Analysis Of UTS Hospital Patient Data

Background information

This paper assesse the patient on the UTS Hospital observed on over 34000 patients. The data was collected to observe different issues touching patients and the hospital. The data covered many issues including but not limited to the hours taken in the ICU, financial status, the level of emergency of their need and many others.

By addressing these issues, the report is establishing ways the hospital can improve on the service they offer to patient upholding the image of the hospital in general. The areas with shortages will be improved for future better health care.

The data was analyzed using (SPSS) and the main outcome from our findings were that many patients visited General medicine as the General Practice receiving least patients. The most number of patient were between the age of 21-40 years and many of them were in marriage. Acute service category received almost all patients. It also indicate that the main mode of separation is discharge by the hospital. (Galt, 2008)

Introduction

UTS Hospital is a public hospital in Australia which is located in the New South Wales. It is the University of Technology of Sydney serving both students and the public. They offer several medical services including treating medical conditions, illness and other physical problems. The hospital also offers consultation for a broad range for issues of lifestyle and sexuality and health.

Health issues of women including the contraception advice, testing pregnancy and even the antenatal care are dealt with. Services on the travelling advice and vaccination, pamphlets providing information on health issues, vaccines for students taking nursing and assistance of students with difficulties in examinations are some of the services offered. The data assessed contained the health information of the patient recorded sometimes back.

The health information contain the medical history of the patients including the symptoms, diagnoses, procedures done and the outcomes. The information also contain records such as the history of the patient, result of the lab tests, x-rays, clinical information and the notes. There is importance of analyzing such information as they help to see how the health of patients have changed.

Background information

The health information the patients are taken whenever they visited a hospital. These information includes their medical history, clinical information, the results of the labs x-rays etc. These information are very important for both the hospital and the patients. These health information are visited by the health care providers for the analysis of the general healthcare.

Health information helps the hospital to make some informed decision in providing health care to the patients. But this need a proper analysis of the data contained in the patient files.

The data from the UTS Hospital contained the information of the patients ranging from the number of hours they stayed in ICU, the number of hours they stay in the hospital, whether they are able to settle their medical bills. Such information are the basis of through which the management can make informed decision to improve the image and offer good services.

Methods

Methods

The data was obtained from the health information department of the UTS Hospital. Through the use of research assistants, the information were extracted from the patient files. These are personal files of the patients recorded from the health workers and kept safely on the selves. 

The analysis involved the whole target population. All the patients file with the information needed were data got extracted from.

The data was then recorded in the Microsoft excel and then transferred to SPSS for the analysis. The descriptive statistics were obtained to compare the frequencies and the percentages of the variables. (Dawn J. Storey, 2008) (Robert Gürlich, 2005)

The following are the findings of the UTS Hospital data

1. AMO specialist

The table below shows the different specialist visited by the patients surveyed the hospitals. The majority of the specialists involved in the General Medicine at 19% while the specialists in general practice form the lowest number of 0.001%. (Mary L. McHugh, 2003) (Besselaar, 2003)

	Frequency	Percent
Anesthetics	156	.5
Cardiology	817	2.4
Cardiothoracic Surgery	419	1.2
Casualty	3629	10.5
Dental	204	.6
Ear, Nose & Throat	677	2.0
Endocrinology	237	.7
Faciomaxillo Surgery	262	.8
General Medicine	6565	19.0
General Practice	1	.0
General Surgery	3385	9.8
Gynaecology	1582	4.6
Neurology	225	.6
Neurosurgery	662	1.9
Obstetrics	7652	22.1
Oncology	704	2.0
Ophthalmology	219	.6
Orthopedics	1812	5.2
Pediatrics	2568	7.4
Plastic Surgery	889	2.6
Psychiatry	823	2.4
Radiology	3	.0
Rehabilitation	173	.5
Renal Medicine	186	.5
Urology	774	2.2
Total	34624	100.0

Gender

	Frequency	Percent
Female	20200	58.3
Male	14424	41.7
Total	34624	100.0

Age

On the age of the respondents; 25.7% were the people between 0-20 years of age, 30.4% were people between 21-40 years of age, 19.1% were people of age between 41-60 years of age, 18.8% were people of age between 61-80 and 6% were between the ages of 81-100 years. (Miller, 2013) (Billard, 2006)

	Frequency	Percent
0-20	8909	25.7
21-40	10523	30.4
41-60	6608	19.1
61-80	6514	18.8
81-100	2070	6.0
Total	34624	100.0

Marital status

On the marital status of the respondents, 2.9% said they are divorced, while the married formed the majority of 44.5% of the total population surveyed, followed by 39.5% who said they are single, 3.3% said they do not know their marital status, 8.3% of them said they are widowed while the least group 1.5% was formed by separated. (Cutright, 2008) (Teachman, 2016)

	Frequency	Percent
Divorced	1003	2.9
Married	15400	44.5
Separated	503	1.5
Single	13678	39.5
Unknown	1151	3.3
Widowed	2889	8.3
Total	34624	100.0

Discharge intension

On the intention of discharging; 81% said their intended discharge was overnight while 19% their intended discharge was the same day.

	Frequency	Percent
Overnight	28051	81.0
Same Day	6573	19.0
Total	34624	100.0

Length of stay

On the length of stay in the hospital by the patients; 96.4% was found to have stayed in the hospital between 1-19 days, 2.6% patients stayed in the hospital for days between 20-39 it followed by 0.6% of patients who stayed in the hospital between 40-59 while 0.2% of the patients stayed in the hospital for days between 60-79 as the patients who stayed beyond those days were small in number as shown in the table. (Farid Yudoyono, 2016)

	Frequency	Percent
1-19	33362	96.4
20-39	893	2.6
40-59	214	0.6
60-79	80	0.2
80-99	27	0.07
100-119	11	0.03
120-139	6	0.02
140-159	1	0.0
Others	4	0.0
Total	34624	100.0

Service category

On the category of service of the respondents; 88.3% of the respondents had their service categorized under acute, followed by 9.8% who had their service categorised under neonate, 0.9% had their service categorized under rehabilitation, 0.8% had their service categorized under palliative care, 0.1% had their service categorized under maintenance care, 0.001% both had their service categorized under geriatric evaluation and psychogeriatric.

	Frequency	Percent
Acute	30586	88.3
Geriatric Evaluation	3	.0
Maintenance Care	45	.1
Neonate	3400	9.8
Palliative Care	289	.8
Psychogeriatric	4	.0
Rehabilitation	297	.9
Total	34624	100.0

ICU hours

On the average hour the patients stayed in the ICU care, 98.9% indicated that they stayed in the ICU for between 0-200 hours, followed by 0.05% who stayed in the ICU for between 201-400 hours. 0.2% stayed in the ICU for hours between 401-600 as 0.1% stayed in the ICU for hours between 601-800. The rest who stayed in ICU beyond 800 hour are negligible as shown in the table below. (Brand, 2013) (S Kongsayreepong, 2010)

	Frequency	Percent
0-200	34253	98.9
201-400	164	0.5
401-600	84	0.2
601-800	46	0.1
801-1000	24	0.05
1001-1200	14	0.04
1201-1400	10	0.03
1401-1600	9	0.03
1601-1800	2	0.0
1801-2000	7	0.02
2001-2200	3	0.0
2201-2400	3	0.0
2401-2600	2	0.0
Total	34624	100.0

Findings

Separation mode

On the mode of separation, we find that the separation mode of the majority 90.8% was a discharge by the hospital followed by 4.4% whose their mode of separation was the transfer to another hospital and 1.2% had their separation mode to be death without autopsy, 1.2% was through statistical discharge, 1.1% were transferred to a nursing home and the other negligible number of people were separated through transfer to psychiatric hospital, transfer to palliative care, discharge on leave and death with autopsy as shown.

	Frequency	Percent
Death with autopsy	48	.1
Death without autopsy	414	1.2
Discharge by Hospital	31451	90.8
Discharge on leave	39	.1
Left against advice	263	.8
Statistical discharge	405	1.2
Transfer another hospital	1537	4.4
Transfer other accom	21	.1
Transfer to nursing Home	382	1.1
Transfer to Palliative	1	.0
Transfer to psych hosp	63	.2
Total	34624	100.0

Financial class

On the financial class of the patients, the majority of the patients 80.8% were under the Public patient-general and Psych, 8.2% were under unqualified baby of public patient, 4% under private-shared ward overnight, 2.1% under the veterans affairs, 1.1% were under private patient same day band 1 and other negligible percentages falling under different category as shown. (John, 2013) (Bruns, 2008)

	Frequency	Percent
Medicare Ineligible	64	.2
Motor Vehicle Accident	120	.3
Other Compensable	6	.0
Private – Shared Ward Overnight	1402	4.0
Private – single room overnight	272	.8
Private Patient – Same Day Band 1	390	1.1
Private Patient – Same Day Band 2	131	.4
Private Patient – Same Day Band 3	189	.5
Private Patient – Same Day Band 4	73	.2
Public Patient – general & Psych	27990	80.8
Public Patient – Other Eligible	46	.1
Public Patient – Overseas reciprocal	52	.2
Unqualified baby of Private Patient	89	.3
Unqualified Baby of Public Patient	2825	8.2
Veterans Affairs	724	2.1
Workers Compensation	251	.7
Total	34624	100.0

Mechanical of hour of ventilators

When the hours for mechanical ventilation was recorded, 98.7% of the times the mechanical ventilation was working, it was on for between 0-100 hours, only 0.2% show that the mechanical ventilation was on for 101-200 hours. More than 200 hour the percentage at which the mechanical ventilation was on was negligible. (RJ Jackson, 2012) (Ntoumenopoulos, 2007)

	Frequency	Percent
0-100	34476	98.7
101-200	61	0.2
201-300	27	0.07
301-400	20	0.06
401-500	13	0.04
501-600	9	0.03
601-700	4	0.0
701-800	5	0.01
Others	6	0.01
Total	34624	100.0

Country of birth

On the county of birth, the majority of the patients whom their information were observed were coming from Australia at 78.5%. There were more than 100 countries recorded, it is only England which had some good number at5.5%.

	Frequency	Percent
Afghanistan	37	.1
Argentina	24	.1
Australia	27190	78.5
Austria	45	.1
Bangladesh	4	.0
Belgium	11	.0
Bosnia_Herzegovina	23	.1
Brazil	4	.0
Bulgaria	1	.0
Burma (Myanmar)	3	.0
Cambodia	8	.0
Canada	27	.1
Central African Republic	2	.0
Chile	34	.1
China (exluding Taiwan)	64	.2
Colombia	3	.0
Congo	3	.0
Cook Islands	7	.0
Croatia	94	.3
Cuba	1	.0
Cyprus	28	.1
Czech Republic	8	.0
Czechoslovakia	41	.1
Denmark	20	.1
Ecuador	4	.0
Egypt	106	.3
El Salvador	14	.0
England	1918	5.5
Equatorial Guinea	1	.0
Estonia	4	.0
Fiji	142	.4
Finland	12	.0
Former Yugoslav Republic of Macedonia	23	.1
France	20	.1
Germany (United)	217	.6
Ghana	1	.0
Gibraltar	3	.0
Greece	118	.3
Grenada	1	.0
Guatamala	1	.0
Holy See	8	.0
Hong Kong	17	.0
Hungary	87	.3
India	192	.6
Indonesia	23	.1
Iran	30	.1
Iraq	43	.1
Ireland	163	.5
Isle of Man	1	.0
Israel	6	.0
Italy	237	.7
Jamaica	2	.0
Japan	5	.0
Jordan	6	.0
Kenya	4	.0
Korea, People’s Republic	2	.0
Korea, Republic of	5	.0
Kuwait	15	.0
Laos	1	.0
Latvia	23	.1
Lebanon	124	.4
Libya	2	.0
Lituania	8	.0
Luxembourg	1	.0
Macau	3	.0
Malaysia	25	.1
Mali	1	.0
Malta	220	.6
Mauritania	1	.0
Mauritius	20	.1
Mongolia	2	.0
Morocco	1	.0
Nepal	2	.0
Netherlands	250	.7
New Caledonia	9	.0
New Zealand	518	1.5
Nicaraqua	2	.0
Nigeria	3	.0
Niue	1	.0
Norfolk Island	1	.0
Northern Ireland	46	.1
Norway	4	.0
Pakistan	49	.1
Papua New Guinea	19	.1
Peru	25	.1
Philippines	314	.9
Poland	156	.5
Portugal	24	.1
Romania	11	.0
Russian Federation (not USSR)	11	.0
Samoa, American	5	.0
Samoa, Western	130	.4
Scotland	409	1.2
Seychelles	1	.0
Singapore	18	.1
Slovak Republic	1	.0
Slovenia	13	.0
Somalia	2	.0
South Africa	76	.2
Spain	35	.1
Sri Lanka	68	.2
Sudan	12	.0
Swaziland	1	.0
Sweden	35	.1
Switzerland	12	.0
Syria	12	.0
Taiwan	2	.0
Tanzania	2	.0
Thailand	18	.1
Tokelau	9	.0
Tonga	24	.1
Trinidad and Tobago	2	.0
Turkey	40	.1
Tuvalu	1	.0
U.S.S.R (former combined states)	1	.0
Uganda	2	.0
Ukraine	36	.1
United Arab Emirates	1	.0
United States of America	66	.2
Unknown/Not Known	363	1.0
Uraguay	37	.1
Venezuela	1	.0
Viet Nam	19	.1
Wales	32	.1
West Bank	2	.0
Western Sahara	2	.0
Yugoslavia, (not otherwise defined)	138	.4
Yugoslavia, other than Croatia, Slovenia	1	.0
Zambia	2	.0
Zimbabwe	3	.0
Total	34624	100.0

Indigenous status

On the indigenous status the majority of 98.1% said they are of other indigenous status from the ones mentioned. 1.9% had a status of Aboriginal.

	Frequency	Percent
Aboriginal	648	1.9
Both	8	.0
Not Stated	1	.0
Other	33964	98.1
Torres Strait Islander	3	.0
Total	34624	100.0

Readmit code

For the code for readmission, 83.4% said the code for readmission was not applicable to them, while 4.3% said the readmission code was for other hospital and 12.3% was for the hospital in question.

	Frequency	Percent
Not applicable	28882	83.4
Other hospital	1492	4.3
This hospital	4250	12.3
Total	34624	100.0

Emergency status

On whether their cases were urgent; 55.5% said their cases were emergency, 22.3% said they planned for their cases while the emergency status of 22.1% was other urgencies.

	Frequency	Percent
Emergency	19233	55.5
Other	7665	22.1
Planned	7726	22.3
Total	34624	100.0

Discussion and Recommendations

Currently the incidences and prevalence of asthma and bronchitis is very high. This might be as result of immigrants since it is found to be mostly attacking the non-Australians.

Admission of the patients with asthma and bronchitis has increased over the past few years making the hospital to crowded hence making a lot of delays for services. Some patients are taken in-patients staying in for a very long time. (Fujioka, 2013) (Fiona Farringdon, 2014)

On the UTS Hospital dataset, it is realized that the majority of patients visiting the hospital are of the age between 21-40 and the majority are married females. Most of the patient admitted are of acute.

Most of the patient said their readmit is not applicable because they are visiting the hospital more than twice and at a very high frequency. The emergency cases also increased as many patients reporting high cases of emergency.

To reduce long hours of stay, more hospitals to be equipped with necessary facilities so that they can also admit part of the patients. (M. Namer, 2006)

Increased number of personnel dealing in curbing such cases will be effective.

Conclusion

 From the assessment of the data from the UTS Hospital it evident that there are many patients stay long in the hospital and the majority are from Australia.

By addressing these issues, the report is establishing ways the hospital can improve on the service they offer to patient upholding the image of the hospital in general. The areas with shortages will be improved for future better health care.

The main findings were that many patients visited General medicine as the General Practice receiving least patients. The most number of patient were between the age of 21-40 years and many of them were in marriage. Acute service category received almost all patients. It also indicate that the main mode of separation is discharge by the hospital. 

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