Real-World Evidence from the Integrative Medicine Primary Care Trial (IMPACT): Assessing Patient-Reported Outcomes at Baseline and 12-Month Follow-Up.

PURPOSE: The University of Arizona Integrative Health Center (UAIHC) was an innovative membership-supported integrative medicine (IM) adult primary care clinic in Phoenix, Arizona. UAIHC delivered healthcare using an integrative medicine model that combined conventional and complementary medical treatments, including nutrition, mind-body medicine, acupuncture, manual medicine, health coaching, educational classes, and groups. Results from pre-post evaluation of patient-reported outcomes on several standardized measures are presented here. METHODS: UAIHC patients completed surveys at baseline and after 12 months of continuous integrative primary care. Patients reported on perceived changes in health outcomes as measured by Short-Form Health Survey (SF-12 general, mental, and physical health), Perceived Stress Scale (PSS4), Work Productivity and Activity Impairment Questionnaire (WPAI), World Health Organization Well-Being Index (WHO-5), Pain Visual Analog Scale (VAS), Fatigue Severity Scale (VAS; FSS), Generalized Anxiety Disorder Scale (GAD2), Patient Health Questionnaire for depression (PHQ2), Pittsburgh Sleep Quality Index (PSQI) global rating of sleep quality, and the Behavioral Risk Factor Surveillance System (BRFSS; nutrition, exercise, and physical activity). Overall differences between time points were assessed for statistical significance. Patient demographics are also described. RESULTS: 177 patients completed baseline and follow-up outcome measures. Patients were predominantly white, female, college-educated, and employed. Baseline to one-year follow-up results indicate statistically significant improvements (p <.05) on all but perceived stress (PSS-4) and work absenteeism (WPAI). Clinical impact and/or practical effects are reported as percent change or standardized effect sizes whenever possible. Other demographic and descriptive information is summarized. CONCLUSIONS: Following one year of IM primary care at UAIHC, patient-reported outcomes indicated positive impacts in several areas of patients' lives: mental, physical, and overall health; work productivity; sleep quality; pain; fatigue; overall well-being; and physical activity.

Integrative medicine primary care: assessing the practice model through patients' experiences.

BACKGROUND: The University of Arizona Integrative Health Center (UAIHC) was an innovative integrative medicine (IM) adult primary care clinic in Phoenix, Arizona. UAIHC used a hybrid payment model to deliver comprehensive healthcare that includes conventional and complementary medical treatments. METHODS: Fidelity measures were collected to evaluate how well the IM care delivery process matched ideals for IM. Patient experiences are presented here. Patients visiting UAIHC on 1 of 10 randomly selected days between September 2013 and February 2015 were surveyed. Patients were asked about their experience with: holistic care; promotion of health, self-care, and well-being; relationship and communication with practitioners; and overall satisfaction. RESULTS: Eighty-three patients completed surveys. Based on patient-reported experiences, UAIHC delivered IM care as defined by the practice model. CONCLUSIONS: Patients received holistic care, established positive caring relationships with providers who promoted their self-care and well-being, and reported high overall satisfaction with UAIHC.

Accepting Medication Therapy Management Recommendations to Add ACEIs or ARBs in Diabetes Care.

BACKGROUND: National guidelines and initiatives have promoted the use of angiotensin-converting enzyme inhibitors (ACEIs) and angiotensin receptor blockers (ARBs) for patients with diabetes. The University of Arizona Medication Management Center (UA-MMC) is contracted by Medicare health plans, pharmacy benefit managers (PBMs), and multiple commercial health insurance plans to provide medication therapy management (MTM) services for plan members. As part of the MTM program, recommendations have been made for those patients who may benefit from the addition of an ACEI/ARB. Although the intervention benefits and guidelines for using ACEIs/ARBs are clear, real-world evidence is needed to understand and potentially increase uptake of guideline interventions among eligible patients. OBJECTIVES: To (a) identify patient characteristics that predict acceptance of guideline recommendations to add ACEI/ARB medications to diabetic treatment via MTM services and (b) examine how well different case characteristics (i.e., patient age and sex, type and number of recommendation attempts, type of health care plan) predict the odds of adding ACEI/ARB medications to diabetic regimens when recommended through an MTM call center. METHODS: This was a retrospective analysis of secondary data provided by the UA-MMC. The de-identified national data included adult plan members with diabetes who the UA-MMC recommended adding an ACEI/ARB prescription based on 2012 national guidelines. The UA-MMC made recommendations by either patient letters, patient phone calls, physician faxes, or any combination thereof. We conducted a binary logistic regression analysis to assess the impact of case characteristics on the likelihood of accepting recommendations to add ACEI/ARB medications. The outcome variable was recommendation acceptance (yes/no), defined as new prescription claims for an ACEI/ARB within 120 days following the recommendation. Five predictor variables were assessed: (1) patient's age quartile; (2) method of communicating recommendations (letter, phone call, fax, or some combination thereof); (3) whether recommendations were made once or twice on separate dates; (4) patient's sex; and (5) type of health care plan. RESULTS: Recommendations were made for 31,495 members of health plans or PBMs that contracted with the UA-MMC. Patients' ages ranged from 19-90 (Mean =72.01; SD =10.21), with females comprising 56% of the sample. The recommendation to add ACEI/ARB medications was accepted for 14.5% (4,559) of patients. In most cases (73%), recommendations occurred via a letter to patients together with a fax to their providers. The fitted model, containing 3 predictor variables (age quartile, type of contact to communicate the recommendations, and whether recommendation contacts were made twice), was statistically significant, χ(2) (10; N = 31,495) = 112.82 (P < 0.001), indicating that the model was able to distinguish between those who did and did not accept UA-MMC's recommendations to add ACEI/ARB medications. The likelihood of recommendation acceptance decreased as patient age increased compared with patients in the first age quartile (ages 19-67; P ≤ 0.005 at all levels). Compared with sending only a provider fax, patients who received all 3 types of contact (provider fax with patient phone call and letter) were estimated to be 1.34 times more likely (34% increase) to have recommendation acceptance ( P = 0.004; 95% CI = 1.10-1.63). Similarly, patients who received only letters were also 1.32 times more likely (32% increase) than provider faxes alone to result in recommendation acceptance ( P = 0.003; 95% CI = 1.10-1.59). Patients for whom recommendations were made twice were less likely to have recommendation acceptance than for those contacted once, controlling for all other predictor variables in the model ( P < 0.001; OR = 0.77; 95% CI = 0.69-0.86). CONCLUSIONS: Recommendations to add an ACEI/ARB to diabetic regimens are more likely to be accepted for younger patients and those who receive recommendations through all 3 communication types (provider fax combined with patient phone call and letter) or just letters than provider faxes alone. Further research is needed to understand why prescribers are not accepting MTM recommendations.

IMPACT--Integrative Medicine PrimAry Care Trial: protocol for a comparative effectiveness study of the clinical and cost outcomes of an integrative primary care clinic model.

BACKGROUND: Integrative medicine (IM) is a patient-centered, healing-oriented clinical paradigm that explicitly includes all appropriate therapeutic approaches whether they originate in conventional or complementary medicine (CM). While there is some evidence for the clinical and cost-effectiveness of IM practice models, the existing evidence base for IM depends largely on studies of individual CM therapies. This may in part be due to the methodological challenges inherent in evaluating a complex intervention (i.e., many interacting components applied flexibly and with tailoring) such as IM. METHODS/DESIGN: This study will use a combination of observational quantitative and qualitative methods to rigorously measure the health and healthcare utilization outcomes of the University of Arizona Integrative Health Center (UAIHC), an IM adult primary care clinic in Phoenix, Arizona. There are four groups of study participants. The primary group consists of clinic patients for whom clinical and cost outcomes will be tracked indicating the impact of the UAIHC clinic (n = 500). In addition to comparing outcomes pre/post clinic enrollment, where possible, these outcomes will be compared to those of two matched control groups, and for some self-report measures, to regional and national data. The second and third study groups consist of clinic patients (n = 180) and clinic personnel (n = 15-20) from whom fidelity data (i.e., data indicating the extent to which the IM practice model was implemented as planned) will be collected. These data will be analyzed to determine the exact nature of the intervention as implemented and to provide covariates to the outcomes analyses as the clinic evolves. The fourth group is made up of patients (n = 8) whose path through the clinic will be studied in detail using qualitative (periodic semi-structured interviews) methods. These data will be used to develop hypotheses regarding how the clinic works. DISCUSSION: The US health care system needs new models of care that are more patient-centered and empower patients to make positive lifestyle changes. These models have the potential to reduce the burden of chronic disease, lower the cost of healthcare, and offer a sustainable financial paradigm for our nation. This protocol has been designed to test whether the UAIHC can achieve this potential. TRIAL REGISTRATION: Clinical Trials.gov NCT01785485.

When a whole practice model is the intervention: developing fidelity evaluation components using program theory-driven science for an integrative medicine primary care clinic.

Integrative medicine (IM) is a clinical paradigm of whole person healthcare that combines appropriate conventional and complementary medicine (CM) treatments. Studies of integrative healthcare systems and theory-driven evaluations of IM practice models need to be undertaken. Two health services research methods can strengthen the validity of IM healthcare studies, practice theory, and fidelity evaluation. The University of Arizona Integrative Health Center (UAIHC) is a membership-supported integrative primary care clinic in Phoenix, AZ. A comparative effectiveness evaluation is being conducted to assess its clinical and cost outcomes. A process evaluation of the clinic's practice theory components assesses model fidelity for four purposes: (1) as a measure of intervention integrity to determine whether the practice model was delivered as intended; (2) to describe an integrative primary care clinic model as it is being developed and refined; (3) as potential covariates in the outcomes analyses, to assist in interpretation of findings, and for external validity and replication; and (4) to provide feedback for needed corrections and improvements of clinic operations over time. This paper provides a rationale for the use of practice theory and fidelity evaluation in studies of integrative practices and describes the approach and protocol used in fidelity evaluation of the UAIHC.

Evaluation of risk factors and health outcomes among persons with asthma.

OBJECTIVE: To examine risk factors associated with healthcare utilization in Arizona Medicaid patients with asthma. METHODS: Data were obtained from Arizona Medicaid between 1/1/2002 and 12/31/2003. Inclusion criteria consisted of persons with an asthma diagnosis (ICD9-CM 493.XX), 5 to 62 years of age; and were new users of inhaled-corticosteroids (ICS), combination ICS+long-acting beta-agonist, or leukotriene-modifiers. Factors examined included age, geographic location (urban/rural), race/ethnicity (White, non-Hispanic Black, Hispanic, other), medication adherence, pre-period short-acting beta-agonist use (SABA), and co-morbidities. Utilization measures examined included SABA use; exacerbations measured by hospital visits; and asthma-related and total healthcare costs. Analyses for utilization measures were performed using negative binomial, logistic regression, and generalized linear modeling gamma-family, log-link, respectively. RESULTS: A total of 3,013 subjects met inclusion/exclusion criteria and had a mean age (+/-SD) of 24.7 +/-13.7 years. Urban residents were 55% more likely to have an exacerbation than rural residents (odds ratio-OR 0.45, 95%CI: 0.27-0.78). Age (years 18 to 62) was a significant predictor for SABA use (incidence rate ratio-IRR 1.22, 95% CI: 1.06-1.41); and exacerbations (OR 2.07, 95% CI: 1.28-3.38). Mean predicted asthma cost was $530 (95% CI: $461-608) for ages 5 to 17, $702 (95% CI $600-822) for ages 18 to 39), and $583 (95% CI $468-726) for ages 40 to 62. Males were 46% less likely to have an exacerbation than females (OR 0.54, 95% CI: 0.31-0.94). Exacerbations were not different between race/ethnicity categories. Predicted mean asthma-related costs were not different between Whites ($591, 95% CI: $509-686), Blacks ($638, 95% CI: $499-815), or Hispanics ($535, 95% CI: $466-614). CONCLUSIONS: Results of these analyses found urban areas had higher rates of asthma-related hospital visits compared to rural counties, but no difference in asthma-costs between urban and rural areas which may suggest rural exacerbations may be more costly or severe. Persons with asthma aged 18 to 62 had higher rates of asthma-related emergency-room visits/hospitalizations than those aged 5 to 18. Persons 18 to 39 years of age had higher costs than person 5 to 17 or 40 to 62. Race/ethnicity in this population was not a significant predictor of outcomes or asthma-related costs.

Gender and age differences in medications dispensed from a national chain drugstore.

OBJECTIVES: Our objective was to compare sex and age differences in the medications dispensed in pharmacies from a large national drugstore chain. METHODS: Using a list for the 200 most commonly prescribed medicines, we assessed prescriptions dispensed by a large national chain drug store over 1 year (2002-2003). The analysis used U.S. census data adjusted for the population by sex and age and weighted by the number of pharmacies per state. Results are reported as an odds ratio (OR) of prescriptions dispensed to females and males. RESULTS: Under age 18, 24 drug classes were dispensed more commonly to females (OR > 1) and 18 drug classes more commonly to males (OR < 1). In the 18-24 age group, 48 of 53 drug classes were dispensed more frequently to females. Across other adult groups, females were dispensed more medications than males for 156 of 180 medications. There was greater dispensing to females of antibiotics (OR = 1.74, 95% confidence interval [CI] 1.74-1.74), analgesics (OR = 1.70, 95% CI 1.70-1.70), antihistamines and sympathomimetics (OR = 1.46, 95% CI 1.45-1.46), benzodiazapines (OR = 2.08, 95% CI 2.07-2.08), antidepressants (OR = 2.40, 95% CI 2.39-2.40), diuretics (OR = 1.9328, 95% CI 1.93-1.94), and thyroid drugs (OR = 4.80, 95% CI 4.78-4.82). However, males had higher dispensing of antianginal drugs (OR = 0.84, 95% CI 0.83-0.85), anticoagulants (OR = 0.89, 95% CI 0.88-0.90), glycosides (OR = 0.80, 95% CI 0.79-0.81), and antihypertensives (OR = 0.91, 95% CI 0.91-0.91). More females were dispensed propoxyphene with acetaminophen (OR = 2.23, 95% CI 2.23-2.24), which has been associated with adverse outcomes (hospitalizations, emergency department visits, and deaths). CONCLUSIONS: Females, especially during the reproductive years, are dispensed more medications than males.

Prescribers' knowledge of and sources of information for potential drug-drug interactions: a postal survey of US prescribers.

BACKGROUND: Given the high prevalence of medication use in the US, the risk of drug-drug interactions (DDIs) and potential for patient harm is of concern. Despite the rise in technologies to identify potential DDIs, the ability of physicians and other prescribers to recognize potential DDIs is essential to reduce their occurrence. The objectives of this study were to assess prescribers' ability to recognize potential clinically significant DDIs and to examine the sources of information they use to identify potential DDIs and prescribers' opinions on the usefulness of various DDI information sources. METHODS: A postal questionnaire was developed to assess prescriber knowledge of medications that may interact and prescribers' usual sources of DDI information. Recipients were asked to classify 14 drug pairs as 'contraindicated', 'may be used together but with monitoring' or 'no interaction'. A response option of 'not sure' was also provided. The questionnaires were sent to a national sample of 12 500 prescribers based on past history of prescribing drugs associated with known potential for DDI, who were identified using data from a pharmacy benefit manager covering over 50 million individuals. RESULTS: Usable questionnaires were obtained from 950 prescribers. The percentage of prescribers who correctly classified specific drug pairs ranged from 18.2% for warfarin and cimetidine to 81.2% for paracetamol (acetaminophen) with codeine and amoxicillin, with 42.7% of all combinations classified correctly. The number of drug pairs correctly classified by the prescribers ranged from 0 to 13. For half of the drug pairs over one-third of the respondents answered 'not sure'; among those drug pairs, two were contraindicated. When asked what source was used to learn more about a potential DDI, a quarter of the prescribers reported using personal digital assistants and another quarter used printed material. The majority of the prescribers (68.4%) reported that they were usually informed by pharmacists about their patients' potential exposure to DDIs. Compared with the prescribers who used other sources, those who used computerized DDI alerts as their usual source of DDI information consistently gave a lower rating score to the five statements that assessed the usefulness of the information. CONCLUSION: This study suggests that prescribers' knowledge of potential clinically significant DDIs is generally poor. These findings are supported by other research and emphasize the need to develop systems that alert prescribers about potential interactions that are clinically relevant. Physicians most commonly reported learning about potential DDIs from pharmacists, suggesting further work is needed to improve the drug-prescribing process to identify potential safety issues earlier in the medication use process.

Pharmacist workload and pharmacy characteristics associated with the dispensing of potentially clinically important drug-drug interactions.

BACKGROUND: Drug-drug interactions (DDIs) are preventable medical errors, yet exposure to DDIs continues despite systems that are designed to prevent such exposures. The purpose of this study was to examine pharmacy characteristics that may be associated with dispensed potential DDIs. METHODS: This study combined survey data from community pharmacies in 18 metropolitan statistical areas with pharmacy claims submitted to 4 pharmacy benefit managers (PBMs) over a 3-month period from January 1, 2003 to March 31, 2003. Pharmacy characteristics of interest included prescription volume, the number of full-time equivalent pharmacists and pharmacy staff, computer software programs, and the ability to modify those programs with respect to DDI alerts, the use of technologies to assist in receiving, filling and dispensing medication orders, and prescription volume. The dependent variable in this study was the rate of dispensed medications that may interact. RESULTS: A total of 672 pharmacies were included in the analysis. On average (+/-SD), the respondents filled 1375 +/- 691 prescriptions per week, submitted 17,948 +/- 23,889 pharmacy claims to the participating PBMs, had 1.2 +/- 0.3 full-time equivalent pharmacists per hour open, and 545 (81%) were affiliated with a chain drug store organization. Factors significantly related to an increased risk of dispensing a potential DDI included pharmacist workload (odds ratio [OR] 1.03; 95% confidence interval [CI] 1.028-1.048), pharmacy staffing (OR 1.10; 95% CI: 1.09-1.11), and various technologies (eg, sophisticated telephone systems, internet receipt of orders, and refill requests) that assist with order processing, and the ability to modify DDI alert-screening sensitivity and detailed pharmacological information about DDIs. CONCLUSIONS: This study found that there was an increase in the risk of dispensing a potential DDI with higher pharmacist and pharmacy workload, use of specific automation, and dispensing software programs providing alerts and clinical information.

Workload and availability of technology in metropolitan community pharmacies.

OBJECTIVE: To assess workload characteristics and the presence of prescription processing technologies within metropolitan community pharmacies in the United States. DESIGN: Cross-sectional postal survey. SETTING: 18 metropolitan statistical areas (MSAs) in the United States. PARTICIPANTS: 3000 managers located in community pharmacies processing at least 500 third-party claims per month for four major pharmacy benefits managers. INTERVENTIONS: 34-item survey instrument designed to collect data about the pharmacy including demographics, workload issues, handling of drug-drug interactions (DDIs), and pharmacists' attitudes toward computerized DDI alerts. MAIN OUTCOME MEASURES: Workload (hours of operation, prescription volume, staffing hours, prescription processing intensity) and prescription processing technologies (telecommunication systems, automated counting/filling or verification devices, number of computer terminals, and computer software vendors). RESULTS: Overall, 736 usable surveys were returned (response rate, 25.3%). On average, respondents reported a volume of approximately 1340 prescriptions per week processed at a rate of almost 17 prescriptions per hour. Independent pharmacies processed approximately 3 prescriptions per hour more than chain pharmacies even though a statistically equal or slightly lower proportion of those pharmacies had automated technologies. The presence of technology was generally high for all pharmacies, particularly countertop tablet/capsule-counting devices and telefacsimile machines. The most common software vendors differed considerably between chain and independent pharmacies. CONCLUSION: The number of prescriptions processed per hour and number of technologies available increased with the total weekly volume of prescriptions processed in this national survey. A majority of pharmacies had at least one type of automated prescription processing technology and an automated telecommunication system for accepting new or refill prescriptions. Independent pharmacies processed more prescriptions per hour than did chains but did so with fewer categories of technologies.

Community pharmacy managers' perception of computerized drug-drug interaction alerts.

OBJECTIVE: To examine community pharmacists' attitudes toward computerized drug-drug interaction (DDI) alerts and identify factors associated with more favorable perceptions of these alerts. DESIGN: Cross-sectional postal survey. SETTING: 18 metropolitan statistical areas (MSAs) in the United States. PARTICIPANTS: 3000 community pharmacy managers. INTERVENTIONS: 34-item survey instrument designed to collect data about the pharmacy including demographics, workload issues, handling of DDIs, and pharmacists' attitudes toward computerized DDI alerts. MAIN OUTCOME MEASURE: Responses to items concerning community pharmacy managers' attitudes toward DDI alerts and factors associated with more favorable attitudes toward these alerts. RESULTS: A total of 736 usable surveys were returned (25.3% response rate). Pharmacy managers generally disagreed that DDI alerts were a waste of time (mean +/- SD, 2.1 +/- 1.1 on a scale of 1, strongly disagree, to 6, strongly agree). However, they were not completely confident that their computer systems provided them with meaningful DDI alerts (mean +/- SD, 4.5 +/- 1.2). They were confident in their ability to identify DDIs (mean +/- SD, 4.9 +/- 0.9) and discuss DDIs with physicians (mean +/- SD, 5.2 +/- 0.7). Pharmacy software that provided detailed DDI information as well as the ability to customize DDI alerts were associated with more favorable perceptions of DDI alerts. CONCLUSION: Despite being presented with a large proportion of clinically unimportant alerts, community pharmacy managers did not believe DDI alerts were meaningless or a waste of time. Incorporation of features that streamline DDI alerts may improve their effectiveness in community pharmacy practice.