A Multi-Component Implementation Strategy to Expand Hepatitis B Screening in Primary Care in Viet Nam: A Mixed-Methods Study

A Multi-Component Implementation Strategy to Expand Hepatitis B Screening in Primary Care in Viet Nam: A Mixed-Methods Study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article A Multi-Component Implementation Strategy to Expand Hepatitis B Screening in Primary Care in Viet Nam: A Mixed-Methods Study Thanh V. Kim, Diem Dao, Trang N.D. Pham, Loc Phan, Linh H.H. Le, and 10 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9200793/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background. Chronic hepatitis B (CHB) remains substantially underdiagnosed in Viet Nam despite widespread availability of effective antiviral therapy. In routine primary care, hepatitis B surface antigen (HBsAg) testing is typically performed only when clinically indicated, resulting in missed opportunities for early detection. Evidence on how to operationalize routine hepatitis B screening in real-world, resource-constrained primary care settings is limited. Methods. We conducted a quasi-experimental implementation trial with mixed-method evaluation at a large public primary care hospital in Ho Chi Minh City, Viet Nam. A three-component strategy informed by constructs from the Consolidated Framework for Implementation Research (CFIR), including continuing medical education (CME), an electronic best practice advisory (BPA), and point-of-care (POC) HBsAg rapid testing, was introduced sequentially over 12 months. Implementation outcomes (adoption, reach) and service outcomes (weekly HBsAg testing per 1,000 visits) were evaluated using electronic medical record data, Kaplan–Meier and Cox regression analyses, and segmented negative binomial interrupted time-series models. Negative control outcomes (LDL and glucose testing) were analyzed in parallel. Qualitative data from observations and interviews were analyzed using a CFIR 2.0-guided framework to interpret mechanisms and contextual influences. Results. Among 225,209 outpatient visits and 46,857 unique patients, CME improved provider knowledge but resulted in only modest changes in testing. BPA reminders were frequently bypassed during high-volume sessions, limiting adoption. In contrast, introduction of free POC HBsAg rapid testing produced a sharp and sustained increase in weekly testing rates and substantially shortened time-to-testing among eligible patients. These effects were substantially larger than those observed for negative control outcomes, supporting a strategy-specific effect rather than background testing trends. Qualitative findings indicated that removal of financial and procedural barriers was central to uptake, while workflow constraints and team-based task division shaped implementation performance. Conclusions. A multi-component implementation strategy integrating provider education, EMR-based clinical decision support, and point-of-care HBsAg rapid testing substantially increased hepatitis B screening uptake in a high-volume public primary care system in Viet Nam. Structural interventions that remove financial and workflow barriers appear necessary for successful implementation. Integrating HBV screening into routine primary care workflows may represent a scalable strategy to accelerate hepatitis B diagnosis and support progress toward global elimination targets. Registration: NCT06403657 on ClinicalTrials.gov Chronic hepatitis B Primary care screening Implementation science Point-of-care testing Mixed-methods study CFIR 2.0 Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Contributions to the literature This study provides one of the first mixed-methods implementation evaluations of hepatitis B screening in primary care from Viet Nam and other low- and middle-income settings, where evidence on how to operationalize routine screening within high-volume, resource-constrained systems remains limited. By combining interrupted time-series analysis with CFIR-guided qualitative inquiry, the study demonstrates that implementation components contribute unequally to adoption and reach, with structural determinants, particularly financing constraints, workflow compatibility, and relative priority, exerting stronger influence than informational strategies alone. The findings clarify that provider education and electronic reminders may increase knowledge and cognitive awareness, but are insufficient when layered onto persistent structural frictions embedded in routine care delivery. In contrast, resource-enabling strategies that remove patient-facing financial and procedural barriers generate substantially greater impact. The integration of negative control outcomes, direct workflow observations, and patient-reported acceptability strengthens causal interpretation and helps distinguish strategy-specific effects from secular testing trends or documentation artifacts. For scale-up in Viet Nam and similar settings, the study highlights the importance of aligning implementation strategies with contextual determinants, particularly reducing out-of-pocket costs, minimizing workflow disruption, and enhancing perceived feasibility, rather than relying solely on education or digital prompting. INTRODUCTION Chronic hepatitis B (CHB) remains a major global health challenge, responsible for 254 million chronically infected and over 1 million CHB-related deaths annually. 1 In Viet Nam – among the countries with the highest HBV burden – antiviral treatment such as tenofovir and entecavir is widely available and largely reimbursed by national health insurance. 2 Yet treatment coverage remains extremely low, with fewer than 5% of eligible individuals receiving antiviral therapy. 3 A central driver of this treatment gap is the deficit in diagnosis, with an estimated 70% of people living with CHB in Viet Nam unaware of their infection status. 4 This undiagnosed population, disconnected from the care cascade, continues to suffer preventable complications and perpetuate community transmission. HBsAg testing is the first critical step for diagnosing CHB. Both the World Health Organization and the US Centers for Disease Control recommend routine HBsAg screening as part of universal hepatitis elimination strategies. 5,6 For current practice in Viet Nam, however, HBsAg testing is usually performed only under specific circumstances (e.g., clinical suspicion, patient request, documented risk factors, or pregnancy) rather than as a routine preventive service. 7 This testing gap is shaped by multiple barriers at several levels. At the patient level, limited knowledge of the disease, concerns about out-of-pocket costs, fear of invasive procedures deter screening, and slow turnaround of test results. 8,9 At the healthcare provider level, unawareness of the burden of hepatitis B, time constraints, and competing clinical priorities contribute to missed testing opportunities. 10,11 . Taken together, these barriers span multiple domains of healthcare delivery, including provider knowledge and beliefs, workflow compatibility within clinical settings, and structural constraints affecting patient access to testing. Primary care systems represent an important platform for expanding CHB diagnosis, particularly in high-burden settings where specialist hepatology services are limited. Our prior systematic review and analysis has documented that provider education, electronic reminders, and point-of-care rapid testing can increase uptake of CHB screening service in primary care setting, 12 supporting a multi-component implementation strategy. However, the effectiveness of such strategies varies across health systems and has not been tested in practice. 12 As such, it remains unclear whether they can be successfully integrated into Viet Nam’s primary care environment with different contextual influencers. To date, no study has examined the real-world implementation of a combined approach involving provider education, electronic reminders, and point-of-care HBsAg testing in Vietnamese public primary care settings. 12 Taken together, this study tests the implementation of a multi-component strategy (combining provider training, electronic reminders, and point-of-care HBsAg testing) within a large public primary care hospital in Ho Chi Minh City. Drawing on constructs from the Consolidated Framework for Implementation Research 2.0 (CFIR 2.0), the intervention components were designed to address barriers operating at the level of individual providers, clinical workflow, and patient access to testing. Our primary aim is to assess key implementation outcomes, including reach and adoption, and to determine whether the strategy increases the overall volume of HBsAg testing delivered. The secondary aim is to explore clinician and patient experiences with the implementation strategies and to identify contextual factors influencing their integration and sustainability in routine practice. Ultimately, this study seeks to generate actionable evidence to support system-level integration of routine CHB testing across Viet Nam’s primary care system and contribute to national hepatitis B elimination goals. METHODS Study design and context We conducted a quasi-experimental implementation trial with a mixed-methods evaluation to increase uptake of HBsAg testing in primary care. Quantitative analyses of electronic health record (EHR) data assessed implementation outcomes (adoption and reach) and service outcomes using interrupted time-series and survival analyses. Qualitative methods were used to examine contextual factors influencing implementation and to interpret quantitative findings. The study was conceptually informed by the CFIR 2.0, which guided identification of contextual determinants, interpretation of implementation mechanisms, and qualitative analysis of barriers and facilitators. 13 The study was conducted in the primary care consultation rooms of the outpatient department at Lê Văn Thịnh Hospital, a large public primary care hospital in Ho Chi Minh City, Viet Nam, serving the eastern catchment of the city. The hospital uses the HIS 2.0 system to support clinical and administrative workflows. During the study period, 13 providers (10 physicians and 3 nurses) staffed the participating consultation rooms. At baseline, HBsAg testing was performed exclusively using phlebotomy-based laboratory assays, and screening tests were not reimbursed by national health insurance. In addition to screening, the hospital provides hepatitis B vaccination services and specialty hepatology consultation. Implementation Strategy The innovation under study was routine HBsAg screening delivery in primary care. To support its implementation, we introduced a three-component implementation strategy using a stepwise rollout over 12 months. Each strategy component was designed to address specific determinants identified during the pre-implementation assessment: Continued Medical Education training (CME) targeted provider knowledge and beliefs about screening, the Best Practice Advisory reminder (BPA) addressed missed opportunities within clinical workflow, and Point-of-care HBsAg testing (POC HBsAg) addressed structural and patient-level barriers including cost, venipuncture, and turnaround time. In the first four months, we introduced CME-accredited training to improve provider knowledge, confidence, and perceived appropriateness of hepatitis B screening, without changing routine clinical workflows. In months 5–8, we added BPA within the EHR to prompt screening during eligible outpatient encounters and address workflow-related missed opportunities. In the final four months, POC HBsAg was integrated on top of the BPA to reduce patient-level barriers, including cost, venipuncture, and long turnaround times, and to enable same-day screening. This sequential implementation enabled assessment of the incremental contribution of each strategy component to the delivery of routine HBsAg screening as it was embedded into primary care practice. Selection of strategy components was informed by an a priori assessment of contextual barriers using the CFIR 2.0 13 , ensuring alignment between identified determinants and implementation strategies (Table S1 ). The CME component comprised in-person, small-group workshops delivered by a hepatology specialist with support from the research team. Content focused on CHB epidemiology, prevention, screening indications, referral pathways, health insurance procedures, and updated screening guidance, tailored to primary care providers’ roles in screening and referral rather than specialist treatment decisions. Three 3-hour sessions were delivered at Lê Văn Thịnh Hospital in June 2024, with CME certification provided. Although sessions were open to other departments, evaluation focused on providers working in the targeted primary care consultation rooms. CME content and format remained unchanged throughout the implementation period. The BPA was embedded in the electronic health record and triggered during outpatient encounters when no prior HBsAg result or CHB diagnosis was documented, or when the most recent HBsAg test was more than five years old. When triggered, an interruptive pop-up alert appeared, recommending CHB screening and offering three response options: “Accept,” “Reject,” or “Has evidence of testing” (to suppress alerts when prior testing occurred outside the hospital system). The alert automatically ceased once an HBsAg result or diagnosis was recorded. The clinical logic and eligibility criteria remained constant throughout the study. An interface-level modification was made mid-implementation: the option to dismiss the alert without selecting a response was removed to reduce passive dismissal and improve capture of provider actions, without altering the screening recommendation. POC HBsAg testing was introduced as an additional screening option alongside standard laboratory testing. The SD Bioline HBsAg WB® assay (World Health Organization-prequalified and nationally approved) was used for finger-stick capillary blood testing, with qualitative results available within approximately 20 minutes. 14 Testing was conducted by trained nurses in the Department of Microbiology, consistent with existing workflows. Clinicians provided brief pre- and post-test counseling according to hospital practice. Patients with negative results received prevention and vaccination advice, while those with positive results were referred to hepatology services for confirmatory testing and clinical evaluation. No changes to test procedures or eligibility criteria occurred during the implementation period. In this study, POC HBsAg testing functioned both as an additional screening modality and as an implementation strategy designed to reduce patient-level and structural barriers to completion of routine HBsAg screening. Outcomes and Data Sources Quantitative components Implementation outcomes included adoption and reach. These outcomes were selected to capture key dimensions of implementation performance, including provider engagement with intervention components and patient access to screening services. Adoption reflected clinician engagement with each strategy component. CME adoption was assessed using attendance logs. BPA adoption was defined as the proportion of triggered alerts that elicited any clinician response (accept, reject, or documentation of prior testing), based on EHR data. Adoption of POC HBsAg testing was measured as the proportion of all completed HBsAg tests performed using the POC modality during the final implementation phase, also derived from the EHR. Reach captured patient access to HBsAg testing during each implementation phase. Eligible patients were defined as those without prior hepatitis B testing or diagnosis at baseline. Reach was quantified as the proportion of unique eligible patients who completed HBsAg testing and the time from eligibility to testing among those tested, using EHR data. The primary service outcome was the HBsAg testing rate, defined as the number of completed tests per 1,000 outpatient visits per week, calculated from EHR-derived visit and testing records. Screening uptake was defined as the proportion of eligible primary care patients receiving HBsAg testing during the study period. Qualitative components Qualitative data were collected during the final four months of implementation, when all three strategy components were active, to explain quantitative patterns in adoption, reach, and service outcomes and to examine contextual influences on integration and sustainability. We used three complementary qualitative methods. First, non-participatory observations (NPO) were conducted by a trained research staff member in consultation rooms using structured tools to document real-time workflow and strategy execution, including BPA triggering, clinician responses, counseling behaviors, and completion of phlebotomy-based or POC testing. Given high patient volume, consecutive visits were observed as feasible. A supplemental special-case form was used to capture illustrative encounters that highlighted contextual barriers, adaptations, or deviations from expected practice. Second, brief patient exit interviews were conducted on observation days with patients who completed either phlebotomy-based or POC HBsAg testing. These 10-minute interviews focused on acceptability, perceived barriers, clarity of counseling, and comparisons between testing modalities. Responses were documented as structured notes in Vietnamese to minimize participant burden. Third, semi-structured in-depth interviews were conducted with primary care physicians and nurses across roles and seniority. Interviews were conducted online, lasted approximately 30 minutes, and explored perceptions of the acceptability, appropriateness, and feasibility of each strategy component, as well as workflow fit, role clarity, and sustainability. All interviews were conducted in Vietnamese, audio-recorded with consent, and transcribed verbatim for analysis, and guided by semi-structured interview guides developed a priori. Statistical Analysis Quantitative analyses evaluated implementation outcomes (adoption and reach) and service outcomes (HBsAg testing) across sequential implementation phases. Adoption metrics were summarized descriptively. CME adoption was defined as the proportion of eligible primary care providers attending each training session. BPA adoption was defined as the proportion of alerts that elicited acceptance of the recommendation or documentation of prior testing. Adoption of POC HBsAg was measured as the proportion of all completed HBsAg tests performed using the POC modality during the final implementation phase. Reach was assessed using time-to-event analyses among eligible patients, defined as those without prior hepatitis B testing or diagnosis. Time-to-testing was compared across phases using Kaplan–Meier curves and Cox proportional hazards models, with time zero defined as the first eligible outpatient visit within each phase. Patients were censored at the time of testing or at the last observed outpatient visit. Models were adjusted for age, sex, residence, route of national health insurance access, and calendar month. The unit of analysis was the individual patient. Service outcomes were evaluated using segmented regression models to assess changes in weekly HBsAg testing rates per 1,000 outpatient visits. Negative binomial regression was used to account for overdispersion. Separate models estimated immediate and gradual changes associated with the sequential introduction of CME training, CME plus BPA, and CME plus BPA plus POC testing. Model diagnostics showed no evidence of significant autocorrelation or seasonality. The unit of analysis was outpatient visits aggregated by week. All reach and service outcome analyses were replicated for prespecified negative control outcomes (LDL and glucose testing). Analyses were conducted using RStudio with R version 4.4.0. Qualitative Analysis We used a descriptive qualitative analytic approach to identify contextual factors influencing implementation. Provider interview transcripts, patient exit-interview notes, and non-participatory observation narratives were analyzed inductively. Data were read repeatedly to identify themes reflecting implementation experiences, barriers, and facilitators. Themes were then mapped post hoc onto domains and constructs of CFIR 2.0 to support systematic interpretation. 13 RESULTS Adoption Continiued medical education Table 1 summarizes participation in the three CME sessions and completion of post-session evaluations delivered between June 12 and June 19, 2024. Total number of participants varied across sessions. Among them, from 9 to 12 primary care providers (out of a total of 13) from targeted consultation rooms attended the sessions completed and passed the corresponding post-session evaluation. Table 1 Adoption of CME Sessions Based on Participation and Evaluation Completion Total participants completing pre-session evaluation Session 1 (June 12, 2024) Session 2 (June 18, 2024) Session 3 (June 19, 2024) 70 42 30 Total participants completing post- session evaluation 55 (55/55 Passed) 27 (27/27 Passed) 31 (31/31 Passed) Targeted PCPs completing pre-session evaluation 9 6 12 Targeted PCPs completing post-session evaluation 9 (9/9 Passed) 5 (5/5 Passed) 12 (12/12 Passed) Abbreviation: PCPs – Primary care professionals Best practice advisory From the introduction of the BPA on September 19, 2024 to the end of the study period, a total of 84,367 outpatient visits were recorded. BPA alerts did not fire in 4,307 visits (5.1%) which had documented prior hepatitis B testing (Table 2 ). Among the remaining 80,060 visits in which BPA fired, the most common provider response was to dismiss the alert without selecting a response option (66,765; 79.1%). In contrast, “Accept” was chosen in 343 (0.4%) alerts. Table 2 Summary of BPA Responses from Sep 19, 2024 onward Response Category Number of patient visits (%) No alerts 4,307 (5.1%) Dismissed 66,765 (79.1%) Accepted 343 (0.4%) Documented proof of prior testing 172 (0.2%) Rejected 12,780 (15.1%) Figure 1 shows weekly trends in BPA response following implementation. The number of ignored BPA alerts remained consistently the highest among all response categories. In contrast, “Accepted” responses remained relatively infrequent, but showed a modest upward trend over time. Point-of-Care HBsAg Rapid Testing Weekly rates for both standard phlebotomy-based and POC HBsAg rapid testing from September 16, 2024 onwards are presented in Fig. 2 . Prior to the introduction of POC HBsAg, only phlebotomy-based HBsAg tests were conducted. Immediately following POC HBsAg rollout, POC HBsAg increased sharply, reaching approximately 45 tests per 1,000 visits per week. This elevated rate was sustained for several weeks before declining gradually. In contrast, phlebotomy-based HBsAg testing rates decreased after POC rollout and remained low throughout the subsequent period. 2. Reach Descriptive Characteristics Table 3 presents the characteristics of 46,857 unique patients who entered care across four sequential periods defined by the timing of implementation components. Sex and age distributions were similar across periods. The majority of patients resided in Ho Chi Minh City, and most accessed care through in-network facilities. HBsAg testing uptake increased progressively across periods. The proportion of patients receiving HBsAg testing rose from 2.5% in the pre-intervention period to 2.7% during the CME phase, 3.2% after addition of the BPA, and 9.2% following the introduction of point-of-care testing. Measures of follow-up time and time to HBsAg testing decreased across successive periods. Median follow-up time declined from 27.8 days in the pre-intervention period to 0 days in the final period. Similarly, the median time from the first internal medicine visit to HBsAg testing decreased from 299 days before implementation to 0 days after the introduction of point-of-care testing. Table 3 Characteristics of patients by entry period at first internal medicine visits Variable Before Jun 13, 2024 a Pre-Implementation Jun 13–Sep 15, 2024 a CME Sep 16–Feb 23, 2025 a Adding BPA on top After Feb 24, 2025 a Adding POC HBsAg on top Number of unique patients 31,589 4,101 6,204 4,963 Sex Male 11,522 (36.5%) 1,523 (37.1%) 2,298 (37.0%) 1,807 (36.4%) Female 20,067 (63.5%) 2,578 (62.9%) 3,906 (63.0%) 3,156 (63.6%) Age 53 (39, 63) 49 (35, 60) 49 (36, 61) 49 (36, 60) Residence HCMC 17,815 (56.4%) 2,213 (54.0%) 3,538 (57.0%) 2,721 (54.8%) Bình Dương 131 (0.4%) 18 (0.4%) 30 (0.5%) 24 (0.5%) Vũng Tàu 209 (0.7%) 39 (1.0%) 71 (1.1%) 44 (0.9%) Other provinces 13,434 (42.5%) 1,831 (44.6%) 2,565 (41.3%) 2,174 (43.8%) Route of national health insurance access In-network (with referral) 17,633 (55.8%) 1,967 (48.0%) 3,036 (48.9%) 2,231 (45.0%) In-network (cross-facility access) 13,939 (44.1%) 2,131 (52.0%) 3,166 (51.0%) 2,732 (55.0%) Out-of-network (without referral) 17 (0.1%) 3 (0.1%) 2 (0.0%) 0 (0.0%) Tested for HBsAg 805 (2.5%) 110 (2.7%) 197 (3.2%) 455 (9.2%) Follow-up Time, days Mean (SD): 244.1 (316.0) Median (IQR): 27.8 (0.0, 477.7) Max: 909.2 Total: 7,711,479.6 Mean (SD): 55.0 (104.5) Median (IQR): 0.0 (0.0, 36.0) Max: 382.0 Total: 225,620.0 Mean (SD): 31.3 (64.0) Median (IQR): 0.0 (0.0, 16.9) Max: 283.2 Total: 194,438.4 Mean (SD): 7.1 (19.5) Median (IQR): 0.0 (0.0, 0.0) Max: 119.0 Total: 35,029.3 Time to HBsAg test, days Mean (SD): 321 (295) Median (IQR): 299 (14, 582) Max: 897 Total: 258,194 Mean (SD): 111 (123) Median (IQR): 31 (0, 225) Max: 359 Total: 12,260 Mean (SD): 41 (66) Median (IQR): 0 (0, 83) Max: 226 Total: 8,170 Mean (SD): 2 (8) Median (IQR): 0 (0, 0) Max: 69 Total: 794 a n (%), unless indicated otherwise Survival Analysis Kaplan–Meier curves showed differences in time to HBsAg testing across entry periods, with patients entering during later implementation phases experiencing earlier testing compared with those in the pre-implementation period (log-rank test, p < 0.001, Fig. 3 ). As shown in Table 4 , Cox proportional hazards models indicated higher hazards of receiving an HBsAg test among patients entering during the implementation periods relative to the pre-implementation group. In unadjusted analyses, hazard ratios increased across successive periods, from 2.74 (95% CI: 2.21–3.38) during the CME training phase to 10.13 (95% CI: 8.60–11.93) after full implementation. After adjustment for baseline characteristics (age, residence, route of National Health Insurance access, and calendar month), these associations remained statistically significant, although attenuation was observed. In parallel, analyses of glucose and LDL testing demonstrated more modest increases in testing hazards across the same periods. Table 4 Cox regression for time to HBsAg by entry period Study Periods HBsAg Glucose LDL HR (95% CI) Adjusted HR a (95% CI) HR (95% CI) Adjusted HR a (95% CI) HR (95% CI) Adjusted HR a (95% CI) Before Jun 13, 2024 Ref Ref Ref Ref Ref Ref Jun 13–Sep 15, 2024 2.74 (2.21–3.38) 2.36 (1.90–2.93) 1.77 (1.69–1.85) 1.43 (1.36–1.50) 1.81 (1.72–1.89) 1.44 (1.37–1.51) Sep 16–Feb 23, 2025 4.70 (3.93–5.62) 3.97 (3.28–4.81) 1.83 (1.75–1.90) 1.37 (1.32–1.44) 1.92 (1.84–2.00) 1.40 (1.34–1.47) After Feb 24, 2025 10.13 (8.60–11.93) 9.82 (8.31–11.61) 2.08 (1.99–2.18) 2.00 (1.91–2.09) 2.17 (2.07–2.27) 2.07 (1.97–2.16) a Adjustment for baseline variables (Age, Residence, Route of National Health Insurance Access, Calendar Month) Abbreviation: HR – Hazard Ratio 3. Service outcome Characteristics of Patient Visits A total of 225,209 outpatient visits were recorded in targeted consultation rooms across the study period (Table 5 ). Visit volume varied across implementation phases, reflecting the staggered rollout and differing observation windows. Overall patient and visit characteristics were stable across periods. The median patient age was approximately 60 years, and around two-thirds of visits involved female patients. Most visits were covered by in-network national health insurance, either through referral or cross-facility access, with minimal use of out-of-network care. The geographic distribution of visits remained consistent, with the majority originating from Ho Chi Minh City. Across all periods, the most frequent diagnostic categories were circulatory system diseases, followed by endocrine and metabolic conditions, with smaller proportions of digestive, respiratory, and other conditions. Table 5 Characteristics of outpatient visits at clinics by study period Characteristic Overall a Before June 13, 2024 a Pre-Implementation June 13, 2024 – Sept 16, 2024 a CME Sept 16, 2024 – Feb 24, 2025 a Adding BPA on top After Feb 24, 2025 a Adding POC HBsAg on top Total visits 225,209 127,764 23,919 41,299 32,227 Year of Visit 2023 88,875 (39%) 88,875 (70%) 0 (0%) 0 (0%) 0 (0%) 2024 90,871 (40%) 38,889 (30%) 23,919 (100%) 28,063 (68%) 0 (0%) 2025 45,463 (20%) 0 (0%) 0 (0%) 13,236 (32%) 32,227 (100%) Route of national health insurance access In-network (with referral) 146,319 (65%) 83,886 (66%) 15,323 (64%) 26,728 (65%) 20,382 (63%) In-network (cross-facility access) 78,867 (35%) 43,860 (34%) 8,593 (36%) 14,569 (35%) 11,845 (37%) Out-of-network (without referral) 22 (< 0.1%) 17 (< 0.1%) 3 (< 0.1%) 2 (< 0.1%) 0 (0%) Not using insurance 1 (< 0.1%) 1 (< 0.1%) 0 (0%) 0 (0%) 0 (0%) Age 60 (51, 68) 60 (51, 68) 60 (50, 68) 60 (51, 68) 60 (50, 68) Sex Male 84,371 (37%) 48,007 (38%) 8,906 (37%) 15,504 (38%) 11,954 (37%) Female 140,838 (63%) 79,757 (62%) 15,013 (63%) 25,795 (62%) 20,273 (63%) Areas of Residence HCMC 147,238 (65%) 83,201 (65%) 15,544 (65%) 27,214 (66%) 21,279 (66%) Bình Dương 888 (0.4%) 505 (0.4%) 102 (0.4%) 157 (0.4%) 124 (0.4%) Vũng Tàu 877 (0.4%) 452 (0.4%) 96 (0.4%) 195 (0.5%) 134 (0.4%) Other provinces 76,206 (34%) 43,606 (34%) 8,177 (34%) 13,733 (33%) 10,690 (33%) Condition classification by ICD-10 Diseases of the circulatory system 93,219 (41%) 53,470 (42%) 9,697 (41%) 17,189 (42%) 12,863 (40%) Endocrine, nutritional and metabolic diseases 61,267 (27%) 34,021 (27%) 6,509 (27%) 11,391 (28%) 9,346 (29%) Diseases of the digestive system 15,422 (6.8%) 8,930 (7.0%) 1,653 (6.9%) 2,670 (6.5%) 2,169 (6.7%) Diseases of the eye and adnexa 12,472 (5.5%) 6,955 (5.4%) 1,433 (6.0%) 2,242 (5.4%) 1,842 (5.7%) Diseases of the respiratory system 8,930 (4.0%) 4,981 (3.9%) 897 (3.8%) 1,880 (4.6%) 1,172 (3.6%) Other groups 33,899 (15%) 19,407 (15%) 3,730 (16%) 5,927 (14%) 4,835 (15%) a n (%); Median (IQR) Trends in Patient Visits Over Time Weekly patient visit volumes remained stable throughout the study period, with no abrupt disruptions coinciding with the phased introduction of implementation components (Fig. 4 ). No clear seasonal pattern was apparent. Time-Series Analysis of Intervention Impact Figure 5 displays weekly HBsAg testing rates standardized per 1,000 visits, with vertical markers indicating the timing of CME, BPA, and POC HBsAg rollout. Testing rates remained low and relatively stable prior to implementation, with modest changes following CME and BPA introduction. In contrast, a pronounced increase in testing rates occurred immediately after the introduction of POC HBsAg testing, followed by a gradual decline over subsequent weeks. Interrupted time-series analyses in Table 6 showed that the introduction of POC HBsAg was associated with a large and statistically significant immediate increase in HBsAg testing rates. In contrast, CME alone was not associated with significant immediate or gradual changes, and the addition of the BPA was associated with a small immediate decrease in testing rates without evidence of a sustained post-intervention trend. Following the initial increase after POC HBsAg rollout, HBsAg testing rates demonstrated a significant gradual decline over subsequent weeks, indicating attenuation after an early peak. For negative control outcomes, no consistent immediate or gradual effects were observed following CME or BPA implementation. Modest immediate increases were observed for glucose and LDL testing after the final rollout phase but not accompanied by sustained post-rollout trends. Table 6 Immediate and gradual effects of implementation components on HBsAg testing Component Immediate RR (95% CI) Weekly RR following each rollout (95% CI) HBsAg testing Education only 1.14 (0.74 to 1.74) 1.002 (0.957 to 1.049) Education + BPA 0.57 (0.33 to 0.98) 1.045 (0.985 to 1.109) Education + BPA + POC 5.05 (3.13 to 8.19) 0.884 (0.847 to 0.923) Glucose testing Education only 1.10 (0.93 to 1.32) 0.995 (0.976 to 1.014) Education + BPA 1.03 (0.85 to 1.26) 0.995 (0.973 to 1.017) Education + BPA + POC 1.32 (1.09 to 1.58) 1.008 (0.992 to 1.024) LDL testing Education only 1.06 (0.85 to 1.33) 0.991 (0.967 to 1.015) Education + BPA 1.08 (0.85 to 1.37) 0.998 (0.972 to 1.025) Education + BPA + POC 1.35 (1.08 to 1.69) 1.011 (0.992 to 1.031) 4. Acceptability, Appropriateness, Feasibility, and Contextual Changes Qualitative findings contextualized the stepwise changes observed across implementation phases. Table 7 summarizes key contextual factors identified through CFIR-guided analysis, while Table S2 presents detailed results from the qualitative analyses. Although CME improved provider knowledge and perceived appropriateness of HBV screening, structural barriers, particularly lack of insurance reimbursement and high patient volume, limited consistent translation into routine practice. Providers described time pressure and competing acute care priorities that constrained counseling, which may explain the modest gains during the CME and BPA phases. While BPA increased screening prompts, its impact depended on staff engagement and workflow conditions. Observational data indicated that alerts were sometimes dismissed during busy sessions, contributing to incomplete execution of the screening pathway. In contrast, the POC HBsAg phase addressed key barriers identified in earlier phases. Both providers and patients emphasized the convenience, rapid turnaround time, and reduced invasiveness of finger-prick testing. Importantly, removal of out-of-pocket costs substantially increased patient willingness to test. These factors together help explain the marked increase in screening uptake observed during the POC HBsAg phase. Table 7 CFIR-based contextual factors influencing the implementation strategy CFIR Domain CFIR Construct Thematic Interpretation Relevant Strategy Component Illustrative Quotes/Observations Outer Setting Financing Lack of insurance reimbursement for laboratory-based CHB screening created a structural financial barrier, limiting the impact of CME and BPA despite increased provider awareness. CME, BPA, Standard lab “…why do they pay for health insurance but still have to pay out of pocket…” – IDI, Physician 1 “…we rarely manage hepatitis B … because health insurance does not cover care…” – IDI, Physician 2 Inner Setting Relative Priority Preventive screening was deprioritized in insurance-driven visits focused on acute or existing complaints. CME; BPA “…after dealing with chronic conditions or acute issues, there is no time left in the consultation…” – IDI, Physician 4 Inner Setting Compatibility High patient volume and time pressure constrained in-depth counseling and reduced consistent enactment of BPA prompts. BPA; CME “…when the clinic is very busy… we have to move quickly…” – IDI, Physician 5 Inner Setting Compatibility BPA alerts were variably enacted. Prompts did not uniformly translate into counseling or test ordering, particularly during busy sessions. BPA “The BPA reminder appears, but the nurse closed the pop-up…” – NPO, an observed case Individuals Innovation deliverers CME improved perceived appropriateness and knowledge of CHB screening, but structural constraints limited behavioral change. CME “…the training session very useful… guiding us on how to counsel patients for hepatitis B screening…” – IDI, Nurse 1 Individuals Innovation recipients Out-of-pocket costs, low perceived risk among asymptomatic patients, and predefined visit goals reduced acceptance of laboratory screening. CME, BPA, POC HBsAg “…if they have to pay nearly 500,000 VND, most people think it’s not important.” – IDI, Physician 2 Innovation Characteristics Relative Advantage POC HBsAg testing perceived as faster, less invasive, and more convenient, increasing immediate acceptance. POC HBsAg “Patients find the test fast and convenient.” – Patient exit interview, patient 9 “…the results come back quickly… it only takes a few minutes.” – IDI, Physician 1 Innovation Characteristics Cost Removal of patient cost for POC HBsAg testing eliminated financial hesitation and shifted decision-making toward immediate testing. POC HBsAg “Now that the test is free, people are very willing to do it.” – IDI, Physician 1 Innovation Characteristics Complexity Repeated or interruptive BPA alerts contributed to alert fatigue and selective dismissal during high workload periods. BPA “…it keeps reminding repeatedly for many cases… having to close it is quite inconvenient.” – IDI, Physician 1 Innovation Characteristics Evidence-base and Adaptability Uncertainty about POC HBsAg test accuracy and insurance recognition influences provider confidence in use. POC HBsAg “…we are concerned about sensitivity and specificity… and whether insurance covers it.” – IDI, Physician 5 Abbreviation: IDI – In-depth Interview; NPO – Non-participatory observation. Overall, implementation of the multi-component strategy resulted in a substantial increase in CHB screening uptake, with the largest effect observed after removal of structural barriers through free point-of-care rapid testing. DISCUSSION In this study, implementation of a multi-component strategy integrating provider education, EMR-based clinical decision support, and point-of-care HBsAg rapid testing significantly increased hepatitis B screening uptake in a large public primary care system in Vietnam. Within the CFIR framework, several determinants appeared particularly influential for implementation success, including provider knowledge and beliefs (Characteristics of Individuals), workflow compatibility within busy outpatient clinics (Inner Setting), and structural barriers affecting patient access to testing (Outer Setting). At the individual level, survival analyses showed progressively shorter time-to-testing across implementation phases, with the most pronounced acceleration following the introduction of free POC HBsAg testing. At the system level, interrupted time-series analyses confirmed a sharp immediate increase in weekly testing rates after POC HBsAg rollout, while earlier components yielded minimal change. By integrating individual-level, service-level, and qualitative findings, we clarify not only whether screening increased, but how and why different components performed differently within this context. The findings highlight the importance of multi-component implementation strategies that simultaneously address provider knowledge, workflow integration, and diagnostic accessibility to expand hepatitis B diagnosis in primary care settings. CME improved provider knowledge and counseling confidence but translated into only small increases in screening. During the pre-POC-HBsAg phases, testing rose modestly among eligible patients, suggesting that enhanced capability alone was insufficient to overcome structural barriers. Electronic BPA showed similarly limited effect. Although alerts were frequently triggered, most were dismissed, and formal acceptance was rare. Qualitative findings revealed alert fatigue, competing clinical priorities, unclear task ownership, and frustration with inaccurate alerts due to incomplete documentation of prior testing. In high-volume, insurance-driven visits focused on acute complaints, preventive screening held low relative priority. These findings indicate that informational and cognitive supports were layered onto persistent workflow and financing constraints, limiting their practical impact. A recent meta-analysis reported that electronic reminders increased chronic hepatitis B testing by approximately 8% on average, but heterogeneity across studies was substantial (I² = 95%). 12 Our current findings align with this variability and suggest that reminder effectiveness is highly context-dependent. In environments characterized by heavy workload, team-based task delegation, and competing visit objectives, digital prompts alone may not overcome embedded structural frictions. 15 In contrast, free POC HBsAg rapid testing shifted screening behavior. Uptake increased sharply following its introduction, particularly at the individual level where time-to-testing accelerated markedly. Removing cost, reducing procedural burden, and providing same-day results addressed key opportunity constraints identified qualitatively. From a CFIR perspective, POC HBsAg demonstrated strong relative advantage, improved compatibility with patient needs, and reduced perceived complexity. 16 At the same time, some providers expressed uncertainty about rapid-test accuracy and insurance recognition, occasionally prompting confirmatory laboratory testing, highlighting that perceived evidence strength remains relevant for sustainability. The divergence between individual-level reach estimates and aggregate service-level trends warrants consideration. Survival analyses captured acceleration in testing among eligible individuals, whereas interrupted time-series models evaluated weekly testing volume per visit across the entire clinic population. Improvements in access among eligible patients may therefore appear larger at the individual level than at the system level, where effects are diluted across all outpatient visits and constrained by clinic capacity. Together, these analyses provide complementary perspectives on implementation impact across levels of care delivery. The phased rollout functioned as a pragmatic natural experiment, enabling examination of incremental contributions of each component. Education and reminders primarily targeted provider capability and motivation, but screening accelerated only when structural opportunity expanded through removal of financial and procedural barriers. This pattern aligns with behavioral theory emphasizing that opportunity is necessary in addition to capability for behavior change. 17 Additionally, our findings are consistent with community-based hepatitis B screening programs that achieved high uptake through combined strategies, including education, decision support, cost removal, and stakeholder engagement. 18 Primary care platforms may therefore represent one of the most scalable pathways to expand CHB diagnosis in high-burden settings where specialist hepatology services are limited. Applied to primary care, the results suggest that provider-focused strategies must be coupled with workflow redesign and patient-facing enablers. Education remains necessary but insufficient when structural barriers dominate. Strengths of this study include its real-world implementation setting, integration of the intervention within routine clinical workflows, and evaluation within a high-volume public primary care system serving a large patient population. Several limitations are acknowledged. The study was conducted in a single primary care system. However, the intervention components are readily scalable to other settings with EMR infrastructure and existing primary care networks. Also, because this study lacked a concurrent control group, residual secular trends in CHB awareness or screening practices cannot be excluded. To mitigate this concern, we deployed interrupted time-series modeling and negative controls. Furthermore, we evaluated screening uptake but did not assess downstream outcomes such as confirmatory testing, linkage to care, or treatment initiation. Future implementation efforts should integrate structured linkage-to-care pathways to ensure that patients identified through screening receive appropriate evaluation and treatment. In conclusion, a multi-component implementation strategy integrating provider education, EMR-based clinical decision support, and point-of-care HBsAg rapid testing substantially increased CHB screening uptake in a high-volume public primary care system in Vietnam. These findings suggest that integrating HBV screening into routine primary care workflows may represent a scalable strategy to accelerate CHB diagnosis and support progress toward hepatitis B elimination in resource-constrained settings. Declarations Author Contributions T.V.K. conceptualized the study, developed the methodology, conducted the formal analysis and investigation, acquired funding, prepared the visualizations, and wrote the original draft of the manuscript and subsequent revisions. T.N.D.P. conceptualized the study, developed the methodology, supervised the work, validated the findings, and reviewed and edited the manuscript. D.Da. (Diem Dao) and A.N.L. contributed to project administration, resources, and review and editing of the manuscript. L.P. contributed to project administration, resources, and data collection. L.H.H.L. contributed to methodology development, formal analysis, and qualitative data collection. T.T.L., C.Q.L., H.T.V., T.B.D., T.Q.P.T., V.H.L.D., and T.H.T.N. contributed to resources, project administration, and supervision. K.V.T. and D.Do. (Doan Dao) contributed to conceptualization, funding acquisition, resources, supervision, validation, and writing of the original draft, and reviewed and edited the manuscript. All authors contributed to interpretation of the data, critically revised the manuscript, and approved the final version. Funding This work was supported by the All4Liver Grant from Gilead Sciences (Grant No. 23007 in 2023). The funder had no role in the design of the study; collection, analysis, or interpretation of data; or in writing the manuscript. Availability of data and materials The datasets analyzed during the current study include routinely collected electronic medical record data and qualitative interview data. Due to institutional policies, these data are not publicly available. De-identified data may be made available from the corresponding author on reasonable request, subject to approval by the Institutional Review Board of Lê Văn Thịnh Hospital. Ethics approval and consent to participate This study was conducted in accordance with the Declaration of Helsinki. The study was prospectively registered on ClinicalTrials.gov (NCT06403657). Ethical approval was obtained from the Institutional Review Board of Lê Văn Thịnh Hospital (Decision No. 264/QĐ‑BVLVT). The requirement for informed consent was waived by the Institutional Review Board for the use of de‑identified EMR data. Written informed consent was obtained from all individuals participating in the qualitative assessment. Consent for publication Not applicable. Competing interests The authors declare that they have no competing interests. Author details a Department of Epidemiology, Pham Ngoc Thach University of Medicine, Ho Chi Minh City, Viet Nam. b Gastroenterology and Hepatology Division, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA. c School of Public Health, University of Illinois at Chicago, Chicago, IL, USA. d Vietnam Viral Hepatitis Alliance, Reston, VA, USA. e Le Van Thinh Hospital, Thu Duc City, Ho Chi Minh City, Viet Nam. f University of Medicine and Pharmacy at Ho Chi Minh City, Viet Nam. g Department of Gastroenterology, An Binh Hospital, Ho Chi Minh City, Viet Nam. h Program in Global Primary Health Care, Harvard Medical School, Boston, MA, USA. References World Health Organization. Global hepatitis report 2024: action for access in low-and middle-income countries: World Health Organization; 2024. Holt B, Fernandez M, Nguyen D, et al. Embedding viral hepatitis into primary healthcare: results of a strategic landscape analysis in Vietnam and the Philippines. Lancet Reg Health West Pac 2024; 44 : 100990. World Health Organization Regional Office for the Western Pacific. Viral hepatitis situation adn response in Vietnam. Manila, Philippines, 2018. Pham TND, Le DH, Dao DVB, et al. Establishing baseline framework for hepatitis B virus micro-elimination in Ho Chi Minh City, Vietnam – a community-based seroprevalence study. The Lancet Regional Health – Western Pacific 2023; 30 . Conners EE. Screening and testing for hepatitis B virus infection: CDC recommendations—United States, 2023. MMWR Recommendations and Reports 2023; 72 . World Health Organization. Guidelines for the prevention, diagnosis, care and treatment for people with chronic hepatitis B infection, 2024. Fernandez ML, Nguyen H, Nguyen D, et al. Healthcare system readiness to manage viral hepatitis in Viet Nam and the Philippines: results of a brief health facility assessment. BMC Health Serv Res 2026. Pham TND, Hoang LB, Dao DVB, et al. Expanding Hepatitis B Screening with Point-of-Care Rapid Testing in Primary Care: An Implementation Science Study. medRxiv 2024: 2024.08.29.24312788. Holt B, Mendoza J, Nguyen H, et al. Barriers and enablers to people-centred viral hepatitis care in Vietnam and the Philippines: Results of a patient journey mapping study. J Viral Hepat 2024; 31 (7): 391-403. Hang Pham TT, Le TX, Nguyen DT, et al. Knowledge, attitudes and medical practice regarding hepatitis B prevention and management among healthcare workers in Northern Vietnam. PloS one 2019; 14 (10): e0223733. Hoa NT, Derese A, Peersman W, Markuns JF, Willems S, Tam NM. Primary care quality in Vietnam: Perceptions and opinions of primary care physicians in commune health centers - a mixed-methods study. PLoS One 2020; 15 (10): e0241311. Kim TV, Pham TND, Phan P, et al. Effectiveness and implementation of decentralized, community- and primary care-based strategies in promoting hepatitis B testing uptake: a systematic review and meta-analysis. EClinicalMedicine 2024; 76 : 102818. Damschroder LJ, Reardon CM, Opra Widerquist MA, Lowery J. Conceptualizing outcomes for use with the Consolidated Framework for Implementation Research (CFIR): the CFIR Outcomes Addendum. Implementation Science 2022; 17 (1): 7. World Health Organization. WHO list of prequalified in vitro diagnostic products. 2023. https://extranet.who.int/prequal/sites/default/files/document_files/231020_prequalified_IVD_product_list.pdf (accessed March 13 2024). Sequist TD, Zaslavsky AM, Marshall R, Fletcher RH, Ayanian JZ. Patient and Physician Reminders to Promote Colorectal Cancer Screening: A Randomized Controlled Trial. Archives of Internal Medicine 2009; 169 (4): 364-71. Bottero J, Boyd A, Gozlan J, et al. Simultaneous Human Immunodeficiency Virus-Hepatitis B-Hepatitis C Point-of-Care Tests Improve Outcomes in Linkage-to-Care: Results of a Randomized Control Trial in Persons Without Healthcare Coverage. Open Forum Infect Dis 2015; 2 (4): ofv162. Michie S, van Stralen MM, West R. The behaviour change wheel: a new method for characterising and designing behaviour change interventions. Implement Sci 2011; 6 : 42. Ma GX, Lee MM, Tan Y, et al. Efficacy of a community-based participatory and multilevel intervention to enhance hepatitis B virus screening and vaccination in underserved Korean Americans. Cancer 2018; 124 (5): 973-82. Additional Declarations No competing interests reported. Supplementary Files Appendixv1.1260319.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9200793","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":614665517,"identity":"e89612f3-d1ca-4640-8ca5-ac7c57b32564","order_by":0,"name":"Thanh V. Kim","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAyUlEQVRIiWNgGAWjYDACCQYGZoYDDHIQHhsROnigWoxBFGlaEhuI1mIv3fzsccGZw+nbpfsPMHwoO8xgcLuBgC0yx8yNZ9w4nLtzzmEGxhnngFruHCDksAQzaZ4PabkbbiQzMPO2HWaQnJFASEv6N5CWdAOQlr/EackB2nLDJgGshRGohV+CkJYbOWXSPGdsDHfOSDY42HMunYegFvYZ6dukeY5JyJtLJD588KPMWo6NkBY4MADiAyBriVQP1TIKRsEoGAWjACsAAO8aPn9eL4Z8AAAAAElFTkSuQmCC","orcid":"","institution":"Pham Ngoc Thach University of Medicine","correspondingAuthor":true,"prefix":"","firstName":"Thanh","middleName":"V.","lastName":"Kim","suffix":""},{"id":614665518,"identity":"f0b89d76-eb1a-425b-a59f-2fcc4605fa5b","order_by":1,"name":"Diem Dao","email":"","orcid":"","institution":"Vietnam Viral Hepatitis Alliance","correspondingAuthor":false,"prefix":"","firstName":"Diem","middleName":"","lastName":"Dao","suffix":""},{"id":614665519,"identity":"e6b58e5b-d235-47a3-acad-3ce0e8867be6","order_by":2,"name":"Trang N.D. Pham","email":"","orcid":"","institution":"University of Illinois at Chicago","correspondingAuthor":false,"prefix":"","firstName":"Trang","middleName":"N.D.","lastName":"Pham","suffix":""},{"id":614665520,"identity":"76eea2a1-5a72-40fa-a8ca-5c0a2df6b7d7","order_by":3,"name":"Loc Phan","email":"","orcid":"","institution":"Vietnam Viral Hepatitis Alliance","correspondingAuthor":false,"prefix":"","firstName":"Loc","middleName":"","lastName":"Phan","suffix":""},{"id":614665521,"identity":"d8410a38-59c1-47e7-b9a6-86539f6198e2","order_by":4,"name":"Linh H.H. Le","email":"","orcid":"","institution":"Pham Ngoc Thach University of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Linh","middleName":"H.H.","lastName":"Le","suffix":""},{"id":614665522,"identity":"e08d8571-1f4f-4495-8a74-3795a6eeffcb","order_by":5,"name":"Toan T. Le","email":"","orcid":"","institution":"Le Van Thinh Hospital","correspondingAuthor":false,"prefix":"","firstName":"Toan","middleName":"T.","lastName":"Le","suffix":""},{"id":614665523,"identity":"ec5e5f69-315b-4698-beb1-fec3d3a31ef5","order_by":6,"name":"Cong Q. Ly","email":"","orcid":"","institution":"Le Van Thinh Hospital","correspondingAuthor":false,"prefix":"","firstName":"Cong","middleName":"Q.","lastName":"Ly","suffix":""},{"id":614665524,"identity":"ab070e44-9d1f-490b-ad23-d3d478ef1ccc","order_by":7,"name":"Hung T. Vo","email":"","orcid":"","institution":"Le Van Thinh Hospital","correspondingAuthor":false,"prefix":"","firstName":"Hung","middleName":"T.","lastName":"Vo","suffix":""},{"id":614665525,"identity":"a22fc92a-e550-480e-b647-ad6f6861bbc6","order_by":8,"name":"Tung B. Do","email":"","orcid":"","institution":"Le Van Thinh Hospital","correspondingAuthor":false,"prefix":"","firstName":"Tung","middleName":"B.","lastName":"Do","suffix":""},{"id":614665526,"identity":"29fd198c-4813-4207-8420-6099f048853c","order_by":9,"name":"Thuy Q.P. Tran","email":"","orcid":"","institution":"Le Van Thinh Hospital","correspondingAuthor":false,"prefix":"","firstName":"Thuy","middleName":"Q.P.","lastName":"Tran","suffix":""},{"id":614665527,"identity":"2dd51e09-44b1-4e18-bde6-49288c2f0a12","order_by":10,"name":"Vu H. L. Dang","email":"","orcid":"","institution":"Le Van Thinh Hospital","correspondingAuthor":false,"prefix":"","firstName":"Vu","middleName":"H. L.","lastName":"Dang","suffix":""},{"id":614665528,"identity":"61fb9b6b-6d26-4e29-a7e3-170fa8da142d","order_by":11,"name":"Trang H.T. Nguyen","email":"","orcid":"","institution":"Le Van Thinh Hospital","correspondingAuthor":false,"prefix":"","firstName":"Trang","middleName":"H.T.","lastName":"Nguyen","suffix":""},{"id":614665529,"identity":"a21f5b50-2cf2-4d12-8505-99d46b3d2f5c","order_by":12,"name":"Anh N. Le","email":"","orcid":"","institution":"Vietnam Viral Hepatitis Alliance","correspondingAuthor":false,"prefix":"","firstName":"Anh","middleName":"N.","lastName":"Le","suffix":""},{"id":614665530,"identity":"214006a7-6788-46ec-9a9b-a8fe437d4f64","order_by":13,"name":"Khanh V. Tran","email":"","orcid":"","institution":"Le Van Thinh Hospital","correspondingAuthor":false,"prefix":"","firstName":"Khanh","middleName":"V.","lastName":"Tran","suffix":""},{"id":614665531,"identity":"c5bd9601-06c4-4723-8f9a-569b7891dacf","order_by":14,"name":"Doan Dao","email":"","orcid":"","institution":"Massachusetts General Hospital, Harvard Medical School","correspondingAuthor":false,"prefix":"","firstName":"Doan","middleName":"","lastName":"Dao","suffix":""}],"badges":[],"createdAt":"2026-03-23 12:54:10","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9200793/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9200793/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":105882382,"identity":"54ec7491-b510-433c-bb57-6063f201609e","added_by":"auto","created_at":"2026-04-01 06:56:34","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":157114,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eWeekly BPA response trends across categories following rollout on September 19, 2024\u003c/em\u003e\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-9200793/v1/4487377c634cd5eb6e9c7487.png"},{"id":105882617,"identity":"9c80d201-7b51-43f4-8f48-e57c2ab850ce","added_by":"auto","created_at":"2026-04-01 06:57:11","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":86523,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eWeekly Rates of Standard and Point-of-Care (POC) HBsAg Testing Since September 16, 2024\u003c/em\u003e\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-9200793/v1/173ed19bc8dedaf3dd562919.png"},{"id":105882367,"identity":"8a550060-3dfc-412d-9cad-47dfc9c5f6d9","added_by":"auto","created_at":"2026-04-01 06:56:34","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":129912,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eKaplan-Meier curves for time to HBsAg testing by entry period\u003c/em\u003e\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-9200793/v1/94267645880408ba7a0c7a9e.png"},{"id":105882644,"identity":"02d4d277-4e98-43f0-8191-7b99800e7dbb","added_by":"auto","created_at":"2026-04-01 06:57:19","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":109969,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eWeekly patient visit trends during the study period\u003c/em\u003e\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-9200793/v1/883f3075d890774a5d8981a1.png"},{"id":105882364,"identity":"bc1ff5dd-be1c-46e5-9e5f-1c861e272fa4","added_by":"auto","created_at":"2026-04-01 06:56:33","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":77587,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eWeekly HBsAg testing rates per 1,000 visits and implementation time points\u003c/em\u003e\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-9200793/v1/d94b7533701092cba6f6cc31.png"},{"id":106031646,"identity":"f1fae179-1d2e-4e6e-8065-29d3a484b838","added_by":"auto","created_at":"2026-04-02 15:26:56","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2268940,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9200793/v1/7b57dc1b-c0ee-4b0f-b940-8c75da76d80d.pdf"},{"id":105882368,"identity":"2912e749-82dc-40b2-96d5-a5a375dc130c","added_by":"auto","created_at":"2026-04-01 06:56:34","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":46379,"visible":true,"origin":"","legend":"","description":"","filename":"Appendixv1.1260319.docx","url":"https://assets-eu.researchsquare.com/files/rs-9200793/v1/c278cace11757b1728417b95.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"A Multi-Component Implementation Strategy to Expand Hepatitis B Screening in Primary Care in Viet Nam: A Mixed-Methods Study","fulltext":[{"header":"Contributions to the literature","content":"\u003cul\u003e\n \u003cli\u003eThis study provides one of the first mixed-methods implementation evaluations of hepatitis B screening in primary care from Viet Nam and other low- and middle-income settings, where evidence on how to operationalize routine screening within high-volume, resource-constrained systems remains limited.\u003c/li\u003e\n\u003c/ul\u003e\n\u003cul\u003e\n \u003cli\u003eBy combining interrupted time-series analysis with CFIR-guided qualitative inquiry, the study demonstrates that implementation components contribute unequally to adoption and reach, with structural determinants, particularly financing constraints, workflow compatibility, and relative priority, exerting stronger influence than informational strategies alone.\u003c/li\u003e\n\u003c/ul\u003e\n\u003cul\u003e\n \u003cli\u003eThe findings clarify that provider education and electronic reminders may increase knowledge and cognitive awareness, but are insufficient when layered onto persistent structural frictions embedded in routine care delivery. In contrast, resource-enabling strategies that remove patient-facing financial and procedural barriers generate substantially greater impact.\u003c/li\u003e\n\u003c/ul\u003e\n\u003cul\u003e\n \u003cli\u003eThe integration of negative control outcomes, direct workflow observations, and patient-reported acceptability strengthens causal interpretation and helps distinguish strategy-specific effects from secular testing trends or documentation artifacts.\u003c/li\u003e\n\u003c/ul\u003e\n\u003cul\u003e\n \u003cli\u003eFor scale-up in Viet Nam and similar settings, the study highlights the importance of aligning implementation strategies with contextual determinants, particularly reducing out-of-pocket costs, minimizing workflow disruption, and enhancing perceived feasibility, rather than relying solely on education or digital prompting.\u003c/li\u003e\n\u003c/ul\u003e"},{"header":"INTRODUCTION","content":"\u003cp\u003eChronic hepatitis B (CHB) remains a major global health challenge, responsible for 254\u0026nbsp;million chronically infected and over 1\u0026nbsp;million CHB-related deaths annually.\u003csup\u003e1\u003c/sup\u003e In Viet Nam \u0026ndash; among the countries with the highest HBV burden \u0026ndash; antiviral treatment such as tenofovir and entecavir is widely available and largely reimbursed by national health insurance.\u003csup\u003e2\u003c/sup\u003e Yet treatment coverage remains extremely low, with fewer than 5% of eligible individuals receiving antiviral therapy.\u003csup\u003e3\u003c/sup\u003e A central driver of this treatment gap is the deficit in diagnosis, with an estimated 70% of people living with CHB in Viet Nam unaware of their infection status.\u003csup\u003e4\u003c/sup\u003e This undiagnosed population, disconnected from the care cascade, continues to suffer preventable complications and perpetuate community transmission.\u003c/p\u003e \u003cp\u003eHBsAg testing is the first critical step for diagnosing CHB. Both the World Health Organization and the US Centers for Disease Control recommend routine HBsAg screening as part of universal hepatitis elimination strategies.\u003csup\u003e5,6\u003c/sup\u003e For current practice in Viet Nam, however, HBsAg testing is usually performed only under specific circumstances (e.g., clinical suspicion, patient request, documented risk factors, or pregnancy) rather than as a routine preventive service.\u003csup\u003e7\u003c/sup\u003e This testing gap is shaped by multiple barriers at several levels. At the patient level, limited knowledge of the disease, concerns about out-of-pocket costs, fear of invasive procedures deter screening, and slow turnaround of test results.\u003csup\u003e8,9\u003c/sup\u003e At the healthcare provider level, unawareness of the burden of hepatitis B, time constraints, and competing clinical priorities contribute to missed testing opportunities.\u003csup\u003e10,11\u003c/sup\u003e. Taken together, these barriers span multiple domains of healthcare delivery, including provider knowledge and beliefs, workflow compatibility within clinical settings, and structural constraints affecting patient access to testing.\u003c/p\u003e \u003cp\u003ePrimary care systems represent an important platform for expanding CHB diagnosis, particularly in high-burden settings where specialist hepatology services are limited. Our prior systematic review and analysis has documented that provider education, electronic reminders, and point-of-care rapid testing can increase uptake of CHB screening service in primary care setting, \u003csup\u003e12\u003c/sup\u003e supporting a multi-component implementation strategy. However, the effectiveness of such strategies varies across health systems and has not been tested in practice.\u003csup\u003e12\u003c/sup\u003e As such, it remains unclear whether they can be successfully integrated into Viet Nam\u0026rsquo;s primary care environment with different contextual influencers. To date, no study has examined the real-world implementation of a combined approach involving provider education, electronic reminders, and point-of-care HBsAg testing in Vietnamese public primary care settings.\u003csup\u003e12\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e Taken together, this study tests the implementation of a multi-component strategy (combining provider training, electronic reminders, and point-of-care HBsAg testing) within a large public primary care hospital in Ho Chi Minh City. Drawing on constructs from the Consolidated Framework for Implementation Research 2.0 (CFIR 2.0), the intervention components were designed to address barriers operating at the level of individual providers, clinical workflow, and patient access to testing. Our primary aim is to assess key implementation outcomes, including reach and adoption, and to determine whether the strategy increases the overall volume of HBsAg testing delivered. The secondary aim is to explore clinician and patient experiences with the implementation strategies and to identify contextual factors influencing their integration and sustainability in routine practice. Ultimately, this study seeks to generate actionable evidence to support system-level integration of routine CHB testing across Viet Nam\u0026rsquo;s primary care system and contribute to national hepatitis B elimination goals.\u003c/p\u003e"},{"header":"METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy design and context\u003c/h2\u003e \u003cp\u003eWe conducted a quasi-experimental implementation trial with a mixed-methods evaluation to increase uptake of HBsAg testing in primary care. Quantitative analyses of electronic health record (EHR) data assessed implementation outcomes (adoption and reach) and service outcomes using interrupted time-series and survival analyses. Qualitative methods were used to examine contextual factors influencing implementation and to interpret quantitative findings. The study was conceptually informed by the CFIR 2.0, which guided identification of contextual determinants, interpretation of implementation mechanisms, and qualitative analysis of barriers and facilitators.\u003csup\u003e13\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e The study was conducted in the primary care consultation rooms of the outpatient department at L\u0026ecirc; Văn Thịnh Hospital, a large public primary care hospital in Ho Chi Minh City, Viet Nam, serving the eastern catchment of the city. The hospital uses the HIS 2.0 system to support clinical and administrative workflows. During the study period, 13 providers (10 physicians and 3 nurses) staffed the participating consultation rooms. At baseline, HBsAg testing was performed exclusively using phlebotomy-based laboratory assays, and screening tests were not reimbursed by national health insurance. In addition to screening, the hospital provides hepatitis B vaccination services and specialty hepatology consultation.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eImplementation Strategy\u003c/h3\u003e\n\u003cp\u003e The innovation under study was routine HBsAg screening delivery in primary care. To support its implementation, we introduced a three-component implementation strategy using a stepwise rollout over 12 months. Each strategy component was designed to address specific determinants identified during the pre-implementation assessment: Continued Medical Education training (CME) targeted provider knowledge and beliefs about screening, the Best Practice Advisory reminder (BPA) addressed missed opportunities within clinical workflow, and Point-of-care HBsAg testing (POC HBsAg) addressed structural and patient-level barriers including cost, venipuncture, and turnaround time. In the first four months, we introduced CME-accredited training to improve provider knowledge, confidence, and perceived appropriateness of hepatitis B screening, without changing routine clinical workflows. In months 5\u0026ndash;8, we added BPA within the EHR to prompt screening during eligible outpatient encounters and address workflow-related missed opportunities. In the final four months, POC HBsAg was integrated on top of the BPA to reduce patient-level barriers, including cost, venipuncture, and long turnaround times, and to enable same-day screening. This sequential implementation enabled assessment of the incremental contribution of each strategy component to the delivery of routine HBsAg screening as it was embedded into primary care practice.\u003c/p\u003e \u003cp\u003eSelection of strategy components was informed by an a priori assessment of contextual barriers using the CFIR 2.0\u003csup\u003e13\u003c/sup\u003e, ensuring alignment between identified determinants and implementation strategies (Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe CME component comprised in-person, small-group workshops delivered by a hepatology specialist with support from the research team. Content focused on CHB epidemiology, prevention, screening indications, referral pathways, health insurance procedures, and updated screening guidance, tailored to primary care providers\u0026rsquo; roles in screening and referral rather than specialist treatment decisions. Three 3-hour sessions were delivered at L\u0026ecirc; Văn Thịnh Hospital in June 2024, with CME certification provided. Although sessions were open to other departments, evaluation focused on providers working in the targeted primary care consultation rooms. CME content and format remained unchanged throughout the implementation period.\u003c/p\u003e \u003cp\u003eThe BPA was embedded in the electronic health record and triggered during outpatient encounters when no prior HBsAg result or CHB diagnosis was documented, or when the most recent HBsAg test was more than five years old. When triggered, an interruptive pop-up alert appeared, recommending CHB screening and offering three response options: \u0026ldquo;Accept,\u0026rdquo; \u0026ldquo;Reject,\u0026rdquo; or \u0026ldquo;Has evidence of testing\u0026rdquo; (to suppress alerts when prior testing occurred outside the hospital system). The alert automatically ceased once an HBsAg result or diagnosis was recorded. The clinical logic and eligibility criteria remained constant throughout the study. An interface-level modification was made mid-implementation: the option to dismiss the alert without selecting a response was removed to reduce passive dismissal and improve capture of provider actions, without altering the screening recommendation.\u003c/p\u003e \u003cp\u003ePOC HBsAg testing was introduced as an additional screening option alongside standard laboratory testing. The SD Bioline HBsAg WB\u0026reg; assay (World Health Organization-prequalified and nationally approved) was used for finger-stick capillary blood testing, with qualitative results available within approximately 20 minutes.\u003csup\u003e14\u003c/sup\u003e Testing was conducted by trained nurses in the Department of Microbiology, consistent with existing workflows. Clinicians provided brief pre- and post-test counseling according to hospital practice. Patients with negative results received prevention and vaccination advice, while those with positive results were referred to hepatology services for confirmatory testing and clinical evaluation. No changes to test procedures or eligibility criteria occurred during the implementation period. In this study, POC HBsAg testing functioned both as an additional screening modality and as an implementation strategy designed to reduce patient-level and structural barriers to completion of routine HBsAg screening.\u003c/p\u003e\n\u003ch3\u003eOutcomes and Data Sources\u003c/h3\u003e\n\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eQuantitative components\u003c/h2\u003e \u003cp\u003eImplementation outcomes included adoption and reach. These outcomes were selected to capture key dimensions of implementation performance, including provider engagement with intervention components and patient access to screening services. Adoption reflected clinician engagement with each strategy component. CME adoption was assessed using attendance logs. BPA adoption was defined as the proportion of triggered alerts that elicited any clinician response (accept, reject, or documentation of prior testing), based on EHR data. Adoption of POC HBsAg testing was measured as the proportion of all completed HBsAg tests performed using the POC modality during the final implementation phase, also derived from the EHR.\u003c/p\u003e \u003cp\u003eReach captured patient access to HBsAg testing during each implementation phase. Eligible patients were defined as those without prior hepatitis B testing or diagnosis at baseline. Reach was quantified as the proportion of unique eligible patients who completed HBsAg testing and the time from eligibility to testing among those tested, using EHR data.\u003c/p\u003e \u003cp\u003eThe primary service outcome was the HBsAg testing rate, defined as the number of completed tests per 1,000 outpatient visits per week, calculated from EHR-derived visit and testing records. Screening uptake was defined as the proportion of eligible primary care patients receiving HBsAg testing during the study period.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eQualitative components\u003c/h3\u003e\n\u003cp\u003eQualitative data were collected during the final four months of implementation, when all three strategy components were active, to explain quantitative patterns in adoption, reach, and service outcomes and to examine contextual influences on integration and sustainability.\u003c/p\u003e \u003cp\u003eWe used three complementary qualitative methods. First, non-participatory observations (NPO) were conducted by a trained research staff member in consultation rooms using structured tools to document real-time workflow and strategy execution, including BPA triggering, clinician responses, counseling behaviors, and completion of phlebotomy-based or POC testing. Given high patient volume, consecutive visits were observed as feasible. A supplemental special-case form was used to capture illustrative encounters that highlighted contextual barriers, adaptations, or deviations from expected practice.\u003c/p\u003e \u003cp\u003eSecond, brief patient exit interviews were conducted on observation days with patients who completed either phlebotomy-based or POC HBsAg testing. These 10-minute interviews focused on acceptability, perceived barriers, clarity of counseling, and comparisons between testing modalities. Responses were documented as structured notes in Vietnamese to minimize participant burden. Third, semi-structured in-depth interviews were conducted with primary care physicians and nurses across roles and seniority. Interviews were conducted online, lasted approximately 30 minutes, and explored perceptions of the acceptability, appropriateness, and feasibility of each strategy component, as well as workflow fit, role clarity, and sustainability. All interviews were conducted in Vietnamese, audio-recorded with consent, and transcribed verbatim for analysis, and guided by semi-structured interview guides developed a priori.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eQuantitative analyses evaluated implementation outcomes (adoption and reach) and service outcomes (HBsAg testing) across sequential implementation phases. Adoption metrics were summarized descriptively. CME adoption was defined as the proportion of eligible primary care providers attending each training session. BPA adoption was defined as the proportion of alerts that elicited acceptance of the recommendation or documentation of prior testing. Adoption of POC HBsAg was measured as the proportion of all completed HBsAg tests performed using the POC modality during the final implementation phase.\u003c/p\u003e \u003cp\u003eReach was assessed using time-to-event analyses among eligible patients, defined as those without prior hepatitis B testing or diagnosis. Time-to-testing was compared across phases using Kaplan\u0026ndash;Meier curves and Cox proportional hazards models, with time zero defined as the first eligible outpatient visit within each phase. Patients were censored at the time of testing or at the last observed outpatient visit. Models were adjusted for age, sex, residence, route of national health insurance access, and calendar month. The unit of analysis was the individual patient.\u003c/p\u003e \u003cp\u003eService outcomes were evaluated using segmented regression models to assess changes in weekly HBsAg testing rates per 1,000 outpatient visits. Negative binomial regression was used to account for overdispersion. Separate models estimated immediate and gradual changes associated with the sequential introduction of CME training, CME plus BPA, and CME plus BPA plus POC testing. Model diagnostics showed no evidence of significant autocorrelation or seasonality. The unit of analysis was outpatient visits aggregated by week.\u003c/p\u003e \u003cp\u003eAll reach and service outcome analyses were replicated for prespecified negative control outcomes (LDL and glucose testing). Analyses were conducted using RStudio with R version 4.4.0.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eQualitative Analysis\u003c/h3\u003e\n\u003cp\u003eWe used a descriptive qualitative analytic approach to identify contextual factors influencing implementation. Provider interview transcripts, patient exit-interview notes, and non-participatory observation narratives were analyzed inductively. Data were read repeatedly to identify themes reflecting implementation experiences, barriers, and facilitators. Themes were then mapped post hoc onto domains and constructs of CFIR 2.0 to support systematic interpretation.\u003csup\u003e13\u003c/sup\u003e\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eAdoption\u003c/h2\u003e \u003cdiv id=\"Sec12\" class=\"Section3\"\u003e \u003ch2\u003eContiniued medical education\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e summarizes participation in the three CME sessions and completion of post-session evaluations delivered between June 12 and June 19, 2024. Total number of participants varied across sessions. Among them, from 9 to 12 primary care providers (out of a total of 13) from targeted consultation rooms attended the sessions completed and passed the corresponding post-session evaluation.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAdoption of CME Sessions Based on Participation and Evaluation Completion\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTotal participants completing pre-session evaluation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSession 1\u003c/p\u003e \u003cp\u003e(June 12, 2024)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSession 2\u003c/p\u003e \u003cp\u003e(June 18, 2024)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSession 3\u003c/p\u003e \u003cp\u003e(June 19, 2024)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e70\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal participants completing post- session evaluation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e55 (55/55 Passed)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27 (27/27 Passed)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e31 (31/31 Passed)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTargeted PCPs completing pre-session evaluation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTargeted PCPs completing post-session evaluation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9 (9/9 Passed)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (5/5 Passed)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12 (12/12 Passed)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e\u003cem\u003eAbbreviation: PCPs \u0026ndash; Primary care professionals\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eBest practice advisory\u003c/h2\u003e \u003cp\u003eFrom the introduction of the BPA on September 19, 2024 to the end of the study period, a total of 84,367 outpatient visits were recorded. BPA alerts did not fire in 4,307 visits (5.1%) which had documented prior hepatitis B testing (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Among the remaining 80,060 visits in which BPA fired, the most common provider response was to dismiss the alert without selecting a response option (66,765; 79.1%). In contrast, \u0026ldquo;Accept\u0026rdquo; was chosen in 343 (0.4%) alerts.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSummary of BPA Responses from Sep 19, 2024 onward\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eResponse Category\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNumber of patient visits (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo alerts\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4,307 (5.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDismissed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e66,765 (79.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAccepted\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e343 (0.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDocumented proof of prior testing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e172 (0.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRejected\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12,780 (15.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e shows weekly trends in BPA response following implementation. The number of ignored BPA alerts remained consistently the highest among all response categories. In contrast, \u0026ldquo;Accepted\u0026rdquo; responses remained relatively infrequent, but showed a modest upward trend over time.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003ePoint-of-Care HBsAg Rapid Testing\u003c/h2\u003e \u003cp\u003eWeekly rates for both standard phlebotomy-based and POC HBsAg rapid testing from September 16, 2024 onwards are presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. Prior to the introduction of POC HBsAg, only phlebotomy-based HBsAg tests were conducted. Immediately following POC HBsAg rollout, POC HBsAg increased sharply, reaching approximately 45 tests per 1,000 visits per week. This elevated rate was sustained for several weeks before declining gradually. In contrast, phlebotomy-based HBsAg testing rates decreased after POC rollout and remained low throughout the subsequent period.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003e2. Reach\u003c/b\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eDescriptive Characteristics\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e presents the characteristics of 46,857 unique patients who entered care across four sequential periods defined by the timing of implementation components. Sex and age distributions were similar across periods. The majority of patients resided in Ho Chi Minh City, and most accessed care through in-network facilities. HBsAg testing uptake increased progressively across periods. The proportion of patients receiving HBsAg testing rose from 2.5% in the pre-intervention period to 2.7% during the CME phase, 3.2% after addition of the BPA, and 9.2% following the introduction of point-of-care testing. Measures of follow-up time and time to HBsAg testing decreased across successive periods. Median follow-up time declined from 27.8 days in the pre-intervention period to 0 days in the final period. Similarly, the median time from the first internal medicine visit to HBsAg testing decreased from 299 days before implementation to 0 days after the introduction of point-of-care testing.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCharacteristics of patients by entry period at first internal medicine visits\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBefore Jun 13, 2024\u003csup\u003e\u003cem\u003ea\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e\u003cem\u003ePre-Implementation\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eJun 13\u0026ndash;Sep 15, 2024\u003csup\u003e\u003cem\u003ea\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e\u003cem\u003eCME\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSep 16\u0026ndash;Feb 23, 2025\u003csup\u003e\u003cem\u003ea\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e\u003cem\u003eAdding BPA on top\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAfter Feb 24, 2025\u003csup\u003e\u003cem\u003ea\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e\u003cem\u003eAdding POC HBsAg on top\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNumber of\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003eunique patients\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e31,589\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4,101\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6,204\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4,963\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSex\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11,522 (36.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,523 (37.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2,298 (37.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1,807 (36.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20,067 (63.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2,578 (62.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3,906 (63.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3,156 (63.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e53 (39, 63)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e49 (35, 60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e49 (36, 61)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e49 (36, 60)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eResidence\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHCMC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17,815 (56.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2,213 (54.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3,538 (57.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2,721 (54.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eB\u0026igrave;nh Dương\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e131 (0.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18 (0.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e30 (0.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e24 (0.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVũng T\u0026agrave;u\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e209 (0.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e39 (1.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e71 (1.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e44 (0.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther provinces\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13,434 (42.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,831 (44.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2,565 (41.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2,174 (43.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRoute of national health insurance access\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIn-network \u003c/p\u003e \u003cp\u003e(with referral)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17,633 (55.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,967 (48.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3,036 (48.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2,231 (45.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIn-network \u003c/p\u003e \u003cp\u003e(cross-facility access)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13,939 (44.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2,131 (52.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3,166 (51.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2,732 (55.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOut-of-network\u003c/p\u003e \u003cp\u003e(without referral)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17 (0.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (0.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (0.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0 (0.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTested for HBsAg\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e805 (2.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e110 (2.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e197 (3.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e455 (9.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFollow-up Time, days\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMean (SD): 244.1 (316.0)\u003c/p\u003e \u003cp\u003eMedian (IQR): 27.8 (0.0, 477.7)\u003c/p\u003e \u003cp\u003eMax: 909.2\u003c/p\u003e \u003cp\u003eTotal: 7,711,479.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMean (SD): 55.0 (104.5)\u003c/p\u003e \u003cp\u003eMedian (IQR): 0.0 (0.0, 36.0)\u003c/p\u003e \u003cp\u003eMax: 382.0\u003c/p\u003e \u003cp\u003eTotal: 225,620.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMean (SD): 31.3 (64.0)\u003c/p\u003e \u003cp\u003eMedian (IQR): 0.0 (0.0, 16.9)\u003c/p\u003e \u003cp\u003eMax: 283.2\u003c/p\u003e \u003cp\u003eTotal: 194,438.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMean (SD): 7.1 (19.5)\u003c/p\u003e \u003cp\u003eMedian (IQR): 0.0 (0.0, 0.0)\u003c/p\u003e \u003cp\u003eMax: 119.0\u003c/p\u003e \u003cp\u003eTotal: 35,029.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTime to HBsAg test, days\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMean (SD): 321 (295)\u003c/p\u003e \u003cp\u003eMedian (IQR): 299 (14, 582)\u003c/p\u003e \u003cp\u003eMax: 897\u003c/p\u003e \u003cp\u003eTotal: 258,194\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMean (SD): 111 (123)\u003c/p\u003e \u003cp\u003eMedian (IQR): 31 (0, 225)\u003c/p\u003e \u003cp\u003eMax: 359\u003c/p\u003e \u003cp\u003eTotal: 12,260\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMean (SD): 41 (66)\u003c/p\u003e \u003cp\u003eMedian (IQR): 0 (0, 83)\u003c/p\u003e \u003cp\u003eMax: 226\u003c/p\u003e \u003cp\u003eTotal: 8,170\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMean (SD): 2 (8)\u003c/p\u003e \u003cp\u003eMedian (IQR): 0 (0, 0)\u003c/p\u003e \u003cp\u003eMax: 69\u003c/p\u003e \u003cp\u003eTotal: 794\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003csup\u003e\u003cem\u003ea\u003c/em\u003e\u003c/sup\u003e\u0026nbsp;n (%), unless indicated otherwise\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eSurvival Analysis\u003c/h2\u003e \u003cp\u003eKaplan\u0026ndash;Meier curves showed differences in time to HBsAg testing across entry periods, with patients entering during later implementation phases experiencing earlier testing compared with those in the pre-implementation period (log-rank test, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAs shown in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, Cox proportional hazards models indicated higher hazards of receiving an HBsAg test among patients entering during the implementation periods relative to the pre-implementation group. In unadjusted analyses, hazard ratios increased across successive periods, from 2.74 (95% CI: 2.21\u0026ndash;3.38) during the CME training phase to 10.13 (95% CI: 8.60\u0026ndash;11.93) after full implementation. After adjustment for baseline characteristics (age, residence, route of National Health Insurance access, and calendar month), these associations remained statistically significant, although attenuation was observed. In parallel, analyses of glucose and LDL testing demonstrated more modest increases in testing hazards across the same periods.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCox regression for time to HBsAg by entry period\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eStudy Periods\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eHBsAg\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003eGlucose\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003eLDL\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHR\u003c/p\u003e \u003cp\u003e(95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAdjusted HR\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eHR\u003c/p\u003e \u003cp\u003e(95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eAdjusted HR\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eHR\u003c/p\u003e \u003cp\u003e(95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eAdjusted HR\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e(95% CI)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBefore Jun 13,\u003c/p\u003e \u003cp\u003e2024\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eJun 13\u0026ndash;Sep 15,\u003c/p\u003e \u003cp\u003e2024\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.74 (2.21\u0026ndash;3.38)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.36 (1.90\u0026ndash;2.93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.77 (1.69\u0026ndash;1.85)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.43 (1.36\u0026ndash;1.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.81 (1.72\u0026ndash;1.89)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.44 (1.37\u0026ndash;1.51)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSep 16\u0026ndash;Feb 23,\u003c/p\u003e \u003cp\u003e2025\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.70 (3.93\u0026ndash;5.62)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.97 (3.28\u0026ndash;4.81)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.83 (1.75\u0026ndash;1.90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.37 (1.32\u0026ndash;1.44)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.92 (1.84\u0026ndash;2.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.40 (1.34\u0026ndash;1.47)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAfter Feb 24,\u003c/p\u003e \u003cp\u003e2025\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10.13 (8.60\u0026ndash;11.93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.82 (8.31\u0026ndash;11.61)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.08 (1.99\u0026ndash;2.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.00 (1.91\u0026ndash;2.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2.17 (2.07\u0026ndash;2.27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2.07 (1.97\u0026ndash;2.16)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"9\" nameend=\"c9\" namest=\"c1\"\u003e \u003cp\u003e\u003csup\u003e\u003cem\u003ea\u003c/em\u003e\u003c/sup\u003e\u003cem\u003eAdjustment for baseline variables (Age, Residence, Route of National Health Insurance Access, Calendar Month)\u003c/em\u003e\u003c/p\u003e \u003cp\u003e\u003cem\u003eAbbreviation: HR \u0026ndash; Hazard Ratio\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003e3. Service outcome\u003c/b\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eCharacteristics of Patient Visits\u003c/h2\u003e \u003cp\u003eA total of 225,209 outpatient visits were recorded in targeted consultation rooms across the study period (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). Visit volume varied across implementation phases, reflecting the staggered rollout and differing observation windows. Overall patient and visit characteristics were stable across periods. The median patient age was approximately 60 years, and around two-thirds of visits involved female patients. Most visits were covered by in-network national health insurance, either through referral or cross-facility access, with minimal use of out-of-network care. The geographic distribution of visits remained consistent, with the majority originating from Ho Chi Minh City. Across all periods, the most frequent diagnostic categories were circulatory system diseases, followed by endocrine and metabolic conditions, with smaller proportions of digestive, respiratory, and other conditions.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCharacteristics of outpatient visits at clinics by study period\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOverall\u003csup\u003e\u003cem\u003ea\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBefore\u003c/p\u003e \u003cp\u003eJune 13, 2024\u003csup\u003e\u003cem\u003ea\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e\u003cem\u003ePre-Implementation\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eJune 13, 2024 \u0026ndash;\u003c/p\u003e \u003cp\u003eSept 16, 2024\u003csup\u003e\u003cem\u003ea\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e\u003cem\u003eCME\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSept 16, 2024 \u0026ndash;\u003c/p\u003e \u003cp\u003eFeb 24, 2025\u003csup\u003e\u003cem\u003ea\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e\u003cem\u003eAdding BPA on top\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eAfter\u003c/p\u003e \u003cp\u003eFeb 24, 2025\u003csup\u003e\u003cem\u003ea\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e\u003cem\u003eAdding POC HBsAg on top\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTotal visits\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e225,209\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e127,764\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e23,919\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e41,299\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e32,227\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eYear of Visit\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e88,875 (39%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e88,875 (70%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2024\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e90,871 (40%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e38,889 (30%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e23,919 (100%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e28,063 (68%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2025\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e45,463 (20%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13,236 (32%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e32,227 (100%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRoute of national health insurance access\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIn-network (with referral)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e146,319 (65%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e83,886 (66%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15,323 (64%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e26,728 (65%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e20,382 (63%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIn-network (cross-facility access)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e78,867 (35%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e43,860 (34%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8,593 (36%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e14,569 (35%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e11,845 (37%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOut-of-network (without referral)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22 (\u0026lt;\u0026thinsp;0.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17 (\u0026lt;\u0026thinsp;0.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 (\u0026lt;\u0026thinsp;0.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2 (\u0026lt;\u0026thinsp;0.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNot using insurance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (\u0026lt;\u0026thinsp;0.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (\u0026lt;\u0026thinsp;0.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0 (0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e60 (51, 68)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e60 (51, 68)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e60 (50, 68)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e60 (51, 68)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e60 (50, 68)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSex\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e84,371 (37%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e48,007 (38%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8,906 (37%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15,504 (38%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e11,954 (37%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e140,838 (63%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e79,757 (62%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15,013 (63%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e25,795 (62%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e20,273 (63%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAreas of Residence\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHCMC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e147,238 (65%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e83,201 (65%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15,544 (65%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e27,214 (66%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e21,279 (66%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eB\u0026igrave;nh Dương\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e888 (0.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e505 (0.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e102 (0.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e157 (0.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e124 (0.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVũng T\u0026agrave;u\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e877 (0.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e452 (0.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e96 (0.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e195 (0.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e134 (0.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther provinces\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e76,206 (34%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e43,606 (34%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8,177 (34%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13,733 (33%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10,690 (33%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCondition classification by ICD-10\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiseases of the circulatory system\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e93,219 (41%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e53,470 (42%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9,697 (41%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e17,189 (42%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e12,863 (40%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEndocrine, nutritional and metabolic diseases\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e61,267 (27%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34,021 (27%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6,509 (27%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11,391 (28%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9,346 (29%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiseases of the digestive system\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15,422 (6.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8,930 (7.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,653 (6.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2,670 (6.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2,169 (6.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiseases of the eye and adnexa\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12,472 (5.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6,955 (5.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1,433 (6.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2,242 (5.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1,842 (5.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiseases of the respiratory system\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8,930 (4.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4,981 (3.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e897 (3.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1,880 (4.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1,172 (3.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther groups\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e33,899 (15%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19,407 (15%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3,730 (16%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5,927 (14%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4,835 (15%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003e\u003csup\u003e\u003cem\u003ea\u003c/em\u003e\u003c/sup\u003e\u0026nbsp;n (%); Median (IQR)\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eTrends in Patient Visits Over Time\u003c/h2\u003e \u003cp\u003eWeekly patient visit volumes remained stable throughout the study period, with no abrupt disruptions coinciding with the phased introduction of implementation components (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). No clear seasonal pattern was apparent.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eTime-Series Analysis of Intervention Impact\u003c/h2\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e displays weekly HBsAg testing rates standardized per 1,000 visits, with vertical markers indicating the timing of CME, BPA, and POC HBsAg rollout. Testing rates remained low and relatively stable prior to implementation, with modest changes following CME and BPA introduction. In contrast, a pronounced increase in testing rates occurred immediately after the introduction of POC HBsAg testing, followed by a gradual decline over subsequent weeks.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eInterrupted time-series analyses in Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e showed that the introduction of POC HBsAg was associated with a large and statistically significant immediate increase in HBsAg testing rates. In contrast, CME alone was not associated with significant immediate or gradual changes, and the addition of the BPA was associated with a small immediate decrease in testing rates without evidence of a sustained post-intervention trend. Following the initial increase after POC HBsAg rollout, HBsAg testing rates demonstrated a significant gradual decline over subsequent weeks, indicating attenuation after an early peak.\u003c/p\u003e \u003cp\u003eFor negative control outcomes, no consistent immediate or gradual effects were observed following CME or BPA implementation. Modest immediate increases were observed for glucose and LDL testing after the final rollout phase but not accompanied by sustained post-rollout trends.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eImmediate and gradual effects of implementation components on HBsAg testing\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eComponent\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eImmediate RR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWeekly RR following\u003c/p\u003e \u003cp\u003eeach rollout (95% CI)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHBsAg testing\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducation only\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.14 (0.74 to 1.74)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.002 (0.957 to 1.049)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducation\u0026thinsp;+\u0026thinsp;BPA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.57 (0.33 to 0.98)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.045 (0.985 to 1.109)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducation\u0026thinsp;+\u0026thinsp;BPA\u0026thinsp;+\u0026thinsp;POC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.05 (3.13 to 8.19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.884 (0.847 to 0.923)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGlucose testing\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducation only\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.10 (0.93 to 1.32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.995 (0.976 to 1.014)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducation\u0026thinsp;+\u0026thinsp;BPA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.03 (0.85 to 1.26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.995 (0.973 to 1.017)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducation\u0026thinsp;+\u0026thinsp;BPA\u0026thinsp;+\u0026thinsp;POC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.32 (1.09 to 1.58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.008 (0.992 to 1.024)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLDL testing\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducation only\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.06 (0.85 to 1.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.991 (0.967 to 1.015)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducation\u0026thinsp;+\u0026thinsp;BPA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.08 (0.85 to 1.37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.998 (0.972 to 1.025)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducation\u0026thinsp;+\u0026thinsp;BPA\u0026thinsp;+\u0026thinsp;POC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.35 (1.08 to 1.69)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.011 (0.992 to 1.031)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003e4. Acceptability, Appropriateness, Feasibility, and Contextual Changes\u003c/b\u003e \u003c/p\u003e \u003cp\u003eQualitative findings contextualized the stepwise changes observed across implementation phases. Table\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e summarizes key contextual factors identified through CFIR-guided analysis, while \u003cb\u003eTable S2\u003c/b\u003e presents detailed results from the qualitative analyses. Although CME improved provider knowledge and perceived appropriateness of HBV screening, structural barriers, particularly lack of insurance reimbursement and high patient volume, limited consistent translation into routine practice. Providers described time pressure and competing acute care priorities that constrained counseling, which may explain the modest gains during the CME and BPA phases.\u003c/p\u003e \u003cp\u003eWhile BPA increased screening prompts, its impact depended on staff engagement and workflow conditions. Observational data indicated that alerts were sometimes dismissed during busy sessions, contributing to incomplete execution of the screening pathway.\u003c/p\u003e \u003cp\u003eIn contrast, the POC HBsAg phase addressed key barriers identified in earlier phases. Both providers and patients emphasized the convenience, rapid turnaround time, and reduced invasiveness of finger-prick testing. Importantly, removal of out-of-pocket costs substantially increased patient willingness to test. These factors together help explain the marked increase in screening uptake observed during the POC HBsAg phase.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCFIR-based contextual factors influencing the implementation strategy\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCFIR Domain\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCFIR Construct\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eThematic Interpretation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRelevant Strategy Component\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eIllustrative Quotes/Observations\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOuter Setting\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFinancing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLack of insurance reimbursement for laboratory-based CHB screening created a structural financial barrier, limiting the impact of CME and BPA despite increased provider awareness.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCME, BPA, Standard lab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026ldquo;\u0026hellip;why do they pay for health insurance but still have to pay out of pocket\u0026hellip;\u0026rdquo;\u003c/p\u003e \u003cp\u003e\u0026ndash; IDI, Physician 1\u003c/p\u003e \u003cp\u003e\u0026ldquo;\u0026hellip;we rarely manage hepatitis B \u0026hellip; because health insurance does not cover care\u0026hellip;\u0026rdquo;\u003c/p\u003e \u003cp\u003e\u0026ndash; IDI, Physician 2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eInner Setting\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRelative Priority\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePreventive screening was deprioritized in insurance-driven visits focused on acute or existing complaints.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCME; BPA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026ldquo;\u0026hellip;after dealing with chronic conditions or acute issues, there is no time left in the consultation\u0026hellip;\u0026rdquo;\u003c/p\u003e \u003cp\u003e\u0026ndash; IDI, Physician 4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eInner Setting\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCompatibility\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eHigh patient volume and time pressure constrained in-depth counseling and reduced consistent enactment of BPA prompts.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBPA; CME\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026ldquo;\u0026hellip;when the clinic is very busy\u0026hellip; we have to move quickly\u0026hellip;\u0026rdquo;\u003c/p\u003e \u003cp\u003e\u0026ndash; IDI, Physician 5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eInner Setting\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCompatibility\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBPA alerts were variably enacted. Prompts did not uniformly translate into counseling or test ordering, particularly during busy sessions.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBPA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026ldquo;The BPA reminder appears, but the nurse closed the pop-up\u0026hellip;\u0026rdquo;\u003c/p\u003e \u003cp\u003e\u0026ndash; NPO, an observed case\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eIndividuals\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInnovation deliverers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCME improved perceived appropriateness and knowledge of CHB screening, but structural constraints limited behavioral change.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCME\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026ldquo;\u0026hellip;the training session very useful\u0026hellip; guiding us on how to counsel patients for hepatitis B screening\u0026hellip;\u0026rdquo;\u003c/p\u003e \u003cp\u003e\u0026ndash; IDI, Nurse 1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eIndividuals\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInnovation recipients\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOut-of-pocket costs, low perceived risk among asymptomatic patients, and predefined visit goals reduced acceptance of laboratory screening.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCME, BPA, POC HBsAg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026ldquo;\u0026hellip;if they have to pay nearly 500,000 VND, most people think it\u0026rsquo;s not important.\u0026rdquo;\u003c/p\u003e \u003cp\u003e\u0026ndash; IDI, Physician 2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eInnovation Characteristics\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRelative Advantage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePOC HBsAg testing perceived as faster, less invasive, and more convenient, increasing immediate acceptance.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePOC HBsAg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026ldquo;Patients find the test fast and convenient.\u0026rdquo;\u003c/p\u003e \u003cp\u003e\u0026ndash; Patient exit interview, patient 9\u003c/p\u003e \u003cp\u003e\u0026ldquo;\u0026hellip;the results come back quickly\u0026hellip; it only takes a few minutes.\u0026rdquo;\u003c/p\u003e \u003cp\u003e\u0026ndash; IDI, Physician 1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eInnovation Characteristics\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCost\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRemoval of patient cost for POC HBsAg testing eliminated financial hesitation and shifted decision-making toward immediate testing.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePOC HBsAg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026ldquo;Now that the test is free, people are very willing to do it.\u0026rdquo;\u003c/p\u003e \u003cp\u003e\u0026ndash; IDI, Physician 1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eInnovation Characteristics\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eComplexity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRepeated or interruptive BPA alerts contributed to alert fatigue and selective dismissal during high workload periods.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBPA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026ldquo;\u0026hellip;it keeps reminding repeatedly for many cases\u0026hellip; having to close it is quite inconvenient.\u0026rdquo;\u003c/p\u003e \u003cp\u003e\u0026ndash; IDI, Physician 1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eInnovation Characteristics\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEvidence-base and Adaptability\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eUncertainty about POC HBsAg test accuracy and insurance recognition influences provider confidence in use.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePOC HBsAg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026ldquo;\u0026hellip;we are concerned about sensitivity and specificity\u0026hellip; and whether insurance covers it.\u0026rdquo;\u003c/p\u003e \u003cp\u003e\u0026ndash; IDI, Physician 5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003e\u003cem\u003eAbbreviation: IDI \u0026ndash; In-depth Interview; NPO \u0026ndash; Non-participatory observation.\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eOverall, implementation of the multi-component strategy resulted in a substantial increase in CHB screening uptake, with the largest effect observed after removal of structural barriers through free point-of-care rapid testing.\u003c/p\u003e \u003c/div\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003e In this study, implementation of a multi-component strategy integrating provider education, EMR-based clinical decision support, and point-of-care HBsAg rapid testing significantly increased hepatitis B screening uptake in a large public primary care system in Vietnam. Within the CFIR framework, several determinants appeared particularly influential for implementation success, including provider knowledge and beliefs (Characteristics of Individuals), workflow compatibility within busy outpatient clinics (Inner Setting), and structural barriers affecting patient access to testing (Outer Setting). At the individual level, survival analyses showed progressively shorter time-to-testing across implementation phases, with the most pronounced acceleration following the introduction of free POC HBsAg testing. At the system level, interrupted time-series analyses confirmed a sharp immediate increase in weekly testing rates after POC HBsAg rollout, while earlier components yielded minimal change. By integrating individual-level, service-level, and qualitative findings, we clarify not only whether screening increased, but how and why different components performed differently within this context. The findings highlight the importance of multi-component implementation strategies that simultaneously address provider knowledge, workflow integration, and diagnostic accessibility to expand hepatitis B diagnosis in primary care settings.\u003c/p\u003e \u003cp\u003eCME improved provider knowledge and counseling confidence but translated into only small increases in screening. During the pre-POC-HBsAg phases, testing rose modestly among eligible patients, suggesting that enhanced capability alone was insufficient to overcome structural barriers. Electronic BPA showed similarly limited effect. Although alerts were frequently triggered, most were dismissed, and formal acceptance was rare. Qualitative findings revealed alert fatigue, competing clinical priorities, unclear task ownership, and frustration with inaccurate alerts due to incomplete documentation of prior testing. In high-volume, insurance-driven visits focused on acute complaints, preventive screening held low relative priority. These findings indicate that informational and cognitive supports were layered onto persistent workflow and financing constraints, limiting their practical impact.\u003c/p\u003e \u003cp\u003eA recent meta-analysis reported that electronic reminders increased chronic hepatitis B testing by approximately 8% on average, but heterogeneity across studies was substantial (I\u0026sup2; = 95%).\u003csup\u003e12\u003c/sup\u003e Our current findings align with this variability and suggest that reminder effectiveness is highly context-dependent. In environments characterized by heavy workload, team-based task delegation, and competing visit objectives, digital prompts alone may not overcome embedded structural frictions.\u003csup\u003e15\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eIn contrast, free POC HBsAg rapid testing shifted screening behavior. Uptake increased sharply following its introduction, particularly at the individual level where time-to-testing accelerated markedly. Removing cost, reducing procedural burden, and providing same-day results addressed key opportunity constraints identified qualitatively. From a CFIR perspective, POC HBsAg demonstrated strong relative advantage, improved compatibility with patient needs, and reduced perceived complexity.\u003csup\u003e16\u003c/sup\u003e At the same time, some providers expressed uncertainty about rapid-test accuracy and insurance recognition, occasionally prompting confirmatory laboratory testing, highlighting that perceived evidence strength remains relevant for sustainability.\u003c/p\u003e \u003cp\u003eThe divergence between individual-level reach estimates and aggregate service-level trends warrants consideration. Survival analyses captured acceleration in testing among eligible individuals, whereas interrupted time-series models evaluated weekly testing volume per visit across the entire clinic population. Improvements in access among eligible patients may therefore appear larger at the individual level than at the system level, where effects are diluted across all outpatient visits and constrained by clinic capacity. Together, these analyses provide complementary perspectives on implementation impact across levels of care delivery.\u003c/p\u003e \u003cp\u003eThe phased rollout functioned as a pragmatic natural experiment, enabling examination of incremental contributions of each component. Education and reminders primarily targeted provider capability and motivation, but screening accelerated only when structural opportunity expanded through removal of financial and procedural barriers. This pattern aligns with behavioral theory emphasizing that opportunity is necessary in addition to capability for behavior change.\u003csup\u003e17\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eAdditionally, our findings are consistent with community-based hepatitis B screening programs that achieved high uptake through combined strategies, including education, decision support, cost removal, and stakeholder engagement.\u003csup\u003e18\u003c/sup\u003e Primary care platforms may therefore represent one of the most scalable pathways to expand CHB diagnosis in high-burden settings where specialist hepatology services are limited. Applied to primary care, the results suggest that provider-focused strategies must be coupled with workflow redesign and patient-facing enablers. Education remains necessary but insufficient when structural barriers dominate.\u003c/p\u003e \u003cp\u003eStrengths of this study include its real-world implementation setting, integration of the intervention within routine clinical workflows, and evaluation within a high-volume public primary care system serving a large patient population. Several limitations are acknowledged. The study was conducted in a single primary care system. However, the intervention components are readily scalable to other settings with EMR infrastructure and existing primary care networks. Also, because this study lacked a concurrent control group, residual secular trends in CHB awareness or screening practices cannot be excluded. To mitigate this concern, we deployed interrupted time-series modeling and negative controls. Furthermore, we evaluated screening uptake but did not assess downstream outcomes such as confirmatory testing, linkage to care, or treatment initiation. Future implementation efforts should integrate structured linkage-to-care pathways to ensure that patients identified through screening receive appropriate evaluation and treatment.\u003c/p\u003e \u003cp\u003e In conclusion, a multi-component implementation strategy integrating provider education, EMR-based clinical decision support, and point-of-care HBsAg rapid testing substantially increased CHB screening uptake in a high-volume public primary care system in Vietnam. These findings suggest that integrating HBV screening into routine primary care workflows may represent a scalable strategy to accelerate CHB diagnosis and support progress toward hepatitis B elimination in resource-constrained settings.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003cbr\u003e\u0026nbsp;T.V.K. conceptualized the study, developed the methodology, conducted the formal analysis and investigation, acquired funding, prepared the visualizations, and wrote the original draft of the manuscript and subsequent revisions. T.N.D.P. conceptualized the study, developed the methodology, supervised the work, validated the findings, and reviewed and edited the manuscript. D.Da. (Diem Dao) and A.N.L. contributed to project administration, resources, and review and editing of the manuscript. L.P. contributed to project administration, resources, and data collection. L.H.H.L. contributed to methodology development, formal analysis, and qualitative data collection. T.T.L., C.Q.L., H.T.V., T.B.D., T.Q.P.T., V.H.L.D., and T.H.T.N. contributed to resources, project administration, and supervision. K.V.T. and D.Do. (Doan Dao) contributed to conceptualization, funding acquisition, resources, supervision, validation, and writing of the original draft, and reviewed and edited the manuscript. All authors contributed to interpretation of the data, critically revised the manuscript, and approved the final version.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the All4Liver Grant from Gilead Sciences (Grant No. 23007 in 2023). The funder had no role in the design of the study; collection, analysis, or interpretation of data; or in writing the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets \u0026nbsp;analyzed during the current study include routinely collected electronic medical record data and qualitative interview data. Due to institutional policies, these data are not publicly available. De-identified data may be made available from the corresponding author on reasonable request, subject to approval by the Institutional Review Board of L\u0026ecirc; Văn Thịnh Hospital.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eEthics approval and consent to participate\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThis study was conducted in accordance with the Declaration of Helsinki. The study was prospectively registered on ClinicalTrials.gov (NCT06403657). Ethical approval was obtained from the Institutional Review Board of L\u0026ecirc; Văn Thịnh Hospital (Decision No. 264/QĐ‑BVLVT). The requirement for informed consent was waived by the Institutional Review Board for the use of de‑identified EMR data. Written informed consent was obtained from all individuals participating in the qualitative assessment.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eConsent for publication\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eCompeting interests\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAuthor details\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003csup\u003ea\u003c/sup\u003e Department of Epidemiology, Pham Ngoc Thach University of Medicine, Ho Chi Minh City, Viet Nam. \u003csup\u003eb\u0026nbsp;\u003c/sup\u003eGastroenterology and Hepatology Division, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA. \u003csup\u003ec\u003c/sup\u003e School of Public Health, University of Illinois at Chicago, Chicago, IL, USA. \u003csup\u003ed\u003c/sup\u003e Vietnam Viral Hepatitis Alliance, Reston, VA, USA. \u003csup\u003ee\u003c/sup\u003e Le Van Thinh Hospital, Thu Duc City, Ho Chi Minh City, Viet Nam. \u003csup\u003ef\u003c/sup\u003e University of Medicine and Pharmacy at Ho Chi Minh City, Viet Nam. \u003csup\u003eg\u003c/sup\u003e Department of Gastroenterology, An Binh Hospital, Ho Chi Minh City, Viet Nam. \u003csup\u003eh\u003c/sup\u003e Program in Global Primary Health Care, Harvard Medical School, Boston, MA, USA.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eWorld Health Organization. Global hepatitis report 2024: action for access in low-and middle-income countries: World Health Organization; 2024.\u003c/li\u003e\n \u003cli\u003eHolt B, Fernandez M, Nguyen D, et al. Embedding viral hepatitis into primary healthcare: results of a strategic landscape analysis in Vietnam and the Philippines. \u003cem\u003eLancet Reg Health West Pac\u003c/em\u003e 2024; \u003cstrong\u003e44\u003c/strong\u003e: 100990.\u003c/li\u003e\n \u003cli\u003eWorld Health Organization Regional Office for the Western Pacific. Viral hepatitis situation adn response in Vietnam. Manila, Philippines, 2018.\u003c/li\u003e\n \u003cli\u003ePham TND, Le DH, Dao DVB, et al. Establishing baseline framework for hepatitis B virus micro-elimination in Ho Chi Minh City, Vietnam \u0026amp;#x2013; a community-based seroprevalence study. \u003cem\u003eThe Lancet Regional Health \u0026ndash; Western Pacific\u003c/em\u003e 2023; \u003cstrong\u003e30\u003c/strong\u003e.\u003c/li\u003e\n \u003cli\u003eConners EE. Screening and testing for hepatitis B virus infection: CDC recommendations\u0026mdash;United States, 2023. \u003cem\u003eMMWR Recommendations and Reports\u003c/em\u003e 2023; \u003cstrong\u003e72\u003c/strong\u003e.\u003c/li\u003e\n \u003cli\u003eWorld Health Organization. Guidelines for the prevention, diagnosis, care and treatment for people with chronic hepatitis B infection, 2024.\u003c/li\u003e\n \u003cli\u003eFernandez ML, Nguyen H, Nguyen D, et al. Healthcare system readiness to manage viral hepatitis in Viet Nam and the Philippines: results of a brief health facility assessment. \u003cem\u003eBMC Health Serv Res\u003c/em\u003e 2026.\u003c/li\u003e\n \u003cli\u003ePham TND, Hoang LB, Dao DVB, et al. Expanding Hepatitis B Screening with Point-of-Care Rapid Testing in Primary Care: An Implementation Science Study. \u003cem\u003emedRxiv\u003c/em\u003e 2024: 2024.08.29.24312788.\u003c/li\u003e\n \u003cli\u003eHolt B, Mendoza J, Nguyen H, et al. Barriers and enablers to people-centred viral hepatitis care in Vietnam and the Philippines: Results of a patient journey mapping study. \u003cem\u003eJ Viral Hepat\u003c/em\u003e 2024; \u003cstrong\u003e31\u003c/strong\u003e(7): 391-403.\u003c/li\u003e\n \u003cli\u003eHang Pham TT, Le TX, Nguyen DT, et al. Knowledge, attitudes and medical practice regarding hepatitis B prevention and management among healthcare workers in Northern Vietnam. \u003cem\u003ePloS one\u003c/em\u003e 2019; \u003cstrong\u003e14\u003c/strong\u003e(10): e0223733.\u003c/li\u003e\n \u003cli\u003eHoa NT, Derese A, Peersman W, Markuns JF, Willems S, Tam NM. Primary care quality in Vietnam: Perceptions and opinions of primary care physicians in commune health centers - a mixed-methods study. \u003cem\u003ePLoS One\u003c/em\u003e 2020; \u003cstrong\u003e15\u003c/strong\u003e(10): e0241311.\u003c/li\u003e\n \u003cli\u003eKim TV, Pham TND, Phan P, et al. Effectiveness and implementation of decentralized, community- and primary care-based strategies in promoting hepatitis B testing uptake: a systematic review and meta-analysis. \u003cem\u003eEClinicalMedicine\u003c/em\u003e 2024; \u003cstrong\u003e76\u003c/strong\u003e: 102818.\u003c/li\u003e\n \u003cli\u003eDamschroder LJ, Reardon CM, Opra Widerquist MA, Lowery J. Conceptualizing outcomes for use with the Consolidated Framework for Implementation Research (CFIR): the CFIR Outcomes Addendum. \u003cem\u003eImplementation Science\u003c/em\u003e 2022; \u003cstrong\u003e17\u003c/strong\u003e(1): 7.\u003c/li\u003e\n \u003cli\u003eWorld Health Organization. WHO list of prequalified in vitro diagnostic products. 2023. https://extranet.who.int/prequal/sites/default/files/document_files/231020_prequalified_IVD_product_list.pdf (accessed March 13 2024).\u003c/li\u003e\n \u003cli\u003eSequist TD, Zaslavsky AM, Marshall R, Fletcher RH, Ayanian JZ. Patient and Physician Reminders to Promote Colorectal Cancer Screening: A Randomized Controlled Trial. \u003cem\u003eArchives of Internal Medicine\u003c/em\u003e 2009; \u003cstrong\u003e169\u003c/strong\u003e(4): 364-71.\u003c/li\u003e\n \u003cli\u003eBottero J, Boyd A, Gozlan J, et al. Simultaneous Human Immunodeficiency Virus-Hepatitis B-Hepatitis C Point-of-Care Tests Improve Outcomes in Linkage-to-Care: Results of a Randomized Control Trial in Persons Without Healthcare Coverage. \u003cem\u003eOpen Forum Infect Dis\u003c/em\u003e 2015; \u003cstrong\u003e2\u003c/strong\u003e(4): ofv162.\u003c/li\u003e\n \u003cli\u003eMichie S, van Stralen MM, West R. The behaviour change wheel: a new method for characterising and designing behaviour change interventions. \u003cem\u003eImplement Sci\u003c/em\u003e 2011; \u003cstrong\u003e6\u003c/strong\u003e: 42.\u003c/li\u003e\n \u003cli\u003eMa GX, Lee MM, Tan Y, et al. Efficacy of a community-based participatory and multilevel intervention to enhance hepatitis B virus screening and vaccination in underserved Korean Americans. \u003cem\u003eCancer\u003c/em\u003e 2018; \u003cstrong\u003e124\u003c/strong\u003e(5): 973-82.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Chronic hepatitis B, Primary care screening, Implementation science, Point-of-care testing, Mixed-methods study, CFIR 2.0","lastPublishedDoi":"10.21203/rs.3.rs-9200793/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9200793/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground. \u003c/strong\u003eChronic hepatitis B (CHB) remains substantially underdiagnosed in Viet Nam despite widespread availability of effective antiviral therapy. In routine primary care, hepatitis B surface antigen (HBsAg) testing is typically performed only when clinically indicated, resulting in missed opportunities for early detection. Evidence on how to operationalize routine hepatitis B screening in real-world, resource-constrained primary care settings is limited.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods. \u003c/strong\u003eWe conducted a quasi-experimental implementation trial with mixed-method evaluation at a large public primary care hospital in Ho Chi Minh City, Viet Nam. A three-component strategy\u003cstrong\u003e informed by constructs from the Consolidated Framework for Implementation Research (CFIR), \u003c/strong\u003eincluding continuing medical education (CME), an electronic best practice advisory (BPA), and point-of-care (POC) HBsAg rapid testing, was introduced sequentially over 12 months. Implementation outcomes (adoption, reach) and service outcomes (weekly HBsAg testing per 1,000 visits) were evaluated using electronic medical record data, Kaplan–Meier and Cox regression analyses, and segmented negative binomial interrupted time-series models. Negative control outcomes (LDL and glucose testing) were analyzed in parallel. Qualitative data from observations and interviews were analyzed using a CFIR 2.0-guided framework to interpret mechanisms and contextual influences.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults.\u003c/strong\u003e Among 225,209 outpatient visits and 46,857 unique patients, CME improved provider knowledge but resulted in only modest changes in testing. BPA reminders were frequently bypassed during high-volume sessions, limiting adoption. In contrast, introduction of free POC HBsAg rapid testing produced a sharp and sustained increase in weekly testing rates and substantially shortened time-to-testing among eligible patients. These effects were substantially larger than those observed for negative control outcomes, supporting a strategy-specific effect rather than background testing trends. Qualitative findings indicated that removal of financial and procedural barriers was central to uptake, while workflow constraints and team-based task division shaped implementation performance.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions.\u003c/strong\u003e A multi-component implementation strategy integrating provider education, EMR-based clinical decision support, and point-of-care HBsAg rapid testing substantially increased hepatitis B screening uptake in a high-volume public primary care system in Viet Nam. Structural interventions that remove financial and workflow barriers appear necessary for successful implementation. Integrating HBV screening into routine primary care workflows may represent a scalable strategy to accelerate hepatitis B diagnosis and support progress toward global elimination targets.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRegistration: \u003c/strong\u003eNCT06403657 on ClinicalTrials.gov\u003c/p\u003e","manuscriptTitle":"A Multi-Component Implementation Strategy to Expand Hepatitis B Screening in Primary Care in Viet Nam: A Mixed-Methods Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-01 06:54:12","doi":"10.21203/rs.3.rs-9200793/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"70378bf0-7c27-4c20-b229-5910444bc941","owner":[],"postedDate":"April 1st, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-05-04T06:24:51+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-01 06:54:12","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9200793","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9200793","identity":"rs-9200793","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}