Nurse Identified Hospital to Home Medication Discrepancies: Implications for Improving Transitional Care

FEATURE ARTICLE Nurse Identified Hospital to Home Medication Discrepancies: Implications for Improving Transitional Care Cynthia F. Corbett, PhD, RN Stephen M. Setter, PharmD, DVM Kenn B. Daratha, PhD Joshua J. Neumiller, PharmD Lindy D. Wood, PharmD

Care transitions are clinically dangerous times, particularly for older adults with complex health problems. This article describes the most common medication discrepancies identified by nurses during patients’ (n 5 101) hospital to home transition. Findings indicated that medication discrepancies were astoundingly widespread, with 94% of the participants having at least 1 discrepancy. The average number of medication discrepancies identified was 3.3 per participant. Medication discrepancies were identified in virtually all classes of medications, including those with high safety risks. Evidence-based best practices to reduce transition-related medication discrepancies are presented. (Geriatr Nurs 2010;31: 188-196) he transition from hospital to home is an exceptionally risky time for medication errors. Older adults are particularly vulnerable to medication discrepancies following hospital discharge because they frequently have chronic comorbid medical conditions, functional impairments, complex medication regimens— often with prescriptions from several providers— and extensive changes in their medications during hospitalization. Nearly 20% of Medicare patients are rehospitalized within 30 days of an index hospitalization.1 A contributing aspect of the need for readmission is medication discrepancy,2 defined as any difference between the discharge medication list and the medications patients report actually taking at home.3 Furthermore, medication discrepancies remain common4-6 and lead to medication errors that are the most prevalent adverse event following hospital discharge.7 Medication management has been identified as the most challenging component of a successful hospital-

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to-home transition.8 The purpose of the analyses reported here was to describe the most common medication discrepancies identified by nurses during patients’ transition from hospital to home. In so doing, our goal was to focus specifically on these medications and consider evidence-based best practices to reduce medication discrepancies during the hospital-to-home transition.

Methods Inclusion and Exclusion Criteria This analysis was based on data from a larger study testing the effectiveness of an intervention designed to enhance home care nurses’ abilities to detect and resolve hospital-to-home transition-related medication discrepancies. The parent study was approved for human subjects participation by the institutional review boards of the involved hospitals and the authors’ affiliated university. Written informed consent was provided by all participants. The data used for the descriptive analyses reported here is a subsample of the larger trial and includes participants randomized to the intervention arm of the ongoing clinical trial. The intervention arm of the clinical trial was selected for this report because, as shown in Table 1, it is the only arm in which nurses specifically identify and document medication discrepancies as part of the study protocol. Hospitalized patients were eligible to participate in this study if they were aged 50 years or older, hospitalized at 1 of 2 hospitals located in the Inland Northwest, were referred for home care services following hospital discharge, and had at least 1 of the following diagnoses: 1) cardiovascular condition (congestive heart failure, myocardial infarction, coronary artery disease,

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Table 1. Intervention and Control Conditions to Assess and Resolve Medication Discrepancies Intervention Group

Control Group

Both Groups

 Participants assigned to nurse interventionist who has been trained to implement research protocol  Nurse interventionist receives electronic copy of hospital d/c medication list  Nurse interventionist identifies medication discrepancies between electronic d/c medication list and medications patients report taking at home  Nurse interventionist documents medication discrepancies using MDT and uses MDT to guide resolution of discrepancy  Nurse interventionist manages case and delivers needed skilled nurse services, including ongoing interventions to resolve med discrepancies  Nurse interventionist documents medication changes in the electronic medical record per usual protocols and status of medication discrepancy resolution documented on MDT before home care d/c

 Participants assigned to qualified home care staff nurses who are blinded to patient participation in the study  Staff nurses receive hard copies of hospital d/c medication list  Staff nurses use standard of care procedures to assess for med problems, including discrepancies  Staff nurses manage and deliver needed skilled nursing services, including ongoing interventions to resolve identified med problems  Medication changes are documented in the electronic medical record per usual protocol

 Pharmacist, blinded to group assignment and trained to implement the research protocol, receives an electronic copy of the hospital d/c medication list and basic demographic and health history information for patient participants  Pharmacist makes home visit to each participant within 10 days of hospital d/c to identify med discrepancies between the electronic d/c med list and the medications the patients reported taking at home following hospital d/c  Pharmacist documents med discrepancies using MDT  One month after hospital d/c, pharmacist evaluates the electronic medical record to determine medication discrepancy resolution status

d/c 5 discharge; MDT 5 Medication Discrepancy Tool.

cardiac arrhythmia), 2) peripheral vascular disease, 3) diabetes mellitus, 4) cerebral vascular accident, and 5) chronic obstructive pulmonary disease. Exclusion criteria consist of known terminal illness (documented in medical record with life expectancy 6 months or less); patients were excluded if they were unable to speak or understand English and if they were not anticipated to receive skilled home care nursing services (e.g., referral for therapy-only services). Procedures Home care coordinators notified research assistants about hospitalized patients who were being considered for home care services following discharge. Research assistants then

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recruited hospitalized patients who met the study inclusion criteria. Of the 347 patients approached to participate in the study, 261 (75.2%) agreed to participate. Patients who provided written informed consent were ‘‘prequalified’’ for study participation pending admission to home care services with receipt of skilled nursing care. Of those 261 patients, 201 (77.0%) were admitted for home care nursing services and formally enrolled in the study. Patient participants were randomly assigned to the intervention and control groups before being admitted to home care services. Team leaders at the home care agency were notified of participants, and those randomized to the control group were assigned to nurses per the home care agency’s usual procedure, with

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the exception that they were not assigned to one of the study’s intervention nurses. Patient randomized to the intervention group were assigned to 1 of 2 study intervention nurses who had been trained to implement the research protocol. Medication discrepancies were identified by nurse interventionists during the initial home visit with participants. To identify the discrepancies, nurse interventionists compared participants’ electronic hospital discharge medication lists to the medications the participants reported actually using in the home. Any identified differences between the participant’s hospital discharge list and the medications the participant reported using in the home were documented on the electronic version of the Medication Discrepancy Tool (MDT; Figure 1).

Measures The MDT was designed for use by clinicians from a variety of health disciplines to assess the frequency, causes, and factors contributing to medication discrepancies across the continuum of care.9 The instrument identifies both patientand system-level factors that can contribute to or cause medication discrepancies (Figure 1). The mean interrater reliability (l statistic) across disciplines (nurses, physicians, pharmacists) was 0.56 (15% low agreement, 80% good agreement, and 5% excellent agreement). Between nurses the l statistic was 0.68.9 The MDT was used by nurse interventionists in our study to identify contributing factors for medication discrepancies. The American Hospital Form Service medication classification system categorizes medications into classes.10 This system was used by our pharmacist researchers to categorize medication discrepancies identified in this study.

Findings Sample The sample includes the first 101 participants randomized to the intervention arm of the clinical trial. As is typical of patients who receive home care services, the majority of participants (63%) were female, participants’ average age was 73 years, and their hospital discharge medication lists identified a mean of 10.4 medications (Table 2).

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Data Analyses and Results Descriptive statistics were computed using SPSS 17.0. Of the 101 participants, 95 (94%) had at least 1 identified medication discrepancy. Medication discrepancies were categorized as having patient- and system-level contributing factors. Patient-level contributing discrepancy factors are those which are primarily related to patient characteristics (e.g., intolerance, financial barriers) or decisions made by the patient (e.g., intentional nonadherence, did not need prescription). System-level factors that contribute to medication discrepancies are primarily related to processes of the health care system (e.g., prescription given to patient despite known allergies, incomplete discharge instructions). Nurse-identified medication discrepancies for the sample ranged from 0 to 10 with a mean of 3.26 discrepancies per participant. Nearly 40% of the participants had 1 or more discrepancies that involved at least 1 patient-level contributing factor. The most common patient-level contributing factors identified in this study were intentional nonadherence, nonintentional nonadherence, and not filling a prescription (Table 3). More than 69% of the participants in our study had 1 or more discrepancies that involved at least 1 system-level contributing factor. The most common system-level contributing factors identified in this study were incomplete or inaccurate discharge instructions, conflicting information from different sources, and duplication of medications (Table 3). The most common medications and medication classes involved with medication discrepancies in this study were aspirin and warfarin, digoxin, antianxiety/sleep aids (e.g., zolpidem, lorazepam), vitamin and mineral supplements, bowel agents, opioids, insulin, oral antidiabetic agents, and diuretics. However, nearly all medication classes were involved in one or more instances.

Discussion Frequency and Types of Discrepancies This study sought to describe the most common medication discrepancies identified by nurses during patient transitions from hospital to home. Home care nurse medication assessments revealed that medication discrepancies

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Figure 1. Medication Discrepancy Tool. Ó 2005 Care Transitions Program. www.caretransitions. org. occurred after hospital discharge for the majority of participants. Medication discrepancies reported in this study are even higher than those reported in other research where findings range from 15% to 76%.2,6,11-13 The substantially higher rate of medication discrepancies found in this study is likely related to several factors. In this study, we broadly defined medication discrepancies as any difference in the hospital

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discharge medication list and the medications the participants reported consuming at home. One advantage of this study was the early assessment of medications for discrepancies. Experienced home health care nurses assessed for the presence of discrepancies at their initial posthospital discharge home visit within 72 hours of discharge with participants. The proximity of the assessment to the participants’ discharge from

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Table 2. Demographic and Health Characteristics of Intervention Arm Participants Characteristic Female Caucasian High school graduate At-risk based on self-rated health* Age

Number of medications on hospital discharge list

Value 63% 93% 87% 31% Mean: 72.98 Range: 51–96 SD: 9.84 Mean: 10.43 Range: 1–19 SD: 4.89

*Percent of participants who rated overall health as poor or fair.

the hospital offered an opportunity to promptly discover differences in the discharge medication list and the medications the participants reported taking. The differences noted between our study and others in terms of discrepancies may also be due to the complex health problems and number of medications used by this population. On average, these individuals consumed 10 medications. Older age and polypharmacy are known risk factors for medication discrepancies and errors.2,6 In addition, participants were recruited from acute care settings where hospitalists provide all inpatient generalist care. Such a model compromises continuity of care between inpatient and outpatient settings and increases the challenges associated with obtaining an accurate medication history at the point of admission. An inaccurate medication admission history can also result in an inaccurate reconciliation process at discharge and medication discrepancies following discharge.12,14 Finally, cost control efforts have created increasingly strict medication formularies in acute care settings that result in more medication substitutions and the potential for more medication discrepancies during the hospital to home transition. In our study, we identified more system-level discrepancies (69% of participants) than patientlevel discrepancies (40% of participants). In contrast, other researchers have identified

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a nearly equal proportion of system and patientlevel discrepancies.2,6 The most common contributing factor for system-level discrepancies in our study was incomplete or inaccurate discharge instructions. In general, this contributing factor was identified by the nurses when their assessment revealed that participants were taking medications in the home that were not on their discharge medication list. Such a discrepancy is known as an ‘‘error of omission’’ and has been a common contributing factor for discrepancies in other research.12,14-16 Errors of omission are often related to inaccuracies in the admission medication history. As noted earlier, the hospitalist model of care reduces continuity of inpatient and outpatient care and makes medication history-taking more difficult. One recent study suggests that clinicians’ lack of relevant knowledge and skill in medication history taking contributes to poor medication histories.17 Another common contributing factor to system-level medication discrepancies in our study was the presence of conflicting information from different sources. Nurses’ medication assessments revealed 2 common situations whereby conflicting information from different sources contributed to medication discrepancies: 1) when there were differences in the nurses’ electronic discharge medication list and the list that the participant had been given at discharge, and 2) when there were differences in the dose or frequency on the medication bottle label the participant had in the home compared with the electronic discharge list. Finally, duplication was frequently a contributing factor to systemlevel medication discrepancies. There are several health care delivery system characteristics that can lead to duplication. These include an inaccurate admission medication history, changes in medication based on formularies, failure to reconcile accurately home medications recorded during the admission medication history with discharge medications, and ineffective discharge education. Patient-level discrepancies were assessed by nurses in 40% of participants included in this analysis. The most common contributing factors were directly related to adherence and included not filling a prescription. Intentional nonadherence was the most common contributing factor for patient-level medication discrepancies and often overlapped with their decision not to fill a prescription. Most frequently, patients decided not

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Table 3. Percent of Participants in the Intervention Group with Differing Medication Discrepancy Causes and Contributing Factors Patient Level Medication Discrepancy Causes and Contributing Factors

Percent of Participants

Adverse drug reactions or side effects Intolerance Did not fill prescription Did not need prescription Money/financial barriers Intentional nonadherence Unintentional nonadherence Performance deficit System Level Medication Discrepancy Causes and Contributing Factors Prescribed with known allergies/intolerances Conflicting information from different informational sources Confusion between brand and generic names Discharge instructions incomplete/inaccurate/illegible Duplication Incorrect dosage Incorrect quantity Incorrect label Cognitive impairment not recognized No caregiver/need for assistance not recognized Sight/dexterity limitations not recognized

17.8% 3% 28.7% 7.9% 1% 39.6% 29.7% 5.9%

to fill a prescription because they perceived the medication was not necessary. Medications for pain were often identified in this category with the participants reporting they did not need that medication, generally a narcotic, for pain control or that they already had a pain medication in the home that they were substituting instead of filling the new prescription. Also included in this category were participants who purposely chose to take the medication differently from how it was prescribed (e.g., not as often). Less frequently, intentional nonadherence was related to an inability to pay for the medication or participants’ perceptions that the medication caused unacceptable side effects. Fisher and colleagues18 recently evaluated the rate of electronic prescriptions filled by patients and reported that only 78% of all prescriptions and only 72% of new prescriptions were filled. Nearly 30% of the patient-level discrepancies were attributed to participants not knowing that they were supposed to take a medication or a lack of knowledge about taking the medication as prescribed (nonintentional nonadherence). As such, medication discrepancies with this contributing factor ranged from participants not filling

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0% 35.6% 5.9% 46.5% 15.8% 14.9% 0% 6.9% 6.9% 4% 2%

a new prescription to their taking the wrong dose of a medication or taking the medication at an incorrect frequency. Similarly, other investigators have reported nonintentional nonadherence to be a common contributing factor of medication discrepancies.6,12 Improving Medication Management during Care Transitions Medication discrepancies were identified for nearly all classes of medications, including medication classes typically associated with high safety risks. In this study, nurses identified insulin, anticoagulants, aspirin, and opioids as being common medications involved in a discrepancy. These 4 types of medications are also responsible for adverse drug events that require emergency room visits.19 Consequently, the number and types of medication discrepancies identified in this study are alarming and reinforce the need for improvements in patient-centered care that will enhance communication and education about medications throughout the hospitalization as well as during the hospital to home transition. This is a daunting task, and the challenges of

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doing both have been well-documented elsewhere.5,8,14,16,18,20 The findings of our study, combined with those of others, suggest that medication reconciliation interventions at admission and during hospitalization are a high priority for decreasing postdischarge medication discrepancies in older adults who have multiple comorbid conditions and polypharmacy. Emerging research suggests that increasing resource allocation to medication history at the time of admission and subsequent reconciliation leads to improved care quality and is cost-effective.14,21 Methods that have demonstrated improvements in medication history and reconciliation include clinician training to improve medication history18 and assigning specific staff to reassess medication history and reconcile discrepancies during hospitalization for high-risk patients such as older adults with 10 or more medications and those with heart failure or diabetes.8,14,21 Specific improvements to discharge processes are also warranted to reduce medication discrepancies and improve outcomes. The work of Bombay, published in this volume of the journal, supports the need for better discharge teaching for hospitalized older adults to decrease the risk and occurrence of medication discrepancies. Education should include information about the medication, reason for taking the medication, and administration technique. Further, Transitional Care Models, tested in several clinical trials, have common elements, including a focus on medication management (Figure 2).4,22-24 Although these models have been shown to improve care outcomes and reduce overall health care costs, their adoption has been limited by the structure and reimbursement mechanisms of our current health care system.25 The research reported in this article is testing an intervention that can be enacted to identify and resolve medication discrepancies within the constraints of the current health care system. Nurses caring for high-risk older adults can deliver evidence-based interventions shown to reduce medication discrepancies and improve medication management following care transitions (Table 4). This article has focused on hospital to home medication discrepancies. However, similar medication discrepancies occur during transitions between hospital and other outpatient settings26 and between longterm care and acute care.27-29 Thus, although more research is required to evaluate definitively

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Figure 2. Elements of Transitional Care Models. their effectiveness, interventions to reduce transition-related medication discrepancies are likely to improve care outcomes across transition settings. The Agency for Healthcare Research and Quality (www.ahrq.gov/qual/pips) has several toolkits containing resources that can be used to implement the evidence-based interventions (Table 4). These resources include blueprints for health literacy assessment tools, medication tables, and discharge instructions.

Summary Medication discrepancies during the hospitalto-home transition are common. Medication discrepancies are wrought with potential patient safety risks, may lead to poor outcomes including adverse events, and are a source of preventable health care utilization. In our study, 94% of the participants transitioning from acute care to home care had at least 1 nurse-identified medication discrepancy. Medication discrepancies were identified for virtually all classes of medications, including those that pose high safety risks (e.g., anticoagulants, insulin). Evidence-based strategies to reduce medication discrepancies and improve medication management as patients transition from hospital to home are suggested. Nurses can also advocate for improved unitbased and health-system policies and procedures, as well as health policy changes, to improve transitional care and patient outcomes.

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Table 4. Evidence-Based Interventions to Reduce Transition-Related Medication Discrepancies Admission Devote adequate time and attention to obtaining and documenting a complete and accurate medication history. Involve family members in history taking as necessary. Ask patients and/or families for a list of home medications, or ask family members to bring in medication bottles (which are then returned home with family members) to improve medication accuracy and completeness. Consult with pharmacy staff or community pharmacy as necessary. During Hospitalization or Other Types of Care Provide education about the medication name, purpose, dose, and frequency as medications are administered. In outpatient settings, assist patients in making a list or table of their medications that includes the name, purpose, dose and frequency. Evaluate patients’ response and tolerance to medications. Consider patients’ capabilities to manage, mentally and physically, their own medication regimens. Discharge Provide patients with a clear and accurate list, or better yet, a medication table, that includes the name, purpose, dose, and frequency of each medication and teach the patient and family about these medications, how they should be administered, and common side effects to report to care providers. Teach patients/families about medications that they were taking before the current episode of care that they will be continuing to take and about medications that are new for them. Teach patients which medications are newly prescribed; be sure patients/families understand whether there is a hard copy of the prescription that they need to present to the pharmacy or whether an electronic prescription has already been sent. Assess patients’ abilities to purchase medications and refer to social services as necessary for assistance. Encourage patients to obtain all medications from the same pharmacy. Doing so helps identify duplication and interaction discrepancies. (Continued )

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Table 4. Continued Instruct patients about their follow-up appointments and the reason each appointment is important. One of the reasons for a follow-up appointment is to evaluate the patients’ use of and the effectiveness of new medication regimes. If possible, facilitate scheduling follow-up appointments before discharge. If appointments are scheduled, be sure to instruct patients verbally about the date, time, and place of the appointment as well as the reason for the appointment. Use ‘‘teach-back’’ techniques such that the patient and family repeat their understanding of the medication teaching you have provided. Reeducate as indicated. Consider whether patients/families may have low health literacy or whether interventions are culturally inappropriate if they are having difficulty understanding instructions.

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10. American Society of Health-Systems Pharmacists. American Hospital Form Service (AHFS) Drug Information 2010. Bethesda, MD: American Society of Health-Systems Pharmacists; 2010. 11. Bernstein L, Frampton J, Minkoff NB, et al. Medication reconciliation: Harvard Pilgrim Health Care’s approach to improving outpatient medication safety. J Healthc Qual 2007;29:40-5. 12. Karapinar-Carkit F, Borgsteede SD, Zoer J, et al. Effects of medication reconciliation with and without patient counseling on the number of pharmaceutical interventions among patients discharged from the hospital. Ann Pharmacother 2009;43:1001-10. 13. Walker PC, Bernstein SJ, Jones JN, et al. Impact of a pharmacist-facilitated hospital discharge program: a quasi-experimental study. Arch Intern Med 2009;169: 1988-95. 14. Gleason KM, McDanial MR, Feinglass J, et al. Results of Medications at Transitions and Clinical Handoffs (MATCH) Study: an analysis of medication reconciliation errors and risk factors at hospital admission [Epub ahead of print Feb 24]. J Gen Int Med 2010; doi:10.1007/s11606010-1256-6. 15. Cornish PL, Knowles SR, Marchesano R, et al. Unintended medication discrepancies at the time of hospital admission. Arch Intern Med 2005;165:424-9. 16. Tam VC, Knowles SR, Cornish PL, et al. Frequency, type and clinical importance of medication history errors at admission to hospital: a systematic review. CMAJ 2005; 173:510-5. 17. Chan AHY, Garratt E, Lawrence B, et al. Effect of education on the recording of medicines on admission to hospital [Epub ahead of print March 17]. J Gen Int Med 2010; doi:10.1007/s11606-010-1317-x. 18. Fisher MA, Stedman MR, Li J, et al. Primary medication non-adherence: analysis of 195,930 electronic prescriptions. J Gen Int Med 2010;25:284-90. 19. Budnitz DS, Pollock DA, Weidenbach KN, et al. National surveillance of emergency department visits for outpatient adverse drug events. JAMA 2006;296:1858-66. 20. Coffey M, Mack L, Streitenberger K, et al. Prevalence and clinical significance of medication discrepancies at pediatric hospital admission. Acad Pediatr 2009;9:360-5. 21. Costa L, Efird L, Feldman L, et al. Nurse-pharmacist collaboration on medication reconciliation: a novel approach to information management. Interdisciplinary Nursing Quality Research Initiative webinar. Available at http://inqri.blogspot.com/2010/01/yesterdays-webinarnursing-pharmacy.html. Cited March 24, 2010.

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22. Jack BW, Chetty VK, Anthony D, et al. A Reengineered hospital discharge program to decrease rehospitalization: a randomized trial. Ann Intern Med 2009;150:178-87. 23. Naylor MD, Brooten D, Jones R, et al. Comprehensive discharge planning for the hospitalized elderly: a randomized clinical trial. Ann Int Med 1994;120: 999-1006. 24. Naylor MD, Brooten DA, Campbell RL, et al. Transitional care of older adults hospitalized with heart failure: a randomized clinical trial. J Am Geriatr Soc 2004;52: 675-84. 25. California Health Care Foundation. Navigating care transitions in California: two models for change. 2008. Available at www.chcf.org/topics/chronicdisease/index. cfm?itemID5133766. Cited March 22, 2010. 26. Lalonde L, Lampron AM, Vanier MC, et al. Effectiveness of a medication discharge plan for transitions of care from hospital to outpatient settings. Am J Health-Sys Pharm 2008;65:1451-7. 27. Boockvar KS, Carlson-LaCorte H, Giambanco V, et al. Medication reconciliation for reducing drug-discrepancy adverse events. Am J Geriatr Pharmacother 2006;4: 236-43. 28. Naylor MD, Kurtzman ET, Pauly MV. Transitions of elders between long-term care and hospitals. Policy Polit Nurs Pract 2009;10:187-94. 29. Varkey P, Cunningham J, Bisping DS. Improving medication reconciliation in the outpatient setting. Jt Comm J Qual Patient Saf 2007;33:286-92. CYNTHIA F. CORBETT, PhD, is an Associate Professor at Washington State University, College of Nursing, Spokane, WA. STEPHEN M. SETTER, PharmD, DVM, is an Associate Professor at Washington State University, College of Pharmacy, Spokane, WA. KENN B. DARATHA, PhD, is an Assistant Professor at Washington State University, College of Nursing, Spokane, WA. JOSHUA J. NEUMILLER, PharmD, is an Assistant Professor at Washington State University, College of Pharmacy, Spokane, WA. LINDY D. WOOD, PharmD, is a clinical research fellow at Washington State University, College of Pharmacy, Spokane, WA. ACKNOWLEDGMENT Support for this work was provided by a grant from the Robert Wood Johnson Foundation’s Interdisciplinary Nursing Quality Research Initiative. 0197-4572/$ - see front matter Ó 2010 Mosby, Inc. All rights reserved. doi:10.1016/j.gerinurse.2010.03.006

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