Impact of PharmaCloud on Pharmacist-Led Medication Reconciliation Efficiency and Error Detection Among Taiwanese Inpatients

Impact of Integrating PharmaCloud on Pharmacist-Led Medication Reconciliation Efficiency and Error Detection Among Internal Medicine Inpatients: A Prospective Non-Randomized Study in Taiwan

Taiwan's National Health Insurance Administration PharmaCloud provides cross-institutional medication access to reimbursed medication records to support best possible medication history (BPMH) compilation. However, its utility among internal medicine inpatients, who typically present with complex regimens and frequent medication changes, remains understudied. This study aims to evaluate the impact of PharmaCloud integration on pharmacist-led medication reconciliation (MedRec) efficiency and error detection among internal medicine inpatients at both admission and discharge.

The non-randomized, single-center study was conducted from May to November 2024 at the Far Eastern Memorial Hospital in Taiwan. Internal medicine inpatients taking at least one pre-admission chronic medication were enrolled and assigned to standard medication reconciliation protocol (control) or PharmaCloud-integrated medication reconciliation (experimental). Best possible medication history compilation time was recorded across two stages: preparation and interview. Medication discrepancies were identified at admission and discharge and classified as intentional or unintentional.

Study Overview

• Status: Completed
• Conditions: Medication Reconciliation; Best Possible Medication History; Medication Discrepancy
• Intervention / Treatment: Other: PharmaCloud-integrated medication reconciliation

• Study Type: Interventional
• Enrollment (Actual): 93
• Phase: Not Applicable

Contacts and Locations

Study Locations

• Taiwan
  • New Taipei City, Taiwan, 220216
    • Far Eastern Memorial Hospital

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Adult; Older Adult
• Accepts Healthy Volunteers: No

Description

Inclusion Criteria:

• Age 18 years or older
• Use of at least one pre-admission medication for a chronic disease

Exclusion Criteria:

• If patient was discharged within 48 hours of admission
• If patient was scheduled for surgery during their inpatient stay

Study Plan

How is the study designed?

Design Details

• Primary Purpose: Health Services Research
• Allocation: Non-Randomized
• Interventional Model: Parallel Assignment
• Masking: None (Open Label)

Number of Arms

2

Arms and Interventions

Participant Group / Arm	Intervention / Treatment
No Intervention: Standard medication reconciliation; Best possible medication histories (BPMHs) were constructed within 72 hours of patient admission. First, designated pharmacists compiled a preliminary BPMH by reviewing in-house electronic medical records. Then, pharmacists conducted patient or caregiver interviews to form the finalized BPMH.
Experimental: PharmaCloud-intergrated medication reconciliation; Best possible medication histories (BPMHs) were constructed within 72 hours of patient admission. First, designated pharmacists compiled a preliminary BPMH by reviewing in-house electronic medical records and PharmaCloud data. Then, pharmacists conducted patient or caregiver interviews to form the finalized BPMH.	Other: PharmaCloud-integrated medication reconciliation; The intervention entailed supplementing in-house electronic medical record with data from PharmaCloud, a platform launched by Taiwan's National Health Insurance Administration to enable cross-institutional access to reimbursed medication records.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Best possible medication history compilation efficiency	The first outcome measure was best possible medication history (BPMH) compilation efficiency, which was measured in minutes as three metrics: preparation time (stage 1), measured from the start of electronic medical record (EMR) and PharmaCloud review to the completion of the preliminary BPMH; interview time (stage 2), measured from the start to the end of the face-to-face interview; and total BPMH compilation time, the sum of stage 1 and 2.	From patient's time of hospital admission to 72 hours post-admission.

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Medication error detection rate	Medication error detection rate was defined as the proportion of participants with at least one identified unintentional discrepancy at either admission or discharge. All identified discrepancies were categorized as either intentional or unintentional, depending on whether or not the medication changes were consciously made by the prescribers, respectively.	Admission: Unintentional discrepancies identified from patient's time of admission to 72 hours post-admission. Discharge: Unintentional discrepancies identified immediately prior to patient's departure from the facility.

Collaborators and Investigators

• Sponsor: Far Eastern Memorial Hospital
• Collaborators: National Yang Ming Chiao Tung University

Publications and helpful links

General Publications

• Huang PP, Poon SY, Chang SH, Kuo CW, Chien MW, Chen CC, Chiang SC. Improving the Efficiency of Medication Reconciliation in Two Taiwanese Hospitals by Using the Taiwan National Health Insurance PharmaCloud Medication System. Int J Gen Med. 2023 Jan 19;16:211-220. doi: 10.2147/IJGM.S389683. eCollection 2023.

Study record dates

Study Major Dates

• Study Start (Actual): May 1, 2024
• Primary Completion (Actual): November 30, 2024
• Study Completion (Actual): November 30, 2024

Study Registration Dates

• First Submitted: July 20, 2026
• First Submitted That Met QC Criteria: July 23, 2026
• First Posted (Actual): July 27, 2026

Study Record Updates

• Last Update Posted (Actual): July 27, 2026
• Last Update Submitted That Met QC Criteria: July 23, 2026
• Last Verified: July 1, 2026

More Information

Terms related to this study

• Other Study ID Numbers: 115116-E

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No