Abstract
Hepatocellular carcinoma (HCC) surveillance rates are suboptimal. We aimed to identify HCC surveillance barriers from both physician’s and patient’s perspectives and assess the effectiveness of physician education using social networks. A nationwide survey with 513 physicians and another single-center survey with 315 HCC-risk patients were conducted. Barriers to suboptimal surveillance were identified using univariate and multivariate logistic regression analysis. We educated 143 physicians by sending brief notes on HCC surveillance guidelines via social networks and re-evaluated their knowledge after 60 days using t test. Surveys showed 458 (86.3%), 254 (47.8%), and 225 (42.4%) physicians recommended surveillance in patients with cirrhosis, at-risk hepatitis B virus, and hepatitis C virus infection, respectively. Only 228 (42.9%) and 241 (38.0%) respondents adhered to recommended surveillance tools and interval, respectively. The main surveillance barriers among physicians were the lack of knowledge and resource limitations. The lack of a doctor’s prescription was identified as a major barrier by patient’ perspectives (odds ratio 1.4, 95% CI: 1.1–1.8, P = .024). Education via social networks enhanced physicians’ knowledge, with pre- and post-education scores for guideline awareness of 63.0% versus 84.3% (P < .001) and for surveillance indication and tools of 40.0% versus 63.0% (P = .001), and 42.0% versus 59.3% (P = .015), respectively. Physicians’ knowledge gap is a primary barrier for adherence to HCC surveillance protocols. Brief education via social networks shows effectiveness at increasing physicians’ knowledge of HCC surveillance.
Keywords: cancer surveillance, education, guidelines adherence, knowledge, social network
1. Introduction
Hepatocellular carcinoma (HCC) is one of the leading causes of cancer-related death worldwide. The prognosis of HCC patients primarily depends on the cancer stage at diagnosis. HCC surveillance has been shown to improve early detection of HCC.[1] Current international guidelines recommend HCC surveillance using ultrasound (US) with or without serum alpha-fetoprotein (AFP) test every 6 months in patients at high-risk for developing HCC.[2,3] Despite these well-known benefits, recent meta-analysis revealed that HCC surveillance remained suboptimal with wide variety among countries, ranging from 18.4%–42% in the United States,[4] 23.1% in Thailand,[5] and 70% in many European countries.[6] Therefore, we aimed to identify barriers of HCC surveillance from both physician’s and patient’s perspectives and assess efficacy of a brief HCC surveillance educational intervention that were disseminated to physicians via social network platforms.
2. Methods
2.1. Study design
This study was registered to the Thai clinical trial registry (number 20210127006). This study included 2 phases from July 2016 to February 2019 (Fig. 1). In Phase 1, we evaluated barriers to HCC surveillance based on physician’s and patient’s perspectives using questionnaires created specifically for the study. In Phase 2, we created a simple educational card for providing knowledge of HCC surveillance to physicians. The card was developed based on the results of Phase 1. Subsequently, we conducted a prospective interventional study to evaluate the effectiveness of the card on improving physicians’ knowledge of HCC surveillance. The study protocol was approved by the Ethics Committee of the Faculty of Medicine, Chulalongkorn University (IRB number 618/58). Written informed consent was obtained from all study participants prior to enrollment.
Figure 1.
Study flow.
2.2. Study cohorts
2.2.1. Phase 1: survey of barriers to HCC surveillance.
Physician’s perspectives
Our primary objective was to identify physician- and patient-based barriers to proper HCC surveillance according to Thailand’s 2015 national guidelines endorsed by the Thai Association for the Study of the Liver. The guidelines recommended HCC surveillance using upper abdominal US with AFP test every 6 to 12 months for high-risk patients with the following conditions: cirrhosis from any causes; chronic hepatitis B virus (HBV) infection in males with age > 40 years or females with age > 50 years; chronic HBV- infected patients with a history of HCC in the first-degree relatives; and chronic hepatitis C virus infection with > F3 fibrosis.
We performed a nationwide survey from physicians working at different hospital levels (community, secondary, and tertiary centers) located in all geographic regions of Thailand (57 of 77 provinces). Physicians with different areas of expertise including general practitioners (GPs), internal medicine residents, internists, and gastroenterologists were recruited to participate in the study. It should be noted that GPs in Thailand are doctors who have not applied for residency programs. Eligibility was limited to physicians who reported seeing at least 1 high-risk HCC patient weekly. We excluded physicians who were retired, worked full-time in private hospitals, or those whose major professional activities were research.
We developed questionnaires to assess 4 primary domains: surveillance knowledge, which comprised of “knowing” the recommendations (indication, tools, and intervals) and “understanding” the recommendations (case-based questions); attitudes toward surveillance; physician practice pattern; and opinions about surveillance barriers including physician factors and healthcare system factors. The questionnaires were pilot-tested on 10 internists and 10 internal medicine residents to ensure comprehension. Reliability testing was also performed with 20 physicians using the test-retest method, which showed that most of the questions (90%) were properly understood (median agreement 80%). The final version of the questionnaires was modified based on the pre-test results. Each questionnaire took approximately 10 minutes to complete (Supplemental document 1, Supplemental Digital Content 1, http://links.lww.com/MD/H303).
Patient’s perspectives
The respondents were patients with high risks for developing HCC who were followed up at the liver clinic at Chulalongkorn Hospital, Thailand. We excluded patients with a follow-up time of <24 months and those diagnosed with HCC. The patient questionnaire was designed by the study investigators and later modified after a pilot test with patients. The questionnaires consisted of 4 sections: patient demographics; HCC knowledge (risk of HCC, optimal tools, and interval for surveillance); attitudes toward HCC surveillance; and opinions about barriers (personal, physician, and healthcare system) to adequate surveillance (Supplemental document 2, Supplemental Digital Content 2, http://links.lww.com/MD/H304).
2.2.2. Phase 2: improving HCC surveillance knowledge by brief educational tool.
We created a brief knowledge card which comprised of indications, tools, and interval protocols for HCC surveillance based on the 2015 Thai Association for the Study of the Liver guidelines (Fig. 2). The card was personally sent to all internal medicine residents (n = 108) from Phase 1 study through Facebook and LINE, which were instant messaging apps widely used in Thailand. The card aimed to educate and remind HCC surveillance recommendations to internal medicine residents. The residents were able to download the educational card and keep it in their personal mobile phones. The card took approximately 2 to 3 minutes to read. All residents were asked to notify investigators after they had read the card. Participants may download the card and use for future review. After 60 days, we re-evaluated their knowledge using the Phase 1 questionnaire. They were requested not to use the card during the re-evaluation.
Figure 2.
Knowledge card.
2.3. Statistical analysis
Sample size estimation was performed before the start of the study. In Phase 1, a systematic stratified random sampling was designed to identify the sample population of physicians. We randomly chose 70% of provinces from each of the 6 regions in Thailand. The number of hospitals and physicians per population ratio was calculated based on information from the Ministry of Public Health to estimate sample size needed for each selected province. The questionnaires were distributed to physicians in community hospitals and secondary/tertiary hospitals in a ratio of 2:1, corresponding to the number of patients and physicians that were doubled in community hospitals.[7,8]
To identify patients’ barriers to HCC surveillance, patients were divided into 2 groups: optimal and suboptimal surveillance groups. Optimal patients were defined as having surveillance that followed the guidelines, while suboptimal patients were defined as having surveillance that were below the guideline standards. Patients in both groups had been followed up during the past 2 years.
The results from questionnaires were presented as number (percentage) and mean (standard deviation, SD) for categorical variables and continuous variables, respectively. Chi-square test was used to compare: physicians’ barriers to HCC surveillance between those in community hospitals and the higher-level hospitals; and patients’ barriers between those in optimal and suboptimal surveillance groups. Univariate and multivariate logistic regression analyses were used to identify barriers to surveillance. For questionnaires assessing patients’ perspective, patient knowledge, attitudes, and surveillance barriers were dichotomous categorical variables (i.e., yes/no, do not know/know). The association between these variables and suboptimal surveillance was analyzed by binary logistic regression.
In Phase 2, results were presented as the percentage of internal medicine residents who correctly answered the questions. Pre-and post-education correct response rates were analyzed by unpaired t test. A P value of < .05 indicated a significant difference. (SPSS version 23.0, Chicago, IL) was used for statistical analysis.
3. Results
3.1. Phase 1: barriers to HCC surveillance
3.1.1. Physician’s perspectives.
Survey response rate among physicians was 75.6% (531/702). Mean + SD age was 28 ± 4 years. Most respondents were GPs (n = 388, 72.9%), followed by internal medicine residents (n = 97, 18.3%), internists (n = 44, 8.3%), and gastroenterologists (n = 2, 0.4%). Most respondents worked at secondary hospitals (n = 300, 56.5%), followed by community hospitals (n = 134, 25.2%), and tertiary hospitals (n = 97, 18.3%).
Overall, 289 (54.4%) of respondents were aware of HCC surveillance guidelines. Most physicians (n = 458, 86.3%) recommended HCC surveillance to patients with cirrhosis. However, less than half of respondents recommended surveillance to chronic HBV patients (n = 254, 42.4%) and hepatitis C virus patients (n = 225, 47.8%). For surveillance tools, 228 (42.9%) respondents answered using US with or without AFP, whereas 187 (35.2%), 40 (7.5%), 48 (9.0%), and 20 (3.8%) physicians answered US plus AFP, US alone, abdominal CT/MRI, and AFP alone, respectively. Regarding surveillance intervals, 241 (45.4%) physicians responded that the surveillance should be performed every 6 to 12 months as recommended by the national guidelines. However, 202 (38.0%) and 69 (13.0%) physicians answered the surveillance intervals of biannually and annually, respectively. A total of 14 physicians (2.6%) answered that surveillance should be done when the patients developed symptoms. The questionnaire also posed a series of 5 case-based questions where physicians were asked to select the correct clinical decision for each case. The percentage of correct answers from Phase 1 study ranged from 13.7% to 33.5% (Phase 1, Table 1).
Table 1.
Physicians’ knowledge of HCC surveillance.
| Variables | Study phase (percentage of correct response) | |||
|---|---|---|---|---|
| Phase 1 (n = 531) | Phase 2* | |||
| Pre-education (n = 97) | Post-education (n = 108) | P † | ||
| Surveillance awareness | 289 (54.4%) | 61 (62.9%) | 91 (84.3%) | <.001 |
| Knowledge of surveillance | ||||
| Indication for surveillance | ||||
| Cirrhosis | 458 (86.3%) | 90 (92.8%) | 106 (98.1%) | .062 |
| HBV with indications | 254 (47.8%) | 39 (40.2%) | 68 (63.0%) | .001 |
| HCV with indications | 225 (42.4%) | 53 (54.6%) | 69 (63.9%) | .180 |
| Surveillance tools(s) | 228 (42.9%) | 41 (42.3%) | 64 (59.3%) | .015 |
| Surveillance interval(s) | 241 (45.4%) | 43 (44.3%) | 55 (50.9%) | .348 |
| Case-based questions‡ | ||||
| Case 1 | 153 (28.8%) | 36 (37.1%) | 69 (63.9%) | <.001 |
| Case 2 | 178 (33.5%) | 37 (38.1%) | 59 (54.6%) | .009 |
| Case 3 | 162 (30.5%) | 28 (28.9%) | 62 (57.4%) | <.001 |
| Case 4 | 173 (32.6%) | 34 (35.1%) | 65 (60.2%) | <.001 |
| Case 5 | 73 (13.7%) | 21 (21.6%) | 43 (39.8%) | .002 |
HBV = hepatitis B virus, HCC = hepatocellular carcinoma, HCV = hepatitis C virus.
Number (%) presents the number of internal medicine residents who correctly answered the questions. P < .05 is significant by the unpaired 2-sample t test.
P value is difference between the percentage between pre- and post-education.
‡Scenario-based questions are as follows: (1) compensated cirrhosis, (2) decompensated cirrhosis, (3) history of HCC in first degree relative(s) in HBV non-cirrhosis, (4) male with HBV non-cirrhosis, age > 40 yr, and (5) female with HBV non-cirrhosis, age > 50 yr.
Regarding physicians’ attitudes, most believed that HCC surveillance was cost-effective (n = 472, 88.9%) and did not increase their workloads (n = 513, 96.6%). More than half of the respondents (n = 288, 54.2%) thought that surveillance was the responsibility of all physicians who worked with at-risk HCC patients. A total of 157 (29.5%) respondents believed that they had been influenced by a history of heavy alcohol in high-risk HCC patients. Thirty one physicians (5.8%) responded that patients’ history of heavy alcohol strongly influenced their decisions, while 126 physicians (23.7%) were moderately influenced to perform fewer HCC surveillance tests (Table S1, Supplemental Digital Content 3, http://links.lww.com/MD/H305).
Regarding the barriers to surveillance, only 33 (6.2%) to 43 (8.0%) physicians reported concerns about the costs of surveillance tools. Instead, many physicians reported the lack of access to an adequate US machine (n = 85, 16.0%) and AFP test (n = 128, 24.1%) as a major barrier. This concern was more common in the community hospitals compared to secondary or tertiary care hospitals (Table 2).
Table 2.
Physicians’ barriers related to HCC surveillance tools.
| Barriers to HCC surveillance | Overall (n = 531) | Community hospitals (n = 134) | Secondary and tertiary centers (n = 397) | P * |
|---|---|---|---|---|
| Factors related to US machine | ||||
| No limitation | 189 (35.6%) | 39 (29.1%) | 150 (37.8%) | <.001 |
| Unavailable US machine | 85 (16.0%) | 75 (56.0%) | 10 (2.5%) | <.001 |
| Limited access to US machine | 154 (29.0%) | 24 (17.9%) | 130 (32.7%) | <.001 |
| Financial concerns | 33 (6.2%) | 13 (9.7%) | 20 (5.0%) | .272 |
| Factors related to AFP measurement | ||||
| No limitation | 240 (45.2%) | 26 (19.4%) | 214 (53.9%) | <.001 |
| Unavailable AFP test | 128 (24.1%) | 97 (72.4%) | 31 (7.8%) | <.001 |
| Financial concerns | 89 (16.8%) | 28 (20.9%) | 61 (15.4%) | .878 |
P < .05 is significant by the t test.
AFP = alpha-fetoprotein, HCC = hepatocellular carcinoma, US = ultrasound.
P value is the difference between community hospital and secondary and tertiary hospital.
3.1.2. Patient’s perspectives.
A total of 79.3% of patients completed the questionnaire (303 out of 382). It should be highlighted that only 92 (30.3%) patients were undergoing optimal HCC surveillance, and 211 (69.6%) patients had suboptimal surveillance. All baseline characteristics including age, gender, educational level, income, HCC risk, medical specialty of healthcare providers, and knowledge about HCC showed no significant differences between the 2 groups (Table 3). Patient barriers to HCC surveillance included a lack of surveillance prescription from physicians, long appointment intervals, failure to recall the appointment, long distances from home to a hospital, inequality of health insurance status, transportation difficulty, and the cost of surveillance test (Table S2, Supplemental Digital Content 4, http://links.lww.com/MD/H306). In comparison between those receiving optimal and suboptimal surveillance, the lack of US prescription from physicians was the only factor showing a significant association with suboptimal surveillance with an odds ratio (95% CI) of 1.4 (1.1–1.8), P = .024 (Table 4).
Table 3.
Baseline characteristics of high-risk HCC patients.
| Variables | Optimal surveillance (n = 92, 30.3%) | Suboptimal surveillance (n = 211, 69.6%) | P |
|---|---|---|---|
| Age, mean ± SD (yr) | 57.4 ± 9.8 | 55.4 ± 11.9 | .170 |
| Male gender | 50 (54.9%) | 41 (45.1%) | .374 |
| Education level | .514 | ||
| Low (primary school or under) | 48 (52.2%) | 99 (46.9%) | |
| Medium to high (secondary school or higher) | 44 (47.8%) | 112 (53.1%) | |
| Income (low vs medium to high) | .363 | ||
| Low (<330 US dollars per month) | 18 (19.6%) | 51 (24.2%) | |
| Medium to high (>330 US dollars per month) | 74 (80.4%) | 160 (75.8%) | |
| Types of medical coverage and insurance | .122 | ||
| Universal coverage | 25 (27.2%) | 63 (29.9%) | |
| Government/state enterprise officer | 46 (51.1%) | 90 (43.1%) | |
| Social security | 11 (12.0%) | 35 (16.6%) | |
| Self-payment | 7 (7.8%) | 21 (10.0%) | |
| Monitoring indications | |||
| Cirrhosis | 75 (81.5%) | 182 (86.3%) | .428 |
| Non-cirrhosis, high-risk | 17 (18.5%) | 29 (13.7%) | .387 |
| Knowledge score (min = 0, max = 100), mean ± SD | |||
| Total score | 41.9 + 13.7 | 41.2 + 14.8 | .680 |
| Risk of HCC | 53.9 + 24.1 | 53.0 + 24.5 | .773 |
| Prognosis of HCC | 48.9 + 26.3 | 48.2 + 30.5 | .854 |
| Optimal tool and interval for surveillance | 37.3 + 14.7 | 36.2 + 15.1 | .614 |
α < 0.05 is significant by Chi-square test for knowledge score.
P < .05 is significant by unpaired t test for other parameters.
HCC = hepatocellular carcinoma, SD = standard deviation, US = United States of America.
Table 4.
Factors associated with suboptimal surveillance by patient’s perspective.
| Variables | OR (95% CI) | P |
|---|---|---|
| Patient demographics | ||
| Female gender (reference: male gender) | 0.8 (0.5–1.3) | .354 |
| Age (per yr) | 1.0 (0.96–1.01) | .170 |
| Low education level (reference: medium to high) | 0.8 (0.5–1.4) | .451 |
| Low monthly income (reference: medium to high) | 1.4 (0.7–2.5) | .328 |
| Types of medical coverage and insurance (self-payment vs reimbursable*) | 1.3 (0. 5–3.2) | .538 |
| Patient knowledge (do not know vs know) | ||
| Risk of HCC | 1.0 (0.99–1.01) | .772 |
| Natural history and burden of HCC | 1.0 (0.99–1.01) | .853 |
| HCC surveillance guidelines | 1.0 (0.98–1.01) | .613 |
| Attitude to HCC surveillance (do not know vs know) | ||
| Knowing HCC surveillance guidelines was important for early HCC detection | 0.8 (0.3–1.9) | .585 |
| Responders had a high risk of developing HCC | 0.9 (0.6–1.4) | .714 |
| Responders were at risk of death from HCC | 1.0 (0.7–1.5) | .829 |
| US and AFP are beneficial tools for detecting early HCC | 0.6 (0.3–1.2) | .151 |
| Responders received sufficient knowledge and advice about HCC surveillance from physicians | 1.1 (0.7–1.6) | .750 |
| Major surveillance barriers (yes vs no) | ||
| Lack of surveillance prescription from physicians | 1.4 (1.1–1.8) | .024 |
| Non-gastroenterologist was a care provider | 1.0 (0.9–1.1) | .465 |
| Surveillance indication (cirrhosis vs non-cirrhosis) | 1.0 (1.0–1.0) | .263 |
| Patient lived too far from hospital | 1.0 (0.8–1.4) | .839 |
| Forget surveillance schedule | 1.1 (0.8–1.6) | .466 |
| Long waiting time for doctor visit and surveillance | 0.9 (0.7–1.2) | .426 |
| No caregiver to assist with visiting hospital | 0.9 (0.6–1.3) | .567 |
| Financial concern | 1.1 (0.8–1.5) | .706 |
| Healthcare re-imbursement and referral system | 1.1 (0.8–1.6) | .650 |
P < .05 is significant by logistic regression analysis.
AFP = alpha-fetoprotein, CI = confidence interval, HCC = hepatocellular carcinoma, US = ultrasound.
Reimbursable by universal coverage, government or state enterprise officer, social security.
3.2. Phase 2: improving physicians’ knowledge on HCC surveillance with brief educational intervention
Of the 143 internal medicine residents, response rates before and after delivery of the brief educational intervention were 67.8% (n = 97) and 75.5% (n = 108), respectively. Baseline characteristics are shown in Table S3, Supplemental Digital Content 5, http://links.lww.com/MD/H307. Mean + SD age was 28 + 4 years. Pre-education analysis (Table 1) showed that 61 (63.0%) residents self-reported awareness of the HCC surveillance guidelines, with 90 (93.0%) remembering cirrhosis as a surveillance indication, and 40.0% to 55.0% of residents correctly identified surveillance indications for non-cirrhosis patients. Only 42.0% and 44.0% of residents correctly chose the surveillance tools and intervals, respectively. Data from the 5 cases-based scenarios showed correct response rates before giving education ranging from 22.0% to 38.0% (Pre-education in Phase 2, Table 1).
After delivering the brief educational intervention via social networks, we confirmed that all participants had read the card. Correct response rates increased in all domains, especially for the indications for HCC surveillance in chronic HBV non-cirrhosis patients (40.0% vs 63.0% at pre- and post-education, respectively, P = .001). The percentage of correct responses of all case-based surveillance scenario significantly increased after education (Table 1). Knowledge area regarding surveillance indication for HBV non-cirrhosis and surveillance tools statistically improved between pre- and post-education. After the educational intervention, most residents (n = 85, 78.7%) strongly disagreed that HCC surveillance increased their workload (Table S4, Supplemental Digital Content 6, http://links.lww.com/MD/H308).
4. Discussion
In this study, we found that more than half of physicians failed to suggest proper surveillance to patients at risk for HCC. This stemmed from insufficient knowledge regarding indication, tool, and interval for HCC surveillance. From patients’ perspective, a lack of US prescriptions from physicians was significantly associated with suboptimal surveillance.
We hypothesized that patients’ perspective of inadequate US prescription was most likely related to insufficient physicians’ knowledge. This was supported by the finding from a previous study reporting that physicians’ knowledge deficit regarding the clinical indications may indicate as a reason for the lack of US prescription.[9] This observation was consistently reported in several studies,[9–13] suggesting that physician knowledge of HCC screening guidelines was the most important factor to proper HCC surveillance. Regarding the physicians’ attitude toward HCC surveillance, most physicians believed that the surveillance was a responsibility shared by all healthcare providers regardless of medical specialty and hospital limitations. They also agreed that surveillance was cost-effective and did not increase their workload. These positive attitudes of physicians toward HCC surveillance were also observed in a previous study.[14] Interestingly, a minority of physicians responded that they had been influenced by patients’ history of heavy alcohol and were less likely to offer HCC surveillance for alcoholic patients. However, their responses do not reflect their decisions in real clinical practice.
Resource availability also played an important role as a barrier to HCC surveillance. A previous study showed that inadequate resources were identified as potential barriers to surveillance even in high income countries.[15] We found that almost half of physicians reported having limited access to US machines, especially in community hospitals. Due to that limitation, physicians might need to use US machines as diagnostic tools for symptomatic patients, rather than as screening and surveillance tools for asymptomatic patients. Our finding was in line with a finding from a previous research reporting that inadequate US training programs were a potential barrier to proper usage of US for HCC surveillance in developing countries.[16] Additionally, we found that the AFP test was unavailable in 72.4% of community hospitals. This high unavailability rate might be due to the outweighed benefits and versatility of the US machine compared to the AFP test. Due to resource limitation, surveillance might still be difficult to achieve despite sufficient physicians’ knowledge and proactive attitudes toward surveillance, and these were also documented as barriers in many other countries with limited resources.[17] One of the possible causes of inadequate healthcare resources might be due to insufficient healthcare fundings. It was shown that low- and middle-income countries distributed smaller funds to healthcare expenditures than high-income countries.[18] Moreover, inadequate resources might be resource allocation.[19] Using the mathematical formulas for distributing healthcare budgets impartially could potentially alleviate this issue.[18] Accordingly, the issue for US shortage in some hospitals could potentially be solved by offering more financial fundings and effective resource allocation formulae.
Financial concerns were not a significant barrier to surveillance from both patients’ and physicians’ perspective, indicating that patients’ socioeconomic status was not the main contributor to surveillance inaccessibility in the Thai population. In Thailand, the universal medical coverage scheme supports HCC surveillance programs for all patients with high-risk liver diseases, which relieves most of patients’ financial concerns.[20] Unlike those observed in some countries, such as the United States, financial constraints and the type of health insurance system were reported to be significant barriers to HCC surveillance.[11,14,21] For example, costs of surveillance testing was found to be one of the most common patient-reported barriers to HCC surveillance.[21] These inconsistent findings could possibly be explained by differences in healthcare system and the type of patients’ health insurance in different countries.[14,21] This explanation was supported by a study from Switzerland showing patients with private health insurance typically were more likely to undergo HCC surveillance.[22] Likewise, in the United States, patients who had stable health insurance reported less financial concern.[23] These findings highlighted the critical role of health coverage in increasing the rate of HCC surveillance.
Consistent with prior studies, the findings from Phase 2 of this study indicated that educating physicians using a brief social network-based intervention was an effective strategy to enhance knowledge regarding HCC surveillance.[9,24] Interestingly, many physicians from other surveys responded that guidelines were inconvenient and difficult to follow[25,26] and one of physician barriers to appropriate guideline adherence was not being up-to-date on the guideline recommendations.[10,27] This signified the importance of developing a simple and concise educational intervention that can quickly remind physicians about the updated guideline recommendations.
There are several strengths in this study. First, we assessed both physicians’ and patients’ perspectives. Recruited participants were physicians from various fields and medical facilities working at all hospital levels from all around country. Participants can therefore be viewed as representative of Thai physicians who implement the national HCC guidelines.[28] Their responses can be beneficial to policy makers who set national healthcare budgets and surveillance programs. Most previous studies were performed in the Western countries with high income,[11,14,21,23,29,30] while our study took place in a country which is a representative of a developing country with middle income in Asia-Pacific region. Our findings might be generalizable to other countries with a similar development background and income status, especially those that provide national health coverage.
The study has some limitations. First, survey studies are inherently confounded by response bias. The questionnaires were based on findings from previous studies that used closed-ended questions, in which some potential barriers might not be included. To overcome this drawback, open-ended questions will be included in the future surveys. Physicians in our study may have answered questions regarding how they should practice, instead of their real clinical routine. Regarding the education intervention, we did not check the frequency that participants reviewed the cards before performing the post-test. The unequal frequency of card review among participants might vary the efficacy of the card, and hence affect each physician’s post-test performance. Despite that limitation, the overall performance on knowledge about HCC surveillance enhanced. To determine whether implementing physician education on HCC guidelines is an efficient strategy in improving HCC surveillance, US prescription rate and early HCC detection rate in real clinical settings after education needs to be further investigated.
5. Conclusions
Gap in physicians’ knowledge is a major barrier to HCC surveillance, which leads to inadequate US prescription in high risk HCC patients. Knowledge card is an effective method to improve physician understanding and recognition of surveillance recommendations.
Author contributions
TT performed statistical analysis and data interpretation, and drafted the manuscript; YS designed instruments and collected data in phase 1 of the study; DA and KK performed statistical analysis and revised manuscript; PP and PP designed instruments and collected data in phase 2 of the study; CP assisted with statistical analysis; PT, ST and RR provided oversight for the study, performed critical revisions of the important intellectual content, and obtained study funding; RC designed and supervised the study, performed data interpretation and critical revisions of the important intellectual content. All authors have read and approved the final manuscript.
Conceptualization: Tongluk Teerasarntipan, Yingluk Sritunyarat, Parinda Prathyajuta, Palada Pitakkitnukun, Pisit Tangkijvanich, Sombat Treeprasertsuk, Rungsun Rerknimitr, Roongruedee Chaiteerakij.
Data curation: Yingluk Sritunyarat, Parinda Prathyajuta, Palada Pitakkitnukun.
Formal analysis: Tongluk Teerasarntipan, Chonlada Phathong, Darlene Ariyaskul, Kittipat Kulkraisri, Roongruedee Chaiteerakij.
Funding acquisition: Roongruedee Chaiteerakij.
Methodology: Roongruedee Chaiteerakij.
Validation: Darlene Ariyaskul, Kittipat Kulkraisri.
Writing – original draft: Tongluk Teerasarntipan.
Writing – review & editing: Darlene Ariyaskul, Kittipat Kulkraisri, Pisit Tangkijvanich, Sombat Treeprasertsuk, Rungsun Rerknimitr, Roongruedee Chaiteerakij.
Acknowledgments
Authors thank the research team of the Department of Medicine, Faculty of Medicine, Chulalongkorn University for editing the final manuscript.
Supplementary Material
Abbreviations:
- AFP =
- alpha-fetoprotein
- GP =
- general practitioner
- HBV =
- hepatitis B virus
- HCC =
- hepatocellular carcinoma
- SD =
- standard deviation
- US =
- ultrasound
This research is funded by Chulalongkorn University (grant number CU-GRS-62-02-30-01). Funder has no role in study design; the collection, analysis, and interpretation of data; in the writing of the report; and in the decision to submit the article for publication.
The authors have no conflicts of interest to disclose.
The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.
Supplemental Digital Content is available for this article.
How to cite this article: Teerasarntipan T, Sritunyarat Y, Prathyajuta P, Pitakkitnukun P, Phathong C, Ariyaskul D, Kulkraisri K, Tangkijvanich P, Treeprasertsuk S, Rerknimitr R, Chaiteerakij R. Physician- and patient-reported barriers to hepatocellular carcinoma surveillance: A nationwide survey. Medicine 2022;101:36(e30538).
Contributor Information
Tongluk Teerasarntipan, Email: kulgnotb@hotmail.com.
Yingluk Sritunyarat, Email: som-o_ys@hotmail.com.
Parinda Prathyajuta, Email: parindaprathyajuta@gmail.com.
Palada Pitakkitnukun, Email: paladapitakkitnukun@docchula.com.
Chonlada Phathong, Email: chonlada.pha@gmail.com.
Darlene Ariyaskul, Email: dariyaskul@docchula.com.
Kittipat Kulkraisri, Email: kittipatkulkraisri@docchula.com.
Pisit Tangkijvanich, Email: pisittkvn@yahoo.com.
Sombat Treeprasertsuk, Email: battan5410@gmail.com.
Rungsun Rerknimitr, Email: ercp@live.com.
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