The NICE Cost-Effectiveness Threshold: What it is and What that Means

The National Institute for Health and Clinical Excellence (NICE) has been using a cost-effectiveness threshold range between £20 000 and £30 000 for over 7 years. What the cost-effectiveness threshold represents, what the appropriate level is for NICE to use, and what the other factors are that NICE should consider have all been the subject of much discussion. In this article, we briefly review hese questions, provide a critical assessment of NICE’s utilization of the incremental cost-effectiveness ratio (ICER) threshold to inform its guidance, and suggest ways in which NICE’s utilization of the ICER threshold could be developed to promote the efficient use of health service resources. We conclude that it is feasible and probably desirable to operate an explicit single threshold rather than the current range; the threshold should be seen as a threshold at which ‘other’ criteria beyond the ICER itself are taken into account; interventions with a large budgetary impact may need to be subject to a lower threshold as they are likely to displace more than the marginal activities; reimbursement at the threshold transfers the full value of an innovation to the manufacturer. Positive decisions above the threshold on the grounds of innovation reduce population health; the value of the threshold should be reconsidered regularly to ensure that it captures the impact of changes in efficiency and budget over time; the use of equity weights to sustain a positive recommendation when the ICER is above the threshold requires knowledge of the equity characteristics of those patients who bear the opportunity cost. Given the barriers to obtaining this knowledge and knowledge about the characteristics of typical beneficiaries of UK NHS care, caution is warranted before accepting claims from special pleaders; uncertainty in the evidence base should not be used to justify a positive recommendation when the ICER is above the threshold. The development of a programme of disinvestment guidance would enable NICE and the NHS to be more confident that the net health benefit of the Technology Appraisal Programme is positive

Cost-effectiveness of adjunct non-pharmacological interventions for osteoarthritis of the knee

BACKGROUND: There is limited information on the costs and benefits of alternative adjunct non-pharmacological treatments for knee osteoarthritis and little guidance on which should be prioritised for commissioning within the NHS. This study estimates the costs and benefits of acupuncture, braces, heat treatment, insoles, interferential therapy, laser/light therapy, manual therapy, neuromuscular electrical stimulation, pulsed electrical stimulation, pulsed electromagnetic fields, static magnets and transcutaneous electrical nerve Stimulation (TENS), based on all relevant data, to facilitate a more complete assessment of value. METHODS: Data from 88 randomised controlled trials including 7,507 patients were obtained from a systematic review. The studies reported a wide range of outcomes. These were converted into EQ-5D index values using prediction models, and synthesised using network meta-analysis. Analyses were conducted including firstly all trials and secondly only trials with low risk of selection bias. Resource use was estimated from trials, expert opinion and the literature. A decision analytic model synthesised all evidence to assess interventions over a typical treatment period (constant benefit over eight weeks or linear increase in effect over weeks zero to eight and dissipation over weeks eight to 16). RESULTS: When all trials are considered, TENS is cost-effective at thresholds of £20-30,000 per QALY with an incremental cost-effectiveness ratio of £2,690 per QALY vs. usual care. When trials with a low risk of selection bias are considered, acupuncture is cost-effective with an incremental cost-effectiveness ratio of £13,502 per QALY vs. TENS. The results of the analysis were sensitive to varying the intensity, with which interventions were delivered, and the magnitude and duration of intervention effects on EQ-5D. CONCLUSIONS: Using the £20,000 per QALY NICE threshold results in TENS being cost-effective if all trials are considered. If only higher quality trials are considered, acupuncture is cost-effective at this threshold, and thresholds down to £14,000 per QALY

Cognitive and behavioral predictors of light therapy use

Objective: Although light therapy is effective in the treatment of seasonal affective disorder (SAD) and other mood disorders, only 53-79% of individuals with SAD meet remission criteria after light therapy. Perhaps more importantly, only 12-41% of individuals with SAD continue to use the treatment even after a previous winter of successful treatment. Method: Participants completed surveys regarding (1) social, cognitive, and behavioral variables used to evaluate treatment adherence for other health-related issues, expectations and credibility of light therapy, (2) a depression symptoms scale, and (3) self-reported light therapy use. Results: Individuals age 18 or older responded (n = 40), all reporting having been diagnosed with a mood disorder for which light therapy is indicated. Social support and self-efficacy scores were predictive of light therapy use (p's<.05). Conclusion: The findings suggest that testing social support and self-efficacy in a diagnosed patient population may identify factors related to the decision to use light therapy. Treatments that impact social support and self-efficacy may improve treatment response to light therapy in SAD. © 2012 Roecklein et al

Predictors of tuberculosis (TB) and antiretroviral (ARV) medication non-adherence in public primary care patients in South Africa: A cross sectional study

Background: Despite the downward trend in the absolute number of tuberculosis (TB) cases since 2006 and the fall in the incidence rates since 2001, the burden of disease caused by TB remains a global health challenge. The co-infection between TB and HIV adds to this disease burden. TB is completely curable through the intake of a strict anti-TB drug treatment regimen which requires an extremely high and consistent level of adherence.The aim of this study was to investigate factors associated with adherence to anti-TB and HIV treatment drugs. Methods: A cross-sectional survey method was used. Three study districts (14 primary health care facilities in each) were selected on the basis of the highest TB caseload per clinic. All new TB and new TB retreatment patients were consecutively screened within one month of anti-tuberculosis treatment. The sample comprised of 3107 TB patients who had been on treatment for at least three weeks and a sub-sample of the total sample were on both anti-TB treatment and anti-retro-viral therapy(ART) (N = 757). Data collection tools included: a Socio-Demographic Questionnaire; a Post-Traumatic-Stress-Disorder (PTSD) Screen; a Psychological Distress Scale; the Alcohol Use Disorder Identification Test (AUDIT); and self-report measures of tobacco use, perceived health status and adherence to anti-TB drugs and ART. Results: The majority of the participants (N = 3107) were new TB cases with a 55.9% HIV co-infection rate in this adult male and female sample 18 years and older. Significant predictors of non-adherence common to both anti-TB drugs and to dual therapy (ART and anti-TB drugs) included poverty, having one or more co-morbid health condition, being a high risk for alcohol mis-use and a partner who is HIV positive. An additional predictor for non-adherence to anti-TB drugs was tobacco use. Conclusions: A comprehensive treatment programme addressing poverty, alcohol mis-use, tobacco use and psycho-social counseling is indicated for TB patients (with and without HIV). The treatment care package needs to involve not only the health sector but other relevant government sectors, such as social development.IS

Rational use of antibiotics by community health workers and caregivers for children with suspected pneumonia in Zambia: A cross-sectional mixed methods study

Background: Antibiotic resistance is an issue of growing global concern. One key strategy to minimise further development of resistance is the rational use of antibiotics, by providers and patients alike. Through integrated community case management (iCCM), children diagnosed with suspected pneumonia are treated with antibiotics; one component of an essential package to reduce child mortality and increase access to health care for remote populations. Through the use of clinical algorithms, supportive supervision and training, iCCM also offers the opportunity to improve the rational use of antibiotics and limit the spread of resistance in resource-poor contexts. This study provides evidence on antibiotic use by community health workers (CHWs) and caregivers to inform iCCM programmes, safeguarding current treatments whilst maximising access to care. Methods: 1497 CHW consultations were directly observed by non-clinical researchers, with measurement of respiratory rate by CHWs recorded by video. Videos were used to conduct a retrospective reference standard assessment of respiratory rate by experts. Fifty-five caregivers whose children were prescribed a 5-day course of antibiotics for suspected pneumonia were followed up on day six to assess adherence through structured interviews and pill counts. Six focus group discussions and nine in depth interviews were conducted with CHWs and caregivers to supplement quantitative findings. Results: The findings indicate that CHWs adhered to treatment guidelines for 92 % of children seen, prescribing treatment corresponding to their assessment. However, only 65 % of antibiotics prescribed were given for children with experts' confirmed fast breathing pneumonia. Qualitative data indicates that CHWs have a good understanding of pneumonia diagnosis, and although caregivers sometimes applied pressure to receive drugs, CHWs stated that treatment decisions were not influenced. 46 % of caregivers were fully adherent and gave their child the full 5-day course of dispersible amoxicillin. If caregivers who gave treatment for 3 to 5 days were considered, adherence increased to 76 %. Conclusions: CHWs are capable of prescribing treatment corresponding to their assessment of respiratory rate. However, rational use of antibiotics could be strengthened through improved respiratory rate assessment, and better diagnostic tools. Furthermore, a shorter course of dispersible amoxicillin could potentially improve caregiver adherence, reducing risk of resistance and cost

Targeting medication non-adherence behavior in selected autoimmune diseases: a systematic approach to digital health program development

Background 29 autoimmune diseases, including Rheumatoid Arthritis, gout, Crohn’s Disease, and Systematic Lupus Erythematosus affect 7.6-9.4% of the population. While effective therapy is available, many patients do not follow treatment or use medications as directed. Digital health and Web 2.0 interventions have demonstrated much promise in increasing medication and treatment adherence, but to date many Internet tools have proven disappointing. In fact, most digital interventions continue to suffer from high attrition in patient populations, are burdensome for healthcare professionals, and have relatively short life spans. Objective Digital health tools have traditionally centered on the transformation of existing interventions (such as diaries, trackers, stage-based or cognitive behavioral therapy programs, coupons, or symptom checklists) to electronic format. Advanced digital interventions have also incorporated attributes of Web 2.0 such as social networking, text messaging, and the use of video. Despite these efforts, there has not been little measurable impact in non-adherence for illnesses that require medical interventions, and research must look to other strategies or development methodologies. As a first step in investigating the feasibility of developing such a tool, the objective of the current study is to systematically rate factors of non-adherence that have been reported in past research studies. Methods Grounded Theory, recognized as a rigorous method that facilitates the emergence of new themes through systematic analysis, data collection and coding, was used to analyze quantitative, qualitative and mixed method studies addressing the following autoimmune diseases: Rheumatoid Arthritis, gout, Crohn’s Disease, Systematic Lupus Erythematosus, and inflammatory bowel disease. Studies were only included if they contained primary data addressing the relationship with non-adherence. Results Out of the 27 studies, four non-modifiable and 11 modifiable risk factors were discovered. Over one third of articles identified the following risk factors as common contributors to medication non-adherence (percent of studies reporting): patients not understanding treatment (44%), side effects (41%), age (37%), dose regimen (33%), and perceived medication ineffectiveness (33%). An unanticipated finding that emerged was the need for risk stratification tools (81%) with patient-centric approaches (67%). Conclusions This study systematically identifies and categorizes medication non-adherence risk factors in select autoimmune diseases. Findings indicate that patients understanding of their disease and the role of medication are paramount. An unexpected finding was that the majority of research articles called for the creation of tailored, patient-centric interventions that dispel personal misconceptions about disease, pharmacotherapy, and how the body responds to treatment. To our knowledge, these interventions do not yet exist in digital format. Rather than adopting a systems level approach, digital health programs should focus on cohorts with heterogeneous needs, and develop tailored interventions based on individual non-adherence patterns

Lipids modulate the conformational dynamics of a secondary multidrug transporter

Direct interactions with lipids have emerged as key determinants of the folding, structure and function of membrane proteins, but an understanding of how lipids modulate protein dynamics is still lacking. Here, we systematically explored the effects of lipids on the conformational dynamics of the proton-powered multidrug transporter LmrP from Lactococcus lactis, using the pattern of distances between spin-label pairs previously shown to report on alternating access of the protein. We uncovered, at the molecular level, how the lipid headgroups shape the conformational-energy landscape of the transporter. The model emerging from our data suggests a direct interaction between lipid headgroups and a conserved motif of charged residues that control the conformational equilibrium through an interplay of electrostatic interactions within the protein. Together, our data lay the foundation for a comprehensive model of secondary multidrug transport in lipid bilayers

Extensions to decision curve analysis, a novel method for evaluating diagnostic tests, prediction models and molecular markers

<p>Abstract</p> <p>Background</p> <p>Decision curve analysis is a novel method for evaluating diagnostic tests, prediction models and molecular markers. It combines the mathematical simplicity of accuracy measures, such as sensitivity and specificity, with the clinical applicability of decision analytic approaches. Most critically, decision curve analysis can be applied directly to a data set, and does not require the sort of external data on costs, benefits and preferences typically required by traditional decision analytic techniques.</p> <p>Methods</p> <p>In this paper we present several extensions to decision curve analysis including correction for overfit, confidence intervals, application to censored data (including competing risk) and calculation of decision curves directly from predicted probabilities. All of these extensions are based on straightforward methods that have previously been described in the literature for application to analogous statistical techniques.</p> <p>Results</p> <p>Simulation studies showed that repeated 10-fold crossvalidation provided the best method for correcting a decision curve for overfit. The method for applying decision curves to censored data had little bias and coverage was excellent; for competing risk, decision curves were appropriately affected by the incidence of the competing risk and the association between the competing risk and the predictor of interest. Calculation of decision curves directly from predicted probabilities led to a smoothing of the decision curve.</p> <p>Conclusion</p> <p>Decision curve analysis can be easily extended to many of the applications common to performance measures for prediction models. Software to implement decision curve analysis is provided.</p

Evidence synthesis as the key to more coherent and efficient research

<p>Abstract</p> <p>Background</p> <p>Systematic review and meta-analysis currently underpin much of evidence-based medicine. Such methodologies bring order to <it>previous </it>research, but <it>future </it>research planning remains relatively incoherent and inefficient.</p> <p>Methods</p> <p>To outline a framework for evaluation of health interventions, aimed at increasing coherence and efficiency through i) making better use of information contained within the existing evidence-base when designing future studies; and ii) maximising the information available and thus potentially reducing the need for future studies.</p> <p>Results</p> <p>The framework presented insists that an up-to-date meta-analysis of existing randomised controlled trials (RCTs) should always be considered before future trials are conducted. Such a meta-analysis should inform critical design issues such as sample size determination. The contexts in which the use of individual patient data meta-analysis and mixed treatment comparisons modelling may be beneficial before further RCTs are conducted are considered. Consideration should also be given to how any newly planned RCTs would contribute to the totality of evidence through its incorporation into an updated meta-analysis. We illustrate how new RCTs can have very low power to change inferences of an existing meta-analysis, particularly when between study heterogeneity is taken into consideration.</p> <p>Conclusion</p> <p>While the collation of existing evidence as the basis for clinical practice is now routine, a more coherent and efficient approach to planning future RCTs to strengthen the evidence base needs to be developed. The framework presented is a proposal for how this situation can be improved.</p

Impact of statins and ACE inhibitors on mortality after COPD exacerbations

<p>Abstract</p> <p>Background</p> <p>The purpose of our study was to examine the association of prior outpatient use of statins and angiotensin converting enzyme (ACE) inhibitors on mortality for subjects ≥ 65 years of age hospitalized with acute COPD exacerbations.</p> <p>Methods</p> <p>We conducted a retrospective national cohort study using Veterans Affairs administrative data including subjects ≥65 years of age hospitalized with a COPD exacerbation. Our primary analysis was a multilevel model with the dependent variable of 90-day mortality and hospital as a random effect, controlling for preexisting comorbid conditions, demographics, and other medications prescribed.</p> <p>Results</p> <p>We identified 11,212 subjects with a mean age of 74.0 years, 98% were male, and 12.4% of subjects died within 90-days of hospital presentation. In this cohort, 20.3% of subjects were using statins, 32.0% were using ACE inhibitors or angiotensin II receptor blockers (ARB). After adjusting for potential confounders, current statin use (odds ratio 0.51, 95% confidence interval 0.40–0.64) and ACE inhibitor/ARB use (0.55, 0.46–0.66) were significantly associated with decreased 90-day mortality.</p> <p>Conclusion</p> <p>Use of statins and ACE inhibitors prior to admission is associated with decreased mortality in subjects hospitalized with a COPD exacerbation. Randomized controlled trials are needed to examine whether the use of these medications are protective for those patients with COPD exacerbations.</p