92917 Using Health Care Data For Decision Making

92917 Using Health Care Data For Decision Making

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92917 Using Health Care Data For Decision Making

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92917 Using Health Care Data For Decision Making

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Course Code: 92917
University: University Of Technology Sydney

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Country: Australia

Question

You have been engaged as a consultant to the Local Health District (LHD). The LHD governing council requires you to develop a report based on data from ‘UTS Hospital’ (an Australian public hospital situated in New South Wales) to address issues outlined in the topic below . The report must contain a data analysis strategy, the analysis, and appropriate reference to the literature. Note that the governing council is primarily interested in the analysis, and expects clear recommendations that apply to, and are implementable by, ‘UTS Hospital’.

Answer

Using Health Care Data 
Introduction
One of the most common chronic diseases of the respiratory system is bronchial asthma. This is responsible for affecting almost 300 million people on a worldwide basis. The guidelines of the Global Initiative for Asthma (GINA) presents that the prevalence of asthma is estimated to be 1% to 18% (Wong et al. 2013). Bronchitis is seen to be a very crucial health problem for several people therefore, it is required to understand the problem and the process by which its prevalence can be reduced in our societies. Whereas in Asthma the airways become narrow and often shows swelling  to produce some extra mucus. In  Asthma, breathing process become very difficult and may trigger coughing,  shortness of breath and sneezing (De Marco et al. 2013). In  Australia, it is seen that many of the Australian citizens are  suffering from bronchitis and asthma.
In the present study, the dataset obtained from the UTS hospital showed that the several patients were admitted in the hospital who were suffering from bronchitis and asthma. The affected population consisted of both older and the younger population, and females and males and they are  admitted in this hospital due to the problem of asthma and bronchitis. Therefore there two disorders are presented to be serious problems in our societies and there is specific needs to study in detail to know how the problems  can be lowered in our societies. The aim of the paper is to prepare a comprehensive report that will entail a specific analysis of the patients with asthma and bronchitis in UTS Hospital, and this report will help to take  some measures which can be used to rectify  these health problems. This report will help to answer the following research questions which are as follows:
What is the prevalence rate  of bronchitis and asthma in UTS Hospital?
Method that can be used to reduce the cases of bronchitis and asthma in our societies?
Background
A study showed that during the second half of the past century the prevalence of asthma and allergic diseases increased considerably in most developed countries. Additionally in the recent times asthma and allergic diseases are the most common chronic non-communicable diseases among children, teenagers and adults up to middle-age (Accordini et al. 2015). Over the past decades, the prevalence of asthma has increased also in developing countries.  Studies have shown that there are prevalence of mainly two types of bronchitis that include chronic bronchitis and acute bronchitis. Acute bronchitis improves and mostly lasts  for  7 to 10 days and there is no severe  effects. However, the patients can have a  long- lasting cough that may last for two weeks (Varmaghani et al. 2016). Chronic bronchitis on the other hand is most of the time caused mainly due to smoking. Several symptoms are associated with bronchitis that  include serious coughs where the patients  may have thick mucus in their coughs, discomfort in chest and along with this feeling of shortness in breathing , tiredness. Studies show that this is a very crucial condition for the people of Australia and even more prevalent in the indigenous people of Australia (Backman et al. 2014). According to the reports chronic bronchitis is quite common in the regular smoker. In Australia, 18% of male smokers and 14% of female smoker are suffering from chronic bronchitis. In case of non-smoker people the number is 7% for the male population and 6% for the female population (Tai et al. 2014). This puts forward the fact that the individuals who are smokers mostly suffer from chronic bronchitis in comparison to those who are non-smokers.
On the other, another  major issue by which  most of the Australians are  suffering from is Asthma. Although asthma can never be completely cured, however the signs and symptoms of asthma can be properly controlled. Several researches have shown that one out of 9 Australian citizens, is suffering from asthma and that makes total number  of about 2.5 million people of total population having  asthma. The study also showed  that asthma is more common to the males of  specific age group(age between 0 and 14 years) and more common to the females with age group of  15 years and above (Brozek et al. 2015).  It is see that the rate  of asthma disease  is much higher to the indigenous Australians whereas the non-indigenous Australians are less prone to the disease  and the number of Asthma affected indigenous Australians is almost double in comparison to  the number of the non-indigenous affected  Australians. The prevalence rate  is higher in the lower socioeconomic areas whereas the rate is quite lower in  comparatively higher socioeconomic areas. Generally, we can say that asthma is a alarming health issue  in Australia and a huge amount of money is spent every year trying to reduce this problem (Islam et al. 2014).
As discussed above, asthma and bronchitis are key  health issues that affecting many Australians and many people worldwide . There are various studies that have been done to address Asthma , and some measures also have been planned on how these diseases can be minimized. However, there are various large gap regarding research and circulating awareness about these diseases to all the citizens  of Australia. However ,Many people don’t have adequate  information about those diseases and how they also don’t know about the prevention policy, and that’s  the key reason  why the prevalence rate is so high in the people (Toelle et al., 2013). In addition to this, the available information is so inadequate and there is no detail way out  of how these diseases can be rectified completely, and for this reason ,we shall come up with some implications that can help to improve the methods of addressing  these diseases and also to  prevent those diseases in Australian societies.
Method
The UTS Hospital’s data was analysed in this section in order to access and address the prevalence of asthma and bronchitis in the hospital setting. The methodology implemented for this research uses the pivot tables which helps to sort the data, as the data set available is quite large in size. The pivot table not only sorts the data but also analyses it is able to summarize the available data along with recognizing it through segregating it into data tables and spread sheets. The variables provided AR-DRGs E69A, & E69B, were analyzed and their profiles were compared using the pivot table in the excel sheet.
From the comparison of the data of the variables, it was acquired that it was the female patients who were suffering and had to spend more time in the hospital in comparison to the male patients suffering from bronchitis. Several other observations can be made from the pivot table, which are represented using the bar graphs and tables, which helps us to understand to the prevalence of bronchitis and asthma in UTS Hospital and the entire of Australia.
Results
The profile of the patients in AR-DRGs E69A, & E69B are as follows:
AR-DRGs E69A

AR DRG_v6_Description

Bronchitis and Asthma without Complications

AMOSpecialty

General medicine

Gender

Female

Age

53

Marital Status

Married

LOS

22

Discharge Intention

Statistical discharge

Service Category

acute

ICU Hours

married

Separation Mode

Discharge by Hospital

Financial Class

Private – single room overnight

Mech Vent Hrs

0

Country of Birth

Australia

IndigenousStatus

Other

EmergencyStatus

NA

Principal Diagnosis

J46

Secondary Diagnosis

G72.2, F41.2, R25.2, K52.9, R40.0

AR-DRGs E69B

AR DRG_v6_Description

Bronchitis and Asthma without Complications

AMOSpecialty

General medicine

Gender

Female

Age

70

Marital Status

Divorced

LOS

20

Discharge Intention

Overnight

Service Category

acute

ICU Hours

married

Separation Mode

Discharge by Hospital

Financial Class

Public Patient – general & Psych

Mech Vent Hrs

0

Country of Birth

USA

IndigenousStatus

Other

EmergencyStatus

NA

Principal Diagnosis

J45.9

Secondary Diagnosis

J22, G47.32, K21.9, R13

The diagnosis of the first patient shows that the patient is suffering from the following symptoms of acute severe asthma (J46). This is the primary diagnosis. The secondary diagnosis involves myopathy due to other toxic agents, mixed anxiety and depressive disorder, Non-infective gastroenteritis and colitis, unspecified and Somnolence.
The diagnosis of the second patient shows the primary diagnosis to be other and unspecified asthma. The secondary diagnosis involves unspecified acute lower respiratory infection, high altitude periodic breathing, gastro-esophageal reflux disease and dysphagia.
On comparison of the variables it can be seen that the first variable is for a patient who has no complications and then second is for patient who has complication related to bronchitis and asthma. Both of the patients are females however one of them is an older adult. The patient having complications is an indigenous individual whereas the non-indigenous individual is without complications.
On comparison of the variables of AR-DRGs E69A, & E69B, it was deduced from the pivot table show that the total length of stay (LOS) of female patients is 240 hours while the LOS of male patients is 153 hours. Additionally it was deduced that the average total stay in the UTS hospital of the female patient and the male patient was 393 hours. It can also be mentioned that since the LOS of the male patient was less, therefore male patients spend fewer hours in UTS hospital, however it was seen that the male patients spend more hours in the ICU. The pivot table shows that the ICU hours of male patients are 103 hours while the ICU hours of female patients are 63 hours. Observations were also made from the pivot table that revealed that bronchitis and asthma are widely prevalent in the people whose relationship status is single people in comparison to those who are married. The analysis of the pivot tables, showed that the LOS of the single people was higher than that of married people. While the statistics of males alone were considered, it was seen that the LOS of single men was 73 hours while that of married men was 66 hours. The pivot table also showed that most of the patients who are  suffering from bronchitis and asthma were public patients who were general and Psych. They can be classified as the people belonging to the lower economical classes.

Gender

LOS in hours

Male

153

Female

240

The bar graph above clearly shows that the ICU hours of the male patients are more than the ICU hours of the female patients.

Gender

ICU hours

Male

103

Female

63

From the pivot table, we can see that the single people had longer LOS than the married people. From the bar graph, it’s clear that the LOS of the single men suffering from bronchitis and asthma is longer than that of the married men.

Marital status of the male patients

LOS in hours

Single

73

Married

66

Discussion
From the results acquired from the given dataset of UTS hospital, it was inferred that the LOS of the female patients was longer in comparison to the male patients. However the ICU hours of the male patients were longer than the female patients even though their LOS were longer. This might be because the female individuals possess a stronger immunity in comparison to the males which acts as a reason that why in spite of being affected by bronchitis and asthma, the health conditions if the female patients do not worsen to that extend where they might be required to be admitted to the ICU for longer periods of time (Backman et al. 2014).
Another factor that was emphasised from the results was that single patients have longer LOS than married patients. One of the major factor which could contribute to these results is the fact that the number of single people who smoke and who take other drugs is generally higher than that of the married people (Lundbäck et al. 2016). From this it can be understood that the prevalence of bronchitis and asthma is higher in the single people.
Another observation deduced from the results was that the disorder was mostly prevalent in the native Australians that is the indigenous people is mostly associated with the prevalence of bronchitis and asthma. This might be because the genes of the indigenous are more prone to the disease as compared to the other Australians. The genes are involved in determining the immunity of the systems (Varmaghani et al. 2016).
Recommendations
There were various limitations present in the research included that the data presented was not quite comprehensive and the data was quite complex hence it was difficult to analyse the given data. Additionally very less amount of literature was present regarding the current trends of bronchitis and asthma in Australia hence no such reason was present to fully explain the prevalent situation in the UTS hospital.
The recommendations that can be presented regarding the prevalent situation includes that the individuals should avoid taking drugs and reduce smoking in order to reduce the risk of the disease. It is required for the general public to be more aware of the prevalence of the disease in order to reduce the risks. It might be also recommended that the individuals undergo regular checkups more often in order to monitor their health conditions and take appropriate actions if required.
Conclusion
From the entire project, we can see that bronchitis and asthma are major health problems which affect many people in Australia. The prevalence of these diseases varies depending on various factors as we have seen in the analysis. These diseases are serious health problems and need to be addressed and prevented using the measures we have discussed in the recommendations section, and sick people need to go to hospitals to be treated as early as possible before their health conditions can worsen.
References
Accordini, S., Corsico, A. G., Calciano, L., Bono, R., Cerveri, I., Fois, A., … and De Marco, R. 2015. The impact of asthma, chronic bronchitis and allergic rhinitis on all-cause hospitalizations and limitations in daily activities: a population-based observational study. BMC pulmonary medicine, 15(1), 10.
Backman, H., Hedman, L., Jansson, S.A., Lindberg, A., Lundbäck, B. and Rönmark, E., 2014. Prevalence trends in respiratory symptoms and asthma in relation to smoking-two cross-sectional studies ten years apart among adults in northern Sweden. World Allergy Organization Journal, 7(1), p.1.
Backman, H., Hedman, L., Jansson, S.A., Lindberg, A., Lundbäck, B. and Rönmark, E., 2014. Prevalence trends in respiratory symptoms and asthma in relation to smoking-two cross-sectional studies ten years apart among adults in northern Sweden. World Allergy Organization Journal, 7(1), p.1.
Brozek, G., Lawson, J., Szumilas, D. and Zejda, J., 2015. Increasing prevalence of asthma, respiratory symptoms, and allergic diseases: Four repeated surveys from 1993-2014. Respiratory medicine, 109(8), pp.982-990.
De Marco, R., Pesce, G., Marcon, A., Accordini, S., Antonicelli, L., Bugiani, M., Casali, L., Ferrari, M., Nicolini, G., Panico, M.G. and Pirina, P., 2013. The coexistence of asthma and chronic obstructive pulmonary disease (COPD): prevalence and risk factors in young, middle-aged and elderly people from the general population. PloS one, 8(5), p.e62985.
Islam, M.M., Valderas, J.M., Yen, L., Dawda, P., Jowsey, T. and McRae, I.S., 2014. Multimorbidity and comorbidity of chronic diseases among the senior Australians: prevalence and patterns. PloS one, 9(1), p.e83783.
Lundbäck, B., Backman, H., Lötvall, J. and Rönmark, E., 2016. Is asthma prevalence still increasing?. Expert review of respiratory medicine, 10(1), pp.39-51.
Network, G.A., 2014. The global asthma report 2014. Auckland, New Zealand, 769.
Perret, J.L., Bui, D.S. and Dharmage, S.C., 2018. Chronic Asthma and Bronchitis without Persistent Airflow Limitation May Have Been Misclassified as COPD Using Administrative Data. Annals of the American Thoracic Society, 2(1), pp.8-20.
Ritz, T., Rosenfield, D., Steele, A.M., Millard, M.W. and Meuret, A.E., 2014. Controlling asthma by training of Capnometry-Assisted Hypoventilation (CATCH) vs. slow breathing: a randomized controlled trial. Chest, 146(5), pp.1237-1247.
Rolfes, T., Roth, J., and Schnotz, W., 2018. Effects of Tables, Bar Charts, and Graphs on Solving Function Tasks. Journal für Mathematik-Didaktik, 39(1), pp.97-125
Schubert, J., Kruavit, A., Mehra, S., Wasgewatta, S., Chang, A.B. and Heraganahally, S., 2018. Prevalence and nature of lung function abnormalities among indigenous Australians referred to specialist respiratory outreach clinics in the Northern Territory. Internal medicine journal, 1(2), pp.2-11.
Smith, S.M., Fahey, T., Smucny, J. and Becker, L.A., 2017. Antibiotics for acute bronchitis. Cochrane Database of Systematic Reviews, 2(6), pp.2-5.
Stout, J.W., White, L.C., Redding, G.J., Morray, B.H., Martinez, P.E. and Gergen, P.J., 2016. Differences in asthma prevalence between samples of American Indian and Alaska Native children. Public Health Reports.
Tai, A., Tran, H., Roberts, M., Clarke, N., Wilson, J. and Robertson, C.F., 2014. The association between childhood asthma and adult chronic obstructive pulmonary disease. Thorax, 69(9), pp.805-810.
Tai, A., Tran, H., Roberts, M., Clarke, N., Wilson, J. and Robertson, C.F., 2014. The association between childhood asthma and adult chronic obstructive pulmonary disease. Thorax, 69(9), pp.805-810.
Toelle, B.G., Xuan, W., Bird, T.E., Abramson, M.J., Atkinson, D.N., Burton, D.L., James, A.L., Jenkins, C.R., Johns, D.P., Maguire, G.P. and Musk, A.W., 2013. Respiratory symptoms and illness in older Australians: the Burden of Obstructive Lung Disease (BOLD) study. Med J Aust, 198(3), pp.144-148.
Varmaghani, M., Farzadfar, F., Sharifi, F., Rashidian, A., Moin, M., Moradi-Lakeh, M., Rahimzadeh, S., saeedi Moghaddam, S. and Kebriaeezadeh, A., 2016. Prevalence of asthma, COPD, and chronic bronchitis in Iran: a systematic review and meta-analysis. Iranian Journal of Allergy, Asthma and Immunology, 15(2), pp.93-104.
Varmaghani, M., Farzadfar, F., Sharifi, F., Rashidian, A., Moin, M., Moradi-Lakeh, M., Rahimzadeh, S., saeedi Moghaddam, S. and Kebriaeezadeh, A., 2016. Prevalence of asthma, COPD, and chronic bronchitis in Iran: a systematic review and meta-analysis. Iranian Journal of Allergy, Asthma and Immunology, 15(2), pp.93-104.
Wong, G.W., Brunekreef, B., Ellwood, P., Anderson, H.R., Asher, M.I., Crane, J., Lai, C.K. and ISAAC Phase Three Study Group, 2013. Cooking fuels and prevalence of asthma: a global analysis of phase three of the International Study of Asthma and Allergies in Childhood (ISAAC). The lancet Respiratory medicine, 1(5), pp.386-394.

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92917 Using Health Care Data For Decision Making

92917 Using Health Care Data For Decision Making

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92917 Using Health Care Data For Decision Making

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92917 Using Health Care Data For Decision Making

0 Download5 Pages / 1,092 Words

Course Code: 92917
University: University Of Technology Sydney

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Country: Australia

Question:

1 Provide a response to each of the three sections that demonstrates an understanding of the application and management of health data and refers to literature related to the identified issues and associated tasks.
2 In each response, apply your findings to the hospital so as to assist the executive group indecision making and planning.
Case Scenario – UTS Hospital
UTS hospital is a well-established charitable hospital operated on a not for profit basis. It has 250 beds in an inner-city location. The population of the local community, from which it draws the majority of its patients, is ageing: 40% are over the age of 65 years. UTS hospital has an excellent reputation
for innovative care, rapid uptake of new technologies, teaching and research. It gets very little support from the government for running costs, although previous governments have been generous in meeting the cost of constructing new buildings and refurbishing old ones.
The hospital is in financial difficulty. Over 90% of the funding to the hospital for acute inpatients comes from private health insurers. The remainder is from the Department of Veterans Affairs, patients who pay for their own admissions, compensable patients from motor vehicle and workplace insurance, and patients whose stay is paid from a research grant. The rate of reimbursement from private insurers is based on a negotiated rate for each AR-DRG. Every year, insurance companies
negotiate with the hospital the rate it pays for each AR-DRG (i.e. a type of case mix- or activity-based funding). The fees are based on the average length of stay for each AR-DRG using the Australian cost weights.
The Chief Executive Office (CEO) has called a special meeting of the executive to discuss the issues facing the hospital and to plan the action they need to take. Present at the meeting are the Director of Nursing (DON), the Chief Financial Officer (CFO) and the Chief Information Officer (CIO).
1: The DON suggested that the problem is that case mix-based funding using AR- DRGs are not the best method to record performance because they do not suit the type of patients treated by UTS Hospital. She said that the majority of patients are older and more complex, and need to stay longer than the average length of stay for each AR-DRG. She suggested that AR-DRGs are useless for measuring the hospital’s performance when the length of stay of the patients was different to that of the average hospital. She was of the view that the hospital should go back to the insurance funds and negotiate a return to the funding of patients on a fixed per diem basis.
Provide a short statement for the executive that identifies the pros and cons of case mix-based funding approach compared to a fixed per diem rate. Provide the executive with a recommendation.
1.The CIO disagree that the age and complexity of the patient made the DRG system useless. He noted that there were many examples where older patients or those with more complex care, that needed a longer length of stay, had been classified into a different AR-DRG. UTS hospital is using AR-DRG version 5, and he was not sure if this was the most recent version.
Provide a short statement with two or three examples of where the AR-DRG had been split to allow for patients of different age or complexity in the current version of AR-DRGs in use in Australia. Given the nature of the UTS Hospital’s patients. outline to the executives the implications of changing AR-DRG versions.
The CFO said that there was no reason to believe that UTS hospital’s patients in a given AR-DRG classification were older or more complex than the patients in the same AR-DRG at a different hospital. He noted that there were established methods in use to compare the performance of similar hospitals.
Provide a short statement on the way peer hospitals are compared with in Australia. Identify, for the executive, the peer groups used in Australia. Provide an example of a benchmark used for comparing hospitals and identify the type of patients where there could be a particular issue with falling outside that benchmark. Describe the implications for the hospital.
Defends the advantages and disadvantages of case mix and per-diem funding and their potential impact on a hospital
Explain the different approaches to resource splits in AR-DRG. Considers data quality and accuracy challenges inherent in health communication such as medical coding, medical notes and discharge summaries

Answer:

Statement 01:
AR-DRG system or Australian refined diagnosis related groups can be defined as the contemporary patient classification system that uses scientific and clinically meaningful patient tagging system that relays information about the number and type of the patients admitted in the health care facility. This method of patent tagging is characterised a mixed case type patient classification, where the number of patients are compartmentalized depending on the type of care they are seeking (Hamada, Sekimoto and Imanaka 2012). This method of statistically relating the patients helps the health care facility to divide and subdivide patients into different groups according to the care type they are going to receive in a broader sense and decide the payment bundle according the grouping. This method allows the health care team to bill the patients according to the care items they are purchasing according their care needs which brings ease and clarity in the charging system and makes the billing procedure in health care much more transparent (Thomson et al. 2012).
However this classification system is a much narrower classification system that groups patients into very basic groups like acute and newborn. It creates a lot discrepancies in the costing methods as the care of different patients differ drastically in spite of belonging to acute care group or new born care group (Hamada, Sekimoto and Imanaka 2012). As the patients for this hospital and predominantly aged the care On the other hand per diem fixed rate system is a per day allowance system for the patients that will allow the health care services to charge the patients for each and every care services they avail rather than a care bundle that they did not avail or availed much more than what the care bundle entails (Thomson et al. 2012).
Statement 02: 
The diagnosis related grouping has been in place in Australia since a very long time and the patterns have been changed and refined a lot of times. The very first version for ARDRG that was introduced in the health care of Australia, have been a very basic grouping system that compartmentalized patients depending on their care needs be it acute, general or neonatal. However as the health care industry progressed there have been a lot of numbers of variations along the years. And there have been a lot of factors that have been included in the system of ARDRG. The element of age as a grouping factor has been added in the ARDRG system in the third version (Aihw.gov.au. 2017).
The hospital has been using the version 5 of the ARDRG which is not the recent version of patient classification in place in Australia. The recent version of the ARDRG system is the version 8 which has had a lot more improvements included (Cheng, Chen and Tsai 2012). This version has been introduced in 2016 where phases of clinical complexity have been categorized as the grouping factor. The diagnosis related groups have been increased from 698 to 807 in the recent version. A lot of complex cases and relevant care needs have been incorporated in the different groups like anxiety disorders, sleep disorders, musculoskeletal disorders and endocrine and nutritional disorders which are very common occurrences within the elderly population. As the most of clientele for UTS hospital is elderly adapting to the version 8 can prove to be beneficial (Online.uts.edu.au. 2017).
Statement 03: 
Peer groups can be defined as the group of similar hospitals that have operational characteristics alike or identical. Peer groups within the health care sector have been compared a lot of times in the history to gauge the performance standards of different hospitals (Alkhenizan and Shaw 2011). The comparison in the operational characteristics of the similar hospitals and their care delivery and performance standards provides a wealth of information for the regulatory authorities to determine the progress in the health care industry and room for improvements. Australian institute of health and welfare compares peer hospital groups in regular intervals to judge the performance and progress standards across different hospitals with hopes to identify the health care facilities that do not meet the quality and performance benchmarks (Aihw.gov.au. 2017).
There are different benchmarks used to compare the hospitals in Australia, for instance the time the patients spend in the emergency departments. However, it has to be considered that there are a lot of inter related external and internal factors associated with the different operations within the health care sector. Taking the customer base of UTS hospital as an example the patients are mostly aged and ridden with a myriad of complex diseases (Online.uts.edu.au. 2017). The prolonged stay in the emergency departments for these patients is mostly due to the health related complications like diabetes, coronary heart complication they already have or the age related complications like respiratory infections they develop during the stay in the emergency departments. All this factors play an influential role in determining the recovery rate in the different departments of the hospital and prolong and complicate the care needs. The lack of proper staff training due to limited funds is another important factor that contributes to prolonged stay of patients in emergency wards (Bartram et al. 2012). Inadequately trained staff lack in the efficiency that is required for the emergency wards and proper funding for the hospital is required for the hospital to elevate performance standards.
Reference:
Aihw.gov.au. (2017). Australian Institute of Health and Welfare. [online] Available at: https://www.aihw.gov.au [Accessed 22 Apr. 2017].
Alkhenizan, A. and Shaw, C., 2011. Impact of accreditation on the quality of healthcare services: a systematic review of the literature. Annals of Saudi medicine, 31(4), p.407.
Bartram, T., Casimir, G., Djurkovic, N., Leggat, S.G. and Stanton, P., 2012. Do perceived high performance work systems influence the relationship between emotional labour, burnout and intention to leave? A study of Australian nurses. Journal of Advanced Nursing, 68(7), pp.1567-1578.
Cheng, S.H., Chen, C.C. and Tsai, S.L., 2012. The impacts of DRG-based payments on health care provider behaviors under a universal coverage system: a population-based study. Health Policy, 107(2), pp.202-208.
Hamada, H., Sekimoto, M. and Imanaka, Y., 2012. Effects of the per diem prospective payment system with DRG-like grouping system (DPC/PDPS) on resource usage and healthcare quality in Japan. Health Policy, 107(2), pp.194-201.
Online.uts.edu.au. (2017). UTSOnline – Blackboard Learn. [online] Available at: https://online.uts.edu.au [Accessed 22 Apr. 2017].
Thomson, S., Osborn, R., Squires, D. and Jun, M., 2012. International profiles of health care systems 2012: Australia, Canada, Denmark, England, France, Germany, Iceland, Italy, Japan, the Netherlands, New Zealand, Norway, Sweden, Switzerland, and the United States.

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92917 Using Health Care Data For Decision Making

92917 Using Health Care Data For Decision Making

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92917 Using Health Care Data For Decision Making

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92917 Using Health Care Data For Decision Making

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Question:

Discuss About The Using Healthcare Data For Making Decision?

 
Answer:
Introducation

Per-diem refers to a hospital activity of charging rates on daily bases where the expenses incurred are all averaged over the entire hospital population.
Casemix funding refers to a method of allocating funds considering number of patients treated and also the types of patients treated (Milovic, 2012). For case mix funding to be used there are requirements needed:-
Patients treated classified considering the disease treated and type of treatment administered.
The total cost of the patients treated.
For counting its required for proper administrative health data collections that are maintained by health departments (Stiggelbout, Van der Weijden, De Wit, Frosch, Légaré, Montori, Trevena and Elwyn, 2012). For classification all patients treated are classified into different diagnosis related groups that shows patients those who have similar conditions and require the same treatment and resources.
Costing includes all cash paid to be reported as a part of good hospital management for both patients who are admitted and those who were not admitted.
One of the disadvantage of casemix funding is that one cost fund is used in order to fund each of the Patient considering that not every individual needs the same amount for treatment each patient has his/her own charges requirement.
Also casemix funding creates financial risks to the patients and also the providers of health care unlike for the case of per-diem rate where finances are properly management ensuring no misusing of funds and every cost is taken care of through proper planning (Ryan, Gerard, and Amaya-Amaya, 2007). Since there is lenient record keeping there are no financial risks at all for per-diem rate.
 
Per-diem helps a lot in covering the staffing needs this is because the staffing needs varies from time to time considering the climatic condition of a place where hospitals are located.
In Australian hospitals before they paid per diem only but later the national health insurance scheme was introduced and after the introduction the hospitals were of the completely new settlement settings to become much more utilized (Ryan, Gerard and Amaya-Amaya, 2007). Hospitals that offered much more intricate services required extra benefits and there some more categories of hospitals were added including surgical, medical and advanced surgical.
For patients classifications the government adopted private sector hospital classification that was not friendly at all and thus ruined it. Some years later the government introduced patient classification. In additional casemix funding in Australia is expected to put all hospital funding above politics and payments of this funding varies from one hospital to another. Public sector casemix has been introduced also and suggests that repayments would certainly cover up the adjustable expenses of hospitals along with the fixed populace dependent area financing would certainly cover up all the fixed expenses.
Description of difference between case mix funding and per diem funding model
The casemix funding method highlight the kind of the mix which the patient was treated when it comes the resources that depends on the parameter of interest. UTS hospital has classified people into various groups (Koh and Tan, 2011). On the per diem model there is a fixed amount of payment which is offered to the patient per day while in hospital, regardless of the charges which they incur in the hospital.
Statement of aim of analysis
The aims of this analysis was to highlights the difference between the casemix funding and fixed per diem funding. The focus has been on the pros and cons of these methods.
Methods
Data from the Common Practice Research Database (GPRD) was employed for this study. Basic procedures working for the GPRD carry out consented recommendations for the recording of medical and prescribing information, and submit anonymized patient-based clinical records to the database with some regularity. The precision and comprehensiveness of the data documented in the GPRD continues to be documented previously. The data includes demographic items, clinical data, laboratory tests and other values, and prescribing information. Data from the GPRD on patient diagnoses, prescriptions, age and gender were acquired. Initially based on age, gender and a combination of documented diagnoses over a one year period, patients were allocated using the ACG System software5. These types of ACGs were after that grouped into six collectively exclusive classes employing the ACG software program which ranks the ACGs based on the patients’ estimated resource use , depending on that of a nationally representative database of two million patients of below 65 years of age in the Australia ( Ryan and Farrar , 2000 ) . These types of 6 groups were accustomed to characterize patient morbidity sets ranging from the healthiest to the sickest in addition to were employed like a method of clinical circumstance mix of the patients. Age was arranged as young people , teenagers , older grownups as well as aged The variety of medications documented in the GPRD was adequate to approximate the models’ Coefficients with preferred degree of accuracy .
Results
After exemption, there have been 129 procedures in the GPRD with an overall of 1, 032, 072 patients, with 49 .3% men as well as 50 .7% women. The total prescribing rate was 4 .5 products per affected person per year as well as 64% of the affected individuals were given a prescribed at least one time in the course of 2001 . The median percent of victims given a medication by practice was 65%. The median number of prescription medications issued was determined for every of the 129 practices and median of those was two. The percent of the patient in the several sickest morbidity groups were little and therefore were joined in most analyses. The median variety of prescription medications given amplified with age bracket together with morbidity sets and was larger for females (Koh and Tan, 2011). The gender distribution of the victims was equivalent across the procedures. The proportion of victims in various age group and morbidity groupings diversified across methods to certain scope with the largest variance observed for patients above sixty five years of age and for morbidity. There was clearly furthermore certain variance across techniques in patient syndication for the 2 healthful morbidity sets. The median variety of prescription medications given diversified the majority of between the methods for patients aged above sixty-five as well as for the sickest morbidity sets. The estimated amount of prescription medications for men and women aged zero to fifteen were projected to be 1 .6 and also 2 .2 respectively (Ryan and Farrar, 2000). The related estimated figure is 9 .2 and also 12 .7 for men and women aged sixty-five in addition to over respectively. For the healthiest males and females aged zero to fifteen, the projected range of prescriptions is 0 .05.
 
Visual representation between Lengths of stay and age
Discussion of findings
From the diagram below it highlights the average length of stage in hospitals by age. In the figure shows that the higher the age of the patient the higher the number of stay in the hospital. This is applicable also to the lower age groups. The young individuals stays fewer days than the old.
Tabulated presentation
Discussion of findings
Based on the data presented on DRG it is evident to highlights that the older individual who are over 70 years suffers more from the common ailments and as highlighted there are various AR-DRG components that are shown.
The affected individual’s morbidity describes significantly more of the variability in prescribing compared to affected person age as well as gender only (Edwards and Elwyn, 2009). Relating to 4% of the entire variance is at the practice degree in addition to the majority of the variance is within methods.
Conclusions
This research reveals that addition of a diagnosis dependent affected person morbidity measure into prescribing models can describe a lot of variability at both patient and practice levels. The usage of patient-based scenario mix techniques needs to be researched additional whenever investigating variance in prescribing designs between procedures in the Australia, particularly for particular prescribing categories, together with may confirm beneficial in fairer utilization of financial budgets.
 
References
Edwards, A. and Elwyn, G. eds., 2009. Shared decision-making in health care: Achieving evidence-based patient choice. Oxford University Press.
Koh, H.C. and Tan, G., 2011. Data mining applications in healthcare. Journal of healthcare information management, 19(2), p.65.
Milovic, B., 2012. Prediction and decision making in health care using data mining. Kuwait chapter of arabian journal of business and management review, 1(12), pp.126-136.
Ryan, M. and Farrar, S., 2000. Using conjoint analysis to elicit preferences for health care. BMJ: British Medical Journal, 320(7248), p.1530.
Ryan, M., Gerard, K. and Amaya-Amaya, M. eds., 2007. Using discrete choice experiments to value health and health care (Vol. 11). Springer Science & Business Media.
Stiggelbout, A.M., Van der Weijden, T., De Wit, M.P., Frosch, D., Légaré, F., Montori, V.M., Trevena, L. and Elwyn, G., 2012. Shared decision making: really putting patients at the centre of healthcare. BMJ: British Medical Journal (Online), 344

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I have conducted a survey at my workplace maned Lady’s Hospice and Care Services to observe the working environment. The aim of the survey is to find if it is a safe, healthy, secured and fulfilling place to work. A visual survey was conducted to locate and record the safety signs in the workplace. The objective of the survey is to observe and list different types of signs, location, their prom…
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Introduction
Palliative care services are designed to improve the life of patient with progressive disease. People receiving palliative care have illness that has no prospect of cure.  As per the World Health Organisation, palliative care is a care given to patient suffering from life threatening illness to improve their quality of life by preventing and providing relief from sufferings by early recognition , assessment and trea…
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Human Immunodeficiency Virus Infection and Acquired Immune Deficiency Syndrome (HIV/AIDS) is the spectrum of medical conditions caused due to human immunodeficiency virus (HIV) following which the patient suffers from a series medical complications due to suppression of the immune system of the body. With the progression of the disease, the patient is likely to suffer from a wide range of infections like tuberculosis and other opportu…
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Answer:
Introduction
Leadership in the hospital is the ability to influence the staff toward providing quality health care. Leadership involves influencing human behavior to create a positive working environment (Langlois, 2012). Good leadership enables healthy relationships among staffs in the hospital enhancing quality delivery of health care services. Leadership is responsible to building teams that have trust, respect, support and effecti…
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Answer:
Introduction
According to the researchers, it can be said that the management of the health care organizations has become a difficult task nowadays and the reason behind this is the occurrence of various issues in this sector (Hall et al., 2014). Therefore, the administrative employees of the organization should incorporate various revolutionized strategies for enriching the worth of care provided by the hospital to its clients and re…
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92917 Using Health Care Data For Decision Making

92917 Using Health Care Data For Decision Making

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92917 Using Health Care Data For Decision Making

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92917 Using Health Care Data For Decision Making

0 Download6 Pages / 1,458 Words

Course Code: 92917
University: University Of Technology Sydney

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Country: Australia

Question:

Discuss About The Using Healthcare Data For Making Decision?

 
Answer:
Introducation

Per-diem refers to a hospital activity of charging rates on daily bases where the expenses incurred are all averaged over the entire hospital population.
Casemix funding refers to a method of allocating funds considering number of patients treated and also the types of patients treated (Milovic, 2012). For case mix funding to be used there are requirements needed:-
Patients treated classified considering the disease treated and type of treatment administered.
The total cost of the patients treated.
For counting its required for proper administrative health data collections that are maintained by health departments (Stiggelbout, Van der Weijden, De Wit, Frosch, Légaré, Montori, Trevena and Elwyn, 2012). For classification all patients treated are classified into different diagnosis related groups that shows patients those who have similar conditions and require the same treatment and resources.
Costing includes all cash paid to be reported as a part of good hospital management for both patients who are admitted and those who were not admitted.
One of the disadvantage of casemix funding is that one cost fund is used in order to fund each of the Patient considering that not every individual needs the same amount for treatment each patient has his/her own charges requirement.
Also casemix funding creates financial risks to the patients and also the providers of health care unlike for the case of per-diem rate where finances are properly management ensuring no misusing of funds and every cost is taken care of through proper planning (Ryan, Gerard, and Amaya-Amaya, 2007). Since there is lenient record keeping there are no financial risks at all for per-diem rate.
 
Per-diem helps a lot in covering the staffing needs this is because the staffing needs varies from time to time considering the climatic condition of a place where hospitals are located.
In Australian hospitals before they paid per diem only but later the national health insurance scheme was introduced and after the introduction the hospitals were of the completely new settlement settings to become much more utilized (Ryan, Gerard and Amaya-Amaya, 2007). Hospitals that offered much more intricate services required extra benefits and there some more categories of hospitals were added including surgical, medical and advanced surgical.
For patients classifications the government adopted private sector hospital classification that was not friendly at all and thus ruined it. Some years later the government introduced patient classification. In additional casemix funding in Australia is expected to put all hospital funding above politics and payments of this funding varies from one hospital to another. Public sector casemix has been introduced also and suggests that repayments would certainly cover up the adjustable expenses of hospitals along with the fixed populace dependent area financing would certainly cover up all the fixed expenses.
Description of difference between case mix funding and per diem funding model
The casemix funding method highlight the kind of the mix which the patient was treated when it comes the resources that depends on the parameter of interest. UTS hospital has classified people into various groups (Koh and Tan, 2011). On the per diem model there is a fixed amount of payment which is offered to the patient per day while in hospital, regardless of the charges which they incur in the hospital.
Statement of aim of analysis
The aims of this analysis was to highlights the difference between the casemix funding and fixed per diem funding. The focus has been on the pros and cons of these methods.
Methods
Data from the Common Practice Research Database (GPRD) was employed for this study. Basic procedures working for the GPRD carry out consented recommendations for the recording of medical and prescribing information, and submit anonymized patient-based clinical records to the database with some regularity. The precision and comprehensiveness of the data documented in the GPRD continues to be documented previously. The data includes demographic items, clinical data, laboratory tests and other values, and prescribing information. Data from the GPRD on patient diagnoses, prescriptions, age and gender were acquired. Initially based on age, gender and a combination of documented diagnoses over a one year period, patients were allocated using the ACG System software5. These types of ACGs were after that grouped into six collectively exclusive classes employing the ACG software program which ranks the ACGs based on the patients’ estimated resource use , depending on that of a nationally representative database of two million patients of below 65 years of age in the Australia ( Ryan and Farrar , 2000 ) . These types of 6 groups were accustomed to characterize patient morbidity sets ranging from the healthiest to the sickest in addition to were employed like a method of clinical circumstance mix of the patients. Age was arranged as young people , teenagers , older grownups as well as aged The variety of medications documented in the GPRD was adequate to approximate the models’ Coefficients with preferred degree of accuracy .
Results
After exemption, there have been 129 procedures in the GPRD with an overall of 1, 032, 072 patients, with 49 .3% men as well as 50 .7% women. The total prescribing rate was 4 .5 products per affected person per year as well as 64% of the affected individuals were given a prescribed at least one time in the course of 2001 . The median percent of victims given a medication by practice was 65%. The median number of prescription medications issued was determined for every of the 129 practices and median of those was two. The percent of the patient in the several sickest morbidity groups were little and therefore were joined in most analyses. The median variety of prescription medications given amplified with age bracket together with morbidity sets and was larger for females (Koh and Tan, 2011). The gender distribution of the victims was equivalent across the procedures. The proportion of victims in various age group and morbidity groupings diversified across methods to certain scope with the largest variance observed for patients above sixty five years of age and for morbidity. There was clearly furthermore certain variance across techniques in patient syndication for the 2 healthful morbidity sets. The median variety of prescription medications given diversified the majority of between the methods for patients aged above sixty-five as well as for the sickest morbidity sets. The estimated amount of prescription medications for men and women aged zero to fifteen were projected to be 1 .6 and also 2 .2 respectively (Ryan and Farrar, 2000). The related estimated figure is 9 .2 and also 12 .7 for men and women aged sixty-five in addition to over respectively. For the healthiest males and females aged zero to fifteen, the projected range of prescriptions is 0 .05.
 
Visual representation between Lengths of stay and age
Discussion of findings
From the diagram below it highlights the average length of stage in hospitals by age. In the figure shows that the higher the age of the patient the higher the number of stay in the hospital. This is applicable also to the lower age groups. The young individuals stays fewer days than the old.
Tabulated presentation
Discussion of findings
Based on the data presented on DRG it is evident to highlights that the older individual who are over 70 years suffers more from the common ailments and as highlighted there are various AR-DRG components that are shown.
The affected individual’s morbidity describes significantly more of the variability in prescribing compared to affected person age as well as gender only (Edwards and Elwyn, 2009). Relating to 4% of the entire variance is at the practice degree in addition to the majority of the variance is within methods.
Conclusions
This research reveals that addition of a diagnosis dependent affected person morbidity measure into prescribing models can describe a lot of variability at both patient and practice levels. The usage of patient-based scenario mix techniques needs to be researched additional whenever investigating variance in prescribing designs between procedures in the Australia, particularly for particular prescribing categories, together with may confirm beneficial in fairer utilization of financial budgets.
 
References
Edwards, A. and Elwyn, G. eds., 2009. Shared decision-making in health care: Achieving evidence-based patient choice. Oxford University Press.
Koh, H.C. and Tan, G., 2011. Data mining applications in healthcare. Journal of healthcare information management, 19(2), p.65.
Milovic, B., 2012. Prediction and decision making in health care using data mining. Kuwait chapter of arabian journal of business and management review, 1(12), pp.126-136.
Ryan, M. and Farrar, S., 2000. Using conjoint analysis to elicit preferences for health care. BMJ: British Medical Journal, 320(7248), p.1530.
Ryan, M., Gerard, K. and Amaya-Amaya, M. eds., 2007. Using discrete choice experiments to value health and health care (Vol. 11). Springer Science & Business Media.
Stiggelbout, A.M., Van der Weijden, T., De Wit, M.P., Frosch, D., Légaré, F., Montori, V.M., Trevena, L. and Elwyn, G., 2012. Shared decision making: really putting patients at the centre of healthcare. BMJ: British Medical Journal (Online), 344

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