Closed-Loop Medication Management with an Electronic Health Record System in U.S. and Finnish Hospitals.

Many medication errors in the hospital setting are due to manual, error-prone processes in the medication management system. Closed-loop Electronic Medication Management Systems (EMMSs) use technology to prevent medication errors by replacing manual steps with automated, electronic ones. As Finnish Helsinki University Hospital (HUS) establishes its first closed-loop EMMS with the new Epic-based Electronic Health Record system (APOTTI), it is helpful to consider the history of a more mature system: that of the United States. The U.S. approach evolved over time under unique policy, economic, and legal circumstances. Closed-loop EMMSs have arrived in many U.S. hospital locations, with myriad market-by-market manifestations typical of the U.S. healthcare system. This review describes and compares U.S. and Finnish hospitals' EMMS approaches and their impact on medication workflows and safety. Specifically, commonalities and nuanced differences in closed-loop EMMSs are explored from the perspectives of the care/nursing unit and hospital pharmacy operations perspectives. As the technologies are now fully implemented and destined for evolution in both countries, perhaps closed-loop EMMSs can be a topic of continued collaboration between the two countries. This review can also be used for benchmarking in other countries developing closed-loop EMMSs.

Claims-based pharmacy markers for comprehensive medication management program case identification: Validation against concurrent and prospective healthcare costs and utilization.

BACKGROUND: Three claims-based pharmacy markers (complex, costly and risky medications) were developed to help automatically identify patients for comprehensive medication management. OBJECTIVE: To evaluate the association between newly-developed markers and healthcare outcomes. METHODS: This was a two-year retrospective cohort study using PharMetrics Plus patient-level administrative claims in 2014 and 2015. We included all claims from 1,541,873 individuals with: (1) 24-month medical and pharmacy enrollment in 2014 and 2015, (2) aged between 18 and 63 in 2014, and (3) known gender. Independent/control variables came from 2014 while outcomes came from 2014 (concurrent analysis) and 2015 (prospective analysis). Three pharmacy markers, separately or together, were added to four base models to predict concurrent and prospective healthcare costs (total, medical, and pharmacy) and utilization (having any hospitalization, having any emergency department visit, and having any readmission). We applied linear regression for costs while logistic regression for utilization. Measures of model performances and coefficients were derived from a 5-fold cross-validation repeated 20 times. RESULTS: Individuals with 1+ complex, risky or costly medication markers had higher comorbidity, healthcare costs and utilization than their counterparts. Nine binary risky category markers performed the best among the three types of risky medication markers; the Medication Complexity Score and three-level complex category both outperformed a simpler complex medication indicator. Adding three novel pharmacy markers separately or together into the base models provided the greatest improvement in explaining pharmacy costs, compared with medical (non-medication) costs. These pharmacy markers also added value in explaining healthcare utilization among the simple base models. CONCLUSIONS: Three claims-based pharmacy indicators had positive associations with healthcare outcomes and added value in predicting them. This initial study suggested that these novel markers can be used by pharmacy case management programs to help identify potential high-risk patients most likely to benefit from clinical pharmacist review and other interventions.

Comparing and validating medication complexity from insurance claims against electronic health records.

BACKGROUND: Patient effort to comply with complex medication instructions is known to be related to nonadherence and subsequent medical complications or health care costs. A widely used Medication Regimen Complexity Index (MRCI) has been used with electronic health records (EHRs) to identify patients who could benefit from pharmacist intervention. A similar claims-derived measure may be better suited for clinical decision support, since claims offer a more complete view of patient care and health utilization. OBJECTIVE: To define and validate a novel insurance claims-based medication complexity score (MCS) patterned after the widely used MRCI, derived from EHRs. METHODS: Insurance claims and EHR data were provided by HealthPartners (N = 54,988) (Bloomington, Minnesota) and The Johns Hopkins Health System (N = 28,589) (Baltimore, Maryland) for years 2013 and 2017, respectively. Yearly measures of medication complexity were developed for each patient and evaluated with one another using rank correlation within different clinical subgroupings. Indicators for the presence of individually complex prescriptions were also developed and assessed using exact agreement. Complexity measures were then correlated with select covariates to further validate the concordance between MCS and MRCI with respect to clinical metrics. These included demographic, comorbidity, and health care utilization markers. Prescribed medications in each system's EHR were coded using the previously validated MRCI weighting rules. Insurance claims for retail pharmacy medications were coded using our novel MCS, which closely followed MRCI scoring rules. RESULTS: EHR-based MRCI and claims-based MCS were significantly correlated with one another for most clinical subgroupings. Likewise, both measures were correlated with several covariates, including count of active medications and chronic conditions. The MCS was, in most cases, more associated with key health covariates than was MRCI, although both were consistently significant. We found that the highest correlation between MCS and MRCI is obtained with patients who have similar counts of pharmacy records between EHRs and claims (HealthPartners: P = 0.796; Johns Hopkins Health System: P = 0.779). CONCLUSIONS: The findings suggest good correspondence between MCS and MRCI and that claims data represent a useful resource for assessing medication complexity. Claims data also have major practical advantages, such as interoperability across health care systems, although they lack the detailed clinical context of EHRs. DISCLOSURES: The Johns Hopkins University holds the copyright to the Adjusted Clinical Groups (ACG) system and receives royalties from the global distribution of the ACG system. This revenue supports a portion of the authors' salary. No additional or external funding supported this work. The authors have no conflict of interest to disclose.

Development of measurable criteria to identify and prioritize patients for inclusion in comprehensive medication management programs within primary care settings.

BACKGROUND: Pharmacists optimize medication use and ensure the safe and effective delivery of pharmacotherapy to patients using comprehensive medication management (CMM). Identifying and prioritizing individual patients who will most likely benefit from CMM can be challenging. Health systems have far more candidates for CMM than there are clinical pharmacists to provide this service. Furthermore, current evidence lacks widely accepted standards or automated mechanisms for identifying patients who would likely benefit from a pharmacist consultation. Existing tools to prioritize patients for pharmacist review often require manual chart review by a pharmacist or other clinicians or data collection by patient survey. OBJECTIVES: To (1) create new medication risk markers for identifying and prioritizing patients within a population and (2) identify patients who met these new markers, assess their clinical characteristics, and compare them with criteria that are widely used for medication therapy management (MTM). METHODS: Along with published literature, a panel of subject matter experts informed the development of 3 medication risk markers. To assess the prevalence of markers developed, we used Multum, a medication database, for medication-level characteristics, and for patient-level characteristics, we used QuintilesIMS, an administrative claims database derived from health plans across the United States, with data for 1,541,873 eligible individuals from 2014-2015. We compared the health care costs, utilization, and medication gap among patients identified through MTM criteria (both broad and narrow, as these are provided as ranges) and our new medication management score markers. RESULTS: We developed 3 claims-derivable markers: (1) instances when a patient filled a medication with high complexity that could affect adherence, (2) instances where a patient filled a medication defined as costly within a therapeutic category that could affect access, and (3) instances when a patient filled a medication defined as risky that could increase incidence of adverse drug events. In the QuintilesIMS database, individuals with 2 new medication risk markers plus at least 3 conditions and more than $3,017 in medication costs when compared with individuals meeting narrow MTM eligibility criteria (≥ 8 medications, ≥ 3 conditions, and > $3,017 medication costs) had increased costs ($36,000 vs $26,100 total; $24,800 vs 21,400 medical; $11,300 vs $4,800 pharmacy); acute care utilization (0.328 vs 0.256 inpatient admissions and 0.627 vs 0.579 emergency department visits); and 1 or more gaps in medication adherence(41.5% vs 34.7%). CONCLUSIONS: We identified novel markers of medication use risk that can be determined using insurance claims and can be useful to identify patients for CMM programs and prioritize patients who would benefit from clinical pharmacist intervention. These markers were associated with higher costs, acute care utilization, and gaps in medication use compared with the overall population and within certain subgroups. Providing CMM to these patients may improve health system performance in relevant quality measures. Evaluation of CMM services delivered by a pharmacist using these markers requires further investigation. DISCLOSURES: No outside funding supported this study. All authors are Johns Hopkins employees. The Johns Hopkins University receives royalties for nonacademic use of software based on the Johns Hopkins Adjusted Clinical Group (ACG) methodology. Chang, Kitchen, Weiner, and Kharrazi receive a portion of their salary support from this revenue. The authors have no conflicts of interests relevant to this study.

Budgeting in the post-COVID era: Be in the room where it happens.

In an effort to expedite the publication of articles related to the COVID-19 pandemic, AJHP is posting these manuscripts online as soon as possible after acceptance. Accepted manuscripts have been peer-reviewed and copyedited, but are posted online before technical formatting and author proofing. These manuscripts are not the final version of record and will be replaced with the final article (formatted per AJHP style and proofed by the authors) at a later time.

Assessment of Availability, Clinical Testing, and US Food and Drug Administration Review of Biosimilar Biologic Products.

Importance: Biosimilar biologic products were authorized in 2010, after the US Congress established an expedited pathway for approval of clinically similar versions of approved biologic products. Unlike for most small-molecule generic drugs, approval requirements for a biosimilar included animal studies and a comparative efficacy clinical trial. Objective: To analyze the evidence required to support a biosimilarity license application, examine the US Food and Drug Administration (FDA) evaluation process, and estimate the costs of the key clinical trial evidence. Design: This study evaluated all biosimilar biologic products approved from January 2010 through October 2019, using the publicly available FDA review documents, disclosures from ClinicalTrials.gov, and the published peer-reviewed literature. The costs of efficacy clinical trials were estimated using licensed proprietary software. Main Outcomes and Measures: The following elements of each approved biosimilar were evaluated: the extent of human clinical testing to establish that the biosimilar had no clinically meaningful differences with the reference product, results of comparative animal studies, and FDA-cited application deficiencies. The cited deficiencies included the following categories: (1) facility inspection, (2) manufacturing or product quality, (3) animal studies, (4) laboratory analytical studies, (5) phase 1 and/or immunogenicity studies, and (6) phase 3 comparative efficacy trials. Results: As of October 2019, the FDA had approved 23 biosimilar biologics for 9 reference products. The 29 clinical trials that established that the efficacy of the biosimilar products was comparable to that of the reference products enrolled a median (interquartile range [IQR]) of 504 (258-612) patients, had a median (IQR) estimated cost of $20.8 ($13.8-$35.3) million, and had a median (IQR) treatment duration of 52 (28-68) weeks. Substantial deficiencies temporarily halted the review of 9 applications, and the most frequent deficits were failed facilities inspections (n = 5) and manufacturing process quality problems (n = 6). The approved biosimilar submissions included 51 animal studies on species that included mice, rats, rabbits, dogs, and cynomolgus monkeys. Negative outcomes in 2 animal studies were attributed to differences between human and test species. The FDA generally met the standard 12-month review deadlines or stopped the review clock when serious deficiencies were identified. Conclusions and Relevance: This study found that most comparative efficacy trials supporting the FDA approval of biosimilars appeared to be as rigorous as and often larger, longer, and more costly than pivotal trials for new molecular entities. Further research is needed into whether less costly comparative efficacy trials could provide adequate evidence of biosimilarity and whether animal studies contribute useful scientific evidence.

Integrating E-Prescribing and Pharmacy Claims Data for Predictive Modeling: Comparing Costs and Utilization of Health Plan Members Who Fill Their Initial Medications with Those Who Do Not.

BACKGROUND: Nonfilling of prescribed medications is a worldwide problem of serious concern. Studies of health care costs and utilization associated with medication nonadherence frequently rely on claims data and usually focus on patients with specific conditions. Past studies also have little agreement on whether higher medication costs associated with higher adherence can reduce downstream health care consumption. OBJECTIVES: To (a) compare the characteristics between people with and without complete medication initiations from a general population and (b) quantify the effect of medication initiation on health care utilization and expenditures with propensity score weighting. METHODS: We conducted a retrospective cohort study using 2012 and 2013 electronic health records (EHR) and insurance claims data from an integrated health care delivery network. We included 43,097 eligible primary care patients in the study. Annual medication fill rates of initial prescriptions in 2012 were defined as the number of filled prescriptions from claims divided by the number of e-prescriptions from EHRs, while excluding all refills. A claim was considered filled if (a) EHR and claims records were from the same drug class; (b) claims occurred between the date of a current EHR order and that of the next EHR order of the same class; and (c) the maximum fill rate was 100%. The 6 annual outcomes included total costs, medical costs, pharmacy costs, being a high-cost "outlier" (in top 5%), having 1 or more hospitalizations, and having 1 or more emergency department (ED) visits. Individuals were classified as either having completed all medication initiations (100% annual filling rate for initiations) or not. We used propensity score weighting to control for baseline differences between complete and incomplete initial fillers. We adopted linear and logistic regressions to model costs and binary utilization indicators for the same year (concurrently) and next year (prospectively). RESULTS: Approximately 42% of the study sample had complete medication initiations (100% filling rate), while the remaining 58% had incomplete initiations. Individuals who fully filled initial prescriptions had lower comorbidity burden and consumed fewer health care resources. After applying propensity score weighting and controlling for variables such as the number of prescription orders, patients with complete medication initiations had lower overall and medical costs, concurrently and prospectively (e.g., $751 and $252 less for annual total costs). Complete medication initiation fillers were also less likely to have concurrent health care utilization (OR = 0.78, 95% CI = 0.68-0.90 for hospitalization; OR = 0.77, 95% CI = 0.72-0.82 for ED admissions) but no difference in prospective utilization other than for ED visits (OR = 0.93, 95% CI = 0.87-0.99). CONCLUSIONS: Identifying the subpopulation of patients with incomplete medication initiations (i.e., filling less than 100% of initial prescriptions) is a pragmatic approach for population health management programs to align resources and potentially contain cost and utilization. DISCLOSURES: No outside funding supported this study. This study applied the Adjusted Clinical Group (ACG) case-mix/risk adjustment methodology, developed at Johns Hopkins Bloomberg School of Public Health. Although ACGs are an important aspect of this study, the goal of the study was not to directly assess or evaluate the methodology. The Johns Hopkins University receives royalties for nonacademic use of software based on the ACG methodology. Chang, Kharrazi, and Weiner receive a portion of their salary support from this revenue. Chang is also a part-time consultant for Monument Analytics, a health care consultancy whose clients include the life sciences industry, as well as plaintiffs in opioid litigation. Alexander is past Chair of FDA's Peripheral and Central Nervous System Advisory Committee; has served as a paid advisor to IQVIA; is a co-founding Principal and equity holder in Monument Analytics; and is a member of OptumRx's National P&T Committee. These arrangements have been reviewed and approved by Johns Hopkins University in accordance with its conflict of interest policies. The other authors have nothing to disclose.

Assessment of impact of daily huddles and visual displays on medication delivery timeliness in a large academic medical center.

PURPOSE: To evaluate the impact of pharmacy team huddles and near real-time performance dashboards on the punctuality of medication delivery departures from the adult inpatient pharmacy of a multihospital medical center. METHODS: Baseline delivery punctuality was established during a 2-week unannounced preintervention period, followed by the implementation of daily huddles focused on delivery timeliness along with visual displays of delivery performance metrics. The 5- to 15-minute huddles included pharmacy technicians, pharmacists, and managers. Printed visual displays that tracked hour-by-hour timeliness over the prior 24 hours were prominently displayed in the pharmacy. The primary outcome was the overall change in the percentage of punctual medication delivery departures (ie, deliveries leaving the pharmacy at the scheduled time) during the 2 weeks after implementation of huddles and visual displays (the postintervention period). Punctuality was assessed at both the day and shift levels using generalized estimating equations in a piecewise regression model. A multivariable model was constructed using a forward stepwise selection process to assess the potential impacts of workload drivers and staffing levels on medication delivery punctuality. RESULTS: During the pre- and postintervention periods, the punctuality of a total of 1,032 deliveries was recorded. Punctuality of deliveries across all shifts increased by 37% (95% confidence interval [CI], 18%-56% [P < 0.001]), from 50% to 87%, immediately following implementation of the huddle intervention. When punctuality was assessed by individual shift, we observed statistically significant increases for the day (35% [95% CI, 13%-57%], P = 0.002), evening (34% [95% CI, 12%-56%], P = 0.003) and night (57% [95% CI, 35%-79%], P < 0.001) shifts. During the forward stepwise multivariable model-building process, order volume, message volume, and technician staffing levels were not significantly correlated with delivery punctuality at the day or shift level. CONCLUSION: Daily huddles with visual displays were successful in improving the punctuality of medication delivery departures from the pharmacy, independent of workload drivers and staffing levels.

Medication safety risks to be managed in national implementation of automatic substitution of biological medicines: a qualitative study.

OBJECTIVES: To explore relevant Finnish stakeholders' perceptions on the automatic substitution of biological medicines with particular focus on medication safety and issues that need to be considered to create an appropriate model for automatic biological product substitution. DESIGN: Qualitative interview study. METHODS: Data were collected in semistructured individual (n=17), pair (n=7) and group (n=8) interviews (32 interviews, 62 participants) in 2018. Participants represented a wide range of stakeholders involved in the pharmacotherapy process: community pharmacists (n=8 interviews), authorities (n=7), prescribers (n=7), pharmaceutical industry and wholesalers (n=6), patients/customers (n=2), hospital pharmacists (n=1) and nurses (n=1). Inductive content analysis was performed. RESULTS: Benefits of automatic substitution were identified as cost savings, more patients receiving biological treatments and enhanced continuity of treatment. Six major risk categories were identified: (1) the patient's medication is interrupted or complicated temporarily or permanently, (2) the patient uses two products with the same active substance, (3) the traceability of the product is compromised, (4) the patient cannot get into healthcare in case of problems, (5) the patient does not receive substitution-related advice from a pharmacy and (6) the patient is distracted by the support material he/she receives. Several risk mitigation measures were commonly mentioned: medication and device counselling by pharmacists (n=23), infrequent substitution interval (n=15) and better knowledge on biosimilars among healthcare providers (n=13). CONCLUSION: Automatic substitution of biologics is associated with risks that should be prospectively managed before implementing the procedure. The substitution also introduces new tasks and communication needs to those involved in actual medication use process, particularly to community pharmacists who will be responsible for substitution and counselling the patients.

Costs Associated with Productivity Loss Among U.S. Patients Newly Diagnosed with Multiple Myeloma Receiving Oral Versus Injectable Chemotherapy.

BACKGROUND: The use of novel drug agents in the treatment of multiple myeloma (MM) has been associated with improved therapeutic outcomes and survival; however, MM continues to pose a significant economic burden on patients and health care systems. Evaluating economic implications of therapies can provide key points of distinctions between available treatment options. Patients with MM may experience productivity loss, including lost days from work or inability to work due to MM symptoms or to undergoing treatment. Although direct costs of illness have been well described in the literature, indirect costs associated with MM are understudied. OBJECTIVE: To compare the extent of disability benefit use and resultant workplace productivity loss among U.S. adult patients with newly diagnosed MM who received oral versus injectable MM therapy. METHODS: A retrospective cohort study was conducted using the Truven Health Analytics MarketScan Commercial Claims and Encounters, Medicare Supplemental Coordination of Benefits, and Health and Productivity Management databases (2008-2015). Workplace absenteeism, as measured by disability benefit use, was evaluated 1 year before and 1 year after first MM diagnosis. Patients receiving only oral chemotherapy were compared with those who received injectable therapy. Absenteeism days and associated costs were compared among study groups using multivariable zero-inflated Poisson regression. RESULTS: The final study cohort included 299 patients with newly diagnosed MM, of whom 73 received oral therapy only and 226 received injectable therapy. Treatment type was a significant predictor of disability benefit use. Patients who received injectable therapy missed an average of 110 work days in the 1 year after diagnosis, compared with 87 for patients receiving only oral therapy (difference of 23 days, 95% CI = 19-26, P < 0.001). Treatment type was also a significant predictor of costs associated with lost productivity. Patients who received injectable therapy experienced productivity loss valued at $18,315, compared with patients who only received oral drug therapy ($14,429). The difference between these estimates was statistically significant ($3,886, 95% CI = $3,540-$4,231, P < 0.001). CONCLUSIONS: Patients newly diagnosed with MM face significant losses in productivity. Patients receiving injectable MM therapy use significantly more disability benefits and incur higher productivity costs, compared with those receiving oral MM therapy. Further studies elucidating the nature of the differences between injectable and noninjectable chemotherapy users are needed. DISCLOSURES: This study was funded by Millennium Pharmaceuticals, a wholly owned subsidiary of Takeda Pharmaceutical Company. Yong and Noga are employees of Millennium Pharmaceuticals. Merola reports personal fees from Millennium Pharmaceuticals during the time of this study.

Limited distribution networks stifle competition in the generic and biosimilar drug industries.

A limited distribution network (LDN) restricts the distribution channel for a pharmaceutical drug to 1 or a very small number of distributors. This strategy may allow for more effective allocation of drugs in shortage and is purported to help ensure the safe distribution of high-risk drugs to small patient populations. However, in recent years, some drug companies, including Turing Pharmaceuticals, have used LDNs to prevent generic and biosimilar companies from accessing samples of drug products necessary to perform testing required by the FDA for generic and biosimilar drug applications. LDNs also hamper provider access to pharmaceuticals and facilitate price gouging. This paper synthesizes existing knowledge on the misuse of LDNs to thwart competition, clarifies the relationship between limited distribution and the FDA Risk Evaluation and Mitigation Strategies, discusses proposed federal legislation under consideration to address this issue, and offers several policy options to remedy this anticompetitive practice, including authorizing the FDA to require the sale of approved drug products to generic and biosimilar drug developers.

Evaluating the Impact of Prescription Fill Rates on Risk Stratification Model Performance.

BACKGROUND: Risk adjustment models are traditionally derived from administrative claims. Prescription fill rates-extracted by comparing electronic health record prescriptions and pharmacy claims fills-represent a novel measure of medication adherence and may improve the performance of risk adjustment models. OBJECTIVE: We evaluated the impact of prescription fill rates on claims-based risk adjustment models in predicting both concurrent and prospective costs and utilization. METHODS: We conducted a retrospective cohort study of 43,097 primary care patients from HealthPartners network between 2011 and 2012. Diagnosis and/or pharmacy claims of 2011 were used to build 3 base models using the Johns Hopkins ACG system, in addition to demographics. Model performances were compared before and after adding 3 types of prescription fill rates: primary 0-7 days, primary 0-30 days, and overall. Overall fill rates utilized all ordered prescriptions from electronic health record while primary fill rates excluded refill orders. RESULTS: The overall, primary 0-7, and 0-30 days fill rates were 72.30%, 59.82%, and 67.33%. The fill rates were similar between sexes but varied across different medication classifications, whereas the youngest had the highest rate. Adding fill rates modestly improved the performance of all models in explaining medical costs (improving concurrent R by 1.15% to 2.07%), followed by total costs (0.58% to 1.43%), and pharmacy costs (0.07% to 0.65%). The impact was greater for concurrent costs compared with prospective costs. Base models without diagnosis information showed the highest improvement using prescription fill rates. CONCLUSIONS: Prescription fill rates can modestly enhance claims-based risk prediction models; however, population-level improvements in predicting utilization are limited.

The Johns Hopkins Venous Thromboembolism Collaborative: Multidisciplinary team approach to achieve perfect prophylaxis.

Venous thromboembolism (VTE) is an important cause of preventable harm in hospitalized patients. The critical steps in delivery of optimal VTE prevention care include (1) assessment of VTE and bleeding risk for each patient, (2) prescription of risk-appropriate VTE prophylaxis, (3) administration of risk-appropriate VTE prophylaxis in a patient-centered manner, and (4) continuously monitoring outcomes to identify new opportunities for learning and performance improvement. To ensure that every hospitalized patient receives VTE prophylaxis consistent with their individual risk level and personal care preferences, we organized a multidisciplinary task force, the Johns Hopkins VTE Collaborative. To achieve the goal of perfect prophylaxis for every patient, we developed evidence-based, specialty-specific computerized clinical decision support VTE prophylaxis order sets that assist providers in ordering risk-appropriate VTE prevention. We developed novel strategies to improve provider VTE prevention ordering practices including face-to-face performance reviews, pay for performance, and provider VTE scorecards. When we discovered that prescription of risk-appropriate VTE prophylaxis does not ensure its administration, our multidisciplinary research team conducted in-depth surveys of patients, nurses, and physicians to design a multidisciplinary patient-centered educational intervention to eliminate missed doses of pharmacologic VTE prophylaxis that has been funded by the Patient Centered Outcomes Research Institute. We expect that the studies currently underway will bring us closer to the goal of perfect VTE prevention care for every patient. Our learning journey to eliminate harm from VTE can be applied to other types of harm. Journal of Hospital Medicine 2016;11:S8-S14. © 2016 Society of Hospital Medicine.

Factors Associated with Adherence Rates for Oral and Intravenous Anticancer Therapy in Commercially Insured Patients with Metastatic Colon Cancer.

BACKGROUND: Over the past decade, oncology therapies have trended toward orally administered regimens, and there has been growing attention on evaluation of factors that affect adherence. There has not been a rigorous investigation of factors associated with adherence to intravenous (i.v.) and oral anticancer drugs in the setting of metastatic colorectal cancer (mCRC). OBJECTIVES: To (a) assess potential patient-specific factors related to adherence to mCRC chemotherapy regimens and (b) compare adherence with IV versus oral dosage forms. METHODS: A retrospective analysis was performed using the Optum Oncology Management claims database. Patients aged 18 years and older diagnosed with mCRC between July 1, 2004, and December 31, 2010, who were insured by a commercial health plan were included in the study. Adherence to i.v. and oral chemotherapy regimens was assessed using the National Comprehensive Cancer Network (NCCN) guidelines as the standard for expected cycle/regimen duration. The most commonly prescribed chemotherapy regimens were assessed. Adherence was evaluated using the medication possession ratio (MPR), calculated as the number of days a patient was covered by their chemotherapy regimen, according to NCCN guidelines, divided by the number of days elapsed from the first to the last infusion of that regimen. For most analyses, the MPR was considered a continuous variable that could take on values between 0 and 1. In other analyses, a dichotomous categorical variable designated if the MPR was at least 0.8 versus less than 0.8. The Wilcoxon rank sum, Kruskal-Wallis, and Student's t-test were used to detect differences in continuous measures between patients receiving oral capecitabine therapy versus i.v. chemotherapy. The chi square test (X(2) test) or Fisher's exact test was used to assess differences in the dichotomous MPR variable. Generalized estimating equation (GEE) models were used for regimen-level analyses to account for correlated responses within individuals. RESULTS: A total of 6,780 patients were included in the analysis, virtually all (98%) with commercial insurance coverage and the remaining (2%) with Medicare Advantage. Patients with mCRC received 17,095 regimens of chemotherapy, including 2,252 regimens of oral capecitabine. Of the 17,095 regimens, 6,780 (40%) were first-line regimens (i.e., the first time mCRC was treated for a given patient). The most common chemotherapy regimen, regardless of line of therapy, was FOLFOX (2,991 regimens, 17.5% of all regimens used). FOLFOX-based therapies with or without bevacizumab were the most common regimens for first- and second-line chemotherapy, while oral capecitabine treatment was the most commonly prescribed regimen for patients in third- or fourth-line therapy. Overall, medication adherence across all regimens was relatively high, with a mean MPR of 0.87 (SD = 0.17). Evaluation of the distribution of i.v. and oral capecitabine regimens revealed that 28% of all regimens were associated with an MPR of less than 0.8. The average MPR was clinically similar, but statistically higher for i.v. chemotherapy regimens (0.881) compared with oral capecitabine regimens (0.799; P < 0.0001). In the multivariable GEE model, lung or liver metastases were associated with a higher MPR, while lower Charlson Comorbidity Index and oral anticancer therapy were associated with lower MPR. Furthermore, as line of therapy increased, the difference in MPR between patients receiving oral capecitabine and i.v. chemotherapy increased. CONCLUSIONS: This analysis determined that adherence with i.v. chemotherapy regimens was clinically similar, but statistically higher, compared to oral capecitabine therapy. The difference in adherence rates between the 2 routes of administration increased as the line of anticancer regimen increased. These results suggest that there should be an increased focus on improving adherence rates in patients receiving oral capecitabine.

Evaluating treatments and corresponding costs of prostate cancer patients treated within an inpatient or hospital-based outpatient setting.

AIM: To describe treatments and cost of care for prostate cancer (PCa) in hospital-based outpatient and inpatient settings. METHODS: Hospital encounters associated with PCa (ICD-9 codes 185, 233.4) and PCa-related treatment in a hospital claims database were included. RESULTS: There were 211,440 encounters for PCa between January 2006 and December 2010 (88,151 inpatient and 123,289 outpatient). Average cost per inpatient stay was US$12,286 versus US$4364 per outpatient visit. Most common treatment during an inpatient stay and outpatient visit was surgery (57%) and radiation (76%), respectively. A total of 80% of outpatient visits and 69.9% inpatient stays were associated with a single treatment; remaining encounters were associated with ≥2 treatments. CONCLUSION: Costs are consistent with previous estimates; however, multimodal therapy is an emerging trend that may be related to greater costs in the future which may also be a challenge for hospital decision makers.

Development and implementation of a postdischarge home-based medication management service.

PURPOSE: The development and implementation of a postdischarge home-based, pharmacist-provided medication management service are described. SUMMARY: A work group composed of pharmacy administrators, clinical specialists, physicians, and nursing leadership developed the structure and training requirements to implement the service. Eligible patients were identified during their hospital admission by acute care pharmacists and consented for study participation. Pharmacists and pharmacy residents visited the patient at home after discharge and conducted medication reconciliation, provided patient education, and completed a comprehensive medication review. Recommendations for medication optimization were communicated to the patient's primary care provider, and a reconciled medication list was faxed to the patient's community pharmacy. Demographic and medication-related data were collected to characterize patients receiving the home-based service. A total of 50 patients were seen by pharmacists in the home. Patient education provided by the home-based pharmacists included monitoring instructions, adherence reinforcement, therapeutic lifestyle changes, administration instructions, and medication disposal instructions. Pharmacists provided the following recommendations to providers to optimize medication regimens: adjust dosage, suggest laboratory tests, add medication, discontinue medication, need prescription for refills, and change product formulation. Pharmacists identified a median of two medication discrepancies per patient and made a median of two recommendations for medication optimization to patients' primary care providers. CONCLUSION: The implementation of a post-discharge, pharmacist-provided home-based medication management service enhanced the continuity of patient care during the transition from hospital to home. Pharmacists identified and resolved medication discrepancies, educated patients about their medications, and provided primary care providers and community pharmacies with a complete and reconciled medication list.

Systemic therapy for colorectal cancer: patterns of chemotherapy and biologic therapy use in nationally representative US claims database.

BACKGROUND: Treatment strategies for colorectal cancer (CRC) are highly variable. The aim of this study is to examine the patterns of chemotherapy and biologic therapy use for CRC patients in a national medical claims database. METHODS: A retrospective and observational analysis was performed using the i3 Innovus claims database to identify healthcare services consumed by patients aged 18 years and older, diagnosed with CRC between 1 January 2005 and 30 June 2009 in commercial health plans. RESULTS: Of 9,876 subjects diagnosed with CRC, fluorouracil (23.5 %) and capecitabine (10.0 %) were the dominant first-line monotherapies, followed by bevacizumab (3.2 %) and oxaliplatin (2.9 %). The most common combination regimen at first line and first and second line was FOLFOX (fluorouracil, leucovorin, and oxaliplatin; more than 25 %). The combinations FOLFIRI (fluorouracil, leucovorin, and irinotecan) plus bevacizumab (14.2 %) and FOLFOX plus bevacizumab (13.9 %) were significantly more frequent in third and successive lines of CRC therapy than other regimens (χ(2) = 191.2; P < 0.01). Additionally, the average annualized cost of CRC treatment for all patients was $US66,452, and the adjusted analysis demonstrated that patients receiving FOLFOX-A (FOLFOX + avastin) or FOLFIRI-A (FOLFIRI + avastin) had higher costs for CRC treatment. CONCLUSIONS: With the exception of a sizeable portion of patients on monotherapy, the treatment patterns for CRC were largely consistent with National Comprehensive Cancer Network (NCCN) guidelines.

Medical costs associated with use of systemic therapy in adults with colorectal cancer.

BACKGROUND: New cytotoxic agents and regimens, as well as immunotherapeutics, have recently been introduced for treatment of colorectal cancer (CRC).  OBJECTIVE: To identify the patient-related and clinical and treatment-related factors associated with higher total health care expenditures in newly diagnosed patients with CRC who are receiving systemic therapy (biologic or chemotherapy) from a commercially insured population.  METHODS: A longitudinal, retrospective analysis was employed to estimate costs and determinants of CRC treatment in a U.S. claims database for health care services used by commercial patients aged 18 to 64 years, who were diagnosed with CRC between January 1, 2005, and June 30, 2009. Generalized linear regression modeling was used to estimate the influence of demographic, clinical, and treatment factors on medical expenditures.  RESULTS: Among the 5,160 patients newly diagnosed with CRC, 99.6% of patients had chemotherapy; 32.6% had biologics; and 85.6% had other pharmaceuticals (excluding the chemotherapy and biologics of interest). The average annualized per patient cost of CRC treatment was $97,400 and consisted of chemotherapy ($17,500), biologics ($30,400), other pharmaceuticals ($2,300), inpatient treatment ($26,300), and outpatient treatment ($42,900). From first line only, first and second lines only, and third+ lines, the cost per patient was $70,500, $100,100, and $152,900, respectively. After adjusting for health care inflation, the average treatment cost of CRC patients increased by 73% from 2005 to 2009. Adjusted analyses showed that the higher medical cost for CRC patients was associated with use of new regimens, metastasis, comorbidities, surgery, radiation, insurance plan, age, sex, and region.   CONCLUSION: The health care cost of CRC treatment is increasing significantly over time, which is most likely caused by the use of new regimens, higher chances of surgery and radiation, and occurrence of various comorbidities and metastatic diseases due to increasing survival time.