Dataset Information

Analysis of seasonal variation of antibiotic prescribing for respiratory tract diagnoses in primary care practices.

ABSTRACT:

Objective

To determine antibiotic prescribing appropriateness for respiratory tract diagnoses (RTD) by season.

Design

Retrospective cohort study.

Setting

Primary care practices in a university health system.

Patients

Patients who were seen at an office visit with diagnostic code for RTD.

Methods

Office visits for the entire cohort were categorized based on ICD-10 codes by the likelihood that an antibiotic was indicated (tier 1: always indicated; tier 2: sometimes indicated; tier 3: rarely indicated). Medical records were reviewed for 1,200 randomly selected office visits to determine appropriateness. Based on this reference standard, metrics and prescriber characteristics associated with inappropriate antibiotic prescribing were determined. Characteristics of antibiotic prescribing were compared between winter and summer months.

Results

A significantly greater proportion of RTD visits had an antibiotic prescribed in winter [20,558/51,090 (40.2%)] compared to summer months [11,728/38,537 (30.4%)][standardized difference (SD) = 0.21]. A significantly greater proportion of winter compared to summer visits was associated with tier 2 RTDs (29.4% vs 23.4%, SD = 0.14), but less tier 3 RTDs (68.4% vs 74.4%, SD = 0.13). A greater proportion of visits in winter compared to summer months had an antibiotic prescribed for tier 2 RTDs (80.2% vs 74.2%, SD = 0.14) and tier 3 RTDs (22.9% vs 16.2%, SD = 0.17). The proportion of inappropriate antibiotic prescribing was higher in winter compared to summer months (72.4% vs 62.0%, P < .01).

Conclusions

Increases in antibiotic prescribing for RTD visits from summer to winter were likely driven by shifts in diagnoses as well as increases in prescribing for certain diagnoses. At least some of this increased prescribing was inappropriate.

SUBMITTER: Serletti L

PROVIDER: S-EPMC10523546 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature

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Publications

Analysis of seasonal variation of antibiotic prescribing for respiratory tract diagnoses in primary care practices.

Serletti Lacey L Dutcher Lauren L Degnan Kathleen O KO Szymczak Julia E JE Cluzet Valerie V David Michael Z MZ Cressman Leigh L Glassman Lindsay W LW Hamilton Keith W KW

Antimicrobial stewardship & healthcare epidemiology : ASHE 20230905 1

<h4>Objective</h4>To determine antibiotic prescribing appropriateness for respiratory tract diagnoses (RTD) by season.<h4>Design</h4>Retrospective cohort study.<h4>Setting</h4>Primary care practices in a university health system.<h4>Patients</h4>Patients who were seen at an office visit with diagnostic code for RTD.<h4>Methods</h4>Office visits for the entire cohort were categorized based on ICD-10 codes by the likelihood that an antibiotic was indicated (tier 1: always indicated; tier 2: someti ...[more]

PMID: 37771744

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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.

Project description:ObjectivesInappropriate antibiotic use for respiratory tract infection (RTI) is an ongoing problem linked to the emergence of drug resistance and other adverse effects. Less is known about the prescribing practices of individual physicians or the impact of physician prescribing habits on patient outcomes. We studied the prescribing practices of providers for acute RTIs in an integrated health system, identified patient factors associated with receipt of an antibiotic and assessed the relation between providers' adjusted prescribing rates and a number of patient outcomes.MethodsThis was a retrospective analysis of adults with an RTI visit to any primary care providers across the Cleveland Clinic Health System in 2011-2012. Patients with a history of chronic obstructive pulmonary disease or immunocompromised status were excluded. Logistic regression was used to examine patient factors associated with receipt of an antibiotic.ResultsOf 31,416 patients with an RTI, 54.8% received an antibiotic. Patient factors associated with antibiotic prescribing included white race (odds ratio [OR] 1.35, P < 0.001), presence of fever (OR 1.66, P < 0.001), and a diagnosis of bronchitis (OR 10.98, P < 0.001) or sinusitis (OR 33.85, P < 0.001). Among 290 providers with ≥10 RTI visits, adjusted antibiotic prescribing rates ranged from 0% to 100% (mean 49%). Antibiotics were prescribed more often for sinusitis (OR 33.85, P < 0.001), bronchitis (OR 10.98, P < 0.001), or pharyngitis (OR 1.76, P < 0.001) compared with upper respiratory tract infection. Patients who were prescribed antibiotics at the index visit were more likely to return for RTI within 1 year (adjusted OR 1.26, P < 0.001). Emergency department visits for respiratory complications were rare and not associated with antibiotic receipt.ConclusionsAntibiotic prescribing for RTI varies widely among physicians and cannot be explained by patient factors. Patients prescribed antibiotics for RTI were more likely to return for RTI.

Project description:ObjectiveTo estimate the effectiveness of different strategies involving delayed antibiotic prescription for acute respiratory tract infections.DesignOpen, pragmatic, parallel group, factorial, randomised controlled trial.SettingPrimary care in the United Kingdom.Patients889 patients aged 3 years and over with acute respiratory tract infection, recruited between 3 March 2010 and 28 March 2012 by 53 health professionals in 25 practices.InterventionsPatients judged not to need immediate antibiotics were randomised to undergo four strategies of delayed prescription: recontact for a prescription, post-dated prescription, collection of the prescription, and be given the prescription (patient led). During the trial, a strategy of no antibiotic prescription was added as another randomised comparison. Analysis was intention to treat.Main outcome measuresMean symptom severity (0-6 scale) at days 2-4 (primary outcome), antibiotic use, and patients' beliefs in the effectiveness of antibiotic use. Secondary analysis included comparison with immediate use of antibiotics.ResultsMean symptom severity had minimal differences between the strategies involving no prescription and delayed prescription (recontact, post-date, collection, patient led; 1.62, 1.60, 1.82, 1.68, 1.75, respectively; likelihood ratio test χ(2) 2.61, P=0.625). Duration of symptoms rated moderately bad or worse also did not differ between no prescription and delayed prescription strategies combined (median 3 days v 4 days; 4.29, P=0.368). There were modest and non-significant differences in patients very satisfied with the consultation between the randomised groups (79%, 74%, 80%, 88%, 89%, respectively; likelihood ratio test χ(2) 2.38, P=0.667), belief in antibiotics (71%, 74%, 73%, 72%, 66%; 1.62, P=0.805), or antibiotic use (26%, 37%, 37%, 33%, 39%; 4.96, P=0.292). By contrast, most patients given immediate antibiotics used antibiotics (97%) and strongly believed in them (93%), but with no benefit for symptom severity (score 1.76) or duration (median 4 days).ConclusionStrategies of no prescription or delayed antibiotic prescription result in fewer than 40% of patients using antibiotics, and are associated with less strong beliefs in antibiotics, and similar symptomatic outcomes to immediate prescription. If clear advice is given to patients, there is probably little to choose between the different strategies of delayed prescription.Trial registrationISRCTN38551726.

Project description:ObjectivesThere is variation in antibiotic prescribing for lower respiratory tract infections (LRTI) in primary care that does not benefit patients. This study aims to investigate clinicians' accounts of clinical influences on antibiotic prescribing decisions for LRTI to better understand variation and identify opportunities for improvement.DesignMulti country qualitative interview study. Semi-structured interviews using open-ended questions and a patient scenario. Data were subjected to five-stage analytic framework approach (familiarisation, developing a thematic framework from the interview questions and emerging themes, indexing, charting and mapping to search for interpretations), with interviewers commenting on preliminary reports.SettingPrimary care.Participants80 primary care clinicians randomly selected from primary care research networks based in nine European cities.ResultsClinicians reported four main individual clinical factors that guided their antibiotic prescribing decision: auscultation, fever, discoloured sputum and breathlessness. These were considered alongside a general impression of the patient derived from building a picture of the illness course, using intuition and familiarity with the patient. Comorbidity and older age were considered main risk factors for poor outcomes. Clinical factors were similar across networks, apart from C reactive protein near patient testing in Tromsø. Clinicians developed ways to handle diagnostic and management uncertainty through their own clinical routines.ConclusionsClinicians emphasised the importance of auscultation, fever, discoloured sputum and breathlessness, general impression of the illness course, familiarity with the patient, comorbidity, and age in informing their antibiotic prescribing decisions for LRTI. As some of these factors may be overemphasised given the evolving evidence base, greater standardisation of assessment and integration of findings may help reduce unhelpful variation in management. Non-clinical influences will also need to be addressed.

Project description:BackgroundThe emergence and increased spread of microbial resistance is a major challenge to all health care systems worldwide. In primary care, acute respiratory tract infection (ARTI) is the health condition most strongly related to antibiotic overuse.ObjectiveThe RESIST program aims at optimizing antibiotic prescribing for ARTI in German primary care. By completing a problem-orientated online training course, physicians are motivated and empowered to utilize patient-centered doctor-patient communication strategies, including shared decision making, in the treatment of patients with ARTI.MethodsRESIST will be evaluated in the form of a nonrandomized controlled trial. Approximately 3000 physicians of 8 (out of 16) German federal states can participate in the program. Patient and physician data are retrieved from routine health care data. Physicians not participating in the program serve as controls, either among the 8 participating regional Associations of Statutory Health Insurance Physicians (control group 1) or among the remaining associations not participating in RESIST (control group 2). Antibiotic prescription rates before the intervention (T0: 2016, 1st and 2nd quarters of 2017) and after the intervention (T1: 3rd quarter of 2017 until 1st quarter of 2019) will be compared. The primary outcome measure is the overall antibiotic prescription rate for all patients insured with German statutory health insurance before and after provision of the online course. The secondary outcome is the antibiotic prescription rate for coded ARTI before and after the intervention.ResultsRESIST is publicly funded by the Innovations funds of the Federal Joint Committee in Germany and was approved in December 2016. Recruitment of physicians is now completed, and a total of 2460 physicians participated in the intervention. Data analysis started in February 2020.ConclusionsWith approximately 3000 physicians participating in the program, RESIST is among the largest real-world interventions aiming at reducing inadequate antibiotic prescribing for ARTI in primary care. Long-term follow up of up to 21 months will allow for investigating the sustainability of the intervention.Trial registrationISRCTN Registry ISRCTN13934505; http://www.isrctn.com/ISRCTN13934505.International registered report identifier (irrid)RR1-10.2196/18648.

Dataset Information

Analysis of seasonal variation of antibiotic prescribing for respiratory tract diagnoses in primary care practices.

Objective

Design

Setting

Patients

Methods

Results

Conclusions

Publications

Analysis of seasonal variation of antibiotic prescribing for respiratory tract diagnoses in primary care practices.

Similar Datasets

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