BACKGROUND: The optimization of medication use during care transitions represents an opportunity to improve overall health-related outcomes. The utilization of clinical pharmacists during care transitions has demonstrated benefit, although the optimal method of integration during the care transition process remains unclear.
OBJECTIVE: To evaluate the impact of pharmacist-provided telephonic medication therapy management (MTM) on care quality in a care transitions program (CTP) for high-risk older adults.
METHODS: This prospective, randomized, controlled study was conducted from December 8, 2011, through October 25, 2012, in a primary care work group at a tertiary care academic medical center in the midwestern United States. High-risk elderly (aged ≥60 years) patients were randomized to a pharmacist-provided MTM program via telephone or to usual care within an existing outpatient CTP. The primary outcome was the quality of medication prescribing and utilization based on the Screening Tool to Alert Doctors to the Right Treatment (START) and the Screening Tool of Older Persons’ Prescriptions (STOPP) scores. The secondary outcomes were medication utilization using a modified version of the Medication Appropriateness Index, hospital resource utilization within 30 days of discharge, and drug therapy problems.
RESULTS: Of 222 eligible high-risk patients, 25 were included in the study and were randomized to the pharmacist MTM intervention (N = 13) or to usual care (N = 12). No significant differences were found between the 2 groups in medications meeting the STOPP or START criteria. At 30-day follow-up, no significant differences were found between the 2 cohorts in medication utilization quality indicators or in hospital utilization. At 30-day follow-up, 3 (13.6%) patients had an emergency department visit or a hospital readmission since discharge. In all, 22 patients completed the study. Medication underuse was common, with 20 START criteria absent medications evident for all 25 patients at baseline, representing 15 (60%) patients with ≥1 missing medications. Overall, 55 drug therapy problems were identified at baseline, 24 (43.6%) of which remained unresolved at 30-day follow-up.
CONCLUSION: The use of a pharmacist-provided MTM program did not achieve a significant difference compared with usual care in an existing CTP; however, the findings demonstrated frequent utilization of inappropriate medications as well as medication underuse, and many drug therapy problems remained unresolved. The small size of the study may have limited the ability to detect a difference between the intervention and usual care groups.
A key measure of the 2010 Affordable Care Act is the improvement of care transitions within the healthcare continuum.1 Optimal medication utilization is important during these care transitions. Elderly patients have shown a higher risk for drug-related adverse events with certain medications.2-7 Thus, Medicare Part D prescription drug plans are required to offer medication therapy management (MTM) to patients who meet certain criteria.8,9 The Medicare criteria for MTM eligibility vary by plan type and by disease, and include a diagnosis of a minimum number of chronic diseases, the use of a specific minimum number of prescription medications, and the likelihood of exceeding a predetermined annual medication cost threshold.10 Patients in care transitions often meet the MTM eligibility criteria; however, the optimal model of pharmacist integration during the care transition process remains unclear.
A variety of screening tools have been developed to improve medication quality and reduce the prevalence of drug-related adverse events. The Screening Tool of Older Persons’ Prescriptions (STOPP) was developed to identify potentially inappropriate medications, and the Screening Tool to Alert Doctors to the Right Treatment (START) was created to identify potential prescribing omissions.
The STOPP and START tools are scored by totaling the number of medications that meet certain criteria, with each potentially inappropriate medication and potential prescribing omission generating 1 point. Previous research indicates that a 0.5 decrease in STOPP score yielded a 17% risk reduction in medication-related hospital admissions.19 Although the START criteria were developed using evidence-based disease management, the clinical impact of this intervention remains to be explored.
Our objective was to assess the impact of comprehensive pharmacist-provided telephonic MTM on care quality in an outpatient care transitions program (CTP) in high-risk adults aged ≥60 years.
In this prospective, randomized, controlled trial, patients were randomized in a 1 to 1 ratio to the MTM intervention or the usual care cohort. The study was conducted from December 8, 2011, through October 25, 2012, in a primary care work group at a tertiary care academic medical center in the midwestern United States. The primary care work group included the family medicine and primary care internal medicine departments. The study was reviewed and approved by the Institutional Review Board.
The target enrollment for the study was set at 50 independent-living elderly adults (aged ≥60 years) who were enrolled in the local CTP. The determination of eligibility for the CTP required stratification of patients during hospitalization using the Elders Risk Assessment (ERA) index, which was developed to identify elderly patients who are at high risk for an emergency department visit or a hospital readmission.20 Patients who were newly enrolled in the CTP were targeted for participation in this study.
Each patient was reimbursed $25 as compensation for the time commitment required for the completion of the study. Patients were offered enrollment in the CTP during their hospitalization if they were empaneled in the primary care work group, resided within a 20-minute drive, and were predicted to be at risk for high healthcare utilization (ie, had an ERA index score of ≥16). The study coordinator recruited participants for the study and obtained informed consent during hospitalization or via a telephone call shortly after discharge from the hospital.
Patients were randomly assigned to either the intervention group or to the usual care group by a study coordinator. Randomization was completed during the phone call by the study coordinator, who opened a sealed envelope that contained an indication of which group the patient was assigned to.
The study statistician used a random number generator to determine the allocation sequence. The trial was unblinded (ie, the participants and the investigators were aware of the intervention), and the patients received a telephone call from the pharmacist if they were randomized to the intervention group. However, all outcomes were assessed while blinded to the intervention or the usual care group allocations.
The intervention group received an MTM consultation with a pharmacist by telephone, preferably within 3 (and up to 7) business days after hospital discharge. This intervention was developed using successful methods of pharmacist integration during care transitions,11,12 while complementing the services of an existing CTP, to assess the impact on the quality of medication use. The pharmacist obtained the necessary information and clinical assessments from each patient’s electronic medical record to complete a comprehensive review of all prescription, nonprescription, and herbal medications taken. This systematic review of medications included the identification, resolution, and prevention of drug-related problems, including adverse events or the use of potentially inappropriate medications.
In addition, the electronic medical record was investigated for potential prescribing omissions. This review was the foundation for the phone consultation with the patient to ensure medication optimization. Decisions were based on the pharmacist’s clinical judgment after considering practice guidelines, 2 clinical support databases (Truven Health Analytics’ Micromedex21 and Wolters Kluwer Lexi-Drugs22), or the highest-quality evidence available, as well as patient preferences. Recommendations were communicated by the pharmacist via a secure messaging function within the electronic medical record to the CTP provider for review on completion of the phone consultation.
The study included 5 pharmacists—2 had delivered the interventions and 3 performed the analysis; all the pharmacists had pharmacy doctoral degrees and were required to complete an MTM certification program.
The usual care group was defined as the preexisting CTP without pharmacist intervention. Patients enrolled in the CTP during their hospitalization received a home visit by a nurse practitioner within 3 business days after their discharge. As part of the visit, the nurse practitioner reviewed the patient’s medications and made changes as deemed appropriate. The changes were implemented directly or were discussed with the patient’s primary care provider, depending on clinical judgment. Follow-up telephone calls at scheduled intervals were implemented, depending on the needs of the individual patients.
The study coordinators functioned only in a research capacity, independent of the pharmacist intervention or usual care groups. They performed recruitment and obtained consent from participants. They collected patient characteristics at baseline within 7 days of hospital discharge and at 5 weeks after the intervention with a follow-up phone call. The information collected by the study coordinator included demographic factors, such as age, race, marital status, medication adherence, and patient-reported hospital or emergency department utilization.
Two independent pharmacists assessed the medication quality indicators for each patient at baseline after hospital discharge (before pharmacist intervention and/or the nurse practitioner home visit) and at 30 days after discharge.
The primary outcome was to identify potentially inappropriate medications with the STOPP criteria and potential prescribing omissions using the START criteria.
Is there unnecessary duplication with other drugs?
For the STOPP and START assessments, the medications involved included routinely administered systemic drugs other than topical treatments. The MAI assessment was applied to systemic drugs (other than over-the-counter or topical treatments) that were used on a regular basis.
Additional secondary end points included an assessment of healthcare resource utilization within 30 days of discharge, defined by (1) emergency department visits, (2) hospital readmissions, and (3) the composite of emergency department visits and hospital readmissions. These outcomes were self-reported during the 5-week follow-up telephone call from the study coordinator.
The study data were managed using Research Electronic Data Capture (REDCap) tools that are hosted at our institution.27 REDCap is a secure, web-based application designed to support data capture for research studies, providing (1) an intuitive interface for validated data entry, (2) audit trails for tracking data manipulation and export procedures, (3) automated export procedures for seamless data downloads to common statistical packages, and (4) procedures for importing data from external sources.
The START and STOPP scores were calculated for each patient. The possible scores ranged from 0 to 22 for the START criteria and from 0 to 65 for the STOPP criteria. Using the standard deviation estimates of 2.1 and 1.6 for the START and STOPP scores,28 respectively, a total sample size of 25 patients would allow the detection of mean between-group differences of 1.7 and 1.3, respectively, with 80% power.
The statistical methods used to compare the groups were the Wilcoxon rank-sum test for continuous or discrete ordinal variables and the Pearson’s chi-squared test for discrete nominal variables. In all cases, 2-tailed P values of <.05 were considered statistically significant. The continuous data are reported as the median (interquartile range), and the categorical data are reported as the frequency and percentage of the group represented. The data analysis was generated using SAS version 9.2 for UNIX (SAS Institute, Inc; Cary, NC).
Of the 222 patients eligible for the study, 197 patients were excluded from participation because they were either uninterested, were residing in a skilled nursing facility, unable to reach, had a clinical diagnosis of dementia or a terminal illness, or were unable or unwilling to provide informed consent (Figure). Of the 25 patients who were randomized to the MTM intervention (N = 13) or to usual care (N = 12), 2 died (1 from each cohort) and 1 patient in the intervention group voluntarily withdrew from the study.
Baseline patient characteristics are listed in the Table in the Appendix (see end of article). Table 1 compares baseline and 30-day follow-up outcomes for the 2 study cohorts. The study participants were predominantly male, white, and married, with a median age of approximately 84 years. At baseline, the patients in the pharmacist-intervention group used a median of 17 (interquartile range, 12-20) medications compared with 15.5 (interquartile range, 13-18.5) medications in the control group.
As shown in Table 1, the total number of medications and the number of required daily doses were not significantly different between the 2 groups at baseline and at 30-day follow-up. The between-group differences in medication adherence were also not significant. At the 30-day follow-up, no significant differences were found between the pharmacist-intervention and usual care groups in the number of STOPP medications or missing START medications (Table 2).
The secondary outcomes of the modified MAI assessment and the 30-day rates of emergency department visits, hospital readmissions, or the composite of both showed no significant differences between the 2 groups. Table 3 summarizes the drug therapy problems that were identified by the MTM consultation, which represented the pharmacist intervention. Our results show that 24 (43.6%) of the 55 identified drug therapy problems persisted at the 30-day follow-up (Table 3).
A major factor that might have affected the results of this study was the implementation rate of the pharmacist’s recommendations. The patients were reassessed at 30 days after hospital discharge by review of the electronic medical record to determine the status of their medication therapy problems compared with baseline. There were 55 drug therapy problems identified by the pharmacist at baseline, and 43.6% remained unresolved 30 days after discharge (Table 3). This suboptimal rate might have reduced the impact of the pharmacist’s interventions and the subsequent statistical differences between the 2 groups.
The results from our elderly cohort showed that each patient was taking approximately 9 prescription medications, suggesting an association with an increased number of inappropriate medications. Steinman and colleagues demonstrated the frequency of inappropriate medication use increases with the total number of medications taken. However, the frequency of potential prescribing omissions does not vary with the total number of medications taken.24 Our study demonstrated a fairly balanced percentage of potentially inappropriate medications versus potential prescribing omissions (approximately 68% vs 60%, respectively).
Our findings suggest that the implementation of a telephonic MTM consultation into an already resource-intensive, comprehensive CTP may not represent the optimal integration strategy. One area of potential further research is to identify specific patient populations that derive the most benefit from a pharmacist-provided MTM program during care transitions.
The primary limitation to the study is the small sample size, which yielded inadequate statistical power to allow us to draw definitive conclusions. Our initial intervention included an in-home assessment by the study coordinator to perform the baseline functional measurements. This requirement limited patient recruitment, and the intervention was modified to perform all baseline and follow-up assessments via telephone. However, this modification did not significantly improve patient recruitment. Thus, this study can be considered preliminary, and its data can be regarded as hypothesis-generating.
In addition, the pharmacist’s intervention was part of a multifaceted pilot CTP, and it is difficult to discern the absolute impact of this integration.
Notably, 2 of the 12 patients who were randomized to the usual care group had participated in MTM in the past 12 months. These 2 patients might have confounded the results, and might have introduced bias between the 2 treatment groups.
Finally, the study was conducted at a single center, which might have also limited the results.
Although many studies have examined methods to improve care transitions from a hospital to home, an optimal standard of practice has not yet been determined. Utilizing screening tools such as START, STOPP, or MAI may be helpful in transitioning patients, but it is also important to recognize the individual needs of each patient. Inappropriate medication use and underuse were common within the elderly cohort in our study. Although pharmacist-provided MTM consultation did not demonstrate a statistically significant benefit, the negative findings may be attributable to a lack of statistical power because of the small sample size or to the suboptimal integration into the care model. Future research should include a method to identify the specific patients who would benefit most from intervention by a pharmacist.
The authors would like to thank Stephanie M. Quigg, Betty A. Wirt, and Ivana T. Croghan, PhD.
Dr Haag, Dr Davis, Dr Hoel, Dr Armon, Dr Odell, and Mr Dierkhising reported no conflicts of interest. Dr Takahashi is on the Medical Board of Axial, LLC.
1. Patient Protection and Affordable Care Act, Pub L No. 111-148, 124 Stat 119. https://govtrack.us/congress/bills/111/hr3590/text. Accessed July 20, 2011.
2. Chutka DS, Evans JM, Fleming KC, Mikkelson KG. Symposium on geriatrics—Part I: Drug prescribing for elderly patients. Mayo Clin Proc. 1995;70: 685-693.
3. Chutka DS, Takahashi PY, Hoel RW. Inappropriate medications for elderly patients. MayoClinProc. 2004;79:122-139.
4. Fick DM, Cooper JW, Wade WE, et al. Updating the Beers criteria for potentially inappropriate medication use in older adults: results of a US consensus panel of experts. Arch Intern Med. 2003;163:2716-2724. Erratum in: Arch Intern Med. 2004;164:298.
5. Page RL 2nd, Ruscin JM. The risk of adverse drug events and hospital-related morbidity and mortality among older adults with potentially inappropriate medication use. Am J Geriatr Pharmacother. 2006;4:297-305.
6. Hilmer SN, Mager DE, Simonsick EM, et al; for the Health ABC Study. Drug burden index score and functional decline in older people. Am J Med. 2009;122:1142-1149.e2.
7. Steinman MA, Hanlon JT. Managing medications in clinically complex elders: “there’s got to be a happy medium.” JAMA. 2010;304:1592-1601.
8. Medicare Prescription Drug, Improvement, and Modernization Act of 2003, Pub L No. 108-173, 117 Stat 2066.
9. Smith SR, Clancy CM. Medication therapy management programs: forming a new cornerstone for quality and safety in Medicare. Am J Med Qual. 2006;21:276-279.
10. Centers for Medicare & Medicaid Services. Medication therapy management. http://cms.gov/Medicare/Prescription-Drug-Coverage/PrescriptionDrugCovContra/MTM.html. Accessed January 23, 2014.
11. Dudas V, Bookwalter T, Kerr KM, Pantilat SZ. The impact of follow-up telephone calls to patients after hospitalization. Am J Med. 2001;111(9 suppl 2):26S-30S.
12. Jack BW, Chetty VK, Anthony D, et al. A reengineered hospital discharge program to decrease rehospitalization: a randomized trial. Ann Intern Med. 2009;150:178-187.
13. Stewart S, Pearson S, Horowitz JD. Effects of a home-based intervention among patients with congestive heart failure discharged from acute hospital care. Arch Intern Med. 1998;158:1067-1072.
14. Koehler BE, Richter KM, Youngblood L, et al. Reduction of 30-day postdischarge hospital readmission or emergency department (ED) visit rates in high-risk elderly medical patients through delivery of a targeted care bundle. J Hosp Med. 2009;4:211-218.
15. Zillich AJ, Snyder ME, Frail CK, et al. A randomized, controlled pragmatic trial of telephonic medication therapy management to reduce hospitalization in home health patients. Health Serv Res. 2014;49:1537-1554.
16. Gallagher P, O’Mahony D. STOPP (Screening Tool of Older Persons’ potentially inappropriate Prescriptions): application to acutely ill elderly patients and comparison with Beers’ criteria. Age Ageing. 2008;37:673-679.
17. Petrarca AM, Lengel AJ, Mangan MN. Inappropriate medication use in the elderly. Consult Pharm. 2012;27:583-586.
18. Barry PJ, Gallagher P, Ryan C, O’Mahony D. START (screening tool to alert doctors to the right treatment)—an evidence-based screening tool to detect prescribing omissions in elderly patients. Age Ageing. 2007;36:632-638.
19. Gillespie U, Alassaad A, Hammarlund-Udenaes M, et al. Effects of pharmacists’ interventions on appropriateness of prescribing and evaluation of the instruments’ (MAI, STOPP and STARTs’) ability to predict hospitalization—analyses from a randomized controlled trial. PLoS One. 2013;8:e62401.
20. Crane SJ, Tung EE, Hanson GJ, et al. Use of an electronic administrative database to identify older community dwelling adults at high-risk for hospitalization or emergency department visits: the elders risk assessment index. BMC Health Serv Res. 2010;10:338.
21. Truven Health Analytics. Micromedex 2.0. www.micromedexsolutions.com. Accessed December 8, 2011.
22. Wolters Kluwer. Lexi-Drugs. http://online.lexi.com. Accessed December 8, 2011.
23. Hanlon JT, Schmader KE, Samsa GP, et al. A method for assessing drug therapy appropriateness. J Clin Epidemiol. 1992;45:1045-1051.
24. Steinman MA, Landefeld CS, Rosenthal GE, et al. Polypharmacy and prescribing quality in older people. J Am Geriatr Soc. 2006;54:1516-1523.
25. Morisky DE, Ang A, Krousel-Wood M, Ward HJ. Predictive validity of a medication adherence measure in an outpatient setting. J Clin Hypertens (Greenwich). 2008;10:348-354.
26. Cipolle RJ, Strand LM, Morley PC. Pharmaceutical Care Practice: The Clinician’s Guide. 2nd ed. New York, NY: McGraw-Hill; 2004.
27. Harris PA, Taylor R, Thielke R, et al. Research electronic data capture (REDCap)—a metadata-driven methodology and workflow process for providing translational research informatics support. J Biomed Inform. 2009;42:377-381.
28. Brahmbhatt M, Palla K, Kossifologos A, et al. Appropriateness of medication prescribing using the STOPP/START criteria in veterans receiving home-based primary care. Consult Pharm. 2013;28:361-369.
29. Kwint H-F, Bermingham L, Faber A, et al. The relationship between the extent of collaboration of general practitioners and pharmacists and the implementation of recommendations arising from medication review: a systematic review. Drugs Aging. 2013;30:91-102.
30. Shrank WH, Asch SM, Adams J, et al. The quality of pharmacologic care for adults in the United States. Med Care. 2006;44:936-945.
31. Takahashi PY, Haas LR, Quigg SM, et al. 30-day hospital readmission of older adults using care transitions after hospitalization: a pilot prospective cohort study. Clin Interv Aging. 2013;8:729-736.
32. Fitzgerald LS, Hanlon JT, Shelton PS, et al. Reliability of a modified medication appropriateness index in ambulatory older persons. Ann Pharmacother. 1997;31:543-548.
Medication therapy management (MTM) is an effective way to assess the current medication use and educational needs of a patient. Transitioning care from a healthcare facility to the outpatient setting is a critical point in the treatment process of patients with chronic diseases. The article by Haag and colleagues highlights the importance of proper education and counseling to help patients understand their therapy needs, and the importance of adhering to treatment recommendations.1 The small sample size of the study, however, might have contributed to the lack of differences between the study groups: still, this endeavor points to key challenges for providers, patients, and health plans in the attempt to improve health outcomes by delivering safe and effective medications while enhancing patient quality of life.
These statistics highlight the need for a comprehensive approach to MTM that will involve all stakeholders in the delivery system to achieve quality drug therapy. Missed medications can lead to serious adverse outcomes, including disease exacerbation, medication changes by the provider because of a perceived lack of efficacy, and wasted dollars spent on inappropriately used drugs—all of which creates significant gaps in care.
PHARMACISTS: This study provides insight into potential opportunities for clinical pharmacists, community pharmacists, and institutional pharmacists to help achieve improvements in drug treatment. Haag and colleagues note that even after 30 days, many problems related to drug therapy were still unresolved.1 A systematic approach is needed to effectively target patients in this 30-day window for interventions that will address these problems. These gaps in care increase the risk for an adverse event, promote poor outcomes, and drive up healthcare expenses.
PAYERS: To increase the level of medication management and improve access to MTM services, it may be time to consider compensation to pharmacists for these services, provided that there is documentation of true clinical and financial benefits to the patients and/or the health plan. An effective MTM program can improve health, prevent undesired clinical outcomes, and save scarce resources that may be applied to new and innovative treatments for chronic diseases.
PATIENTS: In addition, patients need to become more engaged in their own care through effective health and wellness programs, counseling, and formal disease education. These activities can be combined with an effective MTM program to ultimately affect poor health and deliver consistent improvements in health outcomes.
1. Haag JD, Davis AZ, Hoel RW, et al. Impact of pharmacist-provided medication therapy management on healthcare quality and utilization in recently discharged elderly patients. Am Health Drug Benefits. 2016;9(5):259-267.
2. Cranor CW, Bunting BA, Christensen DB. The Asheville Project: long-term clinical and economic outcomes of a community pharmacy diabetes care program. J Am Pharm Assoc. 2003;43:173-184.