BACKGROUND AND OBJECTIVES

Mechanical ventilators are essential albeit expensive equipment to support critically ill patients who have gone into respiratory failure. Adequate numbers should always be available to ensure that a hospital provides the optimal care to patients but the number of patients requiring them at any one time is unpredictable. Finding therefore the best balance in providing adequate ventilator numbers while ensuring the financial sustainability of a hospital is important.

A quantitative method using Monte Carlo Simulation was used to identify the optimal strategy for acquiring ventilators in a large private tertiary medical center in Metro Manila. The number of ventilators needed to provide ventilator needs 90% of the days per month (27/30) was determined using historical data on ventilator use over a period of four years. Four acquisition strategies were investigated: three ownership strategies (outright purchase, installment, and staggered purchase) and a rental strategy. Return on Investment (ROI), Internal Rate of Return (IRR), Modified Internal Rate of Return (MIRR), Net Present Value (NPV), and Payback period (or Breakeven Point) for each strategy were determined to help recommend the best strategy. A qualitative survey was also conducted among doctors, nurses, and respiratory therapists who were taking care of patients hooked to ventilators to find out their experiences comparing hospital-owned and rental ventilators.

It was found that a total of 11 respirators were needed by the hospital to ensure that enough respirators were available for its patients at least 90% of the days in any month based on the previous four-year period. This meant acquiring three more ventilators as the hospital already owned eight. Among the strategies studied, projected over a 10-year period, the installment strategy (50% down payment with 0% interest over a 5-year period) proved to be the most financially advantageous with ROI = 9.36 times, IRR = 97% per year, MIRR = 26% per year, NPV = ₱39,324,297.60 and Payback period = 1.03 years). A more realistic installment strategy with 15% (paid quarterly or annually) and 25% annual interest rates were also explored with their financial parameters quite like but not as good as the 0% interest. The outright purchase of three ventilators came in lower (ROI = 4.53 times, IRR = 55% per year, MIRR = 19% per year, NPV = ₱38,064,297.60 and Payback period = 1.81 years) followed last by staggered purchase with ROI = 3.56 times, IRR = 64% per year, MIRR = 28% per year, NPV = ₱29,905,438.08, and payback period of 2.06 years. As there was no investment needed for the rental strategy, the only financial parameter available for it is the NPV which came out as ₱21,234,057.60.

The qualitative part of the study showed that most of the healthcare workers involved in the care of patients attached to the ventilator were aware of the rental ventilators. The rental ventilators were generally described as of lower functionality and can more easily break down. The respondents almost uniformly expressed a preference for the hospital-owned ventilators.

This analysis showed that the best ventilator ownership strategy from a purely financial perspective for this hospital is by installment with a 50% down payment and 0% interest. Moderate rates of 15% and 25% interest per year were also good. These were followed by outright purchase and lastly by staggered purchase. The rental strategy gave the lowest cumulative 10-year income compared to any of the ownership strategies, but may still be considered good income because the hospital did not make any investment. However, it seems that most of the healthcare workers involved in taking care of patients on ventilators thought the rental ventilators were of lower quality and preferred the hospital-owned ventilators.

Traditional manual testing of ventilator performance is labor-intensive, time-consuming, and prone to errors in data recording, making it difficult to meet the current demands for testing efficiency in the development and manufacturing of ventilators. Therefore, in this study we designed an automated testing system for essential performance parameters of ventilators. The system mainly comprises a ventilator airflow analyzer, an automated switch module for simulated lungs, and a test control platform. Under the control of testing software, this system can perform automated tests of critical performance parameters of ventilators and generate a final test report. To validate the effectiveness of the designed system, tests were conducted on two different brands of ventilators under four different operating conditions, comparing tidal volume, oxygen concentration, and positive end expiratory pressure accuracy using both the automated testing system and traditional manual methods. Bland-Altman statistical analysis indicated good consistency between the accuracy of automated tests and manual tests for all respiratory parameters. In terms of testing efficiency, the automated testing system required approximately one-third of the time needed for manual testing. These results demonstrate that the designed automated testing system provides a novel approach and means for quality inspection and measurement calibration of ventilators, showing broad application prospects.
Ventilators, Mechanical/standards* ; Equipment Design ; Humans ; Automation

With the continuous advancement and innovation in medical equipment technology, the transition between high-flow oxygen therapy, non-invasive ventilation, and invasive ventilation can be easily achieved by adjusting the ventilation mode of ventilators. During the weaning phase for tracheotomized patients, it is necessary to disconnect the ventilator circuit, change the ventilator mode, and gradually extend the weaning time to achieve complete ventilator liberation. During the weaning process, due to patients' excessive dependence on the ventilator, there may be situations where respiratory endpoints and Y-connectors of the ventilator are reconnected for invasive ventilation. However, during the weaning process, the Y-connector and expiratory end connectors are exposed to the air, which cannot ensure the tightness of the ventilator circuit, easily increasing the probability of ventilator circuit contamination and subsequently the risk of ventilator-associated pneumonia (VAP). To overcome these issues, the research team of department of critical care medicine of Zhongda Hospital Southeast University has designed a ventilator circuit interface protective device for weaning and has obtained a National Utility Model Patent of China (ZL 2023 2 1453385.8). The main body of the protective device is a Y-connector plug, consisting of multiple components, including a sealing piece, a protective cover, a sealing plug, an interface 1 (connects with the patient's tracheal tube), an interface 2 (connects with the respiratory branch of the ventilator), and an interface 3 (connects with the expiratory branch of the ventilator), featuring a unique design and easy operation. During the patient's weaning training process, the interface 1 and interface 2 is disconnected from the patient's tracheal tube and respiratory branch, respectively. The interface 1 is plugged with a stopper, and the interface 2 is covered with a protective cover to ensure the tightness of the expiratory branch and Y-connector of the ventilator. During the period when the patient is using the ventilator, the protective cover and plug are removed, and connecting them together ensures the tightness of the device itself, reducing the incidence of VAP caused by ventilator circuit contamination, avoiding nosocomial infections, and shortening the prolonged use of invasive ventilation, increased complication rate, extended hospital stay, and increased medical cost associated with weaning.
Humans ; Ventilator Weaning/methods* ; Equipment Design ; Ventilators, Mechanical ; Respiration, Artificial/instrumentation* ; Pneumonia, Ventilator-Associated/prevention & control*

Background and Objectives: Mechanical ventilators are essential albeit expensive equipment to support critically ill patients who have gone into respiratory failure. Adequate numbers should always be available to ensure that a hospital provides the optimal care to patients but the number of patients requiring them at any one time is unpredictable. Finding therefore the best balance in providing adequate ventilator numbers while ensuring the financial sustainability of a hospital is important. Methods: A quantitative method using Monte Carlo Simulation was used to identify the optimal strategy for acquiring ventilators in a large private tertiary medical center in Metro Manila. The number of ventilators needed to provide ventilator needs 90% of the days per month (27/30) was determined using historical data on ventilator use over a period of four years. Four acquisition strategies were investigated: three ownership strategies (outright purchase, installment, and staggered purchase) and a rental strategy. Return on Investment (ROI), Internal Rate of Return (IRR), Modified Internal Rate of Return (MIRR), Net Present Value (NPV), and Payback period (or Breakeven Point) for each strategy were determined to help recommend the best strategy. A qualitative survey was also conducted among doctors, nurses, and respiratory therapists who were taking care of patients hooked to ventilators to find out their experiences comparing hospital-owned and rental ventilators. Results: It was found that a total of 11 respirators were needed by the hospital to ensure that enough respirators were available for its patients at least 90% of the days in any month based on the previous four-year period. This meant acquiring three more ventilators as the hospital already owned eight. Among the strategies studied, projected over a 10-year period, the installment strategy (50% down payment with 0% interest over a 5-year period) proved to be the most financially advantageous with ROI = 9.36 times, IRR = 97% per year, MIRR = 26% per year, NPV = ₱39,324,297.60 and Payback period = 1.03 years). A more realistic installment strategy with 15% (paid quarterly or annually) and 25% annual interest rates were also explored with their financial parameters quite like but not as good as the 0% interest. The outright purchase of three ventilators came in lower (ROI = 4.53 times, IRR = 55% per year, MIRR = 19% per year, NPV = ₱38,064,297.60 and Payback period = 1.81 years) followed last by staggered purchase with ROI = 3.56 times, IRR = 64% per year, MIRR = 28% per year, NPV = ₱29,905,438.08, and payback period of 2.06 years. As there was no investment needed for the rental strategy, the only financial parameter available for it is the NPV which came out as ₱21,234,057.60. The qualitative part of the study showed that most of the healthcare workers involved in the care of patients attached to the ventilator were aware of the rental ventilators. The rental ventilators were generally described as of lower functionality and can more easily break down. The respondents almost uniformly expressed a preference for the hospital-owned ventilators. Conclusion This analysis showed that the best ventilator ownership strategy from a purely financial perspective for this hospital is by installment with a 50% down payment and 0% interest. Moderate rates of 15% and 25% interest per year were also good. These were followed by outright purchase and lastly by staggered purchase. The rental strategy gave the lowest cumulative 10-year income compared to any of the ownership strategies, but may still be considered good income because the hospital did not make any investment. However, it seems that most of the healthcare workers involved in taking care of patients on ventilators thought the rental ventilators were of lower quality and preferred the hospital-owned ventilators.
Ventilators, Mechanical

The setting and adjustment of ventilator parameters need to rely on a large amount of clinical data and rich experience. This paper explored the problem of difficult decision-making of ventilator parameters due to the time-varying and sudden changes of clinical patient's state, and proposed an expert knowledge-based strategies for ventilator parameter setting and stepless adaptive adjustment based on fuzzy control rule and neural network. Based on the method and the real-time physiological state of clinical patients, we generated a mechanical ventilation decision-making solution set with continuity and smoothness, and automatically provided explicit parameter adjustment suggestions to medical personnel. This method can solve the problems of low control precision and poor dynamic quality of the ventilator's stepwise adjustment, handle multi-input control decision problems more rationally, and improve ventilation comfort for patients.
Humans ; Ventilators, Mechanical ; Respiration, Artificial ; Neural Networks, Computer

In order to effectively treat respiratory diseases, a non-invasive positive pressure ventilator system is designed, the overall structure design of the system is proposed, and the hardware construction is completed. The breathing state of the patient is identified by the threshold triggering method of the flow rate of change, and the calculation of the flow rate of change is realized by the least squares method. At the same time, the breathing parameters are calculated in real time according to the flow-time and pressure-time characteristic curves. In addition, CMV, CPAP, BiPAP and PSV ventilation modes are also implemented. Finally, the parameter measurement accuracy and ventilation mode setting tests are carried out. The results show that the calculation of key breathing parameters provided by the system meets the relevant standards, and supports the stable output of 4 ventilation modes at the same time, provides breathing treatment for patients, and meets the basic functional requirements of the ventilator.
Humans ; Ventilators, Mechanical ; Respiration

Ventilator is an important medical instrument which can replace the function of autonomous ventilation artificially. Its safety and reliability are related to the health and even life safety of patients. With the publishing of the new national standard and international standard for ventilators, higher requirements are put forward for the detection and evaluation. This study mainly introduces an automatic test system for ventilator performance. The test system is based on PF-300 air-flow analyzer of Imtmedical and standard simulation lung. The automatic switch module of simulation lung is developed, and the automatic test system of ventilator is designed using the software development platform based on Python. It can not only automatically test all ventilation control parameters and monitoring parameters of the ventilator, but also realize automatic data recording, form reports and data analysis, and improve the efficiency and quality of inspection, detection and quality control.
Humans ; Reproducibility of Results ; Ventilators, Mechanical ; Computer Simulation ; Data Analysis ; Quality Control

In order to solve the problems of quality control and traceability of medical test lung for meeting the calibration conditions of JJF 1234-2018 Calibration Specification for Ventilators, the calibration device and method are researched for compliance and airway resistance of medical test lung in this paper. A calibration device for medical test lung is designed using constant volume active piston technology to simulate human breathing. Through comparison experiment, the deviation between this device and the similar foreign device can be found. The deviation is lower than 0.4% for lung compliance and lower than 0.7% for airway resistance. The calibration of lung compliance and airway resistance can be completed by this device. This device has a clear and complete traceability path to ensure quality control from the source. The calibration of ventilator is improved. This paper provides a reference for related metrology departments and medical institutions to study on quality inspection of respiratory medical instruments.
Humans ; Calibration ; Ventilators, Mechanical ; Respiration ; Quality Control ; Lung

The need for mechanical ventilation due to severe hypoxemia and acute respiratory distress syndrome has increased dramatically in the global pandemic of severe respiratory infectious diseases. In clinical scenarios, it is sometimes necessary to briefly disconnect the ventilator pipeline from the artificial airway. Still, this operation can lead to a sharp drop in airway pressure, which is contrary to the protective lung ventilation strategy and increases the risk of environmental exposure to bioaerosol, posing a serious threat to patients and medical workers. At present, there is yet to be a practical solution. A new artificial airway device was designed by the medical staff from the department of critical care medicine of Beijing Tiantan Hospital, Capital Medical University, based on many years of research experience in respiratory support therapy, and recently obtained the National Utility Model Patent of China (ZL 2019 2 0379605.4). The device comprises two connecting pipes, the sealing device body, and the globe valve represented by the iridescent optical ring. It has a simple structure, convenient operation, and low production cost. The device is installed between the artificial airway and the ventilator pipeline and realizes the instantaneous sealing of the artificial airway by adjusting the shut-off valve. Using this device to treat mechanically ventilated patients can minimize the ventilator-induced lung injury caused by the repeated disconnection of pipelines, avoid iatrogenic transmission of bioaerosols, and realize dual protection for patients and medical workers. It has extensive clinical application prospects and high health and economic value.
Humans ; Respiration, Artificial/adverse effects* ; Ventilators, Mechanical/adverse effects* ; Respiratory Distress Syndrome/therapy* ; Ventilator-Induced Lung Injury/prevention & control* ; Hypoxia/complications*

OBJECTIVE: To find out the circuit pressure and flow at the trigger point by observing the characteristics of the inspiratory trigger waveform of the ventilator, confirm the intra-alveolar pressure as the index to reflect the effort of the trigger according to the working principle of the ventilator combined with the laws of respiratory mechanics, establish the related mathematical formula, and analyze its influencing factors and logical relationship. METHODS: A test-lung was connected to the circuit in a PB840 ventilator and a SV600 ventilator set in pressure-support mode. The positive end-expiratory pressure (PEEP) was set at 5 cmH₂O (1 cmH₂O ≈ 0.098 kPa), and the wall of test-lung was pulled outwards till an inspiratory was effectively triggered separately in slow, medium, fast power, and separately in flow-trigger mode (sensitivity V_Trig 3 L/min, 5 L/min) and pressure-trigger mode (sensitivity P_Trig 2 cmH₂O, 4 cmH₂O). By adjusting the scale of the curve in the ventilator display, the loop pressure and flow corresponding to the trigger point under different triggering conditions were observed. Taking intraalveolar pressure (Pa) as the research object, the Pa (called P_a-T) needed to reach the effective trigger time (T_T) was analyzed in the method of respiratory mechanics, and the amplitude of pressure change (ΔP) and the time span (ΔT) of Pa during triggering were also analyzed. RESULTS: (1) Corresponding relationship between pressure and flow rate at TT time: in flow-trigger mode, in slow, medium and fast trigger, the inhalation flow rate was V_Trig, and the circuit pressure was separately PEEP, PEEP-Pn, and PEEP-Pn' (Pn, Pn', being the decline range, and Pn' > Pn). In pressure-trigger mode, the inhalation flow rate was 1 L/min (PB840 ventilator) or 2 L/min (SV600 ventilator), and the circuit pressure was PEEP-P_Trig. (2) Calculation of P_a-T: in flow-trigger mode, in slow trigger: P_a-T = PEEP-V_TrigR (R represented airway resistance). In medium trigger: P_a-T = PEEP-Pn-V_TrigR. In fast trigger: P_a-T = PEEP-Pn'-V_TrigR. In pressure-trigger mode: P_a-T = PEEP-P_Trig-1R. (3) Calculation of ΔP: in flow trigger mode, in flow trigger: without intrinsic PEEP (PEEPi), ΔP = V_TrigR; with PEEPi, ΔP = PEEPi-PEEP+V_TrigR. In medium trigger: without PEEPi, ΔP = Pn+V_TrigR; with PEEPi, ΔP = PEEPi-PEEP+Pn+V_TrigR. In fast trigger: without PEEPi, ΔP = Pn'+V_TrigR; with PEEPi, ΔP = PEEPi-PEEP+Pn'+V_TrigR. In pressure-trigger mode, without PEEPi, ΔP = P_Trig+1R; with PEEPi, ΔP = PEEPi-PEEP+P_Trig+1R. (4) Pressure time change rate of Pa (F_P): F_P = ΔP/ΔT. In the same ΔP, the shorter the ΔT, the greater the triggering ability. Similarly, in the same ΔT, the bigger the ΔP, the greater the triggering ability. The FP could better reflect the patient's triggering ability. CONCLUSIONS The patient's inspiratory effort is reflected by three indicators: the minimum intrapulmonary pressure required for triggering, the pressure span of intrapulmonary pressure, and the pressure time change rate of intrapulmonary pressure, and formula is established, which can intuitively present the logical relationship between inspiratory trigger related factors and facilitate clinical analysis.
Humans ; Respiration, Artificial/methods* ; Positive-Pressure Respiration ; Lung ; Ventilators, Mechanical ; Respiratory Mechanics