Systems, design and value-for-money in the NHS: mission impossible?

NHS organisations are being challenged to transform themselves sustainably in the face of increasing demands, but they have little room for error. To manage trade-offs and risks precisely, they must integrate two very different streams of expertise: systems approaches to service design and implementation, and economic evaluation of the type pioneered by the National Institute of Health and Care Excellence (NICE) for pharmaceuticals and interventions. Neither approach is fully embedded in NHS service transformation, while the combination as an integrated discipline is still some way away. We share three examples to show how design methods may be deployed within a value-for-money framework to plan operationally and in terms of clinical outcomes. They are real cases briefl y described and the unreferenced ones are anonymised. They have been selected by one of the authors (TY) during his sabbatical research because each illustrates a commonly observed challenge. To meet these challenges, we argue that the health economics cost / quality-adjusted life year (QALY) framework promulgated by NICE provides an under-appreciated lens for thinking about trade-offs and we highlight some systems tools which have also been underutilised in this context

Cost-Effectiveness of HIV Screening in STD Clinics, Emergency Departments, and Inpatient Units: A Model-Based Analysis

Identifying and treating persons with human immunodeficiency virus (HIV) infection early in their disease stage is considered an effective means of reducing the impact of the disease. We compared the cost-effectiveness of HIV screening in three settings, sexually transmitted disease (STD) clinics serving men who have sex with men, hospital emergency departments (EDs), settings where patients are likely to be diagnosed early, and inpatient diagnosis based on clinical manifestations.We developed the Progression and Transmission of HIV/AIDS model, a health state transition model that tracks index patients and their infected partners from HIV infection to death. We used program characteristics for each setting to compare the incremental cost per quality-adjusted life year gained from early versus late diagnosis and treatment. We ran the model for 10,000 index patients for each setting, examining alternative scenarios, excluding and including transmission to partners, and assuming HAART was initiated at a CD4 count of either 350 or 500 cells/µL. Screening in STD clinics and EDs was cost-effective compared with diagnosing inpatients, even when including only the benefits to the index patients. Screening patients in STD clinics, who have less-advanced disease, was cost-effective compared with ED screening when treatment with HAART was initiated at a CD4 count of 500 cells/µL. When the benefits of reduced transmission to partners from early diagnosis were included, screening in settings with less-advanced disease stages was cost-saving compared with screening later in the course of infection. The study was limited by a small number of observations on CD4 count at diagnosis and by including transmission only to first generation partners of the index patients.HIV prevention efforts can be advanced by screening in settings where patients present with less-advanced stages of HIV infection and by initiating treatment with HAART earlier in the course of infection

WHO 2010 Guidelines for Prevention of Mother-to-Child HIV Transmission in Zimbabwe: Modeling Clinical Outcomes in Infants and Mothers

The Zimbabwean national prevention of mother-to-child HIV transmission (PMTCT) program provided primarily single-dose nevirapine (sdNVP) from 2002-2009 and is currently replacing sdNVP with more effective antiretroviral (ARV) regimens.Published HIV and PMTCT models, with local trial and programmatic data, were used to simulate a cohort of HIV-infected, pregnant/breastfeeding women in Zimbabwe (mean age 24.0 years, mean CD4 451 cells/µL). We compared five PMTCT regimens at a fixed level of PMTCT medication uptake: 1) no antenatal ARVs (comparator); 2) sdNVP; 3) WHO 2010 guidelines using "Option A" (zidovudine during pregnancy/infant NVP during breastfeeding for women without advanced HIV disease; lifelong 3-drug antiretroviral therapy (ART) for women with advanced disease); 4) WHO "Option B" (ART during pregnancy/breastfeeding without advanced disease; lifelong ART with advanced disease); and 5) "Option B+:" lifelong ART for all pregnant/breastfeeding, HIV-infected women. Pediatric (4-6 week and 18-month infection risk, 2-year survival) and maternal (2- and 5-year survival, life expectancy from delivery) outcomes were projected.Eighteen-month pediatric infection risks ranged from 25.8% (no antenatal ARVs) to 10.9% (Options B/B+). Although maternal short-term outcomes (2- and 5-year survival) varied only slightly by regimen, maternal life expectancy was reduced after receipt of sdNVP (13.8 years) or Option B (13.9 years) compared to no antenatal ARVs (14.0 years), Option A (14.0 years), or Option B+ (14.5 years).Replacement of sdNVP with currently recommended regimens for PMTCT (WHO Options A, B, or B+) is necessary to reduce infant HIV infection risk in Zimbabwe. The planned transition to Option A may also improve both pediatric and maternal outcomes

ASSESSING THE VALUE OF MODELING AND SIMULATION IN HEALTH CARE: AN EXAMPLE BASED ON INCREASING ACCESS TO STROKE TREATMENT

The use of modelling and simulation (M&S) to design, operate and troubleshoot care delivery processes has not been the subject of economic evaluation, so we undertake such an analysis of a modelling exercise to design better delivery: in this case, stroke care. First, the financial impact is assessed, followed by a cost-effectiveness analysis in which the clinical impact is also assessed. Because it is not usually possible to obtain all the costs of modelling, probabilistic sensitivity and threshold analyses are used to explore the uncertainties in the absence of complete information. Threshold analysis is then applied to calculate the upper bound cost and the level of service improvement that would be needed for M&S to represent good value for money

Evaluating the financial impact of modeling and simulation in healthcare: Proposed framework with a case study

Modeling and simulation have been widely used in health economics and health technology assessment for estimating long-term costs and benefits of health interventions. However, the implementation of simulation in the organizational planning of healthcare delivery is still limited and has not yet received the same level of engagement as it has in other industries. The purpose of this paper is to propose an analytic framework to quantify the value of modeling and simulation, so that the benefits can be evaluated more objectively by the healthcare stakeholders and can be compared across a broad range of health innovations. The application of the framework is illustrated in a case study of acute care for Ischemic stroke. Although the value of modeling and simulation can be measured in various forms, depending on the perspectives of stakeholders, this paper initially focuses on the financial value and takes the perspective of administrators who need to plan and manage health-care budgets

Cost-effectiveness of HIV rescreening during late pregnancy to prevent mother-to-child HIV transmission in South Africa and other resource-limited settings

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Inferring Infection Transmission Parameters That Influence Water Treatment Decisions

One charge of the United States Environmental Protection Agency is to study the risk of infection for microbial agents that can be disseminated through drinking water systems, and to recommend water treatment policy to counter that risk. Recently proposed dynamical system models quantify indirect risks due to secondary transmission, in addition to primary infection risk from the water supply considered by standard assessments. Unfortunately, key parameters that influence water treatment policy are unknown, in part because of lack of data and effective inference methods. This paper develops inference methods for those parameters by using stochastic process models to better incorporate infection dynamics into the inference process. Our use of endemic data provides an alternative to waiting for, identifying, and measuring an outbreak. Data both from simulations and from New York City illustrate the approach.Stochastic Infection Modeling, Water Treatment Policy, Public Health Policy, Bayesian Inference, Risk Dynamics