Keeping medical records is very much important for organizations. For providing better care to patients; an accurate, complete, and up-to-date patient medical record is required. Most of the health sectors of Pakistan except a few uses a paper-based system. The paper-based data system causes some ma
Intelligent Database System for Medical Record Keeping and Retrieval
Keeping medical records is very much important for organizations. For providing better care to patients; an accurate, complete, and up-to-date patient medical record is required. Most of the health sectors of Pakistan except a few uses a paper-based system. The paper-based data system causes some management issues such as; it is time-consuming to access the previous medical records; the hospitals find it difficult to share the data timely with other healthcare sectors that cause a lack of coordination among the healthcare sectors and there is difficulty in keeping medical records for future referral. So, we aim to cope with these challenges, we are going to design a database system to store and manage medical records by preferring the telemedicine domain. To properly manage the data, this database system will be involving Artificial Intelligence that provides a form of intelligence, aiding clinicians with decision support and error avoidance [1]. The medical data in this database system will include; patient registrations, laboratory test details, and other patient care activities. All the data will be entered into this system to convert this amount of data into structured data (standardized representation of medical records) using natural language technique [1].
Nowadays Covid-19 pandemic is one of the major problems in healthcare [2]. The rate of affected COVID patients is increasing day by day. Our system will help in making an intelligent diagnosis of the covid-19 patient to avoid their outdoor exposure by using the patient’s data which is already stored in the database.
Our aim is to replace the traditional paper-based system with an electronic system to make the data more secure and accurate. Usually, hospitals provide paper receipts if patients visit different departments like pharmacies, laboratories, or others so to replace this system, the data should be centralized using a database server through which the required medical records will be shared with the respective departments of hospitals to avoid providing receipts to patients.
The designed system will be easily implementable in the hospitals and user-friendly. Adopting such a system in hospitals can improve the efficiency of management and can provide better satisfaction than the paper-based record.
References
[1] Van Vleck, T. T., Chan, L., Coca, S. G., Craven, C. K., Do, R., Ellis, S. B., Kannry, J. L., Loos, R. J. F., Bonis, P. A., Cho, J., &Nadkarni, G. N. (2019). Augmented intelligence with natural language processing applied to electronic health records for identifying patients with non-alcoholic fatty liver disease at risk for disease progression. International Journal of Medical Informatics, 129, 334–341
https://doi.org/10.1016/j.ijmedinf.2019.06.028
[2] Gates, B. (2020). Responding to Covid-19 — A Once-in-a-Century Pandemic? New England Journal of Medicine, 382(18), 1677–1679 https://doi.org/10.1056/nejmp2003762
Following are the objectives to be achieved:
Initially, we plan to design a generalized database system for the hospital, which keeps and manages all the medical data (records), including patient registrations, other details during patient care in the hospital: such as laboratory test details, pharmacy details, billing details, and others. Separate forms will be created for taking all these records, such as one for patient registration, one for billing, etc so that all the clinical data will be collected. The data obtained by the system is unstructured data that contains critical clinical information. To make proper use of this information, our system firstly converts this data into structured data. For this, natural language processing NLP approaches will be used.
The system will have the option to retrieve the data, to make it helpful for making a diagnosis. Our methodology will use the NLP pipeline to extract data from past medical diagnoses written in natural language, that constitute the knowledge base of our system. The textual information provided to the system will be analyzed through NLP to make a diagnosis of patients. After the database (inner) system will be designed, the next step is to design a frontend for the system. Following factors would be kept in mind while designing frontend:
The system will be installed in all those departments of hospitals, where the hospitals need the systems, such as: in reception, in pharmacy, in laboratory and others. This system will be general so that it can be used in the whole hospital or any particular department depending on the requirement of the hospital.
Finally, the data will be shared through a server. The data will be shared from one department to another, so that all the system will become centralized and every department will get all the data of patient online, keeping in mind that the data should reach timely, and should be updated from time to time.
Some of the benefits that can be achieved from the implementation of this project are:
At the end of our project, we expect to have a proper online-based system for the hospitals, that can solve the problems of the traditional systems, and provides an ease to auto-keep, auto-manage, and auto-retrieve medical records.
| Item Name | Type | No. of Units | Per Unit Cost (in Rs) | Total (in Rs) |
|---|---|---|---|---|
| Server System (Processor Type: Core i3-9100 RAM Size: 4GB DDR4 Hard Dr | Equipment | 1 | 68500 | 68500 |
| External Hard Drive (160GB) | Equipment | 1 | 1500 | 1500 |
| Transport | Miscellaneous | 20 | 300 | 6000 |
| Miscellaneous | 4 | 1000 | 4000 | |
| Total in (Rs) | 80000 |
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