» Articles » PMID: 28562502

Prescribers' Knowledge and Skills for Interpreting Research Results: A Systematic Review

Overview
Date 2017 Jun 1
PMID 28562502
Citations 11
Authors
Affiliations
Soon will be listed here.
Abstract

Introduction: Appropriate medication prescribing may be influenced by a prescriber's ability to understand and interpret medical research. The objective of this review was to synthesize the research related to prescribers' critical appraisal knowledge and skills-defined as the understanding of statistical methods, biases in studies, and relevance and validity of evidence.

Methods: We searched PubMed and other databases from January 1990 through September 2015. Two reviewers independently screened and selected studies of any design conducted in the United States, the United Kingdom, or Canada that involved prescribers and that objectively measured critical appraisal knowledge, skills, understanding, attitudes, or prescribing behaviors. Data were narratively synthesized.

Results: We screened 1204 abstracts, 72 full-text articles, and included 29 studies. Study populations included physicians. Physicians' extant knowledge and skills were in the low to middle of the possible score ranges and demonstrated modest increases in response to interventions. Physicians with formal education in epidemiology, biostatistics, and research demonstrated higher levels of knowledge and skills. In hypothetical scenarios presenting equivalent effect sizes, the use of relative effect measures was associated with greater perceptions of medication effectiveness and intent to prescribe, compared with the use of absolute effect measures. The evidence was limited by convenience samples and study designs that limit internal validity.

Discussion: Critical appraisal knowledge and skills are limited among physicians. The effect measure used can influence perceptions of treatment effectiveness and intent to prescribe. How critical appraisal knowledge and skills fit among the myriad of influences on prescribing behavior is not known.

Citing Articles

Healthcare providers' understanding of data displays of clinical trial information: a scoping review of the literature.

Thompson J, Wines R, Brewington M, Crotty K, Aikin K, Sullivan H J Commun Healthc. 2023; 16(3):260-267.

PMID: 37859459 PMC: 10589436. DOI: 10.1080/17538068.2022.2150236.


Complexity of Data Displays in Prescription Drug Advertisements for Healthcare Providers.

Thompson J, Lynch M, Sullivan H, Aikin K, Dolina S, Brewington M Ther Innov Regul Sci. 2023; 57(4):712-716.

PMID: 37061633 PMC: 10330753. DOI: 10.1007/s43441-023-00523-3.


Expectations for Artificial Intelligence (AI) in Psychiatry.

Monteith S, Glenn T, Geddes J, Whybrow P, Achtyes E, Bauer M Curr Psychiatry Rep. 2022; 24(11):709-721.

PMID: 36214931 PMC: 9549456. DOI: 10.1007/s11920-022-01378-5.


Influence of data disclosures on physician decisions about off-label uses: findings from a qualitative study.

Chansky M, Price S, Aikin K, ODonoghue A BMC Prim Care. 2022; 23(1):87.

PMID: 35439962 PMC: 9017050. DOI: 10.1186/s12875-022-01666-2.


Experts' Views on FDA Regulatory Standards for Drug and High-Risk Medical Devices: Implications for Patient Care.

Dhruva S, Darrow J, Kesselheim A, Redberg R J Gen Intern Med. 2022; 37(16):4176-4182.

PMID: 35138547 PMC: 9708961. DOI: 10.1007/s11606-021-07316-0.


References
1.
Lacy C, Barone J, Suh D, Malini P, Bueno M, Moylan D . Impact of presentation of research results on likelihood of prescribing medications to patients with left ventricular dysfunction. Am J Cardiol. 2001; 87(2):203-7. DOI: 10.1016/s0002-9149(00)01317-5. View

2.
Windish D, Huot S, Green M . Medicine residents' understanding of the biostatistics and results in the medical literature. JAMA. 2007; 298(9):1010-22. DOI: 10.1001/jama.298.9.1010. View

3.
West C, Ficalora R . Clinician attitudes toward biostatistics. Mayo Clin Proc. 2007; 82(8):939-43. DOI: 10.4065/82.8.939. View

4.
Brookhart M, Solomon D, Wang P, Glynn R, Avorn J, Schneeweiss S . Explained variation in a model of therapeutic decision making is partitioned across patient, physician, and clinic factors. J Clin Epidemiol. 2005; 59(1):18-25. DOI: 10.1016/j.jclinepi.2005.07.005. View

5.
Ghosh A, Ghosh K . Translating evidence-based information into effective risk communication: current challenges and opportunities. J Lab Clin Med. 2005; 145(4):171-80. DOI: 10.1016/j.lab.2005.02.006. View