OBJECTIVE: To assess the effect of a service containing self-management support delivered by community pharmacists to patients with asthma.
METHODS: A systematic search was performed in the following databases from inception to January 2017: PubMed, Embase, Cochrane Library's Central Register of Controlled Trials, CINAHL (Cumulative Index to Nursing and Allied Health Literature) Plus, International Pharmaceutical Abstracts, and PsycInfo. Original studies were selected if they met the following criteria: (a) provided by community pharmacists; (b) the intervention service included the essential components of asthma self-management; (c) included a usual care group; and (d) measured control/severity of asthma symptoms, health-related quality of life (HRQOL), or medication adherence.
RESULTS: Of the 639 articles screened, 12 studies involving 2,121 asthma patients were included. Six studies were randomized trials, and the other 6 were nonrandomized trials. Patients with asthma who received a self-management support service by community pharmacists had better symptom control/lower severity compared with those receiving usual care (standardized mean difference [SMD] = 0.46; 95% CI = 0.09-0.82) with high heterogeneity (I2=82.6%; P = 0.000). The overall improvement in HRQOL and medication adherence among patients in the asthma self-management support group was greater than for those in the usual care group with SMD of 0.23 (95% CI = 0.12-0.34) and 0.44 (95% CI = 0.27-0.61), respectively. Evidence of heterogeneity was not observed in these 2 outcomes.
CONCLUSIONS: Self-management support service provided by community pharmacists can help improve symptom control, quality of life, and medication adherence in patients with asthma.
DISCLOSURES: This study received financial support from Naresuan University's Faculty of Pharmaceutical Sciences Research Fund. Two authors, Saini and Krass, have studies that were included in this review. However, they were not involved in the processes that could bias outcomes of the present study, that is, quality assessment and meta-analysis. The remaining authors have declared no conflicts of interest.
DATA SOURCES: We conducted a systematic review of PubMed, EMBASE, Tufts CEA registry, Cochrane CENTRAL, and the UK National Health Services Economic Evaluation Database from 2009 to 2014.
STUDY SELECTION: All cost-effectiveness studies evaluating asthma medication(s) were included. Clinical evidence type, "E," was classified as efficacy-based if the evidence was from an explanatory randomized controlled trial(s) or meta-analysis, while evidence from pragmatic trial(s) or observational study(s) was classified as effectiveness-based. We defined three times the World Health Organization cost-effectiveness willingness-to-pay (WTP) threshold or less as a favorable cost-effectiveness finding. Logistic regression tested the likelihood of favorable versus unfavorable cost-effectiveness findings against the type of "E."
RESULTS AND CONCLUSIONS: 25 cost-effectiveness studies were included. Ten (40.0%) studies were effectiveness-based, yet 15 (60.0%) studies were efficacy-based. Of 17 studies using endpoints that could be compared to WTP threshold, 7 out of 8 (87.5%) effectiveness-based studies yielded favorable cost-effectiveness results, whereas 4 out of 9 (44.4%) efficacy-based studies yielded favorable cost-effectiveness results. The adjusted odds ratio was 15.12 (95% confidence interval; 0.59 to 388.75) for effectiveness-based versus efficacy-based achieving favorable cost-effectiveness findings. More asthma cost-effectiveness studies used efficacy-based evidence. Studies using effectiveness-based evidence trended toward being more likely to disseminate favorable cost-effective findings than those using efficacy. Health policy decision makers should pay attention to the type of clinical evidence used in cost-effectiveness studies for accurate interpretation and application.
Methods: We performed a literature search to determine preference-based value algorithms in the general population of a given country. We then fitted a second-order quadratic function to assess the utility function curve that links health status with health-care utilities. We ranked the countries according to the concavity and convexity properties of their utility functions and compared this ranking with that of the Hofstede index to check if there were any similarities.
Results: We identified 10 countries with an EQ-5D-5L-based value set and 7 countries with an EQ-5D-3L-based value set. Japan's degree of concavity was highest, while Germany's was lowest, based on the EQ-5D-3L and EQ-5D-5L value sets. Japan also ranked first in the Hofstede long-term orientation index, and rankings related to the degree of concavity, indicating a low time preference rate.
Conclusions: This is the first evaluation to identify and report an association between different cultural beliefs and utility values. These findings underline the necessity to take local values into consideration when designing health technology assessment systems.
METHODS: Long-term costs and outcomes were projected using a validated IMS CORE Diabetes Model, version 8.5. Cohort characteristics, baseline risk factors, and costs of diabetes complications were derived from Thai data sources. Relative risk was derived from a systematic review and meta-analysis study. Costs and outcomes were discounted at 3% per annum. Incremental cost-effectiveness ratio (ICER) was presented in 2015 US Dollars (USD). A series of one-way and probabilistic sensitivity analyses were performed.
RESULTS: IDet yielded slightly greater quality-adjusted life years (QALYs) (8.921 vs 8.908), but incurred higher costs than IGlar (90,417.63 USD vs 66,674.03 USD), resulting in an ICER of ∼1.7 million USD per QALY. The findings were very sensitive to the cost of IDet. With a 34% reduction in the IDet cost, treatment with IDet would become cost-effective according to the Thai threshold of 4,434.59 USD per QALY.
CONCLUSIONS: Treatment with IDet in patients with T2DM who had uncontrolled blood glucose with oral anti-diabetic agents was not a cost-effective strategy compared with IGlar treatment in the Thai context. These findings could be generalized to other countries with a similar socioeconomics level and healthcare systems.
METHODS: A validated IMS CORE Diabetes Model was used to estimate the long-term costs and outcomes. The efficacy parameters were identified and synthesized using a systematic review and meta-analysis. Baseline characteristics and cost parameters were obtained from published studies and hospital databases in Thailand. Costs were expressed in 2014 US Dollars. Outcomes were presented as an incremental cost-effectiveness ratio (ICER). One-way and probabilistic sensitivity analyses were performed to estimate parameter uncertainty.
RESULTS: From a societal perspective, treatment with DPP-4 inhibitors yielded more quality-adjusted life years (QALYs) (0.024) at a higher cost (>66,000 Thai baht (THB) or >1,829.27 USD) per person than SFU, resulting in the ICER of >2.7 million THB/QALY (>74,833.70 USD/QALY). The cost-effectiveness results were mainly driven by differences in HbA1c reduction, hypoglycemic events, and drug acquisition cost of DPP-4 inhibitors. At the ceiling ratio of 160,000 THB/QALY (4,434.59 USD/QALY), the probability that DPP-4 inhibitors are cost-effective compared to SFU was less than 10%.
CONCLUSIONS: Compared to SFU, DPP-4 inhibitor monotherapy is not a cost-effective treatment for people with T2DM and CKD in Thailand.
METHODS: A retrospective database analysis at a university-affiliated hospital in Thailand was used. Diabetic patients receiving glucose-lowering medications from July 2008 to June 2011 were included. Patients were categorized into those exposed and not exposed to thiazolidinediones (TZDs). PSs were estimated by using conventional PS and CTS-PS. In the CTS-PS, PS was separately estimated for three specific calendar time periods. Patients were matched 1:1 using caliper matching. The outcomes were cardiovascular and all-cause hospitalizations. The TZD and non-TZD groups were compared with Cox proportional hazard models.
RESULTS: A total of 2165 patients were included. The average conventional PS was 0.198 (95% confidence interval [CI] 0.195-0.202), while the average PS in the CTS-PS approach was 0.212 (0.206-0.218), 0.180 (0.173-0.188), and 0.205 (0.197-0.213) for July 2008 to June 2009, July 2009 to June 2010, and July 2010 to June 2011, respectively. The average difference in PS was 0.012 (P < 0.001), -0.009 (P ≤ 0.002), and 0.000 (P = 0.950) in the three calendar time periods. The adjusted hazard ratios of the conventional PS-matched cohort were 0.97 (95% CI 0.39-2.45) and 0.97 (95% CI 0.78-1.20) for CVD-related and all-cause hospitalizations, while the adjusted hazard ratios of the CTS-PS-matched cohort were 1.11 (95% CI 0.43-2.88) and 1.12 (95% CI 0.91-1.39), respectively.
CONCLUSION: CTS-PS is different from PS estimated by using the conventional approach. CTS-PS should be considered when a pattern of medication use has changed over the study period.