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Coping With Diagnostic Uncertainty in Antibiotic Prescribing: A Latent Class Study of Primary Care Physicians in Hubei China.

ABSTRACT: Background: Misuse of antibiotics is prevalent worldwide and primary care is a major contributor. Although a clear diagnosis is fundamental for rational antibiotic use, primary care physicians often struggle with diagnostic uncertainty. However, we know little about how physicians cope with this situation and its association with antibiotic prescribing. Methods: A total of 583 primary care physicians were surveyed using the Dealing with Uncertainty Questionnaire. Their prescriptions (n = 949,181) over the year 2018 were retrieved retrospectively. Two categories of behavioral patterns of participants were identified based on latent class analyses (high vs. low openness and collaborativeness) in responding to diagnostic uncertainty. Multi-level logistic regression models were established to determine the associations between these behavioral patterns and antibiotic prescribing (overall and broad-spectrum antibiotics) for illness without an indication for antibiotics and those with a conditional indication for antibiotics, respectively, after adjustment for variations of patient (level one) and physician (level two) characteristics. Results: Most physicians reported open communications with their patients (80.96%), collected further information (85.08%), and referred patients to specialists (68.95%) in dealing with diagnostic uncertainly. More than half (56.95%) sought help from colleagues. Less than 20% acted on intuition or adopted a "wait and see" strategy. About 40% participants (n = 238) were classified into the group of low openness and collaborativeness in coping with diagnostic uncertainty. They were more likely to prescribe antibiotics for the recorded illness without an indication for antibiotics (AOR = 1.013 for all antibiotics, p = 0.024; AOR = 1.047 for broad-spectrum antibiotics, p < 0.001), as well as for the recorded illness with a conditional indication for antibiotics (AOR = 1.226 for all antibiotic, p < 0.001; AOR = 1.257 for broad-spectrum antibiotics, p < 0.001). Conclusion: Low tolerance with diagnostic uncertainty is evident in primary care. Inappropriate and over antibiotic prescribing is shaped by physicians' coping methods of diagnostic uncertainty. Physicians' openness and collaborativeness in responding to diagnostic uncertainty is associated with lower antibiotic prescribing in primary care. Interventions targeting on better management of diagnostic uncertainty may offer a promising approach in reducing antibiotic use in primary care.

SUBMITTER: Liu C

PROVIDER: S-EPMC8695689 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Background:Over-prescription of antibiotics is prevalent all over the world, contributing to the development of antibiotic resistance. The importance of understanding how physicians prescribe antibiotics is increasingly highlighted for the purpose of promoting good practice. This study aimed to identify factors that shape the antibiotic prescribing behaviors of physicians in primary care based on the theory of planned behavior (TPB). Methods:Data were collected from 503 prescribers within 65 primary care facilities in Hubei, tapping into four behavioral aspects leading to antibiotic prescribing based on TPB, namely, attitudes (the degree to which a prescriber is in favor of the use of antibiotics), subjective norms (perceived social pressure to which a prescriber is subject in relation to antibiotic prescriptions), perceived control of behaviors (how easy a prescriber feels in making a rational decision on antibiotic prescriptions) and intentions (the degree to which a prescriber is willing to prescribe antibiotics). A total of 440,268 prescriptions were audited to assess physician antibiotic prescribing practices. The four behavioral constructs were further linked with physician's actual use of antibiotics using structural equation modelling (SEM) based on TPB. Results:On average, 40.54% (SD = 20.82%) of the outpatient encounters resulted in a prescription for an antibiotic given by the participants and 9.81% (SD = 10.18%) of the patients were given two or more antibiotics. The participants showing a more favorable attitude toward antibiotics had a higher intention to prescribe antibiotics (β = 0.226, p < 0.001) and a lower intention to reduce antibiotic use (β = - 0.211, p < 0.001). Those who perceived lower social pressure (β = 0.113, p = 0.030) and higher control over prescribing behaviors (β = 0.113, p = 0.037) reported a higher intention to reduce the use of antibiotics. However, such intention did not translate into prescribing practice (p > 0.05), although stronger perceived behavioral control was directly linked with lower antibiotic prescriptions (β = - 0.110, p = 0.019). Weaker perceived behavioral control was evident in the participants who showed a less favorable attitude toward antibiotics (β = 0.128, p = 0.001). Conclusion:Antibiotic prescribing practice is not under the volitional control of prescribers in primary care in China. Their rational prescribing practice is likely to be jeopardized by perceived weak control over prescribing behaviors.

Project description:BackgroundBenzodiazepines, opioids, proton-pump inhibitors (PPIs), and antibiotics are frequently prescribed inappropriately by primary care physicians (PCPs), without sufficient consideration of alternative options or adverse effects. We hypothesized that distinct groups of PCPs could be identified based on their propensity to prescribe these medications.ObjectiveTo identify PCP groups based on their propensity to prescribe benzodiazepines, opioids, PPIs, and antibiotics, and patient and PCP characteristics associated with identified prescribing patterns.DesignRetrospective cohort study using VA data and latent class regression analyses to identify prescribing patterns among PCPs and examine the association of patient and PCP characteristics with class membership.ParticipantsA total of 2524 full-time PCPs and their patient panels (n = 2,939,636 patients), from January 1, 2017, to December 31, 2018.Main measuresWe categorized PCPs based on prescribing volume quartiles for the four drug classes, based on total days' supply dispensed of each medication by the PCP to their patients (expressed as days' supply per 1000 panel patient-days). We used latent class analysis to group PCPs based on prescribing and used multinomial logistic regression to examine patient and PCP characteristics associated with latent class membership.Key resultsPCPs were categorized into four groups (latent classes): low intensity (23% of cohort), medium-intensity overall/high-intensity PPI (36%), medium-intensity overall/high-intensity opioid (20%), and high intensity (21%). PCPs in the high-intensity group were predominantly in the highest quartile of prescribers for all four drugs (68% in the highest quartile for benzodiazepine, 86% opioids, 64% PPIs, 62% antibiotics). High-intensity PCPs (vs. low intensity) were substantially less likely to be female (OR: 0.30, 95% CI: 0.21-0.42) or practice in the northeast versus other census regions (OR: 0.10, 95% CI: 0.06-0.17).ConclusionsVA PCPs can be classified into four clearly differentiated groups based on their prescribing of benzodiazepines, opioids, PPIs, and antibiotics, suggesting an underlying typology of prescribing. High-intensity PCPs were more likely to be male.

Project description:Background: Overuse of antibiotics significantly fuels the development of Antimicrobial resistance, which threating the global population health. Great variations existed in antibiotic prescribing practices among physicians, indicating improvement potential for rational use of antibiotics. This study aims to identify antibiotic prescribing patterns of primary care physicians and potential determinants. Methods: A cross-sectional survey was conducted on 551 physicians from 67 primary care facilities in Hubei selected through random cluster sampling, tapping into their knowledge, attitudes and prescribing practices toward antibiotics. Prescriptions (n = 501,072) made by the participants from 1 January to March 31, 2018 were extracted from the medical records system. Seven indicators were calculated for each prescriber: average number of medicines per prescription, average number of antibiotics per prescription, percentage of prescriptions containing antibiotics, percentage of antibiotic prescriptions containing broad-spectrum antibiotics, percentage of antibiotic prescriptions containing parenteral administered antibiotics, percentage of antibiotic prescriptions containing restricted antibiotics, and percentage of antibiotic prescriptions containing antibiotics included in the WHO "Watch and Reserve" list. Two-level latent profile analyses were performed to identify the antibiotic prescribing patterns of physicians based on those indicators. Multi-nominal logistic regression models were established to identify determinants with the antibiotic prescribing patterns. Results: On average, each primary care physician issued 909 (ranging from 100 to 11,941 with a median of 474) prescriptions over the study period. The mean percentage of prescriptions containing antibiotics issued by the physicians reached 52.19% (SD = 17.20%). Of those antibiotic prescriptions, an average of 82.29% (SD = 15.83%) contained broad-spectrum antibiotics; 71.92% (SD = 21.42%) contained parenteral administered antibiotics; 23.52% (SD = 19.12%) contained antibiotics restricted by the regional government; and 67.74% (SD = 20.98%) contained antibiotics listed in the WHO "Watch and Reserve" list. About 28.49% of the prescribers were identified as low antibiotic users, compared with 51.18% medium users and 20.33% high users. Higher use of antibiotics was associated with insufficient knowledge, indifference to changes, complacency with satisfied patients, low household income and rural location of the prescribers. Conclusion: Great variation in antibiotic prescribing patterns exists among primary care physicians in Hubei of China. High use of antibiotics is not only associated with knowledge shortfalls but also low socioeconomic status of prescribers.

Project description:Background:Irrational use of antibiotics is a major driver of development of antibiotic resistance, which heavily threatens population health worldwide. Understanding the mechanism of physician's antibiotic prescribing decisions is increasingly highlighted to promote prudent use of antibiotics. Therefore, the current study aimed to fill the gap, modelling physician's antibiotic prescribing and identifying the potential intrinsic and external determinants of antibiotic prescribing in primary care. Methods:A total of 428,475 prescriptions from 499 prescribers in 65 primary care facilities in Hubei of China were audited. Teixeira Antibiotic Prescribing Behavioral Model (TAPBM) was referred as theoretical basis to identify intrinsic and external predictors of antibiotic prescriptions. A questionnaire survey was conducted, covering potential physician's intrinsic determinants (knowledge, attitudes and individual characteristics) and external factors both in individual level (patient pressure, time pressure and financial incentives) and institutional level (setting and local socio-economic development). A two-level path analysis was performed linking potential determinants of antibiotic use with physician's actual practices. Results:About 44.28% of the prescriptions contained antibiotics, with 9.28% containing two or more antibiotics. The multi-level path analysis revealed that knowledge was a significant predictor of attitudes (??=?0.154, p?<?0.05), but higher knowledge and attitudes failed to translate into antibiotic prescribing practices ((??=?-?0.076 - 0.039, p?>?0.05). Instead, external factors played a more important role and physician's antibiotic use was significantly associated with patient pressure (??=?0.102, p?=?0.022), time pressure (??=?-?0.164, p?=?0.002), financial incentives (??=?-?0.133- -?0.155, p?=?0.027) and institutional environments (rural area, ??=?0.408, p?=?0.002; and high socioeconomic setting, ??=?-?0.641 - -0.578, p?< 0.001?). The prescribers who were male (??=?-?0.168, p?=?0.007) or had lower qualification (??=?-?0.114, p?=?0.028) were also more likely to prescribe antibiotics than others. Conclusion:Antibiotic prescribing practices are complex process and associated with both intrinsic (prescriber) and external (patients and institutional environment) factors. A systematic approach is required to curb over-prescription of antibiotics. Apart from educating prescribers, it is equally important, if not more, to educate patients, break incentives and nurture professional culture within organization to reduce the overuse of antibiotics.

Project description:BackgroundInappropriate use of antibiotics promotes antibiotic resistance. Little is known about physician characteristics that may be associated with inappropriate antibiotic prescribing. Our objective was to assess whether physician knowledge, time in practice, place of training and practice volume explain the differences in antibiotic prescribing among physicians.MethodsA historical cohort of 852 primary care physicians in Quebec who became certified between 1990 and 1993 was followed for their first 6-9 years of practice (1990-1998). We evaluated whether inappropriate antibiotic prescribing had occurred during the study period (1990-1998) for viral (prescription of antibiotics) and bacterial (prescription of second-or third-line antibiotics given orally) infections. We used logistic regression to estimate the independent contributions of time in practice, practice volume, place of medical training and scores on licensure examinations. Physician sex and visit setting were controlled for, as were patient age, sex, education, income and geographic area of residence.ResultsA total of 104 230 patients who received a diagnosis of a viral infection and 65 304 who received a diagnosis of a bacterial infection were included in our study. International medical graduates were more likely than University of Montréal graduates to prescribe antibiotics for viral respiratory infections (risk ratio [RR] 1.78, 95% confidence interval [CI] 1.30-2.44). Inappropriate antibiotic prescribing increased with time in practice. Physicians with a high practice volume were more likely than those with low practice volume to prescribe antibiotics for viral respiratory infections (RR 1.27, 95% CI 1.09-1.48) and to prescribe second-and third-line antibiotics as first-line treatment (RR 1.20, 95% CI 1.06-1.37). Physician scores on licensure examinations were not predictive of inappropriate antibiotic prescribing.InterpretationInternational medical graduates, physicians with high-volume practices and those who were in practice longer were more likely to prescribe antibiotics inappropriately. Developing effective interventions will require increased knowledge of the mechanisms that underlie these predictors of inappropriate antibiotic prescribing.

Project description:BackgroundUnnecessary antibiotic use is associated with adverse side effects and rising rates of resistance at the individual and population level. This study used a theory-informed approach to identify potentially modifiable determinants of antibiotic prescribing for patients presenting to primary care with upper respiratory tract infection symptoms.MethodsQualitative interviews were conducted with primary care physicians in Ontario, Canada who were identified as medium- or high-volume antibiotic prescribers (high volume defined as top 20th percentile versus "medium" defined as 40th to 60th percentile). The interview guide and analysis were informed by the Theoretical Domains Framework. Each interview was coded by two research team members. Sampling and analysis continued until thematic saturation was achieved.ResultsTwenty family physicians were interviewed. Physicians felt that many decisions about prescribing for upper respiratory tract infection symptoms were straightforward (i.e., black and white). However, intention to avoid prescribing in cases where an antibiotic was not indicated clinically did not always align with the provider action or expectation of the patient. Clinical decisions were influenced by the Theoretical Domain Framework domains that were both internal to the physician (Knowledge, Skills, Social/Professional Role, and Belief about Capabilities) and external to the physician (Social Influence, Belief about Consequences, Reinforcement, Emotions, and Behavioural Regulation). The Environmental Context and Resources played a key role. Physicians reported significant differences in their approach to antibiotic prescribing within episodic (walk-in) or continuity of care settings, as the presence (or not) of longitudinal physician-patient relationships seemed to moderate the role of these factors on the decision-making process in cases of uncertainty.ConclusionsAntibiotic prescribing in primary care is a complex decision-making process in which context may outweigh biology during encounters featuring clinical uncertainty. Differential skill in handling uncertainty and tactics used to operationalize guideline recommendations in the real world seems to contribute to observed variation in prescribing patterns, as much or more than differences in knowledge of best practices.

Project description:BackgroundThere has been a notable decrease in antibiotic prescribing in the last thirty years in Sweden. Little is known about factors influencing antibiotic prescribing over several years.ObjectiveTo compare primary care physicians who, over time, reduced their antibiotic prescribing for respiratory tract infections with those who remained either high or low prescribers regarding potentially influencing factors.Design and settingA register-based study including all RTI visits in primary care in Region Kronoberg, Sweden 2006-2014. The data were divided into three 3-year periods.SubjectsThe data comprised all physicians who had diagnosed at least one RTI for each of the three-year periods. The antibiotic prescribing rate adjusted for the patients' sex and age group was calculated for each physician and period, and based on the change between the first and the third period, the physicians were divided into three prescriber groups: The High Prescribing Group, the Decreasing Prescribing Group, and the Low Prescribing Group.Main outcome measuresFor the three prescriber groups, we compared factors influencing antibiotic prescribing such as the characteristics of the physicians, their use of point-of-care tests, their choice of diagnoses, and whether the patients returned and received antibiotics.ResultsThe High Prescribing Group ordered more point-of-care tests, registered more potential bacterial diagnoses, prescribed antibiotics at lower C-reactive protein levels, and prescribed antibiotics more often despite negative group A Streptococci test than in the Low Prescribing Group. The Decreasing Prescribing Group was between the High Prescribing Group and the Low Prescribing Group regarding these variables. The lower prescription rate in the Low Prescribing Group did not result in more return visits or new antibiotic prescriptions within 30 days.ConclusionPoint-of-care testing and its interpretation differed between the prescriber groups. Focus on interpreting point-of-care test results could be a way forward in antibiotic stewardship.

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Coping With Diagnostic Uncertainty in Antibiotic Prescribing: A Latent Class Study of Primary Care Physicians in Hubei China.

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