Currently Viewing:
The American Journal of Managed Care October 2016
Cost-Effectiveness of a Statewide Falls Prevention Program in Pennsylvania: Healthy Steps for Older Adults
Steven M. Albert, PhD; Jonathan Raviotta, MPH; Chyongchiou J. Lin, PhD; Offer Edelstein, PhD; and Kenneth J. Smith, MD
Currently Reading
Economic Value of Pharmacist-Led Medication Reconciliation for Reducing Medication Errors After Hospital Discharge
Mehdi Najafzadeh, PhD; Jeffrey L. Schnipper, MD, MPH; William H. Shrank, MD, MSHS; Steven Kymes, PhD; Troyen A. Brennan, MD, JD, MPH; and Niteesh K. Choudhry, MD, PhD
Patients' Success in Negotiating Out-of-Network Bills
Kelly A. Kyanko, MD, MHS, and Susan H. Busch, PhD
Connected Care: Improving Outcomes for Adults With Serious Mental Illness
James M. Schuster, MD, MBA; Suzanne M. Kinsky, MPH, PhD; Jung Y. Kim, MPH; Jane N. Kogan, PhD; Allison Hamblin, MSPH; Cara Nikolajski, MPH; and John Lovelace, MS
A Call for a Statewide Medication Reconciliation Program
Elisabeth Askin, MD, and David Margolius, MD
Postdischarge Telephone Calls by Hospitalists as a Transitional Care Strategy
Sarah A. Stella, MD; Angela Keniston, MSPH; Maria G. Frank, MD; Dan Heppe, MD; Katarzyna Mastalerz, MD; Jason Lones, BA; David Brody, MD; Richard K. Albert, MD; and Marisha Burden, MD
Mortality Following Hip Fracture in Chinese, Japanese, and Filipina Women
Minal C. Patel, MD; Malini Chandra, MS, MBA; and Joan C. Lo, MD
Estimating the Social Value of G-CSF Therapies in the United States
Jacqueline Vanderpuye-Orgle, PhD; Alison Sexton Ward, PhD; Caroline Huber, MPH; Chelsey Kamson, BS; and Anupam B. Jena, MD, PhD
Periodic Health Examinations and Missed Opportunities Among Patients Likely Needing Mental Health Care
Ming Tai-Seale, PhD; Laura A. Hatfield, PhD; Caroline J. Wilson, MSc; Cheryl D. Stults, PhD; Thomas G. McGuire, PhD; Lisa C. Diamond, MD; Richard M. Frankel, PhD; Lisa MacLean, MD; Ashley Stone, MPH; and Jennifer Elston Lafata, PhD
Does Medicare Managed Care Reduce Racial/Ethnic Disparities in Diabetes Preventive Care and Healthcare Expenditures?
Elham Mahmoudi, PhD; Wassim Tarraf, PhD; Brianna L. Maroukis, BS; and Helen G. Levy, PhD

Economic Value of Pharmacist-Led Medication Reconciliation for Reducing Medication Errors After Hospital Discharge

Mehdi Najafzadeh, PhD; Jeffrey L. Schnipper, MD, MPH; William H. Shrank, MD, MSHS; Steven Kymes, PhD; Troyen A. Brennan, MD, JD, MPH; and Niteesh K. Choudhry, MD, PhD
The results of this simulation model suggest that implementing a pharmacist-led medication reconciliation intervention at hospital discharge could be cost-saving compared with usual care.
The impact of altering our assumptions about the effectiveness of medication reconciliation are presented in Table 2 and eAppendix Figure B. We found that the initial cost of the intervention would be more than offset by the savings from averted events as long as it reduced medication errors by at least 10%. The results of 1-way sensitivity analysis suggest that the net benefit is most sensitive to the effectiveness of intervention, the proportion of preventable ADEs that result in a rehospitalization or ED visit, and the average length of stay for patients who had an ADE-related rehospitalization (Figure 2).

The results of our probabilistic sensitivity analysis are presented in eAppendix Figure C. We found that the uncertainty around net benefit ranges between –$2 and $577 per patient, with 99% of the simulated trials resulting in a positive net benefit.

Medication Reconciliation for Targeted Patients

The net benefit from targeting medication reconciliation under our base-case assumptions of 70% sensitivity and 70% specificity was $146 savings per patient, which was not superior to the savings from a nontargeted approach ($206 per patient). The impact of alternating our assumptions about sensitivity and specificity of the screening tool are presented in Table 3 and eAppendix Figure D. We found that the net benefit could be as high as $232 per patient, if the specificity and sensitivity of a screening tool were 100%. The net benefit could exceed that which we obtained in the base-case analysis as long as the sensitivity and specificity of the screening tool were at least 90% and 70%, respectively. However, in general, improving the sensitivity of the screening tool has larger impact on net benefits than improving specificity. For example, a screening tool with 100% sensitivity resulted in a net benefit of $222 per patient even if the specificity was only 60%.

The added value of a targeted intervention increased as the effectiveness of the intervention decreased and the cost of intervention increased. For example, if medication reconciliation reduced the risk of medication discrepancy by 20% (rather than 52%) and is more expensive (eg, because it is performed by pharmacists rather than a combination of pharmacist technicians and pharmacists), then a targeted intervention is the preferred approach.

DISCUSSION

Although pharmacist-led medication reconciliation reduces medication errors that commonly occur after hospital discharge, its economic value has not been completely evaluated. We found that this intervention, when performed at the time of hospital discharge, reduced the cost of rehospitalizations and ED visits that resulted from medication discrepancies within 30 days after hospital discharge from $472 per patient to $266. This resulted in a net savings of $206 per patient, after accounting for the cost of the intervention. The magnitude of this savings could be increased if a screening tool, with very high sensitivity and modest specificity, was used to identify and target patients at higher risk of preventable postdischarge ADEs.

More than half of hospitalized patients are estimated to have 1 or more medication discrepancy after hospital discharge.6,8 ADEs resulting from these discrepancies result in the rehospitalization of approximately 4% of discharged patients.6 This highlights the opportunity for interventions that can prevent medication discrepancies to both improve quality and lower costs. Medication reconciliation at the time of hospital discharge involves a bundle of activities including patient counseling and communication with outpatient providers.

Although careful medication reconciliation at hospital discharge can potentially eliminate many discrepancies in discharge medication orders,7,8 it, not surprisingly, has a more limited effect on other types of medication errors that occur during the postdischarge period. For example, patient misunderstanding of their medication regimen could lead to additional discrepancies after discharge.10 Likely for this reason, reconciliation programs that include a telephone follow-up after discharge—along with other, more conventional features such as coordination with physicians, patient education, and transition coaching—have, in general, been more effective.17,34

Our results suggest that despite the use of relatively costly pharmacists and pharmacy technicians, the cost savings from avoided rehospitalizations would more than offset the cost of the intervention. This is consistent with the limited existing cost-effectiveness evidence.35,36 The value of medication reconciliation could be increased if it were preferentially used for individuals at the highest risk of ADEs. This is consistent with the fact that many of the most effective medication reconciliation interventions reported in the literature are those that were targeted interventions, rather than administered to all patients.18,19 Several studies have attempted to develop risk prediction models for hospital readmissions with acceptable accuracy.37,38 However, these models tend to predict risk of all rehospitalizations in the first 30 days after discharge and, therefore, are not necessarily calibrated to predict the risk of readmission specifically resulting from medication errors.1

The estimates of costs and benefits of medication reconciliation in our study assume that those paying for medication reconciliation interventions are the same ones that share the savings from reduced postdischarge HRUs. The extent to which this is true varies tremendously at present; however, it most certainly will increase dramatically in the near future. For example, in 2015, approximately 20% of Medicare payments are based on non–fee-for-service payment models. This share is expected to increase to 30% by 2016 and to 50% in 2018.39 These models included bundled payments, in which providers are at risk for the cost of any readmissions occurring in the 30-to-90-day period after discharge.

Similarly, accountable care organizations put providers at risk for the total cost of care of the populations they serve; these incentives have encouraged providers to target readmissions as an opportunity to improve care and reduce costs. Moreover, Medicare has introduced readmission penalties broadly, and these penalties have led to much greater focus on readmission rates. As a whole, these payment models are critical to creating the business case for hospitals to invest in interventions such as mediation reconciliation.

Factors other than the intervention cost might limit the implementation of medication reconciliation. Pharmacists or other healthcare professionals conducting this intervention must have access to accurate and timely information about inpatient and outpatient mediations. As such, the availability of electronic health records40 that can facilitate obtaining medication records from different points of care will directly affect the feasibility and success of medication reconciliation.41 Patient-specific barriers, such as lower education level and language and other communication barriers, could limit the successful implementation of medication reconciliation in some healthcare settings.

Limitations

Our study should be viewed in light of its limitations. Only a handful of studies have shown the direct impact of medication reconciliation interventions on postdischarge HRU. As a result, our model was based on a chain of events whereby medication discrepancies lead to postdischarge ADEs and HRU, and on studies that show reductions in these discrepancies and in some of the downstream events. Although each link in the chain can be supported by data, we acknowledge that estimates of effectiveness on patient outcomes may be inaccurate. It is reassuring, however, that our results were largely unchanged in the extensive sensitivity analyses we conducted. In addition, the studies we used to derive our base-case estimates were based on specific patient populations, and thus may not be generalizable to all other patient groups or care settings.

CONCLUSIONS

Our study suggests that a pharmacist-led medication reconciliation can be a cost-saving strategy compared with usual care. The net benefit of this intervention could be enhanced using a highly sensitive screening tool for patients at high risk for postdischarge ADEs. Future studies should more directly make the link between interventions and reductions in postdischarge healthcare utilization in order to increase the precision of cost-benefit estimates.

Acknowledgments

The authors would like to thank Sunil Kripalani, MD, MSc, and Kathryn Goggins, MPH, both of Vanderbilt University, for providing unpublished data from the PILL-CVD study that were crucial for developing the current analysis.

Author Affiliations: Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School (MN, NKC).  Division of General Internal Medicine (JLS), Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School. Hospitalist Service (JLS, NKC), Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA; CVS Health (WHS, SK, TAB), Woonsocket, RI.

Source of Funding: This work was supported by an unrestricted grant from CVS Health to Brigham and Women’s Hospital.

Author Disclosures: Drs Shrank, Kymes, and Brennan are employees and stockholders of CVS Health. Dr Choudhry has received a grant from CVS Health. The authors report no other relationship or financial interest with any entity that would pose a conflict of interest with the subject matter of this article. 

Authorship Information: Concept and design (TAB, SK, MN, JLS, WHS); acquisition of data (TAB, NKC, SK, MN, WHS); analysis and interpretation of data (TAB, NKC, SK, MN, JLS, WHS); drafting of the manuscript (NKC, MN); critical revision of the manuscript for important intellectual content (TAB, NKC, SK, MN, JLS, WHS); statistical analysis (MN); obtaining funding (NKC); and supervision (NKC).

Address Correspondence to: Mehdi Najafzadeh, PhD, Division of Pharmacoepidemiology and Pharmacoeconomics, Brigham and Women’s Hospital, Harvard Medical School, 1620 Tremont St, Ste 3030, Boston, MA 02120. E-mail: mnajafzadeh@bwh.harvard.edu.
REFERENCES

1. Pippins JR, Gandhi TK, Hamann C, et al. Classifying and predicting errors of inpatient medication reconciliation. J Gen Intern Med. 2008;23(9):1414-1422. doi: 10.1007/s11606-008-0687-9.

2. von Laue NC, Schwappach DL, Koeck CM. The epidemiology of preventable adverse drug events: a review of the literature. Wien Klin Wochenschr. 2003;115(12):407-415.

3. Kongkaew C, Noyce PR, Ashcroft DM. Hospital admissions associated with adverse drug reactions: a systematic review of prospective observational studies. Ann Pharmacother. 2008;42(7):1017-1025. doi: 10.1345/aph.1L037.

4. Forster AJ, Murff HJ, Peterson JF, Gandhi TK, Bates DW. The incidence and severity of adverse events affecting patients after discharge from the hospital. Ann Intern Med. 2003;138(3):161-167.

5. Forster AJ, Murff HJ, Peterson JF, Gandhi TK, Bates DW. Adverse drug events occurring following hospital discharge. J Gen Intern Med. 2005;20(4):317-323.

6. Kripalani S, Roumie CL, Dalal AK, et al; PILL-CVD (Pharmacist Intervention for Low Literacy in Cardiovascular Disease) Study Group. Effect of a pharmacist intervention on clinically important medication errors after hospital discharge: a randomized trial. Ann Intern Med. 2012;157(1):1-10. doi: 10.7326/0003-4819-157-1-201207030-00003.

7. Mueller SK, Sponsler KC, Kripalani S, Schnipper JL. Hospital-based medication reconciliation practices: a systematic review. Arch Intern Med. 2012;172(14):1057-1069. doi: 10.1001/archinternmed.2012.2246.

8. Lehnbom EC, Stewart MJ, Manias E, Westbrook JI. Impact of medication reconciliation and review on clinical outcomes. Ann Pharmacother. 2014;48(10):1298-1312. doi: 10.1177/1060028014543485.

9. Christensen M, Lundh A. Medication review in hospitalised patients to reduce morbidity and mortality. Cochrane Database Syst Rev. 2013;(2):CD008986. doi: 10.1002/14651858.CD008986.pub2.

10. Schnipper JL, Kirwin JL, Cotugno MC, et al. Role of pharmacist counseling in preventing adverse drug events after hospitalization. Arch Intern Med. 2006;166(5):565-571.

11. 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(21):2003-2010. doi: 10.1001/archinternmed.2009.398.

12. Bolas H, Brookes K, Scott M, McElnay J. Evaluation of a hospital-based community liaison pharmacy service in Northern Ireland. Pharm World Sci. 2004;26(2):114-120.


13. Lisby M, Thomsen A, Nielsen LP, et al. The effect of systematic medication review in elderly patients admitted to an acute ward of internal medicine. Basic Clin Pharmacol Toxicol. 2010;106(5):422-427. doi: 10.1111/j.1742-7843.2009.00511.x.

14. Eggink RN, Lenderink AW, Widdershoven JW, van den Bemt PM. The effect of a clinical pharmacist discharge service on medication discrepancies in patients with heart failure. Pharm World Sci. 2010;32(6):759-766. doi: 10.1007/s11096-010-9433-6.

15. Kwan JL, Lo L, Sampson M, Shojania KG. Medication reconciliation during transitions of care as a patient safety strategy: a systematic review. Ann Intern Med. 2013;158(5, pt 2):397-403. doi: 10.7326/0003-4819-158-5-201303051-00006.

16. Nickerson A, MacKinnon NJ, Roberts N, Saulnier L. Drug-therapy problems, inconsistencies and omissions identified during a medication reconciliation and seamless care service. Healthc Q. 2005;(spec no 8):65-72.

17. Gillespie U, Alassaad A, Henrohn D, et al. A comprehensive pharmacist intervention to reduce morbidity in patients 80 years or older: a randomized controlled trial. Arch Intern Med. 2009;169(9):894-900. doi: 10.1001/archinternmed.2009.71.

18. 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(4):211-218. doi: 10.1002/jhm.427.

19. Pal A, Babbott S, Wilkinson ST. Can the targeted use of a discharge pharmacist significantly decrease 30-day readmissions? Hosp Pharm. 2013;48(5):380-388. doi: 10.1310/hpj4805-380.

20. CPI inflation calculator [2014]. Bureau of Labor Statistics website. http://www.bls.gov/data/inflation_calculator.htm. Accessed June 2, 2015.

21. Bergkvist A, Midlov P, Hoglund P, Larsson L, Bondesson A, Eriksson T. Improved quality in the hospital discharge summary reduces medication errors—LIMM: Landskrona Integrated Medicines Management. Eur J Clin Pharmacol. 2009;65(10):1037-1046. doi: 10.1007/s00228-009-0680-1.

22. Pfuntner A, Wier LM, Steiner C. Costs for hospital stays in the United States, 2011. Healthcare Cost and Utilization Project website. https://www.hcup-us.ahrq.gov/reports/statbriefs/sb168-Hospital-Costs-United-States-2011.jsp. Published December 2013. Accessed June 20, 2015.

23. Williams RM. The costs of visits to emergency departments. N Engl J Med. 1996;334(10):642-646.

24. Medical Expenditure Panel Survey: table 6. emergency room services—mean and median expenses per person with expense and distribution of expenses by source of payment: United States, 2012. Agency for Healthcare Research and Quality website. http://bit.ly/2db645H. Accessed June 1, 2016.

25. Readmissions Reduction Program (HRRP). CMS website. http://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/AcuteInpatientPPS/Readmissions-Reduction-Program.html. Accessed June 20, 2016.

26. Meguerditchian AN, Krotneva S, Reidel K, Huang A, Tamblyn R. Medication reconciliation at admission and discharge: a time and motion study. BMC Health Serv Res. 2013;13:485. doi: 10.1186/1472-6963-13-485.

27. Occupational employment and wages, May 2015. 29-1051 pharmacists. Bureau of Labor Statistics website. http://www.bls.gov/oes/current/oes291051.htm. Updated March 30, 2016. Accessed June 20, 2016.

28. Cooper JB, Lilliston M, Brooks D, Swords B. Experience with a pharmacy technician medication history program. Am J Health Syst Pharm. 2014;71(18):1567-1574. doi: 10.2146/ajhp130590.

29. Hart C, Price C, Graziose G, Grey J. A program using pharmacy technicians to collect medication histories in the emergency department. P T. 2015;40(1):56-61.

30. Johnston R, Saulnier L, Gould O. Best possible medication history in the emergency department: comparing pharmacy technicians and pharmacists. Can J Hosp Pharm. 2010;63(5):359-365.

31. Claxton K, Sculpher M, McCabe C, et al. Probabilistic sensitivity analysis for NICE technology assessment: not an optional extra. Health Econ. 2005;14(4):339-347.

32. Briggs AH. Handling uncertainty in cost-effectiveness models. Pharmacoeconomics. 2000;17(5):479-500.

33. Spiegelhalter DJ, Best NG. Bayesian approaches to multiple sources of evidence and uncertainty in complex cost-effectiveness modelling. Stat Med. 2003;22(23):3687-3709.

34. Jack BW, Chetty VK, Anthony D, et al. A reengineered hospital discharge program to decrease rehospitalization: a randomized trial. Ann Intern Med. 2009;150(3):178-187.

35. Karnon J, Campbell F, Czoski-Murray C. Model-based cost-effectiveness analysis of interventions aimed at preventing medication error at hospital admission (medicines reconciliation). J Eval Clin Pract. 2009;15(2):299-306. doi: 10.1111/j.1365-2753.2008.01000.x.

36. Feldman LS, Costa LL, Feroli ER Jr, et al. Nurse-pharmacist collaboration on medication reconciliation prevents potential harm. J Hosp Med. 2012;7(5):396-401. doi: 10.1002/jhm.1921.

37. Donze J, Aujesky D, Williams D, Schnipper JL. Potentially avoidable 30-day hospital readmissions in medical patients: derivation and validation of a prediction model. JAMA Intern Med. 2013;173(8):632-638. doi: 10.1001/jamainternmed.2013.3023.

38. Kansagara D, Englander H, Salanitro A, et al. Risk prediction models for hospital readmission: a systematic review. JAMA. 2011;306(15):1688-1698. doi: 10.1001/jama.2011.1515.

39. Cutler D. Payment reform is about to become a reality. News @ JAMA website. http://newsatjama.jama.com/2015/02/11/jama-forum-payment-reform-is-about-to-become-a-reality. Published February 11, 2015. Accessed April 30, 2015.

40. Poon EG, Blumenfeld B, Hamann C, et al. Design and implementation of an application and associated services to support interdisciplinary medication reconciliation efforts at an integrated healthcare delivery network. J Am Med Inform Assoc. 2006;13(6):581-592.

41. Schnipper JL, Hamann C, Ndumele CD, et al. Effect of an electronic medication reconciliation application and process redesign on potential adverse drug events: a cluster-randomized trial. Arch Intern Med. 2009;169(8):771-780. doi: 10.1001/archinternmed.2009.51.  
PDF
 
Copyright AJMC 2006-2018 Clinical Care Targeted Communications Group, LLC. All Rights Reserved.
x
Welcome the the new and improved AJMC.com, the premier managed market network. Tell us about yourself so that we can serve you better.
Sign Up
×

Sign In

Not a member? Sign up now!