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# Interactions between physicians and the pharmaceutical industry generally and sales representatives specifically and their association with physicians’ attitudes and prescribing habits: a systematic review

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### Abstract

##### Objectives

The objective of this review is to explore interactions between physicians and the pharmaceutical industry including sales representatives and their impact on physicians’ attitude and prescribing habits.

##### Data sources

PubMed, Embase, Cochrane Library and Google scholar electronic databases were searched from 1992 to August 2016 using free-text words and medical subject headings relevant to the topic.

##### Study selection

Studies included cross-sectional studies, cohort studies, randomised trials and survey designs. Studies with narrative reviews, case reports, opinion polls and letters to the editor were excluded from data synthesis.

##### Data extraction

Two reviewers independently extracted the data. Data on study design, study year, country, participant characteristics, setting and number of participants were collected.

##### Data synthesis

Pharmaceutical industry and pharmaceutical sales representative (PSR) interactions influence physicians’ attitudes and their prescribing behaviour and increase the number of formulary addition requests for the company’s drug.

##### Conclusion

Physician–pharmaceutical industry and its sales representative’s interactions and acceptance of gifts from the company’s PSRs have been found to affect physicians’ prescribing behaviour and are likely to contribute to irrational prescribing of the company’s drug. Therefore, intervention in the form of policy implementation and education about the implications of these interactions is needed.

### Most cited references72

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### Physicians and the pharmaceutical industry: is a gift ever just a gift?

(2000)
Controversy exists over the fact that physicians have regular contact with the pharmaceutical industry and its sales representatives, who spend a large sum of money each year promoting to them by way of gifts, free meals, travel subsidies, sponsored teachings, and symposia. To identify the extent of and attitudes toward the relationship between physicians and the pharmaceutical industry and its representatives and its impact on the knowledge, attitudes, and behavior of physicians. A MEDLINE search was conducted for English-language articles published from 1994 to present, with review of reference lists from retrieved articles; in addition, an Internet database was searched and 5 key informants were interviewed. A total of 538 studies that provided data on any of the study questions were targeted for retrieval, 29 of which were included in the analysis. Data were extracted by 1 author. Articles using an analytic design were considered to be of higher methodological quality. Physician interactions with pharmaceutical representatives were generally endorsed, began in medical school, and continued at a rate of about 4 times per month. Meetings with pharmaceutical representatives were associated with requests by physicians for adding the drugs to the hospital formulary and changes in prescribing practice. Drug company-sponsored continuing medical education (CME) preferentially highlighted the sponsor's drug(s) compared with other CME programs. Attending sponsored CME events and accepting funding for travel or lodging for educational symposia were associated with increased prescription rates of the sponsor's medication. Attending presentations given by pharmaceutical representative speakers was also associated with nonrational prescribing. The present extent of physician-industry interactions appears to affect prescribing and professional behavior and should be further addressed at the level of policy and education.
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### Pharmaceutical Industry-Sponsored Meals and Physician Prescribing Patterns for Medicare Beneficiaries.

(2016)
The association between industry payments to physicians and prescribing rates of the brand-name medications that are being promoted is controversial. In the United States, industry payment data and Medicare prescribing records recently became publicly available.
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### Information from Pharmaceutical Companies and the Quality, Quantity, and Cost of Physicians' Prescribing: A Systematic Review

Introduction Pharmaceutical companies in the United States spent about US$57.5 billion, or 24.4% of their revenue, on promotion in 2004 [1]. One estimate of total promotional expenditure in France for 2004 is €2,908 million (12.2% of revenue). However, another estimate is that pharmaceutical detailing cost €3,300 million and accounted for 75% of the overall cost of promotion in that year making promotion 17.3% of revenue [2]. Expenditure on promotion is aimed at maximizing returns for the corporation and shareholders [3]. The industry claims that promotion also provides scientific and educational information to healthcare professionals: “Appropriate marketing of medicines ensures that patients have access to the products they need and that the products are used correctly for maximum patient benefit. Our relationships with healthcare professionals are critical to achieving these goals because they enable us to – inform healthcare professionals about the benefits and risks of our products to help advance appropriate patient use, provide scientific and educational information, support medical research and education” [4]. There is a wide range of views amongst health professionals about pharmaceutical promotion. Qualitative studies suggest that many perceive pharmaceutical promotion to be a useful and convenient source of information [5]–[7]. Some doctors deny that they are influenced by pharmaceutical company promotion or claim that it influences others but not themselves [8]–[10]. Nonetheless, many of these physicians are willing to give significant amounts of time to engaging in promotional activities [11]. By contrast, several professional organisations have called for more control of promotional activities [12],[13] because of evidence that promotion may be misleading [14]–[17]. The evidence base illuminating these conflicting views is growing. In 2000, Wazana identified eight studies linking pharmaceutical promotion to increased prescribing, “nonrational prescribing,” and increased prescribing costs [18]. A 2005 review concluded that promotion influences the prescribing by physicians in training [19], and a second review in the same year concluded that sales representatives influence prescribing [20]. Those previous reviews are now out of date, narrowly focused, or only partially assessed the relationship between information (promotional or otherwise) from pharmaceutical companies and prescribing costs and quality. The objective of this review is to examine the relationship between exposure to information directly provided by pharmaceutical companies and the quality, quantity, and cost of physicians' prescribing. Methods Criteria for Including Studies Randomized controlled trials, time series analyses, before–after studies, cohort studies, case-control studies, ecological studies, and cross-sectional studies were eligible for inclusion. Studies were included if they had both a measure of exposure to any type of information directly provided by pharmaceutical companies and a measure of physicians' prescribing. We excluded studies that looked at the indirect provision of information, for example, through continuing medical education courses that were funded by unrestricted grants from pharmaceutical companies. Case series, case reports, abstracts, news items, and short reports were excluded. Exposure to information directly provided by pharmaceutical companies was defined as including pharmaceutical sales representative visits, advertisements in journals or prescribing software, presentations from pharmaceutical companies to groups, meetings sponsored by pharmaceutical companies, mailed information including advertisements, and participation in sponsored clinical trials. We did not include studies of other forms of promotion such as gifts or samples or studies of indirect forms of information provision such as sponsored education. The outcome measures were the quality, frequency, and costs of prescribing. Search Methods for Identification of Studies We searched Medline (1966 to February 2008), International Pharmaceutical Abstracts (1970 to February 2008), Embase (1997 to February 2008), Current Contents (2001 to 2008), and Central (The Cochrane Library Issue 3, 2007). The search strategy below was devised for Medline by an expert librarian at the University of Queensland and adapted for the other databases: (exp Drug Industry OR exp Advertising OR exp Gift Giving OR exp “Conflict of Interest”) AND (exp Prescriptions, Drug/OR (prescribing or prescription$).mp.)) We looked for additional articles in the references of each retrieved article including review articles in an iterative, exhaustive process. Efforts to find additional studies included placement of messages on email drug discussion groups, contacting experts in the field, and asking Australian subsidiaries of international pharmaceutical companies for information. All languages were considered. Selection of Studies The title and abstract, if available, of all articles detected by the database searches were reviewed by two authors. Articles that possibly met the inclusion criteria were retrieved and subjected to a formal inclusion process independently by two different authors. Differences of opinion were resolved by consensus and if necessary a third author was involved. Quality Appraisal Articles meeting inclusion criteria were appraised for methodological quality independently by two authors. Randomized studies were assessed for adequacy of randomization method, allocation concealment, blinding, follow-up, and use of intention to treat analyses [21]. Controlled cohort and case-control studies were assessed using the Newcastle-Ottawa scales [22]. For other nonrandomized studies, quality appraisal included assessment of sources of bias, for example presence of a control group, selection methods, control of confounding, response rate (>80%), and use of appropriate statistical tests [23]. Studies were only excluded from the review if two authors found there was insufficient information to appraise their quality. Disagreements were resolved by discussion with a third author. Data Extraction For included studies, two authors independently extracted data on study site, dates of data collection or publication, types of participants (primary care providers, specialists, and residents), study medication(s), exposure to information from pharmaceutical companies, and prescribing outcomes. Reporting of Results For quality of prescribing we accepted the original authors' definitions of what constituted more (or less) appropriate prescribing. We divided studies into two groups on the basis of whether the information was delivered with or without conventional promotional techniques. This distinction was made because information delivered with versus without conventional promotion may produce different effects on prescribing. Conventional promotional techniques were defined as advertisements (in journals and software), representatives' visits, attendance at pharmaceutical sponsored meetings, and mailed information from pharmaceutical companies. In addition, we included in this group studies looking at total promotional investment/summated scores of commercial information use/general use of commercial sources. The other group of studies included warning letters, participation in company sponsored trials, and representatives' visits for nonpromotional purposes. A narrative synthesis of results was undertaken following the MOOSE guidelines and meta-analysis performed where appropriate data were available (Text S1) [24]. The unit of analysis was defined as the combination of exposure to a type of information from a pharmaceutical company (for example pharmaceutical sales representative visits or journal advertisements) and a type of prescribing outcome (quality, frequency, and cost of prescribing). Thus studies were treated as a single unit of analysis if they measured the same type of exposure and the same type of outcome regardless of the number of drugs covered in each study. We classified each analysis as positive or negative rather than no association detected if the p value was less than 5% (p 80% Confounders Controlled Appropriate Statistical Measures Adequate Follow-Up Controlled Cohort Andersen [37] a No Yes Yes Yes Yes Yes Yes Case-Control Spingarn [39] No Yes No Yes (100%) Yes Yes Yes Chren [38] No Yes Yes Yes (88%) Yes Yes Yes a Received research funding from a pharmaceutical company. 10.1371/journal.pmed.1000352.t003 Table 3 Quality appraisal of included studies: time-series analyses. Time-Series Analysis Study (First Author Name) Prospective Design Control Group Confounders Controlled Selection Bias Minimized Appropriate Statistical Measures Econometric Ching [78] No No Yes Yes Yes Venkataraman [40] No No Yes Yes Yes Windmeijer [41] No No Yes Yes Yes Chintagunta [42] No No Yes Yes Yes Narayanan [43] No No Yes Yes Yes Donohue [44] No No Yes Yes Yes Mizik [45] No No Yes Yes Yes Manchanda [46] No No Yes Yes Yes Manchanda and Chintagunta [47] No No Yes Yes Yes Berndt [48] No No Yes Yes Yes Rosenthal [79] No No Yes No Yes Azoulay [49] No No Yes Yes Yes Rizzo [50] No No Yes No Yes Hurwitz [51] No No Yes Yes Yes Mackowiak [52] No No No Yes Yes Leffler [53] No No Yes Yes Yes Telser [54] No No Yes Yes Yes Other Spurling [55] Yes No No No Yes Stafford [56] Yes No No Yes No Charbit [34] No No No Yes No Auvray [57] No No No No No Cleary [26] Yes Yes Yes No Yes Soumerai [58] No Yes No Yes No 10.1371/journal.pmed.1000352.t004 Table 4 Quality appraisal of included studies: before–after studies. Before–After Study (First Author Name) Prospective Design Control Group Response Rate >80% Confounders Controlled Selection Bias Minimized Hemminki [25] No Yes No (68%) No Yes Schwartz [27] No Yes Unsure No Unsure Kazmierczak [59] No No NA No Yes Orlowski [28] No No Yes (100%) Yes No Bowman [60] Yes No No (43%–77%) No No 10.1371/journal.pmed.1000352.t005 Table 5 Quality appraisal of included studies: cross-sectional studies (no control group). Cross-Sectional Study (First Author Name) Prospective Design Response Rate >80% Confounders Controlled Selection Bias Minimized Appropriate Statistical Measures Henderson [29] a No Yes Yes Yes Yes Greving [30] No Yes (96%) Yes Yes Yes Kreyenbuhl [31] Yes No (58%) No Yes Yes de Bakker [61] No Unsure Yes Yes Yes Steinman [62] No Yes Yes No Yes Canli [32] Yes No (79%) No Yes Yes Verdoux [63] Yes No (24%) Yes No Yes Muijrers [64] Yes No (71%) Yes Yes Yes Huang [65] No NA No No Yes Watkins [66] Yes No (64%) Yes Yes Yes Prosser [67] Yes No (73%) No Yes No Caamano [68] Yes No (75%) Yes Yes Yes Gonul [69] Yes NA Yes Unsure Yes Mansfield [82] Yes No (6%) No No Yes Jones [70] Yes NA No No No Caudill [71] Yes No (28%) Yes Yes Yes Berings [72] Yes No (28%) Yes No Yes Lurie [73] Yes No (75–78%) Yes Yes Yes Health Care Communications 1989a [80] No Unsure No No No Peay [33] No No (52%–70%) Yes Yes Yes Blondeel [81] Yes No (30%) Yes Yes Yes Haayer [74] Yes Yes (90%) Yes No Yes Walton [75] Yes Unsure No Yes Yes Dajda [76] No NA No Yes Yes Becker [77] Yes Yes (84%) Yes Yes Yes a Received research funding from a pharmaceutical company. General Characteristics of Studies The most common study design was cross-sectional (24/58 studies, 41%). There were also two cluster randomized controlled trials, one controlled-cohort study, two case-control studies, 24 time-series analyses, and five before–after studies. Over half (55%) of the studies were conducted in the United States. Characteristics of included studies are outlined in Table 6. 10.1371/journal.pmed.1000352.t006 Table 6 Characteristics of included studies (by study design, year of publication, then sample size). Study Design Study (First Author Name) Study Site, Year Participants (n) Medication Intervention/Exposure Outcome Measure(s) RCT Freemantle [35] a UK 2000 PCPs (79: 40 intervention, 39 control) Lansoprazole versus omeprazole PSR visits: PSRs instructed by local health authority (one visit); controls: normal detailing Switch from omeprazole to less costly lansoprazole Dolovich [36] a Canada 1999 PCPs and pediatric specialists (641 in intervention group and 574 in control group) Antibiotics for otitis media PSR visits, PSRs trained in evidence-based education by academic department of a university; Control group: no detailing Market share of antibiotics for otitis media Controlled cohort studies Andersen [37] b Denmark 1999–2003 297 PCPs (26 intevention/271 controls) Asthma medications Participation in a RCT funded by a pharmaceutical company Prescribing trial drug; Adherence to prescribing guidelines Case-control Studies Spingarn [39] US° 1990 Hospital residents (75) Medications for Lyme disease Intervention: presentation by academic who was also a pharmaceutical executive; Controls: did not attend Appropriateness of intention to prescribe for mild versus severe Lyme disease Chren [38] US 1989–1990 Physicians (40 cases, 80 controls) Addition to hospital formulary PSR visits; cases added to formulary, controls did not Addition of detailed drug to hospital formulary Time series analyses (econometric) Ching [78] c Canada 1993–1999 Physician's prescribing antihypertensives in Canada Antihypertensive medications (angiotensin converting enzyme inhibitors and diuretics) PSR visits (n minutes) Market share; Elasticity of demand Venkataraman [40] b Not stated 2002–2003 Physicians (2,774) Statins, coagulation drugs, erectile dysfunction drugs, gastrointestinal drugs, placebo PSR visits (total number); attendance at pharmaceutical; sponsored meetings; (total number attended) n prescriptions Windmeijer [41] c Netherlands 1995–1999 PCPs and psychiatristsd 11 therapeutic markets (over 50% of the Dutch drug market) PSR visits (expenditure); Journal advertisements (expenditure); Mail (expenditure) n prescriptions; Cost of prescriptions Chintagunta [42] c US, UK, Germany, France, Italy 1989–1999 Prescribers of antidepressant medications Fluoxetine, sertraline, paroxetine PSR visits (expenditure) Market share (sales) Narayanan [43] e US 1993–2001 All prescribers of antihistamines in USd 2nd generation antihistamines: loratidine cetirizine, fexofenadine PSR visits (total expenditure) New prescriptions per month Donohue [44] c US 1997–2000 11,000 office and hospital physicians First prescriptions of 6 antidepressants Monthly spending on PSR detailing New prescriptions Mizik [45] b US 2004 Physicians (74,075) 3 unknown drugs PSR visits n new prescriptions for the three study drugs Manchanda [46] b US 1999–2001 Physicians (1,000), 18.5% specialists (for study drug), 60.1% PCPs, 21.4% other specialists, controls (1,000) Drug unknown PSR visits Numbers of prescriptions Manchanda and Chintagunta [47] b US 1996–1998 Physicians (1,000), 11% specialists (for study drug), 59% PCPs, 30% other specialists Drug unknown PSR visits n prescriptions; Prescriptions of specialists versus primary care physicians versus other specialists; Prescriptions by male and female physicians Berndt [48] c US 1977–1993 All US physicians H2 antagonist antiulcer drugs (cimetidine, ranitidine, famotidine, nizatidine) PSR visits (min) Sales volume (units of average daily dose) and market share; Elasticity of demand Rosenthal [79] c US 1996–1999 Large sample of office and hospital physiciansd Medications prescribed in primary care PSR visits (expenditure) Sales of detailed medications per month Azoulay [49] c US 1977–1993 All prescribing physicians H2 antagonist antiulcer drugs (cimetidine, ranitidine, famotidine, nizatidine) PSR visits; Journal advertisements Market share for the four H2 antagonists (patient days of therapy) Gonul [69] c US 1989–1994 Physiciansd One medication for a particular indication “relatively more common among the elderly” PSR visits (min) n prescriptions; Cost of Prescriptions Rizzo [50] c US 1988–1993 All prescribers of antihypertensives in the USd Antihypertensive medications PSR visits (expenditure) Sales of detailed medication; Price elasticity; Quadratic term for sales Hurwitz [51] c US 1978–1983 Specialists and PCPs prescribing promoted drugsd Brand and generic drugs Total promotional investment in PSR visits, journal advertising, direct mail advertising Market share held by original brand; Market share held by generic competitors (measured in n pills sold) Mackowiak [52] c US 1977–1981 Office based physicians across the USd Benzodiazepines for anxiety; Diuretics for hypertension PSR visits (expenditure); Journal advertisements (expenditure) Expenditure on prescriptions; Market size and market share Leffler [53] c US 1968–1977 Not statedd 51 new products Total promotional outlay (PSR visits, journal advertising) Market share 2 y after market entry; Market share in 1977 for drugs introduced since 1968 expressed Telser [54] c US 1963–1972 All prescribing physiciansd Prescription medications in: the hospital market and drugstore market Promotional intensity: ratio of total promotional outlays/total sales (includes PSR visits, journal advertising, direct mail) Proportion of sales for entrant drugs Time series analyses (other) Spurling [55] Australia 2004–2005 PCPs (7) Medications prescribed in primary care PSR visits; Promotional items in PCP surgeries Generic prescribing (% of total) Stafford [56] c US 1996–2002 Physicians (3,500) Alpha-blockers PSR visits (expenditure) Prescriptions Charbit [34] France 1991–2001 Prescribing physicians in Franced 6 classes of antihypertensive medications Journal advertising (n pages) Drug sales for each of the six classes of antihypertensive medications Auvray [57] e France 1992–1998 PCPs, ear nose throat surgeons, chest physicians, psychiatrists-1,600 Macrolide antibiotics and psychoanaleptic antidepressants Total promotional investment n prescriptions Cleary [26] US 1988 Physicians prescribing 3rd generation cephalosporinsd Ceftazidime, cefriaxone, cefotaxime PSR visits New prescriptions; n doses Soumerai [58] e US 1974–1983 All propoxyphene prescribers in USAd Propoxyphene PSR visits (to warn about risks of propoxyphene) Sales of propoxyphene; No-refill rates of prescriptions Before–after Studies Hemminki [25] e Estonia 2000 Gynecologists and PCPs (342) Hormone replacement therapy Journal advertisements; Pharmaceutical company-sponsored medical education Probability of detailed drug being prescribed Schwartz [27] US 1999–2000 Psychiatry residentsd Psychiatric medications PSR detailing (12 wk period when residents were detailed versus 12 wk with no detailing) New prescriptions Kazmierczak [59] US 1996 Physicians (60) Tramadol Drug company letter to physicians warning about tramadol seizure risk Prescriptions for tramadol in high risk patients Orlowski [28] US 1992 Hospital physicians (20) Intravenous hospital medications called A (antibiotic) and B (cardiovascular drug) Attendance at pharmaceutical sponsored meetings (all expenses paid trips to vacation site) n prescriptions before and after the sponsored meetings Bowman [60] US date not stated Physicians (374) Calcium channel blockers and beta-blockers PSR sponsored continuing medical education course Self-reported new prescriptions Cross-sectional studies Henderson [29] Australia 2003–2005 PCPs (1,336) 7 advertised pharmaceutical products Advertising on clinical software n prescriptions Kreyenbuhl [31] US 2003–2004 Psychiatristsd Antipsychotic medication PSR visits; Attendance at pharmaceutical sponsored meetings Use of “switch” or “add” strategies in treatment of refractory schizophrenia de Bakker [61] Netherlands 2001 PCPs (138) Medications prescribed in primary care PSR visits; Reliance on commercial sources of information n prescriptions Steinman [62] US 1995–1990 Physicians (97) Gabapentin PSR visits Intention to prescribe gabapentin Greving [30] Netherlands 2003 PCPs (70) Angiotensin II receptor blockers PSR visits; Journal advertisements; Attendance at pharmaceutical sponsored meetings New prescriptions of this drug Canli [32] Turkey 2001 PCPs (316) Antibiotics for acute tonsillopharyngitis PSR visits Intention to prescribe antibiotics Verdoux [63] France 2004 PCPs (848) Antipsychotic medication PSR visits Initiation of antipsychotic medication in a 1-mo period Muijrers [64] Netherlands 2000–2001 PCPs (1,434) Medications prescribed in primary care PSR visits Quality of prescribing (determined by panel of experts) Huang [65] US 2001–2003 Resident physiciansd Antidepressants Sponsorship of resident conferences Prescription of antidepressants from sponsoring companies Watkins [66] UK 1995–1996 PCPs (1,714) Medications prescribed in primary care PSR visits (at least once per week); Journal advertisements; Reading written material from pharmaceutical companies Cost of prescriptions Prosser [67] UK 1999–2000 PCPs (107) New medications prescribed in primary care PSR visits; Journal advertisements/mailings (considered together) New drug prescriptions (high/medium/low prescribers) Caamano [68] e Spain 1993 Physicians (234) All prescribing PSR visits n prescriptions ; Cost of prescriptions Mansfield [82] Australia 1999 PCPs (1,174) Medications used in primary care PSR visits (self-report); Attendance at pharmaceutical sponsored meetings (self-report) Quality use of medicine score Jones [70] UK 1995–1997 PCPsd Nine new drugs Journal advertisements Prescribing data for the advertised drugs Caudill [71] US 1996 PCPs (446) Medications for acute bronchitis, hypertension and urinary tract infection PSR visits (frequency of use) Cost of prescribing Berings [72] Belgium date not stated PCPs (128) Benzodiazepines PSR visits (n visits in last 4 wk) Prescription of benzodiazepines Lurie [73] US 1987–1988 Hospital physicians (240 faculty staff and 131 residents) Hospital medications PSR visits ( 5 min) Change in prescribing habit Addition to hospital formulary Healthcare Communications [80] US 1987–1988 Physicians (1184) Newly promoted medications Journal advertisements (awareness of) Market share Peay [33] Australia 1981 PCPs (74) and specialists (50) Temazepam PSR visits (contact versus no contact); Direct mailing; Attendance at PSR-sponsored function Temazepam prescription Blondeel [81] Belgium 1987 PCPs (358) Medications prescribed by PCPs PSR visits Response to 8 simulated patients where prescribing was not advisable. Quality index compiled based on GP medication choices by expert panel (range 1–100) Proneness to prescribe (proxy for prescribing frequency) Haayer [74] Netherlands 1979 PCPs (116) Medications that would result from 8 case-histories devised by a panel PSR visits; Journal advertisements; Companies' mailings Prescribing rationality based on a composite scale (drug choice, duration, dose and use of combination products) Walton [75] US 1976–77 PCPs (29%) and specialists (71%) (1,000 total) 186 different medications Journal advertisements Prescriptions of advertised drugs (intention to prescribe) Dajda [76] UK 1975 PCPs in UKd Branded advertised drugs in the UK Mailed advertisements (number in 1 y) n prescriptions Becker [77] US 1970 PCPs (29), internists (3). osteopathic physicians (5) Chloramphenicol, equagesic, vitamin B12, methylphenidate, oral contraceptives Use of journal advertisements PSR visits (frequency) Proportion of chloramphenicol scripts. Physicians' self-reported prescribing behaviour. a Experimental partnerships between pharmaceutical company and health authority or academic department. b Data from pharmaceutical company. c Information from a market research company. d Total number unknown. e Using national prescribing data. PCP, primary care provider; RCT, randomized controlled trial. Pharmaceutical Company Information and Prescribing Quality Prescribing quality was measured by ten studies with 14 units of analysis [37],[39],[58],[59],[61],[64],[74],[77],[81],[82] (Table 7). Quality was assessed in four distinct ways: quality scoring of prescribing decisions, guideline adherence, prescribing appropriateness of an individual drug class, and prescribing range. Three studies used quality scores calculated by coding physicians' drug choices in responses to clinical vignettes [74],[81],[82]. One of these used an expert panel to derive a quality index (1–100) judging primary care providers' prescribing in response to both their actual prescribing and clinical vignettes [81]. In the latter study learning about the drug first from pharmaceutical sales representatives was associated with lower quality of actual prescribing but the number of pharmaceutical sales representatives' visits was not. There was no significant association between primary care providers seeing more pharmaceutical sales representatives or first learning about the drug from pharmaceutical sales representatives and lower quality responses to case vignettes [81]. Another study combined scales examining indication, effectiveness, safety, dosage, duration, and polypharmacy to produce a seven-point scale measuring rationality of prescribing [74]. Primary care providers' self-reported reliance on pharmaceutical companies for information was associated with lower quality scores [74]. A third study used a quality score for a hypertension scenario where thiazides were considered very appropriate and all other drug groups were considered very inappropriate [82]. Self-reported rates of attendance at pharmaceutical company-sponsored meetings were associated with slightly lower quality scores, but self-reported rates of pharmaceutical sales representative visits had no significant association [82]. 10.1371/journal.pmed.1000352.t007 Table 7 Relationship between exposure to information from drug companies and prescribing quality (by year of publication and then study design/size). Exposure to Information from Drug Company Study (First Author Name) Result in Exposed Group Versus Controls (Where Applicable) Change in Prescribing Quality Result Effect of PSR visits de Bakker [61] Wider prescribing range was associated with more visits from PSRs in the last 4 wk Beta coefficient +0.18 (p 0.1 n PSRs received was associated with poorer quality index; p>0.05 Based on prescriptions for actual patients: First contact with a drug from the pharmaceutical industry was associated with reduced quality of prescribing; p 0.1 Becker [77] Fewer visits from PSRs/month were not associated with a change in the appropriateness of prescribing Gamma statistic; 0.04, not statistically significant Attendance at pharmaceutical sponsored meeting Mansfield [82] Attendance at pharmaceutical sponsored meetings was associated with lower quality scores Pearson correlation coefficient of 0.0635; p = 0.043 Spingarn [39] Attendees at a sponsored talk about Lyme disease were less likely to choose appropriate oral antibiotics for mild Lyme disease than nonattendees 0% of attendees (n = 22) chose appropriate antibiotics compared to 21% (n = 53) of nonattendees; Fisher exact test: p = 0.027 For attendees and nonattendees of a sponsored talk about Lyme disease there was no difference in choice of acceptable treatment for Lyme disease with central nervous system signs OR = 3.2 (95% CI 0.8–19.2) Attendees of a sponsored talk about Lyme disease were more likely to appropriately choose the sponsoring company's treatment for Lyme disease complicated by 2nd degree heart block OR = 7.9 (95% CI 2.4–29.3) Journal advertisements Becker [77] Infrequent use of journal ads as a source of prescribing information by doctors was not associated with a change in the appropriateness of prescribing Gamma statistic 0.373, not statistically significant Total promotional investment/summated scores of commercial information use/general use of commercial sources de Bakker [61] There was a positive correlation for how frequently doctors used the pharmaceutical industry as a source of information and the range of drugs they prescribed Beta coefficient +0.15 (p 4 times in the preceding month was not associated with the “add” rather than “switch” strategy for antipsychotic medication prescribing OR 1.22 (95% CI 0.68–2.20) Steinman [8] PSR visits of ≤5 min versus >5 min were not associated with intention to prescribe No association detected PSR visits to doctors in a small group were associated with increase in more frequent intention to prescribea OR 12.9 (95% CI 1.2–138.8)b PSR visits were associated with increased gabapentin prescribing if physician's previous gabapentin prescribing was nila OR 15.1 (95% CI 3.9–58.2)b reference group - medium prescribers of gabapentin PSR visits were associated with increased gabapentin prescribing if physician's previous gabapentin prescribing was lowa OR 8.6 (95% CI 2.4–31.4)b reference group, medium prescribers of gabapentin Venkataraman [40] PSR visits were associated with increased n prescriptions Beta coefficient: +0.944 (significant with a 95% CI) Canli [32] PSR visits were associated with increased antibiotic prescribinga p = 0.0001* Chintagunta [42] Higher levels of detailing were associated with higher market share for that brand in the three of the countries studied and no significant difference in two others Detailing related change in market share; US; beta coefficient +0.06; t statistic 3 (p 0.05); UK; beta coefficient +0.29; t statistic 1.61 (p>0.05) Narayanan [43] PSR visits were associated with an increase in market share 1% increase in expenditure on detailing was associated with increases in market shares for promoted drugs ranging from 0.11% to 0.14% (p 0.05) More frequent PSR visits were associated with diminishing increases in prescribing Quadratic term for PSR visits: −0.49; t statistic −0.49 (p>0.05) Berndt [48] PSR detailing were associated with increased cumulative days of therapy Beta coefficient +0.7414; t statistic 43.12 (p 0.05)* Rizzo [50] PSR visits were associated with increased prescription sales Beta coefficient +0.28; t statistic 4.19 (p 0.05) Chren [38] PSR meetings were associated with a formulary request Multivariate result: OR = 3.4 (95% CI 1.8–6.6); p 0.10 (coefficient not presented where result not significant) PSR visits for faculty staff for less than 5 min were not associated with an addition to the hospital formulary Logistic regression coefficient 0.014; p = 0.06 PSR visits for faculty staff for more than 5 min were not associated with an addition to the hospital formulary p>0.10 (coefficient not presented where result not significant) PSR visits for residents for less than 5 min were associated with more prescribing Logistic regression coefficient 0.049; p = 0.003 PSR visits for residents for more than 5 min were not associated with a change in prescribing p>0.10 (coefficient not presented where result not significant) PSR visits for residents for less than 5 min were not associated with an addition to the hospital formulary p>0.10 (coefficient not presented where result not significant) PSR visits for residents for more than 5 min were not associated with an addition to the hospital formulary p>0.10 (coefficient not presented where result not significant) Peay [33] PSR visits were associated with temazepam prescription Multivariate regression: −0.35 (p 0.1 Based on prescriptions for actual patients: First contact with a drug from the pharmaceutical industry was not associated with proneness to prescribe p>0.1 Number of PSRs received was associated with proneness to prescribe p 0.05 The promotional intensity for new products introduced over a 9-y period was associated with increased market share for the entrant products Beta coefficient +1.25; t statistic 2.35, p 0.05) Hospital: beta coefficient +0.608; t statistic +1.20 (p>0.05) Information delivered without conventional promotion Andersen [37] Participation in pharmaceutical funded research was associated with increase in the sponsoring company's share of asthma drug in practices conducting the trial compared to control practices 6.7% increase (95% CI 3.0%–11.7%)b Freemantle [35] PSR visits were not associated with an increase in the prescription of the detailed medication OR = 1.04 (95% CI 0.83–1.31); p = 0.73 Dolovich [36] PSR visits were not associated with a change in the market share of amoxicillin Intervention group: +0.63% market share, control group: −0.72% market share; p = 0.15 Kazmierczak [59] Mailed warning letters regarding tramadol for those with a seizure risk were not associated with a change in prescription rates for tramadola Before mailing: 10% prescribing rate, after mailing 9% prescribing rate. Soumerai [58] PSR visits: Propoxyphene use continued a preexisting decline of about 8% a year during the time when warnings from the manufacturing pharmaceutical company were expressed by PSRs after which time this decline halted, however a statistical association was not shown. Refill rates and rates of overdose did not change following the warningsa No association detected Mailed information: Propoxyphene use continued a preexisting decline of about 8% a year during the time when warnings from the manufacturing pharmaceutical company were expressed by PSRs after which time this decline halted, however a statistical association was not shown. Refill rates and rates of overdose did not change following the No association detected a Study authors reported that exposure to information from drug companies was associated with decreased quality of prescribing. b Reported by study authors as statistically significant. c Study authors reported that exposure to information from drug companies was associated with increased quality of prescribing. *Chi-squared statistic. ACE, angiotensin converting enzyme; ARA, angiotensin receptor antagonist; CCB, calcium channel blocker; CME, continuing medical education. Conventional Promotional Techniques Pharmaceutical sales representative visits Of the 29 studies of pharmaceutical sales representative visits, 17 found only an association with increased prescribing of the promoted drug [26],[32],[33],[38],[40],[43]–[50],[63],[67],[78],[79]. None found less frequent prescribing. Of the remaining 11, six studies had mixed results: finding a significant association with more frequent prescribing for some measures but no significant association for others [27],[42],[62],[69],[73],[81]. Five did not detect any significant relationship [31],[52],[68],[72],[77]. One study did not use statistical tests for associations. It found that during the time that spending by pharmaceutical companies on promotion of a medication dropped to zero, there was also a significant drop in prescribing of that medication. However most of the decreases in promotion and prescribing occurred after the publication of evidence of problems with that medication [56]. Nine of these studies with either positive or mixed results provided insights into features of pharmaceutical sales representative visits that modified the impact of these visits on prescribing [40],[46],[49],[62],[67],[69],[73],[78]. An association with more frequent prescribing was more likely when pharmaceutical sales representatives visited groups of physicians, when physicians had lower baseline prescribing of the promoted drug [62], and when physicians had larger prescribing volumes overall [67]. Longer pharmaceutical sales representative visits to physicians and residents were also more likely to be associated with increased prescribing [69],[73]. More frequent pharmaceutical sales representative visits were associated with diminishing returns [46],[50],[69]. In addition to increasing the promoted drug's market share, pharmaceutical sales representative visits were associated with a decrease in the market share of competitor products [78]. Pharmaceutical sales representative visits were more likely to be associated with more frequent prescriptions for drugs judged more effective and also for drugs with more side effects [40]. However the authors of that study did not attempt to measure whether higher levels of use represented a change in prescribing quality. Another study found that pharmaceutical sales representative visits were associated with a greater increase in market share for new entrants into a therapeutic field than was positive scientific information [49]. Journal advertisements Four out of the eight studies measuring the effects of journal advertisements presented data but did not include statistical tests [25],[34],[70],[80]. One of these noted use of a medication class increased after pharmaceutical advertising commenced in a country where the medication class was previously available but was not promoted [25]. One study visually compared graphs of the monthly number of advertisements and prescriptions for a group of nine drugs and found no clear relationship between the extent of the advertising of a drug and the amount of prescribing by general practitioners [70]. One study found that the market share of a medication was higher amongst physicians who recognised the advertisement for that medication compared to those who did not [80]. The last study observed decreased prescribing of two drug classes at the same time that advertising decreased [34]. Of the four studies that included statistical tests, one found that journal advertisements have a more pronounced effect on market share for the advertised drug than does positive scientific information published in medical journals [49]. A cross-sectional study found contradictory results. Self-reported infrequent use of journal advertisements by physicians to learn about new medications was not associated with frequency of prescribing. However, infrequent use of journal advertisements was associated with less chloramphenicol prescribing [77]. One cross-sectional study found that physicians who recalled advertisements became prescribers of the advertised products in consistently larger proportions than those who did not recall advertisements [75]. Another study found that 9% of high prescribers of new drugs cited advertisements as an influence on their prescribing compared to 0% for low prescribers; however, this was not a statistically significant association [67]. Attendance at pharmaceutical company-sponsored meetings There were eight studies of pharmaceutical company-sponsored meetings. Five found positive associations with prescribing frequency [28],[31],[43],[60],[65]. Three studies did not detect a significant association [33],[39],[40]. Mailed information from pharmaceutical companies One of the three studies of mailed promotional material found an association with increased prescribing [76]. The others found no association [33],[67]. Advertising in clinical software A single study examined the effect of advertising in clinical practice software and found no association with prescribing frequency for six medications and less prescribing of one medication [29]. The overall result was no association between advertising and prescribing frequency. Total promotional investment Eight studies combined the outcome measures for various exposures to pharmaceutical company information or measured overall promotional investment, a proxy for the amount of exposure to information from pharmaceutical companies. Three studies found that total promotional investment was positively associated with prescribing frequency [30],[33],[51]. Two studies found both positive results and no association [53],[54]. One study did not detect an association [52]. Meta-analysis of promotional information and prescribing frequency We pooled results from a total of seven studies using a random effects model to examine whether exposure to promotion was associated with prescribing of the promoted medication. The seven study results included in the meta-analysis showed significant heterogeneity (I 2 = 91% [95% confidence interval (CI) 84%–95%], tau2 = 0.35), and therefore we have presented the forest plot without the pooled outcome (Figure 2) [29],[30],[31],[38],[39],[63],[75]. Using sensitivity analysis we found that study design, quality factors, year of publication, and type of physician did not explain this heterogeneity. One study provided two units of analysis with outcomes amenable to meta-analysis: a significant association for attendance at sponsored meetings and a nonsignificant result for pharmaceutical sales representative (PSR) visits [31]. We included only that nonsignificant result in the forest plot (Figure 2). When meta-analysis was conducted using the significantly positive result for attendance at a pharmaceutical company-sponsored meeting, the summary result and level of heterogeneity did not differ greatly. The largest difference detected was between exposure to active promotional information (OR 2.34, 95% CI 1.50–3.65), (I 2 = 59%, 95% CI 0%–86%, tau squared = 0.11) [31],[38],[39],[63] and passive promotional information (OR 1.24, 95% CI 0.72–2.15) (I2 = 89.5%, tau squared = 0.14) [29],[75]. 10.1371/journal.pmed.1000352.g002 Figure 2 Forest plot displaying the effect of promotional information on physicians' prescribing of the promoted medication. Information Delivered Without Conventional Promotion Techniques Five studies looked for associations between information delivered without conventional promotion techniques and the frequency of physicians' prescribing [35],[36],[37],[58],[59]. One randomized controlled trial partnered a local health authority and a pharmaceutical company with the aim of promoting a less expensive drug [35], and the other randomized controlled trial aimed to promote rational prescribing through evidence-based detailing by a pharmaceutical company in partnership with an academic institution [36]. Neither found an association with physicians' prescribing. A single controlled-cohort study of a pharmaceutical company-funded randomized controlled trial found that physicians' participation in recruiting subjects was associated with an increase in the number of prescriptions of the sponsoring company's drug [37]. One time-series analysis found no change in the rate of decline in the prescribing of a medication when the main manufacturer was required by a regulatory agency to deliver an educational program warning about problems with the drug via mailed information and pharmaceutical sales representative visits [58]. A cross-sectional study found no change in prescription rates following warning letters regarding drug side effects [59]. Pharmaceutical Company Information and Prescribing Costs Eight studies (Table 9) [35],[41],[50],[55],[66],[68],[69],[71] measured prescribing costs as costs per physician, price elasticity, and changes in generic prescribing (ten units of analysis). In the United States, one econometric time-series analysis found that pharmaceutical sales representative visits were associated with increased price sensitivity among physicians prescribing in one therapeutic class [69], and another found the opposite effect for hypertension [50]. A third, more recent, econometric study found that promotional outlay (the total for pharmaceutical sales representative visits, journal advertisements, and direct mail) was associated with reduced price sensitivity for primary care providers and psychiatrists in 11 therapeutic classes consisting of more than 50% of the Dutch drug market [41]. Of three cross-sectional studies, two detected an association between pharmaceutical sales representative visits and higher prescribing costs [66],[71], but one did not detect an association [68]. One study also found that low cost prescribers were more likely to have rarely or never read promotional mail or journal advertisements from pharmaceutical companies than high cost prescribers [66]. One time-series analysis found that reduced exposure to pharmaceutical sales representative visits and promotional material was associated with an increase in generic prescribing [55]. A randomized controlled trial of pharmaceutical sales representative visits in a noncommercial partnership between a pharmaceutical company and a local health authority measured physicians' prescribing costs for the target drug class and found no effect [35]. 10.1371/journal.pmed.1000352.t009 Table 9 Relationship between exposure to information from drug companies and prescribing costs (by year of publication and then study design/size). Exposure to Information from Drug Company Study (First Author Name) Results Change in Prescribing Costs Effect of PSR visits Watkins [66] High cost prescribers were more likely to see PSRs at least once a week than low cost prescribers OR 3.11 (95% CI 2.48–3.89); p<0.01a Caamano [68] There was no association between PSR visits and the cost of prescriptions Adjusted regression coefficient: 21.0; p = 0.962 Gonul [69] PSR visits were associated with increased physicians' price sensitivity Maximum likelihood estimate, 0.0012; t statistic 3 (p<0.001) Rizzo [50] PSR visits were associated with reduced price elasticity for the promoted drug Sales estimate +0.14; t statistic 2.97 (p<0.01) Caudill [71] Frequency of PSR visits was associated with higher prescribing costs Multivariate regression beta +0.155; p = 0.01 Journal advertisements Watkins [66] High cost prescribers were less likely to “rarely or never” read journal advertisements than low cost prescribers OR 0.79 (95% CI 0.64–0.98); p = 0.02a Mailed information from pharmaceutical companies High cost prescribers were less likely to “rarely or never” read mailed information than low cost prescribers OR 0.49 (95% CI 0.38–0.64); p<0.01a Total promotional investment/summated scores of commercial information use/general use of commercial sources Spurling [55] Reduced n PSR visits and volume of promotional material were associated with an increased generic prescribing at 3 and 9 mo 3 mo: OR 2.28 (95% CI 1.31–3.86); p = 0.0027a 9 mo: OR 2.07 (95% CI 1.13–3.82); p = 0.016a Windmeijer [41] Promotional outlay (PSR visits, journal advertisements, direct mail) was associated with reduced price elasticity for promoted drugs ln regression coefficient −0.0102 (se 0.0055) p<0.05 Information delivered without conventional promotion Freemantle [35] There was no significant difference in costs between the group that was detailed by PSRs instructed by a local health authority and the control group Mean difference: £122.32 (95% CI −£94.91 to £342.91) a Chi-squared statistic. Discussion Overview We found that the reported relationship between exposure to information provided directly by pharmaceutical companies and the quality, frequency, and cost of prescribing varied from case to case. However, with only one exception [39], the included studies reported that exposure to information from pharmaceutical companies was associated with either lower prescribing quality or no association was detected. Similarly, exposure to information from pharmaceutical companies was associated with either an increase in prescribing frequency or no association was detected. Three studies found that exposure was associated with increased drug sales up to a point of diminishing returns beyond which more promotion was increasingly less effective [46],[50],[69]. Finally, with only one exception [69], exposure to information from pharmaceutical companies was associated with an increase in prescribing costs or no association was detected. This review has supported, updated, and extended the findings of previous reviews regarding the effects of exposure to information from pharmaceutical companies. 38 of the 58 included studies (66%) were not included in previous systematic reviews on this topic [25],[29]–[32],[34],[35],[40]–[42],[44],[48],[49],[51]–[59],[61]–[68],[70],[72],[75],[76],[78]–[82], including seven of the ten studies of prescribing quality [37],[58],[59],[61],[64],[81],[82] and four of the seven studies of prescribing costs [35],[55],[66],[68]. Most of the included studies measured the frequency of prescribing. Amongst these, the studies of informational exposure where physicians are active participants, such as representatives' visits, sponsored meetings, or sponsored trials, more consistently found associations with higher prescribing frequency than studies of more passive exposures, such as journal advertisements and mailed information. Poor study quality precludes confident conclusions about journal advertising. However, one higher quality econometric analysis found that advertisements in journals were associated with a more pronounced effect on market share than positive scientific findings published in journals [49]. Also there are claims in the marketing literature that the relatively low cost of passive methods and their ability to synergistically increase the effectiveness of active methods makes them cost effective components of sales campaigns [84]. Limitations of Included Studies All of the included studies had design limitations (Tables 1– 5). We found only two randomized controlled trials [35],[36]. Both lacked adequate reporting of allocation concealment and blinding. These two trials did not examine standard promotional practice but instead assessed novel partnerships of government or academia with industry aiming for less expensive, higher quality prescribing. On the basis of these two negative randomized controlled trials, it seems unlikely that similar partnerships will have beneficial effects on prescribing. No definite conclusions can be extrapolated from these studies to standard promotional practice. All other included studies were observational and thus able to measure associations but not prove causation. There is a risk that reported associations may be false positives, and that statistically significant findings may not necessarily be clinically significant. One example is the study by Mizik et al. that reports only a small increase in prescriptions associated with visits from pharmaceutical sales representatives [45]. Associations may also arise from confounding, bias, or chance. False negatives or inaccurate estimation of effect sizes may result from small sample sizes, measurement errors, overly complex models, or “contamination” when prescribers who are thought to be unexposed are actually influenced by other methods. For example in a study of promotional meetings, nonattenders may be influenced by sales representatives thus reducing the difference from attenders in their prescribing. Another possible source of contamination is indirect influence by colleagues who have been influenced directly. To the extent that the measured associations are real, causality may be bidirectional. The influence of information from pharmaceutical companies on prescribing is a likely explanation for the associations given that the major purpose of pharmaceutical promotion is to influence prescribing [3]. However, it is also possible that physicians who prescribe larger quantities, more expensively or less appropriately may allow themselves to be exposed to, or attract, more promotional information. Some studies found no association between exposure to information from pharmaceutical companies and prescribing outcomes or small effect sizes that seem unlikely to be clinically significant. Some of these may be false negatives or underestimations caused by study flaws, but it is likely that information from companies sometimes has little or no effect, especially when the information is not designed to increase sales, e.g., letters warning about safety problems. Most of the studies included in this review examined single components of promotional campaigns that may have little or no effect alone but have a synergistic effect in combination with other components. Promotion may be less effective if it is used beyond the point of diminishing returns or is up against similarly effective promotion for another similar product. Given the controversial nature of this topic, there are many reasons why the studies could be biased overall in either direction. Authors may have produced results consistent with their ideological bias. Also reciprocal obligation to funders who preferred certain results may have lead to bias with or without conscious awareness. Publication and outcome reporting bias may have led to underrepresentation of negative, positive, uninteresting, or unwanted findings. Strengths and Weaknesses The strengths of this review include use of a comprehensive search strategy over multiple databases without any language exclusions. We consulted widely with experts in the field and we used validated instruments to assess quality of the studies. However, only one of the included studies was conducted in a low-income economy, as defined by the World Bank, so the effects of promotion there are less certain [33]. This study found a positive association between pharmaceutical promotion and prescribing frequency. Promotion may be more influential in these countries given the relative paucity of independent sources of information [85],[86]. Our efforts to access data that was not in the databases we searched had mixed results. Messages on e-mail discussion groups and contact with experts yielded five additional studies subsequent to the initial search [34],[43],[80]–[82] whose results were consistent with the entire review. By contrast, pharmaceutical companies did not provide us with any information that was not already in the public domain. However five studies included in this review analyzed confidential data from pharmaceutical companies and their results were also consistent with the review as a whole [33],[35],[37],[40],[46]. Given the wide range of knowledge and experience among the sources that we consulted and the expertise in our group, we are confident that we exhausted all reasonable avenues in our attempt to obtain additional literature. Data Interpretation Of the 58 studies included in this review, 38 studies reported a single unit of analysis with 25 (66%) finding significant associations between exposure to information from pharmaceutical companies and the quality, frequency, and cost of prescribing and eight (21%) finding no associations. The remaining five (13%) had multiple measures and found significant associations on some measures but not on others. The 20 studies with more than one unit of analysis reported 49 units of analysis of which 21 (43%) found significant associations, 24 (49%) found no associations, and four (8%) found mixed results. The difference between the results of the single versus multiple unit of analysis studies is significant (p<0.05 Freeman-Halton extension of the Fisher exact test). This difference may have been caused by publication bias against publication of single unit of analysis studies when no association was found. We believe the pattern of results suggests that there was little or no reporting bias for the multiple unit of analysis studies. Because the multiple unit of analysis studies found no association more often than the single unit of analysis studies, multiple mentions of the former studies in our narrative synthesis will not exaggerate the frequency of findings of significant associations. Interpretation of our meta-analysis requires caution because many studies included in the narrative synthesis could not be included in the meta-analysis. Where a sufficient number of studies could be combined, there was significant heterogeneity. The summary result has not been presented because it is unlikely to accurately reflect the true effect size of most promotional campaigns for two main reasons. First, effect sizes varied widely so it is likely that promotional campaigns often have effect sizes far from average. Second, single promotional techniques are likely to be less effective individually than campaigns employing multiple promotional methods. A sensitivity analysis found the difference between passive and active promotion is one possible cause of heterogeneity. Other possible explanations for variation in the effectiveness of promotion include variation from campaign to campaign in the relative benefits of the drug being promoted, the promoter's skills and budget, and the target group's level of resistance to promotion. Conclusions The limitations of studies reported in the literature mentioned above mean that we are unable to reach any definitive conclusions about the degree to which information from pharmaceutical companies increases, decreases, or has no effect on the frequency, cost, or quality of prescribing. In theory, advertising may be beneficial in several ways: by distributing information and thus improving the quality of prescribing [20],[78], by reducing costs through increasing price-elasticity [69], by increasing prescribing of drugs that provide better health outcomes, or by improving the cost-effective use of healthcare resources. Because of the limitations of both the included studies and this review we have not disproved those theories but we have found little evidence to support them and have found some evidence of increased costs and decreased quality of prescribing. Any conclusions about harm or benefit for patients are speculative because none of the studies that we found examined clinical outcomes. One clear conclusion from this review is that we did not find evidence of net improvements in prescribing associated with exposure to information from pharmaceutical companies. Some argue that prescribers have an ethical duty to avoid exposure to pharmaceutical promotion [13],[87]–[89]. Even ineffective promotional information may be harmful if it wastes prescribers' time or if the money spent on promotion increases the cost of medicines [90]; this is of concern given the large expenditure involved [1],[2]. In the absence of evidence of net improvement in prescribing from exposure to promotional information, we recommend that practitioners follow the precautionary principle and thus avoid exposure to information from pharmaceutical companies unless evidence of net benefit emerges. Supporting Information Alternative Language Abstract S1 Malaysian translation of the abstract by NO. (0.04 MB DOC) Click here for additional data file. Alternative Language Abstract S2 French translation of the abstract by AIV. (0.05 MB DOC) Click here for additional data file. Alternative Language Abstract S3 Spanish translation of the abstract by Diana L. Matallana. (0.05 MB DOC) Click here for additional data file. Text S1 MOOSE checklist. (1.72 MB PDF) Click here for additional data file.
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### Author and article information

###### Journal
BMJ Open
BMJ Open
bmjopen
bmjopen
BMJ Open
BMJ Publishing Group (BMA House, Tavistock Square, London, WC1H 9JR )
2044-6055
2017
27 September 2017
: 7
: 9
###### Affiliations
[1] Crowd for Cure , Groningen, Groningen, The Netherlands
###### Author notes
[Correspondence to ] Freek Fickweiler; freek@ 123456crowdforcure.com
###### Article
bmjopen-2017-016408
10.1136/bmjopen-2017-016408
5623540
28963287
1190952d-d160-482f-b3de-7eb4973a7bdc
© Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

This is an Open Access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) license, which permits others to distribute, remix, adapt and build upon this work, for commercial use, provided the original work is properly cited. See: http://creativecommons.org/licenses/by/4.0/

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