The Impact of Academic Detailing on Clinician and Patient Outcomes: A Narrative Review

Abstract

Academic detailing (AD) can bridge the gap between evidence-based research and clinical practice to optimize patient outcomes. An up-to-date analysis of AD’s impact on clinician and patient outcomes is lacking. The purpose of this review was to examine updated evidence of AD’s impact on clinician knowledge, behavior, and patient outcomes. A librarian selected the keywords and designed the searches. Articles met full inclusion if they had an AD intervention and evaluated an outcome of change in clinician knowledge, behavior, and/or patient outcomes. The following data was extracted using Covidence: study design, types of outcomes, AD intervention description, number and type of learners and detailers, source of data analysis, outcome results, and if the results supported the use of AD. Forty studies were included in the final analysis. Twenty-seven percent (11 of 40) evaluated clinician knowledge change, 87.5% (35 of 40) evaluated clinician behavior change, and 17.5% (7 of 40) evaluated impact on patient care. Eighty percent of included studies (32 of 40) found a positive impact of AD on desired outcomes. There was a lack of uniform methodology and evaluation methods among the manuscripts. Pharmacists were the most common detailer type in the literature, aligning with AD topics of medication prescribing. The findings of this review reflect previous AD literature; variable interventions with less-than rigorous methodology and reporting, but an overall positive trend on desired outcomes.

Keywords

academic detailing educational outreach interprofessional education pharmacy education

Background

Inappropriate prescribing contributes substantially to adverse clinical outcomes and overall healthcare costs.^1-3 A gap between evidence-based research and prescribing decision-making exists and is exacerbated by the rapid introduction of new pharmacological agents, making it increasingly difficult for clinicians to remain current with emerging evidence and treatment options.^3,4 Academic detailing (AD) has become a pivotal strategy for bridging the gap between evidence-based research and real-world clinical practice, with the aim of optimizing patient outcomes.^3-5

AD is a unique and individualized educational outreach approach for healthcare professionals (HCPs). It entails the dissemination of evidence-based, unbiased, and non-commercial clinical information by trained detailers, typically HCPs such as pharmacists, physicians, or nurses.^1,2,5 Its format is one-on-one or small groups, allowing for bidirectional discussion and tailoring of educational points to individual clinicians’ specific needs and practice settings.^1,5 Unlike traditional continuing education formats, AD is an interactive and adaptive approach, making it an effective strategy for influencing clinicians’ decision-making, knowledge, and behaviors to improve patient care.^1,3,5 Pharmacists are well suited to be academic detailers given their knowledge of pharmacotherapy to treat disease and training in interprofessional care.⁶

First studied in the 1980s, AD was developed from the pharmaceutical industry’s educational outreach methods, more aptly called pharmaceutical detailing, and has since been adopted across various settings, including public health agencies and healthcare systems worldwide.^1-3 HCPs and healthcare system leaders increasingly view AD as a valuable tool for supporting continuing education, increasing clinician knowledge, and improving patient outcomes.^5,7 Furthermore, AD has been shown to address key healthcare priorities, including optimizing medication use, reducing inappropriate prescribing, and enhancing the management of chronic diseases.^1,3,5

In 2007, a Cochrane review of 69 studies of 15 000 health professionals found AD consistently improved prescribing and likely improved other professional performance (such as screenings).⁸ While the authors were conducting this narrative review, Rome and colleagues published a systematic review that evaluated prescribing behavior following AD interventions; they too found statistical significance in prescribing habits but noted variability in the quality and consistency of the evidence.⁹ Therefore, the purpose of this narrative review is to add to the literature, expanding on newer evidence since 2007s Cochrane review and a broader focus than Rome and colleagues’ systematic review, to examine AD’s impact on clinician knowledge, changes in clinical behavior, and patient outcomes.

Methods

The narrative review format was chosen by the authors for the comprehensive overview of AD studies’ characteristics and to identify any trends that influence clinician knowledge, behavior and patient outcomes.¹⁰ A medical librarian was consulted on key search terms and methodology development and performed the database searches. For full inclusion, the definition of AD was broad: any live (in-person or virtual) educational intervention on a medical topic given to a pre-defined set of HCPs by a trained detailer.

Literature searches were conducted in PubMed (NLM/NCBI), Embase (Elsevier), International Pharmaceutical Abstracts (OVID), CINAHL(EBSCO), and Web of Science (Clarivate). Search terms focused on AD and/or inappropriate prescribing with continuing education. No limits or filters were set for language or date. Complete search strings are included in Appendix 1.

Literature was uploaded into Covidence,¹¹ an online platform for organizing evidence-based reviews, weekly until January 9^th, 2025. Duplicates were automatically removed by Covidence and, if any remained, were then manually removed after confirmation by the primary author. Literature screening was conducted in 3 stages: initial title and abstract screening, full text, and then final extraction. The initial inclusion search criteria were English language publications, title or abstract including the terms “academic detailing” or “educational outreach” (not a search term but used interchangeably for academic detailing), primary literature, non-pharmaceutical company-led initiative, and if participants in AD were health professionals. To proceed to full text screening, two authors had to agree on inclusion; any disputes were resolved by the primary author.

Given the large volume of included literature after the initial screening, additional exclusions criteria were applied prior to the full text review. Articles were excluded if the study was not conducted in the United States (U.S.) or Canada, was published prior to 2007, and if the AD intervention was outpatient with additional components (eg, audit and feedback, voucher programs, patient mailings) or was the comparator/control group of another intervention. The rationale for these additional criteria is that the U.S. and Canada are geographically adjacent, follow similar practice guidelines, and have access to similar medications; to build on the 2007 Cochrane review exploring similar outcomes as previously described⁸; and to allow for exploration of the impact of AD alone compared to any other intervention or control. Only one author was required to approve inclusion of the full text to the extraction phase.

Data from the final set of included articles were extracted by all authors into Covidence. Extraction information included citation, study design, outcomes of interest (explained below), intervention description, number and type of learners and detailers, source of data analysis, results, and if the results supported the use of AD. Full text articles were reviewed by primary and senior authors to ensure accuracy and consensus of extracted data.

Articles were included for full analysis if their outcomes measured change in clinician knowledge, clinician behavior, or patient outcomes. Change in clinician knowledge was defined as any evaluation of clinician knowledge change (qualitative [eg, interviews], pre-and post-intervention, or post-intervention only evaluations). Clinician behavior change was defined as pre- and post-intervention comparisons in any medical behavior (eg, prescribing, referrals, documentation). Patient outcome change was defined as any parameter change measured or study or intervention completed in patients who were seen by the healthcare professionals (HCPs) who had received a detailing intervention. For the purposes of this review, articles were deemed “in favor” of AD if articles reported positive outcomes in the AD intervention group, or “not in favor” of AD if articles reported no change from the AD intervention.

Results

One thousand eight hundred and twenty-two unique publications were identified for initial screening. Five hundred and sixty full text studies were reviewed for inclusion; of those, 40 studies met the full inclusion criteria and were included in the final analysis. Figure 1 shows reasons for article exclusion. Study type varied; most were feasibility or quality improvement cohort studies. Less than half (16 of 40, 40%) of included studies used a control or comparator arm.^12-27 Of the 40 studies, 32 (80%) reported a positive impact of academic detailing on desired outcomes. Table 1 breaks down each study.

Figure 1.

PRISMA flow for study inclusion

Table 1.

Summary and Outcomes of Interest of Included Studies

Citation	Study design	Outcome(s) of interest	Intervention and comparison	Detailers	Learners	Data analysis sources	Results	In favor of AD?
Schuster RI, et al. “Implementation of NHLBI Obesity Guidelines in a Primary Care Community Setting: The Physician Obesity Awareness Project” Journal of Nutrition, Health, and Aging 2008.²⁸	Longitudinal cohort study	Clinician knowledge	Intervention: Intervention Group = AD on NHLBI practice guidelines for management of obesity and stating practice expectations + MD’s specific clinical outcomes	Not specified	Primary care physicians (n = 21)	Knowledge: Pre- and post-intervention physician survey	Knowledge: Physicians rating “comfortable” on obesity management increased from 47% (n = 7) to 100% (n = 19) (P = 0.041); average score of knowledge survey increased from 67% to 75% (no P-value)	Clinician knowledge: Yes
		Clinician behavior	Enhanced intervention: Same plus obesity classification stickers in medical records		Intervention group: n = 11 (physicians)	Behavior: Review of medical records	Behavior: 2.4% (6 of 641) of charts had documented diagnosis of obesity at baseline; at follow-up, 9.2% did (25 of 631) (P = 0.001)	Clinician behavior: Yes
		Patient outcomes	Comparator: Pre and post-intervention (baseline to follow up, 12-month), within group		Enhanced intervention group: n = 10 (physicians)	Patient outcomes: Patient based results extracted from medical record	Patient outcomes: Weight, BMI, BP, HgA1c, LDL and triglycerides all decreased numerically (P values reported between 0.83 -0.96); HDL and total cholesterol increased numerically (P = 0.09 and 0.26 respectively)	Patient outcomes: No
Curry WJ, et al. “Academic detailing to increase colorectal cancer screening by primary care practices in Appalachian Pennsylvania” BMC Health Services 2011.²⁹	Pre-post intervention study	Clinician knowledge	Intervention: 3 separate AD visits reviewing colorectal cancer (CRC) screening tests’ effectiveness/guidelines, reimbursement guidelines, referral services, patient counseling, and tools to alert when patient screening is due and follow-up processes; + reinforcement of standard medical practice, educational tools	Physician (n = 1), nurse (n = 1), PhD level behavioral specialist (n = 1)	Primary care providers (n = 15)	Clinician knowledge: Pre- and 6-month post-intervention physician survey	Clinician knowledge: 8 (n = 15, 53%) did not know about fecal immunochemical test (FIT) pre-intervention; 6-month post intervention, 100% (all 15) did know (no statistics provided).	Clinician knowledge: Yes
		Clinician behavior	Comparator: Pre- and post-intervention comparison of clinician knowledge, CRC documentation, and completed CRC rates, within group.			Clinician behavior, patient outcomes: Pre- and 6-month post-intervention patient medical charts review	Clinician behavior: Percentage of records that documented CRC screening currency increased from 16% to 64% post-intervention amongst clinics that used an electronic medical record (P < 0.01)	Clinician behavior: Yes
		Patient outcomes					Patient outcomes: 182 (n = 323, 56%) pre-intervention patients were current with CRC screenings vs 182 (n = 301, 60%) post-intervention patients were current (P = 0.29). However, 56 (17%) of pre-intervention patients had completed CRC screening in year prior, compared to 106 (35%) post-intervention patients (P < 0.001). There was no reported difference in median time from recommendation to colonoscopy (P = 0.82)	Patient outcomes: Yes
Hanson KA, et al. “Pharmacists and Naloxone: Barriers to Dispensing and Effectiveness of an Educational Outreach Program” Journal of the American Pharmacists Association 2023.³⁰	Retrospective analysis	Clinician knowledge	Intervention: 1:1 AD session on promoting naloxone standing order, identifying barriers, and improving access	Pharmacy students (n = 6)	Community pharmacists (n = 270)	Post-intervention survey (detailer assessment of visit effectiveness)	Post-intervention survey results stated that “the visit was informative/useful to the provider” was scored an average of 3.16 on a likert scale; a score of 3 was defined as neutral	No
	Retrospective analysis	Clinician knowledge	Comparator: Post-intervention survey assessing comfort and barriers; within group	Pharmacy students (n = 6)	Community pharmacists (n = 270)			No
Barton JH, et al. “Academic Detailing as a Health Information Technology Implementation Method: Supporting the Design and Implementation of an Emergency Department-Based Clinical Decision Support Tool to Prevent Future Falls.” JMIR Hum Factors. 2024.³¹	Prospective cohort study	Clinician knowledge	Intervention: AD interviews around a clinical decision support (CDS) tool utilizing electronic health record data to predict fall risk; interviews where incomplete or inaccurate information about the CDS tool was corrected in real-time	Intervention expert (n = 1)	Emergency medicine physicians (n = 10), advance practice providers (n = 6)	Semi-structured interviews	Targeted education was provided to improve understanding of the CDS tool for predicting fall risk and its impact on referrals; no post-intervention data or analysis provided	Yes
	Prospective cohort study	Clinician knowledge	Comparator: Post-intervention interview within group	Intervention expert (n = 1)		Semi-structured interviews		Yes
Holliday M, et al. “Evaluation of an Academic Detailing Program to Improve Blood Pressure Measurement and Hypertension Treatment in Urban Community Health Centers.” Journal of Continuing Education in Health Professions. 2023.³²	Prospective cohort study	Clinician knowledge	Intervention: Provided live modules on office blood pressure measurement and evidence-based hypertension treatment	Physician (n = 1)	Urban-based practice site medical assistants (n = 8) and health care providers (n = 50)	Pre- and post-intervention survey	Confidence and knowledge on blood pressure treatment increased among participants from pre- to post-intervention (all P values reported between <0.01 – 0.05)	Yes
	Prospective cohort study	Clinician knowledge	Comparator: Pre- and post-intervention comparison, surveys on blood pressure measurement and evidence-based hypertension treatment, within group	Physician (n = 1)		Pre- and post-intervention survey		Yes
Nguyen M. et al. Direct pharmacist prescribing of emergency contraception: findings of an academic detailing intervention pilot study. Journal of Contemporary Pharmacy Practice. 2021.¹²	Non-blinded randomized controlled trial	Clinician knowledge	Intervention: Handout on emergency contraception (EC) provided to learners; 1 hour continuing education session on EC provided by detailer	Pharmacist (n = 1)	Community pharmacists (n = 8)	Knowledge: Pre- and 30-day post-intervention surveys	Knowledge: 75% of participants demonstrated correct understanding of protocol for EC in intervention group compared to 25% of handout alone group; 100% understood differences between EC types in intervention group compared to 75% in handout group. Intervention group was more likely to agree with feeling well trained (mean 4.75) compared to handout alone (4.00).	Clinician knowledge: Yes
		Clinician behavior	Control: Handout alone		N = 4 in full intervention	Behavior: Surveys and 30-day pharmacist prescription data	Behavior: No difference between groups for intention-to-change behavior or actual prescriptions	Clinician behavior: No
		Clinician behavior	Comparison: Pre- and 30-day post intervention, knowledge survey and pharmacist prescribing data, within group		N = 4 in handout intervention	Behavior: Surveys and 30-day pharmacist prescription data	No statistics were performed (no P-values, no effect sizes)	Clinician behavior: No
Lowery, J. et al. Implementation of a Web-Based Tool for Shared Decision-making in Lung Cancer Screening: Mixed Methods Quality Improvement Evaluation. JMIR Hum Factors. 2022.³³	Implementation study	Clinician knowledge	Intervention: 1:1 meeting with 4-page visual abstract, pocket card, and clinical reminder screenshots and tool link handout, and references for shared decision making (SDM) tool for lung cancer screening	Master’s student in public health (n = 1)	Primary care providers (n = 105)	Knowledge: Semi-structured interviews	Knowledge: “Virtually all” respondents stated that the AD visit provided explanation and evidence of the SDM tool and how to use it	Clinician Knowledge: Yes
		Clinician behavior	Comparator: Within-intervention interview for knowledge, pre- and 6-month post-intervention comparison SDM tool use for behavior, within group			Behavior: Use of SDM tool for lung cancer screening per patient, pre- and post-AD intervention	Behavior: Across all sites, use of the SDM tool changed from baseline average of 114 uses/month to 6-month post intervention average 119 uses/month (P = 0.82)	Clinician Behavior: No
		Clinician behavior					No effect sizes provided	Clinician Behavior: No
Evoy KE, et al Impact of student pharmacist led naloxone academic detailing at community pharmacies in Texas Journal of the American Pharmacists Association 2019.³⁴	Quasi–experimental study	Clinician knowledge	Intervention: Student pharmacists traveled to pharmacies and provided 1:1 education with pharmacist on duty and provided educational handouts for off-duty pharmacist reviewing (1) use of naloxone for opioid overdose (2) populations at risk for overdose (3) available naloxone formulations (4) naloxone access laws in Texas	Pharmacy students	Community pharmacists	Knowledge: Telephone audit/questionnaire of pharmacist on duty	Knowledge: Knowledge of ability to dispense naloxone without prescription increased from 0 of 49 pharmacies to 37 (76% of all detailed pharmacies).	Clinician knowledge: Yes
		Clinician behavior	Comparator: Pre- and post-intervention, within group		(n = 49 pharmacies)	Behavior: Telephone audit/questionnaire	Behavior: The proportion of pharmacies that had naloxone in stock changed from 51% to 71% (P = 0.008) compared to baseline. In addition, the number of pharmacists willing to provide naloxone to a third-party/non-opioid user and submit claims to third party insurances increased post AD, from 43% to 71% (P = 0.002) and from 12% to 37%, respectively (P = 0.005). Lastly, pharmacies that both a) had naloxone in stock and b) were willing to dispense without an outside prescription increased from 0 to 33 (67%) post AD-intervention (P < 0.001)	Clinician behavior: Yes
		Clinician behavior	Comparator: Pre- and post-intervention, within group		(n = 49 pharmacies)	Behavior: Telephone audit/questionnaire	No effect sizes provided	Clinician behavior: Yes
Cameron MJ et al. “Evaluation of Academic Detailing for Primary Care Physician Dementia Education”. American Journal of Alzheimer’s Disease & Other Dementias. 2010.³⁵	Evaluation study	Clinician knowledge	Intervention: 15-minute educational sessions discussing concerns about addressing dementia, management strategies, promoting communication between primary care practice and local organizations, plus provision of materials with a list of triggers of dementia and contact information of local organizations	Team of a physician, Alzheimer’s Association representative, and an area agency on aging representative	Primary care physicians (n = 104), office/clinic staff (n = 248)	Knowledge: Post-intervention surveys	Knowledge: 77.4% of respondents (no n provided, though 216 were reported to have responded to this portion of the survey) stated the AD was “very effective” in providing information about community resources to assist families. The authors interpreted this as the AD “increased [participants] knowledge of specific programs and services available.”	Clinician knowledge: Yes
		Clinician behavior				Behavior: Post-intervention survey assessing change or intent-to-change since visit	Behavior: 65% of physician respondents (n not provided) stated their practice had not made any changes in the way to identify patients with dementia; 35% said they had.	Clinician behavior: Yes
			Comparator: Post-intervention survey within group for knowledge; behavior change compared pre- and post-intervention behaviors, within group				55% of physician respondents stated they had increased referrals to community resources for dementia
							No statistical analysis performed
Vasudev K, et al. “Academic detailing among psychiatrists – feasibility and acceptability”. International Journal of Health Care Quality Assurance. 2017.³⁶	Feasibility study	Clinician knowledge	Intervention: Two 1:1 visits with learners reviewing: 1) patient with severe mental illness (SMI) risk of illness and mortality 2) basic lab monitoring and appropriate documentation 3) managing metabolic and medical conditions in the SMI patient with a multidisciplinary approach 4) education on high dose or combination antipsychotics not being more effective and possibly harmful	Pharmacists (n = 3), masters-level nurse (n = 1)	Psychiatrists (n = 32)	Knowledge: Post-second visit survey	Knowledge: After the second visit, over 60% of respondents stated that AD visit would allow them to better optimize therapy and metabolic management.	Clinician knowledge: Yes
		Clinician behavior	Comparator: Post intervention survey within group for knowledge; behavior change compared pre- and post-intervention behaviors, within group			Behavior: Baseline and post-second visit survey	Behavior: At baseline, 59.1% (n = 23) stated they use >2 antipsychotics simultaneously in <25% of patients with schizophrenia; post-second visit, 54.5% stated this. At baseline, 72.7% participants stated they never use >2 antipsychotic agents simultaneously for patients with bipolar disorder; 68.2% stated this post-second visit. Metabolic monitoring rates were numerically similar. All P-values were cited at >0.05.	Clinician behavior: No
		Clinician behavior				Behavior: Baseline and post-second visit survey	No effect sizes provided	Clinician behavior: No
Foreman JK, et al. “Utilizing Academic Detailing Intervention to Increase Screening, Referral, and Treatment for Opioid Use Disorder Among Primary Care Providers in Randolph County” Journal of Addictions Nursing 2024.³⁷	Quality improvement project	Clinician knowledge	Intervention: 1:1 AD sessions on an opioid use disorder (OUD) resource packet (screening tools, community resources, proper billing procedure, buprenorphine dosing, required education for renewal)	Licensed nurse practitioner in addiction and internal medicine (n = 1)	Primary care nurse practitioners (n = 6), physician associate (n = 1), MD (n = 1)	Knowledge: Pre- and 6 weeks post-intervention survey	Knowledge: Survey results showed that baseline knowledge of providers moved from median of 2.00 (“some knowledge of resources”) to 3.00 (“very knowledgeable about resources”)	Clinician knowledge: Yes
		Clinician behavior	Comparator: Pre- and post-intervention comparison, within group			Behavior: Pre- and 6 weeks post-intervention survey; Provider Satisfaction of Academic Detailing tool (PSAD) immediately after intervention	Behavior: No change in referrals or screening frequency by providers after intervention; baseline, 1 provider (12.5%) reported never screening for OUD, and then 6-week post intervention, no providers reported never screening (no other numbers provided)	Clinician behavior: No
							75% of providers “felt that their practice would likely change” because of visit (actual PSAD score not provided)
							No statistical analysis performed
Uphold H, et al. “Evaluating Implementation and Barriers to Sustainability of an Asthma Clinical Quality Improvement Project” Journal of Nursing & Interprofessional Leadership in Quality and Safety 2022.³⁸	Pre-post test cohort study	Clinician behavior	Intervention 1: AD 11 monthly visits and 1 follow-up visit providing coaching/education on asthma guidelines, curating resources	Not specified	Primary care: Clinic #1: 27 HCP (MD, PA, NP, RN, MA)	Medical charts review (n = 30)	Clinician behavior: Among the AD intervention group, the average % of patients/charts with asthma control documentation increased from 30.7% at baseline to 85.5% 6-month post intervention	Yes
			Intervention 2: Learning collaboratives: 7 monthly group visits and 1 follow up visit providing coaching/education on asthma guidelines, curating resources		Clinic #2: MD (n = 1), care coordinator (n = 2), MA (n = 2)		Similarly, asthma action plan documentation increased from 4.1% to 58.9% in the same timeframe.
			Comparator: Within groups, pre- and post-intervention documentation frequency		Clinic #3: MDs (n = 2), PA (n = 2), NP (n = 1), clinic director (n = 1), admin (n not specified)		No statistical analysis provided
Ragan AP, et al. “Academic Detailing to Reduce Sedative-Hypnotic Prescribing in Older Veterans” Journal of Pharmacy practice 2021.³⁹	Quality improvement and retrospective analysis	Clinician behavior	Intervention: 1:1 (but some small groups of 2-3 providers) AD visit about decreasing sedative-hypnotic (benzodiazepines [BZD], and benzodiazepine receptor agonists [BZD-RA]) prescriptions and alternative treatments for insomnia, anxiety, and PTSD in veterans ≥75 years old.	Trained AD clinical pharmacists (n = 6)	Primary care and mental health prescribers (n = 155)	Pharmacy dispensing data from VA corporate data warehouse	New BZD/BZD-RA prescriptions and new starts decreased pre-intervention to post-intervention (all P-values <0.001). Treatment effect of AD intervention (differences in slope before/after intervention) showed greater reduction of prevalence of veterans on BZD of −0.42 (SE -0.12) per 1000 population (P < 0.001) and −0.13 (SE -0.04) veterans per 1000 population on BZD-RA (P < 0.01).	Yes
	Quality improvement and retrospective analysis	Clinician behavior	Comparator: Sedative-hypnotic prescribing 18 months prior to AD intervention and up to 18 months post-AD intervention, within group	Trained AD clinical pharmacists (n = 6)	Primary care and mental health prescribers (n = 155)	Pharmacy dispensing data from VA corporate data warehouse		Yes
Lane DS, et al. “A Provider Intervention to Improve Colorectal Cancer Screening in County Health Centers” Medical care 2008.²⁴	Cluster RCT	Clinician behavior	Intervention: 1 hour, interactive (Q &A) PowerPoint presentation to small groups about colorectal cancer (CRC) epidemiology, screening guidelines, barriers, approaches to improve patient CRC screening, and shared decision making	Not specified	Health center physicians (n = 15) and physician extenders (n = 11)	Medical record audit (chart notation)	An increase in CRC screening of 16% among intervention group (P < 0.001) and 4% in control group (P = 0.40)	Yes
	Cluster RCT	Clinician behavior	Comparator: 1 year pre- and 1 year post-intervention CRC screening rates (defined as referrals, kit dispensing, completion of screening); also compared to control sites/group data	Not specified		Medical record audit (chart notation)	CRC screening OR of 2.25 (1.67-3.04, P < 0.001) in intervention group vs control group	Yes
Friedmann, PD., et al. “Prescribe to Save Lives: An Intervention to Increase Naloxone Prescribing Among HIV Clinicians” Journal of Addiction Medicine 2023.⁴⁰	Stepped wedge implementation study	Clinician behavior	Intervention: 1.5-hour interactive training discussing rationale and evidence for prescribing naloxone, 3 additional AD visits at months 1,3,5 after initial training, ongoing peer-to-peer support	Study team (n = not specified)	HIV physicians (n = 57), nurse practitioners (n = 49), physician assistants (n = 9), missing clinician type (n = 4)	Pre- and post-intervention survey for intention-to-prescribe.	OR of 4.1 (1.7-9.4, P = 0.001) for survey-reported intention-to-prescribe naloxone post-intervention vs pre-intervention	Yes
			Comparator: Pre- and 6-12 months post-intervention for intent-to-prescribe; post-intervention prescribing data; within group			Electronic health records (EHR) were reviewed for the number of clinicians who prescribed naloxone	Incidence rate ratio of 2.9 (1.1-7.6, P = 0.03) of clinicians prescribing naloxone post-intervention, per EHR review
							Small increase in percentage of patients with HIV prescribed naloxone (0.8% to 1.8%, P = 0.16), per EHR review.
Kisuule F., et al. “Improving antibiotic utilization among hospitalists: A pilot academic detailing project with a public health approach.” Journal of Hospital Medicine. 2008.⁴¹	Pre- and post-intervention pilot study	Clinician behavior	Intervention: Detailing team met with learners for 30-45 minutes; detailing team appraised learner’s prescribing patterns (from pre-intervention survey results) including cost analysis; antibiotic guide provided	N = 2 (physician, pharmacist)	N = 17 (hospital physicians, nurse practitioners, physician assistants)	Chart review and physician order entry (for prescribing information)	Percentage of not appropriate antibiotic prescribing decreased post-intervention (57% [n = 140] to 26% [n = 34], P < 0.001)	Yes
	Pre- and post-intervention pilot study	Clinician behavior	Comparator: Prescribing patterns within group, assessed as appropriate/effective but inappropriate/inappropriate, pre- and 1-month post-intervention	N = 2 (physician, pharmacist)				Yes
Stafford RS., et al. “Impact of the ALLHAT/JNC7 Dissemination Project on Thiazide-type Diuretic Use.” Arch Intern Med. 2010.²⁵	Longitudinal study	Clinician behavior	Intervention (dissemination effort): Presentation with learner individualized focus on blood pressure goals and first-line therapy with thiazide diuretics; specialized materials such as newsletters and pocket cards provided to learners.	N = 147 (investigator-educators, primarily investigators from ALLHAT trial)	N = 18 824 (prescribers of blood pressure medication)	Prescribing patterns collected through national disease and therapeutic index (NDTI) survey and IMS health xponent pharmacy claims database	NDTI survey: Counties with highest number of dissemination effort resulted in 23% relative increase (37.9% to 46.5%) in thiazide-type diuretic use vs 6% (37.1% to 39.6%) in counties with no dissemination (P < 0.01)	Yes
	Longitudinal study	Clinician behavior	Comparator: Counties receiving no dissemination effort/AD intervention		N = 18 824 (prescribers of blood pressure medication)		IMS health xponent database: Counties with highest number of dissemination effort resulted in 8.1% relative increase (from 52.1 scripts/day/1000 people to 56.4/1000) in thiazide-type diuretic use vs 3.9% (from 164.8 scripts/day/1000 people to 171.2/1000) in counties with no dissemination (P < 0.001)	Yes
Boom, JA, et al. “Improvement in Provider Immunization Knowledge and Behaviors Following a Peer Education Intervention” Clinical Pediatrics 2007.⁴²	Pre- and post-intervention study	Clinician behavior	Intervention: 1-hour educational intervention targeting minimizing missed opportunities, utilizing tools and resources to maximize immunization delivery and creating a site-specific action plan. Educational tools as reinforcements were provided to practice sites every 6 months following intervention.	Physician (n = 1), nurse (n = 1), office manager (n = 1) trained 47 nurses, physicians, and office managers as peer educators	Pediatric and family medicine physicians/physician assistants (n = 35), nurses (n = 51), medical assistants (n = 65), office staff (n = 34)	Matched responses from pre- and post-intervention surveys	The average score (total score between 0-11) of correct immunization behaviors increased from 5.2 to 5.6 (+0.4, P = 0.004) among the 186 matched surveys, pre- and post-intervention respectively	Yes
	Pre- and post-intervention study	Clinician behavior	Comparator: Pre- and 6-10 months post-intervention within group			Matched responses from pre- and post-intervention surveys		Yes
Behar E, et al. “Academic Detailing Pilot for Naloxone Prescribing Among Primary Care Providers in San Francisco” Family Medicine 2017.²⁰	RCT	Clinician behavior	Intervention: A 5-60-minute visit provided education around the provider educational booklet (overdose statistics, overdose risk factors, naloxone co-prescriptions, naloxone details, educating patients, and California prescribing laws and resource page) plus a folder of materials: California guidelines for prescribing controlled substances, instructions for registering for the prescription drug monitoring program (PDMP), morphine equivalent dose calculator, and articles on naloxone’s effectiveness and cost-effectiveness.	Study staff (n = 2)	Primary care physicians, nurse practitioners, physician assistants (n = 40)	Number of naloxone prescription claims in medi-cal database	Incidence rate ratio of 11.0 (1.8-67.8, P = 0.010) naloxone prescriptions in intervention group vs control. In the intervention group, number of naloxone prescriptions increased from 0 to 10 post-intervention.	Yes
	RCT	Clinician behavior	Comparator: Naloxone prescriptions at 4 months pre-intervention and 4 months-post intervention, comparison within group and comparison to control group	Study staff (n = 2)		Number of naloxone prescription claims in medi-cal database		Yes
Larson MJ, et al. “Physicians report adopting safer opioid prescribing behaviors after academic detailing intervention” Substance Abuse 2018.⁴³	Pre-post intervention study	Clinician behavior	Intervention: AD visit focusing on patient-provider agreements, using rating scales to optimize treatment, and screening for appropriateness and need for opioid therapy	Pharmacists (n = 4)	Physicians who cared for military members/Veterans (n = 87)	4 weeks pre-intervention and 38 weeks post-intervention surveys	37% (of total response n = 68) of prescription monitoring program users at baseline increased to 88% post-intervention (P < 0.001)	Yes
			Comparison: Pre- and post-intervention within group, evaluating safe opioid use prescribing behaviors				The percentage of physicians who reported usually or always using a multi-dimensional pain scale increased from 47 to 57% post intervention (P = 0.028)
							No reported differences in pain/quality of life/functioning scale use, urine toxicology use, and opioid contract use
Saffore CD, et al. “Practice change intentions after academic detailing align with subsequent opioid prescribing” Journal of the American Pharmacists Association 2020.⁴⁴	Quantitative analysis	Clinician behavior	Intervention: Two 1:1 visit reviewing the 6 messages from the CDC chronic pain prescribing guidelines with opioid prescribing metrics from prescription monitoring program (PMP).	Student pharmacists (n = 8) and pharmacists (n = 2)	Primary care MD (n = 85), DO (n = 38), APN (n = 18), physician assistants (n = 8)	Pre- and post-intervention intent-to-change survey response and opioid prescribing data from Illinois PMP	No difference in mean total opioid prescriptions between intention-to-change and no-intention to change groups (19.78 vs 19.31, P = 0.74; and 11.15 vs 12.16, P = 0.33 respectively).	Yes
			Comparator: Comparison between intention-to-change group to no-to-moderate intention to change group, and baseline to post-intervention within groups				However, there was a decrease in the mean monthly high dose prescriptions per clinician per month in the intention-to-change pre-and post-intervention (1.26 to 0.69, P = 0.01) but not in no-intention-to-change group (0.49 to 0.42, P = 0.27)
					Intention to change group (n = 72)		Lastly, compared to no-intention-to-change group, those in intention-to-change group had 1.48 opioid prescriptions less per clinician per month (P < 0.05)
					No-to-moderate intention to change group (n = 77)
So M, et al. “Antimicrobial stewardship by academic detailing improves antimicrobial prescribing in solid organ transplant patients” European Journal of Clinical Microbiology and Infectious Disease 2019.⁴⁵	Cohort study	Clinician behavior	Intervention: Twice weekly AD “rounds,” (duration not specified) reviewing selection of empiric therapy, tailing regimen, determining treatment duration, when to consult with transplant infectious disease team, modifying dosing, and therapeutic monitoring, discussed in patient case contexts	Pharmacist (n = 1)	Transplant team: nurse practitioners (n not specified), a physician assistant (n = 1), a TID team member (n = 1), and a transplant pharmacist (n = 1)	EHR chart review, pre- and post-intervention (reviewed at four monthly points prior to intervention, and four monthly points post-intervention)	Percentage of antibiotic prescribing classified as “concordant” to AMS principles increased from 69% pre-intervention (60/87) to 83.7% post-intervention (83/111), P = 0.01	Yes
	Cohort study	Clinician behavior	Comparator: Pre- and post-intervention comparison of “concordant” or “discordant” to antimicrobial stewardship (AMS) principles antibiotic prescribing, within group	Transplant & infectious disease (TID) physician (n = 1)				Yes
Bounthavong M, et al. “Impact of Implementing an Academic Detailing Program on Opioid-Benzodiazepine Co-Prescribing Trends at the U.S. Department of Veterans Affairs” Pain Medicine 2021.²²	Cohort study	Clinician behavior	Intervention: AD visit focusing on risk of opioid-benzodiazepine combination (co-prescribing) and overdose, opioid and benzodiazepine tapers, opioid use disorder support for providers and patients	Pharmacists (n = not specified)	Providers at 119 VA stations (n = 16 842)	VA corporate data warehouse for prescribing and dispensing data	VA stations that implemented AD had larger reduction in co-prescriptions vs non-AD stations (−0.44 vs −0.33 per 1000 population, P < 0.036).	Yes
	Cohort study	Clinician behavior	Comparator: Site (or station) that received AD intervention vs control group; average monthly number of patients co-prescribed opioid-benzodiazepine/1000 population	Pharmacists (n = not specified)	Providers at 119 VA stations (n = 16 842)		Based on a fixed effect model, if a station had 100% of its providers receiving AD, that would result in a monthly reduction of 4.9 patients (P < 0.001) with a co-prescription (per 1000 population) vs a station with no providers receiving AD.	Yes
Wynn RE, et al. “Evaluation of Academic Detailing to Impact Pharmacists: Compliance with an Outpatient Pharmacy Partial Fill Policy” Journal of Pharmacy Practice 2022.⁴⁶	Interventional, prospective project	Clinician behavior	Intervention: 1:1 in person or instant-messaging AD visit reviewing correct prescription partial filling protocols, including inappropriate medications and the 7-day medication supply limit on partial fills	Clinical pharmacy specialist (n = 1)	Veterans affairs outpatient pharmacy pharmacists (n = 36)	Pre-, post-intervention, and 6-month follow up of partial fill medication orders verified (from computer system)	Percentage of compliant 7-day supply partial fill policy prescriptions from baseline, 49.2 % (1622/3297) to 87.2% (2398/2849) (P < 0.001) post-intervention.	Yes
	Interventional, prospective project	Clinician behavior	Comparator: Pre- and post-intervention correct partial fill orders, within group	Clinical pharmacy specialist (n = 1)	Veterans affairs outpatient pharmacy pharmacists (n = 36)		Percentage of compliant partial fills at 6-month follow up was 84.4% (no n or P-value vs baseline provided)	Yes
Andrews SL, et al. “Decreased antimicrobial prescribing rate following academic detailing of resident physicians in outpatient clinic” Antimicrobial Stewardship and Healthcare Epidemiology 2023.¹⁹	Pre-and post-intervention observational study	Clinician behavior	Intervention: Low-prescribing residents: Received CDC outpatient antibiotic treatment guidelines via e-mail	Infectious disease fellow (n = 1)	Internal medicine veterans affairs resident physicians	Number of antimicrobial prescriptions per resident from EHR	In the high-prescribing group, prescriptions per 1000 visits decreased, from 3.46 at baseline to 2.04 during the intervention. (P = 0.05)	Yes
			High prescribing residents: Same e-mail + in person visit with infectious disease fellow discussing cases and reviewing guidelines		Low prescribing (n = 17)		While numerically different at baseline, prescriptions between low and high-prescribing groups were not numerically different during intervention (P = 0.31)
			Comparator: Pre-and during-intervention antibiotic prescriptions per 1000 patient visits, within groups and between groups		High prescribing (n = 12)
Awad MH, et al. “The Effect of Pharmacy-Led, Small-Group Academic Detailing on Prescribing Patterns in an Ambulatory Care Clinic” Journal of Pharmacy Technology 2019.⁴⁷	Retrospective analysis	Clinician behavior	Intervention: 1-hour small group, in person sessions delivered via PowerPoint	Pharmacists, pharmacy residents, pharmacy students (n = not specified)	Federally qualified health center physicians, nurse practitioners (n = not specified)	Prescribing patterns of all primary care physicians using EHR	Between April 2010 and Jan 2015, metformin prescribing increased (5.5% to 37.7%, P < 0.005), beta-blockers for HTN prescribing decreased (17.9% to 13.8%, P < 0.005), and statin prescribing increased (77.1% to 86.9%, P < 0.005).	Yes
			Topics discussed were hypertension, type 2 diabetes, hyperlipidemia and their appropriate pharmacological therapy-including dosing, adverse reactions, monitoring parameters.
			Comparator: Pre- and post-intervention prescribing patterns, within group
Bounthavong M, et al. “Comparison of naloxone prescribing patterns due to educational outreach conducted by full-time and part-time academic detailers at the U.S. Veterans Health Administration” Journal of the American Pharmacists Association 2019.²¹	Quality improvement cohort study, using nonequivalent control group posttest-only design	Clinician behavior	Intervention: Opioid overdose education and naloxone distribution (OEND)-related educational outreach by pharmacist academic detailers	Clinical pharmacists (n = not specified)	Veterans affairs primary care providers (n = 2602)	Naloxone prescribing rate: VA corporate data warehouse.	The average number of monthly naloxone prescriptions per provider was 0.60 (SD = 3.7) of those who received education from high FTE, vs 0.53 (SD 2.37) of those who received education from low FTE (P = 0.005)	Yes
			Comparator: Pre- and post-intervention naloxone prescribing of providers who received an AD visit from a detailer assigned <0.4 Full Time Employee (FTE) detailing time allotment (low FTE) versus those received an AD visit from a detailer assigned >0.4 FTE detailing time allotment (high FTE)		N = 1770 received education from high FTE detailer	Details from the AD visit: Data from Salesforce.com	On average, the number of naloxone prescriptions increased by 28/1000 providers for those who received outreach from a high FTE detailer, versus 17/1000 providers receiving visit from low FTE detailer (P = 0.027)
					N = 832 received education from low FTE detailer	Details from the AD visit: Data from Salesforce.com
Kithulegoda N, et al. “Academic detailing to improve appropriate opioid prescribing: a mixed-methods process evaluation” Canadian Medical Association Journal 2023.²³	Mixed methods process evaluation	Clinician behavior	Intervention group: 1:1 AD visit discussing opioid therapy, managing chronic non-cancer pain, and opioid use disorder	Pharmacists (n = 19)	Family physicians	Prescription claims from IQVIA Xponent and longitudinal prescription databases	Intervention group’s mean morphine equivalent (MME) opioid dose decreased by 18.9% by end of evaluation period; control group’s increased by 18.2% (P = 0.0009)	Yes
			Comparator: Control group with no AD, pre- and post-intervention high-risk opioid prescribing comparison		Intervention group (n = 238)		P-value >0.05 for intervention vs control comparisons of number of high-risk opioid prescriptions number of patients on low- and high-dose opioid prescriptions, and total average days supply per patient
					Control group (n = 238)
Leone FT, et al. “Academic Detailing Interventions Improve Tobacco Use Treatment among Physicians Working in Underserved Communities” Annals of the American Thoracic Society 2015.⁴⁸	Non-randomized experimental	Clinician behavior	Intervention: In person individual or small group visit focusing on overcoming smoking cessation reluctance, effective tobacco use treatment, and how to be reimbursed for services, shared resources available online, and an additional follow-up visit 2-4 months later	Allied health professional with public health education experience (n = 2)	Primary care physicians (n = 217)	Physicians’ self-reported responses from 7-item questionnaire	Physician reported frequency of performing complex tobacco treatment behaviors increased from baseline to follow-up (2.63 to 2.92, P < 0.001), as did simple tobacco treatment behaviors (3.98 to 4.13, P = 0.035).	Yes
	Non-randomized experimental	Clinician behavior	Comparator: Baseline to follow-up visit self-reported tobacco treatment behaviors (simple – ask, assess, advise; complex – prescribing, referral to quitline, follow up, billing), within group		Primary care physicians (n = 217)			Yes
Ball SJ. “Academic detailing increases prescription drug monitoring program use among primary care practices.” Journal of American Pharmacist Association. 2021.⁴⁹		Clinician behavior	Intervention: AD visit regarding safe opioid prescribing and importance of checking prescription drug monitoring program (PDMP)	Pharmacist (n = 1)	Primary care prescribers (n = 87), PDMP delegates (n = 42)	PDMP data	Monthly mean of prescriber/delegate PDMP report requests increased from 28.1 to 53.0 post intervention (P < 0.0001)	Yes
			Comparator: 8-month pre-intervention to 6-month post-intervention PDMP requests and opioid prescribing habits, within group
							The rate ratio of association between requesting PDMP report and AD intervention was 40.35 (15.13-107.60, P < 0.001) for prescribers and delegates
							Number of monthly mean dispensed opioid prescriptions from detailed prescribers changed from 57 to 54.5 (P = 0.442) and number of patients dispensed opioid prescriptions changed from 46.6 to 45.2 (P = 0.532).
Jin M et al. “Patient-specific academic detailing for smoking cessation.” Canadian Family Physician. 2014.⁵⁰	Feasibility study	Clinician behavior	Intervention: Patient-specific AD (general messaging with provider’s patient examples) on smoking cessation given to family medicine prescribers	Pharmacists (n = 8)	Family physicians (n = 48), nurse practitioners (n = 9)	Clinic appointment schedule for pharmacist referral, documented into standardized data collection forms	Number of referrals to pharmacist for smoking cessation numerically increased 3 months pre-intervention to 6 months post-intervention (11 patients per FTE, or 66 patients; to 34 patients per FTE, or 200 patients)	Yes
	Feasibility study	Clinician behavior	Comparator: Pre-specified number of pharmacist referrals for smoking cessation defined as “success”; 3 month success 5 patients/pharmacist FTE, 6 month success 10 patients/pharmacist FTE	Pharmacists (n = 8)	Family physicians (n = 48), nurse practitioners (n = 9)		No statistics provided	Yes
Basch C, et al. A Randomized Trial to Compare Alternative Educational Interventions to Increase Colorectal Cancer Screening in a Hard-to-Reach Urban Minority Population with Health Insurance Journal of Community Health 2015.¹⁶	RCT	Clinician behavior	AD intervention group: 1:1 in person AD about colorectal cancer (CRC) screening and follow-up practices, guided by PCP’s responses + binder with evidence for screening recommendations, printed patient education, and forms for supply refills	Member of the research team	AD intervention group: Primary care providers (n = 139) & 7 left with materials	CRC screening medical claims paid by the benefit fund	The screening rates of AD group vs intervention #1 were 20.0% (n = 185 patients) vs 18.3% (n = 180 patients) (χ² = 0.1, P = 0.79)	No
			Intervention #1: Received mailed printed educational material on risk factors for CRC, importance of early screening, how to prepare for colonoscopy, and other tests available		Intervention group #2: Primary care providers (n = 144) & 7 left with materials		The screening rates of AD group vs intervention #2 were 20.0% vs 35.6% (n = 199 patients) (χ² = 1.4, P = 0.23).
			Intervention #2: Received AD + patients received tailored telephone education (TTE)
			Study comparator: CRC screening in study-consenting patients, between groups
Chui D, et al. “Impact of academic detailing on proton pump inhibitor prescribing behaviour in a community hospital” Canadian Pharmacists Journal 2011.⁵¹	Retrospective chart review	Clinician behavior	Intervention: A 10 minute presentation with physician reviewing top 3 inappropriate uses of proton pump inhibitors (PPIs): Double-dose PPIs, PPI use in anemia, and PPI use in surgical prophylaxis, plus a pocket card (indications and side effects)	Clinical research/Drug information pharmacist (n = 1)	Community hospital physicians (n = 31)	Prescribing data was taken from patients’ medical charts	Inappropriate PPI prescribing changed from 53% pre-intervention to 61% in the post-intervention (61%) period (P = 0.253).	No
	Retrospective chart review	Clinician behavior	Comparator: Pre- and post-intervention inappropriate inpatient PPI prescribing, within group	Clinical research/Drug information pharmacist (n = 1)	Community hospital physicians (n = 31)	Prescribing data was taken from patients’ medical charts	Post-hoc: Inpatient-initiated inappropriate PPI prescribing changed from 66% pre-intervention to 57% post-intervention (P = 0.311)	No
Franko TS, et al.“Assessment of student pharmacist-led academic detailing on independent community pharmacy naloxone orders” Journal of the American College of Clinical Pharmacy 2024.¹⁷	RCT	Clinician behavior	Intervention: 1:1 visit involving demonstration and teach-back of naloxone nasal spray use, and practiced communication skills through simulated patient encounters.	Pharmacy students (n = not specified)	Independent pharmacy pharmacists and pharmacy personnel from 15 pharmacies (n = not specified)	Naloxone shipping data provided by VALUE drug (wholesaler)	Post-intervention, intervention pharmacies received 31 naloxone shipments, vs 29 in the control pharmacies (P = 0.25)	No
	RCT	Clinician behavior	Comparator: Pre-and post-intervention naloxone ordering, vs control pharmacies	Pharmacy students (n = not specified)		Naloxone shipping data provided by VALUE drug (wholesaler)		No
Trombetta DP, et al. “Can Academic Detailing Move the Needle for Patients with Diabetes in a State-Based Prescription Drug Benefit Program?” American Health and Drug Benefits 2019.¹⁸	Retrospective, quasi-experimental study design	Clinician behavior	Intervention: Educational visit plus printed material reviewing key diabetes education (lifestyle modification, individualize HgA1c, use of metformin as 1^st line therapy, and managing comorbid conditions)	Not specified (n = not specified)	Primary care prescribers (n = 574)	Pennsylvania pharmaceutical assistance contract for the Elderly’s pharmacy claims data	For all four prescribing metrics, the intervention group prescribing did not increase post-intervention and remained lower than or similar to the comparison group.	No
	Retrospective, quasi-experimental study design	Clinician behavior	Comparator: 360 days pre- and 360 days post-intervention diabetes management prescribing (metformin, ACEi/ARB, statin, long acting sulfonylureas), within group and vs a comparison (non-intervention) group	Not specified (n = not specified)	Primary care prescribers (n = 574)		See Tables 2 and 3 of article for all result details.	No
Lacroix M, et al. “Effectiveness of Audit & Feedback and Academic Detailing Interventions to Support Safer Opioid Prescribing in Primary Care” American Journal of Medicine 2024.¹³	Quasi-experimental matched cohort study	Clinician behavior	Intervention #1: Audit & feedback group: Received a personalized opioid prescribing report from “MyPractice: Primary care” (MPPC) report	Pharmacists (n = not specified)	Primary care physicians intervention #1: n = 1469	Clinician behavior and patient outcomes: ICES databases that collect population-based administrative claims	The monthly mean rate of high-risk opioid prescriptions increased pre- and post-intervention for intervention #2 and intervention #3 (control); the authors reported no difference between the 3 groups	Clinician behavior: No
		Patient outcomes	Intervention #2: Audit & feedback + academic detailing group: Received opioid prescribing MPPC report + at least 1 academic detail visit reviewing messages and resources on chronic noncancer pain management, opioid safety, and opioid prescription titration		Intervention #2: n = 245		The percent difference in change in slope between intervention #1 and intervention #3/Control was −0.61 (−1.02 to −0.21, P < 0.01)	Patient outcomes: No
			Intervention #3: Control group		Intervention #3/Control group: n = 4211		There was no reported difference in patient opioid-related harm between the 3 groups
			Comparator: 12 months pre- and 18 months post-intervention rate of patients per 100 per 30 days receiving opioid prescriptions >90 MEQs or co-prescribed with benzodiazepine (opioid patients), + opioid related harms (opioid-related hospitalization, emergency room visit, or death), between groups		Intervention #3/Control group: n = 4211
Lacroix M, et al. “Effects of an academic detailing service on benzodiazepine prescribing patterns in primary care” PLoS One 2023.¹⁴	Quasi-experimental cohort study	Clinician behavior	Intervention: 1:1 AD visit reviewing appropriate benzodiazepine (BZD) prescribing, with a specific focus on adults ≥65 years	Pharmacist (n not provided)	Family practice physicians intervention (n = 273), control (n = 1064)	Clinician behavior: ICES databases that collect population-based administrative claims; specifically, narcotics monitoring system was used for primary outcome	Clinician behavior: Over 30-month timeframe, average monthly BZD prescriptions per physician decreased in AD group (32.47 to 3061, average monthly percent change −0.49, −1.21- +0.23, P = 0.18) and the control group (31.95 to 26.28, average monthly percent change −0.51, −0.92 to −0.10, P = 0.01)	Clinician behavior: No
		Patient outcomes	Comparator: BZD prescribing and patient BZD-related harms 12 months pre- and 18 months post-intervention, within group vs control group who did not receive AD.			Patient outcomes: National ambulatory care reporting systems databases hospital codes (BZD-related hospitalizations, ED visits, or falls)	Estimate of percent change in slope of total BZD prescriptions between AD group and matched controls was +0.11 (P = 0.82)	Patient outcomes: No
		Patient outcomes					Patient outcomes: No change in hospital codes’ trend lines, pre- and post-intervention or between groups (no statistics provided)	Patient outcomes: No
Tadrous M, et al. “Effect of Academic Detailing on Promoting Appropriate Prescribing of Antipsychotic Medication in Nursing Homes” JAMA Network Open 2020.¹⁵	Cluster randomized trial	Clinician behavior	Intervention: 1:1 or group visit (2-6 clinicians) reviewing barriers and opportunities for improved prescribing of antipsychotic medications among the elderly	Nurses or pharmacists (n = not specified)	AD intervention: Nursing home administrators, physicians, pharmacists, nurses, and support workers (n = 336)	Both clinician and patient outcomes taken from ICES, population-level administrative claims databases, in Ontario, Canada.	Clinician behavior: The between-group difference of antipsychotic prescribing was an OR of 1.06, 95% CI 0.93-1.2, P = 0.49)	Clinician behavior: No
		Patient outcomes	Standard of care: Physician-level online “report cards” showing antipsychotic prescribing practices vs regional rates, overview of clinical and demographics of physician roster				Patient outcomes: Differences reported between groups in pain scores were usual care −0.30vs intervention −0.38, P < 0.001; and depression scores were usual care −2.18 vs intervention −2.81, P < 0.001.	Patient outcomes: Yes
		Patient outcomes	Comparator: 12 months post-intervention vs standard of care group, evaluating antipsychotic dispensing rates (level of resident/patient) and antipsychotic harms/outcomes (falls in past month, ED and hospitalizations, activities of daily living, aggressive behavior, pain scores [0-3 range], depression scores [depression rating scale, range 0-14])					Patient outcomes: Yes
Hudmon KS, et al. “Outcomes of a randomized trial evaluating two approaches for promoting pharmacy-based referrals to the tobacco Quitline” Journal of the American Pharmacists Association 2018.²⁶	RCT	Patient outcomes	Intervention #1: 1:1 AD visit with 30 minute training about the ask-advice-refer process and the tobacco quitline services, published articles/CD-ROM about tobacco quitline, and a quitline brochure/card for patient use or how to directly enroll the patient through fax referral process.	Pharmacist (n = 1)	Community pharmacy staff (n = 32 pharmacies)	Patient outcomes: Intake questions about pharmacy-based referrals to the CT and WA quitlines	The difference between mean numbers of quitline registrants reporting hearing about the quitline from the pharmacy was 2.8 in the intervention #1 group vs 2.4 in the intervention #2 group (P = 0.547)	No
			Intervention #2: Mailed materials to pharmacy staff on quitlines (no published articles or CD-ROM on quitlines provided).
			Comparator: 12 month post-intervention, between groups, number of pharmacy-based referrals registering with quitline.
Shankaran V., et al. “Costs and Cost Effectiveness of a Health Care Provider Directed Intervention to Promote Colorectal Cancer Screening.” Journal of Clinical Oncology. 2009.²⁷	Intervention study	Patient outcomes	Intervention: Four 1:1 AD visits instructing on evidence-based guidelines for colorectal cancer (CRC) screening; print materials and sample patient case materials left with learners	Non US-licensed, foreign-trained physician (n = 1)	Small practices	EHR review	Between intervention and control groups, the OR of screening by colonoscopy was 1.93, 95% CI 1.11-3.37, P = 0.02). There was no reported difference in fecal occult blood test or flexible sigmoidoscopy between the two groups (P = 0.47 for FOBT, P = 0.81 flexible sigmoidoscopy).	Yes
			Comparator: Control group, pre- and 12-month post-intervention, patient completion of: fecal occult blood test (FOBT), flexible sigmoidoscopy, colonoscopy		Intervention: n = 136 physician offices
					Control: n = 128 physician offices

Clinician Knowledge

Of the 40 included articles, 27.5% (11) evaluated the impact of AD on clinician knowledge.^12,28-37 Ten studies reported the specific number of learners who received AD (N = 885).^{12,28-33,35-37} The most frequently detailed HCPs were pharmacists (N = 278), followed by office/clinic staff (N = 248) and physicians (N = 157). Pharmacy was a common detailer type; four articles used pharmacy personnel (pharmacists, students) as sole detailers^12,30,34 or as part of detailing team.³⁶ One article did not specify the detailer type²⁸ and another article, focused on use of a clinical decision support tool, used a non-HCP “intervention expert.”³¹ The most common evaluation method of knowledge change were pre- and post-intervention surveys^{12,28,29,32,37} (45.5%%, 5 of 11); others were post-intervention surveys^30,35,36 (27%, 3 of 11) and qualitative interviews^31,33 (18%, 2 of 11). Of the eleven included articles evaluating clinician knowledge, ten (91%) were in favor of the AD intervention as positively influencing clinician knowledge,^{12,28,29,31-37} and one was not.³⁰

Clinician Behavior

Eighty seven and a half percent of the included articles (35/40) evaluated the impact of AD on influencing clinician behavior.^{12-25,28,29,33-43,45-51} Of the 88.6% (31/35) of studies that reported the number of AD learners (N = 42 314), the most frequently specified HCPs who received an AD intervention were physicians (n = 1762), followed by office staff (n = 325). The most common detailer type reported was pharmacy staff (57%, 20 of 35 studies); eight articles did not specify the detailer type (Table 1). The outcome assessed most commonly was change in prescribing habits; the evaluation methods for prescribing habits were most frequently data analyzed from pharmacy or database claims^{12-15,18,20-23,25,39,44} and chart reviews^{19,40,41,45,47} (written prescriptions/orders). Other behavior changes measured included change in clinician referrals and/or screenings.^{16,24,35,37,48,50} Of the 35 articles that evaluated clinician behavior change, 24 (68.5%) showed that AD had a positive influence on the outcomes measured.^{19-25,28,29,33-35,38-47,49,50}

Patient Outcomes

Seventeen and a half percent (7 of 40) of the articles evaluated the impact of AD on direct patient outcomes.^13-15,26-29 The most detailed HCP was physicians (n = 539). While quantity was not specified, the most common detailer HCP was pharmacists.^13-15,26 Three of the seven articles (42.9%) concluded that AD had a positive impact on patient outcomes; specifically, on pain and depression scores (though no correlating change in antipsychotic prescribing)¹⁵ and the number of patients up to date on CRC screenings.^27,29 Lacroix and colleagues found no difference in patient opioid-related¹³ or benzodiazepine-related¹⁴ harms after a safe prescribing AD campaign, while Schuster and colleagues²⁸ found no impact on weight, body mass index, blood pressure, or lipid panel with an obesity AD campaign (though clinician knowledge on obesity management and documentation of obesity in charts increased). Lastly, completed referrals to a tobacco quitline were not different than control pharmacies after a pharmacy staff-focused tobacco cessation AD campaign.²⁶

Discussion

Staying up to date with the evolving healthcare landscape is crucial for clinicians. Continuing education exists as a method to both reinforce and update knowledge, which should improve clinician care (behaviors) and ultimately improve patient outcomes.⁵² This narrative review describes the impact of AD on changing clinician knowledge, behavior, and patient outcomes. The included articles used an AD intervention on a variety of topics (most commonly, safe opioid and/or benzodiazepine prescribing,^{13,14,22,23,37,39,43,44,49} naloxone use,^{17,20,21,30,34,40} cancer screening,^16,24,27,29 and antimicrobial stewardship^19,41,45), across a variety of detailer and learner types. Most (32 of 40, or 80%) articles included found a positive impact of AD on measured outcomes. Unsurprisingly, most detailers were pharmacists, which aligns with the medication-focused topics. Most learners were prescribers; however, there were a fair number of non-prescribers that received detailing (eg, office staff, administrators). Office staff can help shape clinicians’ engagement in AD by cultivating a constructive working relationship with the detailer and by consistently reinforcing the positive elements of each detailing encounter. They are commonly patient-facing and institutional policymakers, which are critical facets of the medication-use process. While research objectives and methods of measurement were variable, the articles were broadly categorized into clinician knowledge and behavior change, and patient outcomes. AD appears to increase clinician knowledge and change clinician behavior from lack of or inappropriate action to a desired action, with 91% and 68.5% of included articles finding benefit with AD for each clinician category, respectively. The impact on direct patient outcomes is less clear; the minority of studies (42.9%) found AD to be beneficial. Though analyzing the strength and risk of bias of articles are beyond the scope of a narrative review, it is important to note that less than half (40%) used a comparator or control arm. A few did not statistically evaluate some, or all, of the reported results.^{12,14,29,35,37,38,50} No effect sizes were reported for any included outcome analyses. Our findings reflect previous literature; variable interventions with less-than rigorous methodology and reporting, but an overall positive trend on desired outcomes.^8,9

The inconsistent methodology could be attributed to the absence of standardized methods for evaluating the clinical impact of AD. However, there are general best practices and recommendations. The Veterans Affairs PBM National Academic Detailing Service, which is comprised of pharmacists and is a large detailing groups in the U.S., has published an online implementation guide that provides general recommendations for short, medium and long term impact evaluations.⁵³ The National Resource Center for Academic Detailing (NaRCAD), who serves as a resource center supporting AD programs, provided sample clinician surveys to measure clinical knowledge or behavior intent-to-change.⁵⁴ There are also two validated surveys in the AD space, one being the Provider Satisfaction and Academic Detailing (PSAD), which focuses on clinician satisfaction of the detailer, but does have one question about behavioral intent-to-change (“My practice is likely to change as a result of this visit”).⁵⁵ The other is the Detailer Assessment of Visit Effectiveness (DAVE) that evaluates the detailer’s perception of the clinician takeaway (“This visit was informative/useful to the provider,” “the provider is willing to implement the key points”).⁵⁶ One article used the DAVE as an outcome evaluation method³⁰ and another the PSAD³⁷; several interventions were done within the VA system^21,22,39 and in Canada^13-15,23 with access to national claims databases; methodology was similar amongst the latter article groupings. However, most articles included in the review did not explicitly state adherence to any best practices, highlighting the organization-specific, individualized approach to most AD research.

While many continuing education interventions can improve knowledge, literature to support actual behavior change or patient outcomes is necessary to ensure the translation of that knowledge. Our findings expand on the report of Samuel et al, who evaluated all continuing professional development types on the Kirkpatrick level (3 – provider behavior, or 4 – patient outcomes) and found AD to be an effective component influencing these outcomes.⁵⁷ In our review, the most common outcome evaluated was how AD can change clinician behavior. Overwhelmingly, the results show the positive influence of AD on behavior change. This is of particular importance when considering the topics evaluated; safe opioid prescribing, naloxone use, antibiotic stewardship, and cancer screenings, for example. AD is an attractive option for educating clinicians on complicated medication-use subjects, as reflected by the frequency of pharmacist detailers. The medication use system can be extremely complicated and costly; the United States spends 73% more per capita than other countries on prescription drugs and other medical goods (such as medical equipment) without a corresponding improvement in health.⁵⁸ AD can help streamline the medication use process to focus on health outcomes and cost containment.^1-3 The detailer can consolidate the information into what the clinician needs to know, education can be given in the clinician’s practice setting, and it allows for exchange of information between clinician and detailer to tailor practice pearls. AD’s purpose is to frame knowledge in an actionable away, empowering the clinician to implement desired actions or reduce undesired ones. It is logical that the most frequently detailed topics were complex and multi-faceted; for example, common reasons for not prescribing naloxone are reported to be difficult conversations with and educating patients.⁵⁹ AD can provide personalized tools to help clinicians develop these conversations. Other forms of continuing education, such as didactic lectures at conferences or asynchronous recordings, do not allow for such nuance.

While the body of literature supporting AD as an effective educational intervention is large, that body could be strengthened with a uniform methodology for AD research. Though the topic and outcome of interest may change, there are several reporting criteria that should be clearly stated. To improve the strength of results, control groups or pre-and post-AD intervention data should be collected and analyzed. The AD intervention should be clearly defined, including type and number of detailers and learners who completed the intervention. If surveys are used for data collection, investigators should ensure good survey research practices, such as pilot testing to maximize readability and clarity.⁶⁰ Repeated measures would assist in understanding the impact of AD over time; many educational interventions require repeat exposure to create sustained change. Lastly, it would be prudent to focus more research on the direct impact of AD on the patient. Its impact on patient outcomes is still unclear based on our review. For example, in one article included in our analysis, education on safe antipsychotics prescribing among nursing home residents did not result in less prescribing but among included patients, there were lower pain and depression scores.¹⁵ However, in similarly structured research, education on safe opioid and benzodiazepine prescribing did not correlate to changes in prescribing or outcomes on drug-related harms.^13,14 More research is needed. While factors that influence patient outcomes are multifactorial, it is nevertheless a worthy outcome to explore for detailing programs that have resources for more complex research (a statistician will more than likely be needed⁵³) to add meaningfully to the literature.

There are limitations to this review. First, articles that included multi-modal interventions plus AD were excluded; though not the purpose of this article, insights into the best method of implementing AD may have been missed. This exclusion was done intentionally to evaluate the educational aspect of AD alone, ultimately providing generalizability to institutions or programs looking to support AD but not having access to additional strategies (such as clinician-specific prescribing data or clinical decision support tools). Relatedly, given the nature of a narrative review, the methodology could have resulted in beneficial articles being missed. Publication bias could have skewed results “in favor” of AD. Categorizing the outcomes studied as “in favor” or “not in favor” was based on the article authors’ conclusions and could lead to interpretation bias. However, given the breadth and variety of literature that exists for AD, the broad overview and narrative review synthesis adds to the literature by analyzing AD’s impact on clinician and patient outcomes.

Conclusion

This review found that AD can improve clinician knowledge, behavior, and potentially patient outcomes on a variety of topics in a variety of settings. The literature supports pharmacists as academic detailers. Translating best practices for AD research into standardized criteria could strengthen the literature to support AD as an educational intervention. More research is needed to determine AD’s downstream effects on direct patient care and outcomes.

Footnotes

ORCID iDs

Dima Cheetany

Brianna McQuade Hudak

Ethical Considerations

Institutional Review Board submission/approval were not required for this literature review article.

Author Contributions

SP made substantial contributions to the conception of work, analysis of data, draft and revision of manuscript. SS and LO made substantial contributions to the conception of work, analysis of data, and draft of manuscript. DC, AM, CP, and TG made substantial contributions to the conception of work and analysis of data. BMH made substantial contributions to the conception of work, analysis of data, draft and revision and finalizing of manuscript. All authors approve the submitted version and agree to be personally accountable for their own contributions to ensure accuracy and integrity.

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Data Availability Statement

The datasets used and analyzed during the current study are available from the corresponding author on reasonable request.*

Declaration of Generative AI and AI-Assisted Technologies in the Writing Process

During the preparation of this work the authors used ChatGPT in order to streamline text and improve readability. After using this tool/service, the authors reviewed and edited the content as needed and take full responsibility for the content of the published article.

Appendix

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