Impact evaluation of guidelines on antibiotic utilisation & appropriateness in Malaysian public primary care: an interrupted time series analysis.

Background: The National Antimicrobial Guidelines (NAG) 2014 and NAG2019 in Malaysia targeted rational and judicious use of antimicrobials. In this study, we assessed the change in antibiotic utilisation and appropriateness due to the guidelines that were implemented from 2011 to 2019. Methods: Interrupted time series analyses on rates of antibiotic appropriateness and utilisation were performed using prescription data from public primary care clinics in Malaysia between January 2011 and December 2019. Rates of antibiotic utilisation, reported as Defined Daily Dose (DDD) per 1000 patients per day, were stratified by antibiotic classes. Results: Of the 16,081,492 prescriptions recorded during the study period, 4.98% (n = 800,899) contained antibiotics. NAG2014 resulted in a significant increase in antibiotic utilisation trend by 0.029 (p < 0.0001) while NAG2019 had a substantial impact on antibiotic utilisation, decreasing DDD by 1778 and increasing appropriateness by 54.6% (p < 0.0001). Variation in the number of antibiotic molecules being prescribed also decreased after NAG2019. Conclusion: Our findings indicate that the introduction of NAG2019 led to a substantial improvement in antibiotic appropriateness. At the same time, antibiotic utilisation decreased. Further research is needed to ascertain and ensure the sustainability of these changes and to establish targeted improvement strategies focusing on reducing inappropriate and unnecessary prescribing.

A comparison between antibiotic utilisation in public and private community healthcare in Malaysia.

BACKGROUND: There are two parallel systems in Malaysian primary healthcare services: government funded public primary care and privately-owned practices. While there have been several studies evaluating antibiotic utilisation in Malaysian public healthcare, there is a lack of literature on the use of antibiotics in the private sector. There is a dire need to evaluate the more recent performance of public vs. private community healthcare in Malaysia. As such, this study aimed at measuring and comparing the utilisation of antibiotics in the public and private community healthcare sectors of Malaysia in 2018-2021. METHODS: This study was a retrospective analysis of antibiotic utilisation in Malaysian primary care for the period of 1 January 2018 until 31 December 2021 using the nationwide pharmaceutical procurement and sales data from public and private health sectors. Rates of antibiotic utilisation were reported as Defined Daily Doses per 1000 inhabitants per day (DID) and stratified by antibiotic classes. The secondary analysis included proportions of AWaRe antibiotic category use for each sector and proportion of antibiotic utilisation for both sectors. RESULTS: The overall national antibiotic utilisation for 2018 was 6.14 DID, increasing slightly to 6.56 DID in 2019, before decreasing to 4.54 DID in 2020 and 4.17 DID in 2021. Private primary care antibiotic utilisation was almost ten times higher than in public primary care in 2021. The public sector had fewer (four) antibiotic molecules constituting 90% of the total antibiotic utilisation as compared to the private sector (eight). Use of Access antibiotics in the public sector was consistently above 90%, while use of Access category antibiotics by the private sector ranged from 64.2 to 68.3%. Although use of Watch antibiotics in the private sector decreased over the years, the use of Reserve and 'Not Recommended' antibiotics increased slightly over the years. CONCLUSION: Antibiotic consumption in the private community healthcare sector in Malaysia is much higher than in the public sector. These findings highlight the need for more rigorous interventions targeting both private prescribers and the public with improvement strategies focusing on reducing inappropriate and unnecessary prescribing.

Impact of COVID-19 Pandemic on Antibiotic Utilisation in Malaysian Primary Care Clinics: An Interrupted Time Series Analysis.

The COVID-19 pandemic has resulted in a dramatic change in the delivery of primary healthcare across the world, presumably changing trends in consultations for infectious diseases and antibiotic use. This study aimed at describing and evaluating the impact of COVID-19 on antibiotic use in public primary care clinics in Malaysia between 2018 and 2021. Data from the nationwide procurement database of systemic antibiotics from public primary care clinics in Malaysia between January 2018 and December 2021 were analysed using interrupted time series analysis. The monthly number of defined daily doses per 1000 inhabitants per day (DID) was calculated and grouped by antibiotic class. The trend of antibiotic utilisation rates had been decreasing by 0.007 DID monthly before March 2020 (p = 0.659). With the introduction of national lockdown due to COVID-19 beginning March 2020, there was a significant reduction in the level of antibiotic utilisation rates of 0.707 (p = 0.022). Subsequently, the monthly trend showed a slight upward change until the end of the study period (p = 0.583). Our findings indicate that there was a significant decrease in antibiotic utilisation for systemic use in primary care following the COVID-19 pandemic compared with the preceding years (January 2018-March 2020).

Conjoint analyses of patients' preferences for primary care: a systematic review.

BACKGROUND: While patients' preferences in primary care have been examined in numerous conjoint analyses, there has been little systematic effort to synthesise the findings. This review aimed to identify, to organise and to assess the strength of evidence for the attributes and factors associated with preference heterogeneity in conjoint analyses for primary care outpatient visits. METHODS: We searched five bibliographic databases (PubMed, Embase, PsycINFO, Econlit and Scopus) from inception until 15 December 2021, complemented by hand-searching. We included conjoint analyses for primary care outpatient visits. Two reviewers independently screened papers for inclusion and assessed the quality of all included studies using the checklist by ISPOR Task Force for Conjoint Analysis. We categorized the attributes of primary care based on Primary Care Monitoring System framework and factors based on Andersen's Behavioural Model of Health Services Use. We then assessed the strength of evidence and direction of preference for the attributes of primary care, and factors affecting preference heterogeneity based on study quality and consistency in findings. RESULTS: Of 35 included studies, most (82.4%) were performed in high-income countries. Each study examined 3-8 attributes, mainly identified through literature reviews (n = 25). Only six examined visits for chronic conditions, with the rest on acute or non-specific / other conditions. Process attributes were more commonly examined than structure or outcome attributes. The three most commonly examined attributes were waiting time for appointment, out-of-pocket costs and ability to choose the providers they see. We identified 24/58 attributes with strong or moderate evidence of association with primary care uptake (e.g., various waiting times, out-of-pocket costs) and 4/43 factors with strong evidence of affecting preference heterogeneity (e.g., age, gender). CONCLUSIONS: We found 35 conjoint analyses examining 58 attributes of primary care and 43 factors that potentially affect the preference of these attributes. The attributes and factors, stratified into evidence levels based on study quality and consistency, can guide the design of research or policies to improve patients' uptake of primary care. We recommend future conjoint analyses to specify the types of visits and to define their attributes clearly, to facilitate consistent understanding among respondents and the design of interventions targeting them. Word Count: 346/350 words. TRIAL REGISTRATION: On Open Science Framework: https://osf.io/m7ts9.

Cost effectiveness analyses of pharmacological treatments in heart failure.

In a rapidly growing and aging population, heart failure (HF) has become recognised as a public health concern that imposes high economic and societal costs worldwide. HF management stems from the use of highly cost-effective angiotensin converting enzyme inhibitors (ACEi) and ß-blockers to the use of newer drugs such as sodium-glucose cotransporter-2 inhibitors (SGLT2i), ivabradine, and vericiguat. Modelling studies of pharmacological treatments that report on cost effectiveness in HF is important in order to guide clinical decision making. Multiple cost-effectiveness analysis of dapagliflozin for heart failure with reduced ejection fraction (HFrEF) suggests that it is not only cost-effective and has the potential to improve long-term clinical outcomes, but is also likely to meet conventional cost-effectiveness thresholds in many countries. Similar promising results have also been shown for vericiguat while a cost effectiveness analysis (CEA) of empagliflozin has shown cost effectiveness in HF patients with Type 2 diabetes. Despite the recent FDA approval of dapagliflozin and empagliflozin in HF, it might take time for these SGLT2i to be widely used in real-world practice. A recent economic evaluation of vericiguat found it to be cost effective at a higher cost per QALY threshold than SGLT2i. However, there is a lack of clinical or real-world data regarding whether vericiguat would be prescribed on top of newer treatments or in lieu of them. Sacubitril/valsartan has been commonly compared to enalapril in cost effectiveness analysis and has been found to be similar to that of SGLT2i but was not considered a cost-effective treatment for heart failure with reduced ejection fraction in Thailand and Singapore with the current economic evaluation evidences. In order for more precise analysis on cost effectiveness analysis, it is necessary to take into account the income level of various countries as it is certainly easier to allocate more financial resources for the intervention, with greater effectiveness, in high- and middle-income countries than in low-income countries. This review aims to evaluate evidence and cost effectiveness studies in more recent HF drugs i.e., SGLT2i, ARNi, ivabradine, vericiguat and omecamtiv, and gaps in current literature on pharmacoeconomic studies in HF.

Evaluation of BNT162b2 vaccine effectiveness in Malaysia: test negative case-control study.

There is a notable lack of vaccine effectiveness studies using test-negative case-controlled approach in low- and middle-income countries which have different logistic, demographic and socio-economic conditions from high-income countries. We aimed to estimate the effectiveness of BNT162b2 vaccine against COVID-19 infection over time, intensive care unit admission, severe or critical disease and death due to COVID-19. This study was conducted in the resident population of Labuan aged ≥18 years who had been tested for SARS-CoV-2 by Reverse-Transcriptase Polymerase Chain Reaction between 1 March 2021 and 31 October 2021. We used a test-negative case-control design where 2644 pairs of cases and controls were matched by age, sex, testing date, nationality and testing reason. Analysis was stratified by age group to estimate age effect (<60 years and ≥60 years). Of 22217 individuals tested by Reverse-Transcriptase Polymerase Chain Reaction, 5100 were positive for SARS-CoV-2 and aged 18 years and above. Overall vaccine effectiveness ≥ 14 days after the second dose was 65.2% (95% CI: 59.8-69.9%) against COVID-19 infection, 92.5% (95% CI: 72.3-98.8%) against intensive care unit admission, and 96.5% (95% CI: 82.3-99.8%) against COVID-19 deaths. Among infected individuals, vaccine effectiveness was 79.2% (95% CI: 42.3-94.1%) in preventing severe or critical disease due to COVID-19. Vaccine effectiveness for ≥60 years was 72.3% (95% CI: 53.4-83.9%) in fully vaccinated individuals, higher than 64.8% (95% CI: 49.3-59.1%) for those <60 years. Two doses of BNT162b2 were highly effective against COVID-19 infection, severe or critical disease, intensive care unit admission and death due to COVID-19. This study addresses a gap in literature on BNT162b2 vaccine effectiveness in low- and middle-income populations and demonstrates the feasibility of such a study design in a resource limited setting while supporting evidence of waning immunity.

Optimizing Antimicrobial Therapy by Integrating Multi-Omics With Pharmacokinetic/Pharmacodynamic Models and Precision Dosing.

In the era of "Bad Bugs, No Drugs," optimizing antibiotic therapy against multi-drug resistant (MDR) pathogens is crucial. Mathematical modelling has been employed to further optimize dosing regimens. These models include mechanism-based PK/PD models, systems-based models, quantitative systems pharmacology (QSP) and population PK models. Quantitative systems pharmacology has significant potential in precision antimicrobial chemotherapy in the clinic. Population PK models have been employed in model-informed precision dosing (MIPD). Several antibiotics require close monitoring and dose adjustments in order to ensure optimal outcomes in patients with infectious diseases. Success or failure of antibiotic therapy is dependent on the patient, antibiotic and bacterium. For some drugs, treatment responses vary greatly between individuals due to genotype and disease characteristics. Thus, for these drugs, tailored dosing is required for successful therapy. With antibiotics, inappropriate dosing such as insufficient dosing may put patients at risk of therapeutic failure which could lead to mortality. Conversely, doses that are too high could lead to toxicities. Hence, precision dosing which customizes doses to individual patients is crucial for antibiotics especially those with a narrow therapeutic index. In this review, we discuss the various strategies in optimizing antimicrobial therapy to address the challenges in the management of infectious diseases and delivering personalized therapy.