Journal of Gerontological Nursing

Geropharmacology 

Identifying Potential Medication Discrepancies During Medication Reconciliation in the Post-Acute Long-Term Care Setting

Heather Cook, PharmD; Janee Parson, PharmD; Nicole Brandt, PharmD, MBA, BCGP, BCPP, FASCP

Abstract

Medication reconciliation has been an area with increased focus among transitions of care due to associations with error rates and risk of patient harm. Chart reviews were performed to evaluate the discrepancies between the initial physician order sheet (POS), hospital discharge summary, electronic health record (EHR), health information exchange (HIE), and the patient interview/home medication list. The objectives were to determine which medication information source provided the least number of discrepancies and describe the different types of discrepancies among sources. Of all orders, 30% contained a discrepancy. The average number of discrepancies per medication source per patient included: 5.6 for the hospital discharge summary, 7.6 for the EHR, and 9.6 for the home medication list/interview. The most frequent types of discrepancies included: omission of medication orders between lists (42.7%), additional medications not included on the initial POS (24.6%), and discrepancies in frequency (11.8%). The hospital discharge summary proved to be the medication source that provided the least number of discrepancies, compared to the initial POS. [Journal of Gerontological Nursing, 45(7), 5–10.]

Abstract

Medication reconciliation has been an area with increased focus among transitions of care due to associations with error rates and risk of patient harm. Chart reviews were performed to evaluate the discrepancies between the initial physician order sheet (POS), hospital discharge summary, electronic health record (EHR), health information exchange (HIE), and the patient interview/home medication list. The objectives were to determine which medication information source provided the least number of discrepancies and describe the different types of discrepancies among sources. Of all orders, 30% contained a discrepancy. The average number of discrepancies per medication source per patient included: 5.6 for the hospital discharge summary, 7.6 for the EHR, and 9.6 for the home medication list/interview. The most frequent types of discrepancies included: omission of medication orders between lists (42.7%), additional medications not included on the initial POS (24.6%), and discrepancies in frequency (11.8%). The hospital discharge summary proved to be the medication source that provided the least number of discrepancies, compared to the initial POS. [Journal of Gerontological Nursing, 45(7), 5–10.]

In long-term care (LTC) facilities across the country, error rates of up to 21% have been reported during transitions of care into nursing homes (Tjia et al., 2009). During the medication reconciliation process itself, discharge summaries do not match for more than 50% of LTC admissions, with at least one medication discrepancy in 70% of admissions (Tjia et al., 2009). Along with inaccuracy and the opportunity to administer inappropriate medications, these errors are reported to have a higher risk of harm (Desai, Williams, Greene, Pierson, & Hansen, 2011). These high rates of errors demonstrate the need for improvement and standardization of the medication reconciliation process.

Medication reconciliation is the process of creating the most accurate list possible of all medications a patient is taking—including drug name, dosage, frequency, and route—and comparing that list against the physician's admission, transfer, and/or discharge orders, with the goal of providing correct medications to the patient at all transition points within the hospital.

The Institute for Healthcare Improvement (n.d.b) has recommended medication reconciliation as a major patient safety initiative to reduce adverse drug events. Discrepancies between medication lists are potential causes for adverse drug events and patient harm. For the current study, a medication discrepancy was considered any difference in order elements including strength, dosage, frequency, route of administration, formulation, or indication, as well as duplicate therapy or omissions among different medication lists.

One study conducted at several nursing homes in Maryland demonstrated that 64% to 90% of charts reviewed contained a medication discrepancy (Tong et al., 2017). The study compared the resident's hospital discharge list, medication administration record, and previous charts. Of those discrepancies, the five most common types were: incorrect indication (21%), absence of monitoring parameters (17%), omitted medication name (11%), incorrect dose (10%), and incorrect frequency (8%). The study findings indicated that incomplete transfer of information between care systems increased the likelihood of adverse drug events. Medication errors, adverse drug events related to medication discrepancies, and hospital admissions may be reduced with appropriate medication reconciliation (Tong et al., 2017).

Improvement in the transitions of care process, specifically medication reconciliation, is an important step in improving medication use and safety. Multiple studies have shown the impact of implementing this systematic process to minimize medication errors. Fortunately, this longstanding service is gaining increased attention. The Centers for Medicare & Medicaid Services (CMS) implemented the Improving Medicare Post-Acute Care Transformation Act of 2014 (IMPACT Act), which requires submission of standardized data by LTC hospitals, skilled nursing facilities (SNFs), home health agencies, and inpatient rehabilitation facilities. Standardized measures have been developed and implemented for a quality measure domain, one of which is focused on medication reconciliation, specifically the drug regimen review process (CMS, 2018). The quality measure itself is based on the percentage of care episodes in which a drug regimen review was conducted at the start of care/resumption of care, and timely follow up with a physician occurred each time a potential clinically significant medication issue was identified throughout the care episode. The IMPACT Act will ultimately facilitate quality care and improved outcomes, data element uniformity, improved discharge planning, exchangeability of data, and coordinated care. As of October 1, 2018, the medication reconciliation domain is being used across LTC hospitals, SNFs, home health agencies, and inpatient rehabilitation facilities (CMS, 2017).

Based on a literature review, the number and types of medication discrepancies have been established; however, there is limited data to guide health care practitioners regarding which source of medication data proves to be of higher value when providing medication reconciliation to residents in the post-acute LTC setting. Each source of medication information provides insight into the bigger picture of optimal medication management, providing the right medication, right dose, right frequency, right time to the right patient. What is unknown is the “best” source of medication information, the one that provides the least number of discrepancies upon admission to the nursing home. The purpose of the current study was to evaluate the different sources of medication lists during the medication reconciliation process to identify the “best” list.

Method

The current descriptive study included a retrospective chart review/secondary analysis of 30 residents at a single site, SNF in Baltimore, Maryland over a 3-month period. Institutional Review Board approval was provided by the University of Maryland. Participants included adults 18 or older admitted to the SNF within the study period who were provided pharmacy services. Exclusion criteria were residents admitted from hospitals outside of the affiliated health care system. This exclusion was due to the need to access residents' medication administration records during their prior hospital stay.

The current study evaluated the number and types of medication discrepancies between the initial physician order sheet (POS) upon admission to the SNF, hospital discharge summary, electronic health record (EHR), health information exchange (HIE), the patient interview, and home medication list. Of note, the list of medications documented on the hospital medication administration record within the 24 hours prior to discharge was used as the EHR medication list. In addition, the HIE list was reviewed within the Chesapeake Regional Health Information System for our Patients (CRISP). For the purpose of the current study, a discrepancy was noted for any difference in the name, formulation (i.e., immediate release [IR] vs. extended release [ER]), strength, dose, route of administration, or frequency of the medication order. Discrepancies also included duplications, omissions, and additional medication orders.

The retrospective chart reviews entailed the following approach: all lists were independently compared to the initial POS upon admission to the SNF, as this was considered the baseline medication list. A source comparison tool was used to analyze each list and organize the discrepancies. The tool allowed the user to choose among: no discrepancy; omission of drug; duplication; or discrepancy in the name, formulation, strength, dose, route, frequency, or indication.

To prevent inflation of the number of discrepancies, there were several exceptions, which were excluded from the final discrepancy count. First, missing indications were not included, as the indications for medications were not listed within the majority of discharge summaries and home medication lists. Second, any documented intentional change was not considered a discrepancy, as the difference in orders was justified. Next, automatic therapeutic interchanges (ATIs) were a noted exception. The SNF in which the current study was conducted has a protocol with a LTC pharmacy for ATIs among medications within the same drug class. For example, rosuvastatin is automatically substituted to atorvastatin. While collecting data, these ATIs were noted, but not considered discrepancies. Similarly, ATIs for medications changed to accommodate the hospital's formulary were excluded. Additional medication orders that would be expected to be discontinued upon hospital discharge were not included as discrepancies (e.g., heparin for deep venous thrombus prophylaxis). These orders also included route of administration from intravenous to oral. Differences in formulations, such as tablets and capsules, were also exempt as these are used interchangeably by the pharmacy. Differences in topical formulations (e.g., creams, ointments, lotions) were not considered discrepancies. However, IR versus ER formulations of an oral medication were considered to be discrepancies, as this could potentially cause patient harm if dosed incorrectly. Finally, orders that listed “see instructions” were not considered discrepancies, as they were unable to be verified and it could only be assumed that the initial POS was based on the instructions in the discharge summary. For example, an aspart sliding scale insulin and oxycodone oral tablet order both contained directions to “see instructions.”

Each individual discrepancy was counted to determine the number of discrepancies per list and to describe the frequency of each type of discrepancy. This number determined which source of data provided the least discrepancies. However, to account for duplicate types of discrepancies within the same order, the same type of discrepancy among lists was only counted once when evaluating the number of discrepancies per order. Incomplete orders were counted as one discrepancy for each component they were missing. For example, an order on the initial POS listed as “cranberry 1 CAP PO TID [one capsule orally three times daily] for supplement” was considered to have one discrepancy for missing strength. Duplicate orders were counted as one discrepancy, instead of each order being counted individually. This discrepancy occurred for a set of allopurinol orders containing different strengths and frequencies, as well as for a pair of vitamin D orders with different frequencies. Additional medications listed in the EHR or home medication list that were not continued at admission to the SNF were considered a discrepancy. If these additional orders had the same directions across different lists, they were only counted once. If the two orders were different (i.e., different frequencies), they were listed as separate orders and considered as two discrepancies.

Results

Of the 30 chart reviews, 100% of charts had a hospital discharge summary and EHR available. Only 17 (56.7%) charts had a home medication list/interview available. No valuable medication information was available through CRISP for any residents. Among 1,814 medication orders reviewed, 30% contained a discrepancy (Table 1). The average number of discrepancies per medication source per resident included: 5.6 for the hospital discharge summary, 7.6 for the EHR, and 9.6 for the home medication list/interview (Figure 1). The percentages of different types of discrepancies included: omission of medication orders between lists (42.7%); additional medications not included on the initial POS (24.6%); and discrepancies in frequency (11.8%), strength (8.6%), dose (7.5%), formulation (2.3%), route (2%), duplication (0.4%), and name (0.2%) (Figure 2).

Chart Review Source Results (N = 30)

Table 1:

Chart Review Source Results (N = 30)

Average number of discrepancies per medication list per patient.

Figure 1.

Average number of discrepancies per medication list per patient.

Types and frequencies of medication discrepancies.

Figure 2.

Types and frequencies of medication discrepancies.

Discussion

The hospital discharge summary proved to be the medication source that provided the least number of discrepancies compared to the initial POS. It is important to note that the discrepancies noted are simply potential discrepancies, where differences were noted among the lists. These discrepancies do not account for the possibility of the physician intentionally changing medication orders based on clinical judgement. Although “missing indications” were excluded, the overall number of discrepancies in the current study is slightly higher (30%) compared to previous data (11% to 21% [Desai et al., 2011; Tjia et al., 2009]). Interestingly, the EHR from the hospital admission listed indications only for as-needed medication orders. This is important for nursing staff to discern when to administer (e.g., acetaminophen for mild pain vs. oxycodone for severe pain). Technically, indications should be included with every medication order, including hospital discharge summaries, to justify their appropriateness for continued use.

The most common types of potential medication discrepancies included omission of medications (42.7%) and additional medications not listed on the initial POS (24.6%). These findings reveal the need for increased communication between providers and patients to indicate which medications should be continued or discontinued across care systems. The purpose of the Maryland State Health Information Exchange is to act as a data collection site accessible by providers from different health care entities. During the time of the current study, CRISP provided little to no medication information to assist with medication reconciliation. The Prescription Drug Monitoring Program (PDMP) is used as a database to communicate the pharmacy fill history of controlled medications. For this sample of residents, CRISP only provided fill history (i.e., quantity and days' supply) of controlled medications filled in community pharmacies and was not useful for residents who were admitted to the hospital from a LTC facility. As of July 1, 2018, prescribers must query and review their patients' PDMP data prior to initially prescribing an opioid or benzodiazepine agent and at least every 90 days thereafter (Maryland Department of Health and Mental Hygiene, & Maryland Prescription Drug Monitoring Program, 2016). This database will potentially help providers and pharmacists determine ongoing need of controlled medications.

The National Council for Prescription Drug programs is in the process of creating a request system called “RxHistory Request/Response,” a program designed for providers to request information on medications that were dispensed to a patient within a specific time frame. This process would allow a provider to submit a request to an entity that collects medication data from different sources such as pharmacies, pharmacy benefits managers/claims processors, and HIEs. The entity would then provide a medication list in its response. In the future, pharmacies may be required to report their medication dispensing data, potentially by June 2021 (Russell, 2018). At a local level, House Bill 115, Maryland Health Care Commission—Electronic Prescription Records System—Assessment and Report was passed, which requires the Maryland Health Care Commission to assemble a workgroup to conduct a study that will assess the benefits and feasibility of an electronic system that gives access to patient prescription medication history. The findings and recommendations from the study are expected to be reported on or before January 1, 2020, to the Governor and General Assembly (Maryland Health Care Commission, 2019). Perhaps in the future there will be a mandate to require a real-time updated medication list on CRISP at discharge from all health care facilities to improve continuity of care. Ultimately, further work needs to be done to share medication data with and between the post-acute LTC setting.

Implications for Nursing

Ongoing education regarding common medication discrepancies and insight into changes that can be made to prevent future errors is not only important for the medical team but also patients and their caregiver(s). Incomplete medication reconciliation may be a result of patients' lack of knowledge about their medications and limited access to pharmacy records (Barnsteiner, 2008). When compared to community pharmacy records, 25% of home medications were not recorded on the hospital admission record (Lau, Florax, Porsius, & De Boer, 2001). In addition, on average 1.4 medication orders per patient were altered on admission from the hospital to the nursing home (Boockvar et al., 2004). These findings suggest that patients should be encouraged to be active participants in creating their medication action plan and providers should emphasize indications for each drug. Patients should also be encouraged to carry an updated medication list to improve continuity of care across health care settings. Ideally, the pharmacist can be more involved in resolving this gap in knowledge; however, nurses and clinical nurse educators may also be involved in promoting complete and accurate medication reconciliation, as a significant portion of their time is spent in clinical practice support (Coffey & White, 2019).

Developing a standardized medication reconciliation process is critical for all members of the team. Studies have shown that improved accuracy and even decreased mortality are associated when pharmacists complete medication reconciliation compared to other health care professionals (Splawski & Minger, 2016). Standardization of protocols and procedures to complete medication reconciliation, as well as engagement of the patient/care partner in the process, may decrease the number of medication errors upon admission to health care facilities. The World Health Organization (2014) has created a standard operating protocol that describes best practices for completing medication reconciliation in efforts to decrease medication errors and improve outcomes. Furthermore, the Institute for Healthcare Improvement (n.d.a) has released the MATCH (Medications at Transitions and Clinical Handoffs) Toolkit for Medication Reconciliation to guide providers in developing a medication reconciliation process at their clinical practice sites.

Conclusion

The current study findings suggest that more work needs to be done with respect to conducting medication reconciliation to improve workflow process. The results may be of benefit for all involved in the post-acute LTC setting when completing patient medication lists and give a better sense of the differences between sources of medication reconciliation. Although the hospital discharge summary proved to be the source with the least number of discrepancies, it is important to continually use sound clinical judgement to determine if medications are appropriate to be continued and discontinued when an individual is admitted to a post-acute LTC setting. Medication reconciliation is a time-consuming puzzle that attempts to solve the question of what medications the resident is currently taking and what medications he/she should continue. Hopefully, medication discrepancies can be identified and resolved faster and more effectively with emerging resources (e.g., HIE, artificial intelligence).

References

Chart Review Source Results (N = 30)

Variablen (%)
Charts reviewed with two sources: hospital discharge summary, EHR30 (100)
Charts reviewed with three sources: hospital discharge summary, EHR, patient interview17 (56.7)
Charts reviewed with CRISP medication list available0
Medication orders received1,814
Medication discrepancies558 (30)
Authors

Dr. Cook is PGY1 Pharmacy Resident, Medstar Union Memorial Hospital, Dr. Parson is Lead Consultant Pharmacist, Remedi SeniorCare Mid Atlantic Region, and Dr. Brandt is Executive Director, Peter Lamy Center on Drug Therapy and Aging, and Professor, University of Maryland School of Pharmacy, Baltimore, Maryland.

The authors have disclosed no potential conflicts of interest, financial or otherwise.

Address correspondence to Heather Cook, PharmD, PGY1 Pharmacy Resident, Medstar Union Memorial Hospital, 201 E. University Parkway, Baltimore, MD 21218; e-mail: heather.k.cook@medstar.net.

10.3928/00989134-20190612-02

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