Dataset Information

Comparing Prescribing and Dispensing Data of the PCORnet Common Data Model Within PCORnet Antibiotics and Childhood Growth Study.

ABSTRACT: Researchers often use prescribing data from electronic health records (EHR) or dispensing data from medication or medical claims to determine medication utilization. However, neither source has complete information on medication use. We compared antibiotic prescribing and dispensing records for 200,395 patients in the National Patient-Centered Clinical Research Network (PCORnet) Antibiotics and Childhood Growth Study. We stratified analyses by delivery system type [closed integrated (cIDS) and non-cIDS]; 90.5 percent and 39.4 percent of prescribing records had matching dispensing records, and 92.7 percent and 64.0 percent of dispensing records had matching prescribing records at cIDS and non-cIDS, respectively. Most of the dispensings without a matching prescription did not have same-day encounters in the EHR, suggesting they were medications given outside the institution providing data, such as those from urgent care or retail clinics. The sensitivity of prescriptions in the EHR, using dispensings as a gold standard, was 99.1 percent and 89.9 percent for cIDS and non-cIDS, respectively. Only 0.7 percent and 6.1 percent of patients at cIDS and non-cIDS, respectively, were classified as false-negative, i.e. entirely unexposed to antibiotics when they in fact had dispensings. These patients were more likely to have a complex chronic condition or asthma. Overall, prescription records worked well to identify exposure to antibiotics. EHR data, such as the data available in PCORnet, is a unique and vital resource for clinical research. Closing data gaps by understanding why prescriptions may not be captured can improve this type of data, making it more robust for observational research.

SUBMITTER: Lin PD

PROVIDER: S-EPMC6460498 | biostudies-literature | 2019 Apr

REPOSITORIES: biostudies-literature

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Comparing Prescribing and Dispensing Data of the PCORnet Common Data Model Within PCORnet Antibiotics and Childhood Growth Study.

Lin Pi-I D PD Daley Matthew F MF Boone-Heinonen Janne J Rifas-Shiman Sheryl L SL Bailey L Charles LC Forrest Christopher B CB Horgan Casie E CE Sturtevant Jessica L JL Toh Sengwee S Young Jessica G JG Block Jason P JP

EGEMS (Washington, DC) 20190412 1

Researchers often use prescribing data from electronic health records (EHR) or dispensing data from medication or medical claims to determine medication utilization. However, neither source has complete information on medication use. We compared antibiotic prescribing and dispensing records for 200,395 patients in the National Patient-Centered Clinical Research Network (PCORnet) Antibiotics and Childhood Growth Study. We stratified analyses by delivery system type [closed integrated (cIDS) and n ...[more]

PMID: 30993145

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Project description:BackgroundMany physicians are experiencing increasing demands from both their patients and society. Evidence is scarce on the consequences of the pressure on physicians' decision making. We present a theoretical framework and predict that increasing pressure may make physicians disregard societal welfare when treating patients.SettingWe test our prediction on general practitioners' antibiotic-prescribing choices. Because prescribing broad-spectrum antibiotics does not require microbiological testing, it can be performed more quickly than prescribing for narrow-spectrum antibiotics and is therefore often preferred by the patient. In contrast, from a societal perspective, inappropriate prescribing of broad-spectrum antibiotics should be minimized as it may contribute to antimicrobial resistance in the general population.MethodsWe combine longitudinal survey data and administrative data from 2010 to 2017 to create a balanced panel of up to 1072 English general practitioners (GPs). Using a series of linear models with GP fixed effects, we estimate the importance of different sources of pressure for GPs' prescribing.ResultsWe find that the percentage of broad-spectrum antibiotics prescribed increases by 6.4% as pressure increases on English GPs. The link between pressure and prescribing holds for different sources of pressure.ConclusionsOur findings suggest that there may be societal costs of physicians working under pressure. Policy makers need to take these costs into account when evaluating existing policies as well as when introducing new policies affecting physicians' work pressure. An important avenue for further research is also to determine the underlying mechanisms related to the different sources of pressure.JEL-code: I11, J28, J45.HighlightsMany physicians are working under increasing pressure.We test the importance of pressure on physicians' prescribing of antibiotics.The prescribed rate of broad-spectrum antibiotics increases with pressure.Policy makers should be aware of the societal costs of pressured physicians.[Formula: see text].

Project description:Study objectiveHigh prescribers of antibiotics and opioids are an important target for stewardship interventions. The goal of this study was to assess the association between high antibiotic and high opioid prescribing by provider type.DesignA national cross-sectional study.Setting2015-2017 Department of Veterans Affairs (VA) electronic health record data.PopulationPrescribers were identified as dentists (2017: n = 1346) and medical providers (physicians n = 23,072; advanced practice providers [APP] n = 7705; and other providers [pharmacists/chiropractors] n = 3674) (2017: n = 34,451).MeasurementsHigh prescribing was defined as being in the top 25% of visit-based rates of antibiotic or opioid prescribing (number of prescriptions/number of dental or medical visits). Multivariable random effects logistic regression with clustering by facility was used to assess the adjusted association between high antibiotic and opioid prescribing.ResultsMedical providers prescribed 4,348,670 antibiotic and 10,256,706 opioid prescriptions; dentists prescribed 277,170 antibiotic and 124,103 opioid prescriptions. Among all high prescribers of antibiotics, 40% were also high prescribers of opioids as compared to 18% of those who were not high antibiotic prescribers (p < 0.0001). High prescribing of antibiotics was associated with high prescribing of opioids in medical providers (adjusted odds ratio [aOR] = 2.87, 95% confidence interval [CI] = 2.72-3.04) and dentists (aOR = 8.40, 95% CI 6.00-11.76). Older provider age, specific US geographic regions, and lower VA facility complexity and rurality were also associated with high opioid prescribing by medical providers. In dentists, younger provider age, male gender, specific regions of the United States, and lower number of dentists in a facility were associated with high opioid prescribing. At the facility level, high dental prescribers of antibiotics or opioids were not at the same facilities as high medical prescribers, respectively (p < 0.0001).ConclusionsHigh antibiotic prescribing was associated with high opioid prescribing. Thus, stewardship interventions targeting both medication classes may have higher impact to efficiently reduce prescribing of medications with high public health impact. Provider-targeted interventions are needed to improve antibiotic and opioid prescribing in both dentists and medical providers.

Dataset Information

Comparing Prescribing and Dispensing Data of the PCORnet Common Data Model Within PCORnet Antibiotics and Childhood Growth Study.

Publications

Comparing Prescribing and Dispensing Data of the PCORnet Common Data Model Within PCORnet Antibiotics and Childhood Growth Study.

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