TY - JOUR
AU - Sonnett, Travis, E.
AB - Abstract Purpose. The effectiveness of a collaborative pharmacist–nurse intervention on resolving detected medication discrepancies as patients transitioned from hospital to home health care was evaluated. Methods. Patients age 50 years or older who were transitioning from hospital to home health care with qualifying diagnoses were eligible for study inclusion. Patients were assigned to a control or intervention group based on the geographic location of the patients’ home. For the intervention group, the study coordinator initiated consultation with the nurse case manager to facilitate discrepancy resolution. Patients in the control group received usual care after the initial home visit by the study coordinator. Rehospitalization rates and the number of planned and unplanned physician visits were analyzed. Descriptive statistics were used to characterize and contrast patients in each study group. Equivalency testing was conducted to evaluate group comparability for demographic and health status variables and the use of health care services. Results. A total of 490 medication discrepancies were identified. The discrepancy resolution rates in the intervention and control groups were 67.0% and 54.6%, respectively. Assignment to the intervention group was associated with enhanced medication discrepancy resolution (r = 0.539, p = 0.001). There was a trend toward more planned and unplanned physician visits, and a trend toward a greater number of rehospitalization days. Conclusion. A pharmacist–nurse collaboration designed to identify and resolve medication-related discrepancies in patients transitioning from the hospital to home health care led to significant improvement in medication discrepancy resolution. Drugs, adverse reactions, Errors, medication, Health care, Hospitals, Nurses, Patient care, Pharmacists An estimated 3.5 million patients receive home health services annually, the majority of whom receive these services after hospitalization.1 Hospitals strive to shorten patients’ length of hospital stay for fiscal viability, and acutely ill patients are often discharged with instructions to follow complex inpatient-initiated therapeutic regimens at home. Patients are extremely vulnerable during this transition due to illness severity, functional impairment, and medication changes occurring at the interface of acute and ambulatory care.2 As a population, home care patients have a high risk of experiencing medication-related problems and adverse outcomes.3 Unfortunately, when patients are transferred between care environments, accurate communication of their health and medication information does not always occur.4 Limited existing data suggest that approximately 50% of the nearly 3 million adults age 65 years or older who are transitioning from hospital to home care annually experience a medication discrepancy.5,6 Patients are believed to be discharged from the hospital quicker and sicker, and medication interventions designed to maximize patient safety are needed.2,6,7 In a study examining transitions from acute care settings among patients age 65 years or older, the transition from hospitals to home health care was associated with increased health care resource utilization, including subsequent emergency room visits and avoidable hospitalizations.8 In one study, adverse drug events (ADEs) attributed to medication changes (due to differences in institutional and outpatient formularies) occurred in 20% of patients transferred from a hospital to a long-term-care facility.9 Home health care agencies typically serve patients for a short duration, care for the frailest of patients, and are in contact with a patient’s health care provider, family member, or caregiver.1 The home care nurse case manager (NCM) is the single individual to whom information is routed at the time of hospital discharge. Thus, there exists an opportunity for pharmacy and nursing to collaborate to identify and rectify drug-related problems and mitigate ADEs in a timely manner. Such an intervention has the potential to optimize patient outcomes and reduce health care expenditures.1 Little research has been conducted on medication discrepancies experienced by patients as they transition from hospital to home.10,11 In one of the few studies examining transitional care, 14% of patients age 65 years or older experienced a medication discrepancy.10 Of the discrepancies, 50.8% were characterized as patient associated (e.g., did not fill prescription, intentional nonadherence); the remaining 49.2% were characterized as system associated (e.g., prescribed with known allergies, incorrect label). The objective of this study was to evaluate the effect of a pharmacist– nurse collaboration to resolve identified medication discrepancies occurring during the transition from hospital to home health care in adults age 50 years or older. The primary outcome was the percentage of medication discrepancies resolved. Secondary outcomes included the numbers of planned and emergent physician visits and repeat hospitalizations. Methods Study design A prospective, longitudinal study design was used. Patients discharged from the hospital were admitted to the Visiting Nurse Association (VNA). Patients were considered for study enrollment if they were age 50 years or older, were transitioning from hospital to home care, and had been diagnosed with one or more of the following: congestive heart failure, myocardial infarction, coronary artery disease, cardiac arrhythmia, diabetes mellitus, cerebrovascular accident (e.g., stroke), chronic obstructive pulmonary disease, peripheral vascular disease, and major orthopedic surgery or fracture. These diagnoses were chosen because patients with one or more of these often require skilled nursing services when discharged to home. Patients were excluded if they had an impaired cognitive status (failing the MiniCog test), did not speak English, or did not receive skilled nursing services from the VNA. Standard admission protocols for VNA include assigning patients to an east or west nursing team based on the geographic location of the patient’s home. Patients who received nurse-managed care from the east team were placed in the control group, and patients who received care from the west team were placed in the intervention group. This method of patient assignment was preferred over random assignment to avoid the possibility of spillover effects between groups. NCMs provided care to patients in either the intervention or control group but not to both groups. The strength of the intervention was believed to be at risk if individual NCMs were exposed to the collaborative reconciliation process for some patients but not for others (i.e., nurses may seek pharmacy consultation more frequently for patients after exposure to the collaborative intervention). VNA data revealed no differences in the educational level, total years of nursing experience, and years of home health care experience for NCMs in the east and west teams. Data from the VNA also indicated that patients in the east and west teams were similar in sex, age, diagnostic profiles, number of medications, and type of insurance. The study coordinator—a research pharmacist—screened all home care admissions for eligible diagnoses and the use of nursing services and contacted NCMs for permission to contact patients regarding participation in the study. Once permission was received, eligible patients were contacted by the study coordinator and told about the study. Those interested in participating were visited at home by the study coordinator, who obtained informed written consent from patients during this visit. The study coordinator was not blinded to patients’ group assignment. Data collection Patients’ demographic, diagnostic, procedural, and medication information (including hospital admission drug history, hospital drug history, and discharge drug list) was collected. Self-reported health status was assessed during the initial in-home interview, where participants were asked to rate their health as 1 = poor, 2 = fair, 3 = good, 4 = very good, and 5 = excellent. All medication discrepancies were documented using a medication discrepancy tool (MDT).11 For the intervention group, a memo outlining medication discrepancies identified was provided to the NCM by the study coordinator and, as needed, to the patient’s physician, the patient, and his or her family members or caregiver to adequately facilitate discrepancy resolution. The study coordinator initiated consultation with the NCM to facilitate discrepancy resolution, using the MDT for guidance. The NCM, in collaboration with the study coordinator, recorded resolution progress for each medication discrepancy. Eight weeks after study enrollment, medication discrepancies were classified as resolved, unresolved, or pending resolution based on a final assessment by the study coordinator and the patient’s NCM. In contrast, patients in the control group received usual care after the initial home visit by the study coordinator and documentation of medication discrepancies. Usual care included sporadic pharmacy consultation (by a pharmacist other than the study coordinator) only if initiated by the NCM. If identified medication discrepancies were deemed dangerous or life threatening, action was taken immediately to resolve such discrepancies. As in the intervention group, discrepancy resolution rates were assessed for all patients in the control group. Rehospitalization rates and the numbers of planned and unplanned physician visits were also collected for all patients at eight weeks postenrollment by scripted interview via telephone and, when feasible, confirmed using the patients’ chart. Data analysis Statistical analyses was conducted using the Statistical Package for the Social Sciences, version 16.0 (SPSS, Inc., Chicago, IL). Descriptive statistics were used to characterize and contrast patients in each study group. Equivalency testing was conducted to evaluate group comparability for demographic and health status variables and the use of health care services. Discrepancy resolution and health care utilization between groups were compared using t tests. Correlations between independent variables and each outcome variable of interest (i.e., medication discrepancy resolution, number of unplanned physician visits, and total number of days patients were rehospitalized after admission to home health care) were discerned. Variables that were significantly correlated with outcomes of interest served as independent variables in linear regression models. The a priori level of significance was set at 0.05 for all analyses. The study was sufficiently powered to detect a difference in each study endpoint with 95% confidence. All procedures and methods utilized for this study were approved by the institutional review board of Washington State University before study initiation, and appropriate Health Insurance Portability and Accountability Act procedures were followed. Results A total of 220 patients voluntarily enrolled in the study (110 in the control group, 110 in the intervention group). Although geographic patient assignment was used, baseline characteristics, including demographic characteristics, health status, and health care utilization rates between groups were similar (Table 1). The mean ± S.D. numbers of medication discrepancies in the control and intervention groups were 2.1 ± 2.4 and 2.0 ± 2.6, respectively. The total numbers of discrepancies identified in the control and intervention groups were also similar (226 and 222, respectively). For both groups combined, 45.7% of identified contributing factors for discrepancies were categorized as patient associated, and 54.3% were categorized as system associated. There was a trend toward greater mean ± S.D. numbers of planned (3.5 ± 2.7 versus 2.9 ± 1.5) and unplanned (0.4 ± 1.0 versus 0.2 ± 0.6) physician visits and a trend toward a greater mean ± S.D. number of re-hospitalization days after home care admission (1.1 ± 4.2 versus 0.4 ± 1.2) in the control group compared with the intervention group, respectively. In contrast, the control group had a lower mean ± S.D. medication discrepancy resolution rate (0.6 ± 0.4) as compared with the intervention group (0.7 ± 0.4) (p < 0.001). The only variable that was significantly correlated with the discrepancy resolution rate was group assignment. Assignment to the intervention group was associated with enhanced medication discrepancy resolution (r = 0.539, p = 0.001). Several variables were significantly correlated with each of the health care utilization variables (i.e., planned physician visits, unplanned physician visits, and number of days rehospitalized). Regression models based on those variables explained only a small amount of the variance in each of the health care utilization outcomes examined. Variables predicting planned physician visits (R2 = 0.114, p < 0.001) were lower self-rated health (p = 0.01), longer hospital length of stay (p = 0.04), and not keeping a medication list before hospitalization (p = 0.02). Unplanned physician visits were predicted (R2 = 0.138, p < 0.001) by a longer hospitalization (p = 0.001), more prescription medications at hospital admission (p = 0.001), and assignment to the control group (p = 0.04). For the entire study cohort, total rehospitalization days were predicted (R2 = 0.207, p < 0.001) by female sex (p = 0.05) and larger numbers of planned physician visits (p < 0.001). Discussion These findings indicate that a pharmacist–nurse collaboration was effective in resolving medication discrepancies in patients transitioning from the hospital setting to a home health care nursing agency. Findings from other studies indicate that medication discrepancies and ADEs are common during this transition period between health care settings. For example, Forster and colleagues6 determined that nearly one in five patients experienced an ADE during the transition from the hospital to home and that system problems contributed to the majority of the preventable and ameliorable ADEs. Drug dosage changes and discontinuations are common at hospital admission, and upwards of 10,000 hospitalized patients have serious ADEs each year.9,12 Differences between hospital and outpatient formularies and the initiation or discontinuation of medications add to the potential for drug-related problems in the ambulatory care environment. The Joint Commission medication reconciliation requirement may help alleviate some discrepancy problems that occur after hospital discharge. However, prior research indicates that inaccurate and incomplete discharge instructions constitute the majority of system-related problems, while nonintentional nonadherence is the most common patient-associated problem.10 Ultimately, the Joint Commission medication discrepancy mandate is likely to be ineffective in reducing many system problems at the time of discharge. Patients and their families often assume a dependent and passive role for medication management during hospitalizations. Brief instructions given about medication changes to patients and their families, who often manifest anxiety, pain, and sleep deprivation, can facilitate missed information and misunderstanding.10 A collaborative pharmacist–nurse intervention implemented at the time of transition from hospital to home health care has the potential to prevent many drug-related problems and mitigate ADEs.8 While the role of the pharmacist in decreasing drug-related problems and ADEs is well documented in institutional settings,13,–16 there is a paucity of data regarding the potential role of the pharmacist in home care.7,17 Typically, when a patient is discharged from a hospital and transitioned to home health care, an NCM will oversee the process with little or no collaboration with a pharmacist.18,19 Hsia et al.20 conducted a trial involving the use of a pharmacist to provide a medication evaluation visit in the home of 20 patients. A decrease in medication discrepancies and problems was noted three to four weeks after the inhome visit by the pharmacist. In another trial, the effectiveness of a clinical pharmacy service model, including explicit referral criteria, designed to resolve drug-related problems for home care patients at high risk for ADEs was tested.21 Of the 80 patients who received the service, 100% had an identified drug-related problem. Nearly 65% of pharmacist recommendations were implemented. Another randomized trial, using a structured collaboration between a clinical pharmacist and home care nurses to improve medication management in two of the largest home care agencies in the country, found significant improvements in unnecessary therapeutic duplication and in the use of cardiovascular medications in the intervention group.1 One small study examined the effect of providing a list of drugs at hospital discharge to be shared with the community pharmacist.22 Unintentional medication discrepancies occurred in 32.2% of patients who received the list and in 52.7% of patients who did not receive such a list (p < 0.01). This study demonstrated that simple interventions can often have a great effect on reducing medication discrepancies. Other industries (e.g., airlines, space launch programs) have demonstrated the effectiveness of having multiple layers of redundancy, involving independent assessment and evaluation, to reduce errors and improve safety.23 The health care system as a whole, however, lags behind these other industries in terms of quality-control measures and redundancies to improve safety outcomes. The Joint Commission medication discrepancy mandate provides one such layer of evaluation. However, it does not address issues across health care systems throughout the continuum of care, notably the transition from hospital to home. Our study implemented an integrated collaborative medication discrepancy resolution program to provide another level of evaluation and safety using the MDT as a template. Specifically, this study demonstrated that with a multidisciplinary, integrated approach to identifying and resolving medication discrepancies, improved resolution of discrepancies can be achieved. In addition, the numbers of unplanned physician visits and rehospitalization days can be decreased with such an intervention. Although our findings on these endpoints did not reach statistical significance, these outcomes may be clinically important. This study had several limitations. Patients were recruited from a single health care system in Spokane, Washington. In addition, the study was not randomized. Also, participants volunteered for the study, possibly introducing self-selection bias. Furthermore, patients’ literacy level and general medication management abilities may have affected their medication management skills and were not measured in this study. Finally, patients with cognitive impairment were excluded from the study. Further research is needed to explore strategies to efficiently and effectively identify and resolve medication discrepancies and measure their effect on improved outcomes in the home health care environment. Conclusion A pharmacist–nurse collaboration designed to identify and resolve medication-related discrepancies in patients transitioning from the hospital to home health care led to significant improvement in medication discrepancy resolution. Table 1. Characteristics of Patients in the Control and Intervention Groups Characteristic Control Group (n= 110) Intervention Group (n= 110) a1 = poor, 2 = fair, 3 = good, 4 = very good, and 5 = excellent. Mean ± S.D. age, yr 72.7 ± 10.1 74.9 ± 9.9 Male, no. (%) 53 (48) 47 (43) White, non-Hispanic, no. (%) 106 (96) 105 (95) Living with caregiver, no. (%) 41 (37) 39 (35) Mean ± S.D. Charlson comorbidity index score 27.7 ± 31.5 30.0 ± 32.4 Mean ± S.D. self-rated healtha 1.5 ± 1.0 1.5 ± 1.1 Mean ± S.D. length of hospital stay, days 6.2 ± 4.3 6.1 ± 4.9 Mean ± S.D. no. medications at hospital discharge     Prescription 10.0 ± 4.9 9.2 ± 4.5     Nonprescription 2.2 ± 1.8 2.4 ± 2.0     Herbal preparation 0 ± 0.1 0.1 ± 0.5 Mean ± S.D. no. home medications     Prescription 9.8 ± 4.9 9.0 ± 4.3     Nonprescription 2.7 ± 2.0 2.8 ± 2.1     Herbal preparation 0.1 ± 0.4 0.1 ± 0.3 Mean ± S.D. no. medication discrepancies 2.1 ± 2.4 2.0 ± 2.3 Characteristic Control Group (n= 110) Intervention Group (n= 110) a1 = poor, 2 = fair, 3 = good, 4 = very good, and 5 = excellent. Mean ± S.D. age, yr 72.7 ± 10.1 74.9 ± 9.9 Male, no. (%) 53 (48) 47 (43) White, non-Hispanic, no. (%) 106 (96) 105 (95) Living with caregiver, no. (%) 41 (37) 39 (35) Mean ± S.D. Charlson comorbidity index score 27.7 ± 31.5 30.0 ± 32.4 Mean ± S.D. self-rated healtha 1.5 ± 1.0 1.5 ± 1.1 Mean ± S.D. length of hospital stay, days 6.2 ± 4.3 6.1 ± 4.9 Mean ± S.D. no. medications at hospital discharge     Prescription 10.0 ± 4.9 9.2 ± 4.5     Nonprescription 2.2 ± 1.8 2.4 ± 2.0     Herbal preparation 0 ± 0.1 0.1 ± 0.5 Mean ± S.D. no. home medications     Prescription 9.8 ± 4.9 9.0 ± 4.3     Nonprescription 2.7 ± 2.0 2.8 ± 2.1     Herbal preparation 0.1 ± 0.4 0.1 ± 0.3 Mean ± S.D. no. medication discrepancies 2.1 ± 2.4 2.0 ± 2.3 Table 1. Characteristics of Patients in the Control and Intervention Groups Characteristic Control Group (n= 110) Intervention Group (n= 110) a1 = poor, 2 = fair, 3 = good, 4 = very good, and 5 = excellent. Mean ± S.D. age, yr 72.7 ± 10.1 74.9 ± 9.9 Male, no. (%) 53 (48) 47 (43) White, non-Hispanic, no. (%) 106 (96) 105 (95) Living with caregiver, no. (%) 41 (37) 39 (35) Mean ± S.D. Charlson comorbidity index score 27.7 ± 31.5 30.0 ± 32.4 Mean ± S.D. self-rated healtha 1.5 ± 1.0 1.5 ± 1.1 Mean ± S.D. length of hospital stay, days 6.2 ± 4.3 6.1 ± 4.9 Mean ± S.D. no. medications at hospital discharge     Prescription 10.0 ± 4.9 9.2 ± 4.5     Nonprescription 2.2 ± 1.8 2.4 ± 2.0     Herbal preparation 0 ± 0.1 0.1 ± 0.5 Mean ± S.D. no. home medications     Prescription 9.8 ± 4.9 9.0 ± 4.3     Nonprescription 2.7 ± 2.0 2.8 ± 2.1     Herbal preparation 0.1 ± 0.4 0.1 ± 0.3 Mean ± S.D. no. medication discrepancies 2.1 ± 2.4 2.0 ± 2.3 Characteristic Control Group (n= 110) Intervention Group (n= 110) a1 = poor, 2 = fair, 3 = good, 4 = very good, and 5 = excellent. Mean ± S.D. age, yr 72.7 ± 10.1 74.9 ± 9.9 Male, no. (%) 53 (48) 47 (43) White, non-Hispanic, no. (%) 106 (96) 105 (95) Living with caregiver, no. (%) 41 (37) 39 (35) Mean ± S.D. 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Evaluation of the culture of safety: survey of clinicians and managers in an academic medical center. Qual Saf Health Care . 2003 ; 12 : 405 –10. Crossref Search ADS PubMed Author notes Eric A. Coleman, M.D., M.P.H., is acknowledged for his expert consultation on this research project. Funded by a research grant from the ASHP Research and Education Foundation, Bethesda, MD. The authors have declared no potential conflicts of interest. Copyright © 2009, American Society of Health-System Pharmacists, Inc. All rights reserved.
TI - Effectiveness of a pharmacist–nurse intervention on resolving medication discrepancies for patients transitioning from hospital to home health care
JF - American Journal of Health-System Pharmacy
DO - 10.2146/ajhp080582
DA - 2009-11-15
UR - https://www.deepdyve.com/lp/oxford-university-press/effectiveness-of-a-pharmacist-nurse-intervention-on-resolving-JSC9G2j61g
SP - 2027
VL - 66
IS - 22
DP - DeepDyve
ER -