Application of Novel Pharmacists’ Risk in Pharmacotherapy (PHARIPH) Scale for Identification of Factors Affecting the Safety of Hospital Pharmacotherapy—An Observational Pilot Study
Abstract
:1. Introduction
2. Materials and Methods
2.1. Pharmacists’ Risk in Pharmacotherapy (PHARIPH) Scale
2.2. Statistical Methods
2.3. Ethical Considerations
3. Results
3.1. Study Group
3.2. PHARIPH Scale Analysis
- Pharmacist’s ignorance of a list of drug substitutes (risk 8);
- Preparation of a pharmaceutical formulation from an expired/withdrawn drug (risk 14);
- Preparation of a pharmaceutical formulation from a drug stored in abnormal conditions (risk 15);
- Preparation of medications ordered in hospital and patient’s own drugs without verification of possible drug duplication (risk 17) and their potential effect on patient safety.
4. Discussion
Limitations of the Study
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
- Pharmacotherapy. (n.d.) Medical Dictionary for the Health Professions and Nursing. 2012. Available online: https://medicaldictionary.thefreedictionary.com/pharmacotherapy (accessed on 20 April 2020).
- Roughhead, L.; Semple, S.; Rosenfeld, E. Literature Review: Medication Safety in Australia; Australian Commission on Safety and Quality in Health Care: Sydney, Australia, 2013. [Google Scholar]
- Abhimanyu Parashar, V. Medication Errors and Role of Clinical Pharmacist in Identification, Assessment and Prevention: Need of the Time. Asian J. Pharm. Life Sci. 2016, 6, 1–13. [Google Scholar]
- Ferner, R.; Aronson, J. Clarification of terminology in medication errors: Definitions and classification. Drug Saf. 2006, 29, 1011–1022. [Google Scholar] [CrossRef] [PubMed]
- Kauppinen, H.; Ahonen, R.; Timonen, J. The impact of electronic prescriptions on medication safety in Finnish community pharmacies: A survey of pharmacists. Int. J. Med. Inform. 2017, 100, 56–62. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- World Health Organization. WHO Multi-Professional Patient Safety Curriculum Guide; WHO: Geneva, Switzerland, 2011; pp. 21–228. [Google Scholar]
- Yong, F.R.; Garcia-Cardenas, V.; Williams, K.A.; Benrimoj, S.I. Factors affecting community pharmacist work: A scoping review and thematic synthesis using role theory. Res. Soc. Adm. Pharm. 2019, 16, 123–141. [Google Scholar] [CrossRef] [PubMed]
- Elliott, R.A.; Camacho, E.; Jankovic, D.; Sculpher, M.J.; de Faria, R.I.N. Economic analysis of the prevalence and clinical and economic burden of medication error in England. BMJ Qual. Saf. 2020, 30, 96–105. [Google Scholar] [CrossRef]
- Larson, K.; Lo, C. Potential Cost Savings and Reduction of Medication Errors Due to Implementation of Computerized Provider Order Entry and Bar–Coded Medication Administration in the Fraser Health Authority. UBCMJ 2019, 10, 45–46. [Google Scholar]
- Gaur, A.; Haque, I. Impact of unit based clinical pharmacists interventions in prevention of medication errors in a multispecialty hospital. Int. Res. J. Pharm. 2019, 10, 161–166. [Google Scholar] [CrossRef]
- Mangino, P.D. Role of the pharmacist in reducing medication errors. J. Surg. Oncol. 2004, 88, 189–194. [Google Scholar] [CrossRef]
- Gallimore, C.E.; Sokhal, D.; Schreiter, E.Z.; Margolis, A.R. Pharmacist medication reviews to improve safety monitoring in primary care patients. . Fam. Syst. Health 2016, 34, 104–113. [Google Scholar] [CrossRef]
- Bryla, A.; Urbańczyk, K.; Stachowiak, A.; Burkacka, M.; Steczko, M.; Wiela-Hojeńska, A. Clinical pharmacy–at what stage are we in Poland? Farm. Polska 2020, 76, 175–182. [Google Scholar] [CrossRef]
- Vida, M.C.; De La Plata, J.E.M.; Morales-Molina, J.A.; Pérez-Lázaro, J.J.; Robles, P.A. Identification and prioritisation of risks in a hospital pharmacy using healthcare failure mode and effect analysis. Eur. J. Hosp. Pharm. 2017, 26, 66–72. [Google Scholar] [CrossRef] [Green Version]
- Tavakol, M.; Dennick, R. Making sense of Cronbach’s alpha. Int. J. Med. Educ. 2011, 2, 53–55. [Google Scholar] [CrossRef] [PubMed]
- World Health Organization. The Conceptual Framework for the International Classification for Patient Safety; World Alliance for Patient Safety; World Health Organization: Geneva, Switzerland, 2007; Available online: https://apps.who.int/iris/handle/10665/70882 (accessed on 24 November 2021).
- Teplitsky, B. Hazards of sound-alike, look-alike drug names. Calif. Med. 1973, 119, 62. [Google Scholar] [PubMed]
- Tseng, H.-Y.; Wen, C.-F.; Lee, Y.-L.; Jeng, K.-C.; Chen, P.-L. Dispensing errors from look-alike drug trade names. Eur. J. Hosp. Pharm. 2016, 25, 96–99. [Google Scholar] [CrossRef] [PubMed]
- Malfará, M.; Pernassi, M.; Aragon, D.; Carlotti, A. Impact of the clinical pharmacist interventions on prevention of pharmacotherapy related problems in the paediatric intensive care unit. Int. J. Clin. Pharm. 2018, 40, 513–519. [Google Scholar] [CrossRef] [PubMed]
- Perlman, A.; Horwitz, E.; Hirsh-Raccah, B.; Aldouby-Bier, G.; Negev, T.F.; Hochberg-Klein, S.; Kalish, Y.; Muszkat, M. Clinical pharmacist led hospital-wide direct oral anticoagulant stewardship program. Isr. J. Health Policy Res. 2019, 8, 1–9. [Google Scholar] [CrossRef] [Green Version]
- Trbovich, P.L.; Hyland, S. Responding to the challenge of look-alike, sound-alike drug names. BMJ Qual. Saf. 2016, 26, 357–359. [Google Scholar] [CrossRef] [Green Version]
- Report and Outcomes of Joint Royal Pharmaceutical Society of Great Britain and Pharmacy Practice Research Trust Symposium. Workload Pressure and the Pharmacy Workforce: Supporting Professionals and Protecting the Public. Available online: https://pharmacyresearchuk.org/wp-content/uploads/2012/11/workplace-pressures-FINAL-web.pdf (accessed on 24 November 2021).
- Tsao, N.W.; Lynd, L.; Gastonguay, L.; Li, K.; Nakagawa, B.; Marra, C.A. Factors associated with pharmacists’ perceptions of their working conditions and safety and effectiveness of patient care. Can. Pharm. J. 2015, 149, 18–27. [Google Scholar] [CrossRef] [Green Version]
- Yeh, Y.-C.; Lin, B.Y.-J.; Lin, W.-H.; Wan, T.T.H. Job Stress: Its Relationship to Hospital Pharmacists’ Insomnia and Work Outcomes. Int. J. Behav. Med. 2009, 17, 143–153. [Google Scholar] [CrossRef]
- Klopotowska, J.; Kuiper, R.; van Kan, H.; de Pont, A.C.; Dijkgraaf, M.; Lie-A-Huen, L.; Vroom, M.; Smorenburg, M. On-ward participation of a hospital pharmacist in a Dutch intensive care unit reduces prescribing errors and related patient harm: An intervention study. Crit. Care 2010, 14, R174. [Google Scholar] [CrossRef] [Green Version]
- Annual Report 2019-Strengthening Hospital Pharmacist’s Work in Europe. Available online: https://www.eahp.eu/sites/default/files/annualreport2019_final.pdf (accessed on 24 November 2021).
- Onatade, R.; Appiah, S.; Stephens, M.; Garelick, H. Evidence for the outcomes and impact of clinical pharmacy: Context of UK hospital pharmacy practice. Eur. J. Hosp. Pharm. 2017, 25, e21–e28. [Google Scholar] [CrossRef] [PubMed]
- Grissinger, M. Patients Taking Their Own Medications While in the Hospital. Pa. Patient Saf. Advis. 2012, 9, 50–57. [Google Scholar]
- Nielsen, T.R.H.; Kruse, M.G.; Andersen, S.E.; Rasmussen, M.; Honoré, P.H. The quality and quantity of patients’ own drugs brought to hospital during admission. Eur. J. Hosp. Pharm. 2013, 20, 297–301. [Google Scholar] [CrossRef]
- World Health Organization (WHO). Management of Drugs at Health Centre Level; WHO Regional Office Africa Brazzaville: Cape Town, South Africa, 2004; Volume 2, pp. 1–84. [Google Scholar]
- Alnahas, F.; Yeboah, P.; Fliedel, L.; Abdin, A.Y.; Alhareth, K. Expired Medication: Societal, Regulatory and Ethical Aspects of a Wasted Opportunity. Int. J. Environ. Res. Public Health 2020, 17, 787. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Kingma, H.J.; Becker, M.; Hunfeld, N.; van der Hoeven, R. Issues in the interchangeability of generic drugs part II. Hosp. Pharm. Eur. 2013, 70, 33–35. [Google Scholar]
Risk | Risk Factor | Cronbach’s Alpha after Risk Exclusion | Discriminatory Power |
---|---|---|---|
1 | Misreading of a doctor’s order (similar drug nomenclature) | 0.955 | 0.796 |
2 | Preparation of a wrong drug (similar drug packaging, similar drug nomenclature) | 0.954 | 0.809 |
3 | Preparation of a medication in a wrong dose (drug concentration highlighted on packaging vs. barely visible drug capacity) | 0.955 | 0.792 |
4 | Frequent changes in trade drug names in a hospital, e.g., due to a new tender | 0.959 | 0.513 |
5 | The need to replace existing medications with new ones due to shortages in the market | 0.958 | 0.56 |
6 | Time pressure during drug preparation due to, among other things, late orders of a doctor, low staffing, waiting for a medication from a wholesaler or for an administrative decision | 0.957 | 0.653 |
7 | Improper work organization (e.g., answering phone calls, performing other tasks “in the meantime”) | 0.957 | 0.633 |
8 | Pharmacist’s ignorance of a list of drug substitutes | 0.954 | 0.835 |
9 | Errors in doctor’s orders that were unnoticed by the pharmacist before preparation of the drug | 0.954 | 0.866 |
10 | Psychophysiological fatigue | 0.956 | 0.726 |
11 | Scarce availability of training concerning drug preparation. | 0.958 | 0.617 |
12 | No online ordering system | 0.958 | 0.593 |
13 | Ignorance of drug preparation procedures | 0.954 | 0.815 |
14 | Preparation of a pharmaceutical formulationfrom an expired/withdrawn drug | 0.954 | 0.847 |
15 | Preparation of a pharmaceutical formulation stored in improper conditions | 0.954 | 0.851 |
16 | Preparation of a pharmaceutical formulation under inadequate conditions, such as failure to maintain aseptic conditions | 0.954 | 0.846 |
17 | Preparation of medications ordered in hospital and concomitant patient’s self-administration of own drugs without the knowledge of medical personnel | 0.954 | 0.825 |
Factor | Category | n = 125 | % of Total Participants |
---|---|---|---|
sex | female | 93 | 74.4 |
male | 32 | 25.6 | |
age (years) | 20–29 | 10 | 8.0 |
30–39 | 44 | 35.2 | |
40–49 | 31 | 24.8 | |
50–59 | 29 | 23.2 | |
65 and over | 11 | 8.8 | |
job seniority (years) | up to 5 | 14 | 11.2 |
6–10 | 21 | 16.8 | |
11–19 | 40 | 32.0 | |
20–29 | 29 | 23.2 | |
30 and over | 21 | 16.8 | |
specialization | retail pharmacy | 42 | 33.6 |
clinical pharmacy | 14 | 11.2 | |
hospital pharmacy | 33 | 26.4 | |
Others | 8 | 6.4 | |
size of the town where he/she works | city up to 50 thousand inhabitants | 32 | 25.6 |
city between 50 thousand and 100 thousand inhabitants | 11 | 8.8 | |
city between 100 thousand and 500 thousand inhabitants | 21 | 16.8 | |
city with more than 500 thousand inhabitants | 61 | 48.8 |
Risk | Very Significant (5) | Quite Significant (4) | Significant (3) | Insignificant (2) | Negligible (1) | M |
---|---|---|---|---|---|---|
1 | 68.00% | 8.00% | 10.40% | 4.80% | 8.80% | 4.22 |
N = 85 | N = 10 | N = 13 | N = 6 | N = 11 | ||
2 | 68.00% | 9.60% | 7.20% | 7.20% | 8.00% | 4.22 |
N = 85 | N = 12 | N = 9 | N = 9 | N = 10 | ||
3 | 56.00% | 18.40% | 12.80% | 6.40% | 6.40% | 4.11 |
N = 70 | N = 23 | N = 16 | N = 8 | N = 8 | ||
4 | 18.40% | 25.60% | 33.60% | 15.20% | 7.20% | 3.33 |
N = 23 | N = 32 | N = 42 | N = 19 | N = 9 | ||
5 | 16.80% | 24.00% | 43.20% | 10.40% | 5.60% | 3.36 |
N = 21 | N = 30 | N = 54 | N = 13 | N = 7 | ||
6 | 42.40% | 23.20% | 28.80% | 4.80% | 0.80% | 4.02 |
N = 53 | N = 29 | N = 36 | N = 6 | N = 1 | ||
7 | 39.20% | 24.80% | 28.80% | 5.60% | 1.60% | 3.94 |
N = 49 | N = 31 | N = 36 | N = 7 | N = 2 | ||
8 | 31.20% | 24.00% | 21.60% | 11.20% | 12.00% | 3.51 |
N = 39 | N = 30 | N = 27 | N = 14 | N = 15 | ||
9 | 47.20% | 20.00% | 17.60% | 9.60% | 5.60% | 3.94 |
N = 59 | N = 25 | N = 22 | N = 12 | N = 7 | ||
10 | 40.00% | 22.40% | 32.80% | 3.20% | 1.60% | 3.96 |
N = 50 | N = 28 | N = 41 | N = 4 | N = 2 | ||
11 | 28.80% | 27.20% | 28.80% | 10.40% | 4.80% | 3.65 |
N = 36 | N = 34 | N = 36 | N = 13 | N = 6 | ||
12 | 25.60% | 28.80% | 27.20% | 9.60% | 8.80% | 3.53 |
N = 32 | N = 36 | N = 34 | N = 12 | N = 11 | ||
13 | 38.40% | 20.00% | 22.40% | 9.60% | 9.60% | 3.68 |
N = 48 | N = 25 | N = 28 | N = 12 | N = 12 | ||
14 | 58.40% | 12.00% | 8.80% | 3.20% | 17.60% | 3.9 |
N = 73 | N = 15 | N = 11 | N = 4 | N = 22 | ||
15 | 52.80% | 21.60% | 4.80% | 4.80% | 16.00% | 3.9 |
N = 66 | N = 27 | N = 6 | N = 6 | N = 20 | ||
16 | 58.40% | 16.80% | 4.80% | 2.40% | 17.60% | 3.96 |
N = 73 | N = 21 | N = 6 | N = 3 | N = 22 | ||
17 | 56.00% | 16.80% | 16.00% | 4.80% | 6.40% | 4.11 |
N = 70 | N = 21 | N = 20 | N = 6 | N = 8 |
Risk | Sex | Very Significant (5) | Quite Significant (4) | Significant (3) | Insignificant (2) | Negligible (1) | M | p |
---|---|---|---|---|---|---|---|---|
8 | Female | 36.56% | 24.73% | 15.05% | 12.90% | 10.75% | 3.63 | 0.047 |
N = 34 | N = 23 | N = 14 | N = 12 | N = 10 | ||||
Male | 15.62% | 21.88% | 40.62% | 6.25% | 15.62% | 3.16 | ||
N = 5 | N = 7 | N = 13 | N = 2 | N = 5 | ||||
14 | Female | 66.67% | 9.68% | 6.45% | 3.23% | 13.98% | 4.12 | 0.002 |
N = 62 | N = 9 | N = 6 | N = 3 | N = 13 | ||||
Male | 34.38% | 18.75% | 15.62% | 3.12% | 28.12% | 3.28 | ||
N = 11 | N = 6 | N = 5 | N = 1 | N = 9 | ||||
15 | Female | 56.99% | 22.58% | 3.23% | 4.30% | 12.90% | 4.06 | 0.05 |
N = 53 | N = 21 | N = 3 | N = 4 | N = 12 | ||||
Male | 40.62% | 18.75% | 9.38% | 6.25% | 25.00% | 3.44 | ||
N = 13 | N = 6 | N = 3 | N = 2 | N = 8 | ||||
17 | Female | 63.44% | 13.98% | 11.83% | 4.30% | 6.45% | 4.24 | 0.011 |
N = 59 | N = 13 | N = 11 | N = 4 | N = 6 | ||||
Male | 34.38% | 25.00% | 28.12% | 6.25% | 6.25% | 3.75 | ||
N = 11 | N = 8 | N = 9 | N = 2 | N = 2 |
Risk | Age (Years) | Very Significant (5) | Quite Significant (4) | Significant (3) | Insignificant (2) | Negligible (1) | M | p |
---|---|---|---|---|---|---|---|---|
12 | 20–29 (A) | 70.00% | 20.00% | 10.00% | 0.00% | 0.00% | 4.6 | p = 0.034 |
N = 7 | N = 2 | N = 1 | N = 0 | N = 0 | ||||
30–39 (B) | 18.18% | 27.27% | 38.64% | 6.82% | 9.09% | 3.39 | A > C, D, B | |
N = 8 | N = 12 | N = 17 | N = 3 | N = 4 | ||||
40–49 (C) | 32.26% | 25.81% | 12.90% | 16.13% | 12.90% | 3.48 | ||
N = 10 | N = 8 | N = 4 | N = 5 | N = 4 | ||||
50–59 (D) | 13.79% | 34.48% | 34.48% | 13.79% | 3.45% | 3.41 | ||
N = 4 | N = 10 | N = 10 | N = 4 | N = 1 | ||||
60 and over (E) | 27.27% | 36.36% | 18.18% | 0.00% | 18.18% | 3.55 | ||
N = 3 | N = 4 | N = 2 | N = 0 | N = 2 |
Risk | Job Seniority (Years) | Very Significant (5) | Quite Significant (4) | Significant (3) | Insignificant (2) | Negligible (1) | M | p |
---|---|---|---|---|---|---|---|---|
5 | up to 5 (A) | 28.57% | 42.86% | 21.43% | 7.14% | 0.00% | 3.93 | p = 0.037 A, E > C, D |
N = 4 | N = 6 | N = 3 | N = 1 | N = 0 | ||||
6–10 (B) | 19.05% | 14.29% | 52.38% | 4.76% | 9.52% | 3.29 | ||
N = 4 | N = 3 | N = 11 | N = 1 | N = 2 | ||||
11–19 (C) | 10.00% | 20.00% | 50.00% | 17.50% | 2.50% | 3.17 | ||
N = 4 | N = 8 | N = 20 | N = 7 | N = 1 | ||||
20–29 (D) | 10.34% | 20.69% | 51.72% | 6.90% | 10.34% | 3.14 | ||
N = 3 | N = 6 | N = 15 | N = 2 | N = 3 | ||||
30 and over (E) | 28.57% | 33.33% | 23.81% | 9.52% | 4.76% | 3.71 | ||
N = 6 | N = 7 | N = 5 | N = 2 | N = 1 | ||||
15 | up to 5 (A) | 64.29% | 35.71% | 0.00% | 0.00% | 0.00% | 4.64 | p = 0.013 A, E > C |
N = 9 | N = 5 | N = 0 | N = 0 | N = 0 | ||||
6–10 (B) | 57.14% | 19.05% | 9.52% | 4.76% | 9.52% | 4.1 | ||
N = 12 | N = 4 | N = 2 | N = 1 | N = 2 | ||||
11–19 (C) | 37.50% | 22.50% | 7.50% | 7.50% | 25.00% | 3.4 | ||
N = 15 | N = 9 | N = 3 | N = 3 | N = 10 | ||||
20–29 (D) | 44.83% | 27.59% | 3.45% | 3.45% | 20.69% | 3.72 | ||
N = 13 | N = 8 | N = 1 | N = 1 | N = 6 | ||||
30 and over (E) | 80.95% | 4.76% | 0.00% | 4.76% | 9.52% | 4.43 | ||
N = 17 | N = 1 | N = 0 | N = 1 | N = 2 | ||||
16 | up to 5 (A) | 78.57% | 21.43% | 0.00% | 0.00% | 0.00% | 4.79 | p = 0.03 A, E > C |
N = 11 | N = 3 | N = 0 | N = 0 | N = 0 | ||||
6–10 (B) | 57.14% | 19.05% | 9.52% | 0.00% | 14.29% | 4.05 | ||
N = 12 | N = 4 | N = 2 | N = 0 | N = 3 | ||||
11–19 (C) | 45.00% | 17.50% | 5.00% | 5.00% | 27.50% | 3.48 | ||
N = 18 | N = 7 | N = 2 | N = 2 | N = 11 | ||||
20–29 (D) | 51.72% | 20.69% | 6.90% | 3.45% | 17.24% | 3.86 | ||
N = 15 | N = 6 | N = 2 | N = 1 | N = 5 | ||||
30 and over (E) | 80.95% | 4.76% | 0.00% | 0.00% | 14.29% | 4.38 | ||
N = 17 | N = 1 | N = 0 | N = 0 | N = 3 |
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. |
© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Fedorowicz, O.; Rypicz, Ł.; Wiela-Hojeńska, A.; Jaźwińska-Tarnawska, E.; Witczak, I. Application of Novel Pharmacists’ Risk in Pharmacotherapy (PHARIPH) Scale for Identification of Factors Affecting the Safety of Hospital Pharmacotherapy—An Observational Pilot Study. Int. J. Environ. Res. Public Health 2022, 19, 1337. https://doi.org/10.3390/ijerph19031337
Fedorowicz O, Rypicz Ł, Wiela-Hojeńska A, Jaźwińska-Tarnawska E, Witczak I. Application of Novel Pharmacists’ Risk in Pharmacotherapy (PHARIPH) Scale for Identification of Factors Affecting the Safety of Hospital Pharmacotherapy—An Observational Pilot Study. International Journal of Environmental Research and Public Health. 2022; 19(3):1337. https://doi.org/10.3390/ijerph19031337
Chicago/Turabian StyleFedorowicz, Olga, Łukasz Rypicz, Anna Wiela-Hojeńska, Ewa Jaźwińska-Tarnawska, and Izabela Witczak. 2022. "Application of Novel Pharmacists’ Risk in Pharmacotherapy (PHARIPH) Scale for Identification of Factors Affecting the Safety of Hospital Pharmacotherapy—An Observational Pilot Study" International Journal of Environmental Research and Public Health 19, no. 3: 1337. https://doi.org/10.3390/ijerph19031337