The impact of a medication reconciliation programme at geriatric hospital admission: A pre‐/postintervention study

Hung, Pi-Lien; Chen, Jung-Yi; Chen, Miao-Ting; Li, Pao-Lin; Li, Wei‐Chi; Wang, Zicheng; Huang, Tzu-Ting; Liang, Yen-Tzu; Lin, Pei‐Chin

doi:10.1111/bcp.14095

Cited by 7 publications

(4 citation statements)

References 19 publications

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“…The time to complete the medication reconciliation evaluation following a transition of care was not assessed in this study, considering that some guidelines recommend completing it in the first 12 to 72 hours (Hung et al, 2019), but stricter guidelines require finalising it before administering the first prescription to the patient. The High 5s Project emphasises that medication reconciliation must be performed during the first 24 hours of hospitalisation (Cascone, Seguro & Olivera, 2020;Guido, 2015).…”

Section: Discussionmentioning

confidence: 99%

Clinical impact of pharmacotherapeutic follow-up and pharmacist interventions in a reference hospital in Mexico City

Maza Larrea,

Moreno Zamudio,

Gutiérrez Villegas

et al. 2023

Pharm Educ

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Background: Pharmacotherapeutic monitoring is a professional practice focused on identifying, preventing, and resolving drug-related problems (DRPs). Objective: To assess the clinical impact of pharmacotherapeutic follow-up (PFU) and pharmacist interventions in hospitalised patients at the Instituto Nacional de Cardiología Ignacio Chávez. Methods: A retrospective, observational, descriptive study based on the information from two databases between July 2021 and June 2022 was conducted to calculate the risk reduction associated with pharmacist interventions on medical prescriptions. Results: The study involved 3015 patients who received care during the specified timeframe. The pharmacists provided 10130 attentions, including 5593 medication reconciliations, 16027 pharmacotherapeutic profiles, and 18542 assessments of prescription suitability. The pharmacists carried out 3628 interventions, of which 2282 were targeted at medical prescriptions. The results indicated an increase in risk reduction for accepted interventions, achieving a rate of 40.23%. Conclusion: Pharmacist interventions improved prescriptions, identified and prevented DRPs and medication errors, and enhanced medication safety by facilitating informed therapeutic decisions.

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Section: Discussionmentioning

confidence: 99%

Clinical impact of pharmacotherapeutic follow-up and pharmacist interventions in a reference hospital in Mexico City

Maza Larrea,

Moreno Zamudio,

Gutiérrez Villegas

et al. 2023

Pharm Educ

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“…In Brazil, a survey of 406 medical records and identified 3,059 prescription drugs, found that 81.1% of the elderly had at least one PIM. [13][14][15] In Pakistan, 1,044 elderly people were used in intensive care, of which 70.17% experienced at least one potential drug interaction. In addition, 3,019 potential drug interactions were found, of which 1,398 (46%) were more severe, 1,533 (50.8%) were moderate and 6 (0.2%) were less severe, numerous gaps were found in relation to notification of these data only 12% was considered good document while 49.2% was considered bad.…”

Section: Clinical Evaluation For Drug Use and Adverse Reactions In Th...mentioning

confidence: 99%

Elderly patient safety in the hospital environment: an integrative literature review

Ferreira¹,

Álvarez²,

Tourinho³

et al. 2023

IJHS

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Goal: to identify studies published in national and international scientific journals on the safety of elderly patients in the hospital environment. Method: this is an integrative literature review, carried out in May 2021, with a search for publications in the databases SCOPUS, PUBMED, Scientific Electronic Library Online (SCIELO), Web Of Science, between the years 2010 and 2020, in the languages Portuguese, English and Spanish, with the descriptors "elderly", "hospital medicine", "patient safety". Results: 38 articles were part of the review corpus, which were categorized into four themes: Adverse drug reactions in geriatric patients; Elderly medication management; Safety of the geriatric surgical patient; Risk of falls in the elderly. Final considerations: The studies showed the need to establish guidance for professionals working in the hospital environment on the safety of elderly patients, in order to reduce adverse events and ensure a better quality of care provided. Added to this fact, it was found that the adoption of technologies contributes to prevention, risk reduction and governance in elderly care.

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“…Table 12 summarizes these two feature sets, where the human-selected feature set was adopted by the hospital that had implemented and practiced a comprehensive care suggestion system since 2017 [43]. Except the original EMR data, they added two more health indicators (EWS and health score) calculated by patient's physiological indicators.…”

Section: Exp 4: Feature Selectionmentioning

confidence: 99%

Analyzing Groups of Inpatients’ Healthcare Needs to Improve Service Quality and Sustainability

et al. 2021

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The trend towards personalized healthcare has led to an increase in applying deep learning techniques to improve healthcare service quality and sustainability. With the increasing number of patients with multiple comorbidities, they need comprehensive care services, where comprehensive care is a synonym for complete patient care to respond to a patient’s physical, emotional, social, economic, and spiritual needs, and, as such, an efficient prediction system for comprehensive care suggestions could help physicians and healthcare providers in making clinical judgement. The experiment dataset contained a total of 2.9 million electrical medical records (EMRs) from 250 thousand hospitalized patients collected retrospectively from a first-tier medical center in Taiwan, where the EMRs were de-identified and anonymized and where 949 cases had received comprehensive care. Recurrent neural networks (RNNs) are designed for analyzing time-series data but are still lacking in studying predicting personalized healthcare. Furthermore, in most cases, the collected evaluation data are imbalanced with a small portion of positive cases. This study examined the impact of imbalanced data in model training and suggested an effective approach to handle such a situation. To address the above-mentioned research issue, this study analyzed the care need in the different patient groupings, proposed a personalized care suggestion system by applying RNN models, and developed an efficient model training scheme for building AI-assisted prediction models. This study observed several findings: (1) the data resampling schemes could mitigate the impact of imbalanced data on model training, and the under-sampling scheme achieved the best performance with an ACC of 99.80%, a PPV of 70.18%, an NPV of 99.87%, a recall of 82.91%, and an F1 score of 0.7602, while the model trained with the original data had a very low PPV of 6.42% and a low F1 score of 0.1116; (2) patient clustering with multi-classier could predict comprehensive care needs efficiently with an ACC of 99.87%, a PPV of 77.90%, an NPV of 99.90%, a recall of 92.19%, and an F1 score of 0.8404; (3) the proposed long short-term memory (LSTM) prediction model achieved the best overall performance with an ACC of 99.80%, a PPV of 70.18%, an NPV of 99.87%, a recall of 82.91%, and an F1 score of 0.7602.

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The impact of a medication reconciliation programme at geriatric hospital admission: A pre‐/postintervention study

Cited by 7 publications

References 19 publications

Clinical impact of pharmacotherapeutic follow-up and pharmacist interventions in a reference hospital in Mexico City

Clinical impact of pharmacotherapeutic follow-up and pharmacist interventions in a reference hospital in Mexico City

Elderly patient safety in the hospital environment: an integrative literature review

Analyzing Groups of Inpatients’ Healthcare Needs to Improve Service Quality and Sustainability

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