Jan D. Hirsch

Patient-Level Medication Regimen Complexity Across Populations With Chronic Disease

BACKGROUND Expected treatment effectiveness from medications can be diminished due to suboptimal adherence. Medication nonadherence has been linked to pill burden from the quantity of medications; however, medication regimens with similar quantities of medications vary in complexity due to multiple dosage forms, frequency of dosing, and additional usage directions. Thus, a simple medication count ignores medication regimen complexity, especially as it pertains to a patient-level perspective that includes prescription and over-the-counter medications. A gap exists in the study of a patient-level medication regimen complexity metric across disease-specific populations. OBJECTIVE The goal of this study was to implement the quantitative Medication Regimen Complexity Index (MRCI) at the patient level in defined populations with chronic disease (geriatric depression, HIV, diabetes mellitus, and hypertension). Patient-level medication regimen complexity included all prescribed medications and over-the-counter medications documented in the electronic medication list. METHODS Using electronic medical records at the University of Colorado Hospital ambulatory clinics, we sampled 4 retrospective cohorts of adult patients in active care in 2011 with a qualifying medical diagnosis and prescribed disease-specific medication. Samples were randomly selected from all qualifying patients; de-identified information was coded using the MRCI. RESULTS Cohort-defining disease-specific prescription medications (eg, antidepressants for the depression-defined cohort) contributed <20% to the total patient-level complexity MRCI score; the MRCI score was dominated by complexity associated with all other prescription medications. Within disease-specific cohorts, MRCI scores differentiated patients with the highest and lowest medication counts, comorbidity counts, and the Charlson comorbidity index scores. For example, geriatric depression patients had a highest quartile mean MRCI score of 41 and a lowest quartile mean MRCI score of 13. Between disease-specific cohorts, high and low MRCI scores differed because each cohort had its own MRCI ranges. For example, highest quartile MRCI scores varied from a mean MRCI score of 41 (geriatric depression) to 30 (hypertension); lowest quartile scores ranged from a mean MRCI score of 7 (hypertension and HIV) to 13 (geriatric depression). CONCLUSIONS MRCI components of dosing frequency and prescribed medications outside of the cohort-defining disease medications contributed the most to the patient-level scores. Thus, chronic disease management programs may want to consider all medications that patients are taking and examine ways to reduce complexity, such as reducing multiple dosing frequencies when possible. MRCI scores differentiated high and low patient-level complexity measures, representing possible utility as a prospective tool to identify target patients for intervention. Future work includes simplifying the MRCI and enhancing the scores with medication risk factors, as well as explicitly linking to adherence and health services.

Health Care Utilization in Patients with Gout

OBJECTIVE To study health care utilization patterns in patients with gout. METHODS In a gout population from primary care and rheumatology clinics in 3 U.S. metropolitan cities, we collected data on gout-related utilization (primary care, rheumatology, urgent care, emergency room, and other) in the past year. We evaluated the association of comorbidities, age, gender, gout characteristics (time since last gout attack and tophi), and gout severity ratings (mean of serum uric acid, patient-rated, and physician-rated gout severity) and with emergency/urgent care and primary care utilization using regression and correlation analyses. RESULTS Of the 296 patients who reported visiting at least 1 type of health practitioner for gout in the past year, the percentage of patients utilizing the service at least once and annual utilization rates among utilizers were as follows: primary care physician, 60%, 3.0 ± 3.4; nurse practitioner/physician assistant, 26%, 2.7 ± 2.5; rheumatologist, 51%, 3.7 ± 5.7; urgent care, 23%, 2.1 ± 2.2; emergency room, 20%, 2.0 ± 1.7; and hospitalization, 7%, 2.1 ± 1.4. Higher overall gout severity was associated with greater use of each resource type and with overall gout-related utilization. Nonemergency/nonurgent care utilization (primary care physician, nurse practitioner, physicians assistant, and rheumatologist for gout) was the strongest predictor of gout-related emergency/urgent care utilization. Patients with more comorbidities had greater gout-related primary care utilization. CONCLUSIONS Overall gout severity was associated with all types of gout-related utilization. This may help to screen high utilizers for targeted behavioral and therapeutic interventions. Having a higher number of comorbid conditions was a risk factor for higher gout-related primary care utilization.

Primary care-based, pharmacist-physician collaborative medication-therapy management of hypertension: a randomized, pragmatic trial.

PURPOSE A collaborative pharmacist-primary care provider (PharmD-PCP) team approach to medication-therapy management (MTM), with pharmacists initiating and changing medications at separate office visits, holds promise for the cost-effective management of hypertension, but has not been evaluated in many systematic trials. The primary objective of this study was to examine blood pressure (BP) control in hypertensive patients managed by a newly formed PharmD-PCP MTM team versus usual care in a university-based primary care clinic. METHODS This randomized, pragmatic clinical trial was conducted in hypertensive patients randomly selected for PharmD-PCP MTM or usual care. In the PharmD-PCP MTM group, pharmacists managed drug-therapy initiation and monitoring, medication adjustments, biometric assessments, laboratory tests, and patient education. In the usual-care group, patients continued to see their PCPs. Participants were aged ≥ 18 years, were diagnosed with hypertension, had a most recent BP measurement of ≥ 140/≥ 90 mm Hg (≥ 130/≥ 80 mm Hg if codiagnosed with diabetes mellitus), were on at least 1 antihypertensive medication, and were English speaking. The primary outcome was the difference in the mean change from baseline in systolic BP at 6 months. Secondary outcomes included the percentage achieving therapeutic BP goal and the mean changes from baseline in diastolic BP and low- and high-density lipoprotein cholesterol. FINDINGS A total of 166 patients were enrolled (69 men; mean age, 67.7 years; PharmD-PCP MTM group, n = 75; usual-care group, n = 91). Mean reduction in SBP was significantly greater in the PharmD-PCP MTM group at 6 months (-7.1 [19.4] vs +1.6 [21.0] mm Hg; P = 0.008), but the difference was no longer statistically significant at 9 months (-5.2 [16.9] vs -1.7 [17.7] mm Hg; P = 0.22), based on an intent-to-treat analysis. In the intervention group, greater percentages of patients who continued to see the MTM pharmacist versus those who returned to their PCP were at goal at 6 months (81% vs 44%) and at 9 months (70% vs 52%). No significant between-group differences in changes in cholesterol were detected at 6 and 9 months; however, the mean baseline values were near recommended levels. The PharmD-PCP MTM group had significantly fewer PCP visits compared with the usual-care group (1.8 [1.5] vs 4.2 [1.0]; P < 0.001). IMPLICATIONS A PharmD-PCP collaborative MTM service was more effective in lowering BP than was usual care at 6 months in all patients and at 9 months in patients who continued to see the pharmacist. Incorporating pharmacists into the primary care team may be a successful strategy for managing medication therapy, improving patient outcomes and possibly extending the capacity of primary care. ClinicalTrials.gov identifier: NCT01973556.

Validation of a Patient-Level Medication Regimen Complexity Index as a Possible Tool to Identify Patients for Medication Therapy Management Intervention

The Medication Regimen Complexity Index (MRCI) is a 65‐item instrument that can be used to quantify medication regimen complexity at the patient level, capturing all prescribed and over‐the‐counter medications. Although the MRCI has been used in several studies, the narrow scope of the initial validation limits application at a population or clinical practice level.

Waterpipe smoking among health sciences university students in Iran: perceptions, practices and patterns of use

BackgroundIn recent years waterpipe smoking has become a popular practice amongst young adults in eastern Mediterranean countries, including Iran. The aim of this study was to assess waterpipe smoking perceptions and practices among first-year health sciences university students in Iran and to identify factors associated with the initiation and maintenance of waterpipe use in this population.ResultsOut of 371 first-year health sciences students surveyed, 358 eight students completed a self-administered questionnaire in the classrooms describing their use and perceptions towards waterpipe smoking. Two hundred and ninety six responders met study inclusion criteria. Waterpipe smoking was common among first-year health sciences university students, with 51% of students indicating they were current waterpipe smokers. Women were smoking waterpipes almost as frequently as men (48% versus 52%, respectively). The majority of waterpipe smokers (75.5%) indicated that the fun and social aspect of waterpipe use was the main motivating factor for them to continue smoking. Of waterpipe smokers, 55.3% were occasional smokers, using waterpipes once a month or less, while 44.7% were frequent smokers, using waterpipes more than once a month. A large number of frequent waterpipe smokers perceived that waterpipe smoking was a healthier way to use tobacco (40.6%) while only 20.6% thought it was addictive. Compared to occasional smokers, significantly more frequent smokers reported waterpipe smoking was relaxing (62.5% vs. 26.2%, p = 0.002), energizing (48.5% vs. 11.4%, p = 0.001), a part of their culture (58.8% vs. 34.1%, p = 0.04), and the healthiest way to use tobacco (40.6% vs. 11.1%, p = 0.005).ConclusionsSocial and recreational use of waterpipes is widespread among first-year health sciences university students in Iran. Women and men were almost equally likely to be current waterpipe users. Public health initiatives to combat the increasing use of waterpipes among university students in Iran must consider the equal gender distribution and its perception by many waterpipe smokers as being a healthier and non-addictive way to use tobacco.

Minimally important differences of the gout impact scale in a randomized controlled trial

OBJECTIVE The Gout Impact Scale (GIS) is a gout-specific quality of life instrument that assesses impact of gout during an attack and impact of overall gout. The GIS has five scales and each is scored from 0 to 100 (worse health). Our objective was to assess minimally important differences (MIDs) for the GIS administered in a randomized controlled trial (RCT) assessing rilonacept vs placebo for prevention of gout flares during initiation of allopurinol therapy. METHODS Trial subjects (n = 83) included those with two or more gout flares (self-reported) in the past year. Of these, 73 had data for Weeks 8 vs 4 and formed the MID analysis group and were analysed irrespective of the treatment assignment. Subjects completed the GIS and seven patient-reported anchors. Subjects with a one-step change (e.g. from very poor to poor) were considered as the MID group for each anchor. The mean change in GIS scores and effect size (ES) was calculated for each anchors MID group. The average of these created the overall summary MID statistics for each GIS. An ES of 0.2-0.5 was considered to represent MID estimates. Results. Trial subjects (n = 73) were males (96.0%), White (90.4%), with mean age of 50.5 years and serum uric acid of 9.0 mg/dl. The mean change score for the MID improvement group for scales ranged from -5.24 to -7.61 (0-100 scale). The ES for the MID improvement group for the four scales ranged from 0.22 to 0.38. CONCLUSION The MID estimates for GIS scales are between 5 and 8 points (0-100 scale). This information can aid in interpreting the GIS results in future gout RCTs. Trial Registration. Clinicaltrials.gov, www.clinicaltrials.gov, NCT00610363.

Strategies to Improve Medication Adherence Reported by Diabetes Patients and Caregivers: Results of a Taking Control of Your Diabetes Survey

BACKGROUND: Published studies assessing specific methods that patients with diabetes and their caregivers perceive as helpful means of increasing medication adherence are lacking. OBJECTIVE: To determine methods that patients with diabetes and their caregivers have used to improve medication adherence, investigate the perceived helpfulness of these methods, and identify motivating factors and medication characteristics that may positively influence adherence. METHODS: A cross-sectional survey was distributed to patients with diabetes and caregivers of patients with diabetes at the 11th annual Taking Control of Your Diabetes conference in October 2005 at the San Diego Convention Center. Outcome measures were self-reported medication adherence, perceived helpfulness of methods employed to improve adherence, motivating factors that may improve adherence, and medication characteristics that may improve adherence. RESULTS: A total of 524 (40.5% response rate) questionnaires were included in the final analysis, 357 from patients with diabetes and 167 from caregivers. Taking medications as part of a daily routine and using pill boxes were the most frequently reported helpful methods for improving medication adherence. The 3 motivating factors most commonly identified as improving medication adherence were: knowing that diabetes medications work effectively to lower blood glucose, knowing how to manage medication adverse effects, and understanding medication benefits. Many participants thought that newer injectable diabetes medications resulting in weight loss or no additional blood glucose monitoring would be helpful in optimizing adherence. CONCLUSIONS: Participants in this study identified medication education as a key factor in improving adherence. To empower patients to overcome medication adherence barriers, pharmacists could perform more proactive and thorough counseling sessions that include education on indication, mechanism of action, and therapeutic effects of drugs. They could recommend that patients take medications concurrently with a daily routine and use a pill box, as these actions were reported to be likely to improve medication adherence. However, our results also remind us that motivating factors and tools that may improve adherence may be very patient specific and that pharmacists should incorporate an assessment of this variance in their counseling sessions.

Patient-level Medication Regimen Complexity in Older Adults With Depression

PURPOSE Polypharmacy and medication adherence are well known challenges facing older adults. Medication regimen complexity increases the demands of self-care in the home. Some medication regimens may be more complex than others, especially when dosage form, frequency of dosing, and additional usage directions are included in complexity along with the number of medications In older adults with depression, it is unknown what features of their medications most influence their medication regimen complexity. METHODS A sample cohort of 100 adults ≥65 years old with a diagnosis of depression was randomly selected from electronic medical records (EMR) in ambulatory clinics at the University of Colorado (CU) and University of San Diego (SD). Demographic, medical history, and medication-related information was extracted from the EMR. Complexity was determined using the Medication Regimen Complexity Index (MRCI). IRB approval was obtained. FINDINGS The cohort mean age was 74.3 years (SD) and 79.7 years (CU). The mean unweighted Charlson comorbidity index for 1.0 (SD) and 1.8 (CU). The mean number of medications was 7.1 and 8.0, with 1.1 and 1.2 depression meds, 5.4 and 4.3 non-depression prescription meds, and 0.6 and 2.4 OTC meds for the SD and CU cohorts, respectively. 66% of SD adults and 70% of CU adults took six or more meds. Individual MRCI scores were on average 17.62 (SD) and 19.36 (CU). Dosing frequency contributed to 57-58% of the MRCI score, with patients facing an average of 7-8 unique dosing frequencies in their regimen. In both cohorts, there was an average of 3 additional directions added to the regimens to clarify dosing. IMPLICATIONS As expected, in our older adult cohorts with depression the majority of patients took multiple medications. Using a standardized instrument, we characterized the regimen complexity and found that it was increasingly complex due to numerous dosing forms, frequencies and additional directions for use. Patient-level medication regimen complexity should go beyond depression medication to encompass the patients entire regimen for opportunities to reduce complexity and improve ease of self-care.

Development of a pharmacist–psychiatrist collaborative medication therapy management clinic

OBJECTIVE To describe a needs assessment, practice description, practice innovation and reimbursement of a psychiatric pharmacist medication therapy management (MTM) clinic with related challenges and opportunities. SETTING An MTM clinic established in collaboration with the Outpatient Psychiatric Services (OPS) at the University of California San Diego (UCSD), under contract with the San Diego County Health and Human Services Agency Adult and Older Adult Mental Health Services (A/OAMHS). PRACTICE DESCRIPTION Two board-certified psychiatric pharmacists provided direct patient care using a collaborative practice protocol 3 days per week. Clinical services included pharmacotherapy management, laboratory monitoring, medication counseling, and psychosocial referrals to other providers. PRACTICE INNOVATION Payment to UCSD OPS for clinical services was based on a contract between the San Diego County A/OAMHS and the clinic. Two pharmacists co-managed mental health patients and billed for medication management based on face-to-face contact time (medication minutes) and documentation time with each patient. MAIN OUTCOME MEASURES Number of patients comanaged, dropout rates, visit duration, and billed minutes. RESULTS From May 2009 to December 2010, two pharmacists comanaged 68 patients, mean (± SD) age 48.6 ± 11.6 years, diagnosed with major depressive, schizophrenic, schizoaffective, and/or bipolar disorder. A total of 56 (82.3%) patients were clinically stable and remained on the pharmacist caseload, but 12 (17.6%) patients were lost to follow-up (10 lost contact, 1 moved, 1 expired). On average, patients had 7.7 patient visits , for 491 total visits (with an average of 26 minutes per visit) that were billed at a rate of

Patient request for pharmacist counseling and satisfaction: Automated prescription delivery system versus regular pick-up counter

4.82 per minute for medication minutes, translating to