A discrete event simulation model to evaluate the treatment pathways of patients with cataract in the United Kingdom

Assessing the impact of COVID-19 measures on COPD management and patients: a simulation-based decision support tool for COPD services in the UK

OBJECTIVES

To develop a computer-based decision support tool (DST) for key decision makers to safely explore the impact on chronic obstructive pulmonary disease (COPD) care of service changes driven by restrictions to prevent the spread of COVID-19.

DESIGN

The DST is powered by discrete event simulation which captures the entire patient pathway. To estimate the number of COPD admissions under different scenario settings, a regression model was developed and embedded into the tool. The tool can generate a wide range of patient-related and service-related outputs. Thus, the likely impact of possible changes (eg, COVID-19 restrictions and pandemic scenarios) on patients with COPD and care can be estimated.

SETTING

COPD services (including outpatient and inpatient departments) at a major provider in central London.

RESULTS

Four different scenarios (reflecting the UK government's Plan A, Plan B and Plan C in addition to a benchmark scenario) were run for 1 year. 856, 616 and 484 face-to-face appointments (among 1226 clinic visits) are expected in Plans A, B and C, respectively. Clinic visit quality in Plan A is found to be marginally better than in Plans B and C. Under coronavirus restrictions, lung function tests decreased more than 80% in Plan C as compared with Plan A. Fewer COPD exacerbation-related admissions were seen (284.1 Plan C vs 395.1 in the benchmark) associated with stricter restrictions. Although the results indicate that fewer quality-adjusted life years (in terms of COPD management) would be lost during more severe restrictions, the wider impact on physical and mental health must also be established.

CONCLUSIONS

This DST will enable COPD services to examine how the latest developments in care delivery and management might impact their service during and beyond the COVID-19 pandemic, and in the event of future pandemics.

Recent progress and research trend of anti-cataract pharmacology therapy: A bibliometric analysis and literature review

Cataract is the leading cause of blindness worldwide. Cataract phacoemulsification combined with intraocular lens implantation causes great burden to global healthcare, especially for low- and middle-income countries. Such burden would be significantly relieved if cataracts can effectively be treated or delayed by non-surgical means. Excitingly, novel drugs have been developed to treat cataracts in recent decades. For example, oxysterols are found to be able to innovatively reverse lens clouding, novel nanotechnology-loaded drugs improve anti-cataract pharmacological effect, and traditional Chinese medicine demonstrates promising therapeutic effects against cataracts. In the present review, we performed bibliometric analysis to provide an overview perspective regarding the research status, hot topics, and academic trends in the field of anti-cataract pharmacology therapy. We further reviewed the curative effects and molecular mechanisms of anti-cataract drugs such as lanosterol, metformin, resveratrol and curcumin, and prospected the possibility of their clinical application in future.

Improvement in Activities of Daily Living after Cataract Surgery in the Very Old

BACKGROUND

The benefits of cataract surgery for patients aged ≥90 years in terms of improvements in activities of daily living (ADL) have been poorly evaluated using only limited data. Using a large nationwide administrative database of hospitalized patients, we investigated the improvement of ADL after cataract surgery in the very old (age of ≥90 years).

METHODS

We identified 84,747 patients with cataracts aged 80 to 89 years and 7,253 patients with cataracts aged ≥90 years who underwent cataract surgery in both eyes during hospitalization from April 2014 to March 2015. A retrospective matched-pair cohort study was performed to compare the proportion of patients with improved ADL after cataract surgery. We also compared the length of hospital stay between the two groups.

RESULTS

Patients aged ≥90 years were more likely to be female and have a lower ADL score at admission. In the 1:4 matched-pair analysis with 7,253 versus 29,012 pairs, a lower proportion of patients aged ≥90 years had an improved ADL score (odds ratio, 0.33; 95% confidence interval, 0.29-0.36; P < 0.001) even after adjusting for other variables. Patients aged ≥90 years had a slightly shorter length of hospital stay than those aged 80 to 89 years (7.5 vs. 8.2 days, respectively; P < 0.001).

CONCLUSIONS

In this large nationwide cohort of patients with cataracts, those aged ≥90 years showed significantly poorer improvement of ADL than did patients aged 80 to 89 years. Cataract surgery before the age of 90 years may be recommended for patients with cataracts.

Operational Modeling with Health Economics to Support Decision Making for COPD Patients

OBJECTIVE

To assess the impact of interventions for improving the management of chronic obstructive pulmonary disease (COPD), specifically increased use of pulmonary rehabilitation (PR) on patient outcomes and cost-benefit analysis.

DATA SOURCES

We used the national Hospital Episode Statistics (HES) datasets in England, local data and experts from the hospital setting, National Prices and National Tariffs, reports and the literature around the effectiveness of PR programs.

STUDY DESIGN

The COPD pathway was modeled using discrete event simulation (DES) to capture the patient pathway to an adequate level of detail as well as randomness in the real world. DES was further enhanced by the integration of a health economic model to calculate the net benefit and cost of treating COPD patients based on key sets of interventions.

DATA COLLECTION/EXTRACTION METHODS

A total of 150 input parameters and 75 distributions were established to power the model using the HES dataset, outpatient activity data from the hospital and community services, and the literature.

PRINCIPAL FINDINGS

The simulation model showed that increasing referral to PR (by 10%, 20%, or 30%) would be cost-effective (with a benefit-cost ratio of 5.81, 5.95, and 5.91, respectively) by having a positive impact on patient outcomes and operational metrics. Number of deaths, admissions, and bed days decreased (ie, by 3.56 patients, 4.90 admissions, and 137.31 bed days for a 30% increase in PR referrals) as well as quality of life increased (ie, by 5.53 QALY among 1540 patients for the 30% increase).

CONCLUSIONS

No operational model, either statistical or simulation, has previously been developed to capture the COPD patient pathway within a hospital setting. To date, no model has investigated the impact of PR on COPD services, such as operations, key performance, patient outcomes, and cost-benefit analysis. The study will support policies around extending availability of PR as a major intervention.

Resources management impact on neonatal services performance in the United Kingdom: A system dynamics modelling approach

Demand for neonatal care in the United Kingdom (UK) has increased in recent years. This care is provided by neonatal services, which are chronically saturated due to years of budget austerity in the UK. The aim of this paper is to investigate the possible impact of increasing resources to these services to improve their operational performance and alleviate the pressure they are facing. To achieve this aim, a system dynamics (SD) simulation model was built and validated in a UK neonatal unit. The SD model was used initially to evaluate the impact of increasing resources on the unit performance and the results showed that this policy will have a limited effect on performance. The model was then extended to predict the effect of reducing the length of stay (LoS) in conjunction with increasing resources. These joint interventions will have a positive impact on the unit performance if LoS is reduced for all care categories and resources are slightly increased. Results' implications and SD's modelling usefulness to guide decision making in complex health settings are discussed.