Hospital bed booking management systems became a pivotal practice after the National Health Service’s statement rule on patient’s emergency trolley waiting hours. After an accident, inconvenient waiting hours in hospital waiting halls due to improper operational capacity planning and control over managing, allotting, and maintaining beds may turn frustrating when emergency care is required. The lack of real-time data analysis provides a disadvantage resulting in patient overcrowding and malefactions in inpatient bed booking services during emergencies.
Monitoring and managing inpatient-outpatient capacity & patient inflows can be challenging tasks during emergencies. Unplanned inventory, the inability of beds, and other scarce resources may lead to poor operations, and that affects the hospital’s goodwill. The data integrated robust bed booking management systems improve healthcare services by optimizing operations. The digitalized data-driven hospital bed booking management system is a process in which, it has a real-time status of all the available beds and the bed occupied, to plan for the efficient use of beds. It helps the staff and management by reducing the time of counting and recording the availability of. It includes predictive planning, altering beds during emergencies, improved individual patient care, efficiency in diagnosis, and systematized operations.
The hospital bed booking management system is a fusion and integration of various systems, which perform and fulfil distinct operations at the basic level of hospital management. The systems include EHR (electronic health records), ADT system (admission, discharge, and transfer system), emergency department information system, and BMS (bed management system). Utilizing the mentioned technologies and their significant insights help in determining a flowchart of hospital operations that can better the existing bed management system. The optimized hospital information helps in better operations during addressing accidental & emergency cases, medical assessment cases, and patients transferred from other hospitals for better treatment.
ADT system: The admission, discharge, and transfer systems are popularly known as ADT that digitally records information regarding patient status, medication details, allotted bed duration, etc. The ADT system is a digital data analytical tool that uses data analysis to predict and provide real-time information on patient demographic data. The accessibility of analyzing this information can provide an advantage in understanding each bed status in a particular ward for better hospital operations. During an A&E (accident or emergency) situation, the time in allotting and shifting reserved patients to vacant beds can be reduced by announcing the list of available beds in different wards. It helps in taking preventive action against emergencies in a hospital. EHR systems: An electronic health records system is a digital tabulation of patients’ paper charts that provide real-time instant access to individual patient history for authorized users. The data stored in EHR is in an unstructured format. Leveraging NLP tools help in analyzing, interpreting, and decoding valuable insights from data. These insights can predict the chance of re-admissions of old patients, outpatient records, and realtime status of admitted patients. Hence with this data, the hospital operations management can divide and calculate the no. of beds available for occupancy in every ward and the reserved time and date of regular patients who often visit the hospital for checkups.
A&E portal plays a vital role in hospital bed management as 85% of the cases where the hospital runs out of resources is during emergency and accidental mishaps. Predicting and analyzing real-time data and follow up of hospital operations is crucial during this situation. The emergency data information system is integrated with electronic patient records that provide suitable information for clinical and hospital management to tackle emergencies. Information provided supports patient care and operations information, efficient treatment for better cure, notifications on shortage of inventory, and prioritizes in increasing hospital revenues.
The hospital bed management system provides real-time data access to staff and senior management regarding vacant, preoccupied, reserved information of beds through digital dashboard. The HBBMS is systematically interconnected with other systems like ADT, EDIS, and EHR for obtaining, resourcing, and analyzing real-time data.
Tracking all the activities of the patient from the day he has admitted plays a very crucial role. The Hospital Bed Management service must not only allocate the beds but also has to record all the medical records of the patient from the day one till he gets discharged. The system has to record all the details of the patient for future reference.
Hospital Bed Management services are easy to access, a person with little knowledge about the concept can easily take care about the Hospital Bed Management System, as it is very clear and plain to understand, and the other important feature of this system is that it records and tracks all the data about the patient from the day, he got admitted to the date, he got discharged, and even this process can be done easily without any inconvenience.
HBBMS lessens time spent by staff and senior staff in physically counting and recording bed information and with BMS as every staff in a hospital has required information regarding a particular patient on a particular bed, helps in offering better treatment and diagnosis procedure. With the availability of A&E information, HBBMS provides real-time information regarding hospital inventory and resource management.
Ease of flow between intra and internal department communications.
It helps in ending up patients’ long waiting hours, treatments in unhygienic environment, and Oxygen availability transferring to other hospitals.
It improves time management to eradicate delays in surgeries and operation cancellations due to the unavailability of OT.
Better management of internal resources and provides guided instructions for housekeeping in bedding that increases personal patient care.
Clear understanding of every patient through pre-designed diagnosis for each bed defined with a distinct bed number.
Helps in bed assignment operations through data mismatch.
Improving patients care by understanding patient demographics.
Helps in designing and developing new models for better management of inventory.
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