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Medication reconciliation in hemodialysis patients.

Background

Medication reconciliation is an effective process to reduce adverse drug events (ADEs) and harm associated with the loss of medication information as patients transfer between health care settings. Medication reconciliation is a three-step process that verifies medication use, identifies variances and rectifies medication errors at interfaces of care (Vira, Colquhoun, & Etchells, 2006). It may prevent up to 70% of all potential errors and 15% of all adverse drug events (www.saferhealthcarenow.ca/).

A recent Canadian study found that more than one in nine emergency department visits are due to drug-related adverse events (Zed et al., 2008). It is estimated that medication errors cause more than 7,000 deaths per year in the United States. Medication errors and patient harm can result from inaccurate or incomplete medication histories that are used as the basis for medication regimens (Lau, Florax, Porsius, & De Boer, 2000).

Approximately 46% to 56% of all medication errors occur when patients are admitted to hospital, transferred to another unit, or discharged (Barnsteiner, 2005). Studies have shown that pharmacist-acquired medication histories are more efficient, accurate and contain fewer medical errors compared to conventional nurse/physician/delegate medication histories, thereby promoting patient safety (Bond, Raehl, & Franke, 2002; Gleason, Groszek, Sullivan, Rooney, Barnard, & Noskin, 2004; Nester, & Hale, 2002).

Patients with end stage renal disease (ESRD) are at a high risk of experiencing drug-related problems (DRPs) because they take many medications, have multiple comorbidities, and require frequent medication changes. Most medication reconciliation studies have focused on the acute care setting (admission and discharge from hospital). Because ESRD patients are a high-risk population, we decided to evaluate the potential impact of medication reconciliation and optimization in the ambulatory care setting at the time of patient transfer from an in-centre hemodialysis unit to a satellite hemodialysis unit. We determined the number of unintended medication variances and the type of variance, as well as the action taken by the physician or designate to rectify each variance.

Methods

This prospective study was conducted at London Health Sciences Centre (LHSC), a tertiary care hospital. The LHSC renal program encompasses all patients within southwestern Ontario with end stage renal disease (ESRD), approximately 550 hemodialysis and 110 peritoneal dialysis patients. All hemodialysis patients transferring to a satellite dialysis unit were consecutively recruited over a 12-week period from March 17 to May 23 2007 (n=20). All patients had to be able to give verbal consent. There were no additional inclusion or exclusion criteria.

Patients initiate hemodialysis at an in-centre (between 54 and 150 patients per dialysis unit). A lower nurse-to-patient ratio exists (1:3 versus 1:2) and physicians and/or nurse practitioners are available at all times. This, however, requires patients who do not live in London to drive great distances from their home three times per week for hemodialysis treatments. Once a patient is stabilized on hemodialysis, and a satellite hemodialysis unit exists closer to their home, they can be assessed for transfer to this unit if a spot is available. This assessment involves a minimum of three hemodialysis treatments to be performed at the London Regional Dialysis Centre. Transfer medication orders are written for the patient based on the patient's in-centre dialysis medication record. During this assessment period, the patient is seen by nursing, dietary and pharmacy. The pharmacist performs a comprehensive medication history and ensures that all the transfer orders match what the patient is actually taking. Any discrepancies are corrected and suggestions to optimize pharmacotherapy are made at this time.

The study pharmacist conducted a comprehensive medication history on each study participant as per usual practice. The patients' medication orders were compared with the patients' actual medication use based on medication vials, patient/caregiver interviews and outpatient pharmacy records, and/or family physicians were contacted if necessary. A variance could include: an omission of medication(s), extra medication(s) or discrepancies in dose, frequency or dosage form. Variances in prescription medications, acetylsalicylic acid or any other physician-prescribed non-prescription medications were included. All variances were described as intended or unintended. If a variance could lead to harm (death, permanent or temporary disability, admission to hospital or the need for additional treatment or monitoring), it was recorded. All variances were reviewed with the attending nephrologist or designate (i.e., nurse practitioner) and any changes made were at the discretion of the nephrologist/designate and new medication orders written if necessary.

The proportion of patients with at least one unintended medication variance was calculated, as well as the mean number of unintended variances per patient. The type of variance was recorded, as well as the action taken by the physician or designate. The number of suggestions to optimize pharmacotherapy and the acceptance rate of these suggestions were recorded.

Ethics approval from the hospital's ethics committee and verbal consent was obtained from all study participants.

Results

Twenty patients were assessed for transfer over the 12-week study period. Nineteen patients were included in the study over the 12-week period as one patient had to be excluded because they were mentally challenged and unable to give verbal consent. Patient characteristics are summarized in Table One. The main findings are summarized in Table Two. Overall, 15 patients (78.8%) had at least one unintended medication variance. The mean number of unintended variances was 3.3 per patient and the median was three variances per patient. The mean number of unintended variances increased to 4.1 per patient when only the patients with unintended variances (n=15) were examined. One unintended variance led to harm.
Table One. Characteristics of study population (n=19)

% women (n) 42.1% (8)
Mean [+ or -] SD age (years) 64.58 [+ or -] 11.4
Mean [+ or -] SD duration on dialysis (years) 1.23 [+ or -] 2.1
Mean [+ or -] SD # medications on transfer 14.74 [+ or -] 4.3
% cause of ESRD (n)
Diabetes mellitus 31.6% (6)
Hypertension 15.8% (3)
Glomerular nephritis 5.3% (1)
Other 47.4% (9)

Table Two. Summary findings for unintended variances

% of patients with at least one 78.9% (15)
unintended variance (n)

Mean # of unintended variances 3.3 (3.36, 1.64 to 4.88)
per patient (SD, 95% CI) (n=19)

Mean # of unintended variances in patients 4.1 (3.3, 2.32 to 5.94)
with variances (SD, 95% CI) (n=15)
% of variances leading to harm (n) 5.3 (1)


More than 50% of patients had three or more unintended variances and one patient had 11 unintended variances (see Table Three). The majority of unintended variances (56%) were caused by the physician/NP omitting an order for medication that the patient was taking. The most common response to the unintended variances was to order a medication (55.3%). MD response was lost to follow-up on one patient who had nine unintended variances (total number of unintended variances was 62, but responses were only obtained in 53 cases due to the loss of data regarding the MD response to these nine unintended variances). In addition to performing medication reconciliation, recommendations to optimize pharmacotherapy were made. These results are summarized in Table Four. In the majority of patients, a recommendation to optimize therapy was made. The mean number of recommendations per patient was two (SD 1.5, 95% CI 1.28 to 2.72). The recommendation acceptance rate was 79%.
Table Three. Types of unintended medication variances

Omission of medication (n) 56% (35)
Wrong dose/route/frequency (n) 34% (21)
Additional medication 9.6% (6)
unintentionally ordered (n)
Total # of unintended variances (n) 62

Table Four. MD or designate response to unintended variances

Order new medication 52.8% (28)
Discontinue/hold medication 18.9% (10)
Change dose/route/frequency 24.5% (3)
Restart medication 1.9% (1)
No changes made 1.9% (1)
Total 53

Table Five. Number of unintended medication variances

# of unintended variances # of patients (n=19) %

0 4 21.1
1 3 15.8
2 2 10.5
3 4 21.1
4 2 10.5
5 1 5.3
9 1 5.3
10 1 5.3
11 1 5.3

Table Six. Summary of recommendations for therapy optimization

 Total sample (n=19)

# Recommendations to optimize therapy 38

Mean # of recommendations per patient 2 (1.5,
(SD, 95% CI) 1.28 to 2.72)

# Recommendations accepted 30 (79%)

Mean # of recommendations 1.58 (1.3,
accepted per patient 0.95 to 2.21)


Discussion

We found that 78.9% of patients, upon transfer to a satellite dialysis unit, experienced at least one unintended medication variance, including one patient who had 11 unintended variances. The majority of unintended variances (56%) were caused by the physician/NP omitting an order for a medication that the patient was taking. Most patients also had a recommendation to optimize therapy. Examples of optimization include: antiplatelet therapy in diabetics or patients with a high risk of experiencing a cardiovascular event, discontinuation of diuretics in anuric patients, hepatitis B vaccination, alternative phosphate binders for patients experiencing side effects, etc. The mean number of recommendations per patient was two (SD 1.5, 95% CI 1.28 to 2.72) and the recommendation acceptance rate was 79%.

Our results are consistent with previous studies reporting medication errors occurring commonly at points of transfer (Vira, Colquhoun, & Etchells, 2006). In the ambulatory care setting, the Bedell et al. study reported a 76% discrepancy rate. The most common discrepancy was that a patient was taking a medication not recorded in the patient's chart (Bedell et al., 2000). A previous study in hemodialysis patients found that 60% of patients had at least one medication discrepancy when a medication review was completed (Manley, Drayer, McClaran, Bender, & Muther, 2003). This study also cited that patients were at increased risk for experiencing adverse drug events if they had one or more of the following risk factors: more than three concurrent diseases, a drug regimen that is changed four or more times in a year, five or more prescribed medications, 12 or more drug doses/day, history of non-adherence and presence of drugs that require therapeutic monitoring. Impaired renal function is also a risk factor for experiencing adverse drug events (Manley, Drayer, McClaran, Bender, & Muther, 2003). Our dialysis patient population has many of the aforementioned risk factors and, specifically in our study, patients were on an average of 15 medications.

Our study has several limitations, mainly its small sample size. It is a single centre study and there may be a bias in detecting medication errors, as the same study pharmacist performed all the medication histories.

Our dialysis medication lists are thought to be up to date and accurate, and are used to prescribe new medications for patients and to order their admission medications when they are admitted to hospital. When inaccurate lists are used, errors are more likely to occur, possibly resulting in harm to the patient.

Based on these findings, we would like to expand the medication reconciliation services to all hemodialysis patients. Our recommendation would be to perform medication reconciliation every three months. A pharmacist would conduct the process every six months and the patient's primary nurse would perform it at the other six-month intervals. Medication lists are a dynamic, but with increased surveillance by pharmacy and nursing, improved accuracy should result in better patient care and safety. In institutions without dedicated pharmacy resources, nursing can take the lead in designing and implementing systems to record medications and changes in them (Barnsteiner, 2005).

Future research with rigorous methods needs to be performed to establish the clear impact of medication reconciliation on reducing the incidence of medication error and harm to the patient. In a time of scarce health care resources, we do not know who would benefit the most from medication reconciliation and would like to perform this process in areas where it would have the most proven benefit.

In summary, hemodialysis patients are at high risk of experiencing DRPs because they take many medications, have multiple comorbidities and require frequent medication changes. In this small study, medication reconciliation was effective at identifying and rectifying medication errors and optimizing pharmacotherapy at the time of transfer from an in-centre hemodialysis unit to a satellite dialysis unit.

Acknowledgements

The author received the Canadian Society of Hospital Pharmacists (CSHP) Scott Walker Research Grant for this study.

References

Barnsteiner, J.H. (2005). Medication reconciliation. American Journal of Nursing, 105(3, Suppl.), 31-36.

Bedell, S.E., Jabbour, S., Goldberg,R., Glaser, H., Gobble, S., Young-Xu, Y., et al. (2000). Discrepancies in the use of medications: Their extent and predictors in an outpatient practice. Archives of Internal Medicine, 160(14), 2129-2134.

Bond, C.A., Raehl, C.L., & Franke, T. (2002). Clinical pharmacy services, hospital pharmacy staffing and medication errors in United States hospitals. Pharmacotherapy, 22, 134-147.

Gleason, K.M., Groszek, J.M., Sullivan, C., Rooney, D., Barnard, C., & Noskin, G.A. (2004). Reconciliation of discrepancies in medication histories and admission orders of newly hospitalized patients. American Journal of Health-System Pharmacists, 61, 1689-95.

Lau, H.S., Florax, C., Porsius, A.J., & De Boer, A. (2000). The completeness of medication histories in hospital medical records of patients admitted to general internal medicine wards. British Journal of Clinicalof Clinical Pharmacology Jun, 49(6), 597-603.

Manley, H.J., Drayer, D.K., McClaran, M., Bender, W., & Muther, R.S. (2003). Drug record discrepancies in an outpatient electronic medical record: Frequency, type and potential impact on patient care at a hemodialysis center. Pharmacotherapy, 23(2), 231-239.

Nester, T.M., & Hale, L.S. (2002). Effectiveness of a pharmacistacquired medication history in promoting patient safety. American Journal of Health-System Pharmacists, 59, 2221-2225.

Ong, S., Fernandes, O., Cesta, A., & Bajac, J. (2006). Drug-related problems on hospital admission: Relationship to medication information transfer. Annals of Pharmacotherapy, 40, 408-413.

Saferhealthcarenow.ca (2008). Med Rec (Long term care). Retrieved June 17, 2008, from http://www.saferhealthcarenow.ca/

Vira, T., Colquhoun, M., & Etchells, E. (2006). Reconcilable differences: Correcting medication errors at hospital admission and discharge. Quality Safety Health Care, Apr,15(2), 122-126.

Zed, P., Abu-Laban, R., Balen, R., Loewen, P., Hohl, C., Brubacher, J., et al. (2008). Incidence, severity and preventability of medication-related visits to the emergency department: A prospective study. Canadian Medical Association Journal, 178(12), 1563-1569.

By Seadna Ledger, BScPhm, ACPR, and Gail Choma, BScPhm, ACPR

Seadna Ledger BScPhm, ACPR, is Renal Pharmacist, London Heath Sciences Centre, London, ON

Gail Choma BScPhm, ACPR, is Staff Pharmacist, London Health Sciences Centre, London, ON

Address correspondence to: Seadna Ledger, London Health Sciences Centre, 375 South St., London, ON N6A 4G5 E-mail: seadna.ledger@lhsc.on.ca

Submitted for publication: July 5, 2008.

Accepted for publication in revised form: November 3, 2008.
COPYRIGHT 2008 Canadian Association of Nephrology Nurses & Technologists
No portion of this article can be reproduced without the express written permission from the copyright holder.
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Author:Ledger, Seadna; Choma, Gail
Publication:CANNT Journal
Article Type:Clinical report
Geographic Code:1CANA
Date:Oct 1, 2008
Words:2423
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