The analytics and decision support in health
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Running head: ANALYTICS AND DECISION SUPPORT IN HEALTH ORGANISATION
Analytics and Decision Support in Health Organisation
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Analytics and Decision Support in Health Organisation
Name of the Student:
Name of the University:
Author Note:
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1ANALYTICS AND DECISION SUPPORT IN HEALTH ORGANISATION
Table of Contents
Introduction................................................................................................................................2
Importance of analytics and decision support in health care organisations...............................2
Reason of using charts, graphs, and tables.................................................................................2
Bar Chart................................................................................................................................2
Pie Chart.................................................................................................................................3
Tables.....................................................................................................................................4
Conclusion..................................................................................................................................5
Reference....................................................................................................................................6
Table of Contents
Introduction................................................................................................................................2
Importance of analytics and decision support in health care organisations...............................2
Reason of using charts, graphs, and tables.................................................................................2
Bar Chart................................................................................................................................2
Pie Chart.................................................................................................................................3
Tables.....................................................................................................................................4
Conclusion..................................................................................................................................5
Reference....................................................................................................................................6
2ANALYTICS AND DECISION SUPPORT IN HEALTH ORGANISATION
Introduction
The scientific process to discover and communicate the significant patterns from the
data is called Analytics. The decision support system is the application which helps the
healthcare provider to analyse the data in order to make a significant decision to improve the
patient care. In this paper, the discussion is about reason behind using analytics and decision
support in health care organisations.
Importance of analytics and decision support in health care organisations
The analytics and decision support assists the clinicians. This enables the patient data
to analyse and to use the information. This helps the healthcare providers to assist in forming
the diagnosis. This also can be used in diagnosis and improvement of care by elimination of
unnecessary testing, enhancement of patient’s safety and keeping away the potential dangers
and cost issues.
Reason of using charts, graphs, and tables
There are a number of types of charts, graphs and tables and these all have their own
characteristic. Depending on these characteristics charts, graphs and tables are used to explain
unique cases. Some of them are explained in the below section:
Bar Chart
The bar chart presents the categorical variables on the vertical axis and values on the
horizontal axis. The length of the bar are compared to identify the better category. For
example, the below bar chart is presented to compare the death rate for coronary artery
bypass graft. The lengthiest bar presents the highest number of deaths in that particular
hospital.
Introduction
The scientific process to discover and communicate the significant patterns from the
data is called Analytics. The decision support system is the application which helps the
healthcare provider to analyse the data in order to make a significant decision to improve the
patient care. In this paper, the discussion is about reason behind using analytics and decision
support in health care organisations.
Importance of analytics and decision support in health care organisations
The analytics and decision support assists the clinicians. This enables the patient data
to analyse and to use the information. This helps the healthcare providers to assist in forming
the diagnosis. This also can be used in diagnosis and improvement of care by elimination of
unnecessary testing, enhancement of patient’s safety and keeping away the potential dangers
and cost issues.
Reason of using charts, graphs, and tables
There are a number of types of charts, graphs and tables and these all have their own
characteristic. Depending on these characteristics charts, graphs and tables are used to explain
unique cases. Some of them are explained in the below section:
Bar Chart
The bar chart presents the categorical variables on the vertical axis and values on the
horizontal axis. The length of the bar are compared to identify the better category. For
example, the below bar chart is presented to compare the death rate for coronary artery
bypass graft. The lengthiest bar presents the highest number of deaths in that particular
hospital.
3ANALYTICS AND DECISION SUPPORT IN HEALTH ORGANISATION
Figure 1: Death rate for coronary artery bypass graft (ahrq.gov. 2019)
Pie Chart
Pie chart presents the share of the subcategories of the categorical variable. It
visualises the percentage or the share of the subcategories by the area of the circle. For an
example, the below pie chart presents the patients hospitalised with any-listed MRSA
Diagnosis. The patients are divided according to the total number of impatient with a MRSA
diagnosis. The subcategory covers the most area has the highest percentage of he share. In
this example, there are 3 categories which are 1 hospitalisation, 2 hospitalisation and 3
hospitalisation. In this case, the highest percentage is 82.8% for the 1 hospitalisation which
means the highest percentage is for the single number of impatient with a MRSA diagnosis.
Figure 1: Death rate for coronary artery bypass graft (ahrq.gov. 2019)
Pie Chart
Pie chart presents the share of the subcategories of the categorical variable. It
visualises the percentage or the share of the subcategories by the area of the circle. For an
example, the below pie chart presents the patients hospitalised with any-listed MRSA
Diagnosis. The patients are divided according to the total number of impatient with a MRSA
diagnosis. The subcategory covers the most area has the highest percentage of he share. In
this example, there are 3 categories which are 1 hospitalisation, 2 hospitalisation and 3
hospitalisation. In this case, the highest percentage is 82.8% for the 1 hospitalisation which
means the highest percentage is for the single number of impatient with a MRSA diagnosis.
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4ANALYTICS AND DECISION SUPPORT IN HEALTH ORGANISATION
Figure 2: Percentage distribution of the number of MRSA-associated hospital stays among
patients with at least one MRSA admission in California, 2013 (Sutton & Steiner, 2016)
Tables
There are different types of table depending on the test or presentation of statistics.
For example, ANOVA table, result of t-test and z-test and again tables can be created
according to the need of statistics for example summary stats where mean, median, mode,
range, quartiles, skewness, kurtosis and standard deviation are added and subtracted
Figure 2: Percentage distribution of the number of MRSA-associated hospital stays among
patients with at least one MRSA admission in California, 2013 (Sutton & Steiner, 2016)
Tables
There are different types of table depending on the test or presentation of statistics.
For example, ANOVA table, result of t-test and z-test and again tables can be created
according to the need of statistics for example summary stats where mean, median, mode,
range, quartiles, skewness, kurtosis and standard deviation are added and subtracted
5ANALYTICS AND DECISION SUPPORT IN HEALTH ORGANISATION
according to the need. In the below table, clinical condition associated with MRSA is
presented across the categories and subcategories.
Table 1: Characteristics of patients with one or more MRSA hospitalizations by clinical
condition associated with MRSA in California, 2013 (Sutton & Steiner, 2016)
Conclusion
With the help of these charts and tables, at a glance one can differentiate and identify
which one is better or which needs to be chosen according to the decision rule. The bar chart
easily shows the highest and lowest number of deaths in that particular hospital with the help
of the length of the bar. Similarly, the pie hart and tables do.
according to the need. In the below table, clinical condition associated with MRSA is
presented across the categories and subcategories.
Table 1: Characteristics of patients with one or more MRSA hospitalizations by clinical
condition associated with MRSA in California, 2013 (Sutton & Steiner, 2016)
Conclusion
With the help of these charts and tables, at a glance one can differentiate and identify
which one is better or which needs to be chosen according to the decision rule. The bar chart
easily shows the highest and lowest number of deaths in that particular hospital with the help
of the length of the bar. Similarly, the pie hart and tables do.
6ANALYTICS AND DECISION SUPPORT IN HEALTH ORGANISATION
Reference
ahrq.gov. (2019). 1HOSPITAL QUALITY MODEL REPORT: COMPOSITES. Retrieved 27
August 2019, from
http://qualityindicators.ahrq.gov/Downloads/Modules/QI_Reporting/Model_Report_C
omposite.pdf
Caja, G., Castro-Costa, A., & Knight, C. H. (2016). Engineering to support wellbeing of dairy
animals. Journal of Dairy Research, 83(2), 136-147.
Stellamanns, J., Ruetters, D., Dahal, K., Schillmoeller, Z., & Huebner, J. (2017). Visualizing
risks in cancer communication: a systematic review of computer-supported visual
aids. Patient education and counseling, 100(8), 1421-1431.
Sutton, J., & Steiner, C. (2016). Hospital-, Health Care-, and Community-Acquired MRSA:
Estimates From California Hospitals, 2013. Healthcare Cost And Utilization Project
(HCUP) Statistical Briefs.
Reference
ahrq.gov. (2019). 1HOSPITAL QUALITY MODEL REPORT: COMPOSITES. Retrieved 27
August 2019, from
http://qualityindicators.ahrq.gov/Downloads/Modules/QI_Reporting/Model_Report_C
omposite.pdf
Caja, G., Castro-Costa, A., & Knight, C. H. (2016). Engineering to support wellbeing of dairy
animals. Journal of Dairy Research, 83(2), 136-147.
Stellamanns, J., Ruetters, D., Dahal, K., Schillmoeller, Z., & Huebner, J. (2017). Visualizing
risks in cancer communication: a systematic review of computer-supported visual
aids. Patient education and counseling, 100(8), 1421-1431.
Sutton, J., & Steiner, C. (2016). Hospital-, Health Care-, and Community-Acquired MRSA:
Estimates From California Hospitals, 2013. Healthcare Cost And Utilization Project
(HCUP) Statistical Briefs.
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