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PageTable 5.29: Mixed Model Analyses for Prescription Drug Expendituresfor Advertised Antilipemics Controlling for Age, Gender,Access, DTCA Expenditures for Antilipemics, andLipid-Related Physician Visits for the Two Time Periods(Transformed Variables) . . . . . . . . . . . . 326Table 5.30: Test Statistics for Ordinary Least Squares Analysis <strong>of</strong>Gastrointestinal-Related Physician Visits Regressed onAge, Gender, Access, Total DTCA Expenditures forGastrointestinal Drugs and Time Period . . . . . . . . 329Table 5.31: Test Statistics for Ordinary Least Squares Analyses <strong>of</strong>Gastrointestinal-Related Physician Visits Regressed on Age,Gender, Access, and Total DTCA Expenditures forGastrointestinal Drugs for the Two Time Periods . . . . . . 330Table 5.32: Mixed Model Analysis for Prescriptions Written forAdvertised Gastrointestinal Drugs Controlling for Age,Gender, Access, DTCA Expenditures for Gastrointestinals,Gastrointestinal-Related Visits and Time Period(Transformed Variables) . . . . . . . . . . . . 333Table 5.33: Untransformed Mixed Model Analysis for Prescriptions Written forAdvertised Gastrointestinal Drugs Controlling for Age,Gender, Access, DTCA Expenditures for Gastrointestinals,Gastrointestinal-Related Visits and Time Period . . . . . 335Table 5.34: Mixed Model Analysis for Prescriptions Written forAdvertised Gastrointestinal Drugs Controlling for Multiple AgeCategories, Gender, Access, DTCA Expenditures forGastrointestinals, Gastrointestinal-Related Visits and Time Period(Transformed Variables) . . . . . . . . . . . . 337Table 5.35: Untransformed Mixed Model Analysis for Prescriptions Written forAdvertised Gastrointestinal Drugs Controlling for Multiple AgeCategories, Gender, Access, DTCA Expenditures for Gastrointestinals,Gastrointestinal-Related Visits and Time Period . . . . . . 338Table 5.36: Mixed Model Analyses for Prescriptions Written forAdvertised Gastrointestinal Drugs Controlling for Age,Gender, Access, DTCA Expenditures for Gastrointestinal Drugs, andGastrointestinal-Related Physician Visits for the TwoTime Periods (Transformed Variables) . . . . . . . . . 340xxii
PageTable 5.37: Mixed Model Analyses for Prescriptions Written for AdvertisedGastrointestinal Drugs Controlling for Multiple Age Categories,Gender, Access, DTCA Expenditures for Gastrointestinal Drugs,and Gastrointestinal-Related Physician Visits for the Two TimePeriods (Transformed Variables) . . . . . . . . . . 342Table 5.38: Mixed Model Analysis for Prescription Drug Expenditures forAdvertised Gastrointestinal Drugs Controlling for Age, Gender,Access, DTCA Expenditures for Gastrointestinal Drugs,Gastrointestinal-Related Visits and Time Period(Transformed variables). . . . . . . . . . . . . 344Table 5.39: Untransformed Mixed Model Analysis for Prescription DrugExpenditures for Advertised Gastrointestinal Drugs Controlling forAge, Gender, Access, DTCA Expenditures for GastrointestinalDrugs, Gastrointestinal-Related Visits and Time Period . . . . 346Table 5.40: Mixed Model Analysis for Prescriptions Drug Expendituresfor Advertised Gastrointestinal Drugs Controlling for Age,Gender, Access, DTCA Expenditures for Gastrointestinals,and Time Period (Transformed Variables) . . . . . . . . 348Table 5.41: Mixed Model Analysis for Prescription Drug Expendituresfor Advertised Gastrointestinal Drugs Controlling for Multiple AgeCategories, Gender, Access, DTCA Expenditures for GastrointestinalDrugs, Gastrointestinal-Related Visits, and Time Period(Transformed Variables) . . . . . . . . . . . . 349Table 5.42: Untransformed Mixed Model Analysis for Prescription DrugExpenditures for Advertised Gastrointestinal Drugs Controllingfor Multiple Age Categories, Gender, Access, DTCA Expendituresfor Gastrointestinal Drugs, Gastrointestinal-Related Visits, andTime Period . . . . . . . . . . . . . . . . 351Table 5.43: Mixed Model Analysis for Prescription Drug Expendituresfor Advertised Gastrointestinal Drugs Controlling for Multiple AgeCategories, Gender, Access, DTCA Expenditures for GastrointestinalDrugs, and Time Period (Transformed Variables) . . . . . . 352Table 5.44: Untransformed Mixed Model Analysis for Prescription DrugExpenditures for Advertised Gastrointestinal Drugs Controlling forMultiple Age Categories, Gender, Access, DTCA Expenditures forGastrointestinal Drugs, and Time Period . . . . . . . . 354xxiii
Page 1 and 2: CopyrightbyRadhika Anantharaman Nai
Page 3 and 4: EVALUATION OF FACTORS RELATED TO PR
Page 5 and 6: AcknowledgementsThis dissertation a
Page 7 and 8: estimate prices of the drugs. Time
Page 9 and 10: PageRegulatory Changes in 1997 and
Page 11 and 12: PageCHAPTER 4: METHODOLOGY . . . .
Page 13 and 14: PagePrescription Drug Expenditures
Page 15 and 16: PageObjective II . . . . . . . . .
Page 17 and 18: PageDTCA Expenditures . . . . . . .
Page 19 and 20: LIST OF TABLES PageTable 2.1: Regul
Page 21: PageTable 5.20: Mixed Model Analyse
Page 25 and 26: PageTable 5.54: Mixed Model Analyse
Page 27 and 28: PageTable 6.5: Results for Hypothes
Page 29 and 30: PageFigure 5.4: Trends in Total DTC
Page 31 and 32: PageFigure 5.30: Trends in Total DT
Page 33 and 34: CHAPTER 1: INTRODUCTIONBACKGROUNDPr
Page 35 and 36: Figure 1.2: Annual Percent Change i
Page 37 and 38: addition, the guidelines for detect
Page 39 and 40: Direct-to-Consumer Advertising Expe
Page 41 and 42: of the guidelines, manufacturers fe
Page 43 and 44: percent whereas private health insu
Page 45 and 46: public coverage has remained about
Page 47 and 48: According to the National Center fo
Page 49 and 50: As mentioned previously, DTCA can a
Page 51 and 52: one drug prescribed has not increas
Page 53 and 54: drugs is encouraged. 66 All these f
Page 55 and 56: (a) To determine the relationships
Page 57 and 58: enefit of DTCA, many claim that DTC
Page 59 and 60: persistent and will shop around unt
Page 61 and 62: advertisements describe and discuss
Page 63 and 64: These advertisements were aired mai
Page 65 and 66: During this time, the FDA realized
Page 67 and 68: included media tours in which physi
Page 69 and 70: care for their condition, it does n
Page 71 and 72: It is possible that due to the infl
Page 73 and 74:
mistakenly believe that there is a
Page 75 and 76:
Thus, advertising could cause patie
Page 77 and 78:
Kefauver-Harris Drug Amendments als
Page 79 and 80:
equire the industry to provide a de
Page 81 and 82:
(d) Provide a statement that inform
Page 83 and 84:
choose which side effects and contr
Page 85 and 86:
The studies that tested these effec
Page 87 and 88:
were more likely to have seen an ad
Page 89 and 90:
disease it treats (51.0%). One-half
Page 91 and 92:
advertised drug and on average used
Page 93 and 94:
about a specific brand (1999-13.0%,
Page 95 and 96:
Table 2.2: Prevention Magazine Surv
Page 97 and 98:
eported that the physician recommen
Page 99 and 100:
Maddox and Katsanis in a study publ
Page 101 and 102:
drug, but not the disease or condit
Page 103 and 104:
and 35.0 percent were prompted to h
Page 105 and 106:
Glasgow et al. identified factors r
Page 107 and 108:
Time, Inc. conducted two surveys of
Page 109 and 110:
not be disappointed in the physicia
Page 111 and 112:
quit smoking were not aware of it.
Page 113 and 114:
2001 study by Allison-Ottey et al.
Page 115 and 116:
and perceived risk. Argument qualit
Page 117 and 118:
esults were obtained from most stud
Page 119 and 120:
In 1997, IMS Health along with Phys
Page 121 and 122:
medication and 7.0 percent gave the
Page 123 and 124:
Results of the studies described in
Page 125 and 126:
The study reported that 46.0 percen
Page 127 and 128:
setting were more likely to have a
Page 129 and 130:
advertising to build brand loyalty
Page 131 and 132:
advertisements, headlines and subhe
Page 133 and 134:
offer to provide more information i
Page 135 and 136:
was increased, recall of risk infor
Page 137 and 138:
SummaryConsumers are increasingly a
Page 139 and 140:
including drugs used to treat high
Page 141 and 142:
the increased prescription drug exp
Page 143 and 144:
Office focus cluster had high expen
Page 145 and 146:
especially detailing. This made it
Page 147 and 148:
to a 47.8 percent increase in presc
Page 149 and 150:
enign prostatic hypertrophy. 311 Ev
Page 151 and 152:
which helped assess the impact of D
Page 153 and 154:
elationship was significant only af
Page 155 and 156:
DTCA expenditures and market share
Page 157 and 158:
classes accounted for 75.0 percent
Page 159 and 160:
DTCA expenditures along with prescr
Page 161 and 162:
eneficiaries with coverage may rece
Page 163 and 164:
utilization of prescription drugs i
Page 165 and 166:
who were uninsured or were enrolled
Page 167 and 168:
Access to Care and Utilization of P
Page 169 and 170:
Among Medicare beneficiaries, suppl
Page 171 and 172:
coverage filled fewer prescriptions
Page 173 and 174:
than men and are receive more presc
Page 175 and 176:
the prescription drug accounted for
Page 177 and 178:
vs. 17.9%) or heavy users (21.4% vs
Page 179 and 180:
visits than men. In 1998, the avera
Page 181 and 182:
each household was causally associa
Page 183 and 184:
eports, employment status, and read
Page 185 and 186:
Demographics (Age and Gender) and U
Page 187 and 188:
drugs use was largely due to drugs
Page 189 and 190:
The study results indicated that th
Page 191 and 192:
though the difference in the averag
Page 193 and 194:
According to the study based on dat
Page 195 and 196:
Summary of the LiteratureThese stud
Page 197 and 198:
In a model predicting prescription
Page 199 and 200:
Summary of the LiteratureUtilizatio
Page 201 and 202:
esults are skewed, especially when
Page 203 and 204:
Several other factors and market dy
Page 205 and 206:
H 1 : An increase in DTCA expenditu
Page 207 and 208:
H 14 : There is no significant rela
Page 209 and 210:
H 24 : An increase in the proportio
Page 211 and 212:
GastrointestinalsObjective ITo dete
Page 213 and 214:
Page 215 and 216:
access to care will be significantl
Page 217 and 218:
AntihypertensivesObjective ITo dete
Page 219 and 220:
Page 221 and 222:
Data Collection MethodologyThe basi
Page 223 and 224:
As mentioned earlier, CMR also coll
Page 225 and 226:
oadcasting industry survey conducte
Page 227 and 228:
stated previously, data for the rem
Page 229 and 230:
are to be recorded. A perforation b
Page 231 and 232:
truncated, but this leads to an und
Page 233 and 234:
As discussed in Chapter 2, with the
Page 235 and 236:
The total monthly advertising expen
Page 237 and 238:
64 years, 65-74 years, and 75 years
Page 239 and 240:
Table 4.2: United States City Avera
Page 241 and 242:
including chronic conditions (e.g.,
Page 243 and 244:
2000. The ICD-9 CM code for irritab
Page 245 and 246:
The ICD-9 CM codes used to identify
Page 247 and 248:
errors, the significance of the par
Page 249 and 250:
presence of autocorrelation, data w
Page 251 and 252:
measured for each drug over a perio
Page 253 and 254:
August 1997 and September 1997 to A
Page 255 and 256:
CHAPTER 5: RESULTSChapter 5 will pr
Page 257 and 258:
$39.8 million in 1995 accounting fo
Page 259 and 260:
each year to $1,091.7 million in 19
Page 261 and 262:
The number of months represent the
Page 263 and 264:
print and billboard advertising exp
Page 265 and 266:
1998, but then decreased every year
Page 267 and 268:
advertised allergy medications was
Page 269 and 270:
Figure 5.8: Trend in the Number of
Page 271 and 272:
Since 1997, nine out of ten individ
Page 273 and 274:
increase in prescription drug expen
Page 275 and 276:
The total DTCA expenditures for ant
Page 277 and 278:
Figure 5.14: Trend in DTCA Expendit
Page 279 and 280:
1994 to $14.3 million in 1995, but
Page 281 and 282:
Table 5.6: Number and Percentage of
Page 283 and 284:
Figure 5.17: Trends in Percentage o
Page 285 and 286:
Prescription Drug ExpendituresThis
Page 287 and 288:
Figure 5.20: Trends in Prescription
Page 289 and 290:
Since the guidelines for broadcast
Page 291 and 292:
Gastrointestinal-Related Physician
Page 293 and 294:
visits and number of prescriptions
Page 295 and 296:
prescriptions written decreasing to
Page 297 and 298:
64.0%), had health insurance covera
Page 299 and 300:
Figure 5.27: Trends in Total Prescr
Page 301 and 302:
AntidepressantsDTCA ExpendituresFig
Page 303 and 304:
The total DTCA expenditures increas
Page 305 and 306:
percentage of visits when the visit
Page 307 and 308:
Page 309 and 310:
presented in the methodology, the e
Page 311 and 312:
Figure 5.35: Trends in Prescription
Page 313 and 314:
heavily advertised antihypertensive
Page 315 and 316:
antihypertensives and number of hyp
Page 317 and 318:
Figure 5.38: Trend in the Number of
Page 319 and 320:
Page 321 and 322:
study, total drug expenditures did
Page 323 and 324:
the advertised drugs from the respe
Page 325 and 326:
In the dataset for mixed model anal
Page 327 and 328:
monthly allergy-related physician v
Page 329 and 330:
Table 5.14: Test Statistics for Ord
Page 331 and 332:
of individuals 45 years and older,
Page 333 and 334:
and time period indicates that the
Page 335 and 336:
values in the dataset for the perce
Page 337 and 338:
Increase in the allergy-related vis
Page 339 and 340:
Table 5.18: Mixed Model Analysis fo
Page 341 and 342:
elated visit increase, the drug exp
Page 343 and 344:
independent variables was associate
Page 345 and 346:
The Durbin-Watson statistic for thi
Page 347 and 348:
untransformed values yielded differ
Page 349 and 350:
Mixed Model Analysis with Transform
Page 351 and 352:
Table 5.25: Untransformed Mixed Mod
Page 353 and 354:
significant in both time periods (T
Page 355 and 356:
The significant variables in this a
Page 357 and 358:
Page 359 and 360:
in the drug expenditures for advert
Page 361 and 362:
coefficient for this variable was 6
Page 363 and 364:
years, 45-64 years, and 65 years an
Page 365 and 366:
in time period one compared to time
Page 367 and 368:
Page 369 and 370:
Table 5.34: Mixed Model Analysis fo
Page 371 and 372:
every one percent increase in indiv
Page 373 and 374:
less than 25 years, 25-44 years, 45
Page 375 and 376:
significant relationships in both t
Page 377 and 378:
visit {df=235, t=9.64, p
Page 379 and 380:
variables in the equation. For ever
Page 381 and 382:
for gastrointestinal-related visits
Page 383 and 384:
Page 385 and 386:
In the absence of the visit variabl
Page 387 and 388:
expenditures, and drug expenditures
Page 389 and 390:
Table 5.46: Mixed Model Analyses fo
Page 391 and 392:
untransformed variables were reconf
Page 393 and 394:
Page 395 and 396:
while controlling for other variabl
Page 397 and 398:
1997 to April 2001), which categori
Page 399 and 400:
antidepressants, the analysis was r
Page 401 and 402:
variables in the equation. The perc
Page 403 and 404:
The only age variable that was sign
Page 405 and 406:
prescriptions written for advertise
Page 407 and 408:
in time period two was not supporte
Page 409 and 410:
with health insurance coverage had
Page 411 and 412:
with the transformed variables (Tab
Page 413 and 414:
prescription for advertised antidep
Page 415 and 416:
significant variables indicating th
Page 417 and 418:
antidepressants and were 65 years a
Page 419 and 420:
Time series analysis was employed t
Page 421 and 422:
Page 423 and 424:
The results of the mixed model anal
Page 425 and 426:
The significant variables in the an
Page 427 and 428:
number of prescriptions written for
Page 429 and 430:
elated visits, DTCA expenditures fo
Page 431 and 432:
The interaction between DTCA expend
Page 433 and 434:
An increase in number of hypertensi
Page 435 and 436:
in the equation. In time period two
Page 437 and 438:
200 and 360 outlets (spot markets),
Page 439 and 440:
to three reasons for visits were re
Page 441 and 442:
The access or health insurance cove
Page 443 and 444:
• A wider use of the drugs may re
Page 445 and 446:
Table 6.1: Results of the Hypothese
Page 447 and 448:
Tables 6.3 and 6.4 provide a snapsh
Page 449 and 450:
market and advertising of these dru
Page 451 and 452:
(p=0.071). On splitting the dataset
Page 453 and 454:
antidepressants and depression-rela
Page 455 and 456:
The results for age should be inter
Page 457 and 458:
Objective II: Hypotheses for the De
Page 459 and 460:
Objective IV: Hypotheses for Depend
Page 461 and 462:
For every $1,000 increase in DTCA e
Page 463 and 464:
prescriptions written for antidepre
Page 465 and 466:
were positively and significantly r
Page 467 and 468:
coverage were more likely to be pre
Page 469 and 470:
antihypertensives reduced drastical
Page 471 and 472:
The upheavals in the market may be
Page 473 and 474:
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:
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 and 526:
Page 527 and 528:
DrugCapoten®ToprolXL®Altace®Numb
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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