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FRANKLIN LAKES, N.J., Oct. 20, 2025 /PRNewswire/ — BD (Becton, Dickinson and Company) (NYSE: BDX), a global leader in medical technology, introduces the BD Incada™ Connected Care Platform, a new scalable, AI-enabled, cloud-based platform that unifies BD device data into one intelligent ecosystem for the first time. The BD Incada™ Platform is available now with the launch of the next-generation BD Pyxis™ Pro Automated Medication Dispensing Solution, creating enterprise-wide visibility and connectivity that transforms data into actionable insight.  

“Our vision for the BD Incada™ Platform is to go beyond legacy connectivity to create meaningful connections across devices from infusion pumps to patient monitors to pharmacy robotics, and unify data from those solutions into one ecosystem, transforming data into clear, actionable insights for care teams,” said Bilal Muhsin, EVP and President of BD Connected Care. “These launches represent key milestones in BD’s Connected Care strategy, where we are uniquely positioned with our broad portfolio from pharmacy to bedside, to leverage game-changing technology to drive meaningful benefits for our customers.”

AI-powered analytics to drive smarter, faster decisions

Built on Amazon Web Services’ (AWS) on-demand cloud computing infrastructure, the BD Incada™ Platform leverages the latest in AI technologies, such as natural language search in analytics, and is scalable to meet the data volumes created by nearly 3 million smart connected BD devices. With Analytics in the BD Incada™ Platform, data from BD’s leading medication management solutions now flows through a secure, cloud platform and enables:

• Enterprise-wide visibility into medication inventory, which helps clinicians identify patterns and ensure medication availability, reduce medication waste and improve labor efficiency
• The ability to ask natural language questions and receive AI-powered insights and analytics on demand
• User-customizable dashboards that empower frontline clinical teams to act on insights quickly

Flexible, secure storage to get the right medication to the right patient, faster

The new BD Pyxis™ Pro Dispensing Solution delivers smarter, more secure medication storage, which enables faster access at the point of care. The first-of-its-kind flexible, stackable device configuration offers more medication storage capacity to improve medication availability from refrigerated to ambient storage. The BD Pyxis™ Pro Dispensing Solution allows hospitals and health systems to easily adapt to the evolving needs of their patient populations, with features including:

• Expanded capacity in a similar footprint, enabling clinicians to add up to 538 multi-access or 98 secure pockets without taking more space in their medication rooms
• Enhanced security features to improve controlled substance management and medication safety efforts
• More efficient access, with RFID badge scanning, wireless barcode scanners and illuminated bins to streamline medication retrieval

“For over 35 years, the BD Pyxis™ System has been the backbone of medication management across hospitals and health systems, with more than 9.8 million transactions on BD Pyxis™ devices every day,” said Connor Bates, Worldwide President for Medication Management Solutions at BD. “With the enhanced secure capacity, durability and AI-powered analytics of the next-generation BD Pyxis™ Pro Dispensing Solution, we’re ushering in a transformative new era for medication management.”

Together, the BD Incada™ Platform and BD Pyxis™ Pro Dispensing Solution sets a new standard for unified, data-driven healthcare operations.

About BD
BD is one of the largest global medical technology companies in the world and is advancing the world of health by improving medical discovery, diagnostics, and the delivery of care. The company supports the heroes on the frontlines of health care by developing innovative technology, services and solutions that help advance both clinical therapy for patients and clinical process for health care providers. BD and its more than 70,000 employees have a passion and commitment to help enhance the safety and efficiency of clinicians’ care delivery process, enable laboratory scientists to accurately detect disease and advance researchers’ capabilities to develop the next generation of diagnostics and therapeutics. BD has a presence in virtually every country and partners with organizations around the world to address some of the most challenging global health issues. By working in close collaboration with customers, BD can help enhance outcomes, lower costs, increase efficiency, improve safety, and expand access to health care. For more information on BD, please visit bd.com or connect with us on LinkedIn at www.linkedin.com/company/bd1/, X (formerly Twitter) @BDandCo or Instagram @becton_dickinson. 

SOURCE BD (Becton, Dickinson and Company)

Study design

This randomized, prospective study included 90 patients, aged between 18 and 65, with ASA classification I-II-III, who were scheduled for total knee arthroplasty surgery under spinal anesthesia. Patients with a history of bleeding diathesis, receiving anticoagulant treatment, allergies or sensitivity to local anesthetics and opioid drugs, patients with infection in the area where the block will be applied, pregnancy suspicion, pregnant or breastfeeding mothers, and patients who did not accept the procedure were excluded from the study. Ethical approval was obtained from the Bursa City Hospital Ethics Committee on 07.12.2022, protocol number 2022-17/3. Our study was registered on https://clinicaltrials.gov/ with the number NCT06084403. The patient recording and disribution were illustrated by the Consolidated Standards of Reporting Trials (CONSORT) flowchart (Fig. 1).

Patients were randomized into three groups, each containing 30 patients, using a computer program (Group 20 = group receiving ACB with 20 ml, Group 30 = group receiving ACB with 30 ml, Group 40 = group receiving ACB with 40 ml). The practitioners were blind to the data collection, and patients did not know which volume was applied. Postoperative pain scores and opioid consumption were recorded by a pain technician who was blind to the study.

Anesthesia application

After the patients were taken to the operating room, standard monitoring (electrocardiography, noninvasive arterial blood pressure, and peripheral oxygen saturation) was performed, and premedication was administered with 2 mg intravenous midazolam. For spinal anesthesia, the patients were positioned sitting, and following the necessary asepsis and antisepsis rules, a 25-gauge pencil-point spinal needle (B.Braun, Melsungen, Germany) was inserted into the subarachnoid space through a median approach from L3-4 or L4-5. After observing free clear cerebrospinal flow, 15 mg of hyperbaric bupivacaine was administered. To prevent postoperative nausea and vomiting, 4 mg of ondansetron was given intravenously. Total knee arthroplasty surgery was performed by the same surgical team using the same surgical procedure.

Block interventions

The block procedure was performed after the surgery was completed. All adductor canal blocks were performed by two experienced anesthesiologists with advanced clinical expertise in regional anesthesia. After ensuring aseptic conditions, a high-frequency linear ultrasound probe (GE ML6-15-D Matrix Linear, Boston, USA) was covered with a sterile sheath, and a 100 mm block needle (Stimuplex Ultra^®, Braun, Melsungen, Germany) was used. The linear ultrasound probe was placed medial to the patella, and the probe was advanced cephalad to visualize the femoral artery, the adductor hiatus, and the apex of the femoral triangle. Then, 5 ml of saline was injected under ultrasound guidance into the midpoint of the adductor canal to confirm the block site (Fig. 2). Then, local anesthetic solution containing bupivacaine at 0.25% concentration was administered as 20 ml in Group 20, 30 ml in Group 30, and 40 ml in Group 40.

A Adductor canal sonographic anatomy. Sartorius Muscle, A; artery, V; vein. B Sonographic anatomy of block. Needle direction, and spread of local anesthetic during block performing. A; artery

After the operation, patients were taken to the postoperative recovery room. Patients reaching a score of 9 on the Aldrete scoring system were transferred to the ward.

Postoperative analgesia management

All patients received 0.5 mg/kg of intravenous tramadol and 20 mg of tenoxicam 30 min before the end of the surgical procedure. In the postoperative period, patients received 20 mg of tenoxicam intravenously twice a day. A patient-controlled analgesia (PCA) device was connected to all patients as soon as they were taken to the recovery room. The PCA was prepared with tramadol at a concentration of 5 mg/ml, with a lockout interval of 20 min and a bolus dose of 10 mg without a basal infusion. During the ward follow-ups, hourly NRS scores were monitored. If the NRS score was 4 or above, 0.5 mg/kg of intravenous meperidine was administered as a rescue analgesic. NRS scores at designated times as well as rescue analgesic needs and hours were noted in detail.

Postoperative pain assessment was performed using the NRS scoring system (0 = no pain, 10 = worst pain imaginable). Resting and moving NRS scores were evaluated and recorded at 2, 4, 8, 16, 24, and 48 h. If the NRS score was ≥ 4, 0.5 mg/kg of intravenous meperidine was administered as a rescue analgesic.

Motor block was evaluated using the modified Bromage scale (0: can move leg, foot, and knee freely; 1: normal knee and foot movements, but cannot raise leg straight; 2: cannot flex knee; 3: cannot move foot and knee) [8]. The need for rescue analgesics, postoperative opioid consumption, and side effects such as nausea, vomiting, and itching, as well as complications that may arise due to the block, were recorded.

Sample size calculation

The sample size calculation was performed using G*Power software version 3.1.9.2 (Kiel University, Kiel, Germany). Power analysis based on preliminary data on total opioid consumption [Group 20: 107.86 ± 42.17 (n = 7), Group 30: 88.57 ± 50.14 (n = 7), Group 40: 50.14 ± 51.2 (n = 7)] showed an effect size of 0.49, with a 95% confidence interval, an alpha error of 0.05, and a power of 0.95. Based on this effect size and confidence interval, a sample size of 22 patients per group was calculated to be sufficient. To account for potential dropouts, 30 patients were planned to be enrolled in each group.

Statistical analysis

Statistical analysis was performed with IBM SPSS v20.0 (SPSS Inc., Chicago, Illinois, USA) software package. The normality distribution of variables was checked with the Kolmogorov-Smirnov and histogram tests. Descriptive data were expressed as median [%25–75] and a number. Categorical variables were expressed as a number and analysed using the Chi-square and Fisher exact tests. Non-normally distributed continuous variables were analyzed using the Kruskal-Wallis test, followed by Dunn’s test for post-hoc analysis to assess differences among groups. For the statistical analysis, p < 0.05 was considered statistically significant.