ORIGINAL ARTICLE

Prior Authorization in the Treatment of Patients with pDPN and FM Hilary E. D. Placzek, PhD, MPH*; Elizabeth T. Masters, MS, MPH†; Tao Gu, PhD‡; Joseph C. Cappelleri, PhD§; Thomas E. Wasser, PhD¶; Andrew G. Clair, PhD**; Joseph P. Cook, PhD, JD**; Debra F. Eisenberg, MS, PhD‡ *Industry Sponsored Research, HealthCore, Inc., Andover, Massachusetts ; †Health Economics and Outcomes Research, Pfizer, Inc., New York, New York ; ‡Industry Sponsored Research, HealthCore, Inc., Wilmington, Delaware ; §Statistics, Pfizer, Inc., Groton, Connecticut ; ¶ Biostatistics, HealthCore, Inc., Wilmington, Delaware ; **Pfizer, Inc., New York, New York, U.S.A.

& Abstract Purpose: To determine prior authorization (PA) impact on healthcare utilization, costs, and pharmacologic treatment patterns for painful diabetic peripheral neuropathy (pDPN) and fibromyalgia (FM). Methods: This retrospective, observational, longitudinal cohort study used medical and pharmacy claims data. Newly diagnosed patients treated for FM or pDPN between 7/1/2007 and 12/31/2011 were included. PA and no PA groups were matched by propensity score 4:1. Medical resource utilization, direct medical and pharmacy costs, and treatment pattern differences were compared. Pre and postindex differences between PA and no PA cohorts were determined by difference in difference analysis. Results: Analysis of 2,315 FM patients (1,852 PA; 463 no PA) demonstrated greater increases in postindex all-cause costs

($197; P = 0.6673) and disease-related costs ($72; P = 0.4186) in the PA cohort. Analysis of 1,300 pDPN patients (1,040 PA; 260 no PA) demonstrated postindex all-cause cost increases of $1,155 more in the no PA cohort (P = 0.6248); disease-related costs decreased $2,809 more in the no PA cohort (P = 0.4312). Treatment patterns were similar between cohorts; opioid usage was higher in the FM PA cohort (P = 0.0082). Conclusions: There was no evidence of statistically significant differences between PA and no PA cohorts in either FM or pDPN populations for total all-cause or disease-related costs. & Key Words: diabetic neuropathy, fibromyalgia, pain, healthcare utilization, prior authorization, pharmacologic treatment

BACKGROUND Address correspondence and reprint requests to: Hilary Placzek, PhD, MPH, GNS Healthcare, Inc., One Charles Park, Cambridge, MA 02142, U.S.A. E-mail: [email protected] Disclosures: This research was supported by Pfizer, Inc. Joseph C. Cappelleri, Elizabeth T. Masters, Joseph Cook, and Andrew Clair are employees of Pfizer Inc. Hilary Placzek, Debra Eisenberg, Tao Gu, and Tom Wasser are employees of Healthcore, Inc., who were paid consultants to Pfizer, Inc. for this study. Submitted: May 30, 2014; Revision accepted: September 15, 2014 DOI. 10.1111/papr.12258

© 2014 World Institute of Pain, 1530-7085/15/$15.00 Pain Practice, Volume 15, Issue 1, 2015 E9–E19

Painful diabetic peripheral neuropathy (pDPN) and fibromyalgia (FM) are two conditions causing chronic pain among patients requiring a variety of treatments. Neuropathic pain (NeP) is defined by the International Association for the Study of Pain as “pain caused by a lesion or disease of the somatosensory nervous system.”1 pDPN is a type of NeP that has been shown to affect approximately 26% of those with type II diabetes.2 Patients with pDPN may experience pain, tingling, numbness, sensitivity to touch, or loss of

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coordination, and are at increased risk for developing lower-extremity ulcers.3 FM is another type of chronic pain condition affecting approximately 2 to 5% of the U.S.A. population and is characterized by chronic widespread pain.4,5. Symptoms associated with fibromyalgia include sleep disruption, fatigue, cognitive disturbance, and other somatic symptoms.6 Key focus areas of pDPN and FM management include diagnosis, appropriate treatment, and pain management. There are a number of medications that are used to treat pDPN and FM, but only a few are FDA approved for these indications: pregabalin and duloxetine for pDPN, and pregabalin, duloxetine and milnacipran for FM. Other pharmacologic treatments frequently used include tricyclic antidepressants, selective serotonin re-uptake inhibitors, selective serotonin/ norepinephrine re-uptake inhibitors, anticonvulsants, other antidepressants, anesthetics, opioids, and NSAIDs. Prior authorization (PA) is required by some healthcare plans in the U.S.A. for patients to have insurance coverage for access to certain medications, due to perceived higher costs of those medications. Improving quality of care and appropriateness of utilization are also key concepts for PA. However, incentive-based (tiered) formularies and drug utilization management programs, such as PA, have been shown to effectively control prescription expenditures.7–16 In Margolis et al., PA was shown to effectively control access to specific medications, with a $27 lower mean per member per year expenditure for the targeted medication. The overall effect included an increase in the use of opioids and alternative pain management therapies and was associated with increased pDPNrelated prescription costs ($274 higher mean per member per year in the PA restricted group) – providing evidence that while reductions can be achieved on spending for selected prescription drugs these savings may be offset by increases in other medical spending, resulting in an overall increase in medical costs.17 Similar studies have been conducted in other populations. In a study, evaluating the impact of PA policy in a commercially insured population, implementation of a PA did not result in statistically significant differences in pDPN-related medical expenditures.16 Studies of step therapy protocols for medications in FM, pDPN, and postherpetic neuralgia found an increase in all-cause and disease-related expenditures in one case11 and no difference in expenditures between the restricted and unrestricted cohorts in another.12

Few studies, apart from those mentioned above, have examined the impact of PA processes on patients diagnosed with illnesses or conditions where pain is the principal feature, underscoring a need for further research in this area. Although there is a significant body of published research evaluating the impact of drug utilization management programs (eg, formulary restrictions, prior authorization (PA), step edits, quantity level limits), there is a lack of consistency on how programs are evaluated, and most adopt a payer perspective rather than a patient, clinical, or provider focus.13 This study builds on work by other researchers and continues to investigate the impact of PA policies with respect to patients diagnosed with illnesses or conditions where pain is the principal feature. Specific study objectives include: (1) compare healthcare utilization and cost (all-cause and disease-related) of pDPN and FM patients between those who are enrolled in pharmacy benefit plans with prior authorization (PA cohort) and those who are enrolled in pharmacy benefit plans without prior authorization (no PA cohort), and (2) describe how pharmacologic treatment patterns for pDPN or FM patients differ between PA and no PA cohorts.

METHODS Data Source The study applies a retrospective, observational design with predefined outcome measures. The data source for the study is the HealthCore Integrated Research Environment (HIRE).18 The HIRE contains a broad, clinically rich, and geographically diverse spectrum of longitudinal claims data from health insurance plans in the northeastern, southern, mid-western, and western regions of the U.S.A. The database represents administrative claims information from the largest health benefits organization in the U.S.A. and includes lines of business such as health maintenance organizations (HMOs), point of service (POS) plans, preferred provider organizations (PPOs), consumer directed health plans (CDHP), and indemnity plans. Within the HIRE, HealthCore, Inc. has access to medical and pharmacy claims information, partial laboratory result data, and medical record data from member health plans representing approximately 50 million covered lives. HealthCore’s research environment enables the outcomes data retrospectively collected from patients to be compared according to

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the presence or absence of PA (patients enrolled in plans with pharmacy benefit designs requiring prior authorization compared to patients enrolled in plans not requiring prior authorization). This study utilized de-indentified medical and pharmacy claims with dates of service from January 1, 2007 through June 30, 2012. All data were handled with full compliance to the Health Insurance Portability and Accountability Act of 1996 (HIPAA) as a limited data set. As the data were anonymous and there was no patient interaction, Institutional Review Board approval was not required. Patients This observational, retrospective administrative claims database study used claims-based algorithms to identify FM and pDPN patients. The algorithm used a combination of pharmacy and medical claims to identify the patients with the respective conditions. In addition, using 4-to-1 (PA to no PA) propensity score matching (PSM), patients enrolled in plans with pharmacy benefit designs requiring prior authorization (PA cohort) were matched to patients enrolled in plans not requiring prior authorization (no PA cohort).19,20. Further details about the PSM are provided below in the statistical analysis section. The analysis-selected data from a relatively small subset of patients who purchased administrative services only (ASO) plan and who had the option of participating in specific pharmacy benefit structures. The specific employer groups that purchased the pharmacy benefit structure with PA in place served as the PA cohort, while those in the pharmacy benefit structure without PA in place represented the no PA cohort. For all patients in the FM and pDPN populations, the index date was the date of the first pharmacy claim for FM or pDPN medication observed within the intake period, which extended from July 1, 2007 through December 31, 2011. Patients were eligible for inclusion in the study population if they were 18 years of age on the index date, had continuous health plan benefit enrollment for at least 6 months prior to the index date, and were not Medicare enrollees with Part-D plans for prescription benefits. They were eligible for inclusion in the FM population if they had two or more diagnosis codes for FM (ICD-9 729.1) at least 60 days apart, and had initiated a therapy for FM within 6 months of first diagnosis (duloxetine, pregabalin, milnacipran, NSAIDs, antidepressants, opioids, topical agents, or anticonvulsants). This time period of 6 months provides a reasonable amount of time between diagnosis and when an individual may take a

medication to treat their diagnosis. Patients were excluded from the FM analysis if they had ICD-9 diagnosis codes of 345.xx (generalized nonconvulsive epilepsy) or 780.39 (other convulsions), if they had a pharmacy claim for any FM-related medications during the 6 months prior to index date, if they had transplant surgery, long-term care facility residence greater than 90 days, or cancer with the exception of basal cell, squamous cell skin cancer, or benign neoplasms. Patients with pDPN cannot be precisely identified using only the diagnoses codes in administrative claims data, as the codes do not distinguish between DPN patients with and without pain. Therefore, a claimsbased algorithm was implemented. The criteria for pDPN patient selection were as follows: (1) Patients must have at least one claim with a diagnosis of DPN (ICD-9 250.6x or 357.2x), and (2) Patients must have initiated a pDPN-related therapy, with at least 1 pharmacy claim for pDPN medication within 6 months following the first DPN diagnosis (duloxetine, pregabalin, NSAIDs, antidepressants, opioids, topical agents, or anticonvulsants). As such, patients were excluded from the pDPN population if they had 1 or more pharmacy claims for any pDPN-related medication during the 6 months prior to index date. Patients were not included in either population if they had dual FM and pDPN diagnoses, or if data points of interest were missing. Outcome Variables The primary end point measures the impact of PA policies on medical resource utilization and costs, and the secondary end point examines the impact of PA policies on the treatment patterns of patients with painful diabetic peripheral neuropathy (pDPN) or fibromyalgia (FM) in a population of commercially insured patients. Costs included the sum of plan-paid and patient-paid costs, and were adjusted to 2012 dollar values based on U.S. Census Bureau inflation ratios. Allcause costs were defined as direct medical (and pharmacy) costs associated with utilization of health care incurred by each study patient during the pre and postindex periods. Disease-related costs (FM or pDPN) were defined as the medical costs that were associated with services that had been identified as FM (ICD-9 code 729.1x) or pDPN (ICD-9 diagnosis codes 250.6x or 357.2x) claims. Claims that were included in the cost calculations encompassed inpatient admissions (INP), emergency room visits (ED), physician office visits (PO), outpatient visits (OP), and pharmacy claims (Pharm).

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The secondary end points included treatment pattern analysis of pharmacologic agents used during the study period. The use of individual FDA approved medications was compared between PA/no PA patients and stratified by condition (pDPN or FM). These medications included nonsteroidal anti-inflammatory drugs (NSAIDs), antidepressants (serotonin/norepinephrine re-uptake inhibitors (SNRIs), tricyclics, others (excluding duloxetine and milnacipran which were analyzed separately), anticonvulsants (excluding pregabalin which was analyzed separately), opioids, topical agents, pregabalin, duloxetine, and milnacipran. Treatment pattern end points of interest included type and number of concomitant medications, adherence with index medication as measured by proportion of days covered (PDC), rates of discontinuation, and rates of switching. PDC was defined as the number of days supply divided by treatment duration *100. Treatment duration was defined as the date of last index drug minus date of first index drug on or after index date, corresponding to total days’ supply of medication. Patients were classified as discontinued if they had not filled an index drug within the allowable gap in the postindex follow-up period. The allowable gap between two fills or administrations of a particular medication within continuous therapy was designated as 45 days for oral drugs, and 60 days for injectable drugs. Patients were classified as having a medication switch if a claim for a new drug from a different treatment class was observed after stopping the index drug. Patient demographic and clinical characteristics were quantified for each of the cohorts. The mean Deyo– Charlson Index (DCI) score was calculated to assess levels of comorbidity. DCI comorbidity scores take into account the number and seriousness of comorbid diseases which affect an individual’s longevity.21 The resulting score provides a score of risk of death, based on specific comorbid conditions; higher scores indicate greater calculation of comorbidity. Statistical Analysis In determining the covariates used for the PSM, candidate demographic and clinical characteristics were compared between the PA and no PA cohorts using logistic regression (using t-tests for those factors or variables that are continuous and chi-square tests for those that are discrete) to determine the predictor variables that best discriminated between the two groups.19,20 The characteristics assessed included age

group on index date, gender, geographic region, insurance plan type, length of follow-up, comorbidity index, specific comorbidities of interest, and nonpharmacologic treatments of interest. A cutoff P-value of < 0.20 (a reasonable cutoff that allows giving a covariate the benefit of the doubt for inclusion) was used to determine in a univariate logistic regression model which variables differed with respect to PA vs. no PA and to include them subsequently as covariates in the PSM. These covariates were then were used to create each individual propensity score. Using these propensity scores, matched pairs were created using the nearest available method. Once the matched groups were created, goodness of fit statistics (t-tests for continuous data and chi-square for discrete variables) were applied to the sample to establish the generalizability of the study to the population of patients with FM and pDPN. Outcomes such as healthcare utilization and cost, and treatment patterns between the PA/no PA cohorts were assessed separately for FM and pDPN. A difference in difference analysis was applied using a two independent groups t-test for continuous variables to compare mean differences between pre and postindex periods in the PA and no PA cohorts.22 Levene’s test was used to compare equality variances on the difference in differences between the PA and no PA cohorts. If the test rejected the null hypothesis (P < 0.05), the variances were addressed using Satterthwaite’s method; otherwise, the two variances were pooled. Mean, standard deviation, and median values for costs and utilization were presented. The chi-square test was used for categorical variables; t-tests and analysis of variance (ANOVA) were used for normally distributed continuous variables. All outcome variables were normally distributed except for mean costs associated with outpatient services in the pDPN population. For this variable, the Wilcoxon–Mann–Whitney test was used to test the statistical significance of a continuous variable that was not normally distributed.22. A standard P-value of less than 0.05 was considered to indicate a statistically significant difference in the outcome between cohorts.

RESULTS Baseline Demographic and Clinical Characteristics There were a total of 29,746 patients meeting inclusion criteria in the FM population (Figure 1). Of that total, 29,283 patients (98.4%) were identified in the PA cohort and 463 (1.6%) in the no PA cohort. Using the variables

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Patients with at least 2 diagnosis codes for FM (ICD9 729.1x) N=190,239

Patients with at least 1 diagnosis code for DPN (ICD9 250.6x or 357.2x) N=95,068

Patients who initiated FM Rx within 183 days of FM diagnosis N=180,698

Patients who initiated NeP Rx within 183 days of DPN diagnosis N=90,667

Patients who are at least 18 years of age on index date N=180,698

Patients who are at least 18 years of age on index date N=90,667

Patients with at least 6 months continuous enrollment preand post- index date N=119,005

Patients with at least 6 months continuous enrollment preand post-index date N=51,843

After exclusion criteria applied N=29,746

After exclusion criteria applied

Patients after propensity score match in inal cohort N (PA)=1,852 N (no pA)=463

Patients after propensity score match in inal cohort N (PA)=1,040 N (no PA)=260

N=14,233

Figure 1. Attrition table for study inclusion. FM, fibromyalgia; RX, prescription; PA, prior authorization; DPN, diabetic peripheral neuropathy; NeP, neuropathic.

of gender, geographic region, insurance plan type, comorbidity index, depression, neuropathies, physical therapy, chiropractic care, and acupuncture to determine propensity scores, a total of 2,315 eligible patients were included in the PSM and final study cohort (1,852 in the PA cohort, and 463 in the no PA cohort). Goodness of fit analysis demonstrated no statistically significant differences between the PA and no PA cohorts for the FM population. The mean age of this cohort was 45.1 years, and it was 66.6% female. Mean DCI score was 0.2. Depression diagnosis was present in 8.2% of the population during the pre-index period; 46.5% and 49.9% of the FM population received physical therapy and chiropractic care, respectively (Table 1). A total of 14,233 patients met the inclusion criteria for the pDPN population (Figure 1). Of that total, 13,973 (98.2%) were identified in the PA cohort, and 260 (1.8%) were in the no PA cohort. Based upon the selection variables of age group on index date, gender, geographic region, insurance plan type, length of followup, comorbidity index, coronary artery disease, depression, bipolar disorder, anxiety disorder, sleep disorders, physical therapy, transcutaneous electrical stimulation, and chiropractic care, a total of 1,300 eligible patients were included in the PSM and final study population (1,040 in the PA cohort, and 260 in the no PA cohort). Goodness of fit analysis demonstrated no statistically significant differences between the PA and no PA cohorts for the pDPN population. Mean DCI score was 2.9. The mean age of the population was 63.8 years and it was 58.4% male. Pre-index coronary

artery disease diagnosis was present in 22.2%, and 20.8% received physical therapy (Table 1). All-cause Cost (Medical + Pharmacy) All-cause costs are presented in Table 2. Within the FM population, the mean postindex all-cause medical costs were $2,337 higher than during the pre-index period in the PA cohort, and in the no PA cohort postindex all-cause medical costs were $2,153 higher than during the pre-index period. The no PA cohort experienced a smaller increase in all-cause medical costs, with the difference in mean differences being $184 lower compared to the PA cohort (P = 0.6821). For total all-cause pharmacy costs, postindex costs were $248 higher than during the pre-index period in the PA cohort, and for the no PA cohort postindex costs were $235 higher than during the pre-index period. The no PA cohort experience a $13 smaller increase in mean all-cause pharmacy costs compared to the PA cohort (P = 0.8351). For total all-cause costs, the postindex costs were $2,585 higher than during the pre-index periods in the PA cohort, and in the no PA cohort, postindex costs were $2,388 higher than during the pre-index period. Thus, the no PA cohort experienced a smaller increase in total all-cause costs with the difference in these mean differences being $197 lower compared to the PA cohort (P = 0.6673). Within the pDPN population, the mean postindex allcause medical costs were $2,655 higher than during the pre-index period in the PA cohort, and for the no PA

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Table 1. Patient Demographic and Clinical Data, Stratified by Disease State and Pharmacy Benefit Enrollment Fibromyalgia (FM) Population FM Population, Overall Number of patients, N 2,315 Mean Age, years (SD) 45.1 (12.8) Gender, % female 66.6 Geographic Region (%) Mid-west 25.4 Northeast 18.7 South 2.2 West 53.7 Insurance Plan Type on Index Date (%) HMO† 7.8 POS† 67.0 19.5 PPO† Other 5.7 Comorbidities DCI‡, mean (SD) 0.2 (0.5) Coronary artery disease (%) 1.8 Depression (%) 8.2 Bipolar disorder (%) 3.8 Anxiety disorder (%) 5.0 Neuropathic pain (%) 0.1 Neuropathies (%) 0.1 Sleep disorders (%) 2.6

Painful Diabetic Peripheral Neuropathy (pDPN) Population

FM PA (matched controls)

FM No PA* (cases)

pDPN Population, Overall

pDPN PA (matched controls)

pDPN No PA* (cases)

1,852 45.1 (12.9) 66.8

463 45.1 (12.6) 65.9

1,300 63.8 (13.1) 41.6

1,040 63.9 (12.8) 42.4

260 63.4 (14.5) 38.5

25.4 18.9 2.2 53.5

25.5 18.1 2.2 54.2

35.7 39.8 6.2 18.2

35.4 40.4 6.7 17.5

36.9 37.7 4.2 21.2

7.7 67.0 19.4 5.8

8.2 66.7 19.7 5.4

12.8 69.8 12.5 5.0

12.9 69.4 12.7 5.0

12.3 71.2 11.5 5.0

2.9 (2.0) 22.2 9.3 5.3 5.1 1.8 8.7 8.4

2.9 (1.9) 22.8 9.1 5.4 5.2 1.9 8.9 8.3

3.2 (2.2) 19.6 10.0 5.0 4.6 1.5 7.7 8.8

0.2 (0.5) 1.7 8.0 3.6 4.8 0.2 0.1 2.5

0.2 (0.5) 2.2 8.9 4.5 6.0 0 0.2 2.8

*Using propensity score matching techniques, patients enrolled in the pharmacy benefit were matched to patients who were not enrolled in the pharmacy benefit. † HMO, Health Maintenance Organization; PPO, Preferred Provider Organization; POS, Point of Service. ‡ DCI, Deyo–Charlson Comorbidity Index. Reported for 6 months pre-index period.

cohort, the postindex costs were $3,828 higher than the pre-index costs (Table 2). The mean difference in differences between the medical costs was $1,173 higher for the no PA cohort (P = 0.5976). For total all-cause pharmacy costs, the postindex costs were $344 higher than during the pre-index period for the PA cohort, and for the no PA cohort, the postindex costs were $327 higher than during the pre-index period. The no PA cohort experienced a smaller increase in all-cause pharmacy costs, with the difference in the mean differences being $17 lower compared to PA cohort (P = 0.8461). For total all-cause costs, the postindex costs were $2,999 higher than during the pre-index period in the PA cohort, and in the no PA cohort postindex costs were $4,154 higher than during the preindex period. The mean difference in differences being $1,155 higher in the no PA cohort (P = 0.6248). Results above indicate that, for total all-cause medical and total all-cause pharmacy costs, there was no evidence of statistically significant differences between the PA and no PA cohorts in either the FM or pDPN populations. Disease-attributable Costs (Medical + Pharmacy) Disease-attributable costs are presented in Table 3. Within the FM population, the mean postindex

disease-attributable medical cost was $41 lower than during the pre-index period in the PA cohort; postindex disease-attributable medical costs were $112 lower than pre-index in the no PA cohort. The no PA cohort experienced a greater reduction in costs with the mean difference in differences being $71 lower compared to PA cohort (P = 0.4180). For total disease-attributable costs, the postindex cost was $83 higher than during the pre-index time periods in the PA cohort; postindex costs were $11 higher than pre-index costs in the no PA cohort. The no PA cohort had a smaller overall increase in total disease-attributable costs with difference in mean differences being $72 lower in the no PA cohort compared to the PA cohort (P = 0.4186). Within the pDPN population, the mean postindex disease-attributable medical cost in the PA cohort was $1,654 lower than during the pre-index period (Table 3). Mean postindex disease-attributable medical cost was $4,464 lower than during the pre-index period in the no PA cohort. The no PA cohort experience a greater reduction in costs with the difference in differences being $2,810 lower compared to the PA cohort (p=0.4315). For total disease-attributable costs, postindex costs were $1,543 lower than pre-index costs in the PA cohort. Total disease-attributable postindex costs were $4,352 lower than pre-index costs in the no PA

$2,337 ($1,829 to $2,846) $248 ($195 to $301) $2,585 ($2,071 to $3,099)

$2,655 ($744 to $4,566) $344 ($252 to $437) $2,999 ($1,087 to $4,912)

$11,609 $2,547 $14,156

Mean Difference (CI)

$5,741 $844 $6,585

Postindex period

$5,271 $853 $6,125

$15,362 $2,432 $17,794

N = 260 $11,534 $2,105 $13,640

Postindex period

N = 463 $3,118 $618 $3,737

Pre-Index period

$3,828 ( $375 to $8,030) $327 ($174 to $479) $4,154 ( $77 to $8,385)

$2,153 ($1,432 to $2,875) $235 ($127 to $344) $2,388 ($1,651 to $3,125)

Mean Difference (CI)

No WellPoint Pharmacy Benefit (No PA)

$1,173 $18 $1,155

$184 $13 $197

DiD*

$3,184 to $5,529 $218 to $182 $3,211 to $5,521

$1,263 to $895 $131 to $106 $1,289 to $895

CI

0.5976 0.8461 0.6248

0.6821 0.8351 0.6673

P-value (T-test)

Difference Comparison between PA and no PA

$41 ( $161 to $80) $124 ($110 to $137) $83 ( $39 to $205)

$1,654 ( $3,245 to $62) $111 ($94 to $127) $1,543 ( $3,134 to $48)

$1,789 $111 $1,899

Mean Difference (CI)

$521 $124 $645

Postindex period

$419 $123 $542

$967 $112 $1,078

N = 260 $5,430 $0 $5,430

Postindex period

N = 463 $531 $0 $531

Pre-Index period

$4,464 ( $11,305 to $2,377) $112 ($85 to $139) $4,352 ( $11,185 to $2,481)

$112 ( $236 to $12) $122 ($93 to $152) $11 ( $116 to $137)

Mean Difference (CI)

No WellPoint Pharmacy Benefit (No PA)

$2,810 $1 $2,809

$71 $1 $72

DiD*

$7,471 to $1,851 – $7,466 to $1,848

$320 to $178 – $324 to $179

CI†

0.4315 0.9461 0.4312

0.4180 0.9477 0.4186

P-value (T-test)

Difference Comparison between PA and no PA

*DiD, difference in differences (no PA pre–postdifference minus PA pre–postdifference). † We excluded all patients with ≥ 1 pharmacy claim for FM- or pDPN-related medication during the 6 months pre-index period; therefore patients had no pre-index disease-attributable pharmacy costs, which results in no confidence interval value for DiD. ‡ Total medical costs include all direct medical costs associated with utilization of health care for this study population. These costs include all possible costs captured during a patient encounter, and are categorized as inpatient hospitalizations, emergency department visits, physician office visits, and outpatient visits.

Fibromyalgia Number of patients N = 1,852 Total medical costs‡, mean $562 Pharmacy prescriptions cost, mean $0 Total medical + pharmacy costs, mean $562 Painful Diabetic Peripheral Neuropathy Number of patients N = 1,040 Total medical costs‡, mean $3,442 Pharmacy prescriptions cost, mean $0 Total medical + pharmacy costs, mean $3,442

Pre-Index period

WellPoint Pharmacy Benefit (PA)

Table 3. Disease-Attributable Healthcare Cost During 6 Months Pre and Postindex Period for FM and pDPN Patients

*DiD, difference in differences (no PA pre–postdifference minus PA pre–postdifference). † Total medical costs include all direct medical costs associated with utilization of health care for this study population. These costs include all possible costs captured during a patient encounter, and are categorized as inpatient hospitalizations, emergency department visits, physician office visits, and outpatient visits.

Fibromyalgia Number of Patients N = 1,852 $3,404 Total medical costs†, mean Pharmacy prescriptions cost, mean $596 Total medical + pharmacy costs, mean $4,000 Painful Diabetic Peripheral Neuropathy Number of patients N = 1,040 $8,954 Total medical costs†, mean Pharmacy prescriptions cost, mean $2,202 Total medical + pharmacy costs, mean $11,157

Pre-Index period

WellPoint Pharmacy Benefit (PA)

Table 2. All-Cause Healthcare Cost During 6 Months Pre and Postindex Period for FM and pDPN Patients

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cohort. The no PA cohort experienced a greater reduction in postindex costs with the difference in mean differences being $2,809 lower than the PA cohort (P = 0.4312). In summary, results in this subsection indicate that, for total disease-attributable medical and pharmacy costs, there was no evidence of statistically significant differences between the PA and no PA cohorts in either the FM or pDPN populations. Treatment Patterns During the entire 6 month postindex time period, within the FM population, opioids, (64.6% of the matched PA sample and 57.9% of the matched no PA sample; P = 0.0082) and NSAIDs (49.4% in PA vs. 51.8% in no PA; P = 0.3499) were the most commonly prescribed medications (Table 4). Index medication adherence data for FM patients are presented in Table 4. Mean PDC was 77 in both the PA cohort and no PA cohorts. The rate of discontinuation was 70.9% in the PA cohort, and 73.7% in the no PA cohort, with a mean time of 21.5 and 22.3 days,

respectively. Rates of switch were 18.4% and 17.9% with a mean time of 18.4 days and 13.7 days in the PA and no PA cohorts, respectively. Rates of augmentation were 1.4% in the PA cohort and 0.0% in the no PA cohort. There were no significant differences between index-drug treatment patterns or adherence between the PA and no PA cohorts within the FM population. For medication use at any time in the postindex period, within the pDPN population, opioids (71.0% of PA cohort and 75.0% of no PA cohort) and NSAIDs were the most common medications (28.4% in PA, 28.1% in no PA) (Table 4). Index medication adherence data for pDPN patients are presented in Table 4. Mean PDC was 76 in the PA cohort and 73 in the no PA cohort. Rate of discontinuation was 74.0% in the PA cohort, and 71.5% in the no PA cohort, with a mean time of 24.7 and 26.1 days, respectively. Rates of switch were 13.9% and 14.5% with a mean time of 24.3 days and 18.2 days in the PA and no PA cohorts, respectively. There were no significant differences between index-drug treatment patterns between the PA and no PA cohorts within the pDPN population.

Table 4. Disease-Related Medication Use in the FM and pDPN Populations During 6-Month Postindex Period FM Population PA N = 1,852

No PA N = 463

Pharmacologic Treatment Classes, n (%) Pregabalin 57 (3.1) 20 (4.3) Duloxetine 83 (4.5) 15 (3.2) Milnacipran 19 (1.0) 3 (0.6) NSAIDS 914 (49.4) 240 (51.8) Antidepressants SNRIs 41 (2.2) 10 (2.2) Tricyclics 120 (6.5) 21 (4.5) Others 101 (5.5) 25 (5.4) Opioids 1,197 (64.6) 268 (57.9) Topicals 47 (2.5) 16 (3.5) Anticonvulsants 86 (4.6) 29 (6.3) Adherence Data on Patients with Oral Index Medication N = 1,695 N = 418 PDC ratio %, mean (SD) 77 (23.7) 77 (26.0) Patients with PDC > 80%, n (%) 1,105 (65.2) 266 (63.6) Index-Drug Treatment Patterns for patients with Oral Index Medication N = 1,695 N = 418 Continued, n (%) 158 (9.3) 35 (8.4) Discontinued, n (%) 1,202 (70.9) 308 (73.7) Time to discontinue in days, mean (SD) 21.5 (23.7) 22.3 (22.3) Switch, n (%) 312 (18.4) 75 (17.9) Time to switch in days, mean (SD) 18.4 (27.8) 13.7 (25.1) Augment, n (%) 23 (1.4) 0 (0.0) Time to augment in days, mean (SD) 0 (0) 0 (0) Nonpharmacologic Treatments, n (%) Physical Therapy 857 (46.3) 220 (47.5) Transcutaneous electrical stimulation 14 (0.8) 5 (1.1) Chiropractic care 924 (49.9) 231 (49.9) Acupuncture 52 (2.8) 17 (3.7) Items shown in bold italic indicate that the measure achieved statistical significance at P < 0.05.

pDPN Population P-Value

PA N = 1,040

No PA N = 260

P-Value

0.1921 0.3011 0.5976 0.3499

43 25 1 295

(4.1) (2.4) (0.1) (28.4)

12 8 0 73

(4.6) (3.1) (0.0) (28.1)

0.7305 0.5371 1.0000 0.9264

0.9436 0.1286 0.9635 0.0082 0.2665 0.1523

11 34 50 738 28 167

(1.1) (3.3) (4.8) (71.0) (2.7) (16.1)

8 8 10 195 3 38

(3.1) (3.1) (3.8) (75.0) (1.2) (14.6)

0.0152 0.8754 0.5087 0.1957 0.1459 0.5682

0.5851 0.5674

N = 893 76 (24.9) 565 (63.3)

N = 221 73 (26.8) 124 (56.1)

0.0783 0.0497

– – 0.5837 – 0.1858 – N/A

N = 893 106 (11.9) 661 (74.0) 24.7 (28.3) 124 (13.9) 24.3 (29.2) 2 (0.2) 0 (0)

N = 221 30 (13.6) 158 (71.5) 26.1 (30.0) 32 (14.5) 18.2 (25.8) 1 (0.5) 0 (0)

– – 0.5892 – 0.2780 – N/A

0.6395 0.5621 1.0000 0.3583

216 4 72 4

(20.8) (0.4) (6.9) (0.4)

54 1 20 0

(20.8) (0.4) (7.7) (0.0)

1.0000 1.0000 0.6653 0.3166

Prior Authorization in Treatment of pDPN and FM  E17

DISCUSSION In this study, we compared pre-index and postindex costs and differences in costs between those patients with PA and no PA for medications prescribed for the treatment of FM and pDPN. Results demonstrated no significant difference between the PA and no PA cohorts when both total all-cause and disease-attributable costs among the FM and pDPN populations were compared, showing a lack of evidence that the PA process results in a cost savings for these populations of patients. The results of the present research are broadly consistent with those of Udall et al. and Suehs et al., who had similar findings in that the studied formulary restrictions for these disease areas were not associated with a statistically significant decrease in costs.23,24 Moreover, costs associated with PA administrative fees were not included in this analysis. It is possible that costs among patients in the PA cohort could be higher than those in the no PA cohort if these administrative costs had been included in the analysis. The burden of administering PA has been demonstrated to be considerable to medical and pharmacy providers, taking as much as 15 to 33 minutes and costing a mean of $41.60 to complete each request.25–27 This cost has a negative impact on the operating margins of medical providers that should not be overlooked.26 Our results also concur with those seen by Johnston et al., who examined the association between PA and step therapy restrictions in Medicare patients with pDPN, PHN, or FM, and found no associated significant cost savings in the FM population.28 Johnston et al. found that step therapy restrictions in the combined pDPN/PHN population actually resulted in a nonsignificant increase in pain-related health expenditures, while PA restrictions resulted in significantly decreased painrelated health expenditures.28 There were high rates of opioid and NSAID use among this patient population. In the FM population, opioid use was significantly higher in the PA cohort, while this difference was not seen in the pDPN population. The shifting of patients to alternate pharmacologic therapy choices was also evidenced in research by Suehs et al., in which there was a statistically significant increase in the use of gabapentin and a nonsignificant increase in the use of opioids with no significant decrease in disease-related pharmacy expenditures following the implementation of restricting step therapy policy.24 Currently, there is not a good evidence base to support the use of NSAIDs in managing

neuropathic pain. A few small trials of short duration and/or mild to moderate neuropathic pain severity, while showing some benefit, are not substantiated because an evidence base does not exist.29 The use of opioid analgesics in patients with FM is currently reserved as a medication of last resort, or even recommended against by several guidelines including the American Pain Society in 2005, and the European League Against Rheumatism in 2008, due to a lack of evidence of effectiveness coupled with evidence of a physiologic mechanism of opioid induced hyperalgesia.30–32 It is notable that NSAIDs and opioids were prescribed in a high proportion of patients within this study. While it cannot be confirmed that patients within this population were using either medication class specifically to treat their neuropathic pain condition due to the nature of claims data research, their use suggests a need for further research into the root cause of prescribing habits within the population of patients with neuropathic pain conditions. In a population of FM and pDPN patients, Johnston et al. also demonstrated that pregabalin restrictive policies do have an impact upon the choice of drug, with a significant increase in proportion of patients who were prescribed duloxetine over pregabalin.33 We found a nonsignificant increase in duloxetine usage within the FM population; the difference in significance may be explained by the fact that Johnston’s population was limited to only patients who indexed on duloxetine or pregabalin. The patient population examined in this research experienced high rates of index medication discontinuation, with low mean times to discontinuation. These treatment patterns were consistent between PA and no PA cohorts, as well as between FM and pDPN populations. Further research with a patient survey would help to clarify the reasons for this noted treatment pattern. There are limitations to this research. Claims data provide a partial snapshot of the complete portfolio of disease management for FM and pDPN. Other factors such as quality of life measurement and measures of functionality would provide additional information to compare the outcomes of patients with PA or no PA in place. Additional research investigating these outcomes would provide a more comprehensive assessment related to the impact of PA policies on patients diagnosed with pDPN or FM. Due to the goodness of fit statistics applied to the results, this study should be generalizable to FM and pDPN patients, but will not necessarily apply to all PA requirements for other disease states. Prescrip-

E18 

PLACZEK ET AL.

tion claims for pain medications were assumed to be prescribed to manage the diagnosed painful conditions being studied, but it is possible that patients within the cohort used these medications to treat a different pain causing diagnosis, such as osteoarthritis. The nature of claims data does not allow for the confirmation that medications were used for a specific diagnosis. Medical record review and/or survey based research could be used to confirm this relationship. Furthermore, literature has shown that study results from claims data analyses can be sensitive to the choice of database used and hence the type of data captured.34 Therefore, differences in the data collection process used in the HIRE could contribute to possible differences in other published study results on the same research topic. In conclusion, this research attempted to establish what difference, if any, existed in the economic outcomes of patients who were required to obtain PA before accessing a specific treatment option for the treatment of a painful condition, specifically FM or pDPN. Thirdparty payers make use of such policies in an effort to control the rising costs of health care. The results of our investigation suggest that PA did not have an identifiable impact on total all-cause or total disease-related costs, and has no significant impact on the utilization of healthcare resources in these patients. The information obtained from this research may be useful for third-party payers in evaluating their policies, and may lead to a reduced burden of paperwork and associated costs for healthcare providers, pharmacies, and third-party payers if the requirement for PA is discontinued.

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Prior authorization in the treatment of patients with pDPN and FM.

To determine prior authorization (PA) impact on healthcare utilization, costs, and pharmacologic treatment patterns for painful diabetic peripheral ne...
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