Fully independent validation of the Matrix-INI, IMEPAG-group, MERIS instruments for predicting preventable drug-related incidents of hospitalized patients with infectious diseases

Authors

  • Renato Barbosa Rezende Evandro Chagas Infectious Diseases National Institute, Oswaldo Cruz Foundation, Rio de Janeiro, RJ, Brazil , Oswaldo Cruz Foundation image/svg+xml
  • Eduardo Corsino Freire Quality Control in Health National Institute, Oswaldo Cruz Foundation, Rio de Janeiro, RJ, Brazil , Oswaldo Cruz Foundation image/svg+xml
  • Paula Gabriela dos Santos Barreto Evandro Chagas Infectious Diseases National Institute, Oswaldo Cruz Foundation, Rio de Janeiro, RJ, Brazil , Oswaldo Cruz Foundation image/svg+xml
  • André Luiz dos Santos Evandro Chagas Infectious Diseases National Institute, Oswaldo Cruz Foundation, Rio de Janeiro, RJ, Brazil , Oswaldo Cruz Foundation image/svg+xml
  • Fernando de Oliveira Silva Evandro Chagas Infectious Diseases National Institute, Oswaldo Cruz Foundation, Rio de Janeiro, RJ, Brazil , Oswaldo Cruz Foundation image/svg+xml
  • Vanessa Rodrigues Bezerra Evandro Chagas Infectious Diseases National Institute, Oswaldo Cruz Foundation, Rio de Janeiro, RJ, Brazil , Oswaldo Cruz Foundation image/svg+xml
  • Juliana Arruda de Matos Evandro Chagas Infectious Diseases National Institute, Oswaldo Cruz Foundation, Rio de Janeiro, RJ, Brazil , Oswaldo Cruz Foundation image/svg+xml
  • Pedro Emmanuel Alvarenga Americano do Brasil Evandro Chagas Infectious Diseases National Institute, Oswaldo Cruz Foundation, Rio de Janeiro, RJ, Brazil , Oswaldo Cruz Foundation image/svg+xml

DOI:

https://doi.org/10.1590/s2175-97902026e24722

Keywords:

Clinical pharmacy service, Clinical decision rules, Prognosis, Patient safety, Medication errors, Infectious disease medicine

Abstract

Validate and compare three prescription-related incident prediction instruments (Matrix-INI, IMEPAG-group, MERIS) in hospitalized patients with infectious disease. Observational follow-up (cohort) study enrolling adults from June 2019 to March 2020, with no prior care from the clinical pharmacist. Matrix-INI, MERIS, and IMEPAG-group instruments assessing preventable drug-related incidents (PDRI) were applied at ward admission and once a week. The outcome of interest was clinically relevant PDRI. For every participant at every time of analysis, the instruments scores were retrieved, and validation was estimated through calibration (slope, intercept), discrimination indexes, and reclassification indexes. 219 patients were screened, and 212 were included. PDRI affected 78.77% of participants. “Anticoagulants” was the strongest predictor. Discrimination of all instruments was always low. (area under ROC curve < 0.70); and weekly performance was insufficient. No reclassification improvement was observed. Matrix-INI, IMEPAG-group assigned lower risks despite PDRI. Discrimination increases slightly every week, with a corresponding calibration loss. Models lacked sufficient predictive performance, pointing to a need for a specific PDRI prediction tool for this population. Empirically developed instruments, such as Matrix-INI, often exhibit poor performance. Regular risk assessments during hospitalization are crucial for dynamic prioritization in clinical pharmacy, as PDRI risk may change over time.

Downloads

Download data is not yet available.

References

Abuzour AS, Hoad-Reddick G, Shahid M, Steinke DT, Tully MP, Williams SD, et al. Patient prioritisation for hospital pharmacy services: current approaches in the UK. Eur J Hosp Pharm. 2021 Nov 1;28(e1):e102-8.

Agência Nacional de Vigilância Sanitária. Manual para Notificação de Eventos Adversos e Monitoramento de Segurança em Ensaios Clínicos. [Internet]. 2020 [cited 2024 Sep 11]. Available on: https://www.gov.br/anvisa/pt-br/centraisdeconteudo/publicacoes/medicamentos/pesquisa-clinica/manuais-e-guias/manual-para-notificacao-de-eventos-adversos-e-monitoramento-de-seguranca-em-ensaios-clinicos-1a-edicao.pdf/view

Alomi YA, Al-Jarallah SM, Bahadig FA. Cost-efficiency of Clinical Pharmacy Services at Ministry of Health Hospital, Riyadh City, Saudi Arabia. PTB Reports. 2019 Sep 9;5(3s): S20-2.

Alshakrah MA, Steinke DT, Lewis PJ. Patient prioritization for pharmaceutical care in hospital: A systematic review of assessment tools. Res Social Adm Pharm. 2019 Jun 1;15(6):767-79.

Billstein-Leber M, Carrillo CJD, Cassano AT, Moline K, Robertson JJ. ASHP Guidelines on Preventing Medication Errors in Hospitals. Am J Health-System Pharm. 2018 Oct 1;75(19):1493–517.

Canning ML, McDougall R, Yerkovich S, Barras M, Coombes I, Sullivan C, et al. Measuring the impact of pharmaceutical care bundle delivery on patient outcomes: an observational study. Int J Clin Pharm. 2024 Oct;46(5):1172-80.

Chen CC, Hsiao FY, Shen LJ, Wu CC. The cost-saving effect and prevention of medication errors by clinical pharmacist intervention in a nephrology unit. Medicine (Baltimore). 2017 Aug;96(34):e7883.

Collins GS, Dhiman P, Andaur Navarro CL, Ma J, Hooft L, Reitsma JB, et al. Protocol for development of a reporting guideline (TRIPOD-AI) and risk of bias tool (PROBAST-AI) for diagnostic and prognostic prediction model studies based on artificial intelligence. BMJ Open. 2021 Jul;11(7):e048008.

Dean B. What is a prescribing error? Quality in Health Care. 2000 Dec 1;9(4):232-7.

Deawjaroen K, Sillabutra J, Poolsup N, Stewart D, Suksomboon N. Clinical usefulness of prediction tools to identify adult hospitalized patients at risk of drug-related problems: A systematic review of clinical prediction models and risk assessment tools. Br J Clin Pharmacol. 2022;88(4):1613-29.

Dos Santos Barreto PG, Barbosa Rezende R, Dos Santos AL, de Oliveira Silva F, Rodrigues Bezerra Góis V, Corsino Freire E, et al. Fully independent validation and updating of a clinical pharmacy prioritizing risk score in an infectious disease hospital ward. Br J Clin Pharmacol. 2022 Aug;88(8):3695-708.

Falconer N, Barras M, Cottrell N. How hospital pharmacists prioritise patients at high-risk for medication harm. Res Social Adm Pharm. 2019;15(10):1266–73.

Falconer N, Nand S, Liow D, Jackson A, Seddon M. Development of an electronic patient prioritization tool for clinical pharmacist interventions. Am J Health Syst Pharm. 2014 Feb 15;71(4):311–20.

Høj K, Pedersen HS, Lundberg ASB, Bro F, Nielsen LP, Sædder EA. External validation of the Medication Risk Score in polypharmacy patients in general practice: A tool for prioritizing patients at greatest risk of potential drug‐related problems. Basic Clin Pharma Tox. 2021 Oct;129(4):319-31.

ISPM Brasil. Desafio Global de Segurança do Paciente: Medicação Sem Danos. Boletim ISPM Brasil. 2018;7(1):6.

Jourdan JP, Muzard A, Goyer I, Ollivier Y, Oulkhouir Y, Henri P, et al. Impact of pharmacist interventions on clinical outcome and cost avoidance in a university teaching hospital. Int J Clin Pharm. 2018 Dec 1;40(6):1474-81.

Lambden S, Laterre PF, Levy MM, Francois B. The SOFA score-development, utility and challenges of accurate assessment in clinical trials. Crit Care. 2019 Dec;23(1):374.

Lark ME, Kirkpatrick K, Chung KC. Patient Safety Movement: History and Future Directions. J Hand Surg. 2018 Feb;43(2):174-8.

Lázaro Cebas A, Caro Teller JM, García Muñoz C, González Gómez C, Ferrari Piquero JM, Lumbreras Bermejo C, et al. Intervention by a clinical pharmacist carried out at discharge of elderly patients admitted to the internal medicine department: influence on readmissions and costs. BMC Health Serv Res. 2022 Feb 9;22(1):167.

Martinbiancho JK, Zuckermann J, Mahmud SDP, dos Santos L, Jacoby T, da Silva D, et al. Development of risk score to hospitalized patients for clinical pharmacy rationalization in a high complexity hospital. Lat Am J Pharm. 2011;30(7):1342-7.

Michel P. Comparison of three methods for estimating rates of adverse events and rates of preventable adverse events in acute care hospitals. BMJ. 2004 Jan 24;328(7433):199-0.

Müller M. O. farmacêutico que edificou a Farmácia Clínica no Brasil [Internet]. 2018 [cited 2024 Sep 11]. Available on: https://ictq.com.br/opiniao/747-o-farmaceutico-que-edificou-a-farmacia-clinica-no-brasil

New Zealand. Severity Assessment Code (SAC) rating and triage tool for adverse event reporting [Internet]. Health Quality & Safety Commission; 2017 [cited 2022 Nov 11]. Available from: https://www.hqsc.govt.nz/assets/Our-work/System-safety/Adverse-events/Publications-resources/SAC_rating_and_triage_tool_WEB_FINAL.pdf

Pearson TF, Pittman DG, Longley JM, Grapes ZT, Vigliotti DJ, Mullis SR. Factors associated with preventable adverse drug reactions. Am J Health-System Pharm. 1994 Sep 15;51(18):2268-72.

Pencina MJ, D'Agostino Sr RB, Steyerberg EW. Extensions of net reclassification improvement calculations to measure usefulness of new biomarkers. Stat Med. 2011;30(1):11-21.

Ravn-Nielsen LV, Duckert ML, Lund ML, Henriksen JP, Nielsen ML, Eriksen CS, et al. Effect of an In-Hospital Multifaceted Clinical Pharmacist Intervention on the Risk of Readmission: A Randomized Clinical Trial. JAMA Intern Med. 2018 Mar 1;178(3):375-82.

Rodrigues AT. Farmácia Clínica como ferramenta de segurança em unidade de terapia intensiva [Internet] [Doutorado em Ciências Médicas]. [Campinas]: Universidade Estadual de Campinas; 2017. Available on: https://repositorio.unicamp.br/acervo/detalhe/984830

Saedder EA, Lisby M, Nielsen LP, Rungby J, Andersen LV, Bonnerup DK, et al. Detection of Patients at High Risk of Medication Errors: Development and Validation of an Algorithm. Basic Clin Pharmacol Toxicol. 2016 Feb;118(2):143-9.

Skjøt-Arkil H, Lundby C, Kjeldsen LJ, Skovgårds DM, Almarsdóttir AB, Kjølhede T, et al. Multifaceted Pharmacist-led Interventions in the Hospital Setting: A Systematic Review. Basic Clin Pharmacol Toxicol. 2018 Oct;123(4):363-79.

Sociedade Brasileira de Farmacia Hospitalar. Padrões mínimos para farmácia hospitalar e serviços de saúde [Internet]. 3a. São Paulo: SBRAFH; 2017. Available on: https://www.sbrafh.org.br/site/public/docs/padroes.pdf

Steyerberg EW. Clinical Prediction Models: A Practical Approach to Development, Validation, and Updating [Internet]. Cham: Springer International Publishing; 2019 [cited 2024 Sep 11]. (Statistics for Biology and Health). Available from: http://link.springer.com/10.1007/978-3-030-16399-0

Timóteo AT, Aguiar Rosa S, Nogueira MA, Belo A, Cruz Ferreira R. Validação externa do score de risco ProACS para estratificação de risco de doentes com síndrome coronária aguda. Revista Portuguesa de Cardiologia. 2016 Jun;35(6):323-8.

Trivalle C, Burlaud A, Ducimetière P. Risk factors for adverse drug events in hospitalized elderly patients: A geriatric score. Eur Geriatric Med. 2011 Oct 1;2(5):284-9.

Trivalle C, Cartier T, Verny C, Mathieu AM, Davrinche P, Agostini H, et al. Identifying and preventing adverse drug events in elderly hospitalised patients: A randomised trial of a program to reduce adverse drug effects. J Nutr Health Aging. 2010 Jan 1;14(1):57-61.

Weltgesundheitsorganisation, Collaborating Centre for International Drug Monitoring, editors. The importance of pharmacovigilance: safety monitoring of medicinal products. Geneva: WHO [u.a.]; 2002.

World Health Organization. Global Patient Safety Action Plan 2021-2030: towards eliminating avoidable harm in health care. [Internet]. 2021 [cited 2024 Sep 11]. Available on: https://www.who.int/publications/i/item/9789240032705

Downloads

Published

2026-08-04

Data Availability Statement

Data will become available as soon as the manuscript is accepted as an open-access object at ARCA (FIOCRUZ institutional repository): https://www.arca.fiocruz.br/.

Issue

Section

Article

How to Cite

Fully independent validation of the Matrix-INI, IMEPAG-group, MERIS instruments for predicting preventable drug-related incidents of hospitalized patients with infectious diseases. (2026). Brazilian Journal of Pharmaceutical Sciences, 62, e24722. https://doi.org/10.1590/s2175-97902026e24722