Journal of Taibah University Medical Sciences, Dec 1, 2021
Objectives This research explores the association between variables routinely collected in a heal... more Objectives This research explores the association between variables routinely collected in a health information system and the readmission of patients with type 2 diabetes within 30 days of discharge. Methods This retrospective cohort study was conducted at King Fahd Hospital of the University (KFHU) in Al-Khobar, KSA. The study population comprised patients with type 2 diabetes who were admitted to the hospital from January 2016 to November 2016. Data were obtained from the hospital's information system at KFHU. The association between the readmission of patients with type 2 diabetes and routinely collected health information system variables such as demographics, type of diabetes, length of stay, and discharge type were analyzed. Results A total of 497 cases met the inclusion criteria. Of these, 31 (6.2%) cases were readmitted within 30 days. Type 2 diabetes was the only variable found to be significantly associated with readmission within 30 days (χ2 (1, N = 497) = 6.116, p = 0.0134). Diabetes type (p = 0.0133) and discharge type (p = 0.0403) were the only variables that displayed significance utilizing a logistic regression model. Conclusion Overall, the routinely collected demographic, diagnostic, and administrative variables were found to be poor predictors of 30-day readmission for type 2 diabetes at the institution studied. Nonetheless, the only significant variables in the prediction of 30-day readmission were diabetes type and discharge type. To determine the predictors of readmission, it is recommended that future studies include height and weight to the routinely collected health information system variables. We also suggest that future studies be based on data collected over several years or on pooled data collected from several hospitals.
The Canadian Journal of Hospital Pharmacy, Oct 3, 2022
Our objective was to assess the effect of implementing an electronic health record (EHR) on surgi... more Our objective was to assess the effect of implementing an electronic health record (EHR) on surgical resident work flow, duty hours, and operative experience at a large teaching hospital. In May 2012, an EHR was put into effect at our institution replacing paper documentation and orders. Resident time to complete patient documentation, average duty hours, and operative experience before EHR and afterward (at 1, 4, 6, 8, and 24 weeks) were surveyed. We obtained 100 per cent response rate from 15 surgical residents at all time intervals. The average time spent documenting before EHR was 9 6 2 minutes per patient document and at Weeks 1, 4, 6, 8, and 24 after EHR implementation was 22 6 10, 15 6 7, 15 6 7, 14 6 8, and 12 6 4 minutes, respectively. Repeated measures analysis of variance demonstrated a difference among the means (P \ 0.0001). Discharge summary and operative note remained significantly longer to complete at Week 24 compared with paper documentation (P \ 0.05). Average resident work hours and operative cases per week before EHR were 77 6 5 hours and 12 6 5 cases, respectively, which were similar at all time points after EHR implementation (P [ 0.05). At 24 weeks after EHR, 74 per cent of residents felt their risk of performing a medical error using electronic documentation and order entry was higher compared with paper charting and orders. Transition to EHR led to a significant doubling in resident time spent performing documentation for each patient. It improved over 6 months after implementation but never reached the pre-EHR baseline for operative notes and discharge summaries. Average resident work hours and case logs remained similar during this transition.
The aim of this study is to evaluate the WhatsApp social networking application for improving kno... more The aim of this study is to evaluate the WhatsApp social networking application for improving knowledge, self-efficacy and awareness about diabetes management. Methodology: The study was conducted with intervention and control groups at Teaching Hospital in Al-Khobar, Saudi Arabia. The intervention group received weekly educational messages using WhatsApp, while the control group received regular care. Results: Statistically, compared with the control group, the diabetes knowledge and self-efficacy of the intervention group increased significantly after the intervention with the WhatsApp application. Conclusion: The WhatsApp application can be effectively used for enhancing diabetes knowledge, self-efficacy and awareness among the Saudi population.
The Saudi population is at high risk of multimorbidity. The risk of these morbidities can be redu... more The Saudi population is at high risk of multimorbidity. The risk of these morbidities can be reduced by identifying common modifiable behavioural risk factors. This study uses statistical and machine learning methods to predict factors for multimorbidity in the Saudi population. Data from 23,098 Saudi residents were extracted from the “Sharik” Health Indicators Surveillance System 2021. Participants were asked about their demographics and health indicators. Binary logistic models were used to determine predictors of multimorbidity. A backpropagation neural network model was further run using the predictors from the logistic regression model. Accuracy measures were checked using training, validation, and testing data. Females and smokers had the highest likelihood of experiencing multimorbidity. Age and fruit consumption also played a significant role in predicting multimorbidity. Regarding model accuracy, both logistic regression and backpropagation algorithms yielded comparable out...
Purpose: This study aims to examine the prevalence of multimorbidity in Saudi Arabia and identify... more Purpose: This study aims to examine the prevalence of multimorbidity in Saudi Arabia and identify the contributing factors. Methods: A population-based cross-sectional study of 23,098 participants was conducted in 2020 across all 13 administrative regions of Saudi Arabia. Univariable and Multivariable logistic regression models were run to measure the effect of modifiable and non-modifiable risk factors on multimorbidity. Results: A total of 23,098 participants from the 13 administrative regions completed the interview. Fifty percent of the participants were female, with a mean of 36.9 years (SD 13.9 years; range: 18—90 years). The majority of participants were Saudi nationals (95.2%). The overall prevalence of multimorbidity in this sample is 23.3%, with no differences between genders. This study has found that consuming vegetables and fruits and smoking (cigarettes, shisha/waterpipe, and electronic cigarettes) were significantly associated with multimorbidity status. It was also f...
The Ebola epidemic in Guinea, Liberia, and Sierra Leone (three of the four states making up the M... more The Ebola epidemic in Guinea, Liberia, and Sierra Leone (three of the four states making up the Mano River Union) is unprecedented in its level and pace and “continues to be diffi cult to bring under control”. Since there is no drug or vaccine of proven effi cacy, most of the eff orts in controlling the disease are directed towards prevention and containm ent. However, these eff orts are frustrated by false rumours, ignorance, and potentially harmful cultural practices. Addressing these frustrations calls for wisdom, pragmatism, and political will. One such example was the involvement of traditional healers in the fight against HIV/AIDS in Africa. The main drivers, operating from the biomedical perspective, were the ministries of health and WHO. Meanwhile, the traditional leaders were operating from a diametrically opposite perspective, yet, the reality called for their collaboration. Borrowing from this example, religious leaders could be involved in the fight against the spread of...
BackgroundChronic kidney disease (CKD) is a public health problem largely caused by diabetes. The... more BackgroundChronic kidney disease (CKD) is a public health problem largely caused by diabetes. The epidemiology of diabetes mellitus–related CKD (CKD-DM) could provide specific support to lessen global, regional, and national CKD burden.MethodsData were derived from the GBD 2019 study, including four measures and age-standardized rates (ASRs). Estimated annual percentage changes and 95% CIs were calculated to evaluate the variation trend of ASRs.ResultsDiabetes caused the majority of new cases and patients with CKD in all regions. All ASRs for type 2 diabetes–related CKD increased over 30 years. Asia and Middle socio-demographic index (SDI) quintile always carried the heaviest burden of CKD-DM. Diabetes type 2 became the second leading cause of CKD and CKD-related death and the third leading cause of CKD-related DALYs in 2019. Type 2 diabetes–related CKD accounted for most of the CKD-DM disease burden. There were 2.62 million incident cases, 134.58 million patients, 405.99 thousand d...
Journal of Taibah University Medical Sciences, 2021
Objectives This research explores the association between variables routinely collected in a heal... more Objectives This research explores the association between variables routinely collected in a health information system and the readmission of patients with type 2 diabetes within 30 days of discharge. Methods This retrospective cohort study was conducted at King Fahd Hospital of the University (KFHU) in Al-Khobar, KSA. The study population comprised patients with type 2 diabetes who were admitted to the hospital from January 2016 to November 2016. Data were obtained from the hospital's information system at KFHU. The association between the readmission of patients with type 2 diabetes and routinely collected health information system variables such as demographics, type of diabetes, length of stay, and discharge type were analyzed. Results A total of 497 cases met the inclusion criteria. Of these, 31 (6.2%) cases were readmitted within 30 days. Type 2 diabetes was the only variable found to be significantly associated with readmission within 30 days (χ2 (1, N = 497) = 6.116, p = 0.0134). Diabetes type (p = 0.0133) and discharge type (p = 0.0403) were the only variables that displayed significance utilizing a logistic regression model. Conclusion Overall, the routinely collected demographic, diagnostic, and administrative variables were found to be poor predictors of 30-day readmission for type 2 diabetes at the institution studied. Nonetheless, the only significant variables in the prediction of 30-day readmission were diabetes type and discharge type. To determine the predictors of readmission, it is recommended that future studies include height and weight to the routinely collected health information system variables. We also suggest that future studies be based on data collected over several years or on pooled data collected from several hospitals.
Approaches to teaching and learning keep on changing continuously as evidenced in the development... more Approaches to teaching and learning keep on changing continuously as evidenced in the development of sub-disciplines dealing with education within the discipline, for example, medical education. This paper brings in another perspective in the search for the ideal teaching and learning approaches. Starting from the Qur’an and the Sunnah, this paper identifies about 20 different aspects of teaching and learning found in these two Islamic sources. These aspects could be grouped into four categories: pre-learning phase and setting the context; personality qualities needed for good teaching and learning relationship; teaching approaches; and lastly, approaches for enhancing the learning process. The paper demonstrates the great potential of the Qur’an and Sunnah for informing on the effective ways for teaching and learning.
The chapter explores the possibility of registering Ebola virus disease (EVD) as a multiple cause... more The chapter explores the possibility of registering Ebola virus disease (EVD) as a multiple cause of death (part of the civil registration/vital statistics (CR/VS) system) in addition to being a notifiable disease (part of the disease surveillance system). The linkage between the two systems is established, followed by a framework showing how each of the systems would work in the ideal situation. A scoring system is developed and used to score each dimension of this ideal system, giving a total score of 23. This tool can be used to assess the extent to which the EVD is registered both as a multiple cause of death and as a notifiable disease in Africa. The application of the tool requires that the Ebola virus disease is coded at the fourth digit ICD-10 level and that multiple causes of death are routinely collected in the first place. The country that is closest to satisfying these criteria is South Africa. The application of the tool to South Africa data showed that South African system was "fair" (between "poor" and "good"). The results are shown, discussed and recommendations are made for improving two systems in Africa.
The subject of mortality is a meeting ground for diverse disciplines, and hence it is not surpris... more The subject of mortality is a meeting ground for diverse disciplines, and hence it is not surprising to see it being approached from remarkably different perspectives. The book has 13 chapters, covering a wide range of topics, using data from different geographic areas. The chapters can be grouped into three broad themes: mortality estimation and projections (chapters 2, 3, and 5), explanation of trends in mortality and causes of death (chapters 4, 8, 9, 11, and 13), and measurement of impact of determinants (chapters 6, 7, 10, and 12). Chapter 1, by Jon Anson and Marc Luy, adequately summarizes all the chapters in the book. It is clear that the aim of the book is to put together 'state of the art' methods used in mortality and morbidity. However, it is in the chapters dealing with mortality estimation and projections that "cutting edge" methods are used. The remaining chapters, interesting as they are, used methods that would fall under "normal science" rather than cutting-edge methods. Chapter 2 is authored by Peter Congdon, a pioneer in the analysis of small area mortality and the author of books on Bayesian statistical modelling. In this chapter, he exploited correlations between adjacent ages and areas with Bayesian modelling and applied it to data of over 3,000 US counties. He found that "whereas there is little gain in life expectancy in the lowest income counties, high income counties showed expectancy improvements exceeding the US average." This new approach is an improvement on standard conventional life table methods used in small area mortality that overlook spatial or age correlations. Chapter 3, by Joroen Spijker, is clearly the most ambitious chapter in the book. He uses data from 21 countries over the period from 1980 to 2000 to model death rates for 11 causes of death. The model used allows for the simulataneous analysis of inter-country and inter-temporal variations in mortality. As a departure from other models based on extrapolation, this model included data on some known socioeconomic determinants of mortality. The model was validated and then used to produce short-term projections of rates due to causes of death. This is a significant contribution in an area that is still in its youthful stage of development. Chapter 4, by Katalin Kovács, thoroughly reviews the different variants of Epidemiological Transition Theory and the Nutritional Transition Theory. Using causes of death data from Hungary, Kovács tries to group the different causes of death in such a way as to allow her to see the role of the different theories in explaining inequalities in mortality between the less educated and the more educated. Her conclusion was that "nutrition transition theory provides a very plausible explanatory framework for the growth of mortality inequalities." Chapter 5, by Sarinapha Vasunilashorrn and others, attempts to predict mortality from profiles of biological risk and performance measures of functioning. They were able to get a rich set of data by linking a national US survey data with the causes of death data contained in the National Death Index.
While internship training is well established for medical records and for healthcare quality impr... more While internship training is well established for medical records and for healthcare quality improvement, it is not quite so for training related to IT/health informatics. A comparison was made on the hospital-based IT/health informatics internship training received by students completing their training at the Imam AbdulRahman Bin Faisal University (IAU) in the Eastern province of Saudi Arabia. The three hospitals studied all have the Joint Commission International accreditation and advanced Electronic Health Record (EHR) systems. Over the period from 2011 to 2015, interns from the IAU prepared 120 reports based on their training at these three hospitals. Data abstraction was done on the internship reports, and the results were summarized and interpreted. The study found wide differences in the training received at these hospitals. The main reason for the differences is whether or not the EHR system used in the hospital was a commercial one or developed in-house. The hospital that h...
More than 70 measures exist for analyzing the binary association of a 2x2 contingency table. Of t... more More than 70 measures exist for analyzing the binary association of a 2x2 contingency table. Of these, only five are used in multiple-cause mortality. The aim of the paper is to answer the question of whether these measures are adequate. Building on comparative reviews of measures of association, the paper identifies three additional measures as suitable candidates. These additional measures, together with the five existing ones, are assessed for their theoretical utility based on seven criteria laid out in the paper. Subsequently, the same measures are applied to South African multiple-cause data that comprises over four million records. The multiple-cause software Cause_limp v1.1 was used to extract the data for the cell entries of the 2x2 contingency table, with diabetes as a multiple-cause and cardiac arrest as a co-morbid condition. The paper concludes that existing measures of multiple-cause mortality need to be supplemented with other measures, in particular the Positive Matc...
Among the several reasons for disease coding, at the minimum, it allows for easy storage and retr... more Among the several reasons for disease coding, at the minimum, it allows for easy storage and retrieval of information. This facilitates the analysis and interpretation of disease-related data. Disease coding allows for standardisation among users and producers and for international comparability. Disease coding also allows for efficiency in billing (Verma and El-Sayed 2008, Thompson & Greenberg 2009). The de-facto standard for disease coding is the WHO family of disease and health related classification of which the core is the International Classification of Diseases (ICD) system (Last 1995). The two ICD versions currently in use are the ninth version (ICD-9) and the tenth version (ICD-10). However ICD-9 is over 30 years old and is no longer supported or maintained by WHO. For this and other reasons, many countries (users) have either moved or planning to move over from ICD-9 to ICD-10 (Prokhorskas 2002). Some other reasons given for the preference of ICD-10 over ICD-9 include the following: 1) the vastly larger number of codes in ICD-10 compared to ICD-9. For mortality coding alone, while ICD-9 has about 4000 unique codes, ICD-10 has about 8000 unique codes. 2) There is higher specificity in ICD-10 compared to ICD-9. 3) ICD-10 is more in line with advancement in medicine (more current) than ICD-9. 4) ICD-10 codes are more in line with changes in health care delivery system. 5) As ICD-10 is alphanumeric, it has room for more codes than the numeric ICD-9. In other words, ICD-10 is more expandable and hence can easily accommodate newer codes in the future (
Journal of Taibah University Medical Sciences, Dec 1, 2021
Objectives This research explores the association between variables routinely collected in a heal... more Objectives This research explores the association between variables routinely collected in a health information system and the readmission of patients with type 2 diabetes within 30 days of discharge. Methods This retrospective cohort study was conducted at King Fahd Hospital of the University (KFHU) in Al-Khobar, KSA. The study population comprised patients with type 2 diabetes who were admitted to the hospital from January 2016 to November 2016. Data were obtained from the hospital's information system at KFHU. The association between the readmission of patients with type 2 diabetes and routinely collected health information system variables such as demographics, type of diabetes, length of stay, and discharge type were analyzed. Results A total of 497 cases met the inclusion criteria. Of these, 31 (6.2%) cases were readmitted within 30 days. Type 2 diabetes was the only variable found to be significantly associated with readmission within 30 days (χ2 (1, N = 497) = 6.116, p = 0.0134). Diabetes type (p = 0.0133) and discharge type (p = 0.0403) were the only variables that displayed significance utilizing a logistic regression model. Conclusion Overall, the routinely collected demographic, diagnostic, and administrative variables were found to be poor predictors of 30-day readmission for type 2 diabetes at the institution studied. Nonetheless, the only significant variables in the prediction of 30-day readmission were diabetes type and discharge type. To determine the predictors of readmission, it is recommended that future studies include height and weight to the routinely collected health information system variables. We also suggest that future studies be based on data collected over several years or on pooled data collected from several hospitals.
The Canadian Journal of Hospital Pharmacy, Oct 3, 2022
Our objective was to assess the effect of implementing an electronic health record (EHR) on surgi... more Our objective was to assess the effect of implementing an electronic health record (EHR) on surgical resident work flow, duty hours, and operative experience at a large teaching hospital. In May 2012, an EHR was put into effect at our institution replacing paper documentation and orders. Resident time to complete patient documentation, average duty hours, and operative experience before EHR and afterward (at 1, 4, 6, 8, and 24 weeks) were surveyed. We obtained 100 per cent response rate from 15 surgical residents at all time intervals. The average time spent documenting before EHR was 9 6 2 minutes per patient document and at Weeks 1, 4, 6, 8, and 24 after EHR implementation was 22 6 10, 15 6 7, 15 6 7, 14 6 8, and 12 6 4 minutes, respectively. Repeated measures analysis of variance demonstrated a difference among the means (P \ 0.0001). Discharge summary and operative note remained significantly longer to complete at Week 24 compared with paper documentation (P \ 0.05). Average resident work hours and operative cases per week before EHR were 77 6 5 hours and 12 6 5 cases, respectively, which were similar at all time points after EHR implementation (P [ 0.05). At 24 weeks after EHR, 74 per cent of residents felt their risk of performing a medical error using electronic documentation and order entry was higher compared with paper charting and orders. Transition to EHR led to a significant doubling in resident time spent performing documentation for each patient. It improved over 6 months after implementation but never reached the pre-EHR baseline for operative notes and discharge summaries. Average resident work hours and case logs remained similar during this transition.
The aim of this study is to evaluate the WhatsApp social networking application for improving kno... more The aim of this study is to evaluate the WhatsApp social networking application for improving knowledge, self-efficacy and awareness about diabetes management. Methodology: The study was conducted with intervention and control groups at Teaching Hospital in Al-Khobar, Saudi Arabia. The intervention group received weekly educational messages using WhatsApp, while the control group received regular care. Results: Statistically, compared with the control group, the diabetes knowledge and self-efficacy of the intervention group increased significantly after the intervention with the WhatsApp application. Conclusion: The WhatsApp application can be effectively used for enhancing diabetes knowledge, self-efficacy and awareness among the Saudi population.
The Saudi population is at high risk of multimorbidity. The risk of these morbidities can be redu... more The Saudi population is at high risk of multimorbidity. The risk of these morbidities can be reduced by identifying common modifiable behavioural risk factors. This study uses statistical and machine learning methods to predict factors for multimorbidity in the Saudi population. Data from 23,098 Saudi residents were extracted from the “Sharik” Health Indicators Surveillance System 2021. Participants were asked about their demographics and health indicators. Binary logistic models were used to determine predictors of multimorbidity. A backpropagation neural network model was further run using the predictors from the logistic regression model. Accuracy measures were checked using training, validation, and testing data. Females and smokers had the highest likelihood of experiencing multimorbidity. Age and fruit consumption also played a significant role in predicting multimorbidity. Regarding model accuracy, both logistic regression and backpropagation algorithms yielded comparable out...
Purpose: This study aims to examine the prevalence of multimorbidity in Saudi Arabia and identify... more Purpose: This study aims to examine the prevalence of multimorbidity in Saudi Arabia and identify the contributing factors. Methods: A population-based cross-sectional study of 23,098 participants was conducted in 2020 across all 13 administrative regions of Saudi Arabia. Univariable and Multivariable logistic regression models were run to measure the effect of modifiable and non-modifiable risk factors on multimorbidity. Results: A total of 23,098 participants from the 13 administrative regions completed the interview. Fifty percent of the participants were female, with a mean of 36.9 years (SD 13.9 years; range: 18—90 years). The majority of participants were Saudi nationals (95.2%). The overall prevalence of multimorbidity in this sample is 23.3%, with no differences between genders. This study has found that consuming vegetables and fruits and smoking (cigarettes, shisha/waterpipe, and electronic cigarettes) were significantly associated with multimorbidity status. It was also f...
The Ebola epidemic in Guinea, Liberia, and Sierra Leone (three of the four states making up the M... more The Ebola epidemic in Guinea, Liberia, and Sierra Leone (three of the four states making up the Mano River Union) is unprecedented in its level and pace and “continues to be diffi cult to bring under control”. Since there is no drug or vaccine of proven effi cacy, most of the eff orts in controlling the disease are directed towards prevention and containm ent. However, these eff orts are frustrated by false rumours, ignorance, and potentially harmful cultural practices. Addressing these frustrations calls for wisdom, pragmatism, and political will. One such example was the involvement of traditional healers in the fight against HIV/AIDS in Africa. The main drivers, operating from the biomedical perspective, were the ministries of health and WHO. Meanwhile, the traditional leaders were operating from a diametrically opposite perspective, yet, the reality called for their collaboration. Borrowing from this example, religious leaders could be involved in the fight against the spread of...
BackgroundChronic kidney disease (CKD) is a public health problem largely caused by diabetes. The... more BackgroundChronic kidney disease (CKD) is a public health problem largely caused by diabetes. The epidemiology of diabetes mellitus–related CKD (CKD-DM) could provide specific support to lessen global, regional, and national CKD burden.MethodsData were derived from the GBD 2019 study, including four measures and age-standardized rates (ASRs). Estimated annual percentage changes and 95% CIs were calculated to evaluate the variation trend of ASRs.ResultsDiabetes caused the majority of new cases and patients with CKD in all regions. All ASRs for type 2 diabetes–related CKD increased over 30 years. Asia and Middle socio-demographic index (SDI) quintile always carried the heaviest burden of CKD-DM. Diabetes type 2 became the second leading cause of CKD and CKD-related death and the third leading cause of CKD-related DALYs in 2019. Type 2 diabetes–related CKD accounted for most of the CKD-DM disease burden. There were 2.62 million incident cases, 134.58 million patients, 405.99 thousand d...
Journal of Taibah University Medical Sciences, 2021
Objectives This research explores the association between variables routinely collected in a heal... more Objectives This research explores the association between variables routinely collected in a health information system and the readmission of patients with type 2 diabetes within 30 days of discharge. Methods This retrospective cohort study was conducted at King Fahd Hospital of the University (KFHU) in Al-Khobar, KSA. The study population comprised patients with type 2 diabetes who were admitted to the hospital from January 2016 to November 2016. Data were obtained from the hospital's information system at KFHU. The association between the readmission of patients with type 2 diabetes and routinely collected health information system variables such as demographics, type of diabetes, length of stay, and discharge type were analyzed. Results A total of 497 cases met the inclusion criteria. Of these, 31 (6.2%) cases were readmitted within 30 days. Type 2 diabetes was the only variable found to be significantly associated with readmission within 30 days (χ2 (1, N = 497) = 6.116, p = 0.0134). Diabetes type (p = 0.0133) and discharge type (p = 0.0403) were the only variables that displayed significance utilizing a logistic regression model. Conclusion Overall, the routinely collected demographic, diagnostic, and administrative variables were found to be poor predictors of 30-day readmission for type 2 diabetes at the institution studied. Nonetheless, the only significant variables in the prediction of 30-day readmission were diabetes type and discharge type. To determine the predictors of readmission, it is recommended that future studies include height and weight to the routinely collected health information system variables. We also suggest that future studies be based on data collected over several years or on pooled data collected from several hospitals.
Approaches to teaching and learning keep on changing continuously as evidenced in the development... more Approaches to teaching and learning keep on changing continuously as evidenced in the development of sub-disciplines dealing with education within the discipline, for example, medical education. This paper brings in another perspective in the search for the ideal teaching and learning approaches. Starting from the Qur’an and the Sunnah, this paper identifies about 20 different aspects of teaching and learning found in these two Islamic sources. These aspects could be grouped into four categories: pre-learning phase and setting the context; personality qualities needed for good teaching and learning relationship; teaching approaches; and lastly, approaches for enhancing the learning process. The paper demonstrates the great potential of the Qur’an and Sunnah for informing on the effective ways for teaching and learning.
The chapter explores the possibility of registering Ebola virus disease (EVD) as a multiple cause... more The chapter explores the possibility of registering Ebola virus disease (EVD) as a multiple cause of death (part of the civil registration/vital statistics (CR/VS) system) in addition to being a notifiable disease (part of the disease surveillance system). The linkage between the two systems is established, followed by a framework showing how each of the systems would work in the ideal situation. A scoring system is developed and used to score each dimension of this ideal system, giving a total score of 23. This tool can be used to assess the extent to which the EVD is registered both as a multiple cause of death and as a notifiable disease in Africa. The application of the tool requires that the Ebola virus disease is coded at the fourth digit ICD-10 level and that multiple causes of death are routinely collected in the first place. The country that is closest to satisfying these criteria is South Africa. The application of the tool to South Africa data showed that South African system was "fair" (between "poor" and "good"). The results are shown, discussed and recommendations are made for improving two systems in Africa.
The subject of mortality is a meeting ground for diverse disciplines, and hence it is not surpris... more The subject of mortality is a meeting ground for diverse disciplines, and hence it is not surprising to see it being approached from remarkably different perspectives. The book has 13 chapters, covering a wide range of topics, using data from different geographic areas. The chapters can be grouped into three broad themes: mortality estimation and projections (chapters 2, 3, and 5), explanation of trends in mortality and causes of death (chapters 4, 8, 9, 11, and 13), and measurement of impact of determinants (chapters 6, 7, 10, and 12). Chapter 1, by Jon Anson and Marc Luy, adequately summarizes all the chapters in the book. It is clear that the aim of the book is to put together 'state of the art' methods used in mortality and morbidity. However, it is in the chapters dealing with mortality estimation and projections that "cutting edge" methods are used. The remaining chapters, interesting as they are, used methods that would fall under "normal science" rather than cutting-edge methods. Chapter 2 is authored by Peter Congdon, a pioneer in the analysis of small area mortality and the author of books on Bayesian statistical modelling. In this chapter, he exploited correlations between adjacent ages and areas with Bayesian modelling and applied it to data of over 3,000 US counties. He found that "whereas there is little gain in life expectancy in the lowest income counties, high income counties showed expectancy improvements exceeding the US average." This new approach is an improvement on standard conventional life table methods used in small area mortality that overlook spatial or age correlations. Chapter 3, by Joroen Spijker, is clearly the most ambitious chapter in the book. He uses data from 21 countries over the period from 1980 to 2000 to model death rates for 11 causes of death. The model used allows for the simulataneous analysis of inter-country and inter-temporal variations in mortality. As a departure from other models based on extrapolation, this model included data on some known socioeconomic determinants of mortality. The model was validated and then used to produce short-term projections of rates due to causes of death. This is a significant contribution in an area that is still in its youthful stage of development. Chapter 4, by Katalin Kovács, thoroughly reviews the different variants of Epidemiological Transition Theory and the Nutritional Transition Theory. Using causes of death data from Hungary, Kovács tries to group the different causes of death in such a way as to allow her to see the role of the different theories in explaining inequalities in mortality between the less educated and the more educated. Her conclusion was that "nutrition transition theory provides a very plausible explanatory framework for the growth of mortality inequalities." Chapter 5, by Sarinapha Vasunilashorrn and others, attempts to predict mortality from profiles of biological risk and performance measures of functioning. They were able to get a rich set of data by linking a national US survey data with the causes of death data contained in the National Death Index.
While internship training is well established for medical records and for healthcare quality impr... more While internship training is well established for medical records and for healthcare quality improvement, it is not quite so for training related to IT/health informatics. A comparison was made on the hospital-based IT/health informatics internship training received by students completing their training at the Imam AbdulRahman Bin Faisal University (IAU) in the Eastern province of Saudi Arabia. The three hospitals studied all have the Joint Commission International accreditation and advanced Electronic Health Record (EHR) systems. Over the period from 2011 to 2015, interns from the IAU prepared 120 reports based on their training at these three hospitals. Data abstraction was done on the internship reports, and the results were summarized and interpreted. The study found wide differences in the training received at these hospitals. The main reason for the differences is whether or not the EHR system used in the hospital was a commercial one or developed in-house. The hospital that h...
More than 70 measures exist for analyzing the binary association of a 2x2 contingency table. Of t... more More than 70 measures exist for analyzing the binary association of a 2x2 contingency table. Of these, only five are used in multiple-cause mortality. The aim of the paper is to answer the question of whether these measures are adequate. Building on comparative reviews of measures of association, the paper identifies three additional measures as suitable candidates. These additional measures, together with the five existing ones, are assessed for their theoretical utility based on seven criteria laid out in the paper. Subsequently, the same measures are applied to South African multiple-cause data that comprises over four million records. The multiple-cause software Cause_limp v1.1 was used to extract the data for the cell entries of the 2x2 contingency table, with diabetes as a multiple-cause and cardiac arrest as a co-morbid condition. The paper concludes that existing measures of multiple-cause mortality need to be supplemented with other measures, in particular the Positive Matc...
Among the several reasons for disease coding, at the minimum, it allows for easy storage and retr... more Among the several reasons for disease coding, at the minimum, it allows for easy storage and retrieval of information. This facilitates the analysis and interpretation of disease-related data. Disease coding allows for standardisation among users and producers and for international comparability. Disease coding also allows for efficiency in billing (Verma and El-Sayed 2008, Thompson & Greenberg 2009). The de-facto standard for disease coding is the WHO family of disease and health related classification of which the core is the International Classification of Diseases (ICD) system (Last 1995). The two ICD versions currently in use are the ninth version (ICD-9) and the tenth version (ICD-10). However ICD-9 is over 30 years old and is no longer supported or maintained by WHO. For this and other reasons, many countries (users) have either moved or planning to move over from ICD-9 to ICD-10 (Prokhorskas 2002). Some other reasons given for the preference of ICD-10 over ICD-9 include the following: 1) the vastly larger number of codes in ICD-10 compared to ICD-9. For mortality coding alone, while ICD-9 has about 4000 unique codes, ICD-10 has about 8000 unique codes. 2) There is higher specificity in ICD-10 compared to ICD-9. 3) ICD-10 is more in line with advancement in medicine (more current) than ICD-9. 4) ICD-10 codes are more in line with changes in health care delivery system. 5) As ICD-10 is alphanumeric, it has room for more codes than the numeric ICD-9. In other words, ICD-10 is more expandable and hence can easily accommodate newer codes in the future (
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