Int J Clin Pharm DOI 10.1007/s11096-013-9875-8
RESEARCH ARTICLE
Medication reconciliation by a pharmacy technician in a mental health assessment unit Kay Brownlie • Carl Schneider • Roger Culliford Chris Fox • Alexis Boukouvalas • Cathy Willan • Ian D. Maidment
•
Received: 2 August 2013 / Accepted: 24 October 2013 Koninklijke Nederlandse Maatschappij ter bevordering der Pharmacie 2013
Abstract Background Medication discrepancies are common when patients cross organisational boundaries. However, little is known about the frequency of discrepancies within mental health and the efficacy of interventions to reduce discrepancies. Objective To evaluate the impact of a pharmacy-led reconciliation service on medication discrepancies on admissions to a secondary care mental health trust. Setting In-patient mental health services. Methods Prospective evaluation of pharmacy technician led medication reconciliation for admissions to a UK Mental Health NHS Trust. From March to June 2012 information on any unintentional discrepancies (dose, frequency and name of medication); patient demographics; and type and cause of the discrepancy was collected. The potential for harm was assessed based on two scenarios; the discrepancy was continued into primary care, and the discrepancy was corrected during admission. Logistic regression identified factors associated with discrepancies. Main outcome measure Mean number of discrepancies per admission corrected by the pharmacy technician. Results
Unintentional medication discrepancies occurred in 212 of 377 admissions (56.2 %). Discrepancies involving 569 medicines (mean 1.5 medicines per admission) were corrected. The most common discrepancy was omission (n = 464). Severity was assessed for 114 discrepancies. If the discrepancy was corrected within 16 days the potential harm was minor in 71 (62.3 %) cases and moderate in 43 (37.7 %) cases whereas if the discrepancy was not corrected the potential harm was minor in 27 (23.7 %) cases and moderate in 87 (76.3 %) cases. Discrepancies were associated with both age and number of medications; the stronger association was age. Conclusions Medication discrepancies are common within mental health services with potentially significant consequences for patients. Trained pharmacy technicians are able to reduce the frequency of discrepancies, improving safety.
K. Brownlie R. Culliford Basildon Mental Health Unit, South Essex Partnership University NHS Foundation Trust, Nether Mayne, Basildon, Essex SS16 5NL, UK
A. Boukouvalas Aston University, Aston Triangle B4 7ET, UK
C. Schneider Faculty of Pharmacy, The University of Sydney, Sydney, NSW 2006, Australia C. Fox Department of Psychological Sciences, Faculty of Medicine and Health Sciences, Norwich Medical School, University of East Anglia, Norwich Research Park, Norwich NR4 7TJ, UK C. Fox Julian Hospital, Norfolk and Suffolk NHS Foundation Trust, Norwich NR2 3TD, UK
Keywords Continuity of care Medication reconciliation Medication safety Mental health United Kingdom
C. Willan Rochford Hospital, South Essex Partnership University NHS Foundation Trust, Union Lane, Rochford SS4 1RB, UK I. D. Maidment (&) Aston Research Centre for Healthy Ageing (ARCHA), Aston University, Aston Triangle B4 7ET, UK e-mail: [email protected] I. D. Maidment Pharmacy Department, Life and Health Sciences School, Aston University, Aston Triangle B4 7ET, UK
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Int J Clin Pharm
Impacts on practice
Aim of the study
•
To evaluate the impact of a pharmacy-led medication reconciliation service on medication discrepancies on admission to a secondary care mental health trust. Key objectives were:
•
• •
Medication discrepancies are common in mental health services putting patients at a significant risk of harm. Certain parts of society, particularly older people taking many different medicines, appear to be at a particular risk of medication reconciliation errors. Medication reconciliation should be a core pharmacy service. Specially trained pharmacy technicians represent a cost-effective way of reconciling medication.
– – –
to obtain quantitative data on the prevalence of discrepancies and impact of the service; to identify the types of medicines involved, the type of discrepancy and risk factors for a discrepancy; to identify the potential for harm if the discrepancies were not corrected.
Introduction The American Institute for Healthcare Improvement defines medication reconciliation as ‘‘the process of creating the most accurate list possible of all medicines a patient is taking, including drug name, frequency, dose and route, and comparing that list against the physician’s admission, transfer, and/or discharge order with the goal of providing correct medications to the patient at all transition points within the organisation’’ [1]. Unfortunately, discrepancies in medication reconciliation, resulting in medication error, are a common problem when patients move between healthcare organisations [2]. Medication discrepancies, on admission to a secondary care unit, may follow the patient throughout the admission and post-discharge, and therefore have long-term consequences [3]. Obtaining an accurate medication history and medication reconciliation may be particularly difficult during an acute psychiatric illness due to associated cognitive impairment [4–6]. There is, however, a lack of research on the incidence of, and interventions to reduce, medication discrepancies within mental health services [2, 7]. One study, involving 43 patients, within a Mental Health Trust found that discrepancies in the medication record in the medical notes occurred in 43 % of admissions, of which 18 % were judged to be potentially harmful; however, this study did not assess discrepancies on the drug admission chart [8]. A more recent study on two medical wards found a medication reconciliation discrepancy in 47 % (95 % CI 43–51 %) of 670 admitted patients [9]. Pharmacy-led medication reconciliation is designed to reduce the risk of medication discrepancies. Recently a systematic review identified the lack of data and the need for further research on medication reconciliation and whilst there is a limited literature on pharmacy technicians undertaking reconciliation, as far as we are aware there are no studies in a mental health setting [10–12].
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Methods Setting and participants This prospective evaluation was undertaken within South Essex Partnership University NHS Foundation Trust (SEPT) Assessment Unit, based at Basildon Mental Health Unit (MHU) for a 3 month period from 13th March to 8th June 2012. SEPT provides health and social care services for people with mental health problems and learning disabilities. People aged over 18 living within South Essex, who develop mental health problems and people with mental health problems in crisis requiring in-patient admission would be routinely admitted to the 20-bedded assessment unit. The Trust provides services to six local authorities (LAs) in South Essex; two of which—Southend-on-Sea and Thurrock—are Unitary Authorities. The total population is approximately 750,000. The percentage of the population from black and minority ethnic (BME) groups ranges between 6.9 and 13.3 %. Levels of affluence vary within South Essex. Brentwood, Castle-Point and Rochford LAs are among the most affluent in the UK, whereas Southend, Thurrock and Basildon are more deprived than the national average, and also contain pockets of marked deprivation [13]. This project was approved by the clinical governance committee within SEPT; ethics committee approval was not required because the project was an evaluation of an existing service. The results were anonymised and service users were not identifiable to anyone in the team (IM, CS) conducting the secondary analysis of the results for publication. Method of medication reconciliation The method used for medication reconciliation was based upon the appropriate Trust policy and procedure, and in
Int J Clin Pharm
line with National Patient Safety Agency (NPSA) guidance [2]. Briefly, on a daily basis, every weekday, a pharmacy medicines management technician (n = 3) attends the assessment unit and reconciles medication for every new admission. A triage system was operated with nursing staff identifying priority cases. A variety of sources, as listed below, were used, because frequently medication was prescribed by clinicians other than the GP, for example antipsychotic depot injections from secondary care prescribers, and medication may have been recently changed by the outpatient clinic or home treatment team. First, information was gathered from the secondary care notes and any patient’s own drugs (PODs). Second, the GP surgery was contacted and a current list of medication requested. Third, if required and informed by the initial information obtained, other sources including the family, historical notes, community pharmacy, community mental health services, Drug and Alcohol services and other healthcare organisations were consulted. Fourth, the patient was consulted unless advised by nursing staff, because for example the patient was too unwell. The patient was also asked about any other medication taken including over-thecounter medicines (OTC), herbal remedies and illicit substances. The summary of medication used at the time of admission was documented on a standard proforma and compared to the in-patient prescription. The pharmacy medicines management technician discussed any discrepancy with the clinical team to confirm whether or not the discrepancy was intentional or unintentional. If the discrepancy was unintentional the medication chart was modified by a prescribing doctor and the discrepancy was recorded on the data collection form. If the discrepancy was intentional no further action was taken, and the discrepancy was not recorded on the data collection form. Data collection A data collection form was developed to collect the medication reconciliation activity of the pharmacy technician enabling the service evaluation. Based upon the NPSA patient safety criteria the following data fields were collected [14]. 1. 2. 3. 4.
A free text qualitative description of the discrepancy (based on NPSA data field ID05). Any causes or contributing factors (ID06). Details of the medication involved (MI04–MI09). Discrepancy categories were developed using the NPSA patient safety incident classification data fields MI02 and MI03 [14] and supplemented, to ensure a comprehensive categorisation, with previously developed classifications [12, 15]. The proposed list was
discussed with and subsequently modified following discussions with clinical pharmacy staff again to ensure a comprehensive list. The form was piloted, by two pharmacy medicines management technicians, within the Assessment Unit and subsequently modified to improve usability. The form was completed by the technician on the unit as soon as the discrepancy was identified and confirmed as unintentional. Assessment of harm The potential impact on patient care was assessed in a random sample of 20 % of all discrepancies using validated methodology; the sample size of 20 % was chosen based upon the methods of similar studies [16, 17]. Four clinicians including specialist pharmacists, an acute care pharmacist and a consultant psychiatrist rated the potential for harm for each discrepancy using a visual analogue scale with 0 representing no harm and 10 representing death. To test whether the four clinicians rated the severity consistently we performed a two-way repeated measure ANOVA test (PRISM v6.0). Based on previous research assessors were asked to consider two different scenarios. First, standard care—no pharmaceutical medication reconciliation—would not have corrected the discrepancy and the discrepancy would have been continued into primary care post-discharge; this is generally the accepted approach [3, 18]. Recent research has identified that standard care may correct discrepancies during the admission and the second scenario assumed that the discrepancy was corrected at the mid-point of the admission, 16 days (based on a mean length of stay of 32 days; [9, 19]). Based on the assessors’ mean score the discrepancy was classed as minor (score \3), moderate (score 3–7) or severe (score [7). Different medication class The medication class classification was based on the primary BNF indication with the exception of anti-convulsants, which due to their common use in mental health were classed as mood stabilisers. One member of the team classified all the medicines (Ian Maidment—IM); this classification was independently checked (Carl Schneider—CS) with any disagreements resolved by consensus. Regression analysis of medication reconciliation discrepancies A logistic regression model was employed to assess which factors may affect the occurrence of reconciliation
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Int J Clin Pharm Table 1 Demographic characteristics of people admitted to assessment unit
Mean age (±SD) and range
Gender
Mean gap in days between admissions and medication reconciliation (±SD)
Mean total number of medicines taken (±SD)
44.5 (±17.2)
193 male
1.22 (±0.86)
4.65 (±3.19)
18–91
188 female 1 not recorded
Table 2 Different medication class Medication class including mental health sub-category
Mental health subcategories n (% of total)
Total mental health
Table 3 Discrepancy type n (% of total)
Type of discrepancy
N
% of total discrepencies
275 (48.3)
Medicine not prescribed that should have been prescribed (omission)
464
77.2
Anti-depressants
111 (19.5)
Anti-psychotics
74 (13.0)
Wrong/unclear dosage
42
7.0
26 (4.6)
Wrong/unclear strength Wrong/unclear formulation
30 19
5.0 3.2
Benzodiazepines
23 (4.0)
Wrong/unclear frequency
19
3.2
Alcohol dependence
17 (3.0)
8
1.3
Anti-muscarinics
13 (2.3)
Additional medicine—something prescribed that should not have been prescribed
Other mental health medicines
11 (1.9)
Wrong/unclear name of drug or medicine
4
0.7
Mood stabilisers/anticonvulsants
Other
3
0.5
Cardiovascular
63 (11.1)
Wrong/unclear route
1
0.2
Endocrine
53 (9.3)
Clerical error (e.g. script not signed or dated)
1
0.2
Respiratory
50 (8.8)
Unable to be determined
10
1.7
Gastro-intestinal tract
47 (8.3)
Total number of discrepancies
Analgesics
33 (5.8)
Other Overall total
48 (8.4) 569
discrepancies. This model was selected after an empirical comparison to more complex statistical models, which were shown to offer no advantage, and validated by evaluating the average misclassification rate, defined as the proportion of cases where the occurrence of a discrepancy error was misclassified [20]. A Bayesian approach, that incorporates uncertainty in the factors associated with a discrepancy and the logistic model, was used to ensure a robust analysis. The discrepancy error response for the logistic regression model was coded with the 0 label signifying a discrepancy and 1 that no discrepancies were found. All cases with missing values were removed, reducing the available data size to 373 cases.
Results Over the 3 month period there were 382 admissions to the assessment unit. See Table 1 for the demographic characteristics of the people admitted to the unit. An unintentional medication discrepancy was recorded in 212 of 377 (56.2 %) admissions reconciled (in five cases
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601
the patient was discharged before the medication could be reconciled). Three different pharmacy technicians reconciled the medication and mean time for each admission was 16.0 min (range 5–60 min; SD ± 7.2). The technicians corrected discrepancies involving 569 medicines (mean 1.5 medicines per admission). These medicines are broken down into different classes in Table 2. Of the endocrine medicines 21 were medicines for diabetes (insulin or oral anti-diabetic medicines). In total there were 601 different discrepancies. This is higher than the number of medicines, because some medicines had more than one discrepancy e.g. wrong strength and unclear formulation. The different types of discrepancies are described in Table 3—the most common discrepancy was omission. The data on the cause of the discrepancy is not reported, because in the majority of cases the cause of the discrepancy was unclear. The severity of the discrepancy was assessed in 114 medicines (20 %; 114/569). If the discrepancy was corrected within 16 days the potential harm was rated as minor in 71 (62.3 %) cases and moderate in 43 (37.7 %) cases. If the discrepancy was continued into primary care the potential harm was rated minor in 27 (23.7 %) cases and moderate in 87 (76.3 %) cases. We found statistically significant differences between the severity assessments by
Int J Clin Pharm Table 4 Regression analysis of factors associated with medication reconciliation discrepancies Parameter
Median
CI (95 %)
Intercept (constant)
-0.3
[-0.52, -0.09]
Age
-0.47
Sex
0.11
[-0.11, 0.33]
Gap (days) between admission and med rec
0.27
[0.03, 0.50]
Total number meds
-0.32
[-0.71, -0.23]
[-0.59, -0.05]
the raters indicating that the rating was conducted independently by the 4 raters (p \ 0.01). Results of regression analysis of medication reconciliation discrepancies The median and 95 % CIs of the coefficients, corresponding to effects associated with a discrepancy, are described in Table 4. A coefficient of zero indicates no effect; the factor has no association with a discrepancy, a negative value indicates a positive correlation with a discrepancy and a positive value a negative correlation. Gender had no significant effect on the likelihood of a discrepancy. Both age and the number of medications have negative coefficients and therefore increasing age and number of medications predict a reconciliation discrepancy, with age the stronger predictor. The gap between admission and medication reconciliation has a positive coefficient indicating that the longer the gap, the less likely that a discrepancy is found, however, the effect is relatively small compared to age.
Discussion This evaluation found a mean discrepancy rate of 1.5 medicines per admission. This is similar to other studies, which have identified mean discrepancy rates of 0.3–2.91 medicines per admission [3, 21–24]. Over fifty percent (56.2 %) of admissions had a medication discrepancy; this is comparable to other studies, for example 53.6 % [22] and 35.9 % [23]. Finally, similar to other studies, errors of omission were amongst the most frequent discrepancy; 77.2 % of all discrepancies, which compares with 71 and 48.9 % of discrepancies in one UK [25] and one USA study [23], respectively. To understand the impact of the intervention we need to understand the potential real-life harm of the discrepancies [26]. A previous study found that 63 % of non-reconciled medicines had the potential to cause moderate harm and 2 % severe harm [17]. However, this study assumed, like
other previous studies, that the discrepancies are never corrected and we also modelled for the possibility that the discrepancy will be detected by standard care [9, 26]. If the discrepancies were continued into primary care, we found 76.3 % of discrepancies were associated with moderate potential harm, whereas if the discrepancy was detected mid-way through the admission only 37.7 % of cases were associated with moderate harm. Age, polypharmacy and the gap between admission and medication reconciliation correlate with a discrepancy. The likelihood of a discrepancy decreases as the gap between admission and medicine reconciliation increases potentially indicating that standard care does, over time, detect and correct discrepancies. Both polypharmacy and particularly increasing age predicted a medication reconciliation discrepancy. The impact of polypharmacy on medication reconciliation discrepancies has been previously welldescribed [9, 17, 23]. Whilst, this study found that the risk of discrepancies is higher in the elderly, overall the literature on any association between age and the risk of a discrepancy is conflicting. Some studies found no association [9, 17] whereas other studies found that age increased [23] and conversely decreased [15] the risk of a potentially harmful discrepancy. The prevalence of dementia and associated cognitive impairment rises exponentially with age and this cognitive impairment may limit the active involvement of the person with dementia in the reconciliation process, increasing the risk of a discrepancy [4, 27]. Therefore, age could potentially be a surrogate for cognitive impairment. Although, most older people admitted to the mental health unit are likely to suffer from cognitive impairment or dementia, the presence of dementia or cognitive impairment was not collected and could not be included in the regression analysis model. Therefore, a future study should investigate whether cognitive impairment does increase the risk of a medication reconciliation discrepancy. On a more immediate and practical basis, these results suggest medication reconciliation should prioritise older people and people on multiple medications. This evaluation adds to the evidence that medication reconciliation can be carried out by a suitably trained pharmacy technician [11, 12]. It took a mean of 16.0 min per admission for the pharmacy technician to take the medication history and reconcile any discrepancies. Medicines reconciliation is traditionally conducted by clinical pharmacists and a systematic review found that pharmacist-led medicines reconciliation took a mean of 22 min (95 % CI; 12–46 min; [9, 17, 26, 28, 29]). NICE concluded that such an intervention was cost-effective and reduced costs by £3,002 per 1,000 prescription orders [26]. Medication reconciliation is resource intensive and healthcare organizations may lack the resources to deploy pharmacists for routine medication
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reconciliation [30, 31]. Utilizing trained pharmacy technicians further improves the cost-effectiveness and may improve the accessibility of the service.
Strengths and limitations One key strength of this project was the systematic medication management service for all in-patients across the population. However, it cannot be absolutely guaranteed that all admissions were reconciled, particularly in the case of very short-stay admissions as occurred in five instances. As this evaluation was conducted in a single trust the results are not necessarily generalisable. The evaluation demonstrated that the medication history obtained by the pharmacy technician was more comprehensive than that obtained by the medical doctors. However, there is no gold-standard with which to compare the medication histories, and like other similar studies this study did not conclusively demonstrate that the pharmacyobtained history was more accurate [9, 21, 29]. The discrepancies were rated without access to the medical notes and the formal diagnosis, and raters assessed the potential for harm solely based on the medication record. Therefore, future studies should also record the formal diagnosis and the actual clinical outcomes of any discrepancies [10].
Conclusion Medication discrepancies at the time of admission to an inpatient mental health unit were frequent and associated with increasing age and number of medicines on admission. Trained pharmacy technicians may represent an effective and cost-effective solution to reducing the frequency of such discrepancies and thereby improve patient safety in this vulnerable population. Acknowledgments We acknowledge the support from both ward staff and pharmacy staff (including Hilary Scott, Chief Pharmacist). Funding
None.
Conflicts of interest
None.
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2. National Institute for Clinical Excellence. Technical patient safety solutions for medicines reconciliation on admission of adults to hospital. Alert reference: NICE/NPSA/2007/PSG001. National Institute for Clinical Excellence; 2007. Available on http://www.nice.org.uk/nicemedia/pdf/PSG001Guidance.pdf. Accessed 12 Sept 2013. ISBN 1-84629-563-7. 3. Lizer MH, Brackbill ML. Medication history reconciliation by pharmacists in an inpatient behavioral health unit. Am J Health Syst Pharm. 2007;64:1087–91. 4. Maidment ID, Haw C, Stubbs J, Fox C, Katona C, Franklin BD. Medication errors in older people with mental health problems: a review. Int J Geriatr Psychiatry. 2008;23:564–73. 5. Procyshyn RM, Barr AM, Brickell T, Honer WG. Medication errors in psychiatry: a comprehensive review. CNS Drugs. 2010;24:595–609. 6. Marvanova M, Roumie CL, Eden SK, Cawthon C, Schnipper JL, Kripalani S, et al. Health literacy and medication understanding among hospitalized adults. J Hosp Med. 2011;6:488–93. 7. Maidment ID, Parmentier H. Medication error in mental health: implications for primary care. Men Health Fam Med. 2009;6: 203–7. 8. Morcos S, Francis SA, Duggan C. Where are the weakest links? Psychiatr Bull. 2002;26:371–4. 9. Hellstrom LM, Bondesson A, Hogland P, Eriksson T. Errors in medication history at hospital admission: prevalence and predicting factors. BMC Clin Pharmacol. 2012;12:9. 10. Mueller SK, Sponsler KC, Kripalani S, Schnipper JL. Hospitalbased medication reconciliation practices. Arch Int Med. 2012;172:1057–69. 11. Michels RD, Meisel SB. Program using pharmacy-technicians to obtain medication histories. Am J Health Syst Pharm. 2003;60: 1982–6. 12. van den Bemt PM, van den Broek S, van Nunen AK, Harbers JB, Lenderink AW. Medication reconciliation performed by pharmacy technicians at the time of preoperative screening. Ann Pharmacother. 2009;43:868–74. 13. Essex JSNA. Geography and demographics—chapter. Version 1.4—September 2010. Available on http://www.essexpartner shipportal.org/pages/uploads/JSNA/Demography%20refresh% 20chapter%20-%20update%20v1.4.pdf. Accessed 12 Sept 2013. 14. National Patient Safety Agency. Patient safety incident report form; Healthcare Staff. National Patient Safety Agency; 2009. Available on https://www.eforms.npsa.nhs.uk/staffreport/. Accessed 12 Sept 2013. 15. Pippins JR, Gandhi TK, Hamann C, Ndumele CD, Labonville SA, Diedrichsen EK, et al. Classifying and predicting errors of inpatient medication reconciliation. J Gen Int Med. 2008;23: 1414–22. 16. Dean BS, Barber ND. Validated, reliable method of scoring the severity of med errors. Am J Health Syst. 1999;56:57–62. 17. Grimes TC, Duggan CA, Delaney TP, Graham IM, Conlon KC, Deasy E, et al. Medication details documented on hospital discharge: cross-sectional observational study of factors associated with medication non-reconciliation. Br J Clin Pharmacol. 2011; 73:449–57. 18. Galvin M, Jago-Byrne MC, Fitzsimons F, Grimes T. Clinical pharmacist’s contribution to medication reconciliation on admission to hospital in Ireland. Int J Clin Pharm. 2013;35: 14–21. 19. The Information Centre. Hospital episode statistics 2011–12. The Information Centre; 2012. Available on http://www.hesonline. nhs.uk/Ease/servlet/ContentServer?siteID=1937&categoryID= 212. Accessed 14 Sept 2013. 20. Bishop CM. Pattern recognition and machine learning. Berlin: Springer; 2006.
Int J Clin Pharm 21. Mehta R, Onatade R. Auditing medication history-taking can help demonstrate improved pharmacy services. Phar Pract. 2008;18: 209–13. 22. Cornish PL, Knowles SE, Marchesano R, Tam V, Shadowitz S, Juurlink DN, et al. Unintended medication discrepancies at the time of hospital admission. Arch Int Med. 2005;165:424–9. 23. Gleason KM, McDaniel MR, Feinglass J, Baker DW, Lindquist L, Liss D, et al. Results of the Medications at transitions and clinical handoffs (MATCH) study: an analysis of medication reconciliation errors and risk factors at hospital admission. J Gen Int Med. 2010;25:441–7. 24. Lubowski TJ, Cronin LM, Pavelka RW, Briscoe-Dwyer LA, Briceland LL, Hamilton RA. Effectiveness of a medication reconciliation project conducted by PharmD Students. Am J Pharm Educ. 2007;71:1–7. 25. McFazdean E, Isles C, Moffat J, Norrie J, Steward DI. Is there a role for a prescribing pharmacist in preventing prescribing errors in the medical admissions ward? Pharm J. 2003;270:896–9. 26. Campbell F, Karnon J, Czoski-Murray C. A systematic review of the effectiveness and cost effectiveness of interventions aimed at preventing medication error (medicines reconciliation) at hospital admission. The University of Sheffield, School of Health and
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Related Research (ScHARR); 2007. Available on: http://www. nice.org.uk/nicemedia/live/11897/38591/38591.pdf. Accessed 12 Sept 2013. Department of Health. Living well with dementia: A national dementia strategy. Department of Health Publications, London; 2009. Available on: https://www.gov.uk/government/uploads/system/ uploads/attachment_data/file/168220/dh_094051.pdf. Accessed 13 Sept 2013. Chhabra PT, Rattinger GB, Dutcher SK, Hare ME, Parsons KL, Zuckerman IH. Medication reconciliation during the transition to and from long-term care settings: a systematic review. Res Soc Adm Pharm. 2012;8:60–75. Richards M, Ashiru-Oredope D, Chee N. What errors can be identified by pharmacy-led medicines reconciliation? A prospective study. Acute Med. 2011;10:18–21. Greenwald JL, Halasyamani L, Greene J, LaCivita C, Stucky E, Benjamin B, et al. Making inpatient medication reconciliation patient centered, clinically relevant and implementable: a consensus statement on key principles and necessary first steps. J Hosp Med. 2010;5:477–85. Kaboli PJ, Fernandes O. Medication reconciliation: moving forward. Arch Int Med. 2012;172:1069–70.
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RESEARCH ARTICLE
Medication reconciliation by a pharmacy technician in a mental health assessment unit Kay Brownlie • Carl Schneider • Roger Culliford Chris Fox • Alexis Boukouvalas • Cathy Willan • Ian D. Maidment
•
Received: 2 August 2013 / Accepted: 24 October 2013 Koninklijke Nederlandse Maatschappij ter bevordering der Pharmacie 2013
Abstract Background Medication discrepancies are common when patients cross organisational boundaries. However, little is known about the frequency of discrepancies within mental health and the efficacy of interventions to reduce discrepancies. Objective To evaluate the impact of a pharmacy-led reconciliation service on medication discrepancies on admissions to a secondary care mental health trust. Setting In-patient mental health services. Methods Prospective evaluation of pharmacy technician led medication reconciliation for admissions to a UK Mental Health NHS Trust. From March to June 2012 information on any unintentional discrepancies (dose, frequency and name of medication); patient demographics; and type and cause of the discrepancy was collected. The potential for harm was assessed based on two scenarios; the discrepancy was continued into primary care, and the discrepancy was corrected during admission. Logistic regression identified factors associated with discrepancies. Main outcome measure Mean number of discrepancies per admission corrected by the pharmacy technician. Results
Unintentional medication discrepancies occurred in 212 of 377 admissions (56.2 %). Discrepancies involving 569 medicines (mean 1.5 medicines per admission) were corrected. The most common discrepancy was omission (n = 464). Severity was assessed for 114 discrepancies. If the discrepancy was corrected within 16 days the potential harm was minor in 71 (62.3 %) cases and moderate in 43 (37.7 %) cases whereas if the discrepancy was not corrected the potential harm was minor in 27 (23.7 %) cases and moderate in 87 (76.3 %) cases. Discrepancies were associated with both age and number of medications; the stronger association was age. Conclusions Medication discrepancies are common within mental health services with potentially significant consequences for patients. Trained pharmacy technicians are able to reduce the frequency of discrepancies, improving safety.
K. Brownlie R. Culliford Basildon Mental Health Unit, South Essex Partnership University NHS Foundation Trust, Nether Mayne, Basildon, Essex SS16 5NL, UK
A. Boukouvalas Aston University, Aston Triangle B4 7ET, UK
C. Schneider Faculty of Pharmacy, The University of Sydney, Sydney, NSW 2006, Australia C. Fox Department of Psychological Sciences, Faculty of Medicine and Health Sciences, Norwich Medical School, University of East Anglia, Norwich Research Park, Norwich NR4 7TJ, UK C. Fox Julian Hospital, Norfolk and Suffolk NHS Foundation Trust, Norwich NR2 3TD, UK
Keywords Continuity of care Medication reconciliation Medication safety Mental health United Kingdom
C. Willan Rochford Hospital, South Essex Partnership University NHS Foundation Trust, Union Lane, Rochford SS4 1RB, UK I. D. Maidment (&) Aston Research Centre for Healthy Ageing (ARCHA), Aston University, Aston Triangle B4 7ET, UK e-mail: [email protected] I. D. Maidment Pharmacy Department, Life and Health Sciences School, Aston University, Aston Triangle B4 7ET, UK
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Int J Clin Pharm
Impacts on practice
Aim of the study
•
To evaluate the impact of a pharmacy-led medication reconciliation service on medication discrepancies on admission to a secondary care mental health trust. Key objectives were:
•
• •
Medication discrepancies are common in mental health services putting patients at a significant risk of harm. Certain parts of society, particularly older people taking many different medicines, appear to be at a particular risk of medication reconciliation errors. Medication reconciliation should be a core pharmacy service. Specially trained pharmacy technicians represent a cost-effective way of reconciling medication.
– – –
to obtain quantitative data on the prevalence of discrepancies and impact of the service; to identify the types of medicines involved, the type of discrepancy and risk factors for a discrepancy; to identify the potential for harm if the discrepancies were not corrected.
Introduction The American Institute for Healthcare Improvement defines medication reconciliation as ‘‘the process of creating the most accurate list possible of all medicines a patient is taking, including drug name, frequency, dose and route, and comparing that list against the physician’s admission, transfer, and/or discharge order with the goal of providing correct medications to the patient at all transition points within the organisation’’ [1]. Unfortunately, discrepancies in medication reconciliation, resulting in medication error, are a common problem when patients move between healthcare organisations [2]. Medication discrepancies, on admission to a secondary care unit, may follow the patient throughout the admission and post-discharge, and therefore have long-term consequences [3]. Obtaining an accurate medication history and medication reconciliation may be particularly difficult during an acute psychiatric illness due to associated cognitive impairment [4–6]. There is, however, a lack of research on the incidence of, and interventions to reduce, medication discrepancies within mental health services [2, 7]. One study, involving 43 patients, within a Mental Health Trust found that discrepancies in the medication record in the medical notes occurred in 43 % of admissions, of which 18 % were judged to be potentially harmful; however, this study did not assess discrepancies on the drug admission chart [8]. A more recent study on two medical wards found a medication reconciliation discrepancy in 47 % (95 % CI 43–51 %) of 670 admitted patients [9]. Pharmacy-led medication reconciliation is designed to reduce the risk of medication discrepancies. Recently a systematic review identified the lack of data and the need for further research on medication reconciliation and whilst there is a limited literature on pharmacy technicians undertaking reconciliation, as far as we are aware there are no studies in a mental health setting [10–12].
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Methods Setting and participants This prospective evaluation was undertaken within South Essex Partnership University NHS Foundation Trust (SEPT) Assessment Unit, based at Basildon Mental Health Unit (MHU) for a 3 month period from 13th March to 8th June 2012. SEPT provides health and social care services for people with mental health problems and learning disabilities. People aged over 18 living within South Essex, who develop mental health problems and people with mental health problems in crisis requiring in-patient admission would be routinely admitted to the 20-bedded assessment unit. The Trust provides services to six local authorities (LAs) in South Essex; two of which—Southend-on-Sea and Thurrock—are Unitary Authorities. The total population is approximately 750,000. The percentage of the population from black and minority ethnic (BME) groups ranges between 6.9 and 13.3 %. Levels of affluence vary within South Essex. Brentwood, Castle-Point and Rochford LAs are among the most affluent in the UK, whereas Southend, Thurrock and Basildon are more deprived than the national average, and also contain pockets of marked deprivation [13]. This project was approved by the clinical governance committee within SEPT; ethics committee approval was not required because the project was an evaluation of an existing service. The results were anonymised and service users were not identifiable to anyone in the team (IM, CS) conducting the secondary analysis of the results for publication. Method of medication reconciliation The method used for medication reconciliation was based upon the appropriate Trust policy and procedure, and in
Int J Clin Pharm
line with National Patient Safety Agency (NPSA) guidance [2]. Briefly, on a daily basis, every weekday, a pharmacy medicines management technician (n = 3) attends the assessment unit and reconciles medication for every new admission. A triage system was operated with nursing staff identifying priority cases. A variety of sources, as listed below, were used, because frequently medication was prescribed by clinicians other than the GP, for example antipsychotic depot injections from secondary care prescribers, and medication may have been recently changed by the outpatient clinic or home treatment team. First, information was gathered from the secondary care notes and any patient’s own drugs (PODs). Second, the GP surgery was contacted and a current list of medication requested. Third, if required and informed by the initial information obtained, other sources including the family, historical notes, community pharmacy, community mental health services, Drug and Alcohol services and other healthcare organisations were consulted. Fourth, the patient was consulted unless advised by nursing staff, because for example the patient was too unwell. The patient was also asked about any other medication taken including over-thecounter medicines (OTC), herbal remedies and illicit substances. The summary of medication used at the time of admission was documented on a standard proforma and compared to the in-patient prescription. The pharmacy medicines management technician discussed any discrepancy with the clinical team to confirm whether or not the discrepancy was intentional or unintentional. If the discrepancy was unintentional the medication chart was modified by a prescribing doctor and the discrepancy was recorded on the data collection form. If the discrepancy was intentional no further action was taken, and the discrepancy was not recorded on the data collection form. Data collection A data collection form was developed to collect the medication reconciliation activity of the pharmacy technician enabling the service evaluation. Based upon the NPSA patient safety criteria the following data fields were collected [14]. 1. 2. 3. 4.
A free text qualitative description of the discrepancy (based on NPSA data field ID05). Any causes or contributing factors (ID06). Details of the medication involved (MI04–MI09). Discrepancy categories were developed using the NPSA patient safety incident classification data fields MI02 and MI03 [14] and supplemented, to ensure a comprehensive categorisation, with previously developed classifications [12, 15]. The proposed list was
discussed with and subsequently modified following discussions with clinical pharmacy staff again to ensure a comprehensive list. The form was piloted, by two pharmacy medicines management technicians, within the Assessment Unit and subsequently modified to improve usability. The form was completed by the technician on the unit as soon as the discrepancy was identified and confirmed as unintentional. Assessment of harm The potential impact on patient care was assessed in a random sample of 20 % of all discrepancies using validated methodology; the sample size of 20 % was chosen based upon the methods of similar studies [16, 17]. Four clinicians including specialist pharmacists, an acute care pharmacist and a consultant psychiatrist rated the potential for harm for each discrepancy using a visual analogue scale with 0 representing no harm and 10 representing death. To test whether the four clinicians rated the severity consistently we performed a two-way repeated measure ANOVA test (PRISM v6.0). Based on previous research assessors were asked to consider two different scenarios. First, standard care—no pharmaceutical medication reconciliation—would not have corrected the discrepancy and the discrepancy would have been continued into primary care post-discharge; this is generally the accepted approach [3, 18]. Recent research has identified that standard care may correct discrepancies during the admission and the second scenario assumed that the discrepancy was corrected at the mid-point of the admission, 16 days (based on a mean length of stay of 32 days; [9, 19]). Based on the assessors’ mean score the discrepancy was classed as minor (score \3), moderate (score 3–7) or severe (score [7). Different medication class The medication class classification was based on the primary BNF indication with the exception of anti-convulsants, which due to their common use in mental health were classed as mood stabilisers. One member of the team classified all the medicines (Ian Maidment—IM); this classification was independently checked (Carl Schneider—CS) with any disagreements resolved by consensus. Regression analysis of medication reconciliation discrepancies A logistic regression model was employed to assess which factors may affect the occurrence of reconciliation
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Int J Clin Pharm Table 1 Demographic characteristics of people admitted to assessment unit
Mean age (±SD) and range
Gender
Mean gap in days between admissions and medication reconciliation (±SD)
Mean total number of medicines taken (±SD)
44.5 (±17.2)
193 male
1.22 (±0.86)
4.65 (±3.19)
18–91
188 female 1 not recorded
Table 2 Different medication class Medication class including mental health sub-category
Mental health subcategories n (% of total)
Total mental health
Table 3 Discrepancy type n (% of total)
Type of discrepancy
N
% of total discrepencies
275 (48.3)
Medicine not prescribed that should have been prescribed (omission)
464
77.2
Anti-depressants
111 (19.5)
Anti-psychotics
74 (13.0)
Wrong/unclear dosage
42
7.0
26 (4.6)
Wrong/unclear strength Wrong/unclear formulation
30 19
5.0 3.2
Benzodiazepines
23 (4.0)
Wrong/unclear frequency
19
3.2
Alcohol dependence
17 (3.0)
8
1.3
Anti-muscarinics
13 (2.3)
Additional medicine—something prescribed that should not have been prescribed
Other mental health medicines
11 (1.9)
Wrong/unclear name of drug or medicine
4
0.7
Mood stabilisers/anticonvulsants
Other
3
0.5
Cardiovascular
63 (11.1)
Wrong/unclear route
1
0.2
Endocrine
53 (9.3)
Clerical error (e.g. script not signed or dated)
1
0.2
Respiratory
50 (8.8)
Unable to be determined
10
1.7
Gastro-intestinal tract
47 (8.3)
Total number of discrepancies
Analgesics
33 (5.8)
Other Overall total
48 (8.4) 569
discrepancies. This model was selected after an empirical comparison to more complex statistical models, which were shown to offer no advantage, and validated by evaluating the average misclassification rate, defined as the proportion of cases where the occurrence of a discrepancy error was misclassified [20]. A Bayesian approach, that incorporates uncertainty in the factors associated with a discrepancy and the logistic model, was used to ensure a robust analysis. The discrepancy error response for the logistic regression model was coded with the 0 label signifying a discrepancy and 1 that no discrepancies were found. All cases with missing values were removed, reducing the available data size to 373 cases.
Results Over the 3 month period there were 382 admissions to the assessment unit. See Table 1 for the demographic characteristics of the people admitted to the unit. An unintentional medication discrepancy was recorded in 212 of 377 (56.2 %) admissions reconciled (in five cases
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601
the patient was discharged before the medication could be reconciled). Three different pharmacy technicians reconciled the medication and mean time for each admission was 16.0 min (range 5–60 min; SD ± 7.2). The technicians corrected discrepancies involving 569 medicines (mean 1.5 medicines per admission). These medicines are broken down into different classes in Table 2. Of the endocrine medicines 21 were medicines for diabetes (insulin or oral anti-diabetic medicines). In total there were 601 different discrepancies. This is higher than the number of medicines, because some medicines had more than one discrepancy e.g. wrong strength and unclear formulation. The different types of discrepancies are described in Table 3—the most common discrepancy was omission. The data on the cause of the discrepancy is not reported, because in the majority of cases the cause of the discrepancy was unclear. The severity of the discrepancy was assessed in 114 medicines (20 %; 114/569). If the discrepancy was corrected within 16 days the potential harm was rated as minor in 71 (62.3 %) cases and moderate in 43 (37.7 %) cases. If the discrepancy was continued into primary care the potential harm was rated minor in 27 (23.7 %) cases and moderate in 87 (76.3 %) cases. We found statistically significant differences between the severity assessments by
Int J Clin Pharm Table 4 Regression analysis of factors associated with medication reconciliation discrepancies Parameter
Median
CI (95 %)
Intercept (constant)
-0.3
[-0.52, -0.09]
Age
-0.47
Sex
0.11
[-0.11, 0.33]
Gap (days) between admission and med rec
0.27
[0.03, 0.50]
Total number meds
-0.32
[-0.71, -0.23]
[-0.59, -0.05]
the raters indicating that the rating was conducted independently by the 4 raters (p \ 0.01). Results of regression analysis of medication reconciliation discrepancies The median and 95 % CIs of the coefficients, corresponding to effects associated with a discrepancy, are described in Table 4. A coefficient of zero indicates no effect; the factor has no association with a discrepancy, a negative value indicates a positive correlation with a discrepancy and a positive value a negative correlation. Gender had no significant effect on the likelihood of a discrepancy. Both age and the number of medications have negative coefficients and therefore increasing age and number of medications predict a reconciliation discrepancy, with age the stronger predictor. The gap between admission and medication reconciliation has a positive coefficient indicating that the longer the gap, the less likely that a discrepancy is found, however, the effect is relatively small compared to age.
Discussion This evaluation found a mean discrepancy rate of 1.5 medicines per admission. This is similar to other studies, which have identified mean discrepancy rates of 0.3–2.91 medicines per admission [3, 21–24]. Over fifty percent (56.2 %) of admissions had a medication discrepancy; this is comparable to other studies, for example 53.6 % [22] and 35.9 % [23]. Finally, similar to other studies, errors of omission were amongst the most frequent discrepancy; 77.2 % of all discrepancies, which compares with 71 and 48.9 % of discrepancies in one UK [25] and one USA study [23], respectively. To understand the impact of the intervention we need to understand the potential real-life harm of the discrepancies [26]. A previous study found that 63 % of non-reconciled medicines had the potential to cause moderate harm and 2 % severe harm [17]. However, this study assumed, like
other previous studies, that the discrepancies are never corrected and we also modelled for the possibility that the discrepancy will be detected by standard care [9, 26]. If the discrepancies were continued into primary care, we found 76.3 % of discrepancies were associated with moderate potential harm, whereas if the discrepancy was detected mid-way through the admission only 37.7 % of cases were associated with moderate harm. Age, polypharmacy and the gap between admission and medication reconciliation correlate with a discrepancy. The likelihood of a discrepancy decreases as the gap between admission and medicine reconciliation increases potentially indicating that standard care does, over time, detect and correct discrepancies. Both polypharmacy and particularly increasing age predicted a medication reconciliation discrepancy. The impact of polypharmacy on medication reconciliation discrepancies has been previously welldescribed [9, 17, 23]. Whilst, this study found that the risk of discrepancies is higher in the elderly, overall the literature on any association between age and the risk of a discrepancy is conflicting. Some studies found no association [9, 17] whereas other studies found that age increased [23] and conversely decreased [15] the risk of a potentially harmful discrepancy. The prevalence of dementia and associated cognitive impairment rises exponentially with age and this cognitive impairment may limit the active involvement of the person with dementia in the reconciliation process, increasing the risk of a discrepancy [4, 27]. Therefore, age could potentially be a surrogate for cognitive impairment. Although, most older people admitted to the mental health unit are likely to suffer from cognitive impairment or dementia, the presence of dementia or cognitive impairment was not collected and could not be included in the regression analysis model. Therefore, a future study should investigate whether cognitive impairment does increase the risk of a medication reconciliation discrepancy. On a more immediate and practical basis, these results suggest medication reconciliation should prioritise older people and people on multiple medications. This evaluation adds to the evidence that medication reconciliation can be carried out by a suitably trained pharmacy technician [11, 12]. It took a mean of 16.0 min per admission for the pharmacy technician to take the medication history and reconcile any discrepancies. Medicines reconciliation is traditionally conducted by clinical pharmacists and a systematic review found that pharmacist-led medicines reconciliation took a mean of 22 min (95 % CI; 12–46 min; [9, 17, 26, 28, 29]). NICE concluded that such an intervention was cost-effective and reduced costs by £3,002 per 1,000 prescription orders [26]. Medication reconciliation is resource intensive and healthcare organizations may lack the resources to deploy pharmacists for routine medication
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reconciliation [30, 31]. Utilizing trained pharmacy technicians further improves the cost-effectiveness and may improve the accessibility of the service.
Strengths and limitations One key strength of this project was the systematic medication management service for all in-patients across the population. However, it cannot be absolutely guaranteed that all admissions were reconciled, particularly in the case of very short-stay admissions as occurred in five instances. As this evaluation was conducted in a single trust the results are not necessarily generalisable. The evaluation demonstrated that the medication history obtained by the pharmacy technician was more comprehensive than that obtained by the medical doctors. However, there is no gold-standard with which to compare the medication histories, and like other similar studies this study did not conclusively demonstrate that the pharmacyobtained history was more accurate [9, 21, 29]. The discrepancies were rated without access to the medical notes and the formal diagnosis, and raters assessed the potential for harm solely based on the medication record. Therefore, future studies should also record the formal diagnosis and the actual clinical outcomes of any discrepancies [10].
Conclusion Medication discrepancies at the time of admission to an inpatient mental health unit were frequent and associated with increasing age and number of medicines on admission. Trained pharmacy technicians may represent an effective and cost-effective solution to reducing the frequency of such discrepancies and thereby improve patient safety in this vulnerable population. Acknowledgments We acknowledge the support from both ward staff and pharmacy staff (including Hilary Scott, Chief Pharmacist). Funding
None.
Conflicts of interest
None.
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