Evaluating the Hospital Infrastructure

Infrastructure in An Inpatient Care System at A Hospital
We will focus on data management which is the administrative process that involves acquiring, validating, storing, protecting, and processing of the data received by an organization. This is mainly done to ensure the data is accessible, reliable, and timely. Within the hospital, there is an electronic health record (EHR) system. However, the system has not been fully implemented within the hospital. Departments like laboratory and radiology are still using their own independent system that synchronizes data with the EHR every hour. Therefore, all the laboratory test results and radiology results are not readily available once they are uploaded into the system. In order to overcome this challenge, the hospital staff are forced to use manual results as they await the synchronization of the results in the system. The manual process is not recommended since it causes loss of data (Groves, Kayyali, Knott, & Kuiken, 2016). The data that is captured in the EHR is keyed in at the receiving desk of the patient. This is then verified before it is uploaded on to the servers. The verification process is only done to ensure that all the required fields have been filled out and there is no counter checking to ensure that the correct data has been inserted. Once the data is within the system, the data will follow the patient wherever they will go except the laboratory and radiology. All data is securely stored and can only be accessed by an authorized individual.
Existing Gaps and Issues
One of the gaps that are existing is that the system has not been rolled out to the whole organization. This makes it hard for information sharing and the hospital is forced to rely on manual processes for some of the departments. The risk of data loss become apparent since the two systems are not capturing the same patient data and transferring the data from one system to the other is challenging. This has forced the hospital administrators to request the laboratory and radiology department to only enter patient name and results into their respective systems. In essence, there is a loss of data since the results do not show the tests that the patient underwent. With all the data that the hospital collects regarding patients, it should be used to improve on the services they render to patients (Andreu-Perez, Poon, Merrifield, Wong, & Yang, 2015). Since this is an inpatient hospital, the data can be used to determine the areas where the hospital can make improvements in terms of care delivery. However, the hospital only uses the data for patient management and there is no analysis that is done. This could be attributed to the EHR system itself that does not allow for in-depth analysis to be done on the data that is stored. When purchasing the system, the hospital was only concerned with automating patient records and not for any data analysis.
Solutions for Improvement
In order to seal the loopholes that have been identified, there is a need to ensure that the system being used is similar across all the departments within the hospital. This will allow for the seamless sharing of data and there will be no manual records being used. The loss of data that occurs with the use of manual and not entering all the information will be eliminated. To accomplish this the current system should be overhauled and a new more advanced system implemented within the hospital. All the departments will be covered and there will be no usage of different systems within the facility, which will make it easy to retrieve patient records. Data analysis should be the overall aim of the hospital. Towards this goal when searching and settling for a new system, it should allow the hospital the flexibility to create its own reports even if they have not been initially designed or thought (Andreu-Perez et al., 2015). This way, the hospital will be able to cover any unforeseeable future requirements for reports that can be generated from the data stored within the system. The stored data can be used to establish the performance of the hospital at different hours of the day and night. This information can be used to improve upon the service delivery for the hospital. Before acquiring a new system, hospital administrators should first establish the needs of the hospital. This way they will be better placed to source for a system that can fit their particular needs.
Current Technology That Can Change Health Care Infrastructure
There are many advances that are being made within the health care industry. These advances are aimed at improving patient outcomes and the health care facility. Augmented reality (AR) is a real-time digital integration of information and images in the environment of the user. This offers technical and decision support in clinical environments and facility design process (Bhushan, Anandasabapathy, & Shukla, 2018). Virtual reality (VR) is an interactive computer-generated 3D environment. With VR technologies health care can be transformed in predictive clinical simulations, pain management, education, and neurorehabilitation. Artificial Intelligence (AI) refers to computer systems that have been programmed to simulate human thinking and this included machine learning. AI solutions have the potential to offer predictive analytics that results in better clinical outcomes. 3D printing is a printing process that creates three-dimensional solid objects from a digital file. The use of 3D in health care includes customizing implants, custom prostheses, and bioprinting for burn victims. With the continued expansion of these technologies, there is a need for the hospital to make room for these technologies to ensure that they are not left behind.


References
Andreu-Perez, J., Poon, C. C., Merrifield, R. D., Wong, S. T., & Yang, G.-Z. (2015). Big data for health. IEEE journal of biomedical and health informatics, 19(4), 1193-1208.
Bhushan, S., Anandasabapathy, S., & Shukla, R. (2018). Use of Augmented Reality and Virtual Reality Technologies in Endoscopic Training. Clinical Gastroenterology and Hepatology, 16(11), 1688-1691.
Groves, P., Kayyali, B., Knott, D., & Kuiken, S. V. (2016). The'big data'revolution in healthcare: Accelerating value and innovation.