting regardless of the financial resources available.

How Research Will Adapt to HIPAA: A View from Within the Healthcare Delivery System

2002 ◽  
Vol 28 (4) ◽  
pp. 491-502
Author(s):  
Mary L. Durham
Keyword(s):  
Health Information ◽  
Healthcare Delivery ◽  
Healthcare Providers ◽  
The United States ◽  
Personal Health Information ◽  
Personal Health ◽  
Business Associations ◽  
Electronic Information ◽  
Healthcare Delivery System ◽  
Institutional Review

While the new Health Insurance Privacy and Accountability Act (HIPAA) research rules governing privacy, confidentiality and personal health information will challenge the research and medical communities, history teaches us that the difficulty of this challenge pales in comparison to the potential harms that such regulations are designed to avoid. Although revised following broad commentary from researchers and healthcare providers around the country, the HIPAA privacy requirements will dramatically change the way healthcare researchers do their jobs in the United States. Given our reluctance to change, we risk overlooking potentially valid reasons why access to personal health information is restricted and regulated. In an environment of electronic information, public concern, genetic information and decline of public trust, regulations are ever-changing. Six categories of HIPAA requirements stand out as transformative: disclosure accounting/tracking, business associations, institutional review board (IRB) changes, minimum necessary requirements, data de-identification, and criminal and civil penalties.

scholarly journals Integrating Social Determinants of Health to Precision Medicine through Digital Transformation: An Exploratory Roadmap

2021 ◽  
Vol 18 (9) ◽  
pp. 5018
Author(s):  
Ik-Whan G. Kwon ◽  
Sung-Ho Kim ◽  
David Martin
Keyword(s):  
Precision Medicine ◽  
Social Determinants Of Health ◽  
Population Health ◽  
Social Determinants ◽  
Information Technologies ◽  
Healthcare Delivery ◽  
Healthcare Providers ◽  
Determinants Of Health ◽  
Collaborative Tools ◽  
High Level

The COVID-19 pandemic has altered healthcare delivery platforms from traditional face-to-face formats to online care through digital tools. The healthcare industry saw a rapid adoption of digital collaborative tools to provide care to patients, regardless of where patients or clinicians were located, while mitigating the risk of exposure to the coronavirus. Information technologies now allow healthcare providers to continue a high level of care for their patients through virtual visits, and to collaborate with other providers in the networks. Population health can be improved by social determinants of health and precision medicine working together. However, these two health-enhancing constructs work independently, resulting in suboptimal health results. This paper argues that artificial intelligence can provide clinical–community linkage that enhances overall population health. An exploratory roadmap is proposed.

To err is system; a comparison of methodologies for the investigation of adverse outcomes in healthcare

2021 ◽  
pp. 251604352199026
Author(s):  
Peter Isherwood ◽  
Patrick Waterson
Keyword(s):  
Patient Safety ◽  
System Performance ◽  
Healthcare Delivery ◽  
Healthcare Providers ◽  
Real Life ◽  
Adverse Outcomes ◽  
System Level ◽  
Future Performance ◽  
System A ◽  
Regulatory Bodies

Patient safety, staff moral and system performance are at the heart of healthcare delivery. Investigation of adverse outcomes is one strategy that enables organisations to learn and improve. Healthcare is now understood as a complex, possibly the most complex, socio-technological system. Despite this the use of a 20th century linear investigation model is still recommended for the investigation of adverse outcomes. In this review the authors use data gathered from the investigation of a real life healthcare near incident and apply three different methodologies to the analysis of this data. They compare both the methodologies themselves and the outputs generated. This illustrates how different methodologies generate different system level recommendations. The authors conclude that system based models generate the strongest barriers to improve future performance. Healthcare providers and their regulatory bodies need to embrace system based methodologies if they are to effectively learn from, and reduce future, adverse outcomes.

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