| Literature DB >> 25045280 |
Katherine A Johansen Taber1, Barry D Dickinson1.
Abstract
BACKGROUND: The use of pharmacogenomic testing in the clinical setting has the potential to improve the safety and effectiveness of drug therapy, yet studies have revealed that physicians lack knowledge about the topic of pharmacogenomics, and are not prepared to implement it in the clinical setting. This study further explores the pharmacogenomic knowledge deficit and educational resource needs among physicians.Entities:
Keywords: drug response; educational resource; knowledge gap; pharmacogenomics
Year: 2014 PMID: 25045280 PMCID: PMC4100727 DOI: 10.2147/PGPM.S63715
Source DB: PubMed Journal: Pharmgenomics Pers Med ISSN: 1178-7066
Characteristics of survey population (n=300)
| Characteristics | Total respondents (n) |
|---|---|
| Sex | |
| Male | 68.7% (206) |
| Female | 31.3% (94) |
| Age, years | |
| 25–34 | 24.3% (73) |
| 35–44 | 53.7% (161) |
| 45–54 | 3.7% (11) |
| 55–64 | 18.3% (55) |
| Years in practice (postresidency/fellowship) | 10.3±1.59 |
| Hours of direct patient care per week | 48.6±7.51 |
| Medical specialty | |
| Family medicine | 38.3% (115) |
| General medicine | 0.7% (2) |
| Internal medicine | 21.3% (64) |
| Psychiatry | 20.0% (60) |
| Cardiology | 19.7% (59) |
| Region | |
| Northeast | 21.3% (64) |
| Midwest | 19.3% (58) |
| South | 36.7% (110) |
| West | 22.7% (68) |
| Practice setting | |
| Physician office, solo | 14.3% (43) |
| Physician office, single-specialty group | 53.3% (160) |
| Multispecialty group practice | 32.3% (97) |
| Uses an EMR | |
| Primary care physicians | 77.3% (140/181) |
| Psychiatrists | 51.7% (31/60) |
| Cardiologists | 72.9% (43/59) |
| Devices used to access health care-related information | |
| Desktop computer | 75.7% (227) |
| Laptop computer | 76.3% (229) |
| Tablet computer | 33.3% (100) |
| Smartphone | 80.0% (240) |
Notes:
Grouped together as primary care physicians;
significantly more primary care physicians than psychiatrists reported using an EMR (P<0.05).
Abbreviation: EMR, electronic medical record.
Figure 1Factors cited as extremely or very important by physician respondents when choosing appropriate drug therapy or dosage.
Notes: aPsychiatrists were significantly less likely than primary care physicians and cardiologists to report that labeled indication is extremely or very important when making prescribing decisions (38.3% versus 66.9% and 72.9%, respectively, P<0.05).
Figure 2Familiarity with, confidence in and knowledge of, and training in pharmacogenomics, as reported by physician respondents. “Formal training” was defined as medical school, residency, or continuing medical education.
Proportion of respondents indicating that the drug listed could elicit a substantially variable response due to a patient’s genetic background
| Drug | Biomarker(s) | Total | PCP | Psychiatrists | Cardiologists |
|---|---|---|---|---|---|
| Warfarin | CYP2C9 | 47.7 (143) | 51.9 (94) | 18.3 (11) | 64.4 (38) |
| Clopidogrel (Plavix®) | CYP2C19 | 47.0 (141) | 47.0 (85) | 8.3 (5) | 86.4 (51) |
| Atorvastatin (Lipitor®) | LDL-R | 24.7 (74) | 28.2 (51) | 11.7 (7) | 27.1 (16) |
| Carbamazepine (Tegretol®) | HLA-B*1502 | 21.0 (63) | 18.2 (33) | 43.3 (26) | 6.8 (4) |
| Quinidine | 14.3 (43) | 16.0 (29) | 8.3 (5) | 15.3 (9) | |
| Captopril (Capoten®) | 13.3 (40) | 14.9 (27) | 6.7 (4) | 15.3 (9) | |
| Fluconazole (Diflucan®) | 13.0 (39) | 14.9 (27) | 10.0 (6) | 10.2 (6) | |
| Hydrochlorothiazide | 10.7 (32) | 13.8 (25) | 8.3 (5) | 3.4 (2) | |
| Levothyroxine (Synthroid®) | 10.7 (32) | 14.4 (26) | 6.7 (4) | 3.4 (2) | |
| Atomoxetine (Straterra®) | CYP2D6 | 7.7 (23) | 5.0 (9) | 21.7 (13) | 1.7 (1) |
| Metoprolol (Lopressor®) | CYP2D6 | 6.3 (13) | 7.2 (13) | 5.0 (3) | 5.1 (3) |
| Don’t know | 21.3 (64) | 19.3 (35) | 41.7 (25) | 6.8 (4) | |
| Total | (300) | (181) | (60) | (59) |
Notes:
Correct answer (drug elicits substantially variable response due to genetic variation); drugs included on this list are those that are among the most frequently prescribed by the specialties participating in the survey; those considered correct answers have clear pharmacogenomic information in the drug labeling, as well as substantial evidence of pharmacogenomic influence published in the literature;
value significantly higher than corresponding value in “Psychiatrists” column (P<0.05);
value significantly higher than corresponding values in “PCP” and “Cardiologists” columns (P<0.05);
value significantly higher than corresponding values in “PCP” and “Psychiatrists” columns (P<0.05). Manufacturer details are as follows: Plavix® (Sanofi, Bridgewater, New Jersey, USA); Lipitor® and Diflucan® (Pfizer, Inc., New York, NY, USA); Tegretol® and Lopressor® (Novartis International AG, Basel, Switzerland); Capoten® (Par Pharmaceutical, Spring Valley, NY, USA); Synthroid® (Abbott Laboratories, North Chicago, IL, USA); Straterra® (Eli Lilly and Company, Indianapolis, IN, USA).
Abbreviation: PCP, primary care physician.
Figure 3Reasons most commonly cited by physician respondents for not ordering a pharmacogenomic test in the past year, and for not anticipating ordering a pharmacogenomic test in the next year.
Notes: aSignificantly more primary care physicians than cardiologists reported that they did not know what test to order (75.0% versus 52.5%, P<0.05); bsignificantly more primary care physicians and psychiatrists than cardiologists reported that they would not know what test to order (84.6% and 83.9%, respectively, versus 44.8%; P<0.05).
Resources currently consulted when questions arise about pharmacogenomics
| Resources | Total respondents (n) |
|---|---|
| Scientific literature | 58.0% (174) |
| Internet (Google searches, WebMD, etc) | 49.3% (148) |
| Professional society literature/guidelines/recommendations | 47.3% (142) |
| Peer discussion | 41.7% (125) |
| Laboratory directors/personnel | 25.0% (75) |
| Drug labeling | 20.7% (62) |
| FDA website | 17.7% (53) |
| Insurance company/payer | 11.3% (34) |
| Have not consulted resources | 14.3% (43) |
| Do currently available resources enable you to access the pharmacogenomic information you need or want to know? | |
| Yes | 43.0% (129) |
| No | 57.0% (171) |
Notes:
Primary care physicians were significantly more likely than cardiologists to have consulted a laboratory director/personnel (29.8% versus 11.9%, P<0.05);
primary care physicians and psychiatrists were significantly more likely than cardiologists to have consulted the US Food and Drug Administration (FDA) website (18.8% and 26.7%, respectively, versus 5.1%; P<0.05).
Preferred characteristics of an ideal pharmacogenomic educational resource
| Characteristics | Total respondents (n) |
|---|---|
| Content | |
| How to interpret pharmacogenomic test results | 88.4% (260) |
| Recommendations for prescribing | 88.1% (259) |
| Effect of genetic variation on mechanism of drug action | 79.9% (235) |
| Demographics of populations likely to carry variations | 76.9% (226) |
| References (such as scientific literature) | 69.0% (203) |
| List of laboratories offering testing | 63.9% (188) |
| Description of pharmacogenomic information in drug labeling | 62.2% (183) |
| Format | |
| Web-based | 67.7% (199) |
| Mobile application (for smartphone or tablet) | 56.2% (165) |
| Incorporated within EMR | 34.0% (100) |
| Pop-up reminders within prescribing system | 23.4% (69) |
| Print materials | 18.7% (55) |
| Source (organization or institution) | |
| Health care-related software company (eg, Epocrates) | 66.9% (200) |
| Professional/specialty society | 19.4% (58) |
| Government | 6.7% (20) |
| Health insurance company | 5.7% (17) |
Notes:
Values represent combined ratings of 1 or 2 on a scale of 1–5, with 1 representing most preferred and 5 representing least preferred;
significantly more psychiatrists than cardiologists indicated that content on how to interpret pharmacogenomic test results (96.7% versus 82.5%, P<0.05) and a description of pharmacogenomic information in the drug labeling (75.0% versus 52.5%, P<0.05) should be included;
primary care physicians were significantly more interested in EMR incorporation than were psychiatrists (41.2% rating it as a 1 or 2 versus 16.6% rating it as a 1 or 2, P<0.05). Epocrates, Inc. (San Mateo, CA, USA).
Abbreviation: EMR, electronic medical record.
| Extremely important | Very important | Somewhat important | Not very important | Not at all important | ||
|---|---|---|---|---|---|---|
| 10. | Medical history | ○ | ○ | ○ | ○ | ○ |
| 11. | Age | ○ | ○ | ○ | ○ | ○ |
| 12. | Sex | ○ | ○ | ○ | ○ | ○ |
| 13. | Genetic information | ○ | ○ | ○ | ○ | ○ |
| 14. | Labeled indication | ○ | ○ | ○ | ○ | ○ |
| 15. | Adverse effects | ○ | ○ | ○ | ○ | ○ |
| 16. | Insurance coverage | ○ | ○ | ○ | ○ | ○ |
| 1 | 2 | 3 | 4 | 5 | ||
|---|---|---|---|---|---|---|
| 31. | Web-based | ○ | ○ | ○ | ○ | ○ |
| 32. | Mobile application (for smartphone/tablet) | ○ | ○ | ○ | ○ | ○ |
| 33. | Print materials | ○ | ○ | ○ | ○ | ○ |
| 34. | Incorporated within an EMR system | ○ | ○ | ○ | ○ | ○ |
| 35. | Pop-up reminders/information at time of prescription order | ○ | ○ | ○ | ○ | ○ |