HIV-MSS: A user-friendly management support system for better planning of HIV care services.

The advent of antiretroviral therapy (ART) has transformed HIV infection from a deadly disease to a manageable chronic condition. The life expectancy of people living with HIV has been prolonged dramatically. Therefore, health systems are now confronted with new challenges, with ever-increasing number of newly diagnosed cases, fuelling the pool of existing patients, with many comorbidities and requiring hospital admissions. Are health systems prepared to handle large and increasing numbers of people with HIV? We developed a HIV-Management Support System (MSS) to support service evaluation and management using simulation by capturing individual patient's pathways within HIV services in the United Kingdom. Two scenarios were tested: (1) the impact of increasing the number of diagnosed cases in steps of 5% on human resources and (2) the impact of treating all patients with ART on hospital admissions. A 5% increase in newly diagnosed HIV cases increases human resource requirements between 4% and 8%, whereas the impact of treating all HIV patients with ART on hospital admissions is far greater. HIV services are under intense pressure and managing patient and service needs are far more important than ever, hence the development of our HIV MSS is timely, to support better planning of services. Note that the HIV simulation model presented in this study is the first of its kind.

Modelling the neonatal system: A joint analysis of length of stay and patient pathways.

In the United Kingdom, one in seven babies require specialist neonatal care after birth, with a noticeable increase in demand. Coupled with budgeting constraints and lack of investment means that neonatal units are struggling. This will inevitably have an impact on baby's length of stay (LoS) and the performance of the service. Models have previously been developed to capture individual babies' pathways to investigate the longitudinal cycle of care. However, no models have been developed to examine the joint analysis of LoS and babies' pathways. LoS at each stage of care is a critical driver of both the clinical outcomes and economic performance of the neonatal system. Using the generalized linear mixed modelling approach, extended to accommodate multiple outcomes, the association between neonate's pathway to discharge and LoS is examined. Using the data about 1002 neonates, we noticed that there is a high positive association between baby's pathway and total LoS, suggesting that discharge policies needs to be looked at more carefully. A novel statistical approach that examined the association of key outcomes and how it evolved over time is developed. Its applicability can be extended to other types of long-term care or diseases, such as heart failure and stroke.

Co-crystal of Tramadol-Celecoxib Versus Tramadol or Placebo for Acute Moderate-to-Severe Pain After Oral Surgery: Randomized, Double-Blind, Phase 3 Trial (STARDOM1).

INTRODUCTION: Co-crystal of tramadol-celecoxib (CTC) is the first analgesic co-crystal for acute pain. This completed phase 3 multicenter, double-blind trial assessed the efficacy and safety/tolerability of CTC in comparison with that of tramadol in the setting of moderate-to-severe pain up to 72 h after elective third molar extraction requiring bone removal. METHODS: Adults (n = 726) were assigned randomly to five groups (2:2:2:2:1): orally administered twice-daily CTC 100 mg (44 mg rac-tramadol hydrochloride/56 mg celecoxib; n = 164), 150 mg (66/84 mg; n = 160) or 200 mg (88/112 mg; n = 160); tramadol 100 mg four times daily (n = 159); or placebo four times daily (n = 83). Participants in CTC groups also received twice-daily placebo. The full analysis set included all participants who underwent randomization. The primary endpoint was the sum of pain intensity differences over 0 to 4 h (SPID0-4; visual analog scale). Key secondary endpoints included 4-h 50% responder and rescue medication use rates. Safety endpoints included adverse events (AEs), laboratory measures, and Opioid-Related Symptom Distress Scale (OR-SDS) score. RESULTS: All CTC doses were superior to placebo (P < 0.001) for primary and key secondary endpoints. All were superior to tramadol for SPID0-4 (analysis of covariance least squares mean differences [95% confidence interval]: - 37.1 [- 56.5, - 17.6], - 40.2 [- 59.7, - 20.6], and - 41.7 [- 61.2, - 22.2] for 100, 150, and 200 mg CTC, respectively; P < 0.001) and 4-h 50% responder rate. Four-hour 50% responder rates were 32.9% (CTC 100 mg), 33.8% (CTC 150 mg), 40.6% (CTC 200 mg), 20.1% (tramadol), and 7.2% (placebo). Rescue medication use was lower in the 100-mg (P = 0.013) and 200-mg (P = 0.003) CTC groups versus tramadol group. AE incidence and OR-SDS scores were highest for tramadol alone. CONCLUSIONS: CTC demonstrated superior pain relief compared with tramadol or placebo, as well as an improved benefit/risk profile versus tramadol. TRIAL REGISTRATION: ClinicalTrials.gov identifier, NCT02982161; EudraCT number, 2016-000592-24.

Efficacy and safety of co-crystal of tramadol-celecoxib (CTC) in acute moderate-to-severe pain after abdominal hysterectomy: A randomized, double-blind, phase 3 trial (STARDOM2).

BACKGROUND: STARDOM2 is a randomized, double-blind, phase 3 trial evaluating the efficacy and safety of co-crystal of tramadol-celecoxib (CTC)-a first-in-class analgesic co-crystal comprising racemic tramadol hydrochloride and celecoxib in a supramolecular network that modifies their pharmacokinetic properties-for the management of acute postoperative pain (NCT03062644; EudraCT:2016-000593-38). METHODS: Patients with moderate-to-severe pain following abdominal hysterectomy were randomized 2:2:2:2:2:1 to oral CTC 100 mg (rac-tramadol hydrochloride 44 mg/celecoxib 56 mg) twice daily (BID); CTC 150 mg (66/84 mg) BID; CTC 200 mg (88/112 mg) BID; immediate-release tramadol 100 mg four times daily (QID); celecoxib 100 mg BID; or placebo, for 5 days. The primary endpoint was the sum of pain intensity differences over 0-4 h (SPID0-4 ). Key secondary endpoints were rescue medication use within 4 h, 50% response rate at 4 h, and safety/tolerability. RESULTS: Of 1355 patients enrolled, 1138 were randomized (full analysis set) and 1136 treated (safety analysis set). In the prespecified gatekeeping analysis of SPID0-4 , CTC 200 mg was not superior to tramadol but showed non-inferior efficacy (p < 0.001) that was sustained throughout the 120-h period, despite a 5-day cumulative tramadol administration of 880 mg with CTC 200 mg BID versus 2000 mg with tramadol 100 mg QID. Treatment-emergent adverse events (TEAEs) and severe TEAEs were less common with CTC 200 mg versus tramadol. Treatment-related TEAEs were 14.4% with CTC 200 mg and 23.6% with tramadol. CONCLUSIONS: Although the study did not meet its primary endpoint, CTC 200 mg showed a clinically relevant improvement in overall benefit/risk profile versus tramadol alone, with considerably lower cumulative opioid exposure. SIGNIFICANCE: In the randomized, double-blind, phase 3 STARDOM2 trial-in acute moderate-to-severe pain after abdominal hysterectomy-the novel co-crystal of tramadol-celecoxib (CTC) 200 mg BID was superior to placebo and non-inferior to tramadol 100 mg QID. Although superiority to tramadol was not reached, CTC 200 mg BID exposed patients to lower cumulative opioid (tramadol) doses than tramadol (100 mg QID) alone, with fewer treatment-emergent adverse events. CTC 200 mg thus has a clinically relevant improved benefit/risk profile compared with tramadol alone.

Impact of pre-exposure and post-exposure prophylaxes prevention programme on HIV burden and services in a low-resource setting: a simulation modelling approach.

INTRODUCTION: sub-Saharan African countries contribute substantially to the global HIV disease burden. Despite this burden, and the promises that prevention could deliver, the implementation and uptake of HIV prevention programmes are still low. The study used the decision support system model to explore the potential impacts of prevention implementation on HIV burden (incidence) and service delivery. METHODS: an operational research technique known as discrete event simulation model was used to capture an individual patient´s pathways through the HIV care process from diagnosis to treatment and monitoring. The regular monitoring, over a 5-year period, including all the activities and resources utilized at each stage of the pathway were analysed, and the impact of increasing prevention measures for an HIV treatment service in a treatment centre in Nigeria was tested using the simulation model. RESULTS: forty-three patients currently access the Pre-Exposure Prophylaxis (PrEP) and Post Exposure Prophylaxis (PEP) annually, with a 20% and 80% split in the number of patients offered PrEP and PEP, respectively. Scenarios-based on increasing the number of people offered PrEP and PEP from 43 to 250 with a 50/50 split were tested. The outputs revealed improved preventive care by averting new HIV cases, reduction in service demand and utilization, but an increase in the required human resource as well as financial burden. In the next 5 years, the cumulative averted HIV cases are expected to increase from 2 and 5 people (baseline) to 24 and 20 people for PrEP and PEP, respectively. The potentially averted 2 cases per infected persons based on the basic reproductive number of HIV. CONCLUSION: the effective implementation of PrEP/PEP programme offers an additional safety measure to prevent HIV transmission in at-risk individuals and possibility of ending HIV epidemic.

Profiling hospitals based on emergency readmission: a multilevel transition modelling approach.

Emergency readmission is seen as an important part of the United Kingdom government policy to improve the quality of care that patients receive. In this context, patients and the public have the right to know how well different health organizations are performing. Most methods for profiling estimate the expected numbers of adverse outcomes (e.g. readmission, mortality) for each organization. A number of statistical concerns have been raised, such as the differences in hospital sizes and the unavailability of relevant data for risk adjustment. Having recognized these statistical concerns, a new framework known as the multilevel transition model is developed. Hospital specific propensities of the first, second and further readmissions are considered to be measures of performance, where these measures are used to define a new performance index. During the period 1997 and 2004, the national (English) hospital episodes statistics dataset comprise more than 5 million patient readmissions. Implementing a multilevel model using the complete population dataset could possibly take weeks to estimate the parameters. To resolve the problem, we extract 1000 random samples from the original data, where each random sample is likely to lead to differing hospital performance measures. For computational efficiency a Grid implementation of the model is developed. Analysing the output from the full 1000 sample, we noticed that 4 out of the 5 worst performing hospitals treating cancer patients were in London. These hospitals are known to be the leading NHS Trusts in England, providing diverse range of services to complex patients, and therefore it is inevitable to expect higher numbers of emergency readmissions.

Towards effective capacity planning in a perinatal network centre.

OBJECTIVE: To study the arrival pattern and length of stay (LoS) in a neonatal intensive care/high dependency unit (NICU/HDU) and special care baby unit (SCBU) and the impact of capacity shortage in a perinatal network centre, and to provide an analytical model for improving capacity planning. METHODS: The data used in this study have been collected through the South England Neonatal Database (SEND) and the North Central London Perinatal Network Transfer Audit between 1 January and 31 December 2006 for neonates admitted and refused from the neonatal unit at University College London Hospital (UCLH). Exploratory data analysis was performed. A queuing model is proposed for capacity planning of a perinatal network centre. OUTCOME MEASURES: Predicted number of cots required with existing arrival and discharge patterns; impact of reducing LoS. RESULTS: In 2006, 1002 neonates were admitted to the neonatal unit at UCLH, 144 neonates were refused admission to the NICU and 35 to the SCBU. The model shows the NICU requires seven more cots to accept 90% of neonates into the NICU. The model also shows admission acceptance can be increased by 8% if LoS can be reduced by 2 days. CONCLUSIONS: The arrival, LoS and discharge of neonates having gestational ages of <27 weeks were the key determinants of capacity. The queuing model can be used to determine the cot capacity required for a given tolerance level of admission rejection.