Data-analytically derived flexible HbA1c thresholds for type 2 diabetes mellitus diagnostic
- Stranieri, Andrew, Yatsko, Andrew, Jelinek, Herbert, Venkatraman, Sitalakshmi
- Authors: Stranieri, Andrew , Yatsko, Andrew , Jelinek, Herbert , Venkatraman, Sitalakshmi
- Date: 2015
- Type: Text , Journal article
- Relation: Artificial Intelligence Research Vol. 5, no. 1 (2015), p. 111-134
- Full Text:
- Reviewed:
- Description: Glycated haemoglobin (HbA1c) is now more commonly used as an alternative test to the fasting plasma glucose and oral glucose tolerance tests for the identification of Type 2 Diabetes Mellitus (T2DM) because it is easily obtained using the point-of-care technology and represents long-term blood sugar levels. According to WHO guidelines, HbA1c values of 6.5% or above are required for a diagnosis of T2DM. However outcomes of a large number of trials with HbA1c have been inconsistent across the clinical spectrum and further research is required to determine the efficacy of HbA1c testing in identification of T2DM. Medical records from a diabetes screening program in Australia illustrate that many patients could be classified as diabetics if other clinical indicators are included, even though the HbA1c result does not exceed 6.5%. This suggests that a cutoff for the general population of 6.5% may be too simple and miss individuals at risk or with already overt, undiagnosed diabetes. In this study, data mining algorithms have been applied to identify markers that can be used with HbA1c. The results indicate that T2DM is best classified by HbA1c at 6.2% - a cutoff level lower than the currently recommended one, which can be even less, having assumed the threshold flexibility, if additionally to HbA1c being high the rule is conditioned on oxidative stress or inflammation being present, atherogenicity or adiposity being high, or hypertension being diagnosed, etc.
- Authors: Stranieri, Andrew , Yatsko, Andrew , Jelinek, Herbert , Venkatraman, Sitalakshmi
- Date: 2015
- Type: Text , Journal article
- Relation: Artificial Intelligence Research Vol. 5, no. 1 (2015), p. 111-134
- Full Text:
- Reviewed:
- Description: Glycated haemoglobin (HbA1c) is now more commonly used as an alternative test to the fasting plasma glucose and oral glucose tolerance tests for the identification of Type 2 Diabetes Mellitus (T2DM) because it is easily obtained using the point-of-care technology and represents long-term blood sugar levels. According to WHO guidelines, HbA1c values of 6.5% or above are required for a diagnosis of T2DM. However outcomes of a large number of trials with HbA1c have been inconsistent across the clinical spectrum and further research is required to determine the efficacy of HbA1c testing in identification of T2DM. Medical records from a diabetes screening program in Australia illustrate that many patients could be classified as diabetics if other clinical indicators are included, even though the HbA1c result does not exceed 6.5%. This suggests that a cutoff for the general population of 6.5% may be too simple and miss individuals at risk or with already overt, undiagnosed diabetes. In this study, data mining algorithms have been applied to identify markers that can be used with HbA1c. The results indicate that T2DM is best classified by HbA1c at 6.2% - a cutoff level lower than the currently recommended one, which can be even less, having assumed the threshold flexibility, if additionally to HbA1c being high the rule is conditioned on oxidative stress or inflammation being present, atherogenicity or adiposity being high, or hypertension being diagnosed, etc.
Diagnostic with incomplete nominal/discrete data
- Jelinek, Herbert, Yatsko, Andrew, Stranieri, Andrew, Venkatraman, Sitalakshmi, Bagirov, Adil
- Authors: Jelinek, Herbert , Yatsko, Andrew , Stranieri, Andrew , Venkatraman, Sitalakshmi , Bagirov, Adil
- Date: 2015
- Type: Text , Journal article
- Relation: Artificial Intelligence Research Vol. 4, no. 1 (2015), p. 22-35
- Full Text:
- Reviewed:
- Description: Missing values may be present in data without undermining its use for diagnostic / classification purposes but compromise application of readily available software. Surrogate entries can remedy the situation, although the outcome is generally unknown. Discretization of continuous attributes renders all data nominal and is helpful in dealing with missing values; particularly, no special handling is required for different attribute types. A number of classifiers exist or can be reformulated for this representation. Some classifiers can be reinvented as data completion methods. In this work the Decision Tree, Nearest Neighbour, and Naive Bayesian methods are demonstrated to have the required aptness. An approach is implemented whereby the entered missing values are not necessarily a close match of the true data; however, they intend to cause the least hindrance for classification. The proposed techniques find their application particularly in medical diagnostics. Where clinical data represents a number of related conditions, taking Cartesian product of class values of the underlying sub-problems allows narrowing down of the selection of missing value substitutes. Real-world data examples, some publically available, are enlisted for testing. The proposed and benchmark methods are compared by classifying the data before and after missing value imputation, indicating a significant improvement.
- Authors: Jelinek, Herbert , Yatsko, Andrew , Stranieri, Andrew , Venkatraman, Sitalakshmi , Bagirov, Adil
- Date: 2015
- Type: Text , Journal article
- Relation: Artificial Intelligence Research Vol. 4, no. 1 (2015), p. 22-35
- Full Text:
- Reviewed:
- Description: Missing values may be present in data without undermining its use for diagnostic / classification purposes but compromise application of readily available software. Surrogate entries can remedy the situation, although the outcome is generally unknown. Discretization of continuous attributes renders all data nominal and is helpful in dealing with missing values; particularly, no special handling is required for different attribute types. A number of classifiers exist or can be reformulated for this representation. Some classifiers can be reinvented as data completion methods. In this work the Decision Tree, Nearest Neighbour, and Naive Bayesian methods are demonstrated to have the required aptness. An approach is implemented whereby the entered missing values are not necessarily a close match of the true data; however, they intend to cause the least hindrance for classification. The proposed techniques find their application particularly in medical diagnostics. Where clinical data represents a number of related conditions, taking Cartesian product of class values of the underlying sub-problems allows narrowing down of the selection of missing value substitutes. Real-world data examples, some publically available, are enlisted for testing. The proposed and benchmark methods are compared by classifying the data before and after missing value imputation, indicating a significant improvement.
Organisational barriers to effective pain management amongst oncology nurses in Saudi Arabia
- Alqahtani, Mohammed, Jones, Linda, Holroyd, Eleanor
- Authors: Alqahtani, Mohammed , Jones, Linda , Holroyd, Eleanor
- Date: 2015
- Type: Text , Journal article
- Relation: Journal of Hospital Administration Vol. 5, no. 1 (2015), p. 81-89
- Full Text:
- Reviewed:
- Description: Cancer pain is a multi-dimensional syndrome with a combination of acute and chronic pain that causes physical, psycho-social, behavioural, emotional and spiritual problems resulting in adverse effects on patients’ quality of life. Nurses need to be well prepared with knowledge on pain assessment and management techniques in oncology units, due to their vital role in the decision-making process regarding pain management. However, limited research has been conducted regarding nurses’ barriers regarding pain management in oncology units, especially in Saudi Arabia. The overall aim of this study was to explore the nurses’ perceived barriers that hinder the delivery of effective pain management to cancer patients. Five focus group discussions were conducted using a purposive sampling of six to eight nurses in each group, with a total of 35 oncology nurses. The results of focus group analysis revealed two main thematic categories with associated sub themes, being nurses’ workloads, and the absence of health team collaboration. This study provides an increased awareness of the barriers that may hinder the efficacy of pain management provided to cancer patients in Saudi Arabia context. Significant implications will benefit nursing practice, administration and education, in addition to identifying potential future research.
- Authors: Alqahtani, Mohammed , Jones, Linda , Holroyd, Eleanor
- Date: 2015
- Type: Text , Journal article
- Relation: Journal of Hospital Administration Vol. 5, no. 1 (2015), p. 81-89
- Full Text:
- Reviewed:
- Description: Cancer pain is a multi-dimensional syndrome with a combination of acute and chronic pain that causes physical, psycho-social, behavioural, emotional and spiritual problems resulting in adverse effects on patients’ quality of life. Nurses need to be well prepared with knowledge on pain assessment and management techniques in oncology units, due to their vital role in the decision-making process regarding pain management. However, limited research has been conducted regarding nurses’ barriers regarding pain management in oncology units, especially in Saudi Arabia. The overall aim of this study was to explore the nurses’ perceived barriers that hinder the delivery of effective pain management to cancer patients. Five focus group discussions were conducted using a purposive sampling of six to eight nurses in each group, with a total of 35 oncology nurses. The results of focus group analysis revealed two main thematic categories with associated sub themes, being nurses’ workloads, and the absence of health team collaboration. This study provides an increased awareness of the barriers that may hinder the efficacy of pain management provided to cancer patients in Saudi Arabia context. Significant implications will benefit nursing practice, administration and education, in addition to identifying potential future research.
Quantitative exploration of the barriers and facilitators to nurse-patient communication in Saudia Arabia
- Albagawi, Bander, Jones, Linda
- Authors: Albagawi, Bander , Jones, Linda
- Date: 2016
- Type: Text , Journal article
- Relation: Journal of Hospital Administration Vol. 6, no. 1 (2016), p.16-24
- Full Text:
- Reviewed:
- Description: Nurses with effective communication skills play a critical role in minimising the stress associated with hospitalisation for both patients and their families. Effective communication has become increasingly reported as a key component in effective health care outcomes, which is even more crucial in countries such as Saudi Arabia with a large foreign healthcare workforce. The presence of a large expatriate workforce with a different language from the host society and the ensuing complexity of sociocultural linguistic and heath beliefs systems has been poorly researched. This study aimed to investigate barriers and facilitators of nurse-patient communication in Saudi Arabia using the Nurses’ Self-Administered Communication Survey. The survey was distributed to a random sample of 291 nurses working in medical and surgical departments at five hospitals in Saudi Arabia. The results indicate that the Philippine and Saudi Arabian nurses perceived greater barriers to communication with respect to personal/social characteristics, job specifications and environmental factors then nurses of other nationalities. In addition, nurses with shorter experience in Saudi Arabia perceived greater barriers to communication with respect to the clinical situation of patient and environmental factors than the nurses with longer experience. Lastly, nurses who had not attended specialist courses on communication skills acquisition perceived greater barriers to communication with respect to personal characteristics and job specifications than nurses who had attended such courses. This study highlights the need to better prepare expatriate nurses before they enter the workforce in Saudi Arabia on cultural competence and language skills.
- Authors: Albagawi, Bander , Jones, Linda
- Date: 2016
- Type: Text , Journal article
- Relation: Journal of Hospital Administration Vol. 6, no. 1 (2016), p.16-24
- Full Text:
- Reviewed:
- Description: Nurses with effective communication skills play a critical role in minimising the stress associated with hospitalisation for both patients and their families. Effective communication has become increasingly reported as a key component in effective health care outcomes, which is even more crucial in countries such as Saudi Arabia with a large foreign healthcare workforce. The presence of a large expatriate workforce with a different language from the host society and the ensuing complexity of sociocultural linguistic and heath beliefs systems has been poorly researched. This study aimed to investigate barriers and facilitators of nurse-patient communication in Saudi Arabia using the Nurses’ Self-Administered Communication Survey. The survey was distributed to a random sample of 291 nurses working in medical and surgical departments at five hospitals in Saudi Arabia. The results indicate that the Philippine and Saudi Arabian nurses perceived greater barriers to communication with respect to personal/social characteristics, job specifications and environmental factors then nurses of other nationalities. In addition, nurses with shorter experience in Saudi Arabia perceived greater barriers to communication with respect to the clinical situation of patient and environmental factors than the nurses with longer experience. Lastly, nurses who had not attended specialist courses on communication skills acquisition perceived greater barriers to communication with respect to personal characteristics and job specifications than nurses who had attended such courses. This study highlights the need to better prepare expatriate nurses before they enter the workforce in Saudi Arabia on cultural competence and language skills.
- «
- ‹
- 1
- ›
- »