Abstract
BACKGROUND:
Specialty medications are commonly dispensed through specialty pharmacies equipped to meet unique monitoring and dispensing requirements. Integrated health system specialty pharmacies (HSSPs) coordinate with health system providers to deliver specialty medications to patients and ameliorate barriers to care. However, payors may restrict specialty medication fills to specialty pharmacies external to the health system, potentially leading to delayed treatment.
OBJECTIVE:
To compare time to treatment initiation among patients whose specialty medications were transferred to external pharmacies and patients whose medications were filled at an internal HSSP.
METHODS:
This was a retrospective, propensity-matched cohort study examining time to treatment initiation in patients with a specialty medication referral to the University of Kentucky HealthCare Specialty Pharmacy between July 1, 2021, and July 1, 2022. Patients were classified into cohorts by receipt of dispensing services from the internal HSSP or an external specialty pharmacy. Data collected via chart review included insurance type, reason for prescription transfer, dates of service (including prescription order, transfer, and receipt of medication), and whether a prior authorization or clinical intervention was performed. Subgroup analyses were performed for patients requiring a prior authorization or clinical intervention. The Wilcoxon signed-rank test was used to assess for statistically significant differences in time to treatment initiation between cohorts.
RESULTS:
A total of 560 patients with external transfers were identified for inclusion into the study, and after exclusion criteria were applied, 408 external transfer patients were propensity matched 1:1 to 408 patients with internal fills (total n = 816). Time to treatment initiation was significantly longer in the external transfer cohort as compared with the internal fill cohort, (18 days vs 12 days; P < 0.0001). The internal fill cohort had a greater mean days from provider order to the medication being ready to fill compared with the external transfer cohort (10 days vs 6 days; P < 0.0001). The internal fill cohort had fewer mean days from the medication being ready to fill to patient receipt of the medication as compared with the external transfer cohort (2 days vs 12 days; P < 0.0001). Similar findings were observed in the subgroup analyses.
CONCLUSIONS:
Average time to treatment initiation was 6 days shorter for patients whose specialty medications were filled at this HSSP compared with externally transferred patients. Delays in therapy can cause a negative impact on patient care and disease state management, with increased concern for specialty populations. The results of this study highlight the need for continued discussion about policies that limit patient choice to in-network pharmacies.
Plain language summary
Patients received their specialty medications faster from University of Kentucky HealthCare’s in-house specialty pharmacy than from other specialty pharmacies. Receiving medications quickly is important for better patient care. Health system specialty pharmacies can help with things like getting approval from insurance, financial help, and making sure medications are delivered quickly. Future research should continue looking into how requirements on where patients fill their medication affects patient care.
Implications for managed care pharmacy
The findings of this study suggest that integrated health system specialty pharmacies may achieve faster time to treatment initiation of specialty medications compared with external specialty pharmacies. Trends toward vertical integration of payors and health care providers and subsequent restrictions on patient choice to in-network specialty pharmacies could potentially cause delays in treatment. The findings from this study emphasize the importance of ongoing conversations among managed care professionals about policies that restrict patient choice.
Although there is not a universal definition of specialty medications, they are usually characterized by a combination of factors, often including mechanism of action, route of administration, adverse drug event (ADE) profile, rare/complex disease state indications, additional shipping and handling requirements, high medication cost, and limited distribution drug (LDD) networks/payor restriction on sites of care.1 Specialty medications are commonly dispensed through specialty pharmacies equipped to meet unique monitoring and dispensing requirements. In 2021, specialty medications represented approximately 50% of total drug spending despite representing only 18% of all prescriptions dispensed, with drug costs totaling $301 billion (a 43% growth from $211 billion in 2016).2 As more therapies are developed and require specialty management, growth and spending in this sector will continue to rise, and additional patients will use specialty medications.3
To serve patients using specialty medications, health system specialty pharmacies (HSSPs) aim to fully integrate care between the provider, pharmacy, and patient to deliver quality care within the health system.4 The integration of HSSPs within the health system affords the opportunity for close communication with health care providers to optimize clinical management of specialty patients. Multidisciplinary coordination between pharmacies, providers, and patients has been shown to optimize health outcomes, prevent prescription errors, and improve ADE monitoring.5,6 The majority of specialty pharmacies frequently offer additional services that improve the quality of medical management of the patient and their disease state, including but not limited to 24/7 access to a specialty pharmacist, medication adherence management, benefits investigation, patient education and ADE management, and proactive patient outreach for prescription refills.7
Most services that specialty pharmacies provide attempt to mitigate barriers to care. Financial burden and high out-of-pocket expenses for prescriptions are functional barriers to care common in specialty medications and can lead to delays in treatment initiation or primary medication nonadherence.8,9 HSSPs are able to quickly address financial barriers by performing benefits investigations and enrolling patients into financial assistance programs, which often includes close coordination between the patient and prescribing clinic that is facilitated by common electronic medical records and collaborative process design.10,11 The coordination of financial assistance provided by specialty pharmacies increases patient access to these medications while alleviating clinic staff workload.12 Integrated HSSPs have reported higher prior authorization approvals, patient satisfaction, and medication adherence as compared with external specialty pharmacies.13,14
For many specialty disease states, it is imperative to initiate therapy quickly to improve treatment outcomes. For example, in the treatment of rheumatoid arthritis, early initiation of disease-modifying treatments improved remission rates and decreased risk of joint damage.15 Increased time to treatment initiation has been associated with worsened outcomes and increased mortality for many types of cancer.16 Furthermore, previous evidence has found that patients initiating oral chemotherapy at an integrated HSSP had a significantly faster time to treatment initiation compared with that of external specialty pharmacies (6.85 vs 10.91 days).17 However, despite these benefits, payer pharmacy network restrictions and LDD networks, when a medication is restricted to be dispensed from a specific pharmacy, frequently force patients to receive specialty medication distribution from external specialty pharmacies.
The objective of this study was to compare time to treatment initiation among health system patients whose specialty medications were transferred to external specialty pharmacies with that of patients managed at the University of Kentucky HealthCare Specialty Pharmacy (UKSP). The results of this study will assist in evaluating the impact of payor-mandated site-of-care restrictions and LDD networks on providing efficient, quality health care.
Methods
STUDY SETTING
UKSP is an integrated HSSP serving University of Kentucky HealthCare (UKHC) since 2015. UKHC is an academic health system based in Lexington that treats patients residing in Kentucky and surrounding states. UKSP provides specialty prescription management and dispensing services to a specialty patient population of predominantly Medicare, Medicaid, and UKHC employee health plan beneficiaries. In addition to specialty medications, UKSP provides prescription dispensing and management for nonspecialty medications to any patient with an active specialty medication at UKHC.
STUDY DESIGN AND SAMPLE SELECTION
This study was a retrospective, propensity-matched cohort study examining time to treatment initiation in patients with a new specialty medication referral to UKSP between July 1, 2021, and July 1, 2022. All new specialty medication referrals within the study period were considered for inclusion. Referrals were excluded if the referred patient was younger than 18 years at the referral date, had prior medications transferred to an external specialty pharmacy (patient was assumed to be established at external specialty pharmacy), were filling at a local specialty pharmacy, or were ultimately referred to a manufacturer free-drug program. Additionally, referrals for hepatitis C, infusion, or nonspecialty medications, as well as referrals for prescriptions that were transferred to a retail pharmacy, were also excluded. Finally, patients who were deceased at the time of data collection (September 2022) or with insufficient data to evaluate time to treatment initiation were excluded.
Specialty medication referrals were subsequently classified into cohorts as receiving dispensing services from the UKSP (internal fill cohort) or a specialty pharmacy external to the health system (transfer cohort). For all referrals, UKSP performs a benefits investigation, prior authorization processing, and evaluates patient eligibility for internal or external financial assistance programs (Figure 1). Based on the results of these services and coordination with the patient, the prescription is transferred to an external specialty pharmacy or scheduled for filling at UKSP. Regardless of the filling pharmacy, UKSP continues to coordinate with the patient to confirm receipt of medication and resolve any barriers to care.
FIGURE 1.
Timeline Depicting Process From Time of New Prescription Referral to Patient Receipt of Medication
After classification, referrals in the transfer cohort were identified and propensity matched on a 1:1 basis to referrals in the internal fill cohort based on age, sex, ethnicity, and diagnosis. The primary outcome was time to treatment initiation, defined as the time of provider order to patient receipt.
DATA COLLECTION AND OUTCOMES
Eligible referrals were identified via reporting query from TherigySTM Specialty Pharmacy Management Software (CPS Solutions, LLC). Data elements collected from this query included ordered medication and indication (International Classification of Diseases, Tenth Revision, Clinical Modification [ICD-10-CM] code), as well as patient identifiers and demographics, including age, sex, and ethnicity. Further, whether or not a clinical intervention or prior authorization occurred for the referral, as well as the date of and reason for the transfer, (transfer cohort only) was also collected from this data source. Examples of the most common clinical interventions performed included identification of medication interactions and prescription clarification. Determination of whether or not a referral was for a specialty medication was made by application of this institution’s specialty formulary to all referrals within the time period. Indication was categorized into common specialty diagnosis types by investigator-classification for study reporting purposes (Supplementary Table 1 (92KB, pdf) , available in online article).
Additional data necessary to evaluate outcomes were collected via manual investigator medical records review, including patient insurance type, date of provider order, ready-to-fill date, and date of patient receipt. For both cohorts, date of provider order was obtained by review of the referred order in Epic electronic medical records (Epic). The ready-to-fill date for the transfer cohort was considered to be the date that the prescription was transferred to the external specialty pharmacy, whereas for the internal fill cohort, it was considered the date the patient was first contacted to schedule a medication dispense. The date of patient receipt was based on patient-reported dates of medication delivery for both cohorts.
The primary outcome was time to treatment initiation, which was defined as the days between the date of provider order and patient receipt. Secondary outcomes included the days between provider order and ready-to-fill status, as well as the days between ready-to-fill status and patient receipt. Subgroup analyses for these outcomes in patients requiring a prior authorization or clinical intervention for their specialty medication referral were also performed.
PROPENSITY SCORE MATCHING AND STATISTICAL ANALYSIS
Propensity score matching and statistical analysis were performed in SAS 9.4 (SAS Institute Inc.). A logistic regression model was used to estimate the propensity score of transfer status for all transfer and potential internal fill cohort patients.18 Age, sex, and ethnicity, as well as medication indication (ICD-10-CM codes), were used in calculation of the propensity score. Insurance type and diagnosis type were not included in calculating the propensity score. Insurance type was not included as the transferred population is known to include a higher proportion of patients with commercial insurance because of in-network pharmacy restrictions. Diagnosis type was not included as it was derived from medication indication, which was included in the propensity match. A SAS macro, %psmatch_multi, was used to make 1:1 matches between transfer and internal fill referrals without replacement.19 Matches were made using a “close” option, which minimized the aggregate distance between propensity scores for all matches.
Cohort demographics and attributes were assessed for significance using the McNemar test for categorical variables and the Wilcoxon signed-rank test for continuous variables. Differences in time to treatment initiation and secondary outcomes in the main and subgroup analyses were assessed for significance using the Wilcoxon signed-rank test.
Results
STUDY POPULATION
A total of 560 referrals transferred to an external specialty pharmacy were identified for initial inclusion. After exclusion criteria were applied, 408 external referrals were included in the main analysis (Figure 2). The transfer cohort was propensity matched 1:1 to an internal fill cohort derived from a pool of 3,084 internal fill referrals to which exclusion criteria were also applied. Cohort age, sex, and race and ethnic composition were similar, with an approximate pooled mean age of 51 years, and both cohorts being predominantly female (transfer n = 258, 63.2%; internal fill n = 271, 66.4%) and white (transfer n = 361, 88.5%; internal fill n = 359, 88%) (Table 1). The most common diagnosis type for referral indications in both cohorts was oncologic medications (transfer n = 131, 32.1%; internal fill n = 95, 23.3%), followed by rheumatologic (transfer n = 112, 27.5%; internal fill n = 100, 24.5%) and gastrointestinal (transfer n = 57, 14%; internal fill n = 70, 17.2%) indications.
FIGURE 2.
Exclusion Criteria Applied to the External Transfer Cohort
TABLE 1.
Demographics of Patients With Transferred Medications and the Control Cohort
| Internal fill cohort (n = 408) | Transfer cohort (n = 408) | P value | |
|---|---|---|---|
| Agea | |||
| Mean [SD] | 50.1 [17] | 51.1 [15] | 0.2346 |
| Median [IQR] | 50 [36, 63] | 53.5 [41, 61] | |
| Range | 18, 88 | 18, 84 | |
| Sexb, n (%) | |||
| Female | 271 (66.4) | 258 (63.2) | 0.2869 |
| Male | 137 (33.6) | 150 (36.8) | |
| Race and ethnicityb, n (%) | |||
| African American | 24 (5.9) | 20 (4.9) | 0.9987 |
| Alaskan Native | 2 (0.5) | 0 | |
| Asian | 1 (0.2) | 3 (0.7) | |
| Hispanic/Latino | 5 (1.2) | 5 (1.2) | |
| Other/unknown | 17 (4.2) | 19 (4.7) | |
| White | 359 (88) | 361 (88.5) | |
| Diagnosis typeb, n (%) | |||
| Dermatology | 38 (9.3) | 28 (6.9) | 0.0043c |
| Gastroenterology | 70 (17.2) | 57 (14) | |
| Neurology | 48 (11.8) | 27 (6.6) | |
| Oncology | 95 (23.3) | 131 (32.1) | |
| Pulmonary | 32 (7.8) | 25 (6.1) | |
| Rheumatology | 100 (24.5) | 112 (27.5) | |
| Unknown/other | 25 (6.1) | 28 (6.9) | |
| Insurance typeb, n (%) | |||
| Commercial | 112 (27.5) | 367 (90) | <0.0001c |
| Medicare | 144 (35.3) | 38 (9.3) | |
| Medicaid | 152 (37.2) | 3 (0.7) | |
| Reason for transfer, n (%) | |||
| Prescription transfer to payer in-network pharmacy | – | 327 (80.1) | – |
| Inability to dispense medication (ie, LDD, payer mandate, OOS) | – | 56 (13.7) | |
| Patient choice | – | 12 (2.9) | |
| Other/unknown | – | 13 (3.2) | |
| Workflowb | |||
| Clinical intervention performed | 37 (9.1) | 10 (2.5) | <0.0001c |
| Prior authorization required | 369 (90.4) | 368 (90.2) | 0.9081 |
En dash indicates “not applicable.”
a Wilcoxon signed-rank test used to assess for significance.
b McNemar test was used to assess significance.
c Significance at the P<0.05 level.
IQR = interquartile range; LDD = limited distribution drug; OOS = out of stock.
Referred patients in the transfer cohort predominantly had commercial payers (n = 367, 90%), whereas the patients in internal fill cohort most commonly had Medicaid payers (n = 152, 37.2%). Similar numbers of patients in both cohorts needed a prior authorization processed for their referral (transfer n = 368, 90.2%; internal fill n = 369, 90.4%); however, a higher proportion in the internal fill cohort had a clinical intervention performed (transfer n = 10, 2.5%; internal fill n = 37, 9.1%). Among the transfer cohort, the most common reason for transfer was payer requirement of an in-network specialty pharmacy for medication dispensing (n = 327, 80.1%).
TIME TO TREATMENT INITIATION
In the main analysis, time to treatment initiation in the transfer cohort was significantly longer (transfer median 13 days, internal fill 6 days; P < 0.0001) as compared with the internal fill cohort (Table 2). Time from provider order to ready-to-fill status was significantly shorter in the transfer cohort (transfer median 1 day, internal fill 4 days; P < 0.0001); however, time from ready-to-fill status to patient receipt was significantly longer (transfer median 9 days, internal fill 1 day; P < 0.0001). Frequency distributions for each outcome measure are provided in histograms in Figure 3. Distributions were right-skewed, with numerous high outliers.
TABLE 2.
Time to Treatment From Medication Order
| All patients | ||||
|---|---|---|---|---|
| Internal fill cohort (n = 408) | Transfer cohort (n = 408) | Difference | P value | |
| Time from provider order to patient receipt (days)a | ||||
| Mean [SD] | 12 [17] | 18 [17] | -6 | |
| Median [IQR] | 6 [4, 13] | 13 [7, 23] | – | <0.0001b |
| Range | 1, 142 | 1, 147 | – | |
| Time from provider order to ready-to-fill (days)a | ||||
| Mean [SD] | 10 [17] | 6 [10] | 4 | |
| Median [IQR] | 4 [1, 11] | 1 [1, 6] | – | <0.0001b |
| Range | 1, 138 | 1, 83 | – | |
| Time from ready-to-fill to patient receipt (days)a | ||||
| Mean [SD] | 2 [2] | 12 [11] | -10 | |
| Median [IQR] | 1 [1, 4] | 9 [6, 15] | – | <0.0001b |
| Range | 1, 8 | 1, 118 | – | |
| Prior authorization subgroup | ||||
| Internal fill cohort(n = 369) | Transfer cohort(n = 368) | |||
| Time from provider order to patient receipt (days)a | ||||
| Mean [SD] | 12 [17] | 18 [17] | -6 | |
| Median [IQR] | 6 [4, 13] | 13 [7, 25] | – | <0.0001b |
| Range | 1, 142 | 1, 147 | – | |
| Time from provider order to ready-to-fill (days)a | ||||
| Mean [SD] | 10 [17] | 6 [11] | 4 | |
| Median [IQR] | 4 [1, 10] | 2 [1, 6.5] | – | <0.0001b |
| Range | 1, 138 | 1, 83 | – | |
| Time from ready-to-fill to patient receipt (days)a | ||||
| Mean [SD] | 2 [2] | 12 [12] | -10 | |
| Median [IQR] | 2 [1, 4] | 9 [6, 15] | – | <0.0001b |
| Range | 1, 8 | 1, 118 | – | |
| Clinical intervention subgroup | ||||
| Internal fill cohort (n = 37) | Transfer cohort(n = 10) | |||
| Time from provider order to patient receipt (days)a | ||||
| Mean [SD] | 11 [14] | 32 [27] | -21 | |
| Median [IQR] | 6 [4, 14] | 16 [13, 54] | – | <0.0001b |
| Range | 2, 55 | 4, 82 | – | |
| Time from provider order to ready-to-fill (days)a | ||||
| Mean [SD] | 9 [14] | 13 [19] | -4 | |
| Median [IQR] | 4 [1, 13] | 6.5 [1, 16] | – | 0.9411 |
| Range | 1, 53 | 1, 63 | – | |
| Time from ready-to-fill to patient receipt (days)a | ||||
| Mean [SD] | 2 [2] | 19 [22] | -17 | |
| Median [IQR] | 2 [1, 3] | 10.5 [7, 23] | – | <0.0001b |
| Range | 1, 7 | 4, 76 | – | |
En dash indicates “not applicable.”
a Wilcoxon signed-rank test used to assess for significance.
b Significance at the P < 0.05 level.
IQR = interquartile range.
FIGURE 3.
Frequency Distributions for Primary and Secondary Outcomes
In the subanalysis of referrals requiring prior authorization processing (transfer n = 368, internal fill n = 369), similar results were observed as compared to the main analysis (Table 3). Time to treatment initiation was significantly longer in the transfer cohort (transfer median 13 days, internal fill 6 days; P < 0.0001). A significantly shorter time from provider order to ready-to-fill status was observed in the transfer cohort (transfer median 2 days, internal fill 4 days; P < 0.0001). Similar to the main analysis, a significantly longer time from ready-to-fill status to patient receipt was observed (transfer median 9 days, internal fill 2 days; P < 0.0001).
In the subset of referrals requiring clinical intervention (transfer n = 0; internal fill n = 37), time to treatment initiation was significantly longer in the transfer cohort (transfer median 16 days; internal fill 6 days; P < 0.0001. Time from provider order to ready-to-fill status was not significantly different between the two cohorts (transfer median 6.5 days, internal fill 4 days; P = 0.9411), as was time from ready-to-fill status to patient receipt (transfer median 10.5 days, internal fill 2 days; P < 0.0001).
Discussion
This study described time to treatment initiation among patients whose specialty medications were transferred to external specialty pharmacies as compared with a matched cohort of patients managed by this HSSP. In the overall analysis, as well as in the clinical intervention and prior authorization subgroups, time to treatment initiation was significantly longer in the transfer cohort. Previous research has evaluated the positive effect of HSSP management on rates of medication adherence and time to treatment initiation for oral oncolytics.13,17 This study observed similar trends toward longer time to treatment initiation in transferred medications when including the majority of disease states managed by this HSSP.
Delays in treatment initiation have previously been associated with poorer outcomes for patients in specialty disease states.13,15 HSSPs are able to assist patients in initiating their treatments, with minimal delays in care, by coordinating prior authorization processing with health system clinics, applying for internal and external financial assistance, and efficiently communicating with the patient for timely medication dispensing and delivery. Evidence of the gain to medication dispensing efficiency provided by these aspects of HSSP management is supported by the findings of reduced time to treatment initiation in the internal fill cohort of this study.
Health system clinic staff have previously reported that completing prior authorizations often impedes clinic workflow while also creating a barrier to treatment initiation for patients.12 Integrated HSSPs frequently have dedicated staff to complete prior authorization on behalf of providers, speeding up processing time to mitigate this barrier. Previous research has found that prior authorizations performed by HSSPs resulted in increased rates of approval as well as faster turnaround times as compared with processing via health system clinic staff, ultimately addressing the barrier to treatment and increasing patient access to specialty medications.13,14 Additionally, health benefits formulary restrictions, such as required step-wise therapy and preferred products, have been cited as an impediment to patients receiving their specialty medications, slowing time to treatment initiation.5 Specialty pharmacy team members are able to navigate formulary mandates to help improve turnaround times.
At this HSSP, prior authorizations are performed for all patients whose medications require one. Prior authorization approval is received prior to transferring prescriptions to external specialty pharmacies, indicating that delays in care at external specialty pharmacies are independent of prior authorization processing. In our study’s prior authorization subanalysis, the mean time to treatment initiation in the internal fill cohort was 6 days shorter than that in the transfer cohort. Furthermore, the largest delay was seen in the time from ready-to-fill status (ie, the prior authorization was already approved) to patient receipt of the medication in the transfer cohort compared with the internal cohort (median 9 vs 2 days). As the ready-to-fill status occured after the prior authorization was processed and the medication transferred, this suggests that delays in care seen in the transfer cohort cannot be explained by additional processing burden of the external specialty pharmacy.
Furthermore, the close proximity and integration of an HSSP with health system providers allows for the efficient management of necessary clinical interventions identified by the specialty pharmacy. This was seen in the clinical intervention subgroup in which the median time to treatment initiation for the internal cohort was 6 days compared with 16 days for the external cohort. The close collaboration of clinic providers with HSSPs and usage of a common electronic medical record allows for rapid disease state monitoring and fewer prescription errors.6 Additionally, documentation within the mutual electronic medical record by the HSSP is also beneficial for the clinic staff and allows providers across the health system to quickly access pertinent documentation regarding the patient’s treatment.20
LIMITATIONS
A major demographic difference between the otherwise matched internal fill and transfer cohorts was the proportion of commercially insured patients. The vast majority of patients in the external cohort had commercial payers (90%), whereas inversely, Medicaid and Medicare payers were more common in the internal fill cohort (37.2% and 35.3%, respectively). This demographic difference is a limitation of this study, as the two cohorts are not equal in this regard. Commercial payers more frequently mandate site-of-care restrictions, usually to external specialty pharmacies that are vertically integrated with the commercial payer.4,20,21 Aside from in-network dispensing pharmacy restrictions, prescriptions for LDDs or other medications not available on an HSSP formulary require transfer. Circumstances such as site-of-care restrictions and LDDs may force patients to fill at pharmacies external to their health system, leading to suboptimal time to treatment initiation.
An additional limitation of this study includes the single-site design, as standard-of-care practice at other HSSPs and subsequently time to treatment initiation may vary from the observed results in this study. Without access to external specialty pharmacy data, patient-reported dates of receipt of their medication were used, which introduces the possibility for recall bias. Also, without knowledge of how patients were managed at external specialty pharmacies, this study is unable to draw firm conclusions that the decreased time to treatment initiation was attributable to additional management services provided by UKSP. Furthermore, the retrospective, nonrandomized design can introduce time-varying confounders and precludes the ability to make definite conclusions about causality. However, a strength of this study includes the propensity-matching methods used, allowing variances in time to treatment initiation attributable to diagnosis or demographics to be addressed. Future research should be conducted evaluating multiple HSSPs and health systems to best quantify how time to treatment initiation varies among health systems.
Conclusions
This study found that time to treatment initiation was significantly longer in a cohort of patients with medications transferred to an external specialty pharmacy as compared with a matched cohort of patients with medications filled at an integrated HSSP. The culmination of these results further highlights that time to treatment initiation is a barrier faced by specialty pharmacies as a whole and must continue to be addressed to best improve patient outcomes. The rise of insurance vertical integration, pharmacy benefit managers, and LDD networks limits the ability of HSSPs to fill specialty medications for patients, provide overall comprehensive disease state management, and may subsequently result in delays in patient care. The results of this study highlight the need for continued discussion about policies that limit patient choice for their dispensing pharmacy, including restriction of dispensing to in-network pharmacies, LDD networks, and prohibition of use of common mail delivery services.
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