Article Figures & Data
Figures
- Figure 1.
Potentially inappropriate medication prescription rate among primary care physicians in 2013 to 2015. ***P < .001. Note: Data obtained from 2013 to 2015 Medicare Part D PUF and 2015 AMA Masterfile. Potentially inappropriate medications (PIMs) were defined based on primary-care relevant PIMs listed in Appendix Table A.
- Figure 2.
Associations between primary care physician characteristics and potentially inappropriate medication prescription rate. Note: Data obtained from 2013 to 2015 Medicare Part D PUF and 2015 AMA Masterfile. Potentially inappropriate medications (PIMs) were defined based on primary-care relevant PIMs listed in Appendix Table A.
Tables
Low Prescribers (Q1–Q3)a High Prescribers (Q4)b Difference P-Value Mean SD Mean SD PIM rate 0.032 0.018 0.101 0.068 .000 PCP characteristics† Age 51.6 11.0 52.8 11.7 .000 Female 0.324 0.468 0.307 0.461 .000 DO degree 0.126 0.332 0.149 0.356 .000 Medical school cohort Pre-1980 graduate 0.180 0.384 0.213 0.409 .000 1980–1989 graduate 0.293 0.455 0.289 0.453 .036 1990–1999 graduate 0.314 0.464 0.301 0.459 .000 2000–2009 graduate 0.198 0.398 0.181 0.385 .000 2010–present graduate 0.015 0.122 0.016 0.126 .049 Primary care specialty Family medicine 0.524 0.499 0.541 0.498 .000 Internal medicine 0.445 0.497 0.422 0.494 .000 General practice 0.022 0.147 0.034 0.182 .000 Geriatric medicine 0.009 0.092 0.003 0.054 .000 Practice size (No. of providers)‡ 336 888 252 725 .000 Q1 (1–5) 0.303 0.460 0.375 0.484 .000 Q2 (6–65) 0.244 0.429 0.227 0.419 .000 Q3 (66–300) 0.231 0.421 0.215 0.411 .000 Q4 (300+) 0.222 0.416 0.182 0.386 .000 Region of practice Northeast 0.203 0.402 0.163 0.369 .000 Midwest 0.274 0.446 0.184 0.388 .000 South 0.314 0.464 0.463 0.499 .000 West 0.209 0.407 0.190 0.392 .000 Patient panel size (Age 65+) 324 211 311 207 .000 <50 0.019 0.135 0.031 0.173 .000 50–199 0.273 0.446 0.311 0.463 .000 200–499 0.548 0.498 0.500 0.500 .000 ≥500 0.160 0.367 0.159 0.365 .294 Number of PCP-year Observations 209,901 69,957 Number of PCPs** 95,179 40,339 PCP, primary care physician; PIM, potentially inappropriate medication; Q, quartile; SD, standard deviation.
↵a Low prescribers included PCPs with PIM prescription rates in Q1-Q3.
↵b High prescribers were PCPs with PIM prescriptions rates ranked in the highest quartile, Q4.
↵** The total number of PCPs (111,461) in the sample is less than the total number of PCPs in the low and high prescriber groups (135,518). This is due to some PCPs being in different groups across multiple years.
↵† Data obtained from 2013-2015 Medicare Part D Public Use File and 2015 American Medical Association Masterfile.
↵‡ Data obtained from 2015 Physician Compare.
- Table 2.
Comparison of Patient Panel and Area-Level Characteristics between Prescribers with High and Low PIM Prescription Rates
Low Prescribers (Q1–Q3)a High Prescribers (Q4)b Difference P-Value Mean SD Mean SD Patient panel characteristics Patient average age 71.5 4.2 70.9 4.0 .000 Proportion female 0.611 0.099 0.610 0.099 .034 Proportion of patients < age 65 y 0.185 0.130 0.191 0.133 .000 High proportion (> 0.74) of white 0.668 0.471 0.774 0.418 .000 High proportion (> 0.35) of duals 0.349 0.477 0.259 0.438 .000 Patient average HCC risk score 1.305 0.406 1.223 0.327 .000 Area-level characteristics PCP-to-specialist ratio per 100,000 residents 0.575 0.070 0.566 0.066 .000 PCP per 100,000 residents 74.5 12.2 72.8 11.8 .000 Average Medicare Spending 9,520 1189 9,755 1197 .000 Number of PCP-year observations 209,901 69,957 Number of PCPs* 95,179 40,339 PCP, primary care physician; PIM, potentially inappropriate medication; Q, quartile; HCC, hierarchical condition category; SD, standard deviation.
Data obtained from 2013–2015 Medicare Part D PUF and 2015 American Medical Association Masterfile.
↵a Low prescribers included PCPs with PIM prescription rates in Q1–Q3.
↵b High prescribers were PCPs with PIM prescriptions rates ranked in the highest quartile, Q4.
↵* The total number of PCPs (111,461) in the sample is less than the total number of PCPs in the low and high prescriber groups (135,518). This is due to some PCPs being in different groups across multiple years.
- Appendix Table A.
Primary Care to Relevant Potentially Inappropriate Medications from Beers Criteria*
Therapeutic Category/Drug Recommendation Therapeutic Category/Drug Recommendation Anticholinergics (Excludes TCAs) Avoid Barbiturates Avoid Brompheniramine (oral) Butalbital Carbinoxamine Phenobarbital Chlorpheniramine Benzodiazepines Avoid for treatment of insomnia, agitation, or delirium Clemastine Short and interm. acting Cyproheptadine Alprazolam Dexbrompheniramine Estazolam Dexchlorpheniramine Lorazepam Diphenhydramine Oxazepam Doxylamine Temazepam Hydroxyzine Triazolam Promethazine Long acting Triprolidine Chlorazepate Antiparkinson agents Chlordiazepoxide Benztropine Avoid Chlordiazepoxide-amitriptyline Trihexyphenidyl Clidinium-chlordiazepoxide Antispasmodics Avoid except in short-term palliative care Clonazepam Belladonna alkaloids Diazepam Clidinium-chlordiazepoxide Flurazepam Dicyclomine Quazepam Hyoscyamine Nonbenzodiazepine hypnotics Avoid chronic use (>90 days) Propantheline Eszopiclone Scopolamine Zolpidem Tertiary TCAs (Alone or in Combination) Avoid Zaleplon Amitriptyline Megestrol Avoid Chlordiazepoxide-amitriptyline Meprobamate Avoid Clomipramine Trimethobenzamide Avoid Imipramine Pain Medications Perphenazine-amitriptyline Meperidine Avoid Trimipramine Indomethacin Avoid Thioridazine Avoid Ketorolac (oral) Avoid Mesoridazine Avoid Skeletal muscle relaxants Avoid Dessicated thyroid Avoid Carisoprodol Testosterone Avoid unless indicated for moderate to severe hypogonadism Chlorzoxazone Cyclobenzaprine Metaxalone Estrogens with/without progestins Avoid oral and topical patch Methocarbamol Orphenadrine Sulfonylureas, long duration Avoid Chlorpropamide Glyburide TCA, tricyclic antidepressant.
↵* Primary care–relevant PIMs were selected from Table 2 of 2012 American Geriatric Society Beers Criteria for Potentially Inappropriate Medication Use in Older Adults.24
- Appendix Table B.
Associations between Primary Care Physician Characteristics and Potentially Inappropriate Medication Prescription Rate*
Coefficient SE Age 0.016† (0.002) Female −0.708† (0.051) DO degree 0.141† (0.037) Medical school cohort Pre to 1980 graduate Reference Category 1980 to 1989 graduate −0.136† (0.037) 1990 to 1999 graduate −0.050 (0.046) 2000 to 2009 graduate 0.075 (0.066) 2010 to present graduate 0.335 (0.173) Primary care specialty Family medicine Reference Category Internal medicine 0.253† (0.033) General practice 0.740† (0.111) Geriatric medicine −0.082 (0.122) Practice region Northeast Reference Category Midwest 0.107 (0.275) South 0.875‡ (0.313) West 0.305 (0.759) Practice size Quartile 1 (1–5) Reference Category Quartile 2 (6–65) −0.350† (0.040) Quartile 3 (66–300) −0.368† (0.044) Quartile 4 (300+) −0.384† (0.051) Patient panel size (age 65+) <50 Reference Category 50–199 −2.808† (0.228) 200–499 −3.690† (0.241) ≥500 −3.714† (0.247) The model was adjusted for patient panel characteristics, year, and hospital referral region fixed effects. Patient panel characteristics included average age of the panel, proportion of female, proportion of Medicare patients who were under 65 years of age, average CMS-Hierarchial Condition Categories risk score of the panel, and whether the panel had higher than sample average proportion of White and dual-eligible patients.
↵* Data obtained from 2013 to 2015 Medicare Part D Public Use File and 2015 American Medical Association Masterfile.
↵† P < .001.
↵‡ P < .05.
- Appendix Table C.
Top 10 Potentially Inappropriate Medications by Primary Care Specialty in 2015*
All Primary Care Specialties Family Medicine Internal Medicine General Practice Geriatric Medicine Generic Name No. of Claims Generic Name No. of Claims Generic Name No. of Claims Generic Name No. of Claims Generic Name No. of Claims 1 Alprazolam 9,307,093 Alprazolam 4,533,793 Alprazolam 4,326,749 Alprazolam 376,966 Lorazepam 98,998 2 Lorazepam 6,242,998 Lorazepam 3,040,468 Lorazepam 2,888,434 Clonazepam 245,675 Alprazolam 69,585 3 Zolpidem Tartrate 5,297,412 Zolpidem Tartrate 2,497,908 Zolpidem Tartrate 2,606,452 Lorazepam 215,098 Clonazepam 45,441 4 Clonazepam 4,327,491 Clonazepam 2,163,092 Clonazepam 1,873,283 Temazepam 163,465 Zolpidem Tartrate 36,628 5 Temazepam 2,190,692 Amitriptyline HCl 1,100,381 Temazepam 1,095,965 Zolpidem Tartrate 156,424 Temazepam 16,109 6 Diazepam 2,007,972 Cyclobenzaprine HCl 1,055,371 Diazepam 876,957 Diazepam 68,466 Diazepam 10,637 7 Amitriptyline HCl 1,990,803 Diazepam 1,051,912 Amitriptyline HCl 825,497 Cyclobenzaprine HCl 63,564 Cyclobenzaprine HCl 9,304 8 Cyclobenzaprine HCl 1,865,347 Temazepam 915,153 Cyclobenzaprine HCl 737,108 Amitriptyline HCl 56,322 Amitriptyline HCl 8,603 9 Dicyclomine HCl 741,928 Promethazine HCl 384,740 Dicyclomine HCl 341,136 Dicyclomine HCl 51,918 Promethazine HCl 6,468 10 Promethazine HCl 682,210 Dicyclomine HCl 343,910 Promethazine HCl 267,129 Promethazine HCl 23,873 Hydroxyzine HCl 6,330 Number of Top 10 PIM Claims 308,103 Number of Total PIM Claims 343,571 PIM, potentially inappropriate medication.
↵* Data obtained from 2013 to 2015 Medicare Part D Public Use File and 2015 American Medical Association Masterfile.
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