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Number and Percentage of Prescriptions Written for Selected AdvertisedAntidepressants by Patient Age Groups, 1994-1997Drug 0-44years548,077Wellbutrin® (63.09%)Prozac®Paxil®Zoloft®Effexor®Serzone®Total3,272,559(54.64%)1,544,082(50.71%)2,315,068(48.12%)421,832(63.85%)1994 1995 1996 199745 years 0-44 45 years 0-44 45 years 0-44and older years and older years and older years320,696(36.91%)2,716,453(45.36%)1,500,961(49.29%)2,496,050(51.88%)238,787(36.15%)344,867(43.46%)3,025,207(50.47%)1,875,855(51.06%)2,288,384(40.85%)708,465(62.66%)178,698(51.43%)448,585(56.54%)2,969,341(49.53%)1,798,248(48.94%)3,313,923(59.15%)422,173(37.34%)168,790(48.57%)497,137(57.13%)3,652,714(54.79%)1,974,885(46.14%)2,569,330(43.28%)621,764(51.61%)490,857(59.70%)373,063(42.87%)3,013,587(45.21%)2,305,667(53.86%)3,367,374(56.72%)583,029(48.39%)331,367(40.30%)1,324,208(58.15%)3,717,166(45.33%)2,637,367(38.50%)2,930,068(38.52%)768,090(37.23%)1,053,482(67.39%)45 yearsand older952,830(41.85%)4,482,773(54.67%)4,212,078(61.50%)4,677,219(61.48%)1,294,923(62.77%)509,739(32.61%)8,101,618(52.69%7,272,947(47.31%)8,421,476(48.01%)9,121,060(51.99%)9,806,687(49.58%)9,974,087(50.42%)12,430,381(43.52%)16,129,562(56.48%)15,374,565 17,542,536 19,780,774 28,559,943Number and Percentage of Prescriptions Written for Selected AdvertisedAntidepressants by Patient Age Groups, 1998-2001Drug 0-44yearsWellbutrin®Prozac®Paxil®Zoloft®Effexor®1,866,869(60.08%)4,000,405(49.13%)2,357,034(35.79%)3,637,191(43.26%)843,230(51.54%)1,025,646(49.10%)1998 1999 2000 200145 years 0-44 45 years 0-44 45 years 0-44and older years and older years and older years1,240,678(39.92%)4,141,84450.87%4,228,46164.21%4,769,80156.74%792,83448.46%1,063,11650.90%1,471,035(46.44%)3,683,399(46.59%)3,213,556(41.13%)3,089,900(37.13%)1,393,767(47.62%)973,139(57.42%)13,824,796(43.43%)1,696,740(53.56%)4,221,784(53.41%)4,599,052(58.87%)5,232,220(62.87%)1,533,241(52.38%)721,724(42.58%)3,007,162(63.35%)3,271,998(47.74%)3,531,272(42.71%)3,833,474(41.81%)2,165,621(49.20%)790,195(42.13%)1,739,703(36.65%)3,581,210(52.26%)4,736,290(57.29%)5,335,074(58.19%)2,236,398(50.80%)1,085,526(57.87%)1,803,233(46.36%4,498,368(51.31%4,134,830(41.01%4,226,942(43.35%1,631,779(41.24%995,022(57.30%Serzone®13,730,37516,236,73418,004,761 16,599,722 18,714,201 17,290,174(45.82%) (54.18%)(56.57%) (47.01%) (52.99%) (45.28%)Total 29,967,109 31,829,557 35,313,923 38,181,61245 yearsand older2,086,408(53.64%)4,268,918(48.69%)5,947,246(58.99%)5,522,765(56.65%)2,324,544(58.76%)741,557(42.70%)20,891,438(54.72%)494
DrugCapoten®ToprolXL®Altace®Number and Percentage of Prescriptions Written for Selected AdvertisedAntihypertensive Drugs by Patient Age Groups, 1994-19971994 1995 1996 19970-44 45 years 0-44 45 years 0-44 45 years 0-44 45 yearsyears and older years and older years and older years and older411,180 2,590,485 87,634 2,471,158 196,573 2,519,515 160,619 1,783,590(13.70%) (86.30%) (3.42%) (96.58%) (7.24%) (92.76%) (8.26%) (91.74%)143,568 327,625 26,851 699,751 231,523 1,052,574 208,700 2,096,147(30.47%) (69.53%) (3.70%) (96.30%) (18.03%) (81.97%) (9.05%) (90.95%)235,791 715,618 219,442 1,097,893 119,700 886,202 66,616 509,794(24.78%) (75.22%) (16.66%) (83.34%) (11.90%) (88.10%) (11.56%) (88.44%)0 410,186 315,916 837,699 112,115 1,420,314 303,552 1,757,502Adalat® (0.0%) (100.00%) (27.38%) (72.62%) (7.32%) (92.68%) (14.73%) (85.27%)Cardura®64,643 1,193,020 162,982 885,778 235,409 2,229,096 311,439 2,664,975(5.14%) (94.86%) (15.54%) (84.46%) (9.55%) (90.45%) (10.46%) (89.54%)Cardizem® (5.24%) (94.76%) (6.31%) (93.69%) (4.13%) (95.87%) (6.27%) (93.73%)416,592 7,530,493 398,924 5,920,518 246,223 5,721,431 272,735 4,074,354Lotensin®96,599 754,812 292,693 1,139,965 179,937 1,619,495 456,462 2,572,261(11.35%) (88.65%) (20.43%) (79.57%) (10.00%) (90.00%) (15.07%) (84.93%)25,725Coreg® -- -- -- -- -- -- -- (100.0%)1,368,373 13,522,239 1,504,442 13,052,762 1,321,480 15,448,627 1,780,123 15,484,348Total(10.12%) (90.81%) (11.53%) (89.67%) (8.55%) (92.12%) (11.5%) (89.69%)14,890,612 14,557,204 16,770,107 17,264,471495
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CopyrightbyRadhika Anantharaman Nai
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EVALUATION OF FACTORS RELATED TO PR
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AcknowledgementsThis dissertation a
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estimate prices of the drugs. Time
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PageRegulatory Changes in 1997 and
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PageCHAPTER 4: METHODOLOGY . . . .
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PagePrescription Drug Expenditures
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PageObjective II . . . . . . . . .
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PageDTCA Expenditures . . . . . . .
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LIST OF TABLES PageTable 2.1: Regul
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PageTable 5.20: Mixed Model Analyse
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PageTable 6.5: Results for Hypothes
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PageFigure 5.4: Trends in Total DTC
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PageFigure 5.30: Trends in Total DT
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CHAPTER 1: INTRODUCTIONBACKGROUNDPr
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Figure 1.2: Annual Percent Change i
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addition, the guidelines for detect
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Direct-to-Consumer Advertising Expe
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of the guidelines, manufacturers fe
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percent whereas private health insu
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public coverage has remained about
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According to the National Center fo
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As mentioned previously, DTCA can a
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one drug prescribed has not increas
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drugs is encouraged. 66 All these f
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(a) To determine the relationships
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enefit of DTCA, many claim that DTC
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persistent and will shop around unt
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advertisements describe and discuss
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These advertisements were aired mai
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During this time, the FDA realized
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included media tours in which physi
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care for their condition, it does n
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It is possible that due to the infl
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mistakenly believe that there is a
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Thus, advertising could cause patie
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Kefauver-Harris Drug Amendments als
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equire the industry to provide a de
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(d) Provide a statement that inform
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choose which side effects and contr
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The studies that tested these effec
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were more likely to have seen an ad
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disease it treats (51.0%). One-half
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advertised drug and on average used
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about a specific brand (1999-13.0%,
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Table 2.2: Prevention Magazine Surv
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eported that the physician recommen
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Maddox and Katsanis in a study publ
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drug, but not the disease or condit
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and 35.0 percent were prompted to h
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Glasgow et al. identified factors r
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Time, Inc. conducted two surveys of
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not be disappointed in the physicia
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quit smoking were not aware of it.
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2001 study by Allison-Ottey et al.
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and perceived risk. Argument qualit
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esults were obtained from most stud
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In 1997, IMS Health along with Phys
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medication and 7.0 percent gave the
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Results of the studies described in
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The study reported that 46.0 percen
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setting were more likely to have a
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advertising to build brand loyalty
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advertisements, headlines and subhe
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offer to provide more information i
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was increased, recall of risk infor
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SummaryConsumers are increasingly a
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including drugs used to treat high
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the increased prescription drug exp
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Office focus cluster had high expen
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especially detailing. This made it
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to a 47.8 percent increase in presc
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enign prostatic hypertrophy. 311 Ev
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which helped assess the impact of D
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elationship was significant only af
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DTCA expenditures and market share
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classes accounted for 75.0 percent
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DTCA expenditures along with prescr
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eneficiaries with coverage may rece
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utilization of prescription drugs i
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who were uninsured or were enrolled
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Access to Care and Utilization of P
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Among Medicare beneficiaries, suppl
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coverage filled fewer prescriptions
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than men and are receive more presc
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the prescription drug accounted for
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vs. 17.9%) or heavy users (21.4% vs
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visits than men. In 1998, the avera
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each household was causally associa
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eports, employment status, and read
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Demographics (Age and Gender) and U
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drugs use was largely due to drugs
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The study results indicated that th
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though the difference in the averag
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According to the study based on dat
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Summary of the LiteratureThese stud
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In a model predicting prescription
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Summary of the LiteratureUtilizatio
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esults are skewed, especially when
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Several other factors and market dy
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H 1 : An increase in DTCA expenditu
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H 14 : There is no significant rela
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H 24 : An increase in the proportio
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GastrointestinalsObjective ITo dete
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access to care will be significantl
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AntihypertensivesObjective ITo dete
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Data Collection MethodologyThe basi
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As mentioned earlier, CMR also coll
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oadcasting industry survey conducte
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stated previously, data for the rem
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are to be recorded. A perforation b
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truncated, but this leads to an und
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As discussed in Chapter 2, with the
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The total monthly advertising expen
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64 years, 65-74 years, and 75 years
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Table 4.2: United States City Avera
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including chronic conditions (e.g.,
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2000. The ICD-9 CM code for irritab
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The ICD-9 CM codes used to identify
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errors, the significance of the par
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presence of autocorrelation, data w
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measured for each drug over a perio
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August 1997 and September 1997 to A
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CHAPTER 5: RESULTSChapter 5 will pr
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$39.8 million in 1995 accounting fo
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each year to $1,091.7 million in 19
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The number of months represent the
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print and billboard advertising exp
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1998, but then decreased every year
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advertised allergy medications was
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Figure 5.8: Trend in the Number of
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Since 1997, nine out of ten individ
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increase in prescription drug expen
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The total DTCA expenditures for ant
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Figure 5.14: Trend in DTCA Expendit
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1994 to $14.3 million in 1995, but
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Table 5.6: Number and Percentage of
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Figure 5.17: Trends in Percentage o
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Prescription Drug ExpendituresThis
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Figure 5.20: Trends in Prescription
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Since the guidelines for broadcast
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Gastrointestinal-Related Physician
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visits and number of prescriptions
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prescriptions written decreasing to
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64.0%), had health insurance covera
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Figure 5.27: Trends in Total Prescr
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AntidepressantsDTCA ExpendituresFig
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The total DTCA expenditures increas
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percentage of visits when the visit
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presented in the methodology, the e
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Figure 5.35: Trends in Prescription
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heavily advertised antihypertensive
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antihypertensives and number of hyp
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Figure 5.38: Trend in the Number of
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study, total drug expenditures did
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the advertised drugs from the respe
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In the dataset for mixed model anal
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monthly allergy-related physician v
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Table 5.14: Test Statistics for Ord
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of individuals 45 years and older,
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and time period indicates that the
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values in the dataset for the perce
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Increase in the allergy-related vis
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Table 5.18: Mixed Model Analysis fo
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elated visit increase, the drug exp
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independent variables was associate
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The Durbin-Watson statistic for thi
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untransformed values yielded differ
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Mixed Model Analysis with Transform
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Table 5.25: Untransformed Mixed Mod
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significant in both time periods (T
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The significant variables in this a
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in the drug expenditures for advert
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coefficient for this variable was 6
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years, 45-64 years, and 65 years an
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in time period one compared to time
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Table 5.34: Mixed Model Analysis fo
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every one percent increase in indiv
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less than 25 years, 25-44 years, 45
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significant relationships in both t
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visit {df=235, t=9.64, p
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variables in the equation. For ever
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for gastrointestinal-related visits
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In the absence of the visit variabl
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expenditures, and drug expenditures
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Table 5.46: Mixed Model Analyses fo
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untransformed variables were reconf
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while controlling for other variabl
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1997 to April 2001), which categori
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antidepressants, the analysis was r
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variables in the equation. The perc
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The only age variable that was sign
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prescriptions written for advertise
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in time period two was not supporte
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with health insurance coverage had
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with the transformed variables (Tab
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prescription for advertised antidep
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significant variables indicating th
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antidepressants and were 65 years a
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Time series analysis was employed t
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The results of the mixed model anal
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The significant variables in the an
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number of prescriptions written for
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elated visits, DTCA expenditures fo
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The interaction between DTCA expend
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An increase in number of hypertensi
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in the equation. In time period two
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200 and 360 outlets (spot markets),
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to three reasons for visits were re
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The access or health insurance cove
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• A wider use of the drugs may re
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Table 6.1: Results of the Hypothese
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Tables 6.3 and 6.4 provide a snapsh
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market and advertising of these dru
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(p=0.071). On splitting the dataset
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antidepressants and depression-rela
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The results for age should be inter
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Objective II: Hypotheses for the De
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Objective IV: Hypotheses for Depend
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For every $1,000 increase in DTCA e
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prescriptions written for antidepre
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were positively and significantly r
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coverage were more likely to be pre
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antihypertensives reduced drastical
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The upheavals in the market may be
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a result of advertising, patients m
Page 475 and 476: included in the study, inducing phy
Page 477 and 478: new prescriptions or rather are a r
Page 479 and 480: Objective III: Hypotheses for the D
Page 481 and 482: Objective IV: Hypotheses for the De
Page 483 and 484: DTCA ExpendituresSimilar to the rel
Page 485 and 486: expenditures and prescriptions writ
Page 487 and 488: expenditures for antihypertensives.
Page 489 and 490: also possible that individuals rece
Page 491 and 492: eported increased expenditures by a
Page 493 and 494: awareness for consumers and physici
Page 495 and 496: as well as number of prescriptions
Page 497 and 498: Some studies have reported that wom
Page 499 and 500: Physician VisitsPhysician visits (s
Page 501 and 502: individuals had a positive relation
Page 503 and 504: not only due to DTCA, but also othe
Page 505 and 506: should be repeated for these newer
Page 507 and 508: GLOSSARY OF ACRONYMSAARP - American
Page 509 and 510: Average Wholesale Price of Drugs, 1
Page 511 and 512: Total DTCA Expenditures (in million
Page 513 and 514: Number and Percentage of Prescripti
Page 515 and 516: Number and Percentage of Prescripti
Page 517 and 518: Percentage of Women Among those who
Page 519 and 520: Appendix FTables for Percentage of
Page 521 and 522: Percentage of Individuals with Heal
Page 523 and 524: Number And Percentage Of Prescripti
Page 525: Number and Percentage of Prescripti
Page 529 and 530: Appendix HFigures for Percentage of
Page 531 and 532: Percentage of Prescriptions Written
Page 533 and 534: Appendix ITables for Total Prescrip
Page 535 and 536: Total Prescription Drug Expenditure
Page 537 and 538: BIBLIOGRAPHY. 21 C.F.R. § 202.1(1)
Page 539 and 540: Direct-to-consumer advertisement of
Page 541 and 542: Health care in America: Trends in u
Page 543 and 544: Report to the President: Prescripti
Page 545 and 546: Angel JE. Drug advertisements and p
Page 547 and 548: Cain G. A remedy for rising drug co
Page 549 and 550: Eng HJ, Lairson DR. Prescribed medi
Page 551 and 552: Goldman DP, Joyce GF, Escarce JJ, e
Page 553 and 554: IMS-Health. Paper presented at: Pha
Page 555 and 556: Lipsky MS, Taylor CA. The opinions
Page 557 and 558: Morris LA, Mazis MB, Brinberg D. Ri
Page 559 and 560: Rosenbach ML, Irvin C, Coulam RF. A
Page 561 and 562: Smart S, Williams C. Half of drug a
Page 563 and 564: Wind Y. Pharmaceutical advertising:
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