To ensure the sustainability of pharmacy practice and provide health for all, pharmacy as a profession must embrace the digital transformation that has been changing healthcare at a rapid pace. The International Pharmaceutical Federation (FIP) has conducted a global study on digital health in pharmacy education to describe the readiness, adaptability, and responsiveness of pharmacy education programmes to train the current and future pharmaceutical workforce on digital health and to identify the knowledge and skill gaps of the existing pharmaceutical workforce with regard to digital health. An online survey was distributed to collect feedback from academics, pharmacy schools, pharmacists, and pharmacy students. The findings showed that a large proportion of pharmacy schools do not offer any digital health education, and the skillsets and knowledge of how to apply digital health technologies to solve existing clinical problems and improve care have been identified as a gap. The future of pharmacy and pharmaceutical sciences is digital and exciting. A digitally enabled and agile pharmaceutical workforce will capitalise on the benefits of digital health to serve the higher purpose of providing good health and wellbeing for all, leaving no one behind. Therefore, pharmacy and pharmaceutical sciences education should act now.

Background: Ideally, the intensity of postoperative pain should be predicted so as to customize analgesia. The objective of this study was to investigate whether preoperative electrical and pressure pain assessment can predict post-caesarean section pain and analgesic requirement. Materials and Methods: A total of 65 subjects scheduled for elective caesarean section, who gave written informed consent, were studied. Preoperatively, PainMatcher^® was used to evaluate electrical pain threshold, while manual PainTest™ FPN 100 Algometer and digital PainTest™ FPX 25 Algometer determined pressure pain threshold and tolerance. Postoperatively, numerical rating scales were used to assess pain at regular time intervals. Patients received intramuscular pethidine (100mg, 6 hourly), rectal diclofenac (100mg, 12 hourly), and oral paracetamol (1g, p.r.n.) for pain relief. Statistical analysis was conducted using PASW Statistics 18 software. Results: Preoperative electrical pain threshold correlated significantly with post-caesarean pain scores at 6 and 24 hours (r = -0.26, P < 0.02; r = -0.23, P < 0.04, respectively), and with the quantity of paracetamol consumed by the patient within 48 hours of surgery (r = -0.33, P < 0.005). Preoperative pressure pain tolerance measured by PainTest™ FPX 25 Algometer was significantly correlated with pain scores 6 hours postsurgery (r = -0.21, P < 0.05). Pain scores 6 hours post-caesarean section correlated significantly with anesthesia--general or spinal (F = 4.22, v ₁ = 1, v ₂ = 63, P < 0.05). Conclusions: The predictive methods proposed may aid in identifying patients at greater risk for postoperative pain. Electrical pain threshold could be useful in personalizing the postoperative analgesic protocol.

Context: Experimental assessments can determine pain threshold and tolerance, which mirror sensitivity to pain. This, in turn, influences the post-operative experience. Aims: The study intended to evaluate whether the pre-operative pressure and electrical pain tests can predict pain and opioid requirement following cesarean delivery. Settings and Design: Research was conducted on females scheduled for cesarean section at a tertiary care hospital of the state. Twenty women were enrolled, after obtaining written informed consent. Materials and Methods: Pain assessment was performed on the eve of cesarean sections using three devices: PainMatcher; determined electrical pain threshold while the algometers PainTest ^™ FPN100 (manual) and PainTest ^™ FPX 25 (digital) evaluated pressure pain threshold and tolerance. Post-operative pain relief included intravenous morphine administered by patient-controlled analgesia, diclofenac (100 mg, every 12 h, rectally, enforced) and paracetamol (1000 mg, every 4-6 h, orally, on patient request). Pain scores were reported on numerical rating scales at specified time intervals. Statistical Analysis Used: Correlational and regression statistics were computed using IBM SPSS Statistics 21 software (IBM Corporation, USA). Results: A significant correlation was observed between morphine requirement and: (1) electrical pain threshold ( r = -0.45, P = 0.025), (2) pressure pain threshold ( r = -0.41 P = 0.036) and (3) pressure pain tolerance ( r = -0.44, P = 0.026) measured by the digital algometer. The parsimonious regression model for morphine requirement consisted of electrical pain threshold (r ² = 0.20, P = 0.049). The dose of morphine consumed within 48 h of surgery decreases by 0.9 mg for every unit increment in electrical pain threshold. Conclusions: The predictive power of pain sensitivity assessments, particularly electrical pain threshold, may portend post-cesarean outcomes, including opioid requirements.