Home Journals Articles Updates About
CN
image
收藏切换
Evaluation of an intelligent digital platform for population management in cervical cancer screening
收藏切换
PDF
Xinhua Jia1, 2, Chen Gao3, Xi’ao Da1, Jingyi Shi1, 2, Mingyang Chen1, Rufei Duan4, Zhifang Li5, Ruimei Feng6, Yao Yang1, Jiahuan Zhai3, Hanyue Ding1, Alex Ng3, Youlin Qiao1, 2
Cancer Biology & Medicine | 2025, 22(9) : 1068 - 1082
Less
收藏切换
Cancer Biology & Medicine | 2025, 22(9): 1068-1082
• Original Article •
Evaluation of an intelligent digital platform for population management in cervical cancer screening
Full
Xinhua Jia1, 2, Chen Gao3, Xi’ao Da1, Jingyi Shi1, 2, Mingyang Chen1, Rufei Duan4, Zhifang Li5, Ruimei Feng6, Yao Yang1, Jiahuan Zhai3, Hanyue Ding1, Alex Ng3, Youlin Qiao1, 2
Affiliations
  • 1School of Population Medicine and Public Health, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100730, China
  • 2National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100021, China
  • 3Tencent Inclusive Health Lab, Beijing 100193, China
  • 4Department of Cancer Prevention and Control, Yunnan Cancer Hospital, The Third Affiliated Hospital of Kunming Medical University, Kunming 650118, China
  • 5School of Public Health, Changzhi Medical College, Changzhi 046000, China
  • 6School of Public Health, Shanxi Medical University, Jinzhong 030001, China
About Author:

Author contributions

Conceived and designed the analysis: Youlin Qiao; Alex Ng; Jiahuan Zhai; Xinhua Jia.

Collected the data: Rufei Duan; Xi’ao Da; Jingyi Shi; Zhifang Li; Ruimei Feng.

Contributed data or analysis tools: Xi’ao Da; Jingyi Shi.

Performed the analysis: Xinhua Jia.

Wrote the paper: Xinhua Jia; Chen Gao.

Critical revision of the manuscript: Youlin Qiao; Alex Ng; Jiahuan Zhai; Mingyang Chen; Yao Yang; Hanyue Ding.

Published: 2025-09-15 doi: 10.20892/j.issn.2095-3941.2025.0419
Outline
收藏切换
Objective:

To describe temporal changes associated with deployment of an optical character recognition (OCR)-enabled One-Identity (One-ID) digital platform for rural cervical cancer screening, focusing on over-screening rates, CIN2+ detection, colposcopy follow-up, and CIN2+ management.

Methods:

A multi-county pre-post observational study was conducted in six rural counties in Shanxi, Yunnan, and Sichuan Provinces (2021–2024), encompassing 153,978 encounters. The digital platform integrates OCR identity capture, deterministic One-ID linkage, and real-time duplicate alerts. Over-screening proportions before and after digital deployment were compared, changes in CIN2+ detection rate were evaluated, and colposcopy follow-up and CIN2+ management were assessed. Differences were tested with χ2 or Fisher’s exact tests.

Results:

Among 153,978 encounters, the proportion of over-screening decreased from 12.64% in 2023 to 0.17% in 2024 with an absolute reduction of 12.17% (95% CI: 11.94–12.40; P < 0.001). The share of women receiving a first screening within the preceding 3 y increased from 78.3% to 88.2% (P < 0.001). Colposcopy completion improved from 64.1% to 84.9%. The CIN2+ detection rate rose from 0.35% (2021–2023 pooled) to 0.67% in 2024 (P < 0.001) and CIN2+ management completion increased from 56.0% to 76.2% (95% CI: 13.3–27.2; P < 0.001). These improvements were consistent across age groups, counties, and screening strategies.

Conclusions:

The OCR-enabled One-ID platform substantially reduced over-screening, increased CIN2+ detection rate, and strengthened case follow-up/management, particularly where baseline tracking was weak, supporting scalable digital reinforcement of rural screening programmes.

Cervical cancer screening  /  digital health  /  population management  /  over-screening  /  rural China
Xinhua Jia, Chen Gao, Xi’ao Da, Jingyi Shi, Mingyang Chen, Rufei Duan, Zhifang Li, Ruimei Feng, Yao Yang, Jiahuan Zhai, Hanyue Ding, Alex Ng, Youlin Qiao. Evaluation of an intelligent digital platform for population management in cervical cancer screening[J]. Cancer Biology & Medicine, 2025 , 22 (9) : 1068 -1082 . DOI: 10.20892/j.issn.2095-3941.2025.0419
Full Text
Less
Introduction
Less
Cervical cancer is a major global public health challenge with 661,021 new cases and 348,189 deaths reported in 20221. China alone accounted for nearly 22.7% of the global cervical cancer incidence and 16% of cervical cancer-related deaths2. The burden of cervical cancer is highly inequitable. Countries with a Human Development Index (HDI) ≤ 0.55 have twice the incidence and five times the mortality of cervical cancer compared to high-HDI settings3,4. To respond to this burden, the World Health Organization (WHO) released the Global Strategy to Accelerate the Elimination of Cervical Cancer as a Public Health Problem in 20205, which set the “90–70–90” targets to be achieved by 2030. One target requires that 70% of women 35–45 y of age undergo at least one high-quality screening. However, achieving such extensive coverage remains a formidable challenge in most regions.
In recent years China has been attempting to expand cervical cancer screening coverage in rural areas through initiatives, such as the National Two Cancer Screening Program (NTCSP), which has provided free screening for women of eligible age since 2009. However, by 2024 only 36.8% of women nationwide had ever been screened6, which was substantially lower than that observed in high-income countries. The disparity is particularly pronounced in rural regions, where coverage is approximately 32.3% compared to 43.2% in urban settings6. Major barriers include a shortage of trained personnel, limited public awareness, transportation difficulties, and challenges in patient follow-up. Fragmented data management and underdeveloped information systems further constrain the efficiency and quality of screening services7–10. The emergence of digital health technologies offers novel solutions to the challenges outlined above11–14. Evidence indicates that web- and mobile-based interventions can substantially increase participation in cervical cancer screening15–17. Digital platforms hold considerable promise for streamlining workflows, boosting uptake, strengthening follow-up, and providing real-time data surveillance, which are particularly valuable for screening programmes in resource-constrained areas18,19.
In this study an intelligent population management platform for population-based cervical cancer screening was designed, deployed, and used to evaluate six counties in Shanxi, Yunnan, and Sichuan Provinces—Zezhou, Xiangyuan, Mangshi, Xinping, Yanting, and Shimian. The platform encompasses the entire screening continuum—registration, appointment booking, specimen collection, result delivery, and longitudinal follow-up, also integrates One-ID identity authentication, optical character recognition (OCR)-enabled data capture, SMS reminders, and a real-time analytics dashboard. The effectiveness in curbing over-screening, streamlining follow-up, improving CIN2+ detection rate and management was evaluated.
Materials and methods
Less
Study design and analytical framework
A descriptive, real-world pre–post evaluation study was conducted to summarize temporal changes in over-screening, colposcopy completion, CIN2+ management, and CIN2+ detection following platform rollout without making causal claims. The study protocol was approved by the Institutional Review Board of the Chinese Academy of Medical Sciences & Peking Union Medical College (CAMS&PUMC-IEC-2025-043; CAMS&PUMC-IEC-2022-059-1). All participants provided written informed consent, and additional electronic consent was obtained for the mini-program.
Platform design and functional modules
An intelligent, web-based population management platform was developed in partnership with Tencent. It focused on population management and offered integrated services through web and a mobile mini-program. To support population-based management, the platform integrates intelligent tools built on unified individual records (One ID). A real-time check that flags any attempt to rescreen a woman before the guideline-recommended interval [3 y after a negative cytology test or 5 y after a negative high-risk HPV test and an automated follow-up queue that prioritizes women based on risk levels, e.g., human papillomavirus (HPV) 16/18 positive], enabling providers to efficiently manage daily follow-up tasks.
The platform serves the targeted women and primary care providers with multiple digital services and support flexible module reuse. From the patient perspective, the mini-program delivers screening results and follow-up recommendations in real time after physician review and allows access to personal screening history to enhance health awareness and self-management. From the provider perspective, the mobile interface supports offline data collection, making the mobile interface suitable for outreach screening in rural areas. Data are automatically uploaded when connectivity is restored, ensuring completeness and timeliness, while reducing unnecessary patient travel.
Study population and implementation
Six sites were established across Shanxi, Yunnan, and Sichuan Provinces-Zezhou, Xiangyuan, Mangshi, Xinping, Yanting, and Shimian for the current study (Figure 1). All of these counties have long participated in the National Cervical Cancer Screening Program (NTCSP) and therefore have extensive experience in delivering screening services. Variations in population characteristics, screening protocols, and prior operational experience across the sites strengthen the external validity of the findings. To avoid over-screening, Zezhou, Xiangyuan, Xinping, and Yanting rotate screening activities among different townships each year and have partially implemented digital de-duplication strategies.
The study systematically collected all individual-level screening records generated before the project began (2021), including national identification numbers, screening dates, and test results. After the project was launched in 2023, digital components were integrated into the screening workflow-OCR-based registration, questionnaire administration, pelvic examination, HPV DNA testing, result notification, colposcopy, and histopathology. Records produced before 2023 serve as the baseline, reflecting the performance of pre-existing service delivery systems.
Platform evaluation
Over-screening was detected by matching national ID numbers with screening records. An individual who received a negative cytology or HPV result in 1 y but underwent screening again the following year was defined as over-screened. The digital platform captured registration details, questionnaire responses, and user-behavior metrics, including the number of notification clicks and the duration of notification viewing.
Data sources and collection
In the pre-implementation stage (January 2021-mid-2023), the NTCSP was performed in county-level maternal and child health hospitals with screening quotas assigned and confirmed by higher-level government authorities. In accordance with regulatory requirements, all participant screening records were maintained in paper form. The study team retrieved these paper archives, performed double independent manual data entry, and undertook secondary verification of aggregated counts and positive cases to ensure data quality.
Screening data from all field sites were entered directly within the clinical workflow by responsible physicians or healthcare workers and uploaded to the platform in real time in the post-implementation stage (mid-2023 onward). A One-ID together with OCR enabled automated record linkage, real-time electronic de-duplication, and end-to-end integration of screening, follow-up, and management. Follow-up and management statuses were updated in a closed loop on a single interface.
Historical (pre-implementation) records were retained in the original form and were not retrospectively subjected to electronic de-duplication; only post-implementation data underwent automated de-duplication.
Statistical analysis
Data from the platform backend were exported, including age, ID-card, screening site, screening strategy, primary screening time and results, colposcopy time, final results, recall interval, and follow-up status. Baseline characteristics and annual screening volumes were descriptively summarised. The cohort was stratified into pre- and post-digital periods, and the over-screening rate, detection rates of cervical intraepithelial neoplasia grade two or higher (CIN2+) and cervical cancer, and the follow-up completion rate among women with CIN2 plus were compared. The period-specific point estimates were reported together with the absolute delta for each outcome. The 95% confidence intervals (CIs) for the absolute delta were calculated with the Wald normal approximation. Differences in proportions between periods were tested with the Pearson Chi-squared test or Fisher exact test when any expected count was fewer than five. For multiple testing across independent comparisons of the same outcome, the Bonferroni correction was applied to control the family-wise error rate. The threshold for significance was a P < 0.05 in 2-sided tests. All statistical analyses were performed using R (version 4.3.1).
Results
Less
Baseline characteristics of screened women, 2021–2024
A total of 153,978 screening encounters were recorded from 2021 to 2024. As presented in Table 1, the annual volume increased from 31,927 in 2021 to a peak of 46,098 in 2023 before declining to 40,080 in 2024. Across the entire period, women 45–54 y of age constituted the largest age stratum [69,299 (45.01%)], followed by 35–44 y of age [44,550 (28.93%)], and 55–64 y of age [40,129 (26.06%)]. The proportion of women 55–64 y of age rose from 20.70% in 2021 to 31.91% in 2024, indicating a progressive reach into the upper guideline age band (P < 0.001). All six pilot counties contributed cases each year with Mangshi [38,415 (24.95%)] and Yanting [25,523 (16.58%)] together accounting for greater than two-fifths of total encounters. Site-level distributions differed significantly across the years (P < 0.001), reflecting a staggered scale-up. A marked shift in primary screening modality occurred (P < 0.001). Cytology-only examinations, which dominated early [19,039/31,927 (59.63%) in 2021 and 29,925/35,873 (83.42%) in 2022] declined to 10,088 (21.88%) in 2023 and 0 in 2024 as HPV-based strategies were adopted. VIA/VILI + cytology triage was confined to the initial implementation phase (2021), then replaced by HPV-based strategies. Overall test positivity (primary screening result) was 6.20% (9,546/153,978) and showed a modest year-on-year rise from 5.57% in 2021 to 6.92% in 2024 (P < 0.001), which was consistent with increased uptake of higher-sensitivity HPV-based strategies in later years.
OCR-enabled one-ID deduplication and reduction in over-screening
Table 2 showes the impact of real-time OCR de-duplication on cervical cancer over-screening. Following deployment of the OCR-enabled One-ID real-time de-duplication system, the over-screening proportion fell from 12.64% in 2023 to 0.17% in 2024 (single-year window), with an absolute reduction of 12.47 percentage points (pp) and a relative reduction of 98.7%. Using pooled data from 2022 to 2023 as the pre-digital comparator, the overall absolute delta was 12.17 pp (95% CI: 11.94–12.40; P < 0.001). By age, single-year repeat proportions declined from 14.97% to 0.18% (35–44 y), 13.34% to 0.20% (45–54 y), and 8.80% to 0.13% (55–64 y). The corresponding pooled pre-digital vs. 2024 absolute deltas were 15.06 pp (95% CI: 14.59–15.52), 12.55 pp (95% CI: 12.21–12.90), and 8.15 pp (95% CI: 7.77–8.53), respectively (all P < 0.001). The proportions fell from 1.33% to 0.33% for HPV + cytology (−1.02 pp, 95% CI: 0.79–1.25), 8.05% to 0.19% for HPV + VIA/VILI triage (−7.86 pp, 95% CI: 7.29–8.43), and 20.50% to 0.14% for HPV + cytology triage (−20.01 pp, 95% CI: 19.62–21.09) in single-year analyses. The cumulative proportion declined from 3.50% to 0.07% (−3.67 pp, 95% CI: 3.50–3.84) among counties that previously used only manual de-duplication. The cumulative proportion declined from 28.23% to 0.44% in counties without any pre-existing de-duplication. All strata converged to ≤ 0.61% (overall 0.17%) after digitalization. The proportion of women receiving a first screen within the previous 3 y increased from 78.3% in 2023 to 88.2% in 2024 (P < 0.001).
Improvement in colposcopy follow-up completion
The colposcopy follow-up rates increased in every age group after digitalization in age-stratified analyses (Figure 2). The colposcopy follow-up proportion was 59.4% among women 40–44 y of age and 69.9% among women 60–64 y of age during the paper-based phase. The age-specific rates rose to 80.4%–86.5% after digitalization, corresponding to an absolute increase of 11.8 pp in women 35–39 y of age and 23–24 pp in women 40–54 y of age. Follow-up completion rate increased from 64.1% (2820/4397) to 84.9% (4369/5149) at the population level, with an overall improvement of 20.8 pp. Inter-age variability narrowed from 10.5 pp (59.4%–69.9%) before deployment to 6.1 pp (80.4%–86.5%) after deployment.
Enhanced CIN2+ detection and case management
The overall CIN2+ detection rate increased from 0.35% in the pre-digital period (pooled 2021–2023) to 0.67% in 2024 (absolute increase 0.32 pp; 95% CI: 0.25–0.40; P < 0.001) (Table 3). The age-specific gains were consistent. Specifically, the detection rose by 0.28 pp in women 35–44 y of age (0.35% to 0.63%; 95% CI: 0.15–0.41; P < 0.001), 0.31 pp in women 45–54 y of age (0.29% to 0.60%; 95% CI: 0.20–0.41; P < 0.001), and 0.35 pp in women 55–64 y of age (0.46% to 0.82%; 95% CI: 0.20–0.51; P < 0.001). Site-level improvements were heterogeneous. Substantial increases were noted in Yanting County (0.48% to 1.02%; 0.54 pp; 95% CI: 0.33–0.75; P < 0.001) and Xinping County (0.29% to 0.81%; 0.52 pp; 95% CI: 0.34–0.70; P < 0.001) with more modest or borderline changes in Zezhou (0.30% to 0.53%; 0.23 pp; 95% CI: 0.07–0.38; P = 0.003) and Mangshi (0.15% to 0.27%; 0.11 pp; 95% CI: 0.02–0.21; P = 0.014). Xiangyuan remained stable (0.79% to 0.82%; 95% CI: –0.21 to 0.26; P = 0.807) and Shimian had a non-significant difference (0.30% to 0.49%; 95% CI: –0.02 to 0.40; P = 0.059). Primary HPV + VIA/VILI triage and multi-triage algorithms yielded CIN2+ detection rates of 0.70%–0.86% vs. 0.32% in pre-digital cytology-only pathways. Cervical cancer detection rate remained low and did not change materially (0.04% pre-digital vs. 0.04% post-digital; 95% CI: –0.02 to 0.02; P = 0.868), which is consistent with the relative short observation window and small absolute number of invasive cases.
Analysis of follow-up completion rate was restricted to the four sites with fully ascertained 2024 diagnostic and management outcomes (Mangshi, Shimian, Xiangyuan, and Xinping). Zezhou and Yanting were excluded because 2024 case follow-up was ongoing. Among the four sites, the proportion of CIN2+ cases (CIN2/3 or invasive cancer) achieving documented completion of the indicated diagnostic/treatment management pathway increased from 56.0% (154/275) in the pre-digital period (2021–2023) to 76.2% (385/505) in post-digital period (2023–2024), with an absolute increase of 20.2 pp (95% CI: 13.3–27.2; P < 0.001). Management completion of CIN2/3 patients rose from 55.6% to 76.1% (absolute increase 20.6 pp; 95% CI: 13.2–27.9; P < 0.001). The increase for invasive cancer (58.8% to 77.4%; absolute increase 18.6 pp; 95% CI: −3.5 to 40.7) did not reach statistical significance due to the small case count (n = 31). Age-specific improvements in completion rate were greatest among women 35–44 (49.4% to 84.6%; absolute increase 35.2 pp; 95% CI: 22.5–47.8; P < 0.001) and 45–54 y of age (50.5% to 78.9%; 28.4 pp; P < 0.001) with minimal change in women 55–64 y of age (68.3% to 68.5%; P = 0.976). Site-specific effects were large in Xiangyuan (11.4% to 95.5%; 84.1 pp; 95% CI: 76.2–92.0; P < 0.001) and Mangshi (16.7% to 97.4%; absolute increase 80.8 pp; 95% CI: 67.6–93.9; P < 0.001), modest and non-significant in Xinping (91.3% to 98.5%; P = 0.228), and slightly negative in Shimian (96.9% to 92.3%; P = 0.451), suggesting a ceiling effect in which baseline manual tracking was already near-saturation.
Discussion
Less
In this study, historical data were retrospectively collected as a control group and a digital platform was prospectively implemented as an intervention. The effectiveness of the digital population management platform in rural areas of China was evaluated by monitoring the over-screening rate, CIN2+ detection rate, and follow-up/management outcomes. Significant improvements were observed following implementation of the digital intervention across all these indicators, particularly in regions with limited-service capacity.
Impact of digital de-duplication on over-screening rates
Over- and under-screening for cervical cancer are widespread in many regions20–26. There is a common phenomenon in areas with limited health resources-characterized by inadequate services and poor infrastructure3,7. Women with health awareness undergo annual screenings, while women lacking such awareness are often entirely unfamiliar with cervical cancer screening8,27. This disparity highlights a major challenge in China. Despite the expanding coverage of cervical cancer screening programs, the incidence has not declined, in part due to these uneven screening practices6,28–30. In this study the over-screening proportions were 11.96% in 2022 and 12.64% in 2023 based on a single-year look-back. The rates of over-screening varied considerably across regions. Some areas, having already recognized the issue of over-screening, managed to keep the rate < 10% through targeted interventions. However, in the areas that lacked such awareness, the annual over-screening rate remained at approximately 25%. The 2-y cumulative over-screening rate was approximately 40%. In many regions, cytology-based screening methods were previously adopted with guidelines recommending a 3-y screening interval30,31. Within this interval approximately one-half of the individuals should not have undergone screening. This over-screening rate is consistent with findings reported in other studies32. There are many reasons for the widespread occurrence of over-screening, including cervical cancer screening providers unable to keep up with rapidly changing guidelines33,34 or feeling pressured to meet screening quotas assigned by higher authorities35. The absence of individual case records made it impossible to identify repeated screenings in previous national cervical cancer screening programs36. Uncertainty about the timing of the last screening and fears of a missed cancer diagnosis can both lead women to request or undergo unnecessary repeat screenings37–39. There was a decline of over-screening proportion in all 3 age groups with the largest drop (26.18%) occurred among women 35–44 y of age. This finding may because younger women are more aware of self-health management, have more frequent access to the health care system for fertility-related tests, and have more opportunities for screening40, thus having higher baseline repeat screening rates. Previous research had the same finding that women in the lower age group had a higher rate of repeat screening than women in the older age group22,41. There was also a decline in all different screening stratify groups with the largest drop (39.07%) was seen in cytology alone group. Cytology testing is a relatively traditional method among all the screening strategies. Gradual transition from cytology testing to HPV DNA testing makes the digital platform gradually being adopted, so the baseline repeat screening rate of the cytology test group was relatively high with more room for a decline. In addition, HPV DNA testing and combined screening strategies have higher sensitivity and long-term negative predictive value compared to cytology testing alone, allowing for longer screening intervals (5 y vs. 3 y)25 in that case, providers with knowledge of the guidelines will direct women to choose a longer screening interval, thereby reducing the baseline repeat screening rate. In general, the de-duplication function of the digital platform is notable for reducing repeat screening under different screening strategies. Furthermore, compared to the traditional method of recording screening information through paper materials and eliminating duplications, the de-duplication effect of the digital platform has significant advantages with a reduction of 42.24% vs. 8.33%, indicating the OCR-enabled One-ID real-time de-duplication system on the digital platform can be a better system-level strategy that helps reduce unnecessary, repeated screening and promotes the effective use of limited medical resources7,42.
Colposcopy follow-up, CIN2+ detection, and CIN2+ management
Management of CIN2+ individuals, including follow-up colposcopy and disease management, has long been a challenging task at the primary care level43,44 because the target population is often asymptomatic35. Follow-up in China has traditionally been performed through telephone appointments followed by examinations at hospitals or community health centers43. Screening recipients typically perceive screening information passively. The platform we have designed aims to address these issues by promptly delivering screening results and providing appointment channels to recipients via WeChat45, as well as automatically pushing follow-up lists to healthcare providers. The unified digital platform helps prevent fragmentation of screening information and improves referral rates by documenting cases of women who require colposcopy referral due to screening abnormalities and proactively prompting healthcare providers46,47. The detection rate of CIN2+ increased after the implementation of the platform. This improvement appears to be driven primarily by changes in screening modalities and a reduction in over-screening, which enabled previously unscreened individuals to gradually access these services, as well as an enhanced follow-up rate that led to the identification of more lesions. This finding is consistent with previous findings in which lower rates of over-screening co-exist with higher screening adherence and the use of digital tools to systematically manage follow-up data reduces information loss and improves screening efficiency and the follow-up completion rate, making data analysis and quality control more efficient48. However, the relative contributions of reduced over-screening versus changes in screening strategy require further evaluation.
The overall management proportion for CIN2+ increased from 56.0% in the pre-digital period to 76.2% post-digital (P < 0.001) across these four sites with an increase of 20.6% for CIN2/3 lesions (P < 0.001) and 18.6% for invasive cancer (not reaching statistical significance). This finding showed that the digital platform has a promoting effect on achieving the WHO goal that 90% of women identified with cervical disease receive treatment (90% of women with pre-cancer treated and 90% of women with invasive cancer managed), especially in the period of precancerous lesions49, which is conducive to the early prevention and control of cervical cancer. However, there was no statistically significant effect on improving the follow-up rate of invasive cancer, which may be due to the insufficient number of cases, so it is necessary to accumulate screening cases and further study the role of digital platform in the management of women diagnosed with invasive cancer.
Age-stratified gains were largest in women 35–44 y of age (35.2%) and 45–54 y of age (28.4%), while the change in the 55–64 y age group (0.2%) was negligible. This finding is consistent with age trends in data from the three U.S. health systems, which indicates that women 25–29 y of age have a higher follow-up rate for abnormal screening results than women > 40 years of age41. Site-specific improvements were substantial in Mangshi and Xiangyuan but not significant in Xinping and Shimian. Site heterogeneity was driven by baseline management capacity. High-performing sites showed minimal incremental benefit (ceiling effect), whereas low-performing sites realised large gains once provider task prompts and patient reminder messages were available. Challenges vary in different sites when implementing digital platform for cervical cancer control due to the burden of training, technology-specific issues, infrastructure accessibility, and technology inequality14.
Limitations and future directions
This study had limitations. First, the non-randomized pre–post observational design limits our ability to exclude time-varying confounding (e.g., policy changes, resource infusions, outreach activities, and seasonality). Second, records from 2021 to 2023 were retrospectively collected and may include ID-entry errors or incomplete follow-up information, potentially under-ascertaining baseline over-screening. In contrast, the 2024 OCR-enabled One-ID system provided real-time de-duplication and linkage, creating asymmetric data fidelity across periods. Third, the transition from cytology to HPV-based screening can increase sensitivity, so the observed rise in CIN2+ detection rate is best interpreted as a joint effect of strategy adoption and process strengthening, rather than a platform-only effect. Overall, the improvements were contemporaneous with the platform rollout and other changes, so the platform’s independent effect may be overstated. The magnitude of any indirect effects warrants investigation with longer time series.
Future research should conduct multi-center prospective studies and integrate both quantitative and qualitative methods to comprehensively assess healthcare provider experiences and cost-effectiveness. In addition, barriers faced by specific populations, such as women with low literacy, those without mobile phones, or individuals living in border regions, should be addressed through more assistive and inclusive design. For geographically expansive countries, like China, building an interoperable national digital platform is essential to reach hard-to-access or highly mobile populations. Developing additional functionalities on this platform, such as AI-based risk assessment, is an inevitable trend. Finally, issues related to data security and quality monitoring in digital screening programs warrant urgent regulatory attention.
Conclusions
Less
In conclusion, digital deployment of an OCR-enabled One-ID platform nearly eliminated over-screening, improved CIN2+ detection rate, and strengthen case management, especially in rural sites, suggesting a system-level data quality effect. The OCR-enabled One-ID digital platform was associated with less over-screening, higher completion of the care cascade, and greater CIN2+ detection, particularly at sites that had lower baseline performance.
Funding
Less
  • This work was supported by the Chongqing Tencent Sustainable Development Foundation through the project “Comprehensive Prevention and Control Demonstration Project for Eliminating Cervical Cancer and Breast Cancer in Low Health Resource Areas of China” (Project No. SD20240904145730) and by the Tencent Sustainable Social Value (SSV) Inclusive Health Lab (Project No. SSVPJ202307060001).
References
Less
1.
Bray F,Laversanne M,Sung H,Ferlay J,Siegel RL,Soerjomataram I, et al.Global cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries.CA Cancer J Clin.2024; 74: 229–63.
2.
Han B,Zheng R,Zeng H,Wang S,Sun K,Chen R, et al.Cancer incidence and mortality in China, 2022.J Natl Cancer Cent.2024; 4: 47–53.
3.
Yan H,Wang Q,Qiao Y.Cervical cancer prevention in China: where are we now, and what’s next?Cancer Biol Med.2024; 21: 213–7.
4.
Li Z,Liu P,Yin A,Zhang B,Xu J,Chen Z, et al.Global landscape of cervical cancer incidence and mortality in 2022 and predictions to 2030: the urgent need to address inequalities in cervical cancer.Int J Cancer.2025; 157: 288–97.
5.
World Health Organization.Regional Office for South-East Asia. Accelerating the elimination of cervical cancer as a public health problem: towards achieving 90–70–90 targets by 2030; 2022. Available from: https://iris.who.int/handle/10665/361138.
6.
Zhang M,Wang L,Zhang X,Li C,Zhao Z,Yu M, et al.Cervical cancer screening rates among Chinese women – China, 2023–2024.China CDC Wkly.2025; 7: 321–6.
7.
Jia X,Yan H,Shi Z,Gao C,Zhai J,Ding H, et al.Systematic training and technological empowerment: enhancing the quality of cervical and breast cancer screening in low-resource areas of China.Gynecol Obstet Clin Med.2024; 4: e000107.
8.
Petersen Z,Jaca A,Ginindza TG,Maseko G,Takatshana S,Ndlovu P, et al.Barriers to uptake of cervical cancer screening services in low-and-middle-income countries: a systematic review.BMC Women’s Health.2022; 22: 486.
9.
Morse RM,Brown J,Ríos López EJ,Prieto BA,Kohler-Smith A,Gonzales Díaz K, et al.Challenges associated with follow-up care after implementation of an HPV screen-and-treat program with ablative therapy for cervical cancer prevention.BMC Public Health.2024; 24: 2121.
10.
Mantula F,Toefy Y,Sewram V.Barriers to cervical cancer screening in Africa: a systematic review.BMC Public Health.2024; 24: 525.
11.
Liu X,Ning L,Fan W,Jia C,Ge L.Electronic health interventions and cervical cancer screening: systematic review and meta-analysis.J Med Internet Res.2024; 26: e58066.
12.
Arrossi S,Paolino M,Antelo VS,Thouyaret L,Kohler RE,Cuberli M, et al.Effectiveness of an mHealth intervention to increase adherence to triage of HPV DNA positive women who have performed self-collection (the ATICA study): a hybrid type I cluster randomised effectiveness-implementation trial.Lancet Reg Health Am.2022; 9: 100199.
13.
Addo-Lartey AA,Bonful HA,Sefenu RS,Abagre TA,Asamoah A,Bandoh DA, et al.Effectiveness of a culturally tailored text messaging program for promoting cervical cancer screening in accra, Ghana: a quasi-experimental trial.BMC Womens Health.2024; 24: 22.
14.
Rossman AH,Reid HW,Pieters MM,Mizelle C,von Isenburg M,Ramanujam N, et al.Digital health strategies for cervical cancer control in low- and middle-income countries: systematic review of current implementations and gaps in research.J Med Internet Res.2021; 23: e23350.
15.
Huf S,Kerrison RS,King D,Chadborn T,Richmond A,Cunningham D, et al.Behavioral economics informed message content in text message reminders to improve cervical screening participation: two pragmatic randomized controlled trials.Prev Med.2020; 139: 106170.
16.
Firmino-Machado J,Varela S,Mendes R,Moreira A,Lunet N.Stepwise strategy to improve cervical cancer screening adherence (SCAN-Cervical Cancer) – automated text messages, phone calls and reminders: population based randomized controlled trial.Prev Med.2018; 114: 123–33.
17.
Linde DS,Andersen MS,Mwaiselage JD,Manongi R,Kjaer SK,Rasch V.Text messages to increase attendance to follow-up cervical cancer screening appointments among HPV-positive Tanzanian women (Connected2Care): study protocol for a randomised controlled trial.Trials.2017; 18: 555.
18.
Paz AA,Paula ACM,Lima AM,Castro GL,Silva MCB da Silva LT.Health dashboard for information management in cervical cancer screening.Rev Lat Am Enfermagem.2025; 33: e4446.
19.
Nessa A,Azad AK,Uddin SMN,Khan MAH,Zaman S,Khan MAS.Cervical cancer screening data from the case-based national electronic registry in Bangladesh.BMC Global and Public Health.2025; 3: 34.
20.
Almeida CM,Rodriguez MA,Skootsky S,Pregler J,Steers N,Wenger NS.Cervical cancer screening overuse and underuse: patient and physician factors.Am J Manag Care.2013; 19: 482–9.
21.
Fontham ETH,Wolf AMD,Church TR,Etzioni R,Flowers CR,Herzig A, et al.Cervical cancer screening for individuals at average risk: 2020 guideline update from the American Cancer Society.CA Cancer J Clin.2020; 70: 321–46.
22.
Parekh N,Donohue JM,Men A,Corbelli J,Jarlenski M.Cervical cancer screening guideline adherence before and after guideline changes in Pennsylvania Medicaid.Obstet Gynecol.2017; 129: 66–75.
23.
Wright JD,Chen L,Tergas AI,Melamed A,St Clair CM,Hou JY, et al.Overuse of cervical cancer screening tests among women with average risk in the United States from 2013 to 2014.JAMA Netw Open.2021; 4: e218373.
24.
Franklin M,Webel A,Kaelber D,Evans J,Kelley C.Prevalence of cervical cancer overscreening: review of a wellness registry.Comput Inform Nurs.2020; 38: 459–65.
25.
Lee YW,Morgan JR,Fiascone S,Perkins RB.Underscreening, overscreening, and guideline-adherent cervical cancer screening in a national cohort.Gynecol Oncol.2022; 167: 181–8.
26.
Xia C,Basu P,Kramer BS,Li H,Qu C,Yu XQ, et al.Cancer screening in China: a steep road from evidence to implementation.Lancet Public Health.2023; 8: e996–1005.
27.
Farajimakin O.Barriers to cervical cancer screening: a systematic review.Cureus.2024; 16: e65555.
28.
Tan N,Wu Y,Li B,Chen W.Burden of female breast and five gynecological cancers in China and worldwide.Chin Med J (Engl).2024; 137: 2190–201.
29.
Zhang M,Zhong Y,Wang L,Bao H,Huang Z,Zhao Z, et al.Cervical cancer screening coverage – China, 2018–2019.China CDC Wkly.2022; 4: 1077–82.
30.
Zhao F,Lang J,Qiao Y,Zhu L.How can China achieve WHO’s 2030 targets for eliminating cervical cancer?BMJ.2024; 386: e078641.
31.
Zampaoglou E,Boureka E,Gounari E,Liasidi PN,Kalogiannidis I,Tsimtsiou Z, et al.Screening for cervical cancer: a comprehensive review of guidelines.Cancers (Basel).2025; 17: 2072.
32.
Lee YW,Morgan J,Fiascone S,Perkins R.Cervical cancer screening practices: Rates of underscreening, overscreening, and guideline-adherent screening in a national cohort (379).Gynecol Oncol.2022; 166: S193–4.
33.
Arrossi S,Straw C,Sanchez Antelo V,Paolino M,Baena A,Forestier M, et al.Implementation of WHO guidelines for cervical cancer screening, diagnosis and treatment: knowledge and perceptions of health providers from Argentina.BMC Cancer.2024; 24: 996.
34.
Perkins RB,Guido RL,Saraiya M,Sawaya GF,Wentzensen N,Schiffman M, et al.Summary of current guidelines for cervical cancer screening and management of abnormal test results: 2016–2020.J Womens Health (Larchmt).2021; 30: 5–13.
35.
Wu Y,Luo J,Ye D,Gao S.Benefits and challenges of cervical cancer screening since the implementation of the ‘two cancer’ screening programme in China: Findings from Shangyu, Zhejiang in 2019–23.J Glob Health.2025; 15: 04064.
36.
Gopalkrishnan K,Karim R.Addressing global disparities in cervical cancer burden: a narrative review of emerging strategies.Curr HIV/AIDS Rep.2025; 22: 18.
37.
Teoh DG,Marriott AE,Isaksson Vogel R,Marriott RT,Lais CW,Downs LS Jr, et al.Adherence to the 2012 national cervical cancer screening guidelines: a pilot study.Am J Obstet Gynecol.2015; 212: 62.e1–9.
38.
Roland KB,Benard VB,Greek A,Hawkins NA,Manninen D,Saraiya M.Primary care provider practices and beliefs related to cervical cancer screening with the HPV test in Federally Qualified Health Centers.Prev Med.2013; 57: 419–25.
39.
Hawkins NA,Benard VB,Greek A,Roland KB,Manninen D,Saraiya M.Patient knowledge and beliefs as barriers to extending cervical cancer screening intervals in Federally Qualified Health Centers.Prev Med.2013; 57: 641–5.
40.
Buss LF,Levi JE,Longatto-Filho A,Cohen DD,Cury L,Martins TR, et al.Attendance for diagnostic colposcopy among high-risk human papillomavirus positive women in a Brazilian feasibility study.Int J Gynaecol Obstet.2021; 152: 72–7.
41.
Cheng D,Rieu-Werden ML,Lykken JM,Werner CL,Feldman S,Silver MI, et al.Assessing management of abnormal cervical cancer screening results and concordance with guideline recommendations in three US healthcare settings.Cancer Epidemiol Biomarkers Prev.2024; 33: 912–22.
42.
Kulkarni A,Chen L,Gockley A,Khoury-Collado F,Hou J,Clair CST, et al.Patterns of cervical cancer screening follow-up in the era of prolonged screening intervals.Gynecol Oncol.2023; 175: 53–9.
43.
Liao Z,Zou K,Lei M,Wu Y,Yang W,Zhang Y.Performance of government-financed cervical cancer screening in Hunan, China, and optimization of triage strategies.J Low Genit Tract Dis.2025; 29: 207–12.
44.
Benites-Zapata VA,Hernandez-Bustamante EA,Acuña-Chávez LM,Escudero-Gaytan CP,Ulloque-Badaracco JR,Alarcón-Braga EA, et al.Colposcopy in the primary health care: a scoping review.J Prim Care Community Health.2023; 14: 21501319231198942.
45.
Ji L,Yao Y,Yu D,Chen W,Yin S,Fu Y, et al.Performance of a full-coverage cervical cancer screening program using on an artificial intelligence- and cloud-based diagnostic system: observational study of an ultralarge population.J Med Internet Res.2024; 26: e51477.
46.
Reaves S,Hall KC,Stewart MW,Wentzensen N,Ferrell C,Risley C, et al.Evaluation of follow-up colposcopy procedures after abnormal cervical screening result across a statewide study in Mississippi.Cancer Causes Control.2024; 35: 1487–96.
47.
Viswanathan V,Ganeshkumar P,Selvam JM,Selvavinayagam TS.Referral mechanism and beneficiary adherence in cervical cancer screening program in Tiruchirappalli district, Tamil Nadu state, India, 2012–2015.Indian J Cancer.2022; 59: 39–45.
48.
Dong B,Zou H,Mao X,Su Y,Gao H,Xie F, et al.Effect of introducing human papillomavirus genotyping into real-world screening on cervical cancer screening in China: a retrospective population-based cohort study.Ther Adv Med Oncol.2021; 13: 17588359211010939.
49.
Canfell K,Kim JJ,Brisson M,Keane A,Simms KT,Caruana M, et al.Mortality impact of achieving WHO cervical cancer elimination targets: a comparative modelling analysis in 78 low-income and lower-middle-income countries.Lancet (London, England).2020; 395: 591–603.
Appendix
Less
Year 2025 volume 22 Issue 9
PDF
4
2
Cite this Article
BibTeX
Article Info
doi: 10.20892/j.issn.2095-3941.2025.0419
  • Receive Date：2025-07-24
  • Online Date：2026-11-07
  • Published：2025-09-15
Article Data
Affiliations
History
  • Received：2025-07-24
  • Accepted：2025-09-05
Funding
This work was supported by the Chongqing Tencent Sustainable Development Foundation through the project “Comprehensive Prevention and Control Demonstration Project for Eliminating Cervical Cancer and Breast Cancer in Low Health Resource Areas of China” (Project No. SD20240904145730) and by the Tencent Sustainable Social Value (SSV) Inclusive Health Lab (Project No. SSVPJ202307060001).
Affiliations
    1School of Population Medicine and Public Health, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100730, China
    2National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100021, China
    3Tencent Inclusive Health Lab, Beijing 100193, China
    4Department of Cancer Prevention and Control, Yunnan Cancer Hospital, The Third Affiliated Hospital of Kunming Medical University, Kunming 650118, China
    5School of Public Health, Changzhi Medical College, Changzhi 046000, China
    6School of Public Health, Shanxi Medical University, Jinzhong 030001, China

Corresponding:

Correspondence to: Hanyue Ding, Alex Ng and Youlin Qiao, E-mail: , and
References
Share
https://castjournals.cast.org.cn/joweb/cbm/EN/10.20892/j.issn.2095-3941.2025.0419
Share to
QR

Scan QR to access full text

Cite this article
BibTeX
Citations
表12种不同金属材料的力学参数
科
Family		 属数
Number of
genus		 种数
Number of
species		 占总种数比例
Percentage of
total species (%)		 属
Genus		 种数
Number of
species		 占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
关闭全屏
  • BibTeX
  • EndNote
  • RefWorks
  • TxT
Links
Articles
Latest Articles
Most Read
Collections
Updates
Events
News
Multimedia
About
About Us
Contact
No. 86 Xueyuan South Road, Haidian District, Beijing
100081
010-62662699(Operation and Technical Support)
qkjq@cast.org.cn

Copyright © 2025 China Association for Science and Technology. All rights reserved. For all open access content, the relevant licensing terms apply.
Sponsored by the Office of the Leading Group for Cybersecurity and Informatization of CAST, and supported by Science and Technology Review Publishing House