Implementation of a Digital SPD Logistics Model in a Stomatology Department: A Quasi-experimental Study

Summary

This study describes the implementation and evaluation of a hospital-operated Supply–Processing–Distribution (SPD) logistics model for medical consumables management in a stomatology department. The integrated SPD workflow improved consumable traceability, inventory governance, delivery efficiency, workload management, and operational standardization through barcode-enabled digital logistics coordination.

Abstract

Efficient management of medical consumables is essential for maintaining patient safety, workflow efficiency, and financial sustainability in hospital settings. However, many departments continue to rely on decentralized and paper-based inventory coordination processes that may increase dispensing errors, administrative workload, and inventory costs. This study evaluated the implementation of a hospital-operated Supply–Processing–Distribution (SPD) logistics management model in the Department of Stomatology of a tertiary hospital. A quasi-experimental pre–post design was used, including a 6-month baseline period (January–June 2023) and a 6-month post-implementation period (July–December 2023). The SPD model integrated barcode-enabled smart storage cabinets, standardized consumables master-data management, and bidirectional connectivity with the hospital information system. Primary operational outcomes included delivery error rate, delivery time, staff workload, service satisfaction, and inventory capital occupation. Multivariable regression and interrupted time-series analyses were performed. A total of 31,248 dispensing events were evaluated. Following SPD implementation, delivery error rates decreased from 2.00% to 0.50%, and mean delivery time was reduced significantly. Staff workload decreased, while service satisfaction improved after implementation. Monthly inventory capital occupation also declined substantially, with interrupted time-series analysis demonstrating significant post-implementation changes in level and trend. Implementation of the hospital-operated SPD model was associated with improved operational efficiency, traceability of consumables, workflow standardization, and inventory management within the stomatology department. The findings support the potential value of digitally integrated logistics governance systems for optimizing hospital consumables management and reducing workflow interruptions during routine clinical operations.

Introduction

Medical consumables are essential to hospital operations, and their effective management directly influences patient safety, financial sustainability, and clinical workflow efficiency. Inventory governance in hospital supply chains is inherently complex because of high product diversity, fluctuating demand, expiration-sensitive materials, and regulatory oversight^1,2. Inadequate management of consumables may contribute to stock shortages, delivery delays, increased manual workload, inventory obsolescence, and documentation errors, all of which can negatively affect operational performance and the continuity of clinical care.

In recent years, healthcare institutions have increasingly adopted digital supply-chain technologies to improve inventory traceability, accountability, and operational efficiency. Automated dispensing systems, barcode-enabled tracking, radio-frequency identification (RFID), and integration with hospital information systems (HIS) have been associated with improvements in workflow reliability, traceability, and inventory management performance^3,4. However, many previous studies have focused primarily on isolated inventory-monitoring technologies rather than integrated logistics-management systems. In contrast, Supply–Processing–Distribution (SPD) logistics models represent broader operational frameworks that combine centralized consumable coordination, workflow standardization, digital traceability, replenishment governance, and integration between clinical and supply management processes. Accordingly, the present study extends beyond conventional digital inventory tracking by evaluating the real-world operational impact of an integrated hospital-operated SPD logistics model within a clinical stomatology department.

Although most published literature has focused on medication management systems, similar digital governance approaches may also improve the management of medical consumables through real-time transaction capture, standardized master data governance, and automated reconciliation processes. Recent operational studies have reported that digitalization of hospital supply chains may improve inventory visibility, reduce waste, strengthen operational resilience, and support cost containment^2,5. Furthermore, integration between point-of-care inventory systems and centralized procurement or financial-management platforms has been associated with improved material-flow coordination and reduced inventory capital occupation^1,2. Despite growing interest in the digitalization of healthcare logistics, relatively few empirical studies have evaluated hospital-operated SPD systems for consumable management in specialty clinical departments such as stomatology.

The stomatology department was selected as the implementation setting because it presents distinctive consumables-management challenges compared with many other hospital units. Daily clinical activities involve high-frequency use of diverse consumable items, frequent small-batch dispensing, rapid material turnover, and strict traceability requirements for infection control and procedural safety. These operational characteristics make stomatology departments particularly well-suited for evaluating integrated SPD logistics management systems.

Few previous studies have combined quasi-experimental operational evaluation with interrupted time-series analysis to assess the effects of SPD implementation on departmental logistics performance. Therefore, the present study evaluated the implementation of a hospital-operated SPD logistics model in the Department of Stomatology of a tertiary hospital. It was hypothesized that SPD implementation would be associated with reductions in delivery errors, improved delivery efficiency, lower staff workload, improved service satisfaction, and reduced inventory capital occupation. Using predefined pre–post comparison periods and multivariable, segmented regression analyses, this study aimed to provide reproducible operational evidence on SPD-based consumables governance in a real-world clinical environment.

From a healthcare operations management perspective, SPD systems may support supply chain coordination, consumable traceability, workflow standardization, and digital logistics governance within hospital environments. Integrated logistics management models may facilitate real-time monitoring, standardized replenishment processes, and improved coordination between clinical and supply management personnel. Accordingly, this study contributes practical evidence to the literature on hospital logistics management, healthcare quality improvement, and digital transformation by evaluating the operational impact of an integrated SPD logistics model in routine clinical practice. The study primarily assessed operational performance outcomes following SPD implementation while also examining the role of digital governance and workflow standardization in improving consumables management efficiency.

Protocol

1. Ethical approval and regulatory compliance

This study was conducted as a hospital-based quality-improvement and operational evaluation initiative within the Department of Stomatology at Guigang People’s Hospital. Ethical approval was obtained from the Ethics Committee of Guigang People’s Hospital (Approval No. GGPH-2022-061; approved December 15, 2022). The ethics committee approved the analysis of dispensing, inventory management, and logistics system data extracted from institutional information systems. Because no identifiable patient information was collected, informed consent from individual patients was waived. Staff workload and service-satisfaction surveys were conducted voluntarily and anonymously. Completion of the questionnaire was considered implied consent to participate. Survey responses were aggregated prior to analysis, and no personally identifiable information was collected. The workload and satisfaction questionnaires were developed using routine departmental operational indicators for the evaluation of consumables management. Questionnaire items were reviewed by departmental supervisors and pilot-tested for clarity and feasibility before implementation. The research tools used in this protocol are listed in the Table of Materials.

2. Study design and reporting framework

This single-center quasi-experimental pre–post study evaluated the implementation of a hospital-operated Supply–Processing–Distribution (SPD) logistics management model for medical consumables in the Department of Stomatology at Guigang People’s Hospital (Guangxi, China). The pre-implementation period extended from January 1, 2023, to June 30, 2023, and the post-implementation period extended from July 1, 2023, to December 31, 2023. The SPD system became operational on July 1, 2023. The study therefore included 52 weeks of observation, comprising 26 pre-implementation and 26 post-implementation weeks.

This quality-improvement study was reported according to the Standards for Quality Improvement Reporting Excellence (SQUIRE 2.0) guidelines⁶ and, where applicable, the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) recommendations⁷. Interrupted time-series (ITS) segmented regression was prespecified for outcomes with monthly aggregation and sufficient longitudinal observations (≥12 total time points)⁸. ITS analysis was selected because the intervention occurred at a clearly defined institutional implementation point and because the method is appropriate for evaluating longitudinal operational interventions in real-world healthcare settings.

3. Setting

The study was conducted in the Department of Stomatology of a tertiary hospital with approximately 2,400 outpatient visits and 180 minor dental procedures per month. Consumables included routinely used clinical and procedural items managed through the SPD system during the study period, including disposable dental materials, diagnostic consumables, treatment-support items, and temperature-sensitive consumables requiring monitored storage conditions.

Before SPD implementation, consumables management relied on an incomplete hospital information system (HIS), decentralized stock-holding locations, manual requisition procedures, spreadsheet-assisted inventory reconciliation, and manually performed periodic inventory counts.

4. Intervention: Hospital-operated SPD logistics model

The intervention consisted of implementation of a hospital-operated SPD logistics-management model integrating software infrastructure, barcode-enabled hardware systems, and operational-governance workflows.

An SPD implementation team was established, consisting of one project lead, two procurement officers, two warehouse managers, one information-technology engineer, and one quality supervisor. Standardized item master-data parameters—including unique item identifiers, supplier information, pricing, storage requirements, expiration parameters, and barcode encoding—were configured within the SPD platform.

Bidirectional synchronization between the SPD system and the HIS was implemented to enable real-time synchronization of requisitions, inventory movement records, dispensing documentation, and billing reconciliation.

Barcode-enabled smart storage cabinets were installed in clinical areas to support automated stock reduction during consumable dispensing. Relevant staff received standardized workflow training before implementation. Compliance with SPD workflows was monitored through routine departmental supervision and system-based traceability procedures.

Temperature-sensitive consumables were stored in monitored refrigeration units in accordance with institutional storage requirements. Refrigeration temperatures were routinely monitored to maintain recommended storage ranges, and deviations were managed in accordance with departmental consumables governance protocols.

Role-based access control (RBAC) was implemented to restrict access to the SPD system to authorized personnel. Before system activation, two complete-cycle simulation tests were conducted, including requisition submission, inventory receipt, consumable dispensing, billing reconciliation, and item returns. All personnel received role-specific training before the system went live. Daily operational briefings were conducted during the first two weeks after implementation to address technical and workflow issues.

For this study, delivery error was defined as any discrepancy between requested and delivered consumables, including mismatches in quantity, specification, or item type. Irrational usage refers to consumable utilization inconsistent with departmental consumption standards or clinical indications. Integrity incidents included compromised packaging, incomplete documentation, and failures in consumable traceability. Dispensing anomalies were defined as irregularities during the dispensing process, including mismatched items, missing items, or documentation discrepancies.

5. Data sources and eligibility criteria

Staff workload and service satisfaction were evaluated using weekly surveys administered to all personnel involved in consumables management within the Department of Stomatology (N = 18). Surveys were conducted throughout the 52-week observation period.

The maximum number of survey observations was 468 per study period (18 staff × 26 weeks). During the pre-implementation phase, 448 of 468 questionnaires were completed (95.7%), compared with 452 of 468 questionnaires (96.6%) during the post-implementation phase.

Staff workload was assessed using structured weekly time logs documenting hours spent on consumables-related activities, including requisition preparation, stock receiving, manual reconciliation, expiration management, and administrative documentation. Weekly workload was calculated as the mean number of hours per week across responding staff.

Delivery error rate was calculated using the following equation:

Delivery Error Rate (%) = (Number of Erroneous Dispensing Events ÷ Total Dispensing Events) × 100

Service satisfaction was evaluated using a five-item questionnaire scored on a 0–100 scale that assessed delivery timeliness, dispensing accuracy, product availability, requisition-workflow convenience, and overall consumables management satisfaction. Weekly satisfaction scores were calculated as the mean completed-item score.

Because repeated measurements were obtained from the same personnel, workload, and satisfaction outcomes were aggregated at the weekly level before statistical analysis to avoid treating repeated responses as independent observations.

6. Statistical analysis

All statistical analyses were performed using R software (version 4.3.1). Continuous variables were reported as mean ± standard deviation or median and interquartile range, as appropriate. Categorical variables were summarized using frequencies and percentages.

When normality assumptions were satisfied, paired t-tests were used to compare continuous outcomes before and after implementation. Otherwise, Wilcoxon signed-rank tests were applied. Two-proportion z-tests or Fisher’s exact tests were used for proportional outcomes, depending on expected cell counts.

Multivariable regression analyses were prespecified to adjust for potential confounding variables. Linear regression models were used to evaluate weekly mean delivery time, with implementation status as the primary independent variable and weekly consumable volume and clinical-visit frequency included as covariates. Logistic regression models were used to evaluate delivery-error events, adjusting for implementation status, weekly consumable volume, and item category. Adjusted odds ratios (ORs) and 95% confidence intervals (CIs) were reported.

For outcomes with monthly aggregation and sufficient time points, interrupted time-series segmented regression analysis was performed using the following model:

Yt = β0 + β1(Timet) + β2(Interventiont) + β3(Time After Interventiont) + εt

Where Yt represents the outcome at time point t; Timet represents the continuous time sequence; Interventiont represents the pre-implementation (0) and post-implementation (1) periods; Time After Interventiont represents elapsed time after SPD implementation; and εt represents the error term.

Autocorrelation was evaluated using the Durbin–Watson statistic, and Newey–West standard errors were applied when autocorrelation was detected. Statistical significance was defined as a two-sided p-value < 0.05. For segmented regression analyses, regression coefficients (β), standard errors (SEs), and 95% confidence intervals (CIs) were reported for both immediate level changes (β2) and post-intervention slope changes (β3).

Results

Study activity and volume
Clinical activity remained stable throughout the study period, suggesting that observed operational changes were unlikely to be attributable to differences in patient volume. Weekly surveys were administered to 18 staff members involved in consumables management. Of the 468 possible questionnaires per study period, 448 were completed during the pre-implementation phase (95.7%) and 452 during the post-implementation phase (96.6%). Staff-related outcomes were analyzed using we...

Discussion

In this single-center quasi-experimental evaluation, implementation of a hospital-operated Supply–Processing–Distribution (SPD) logistics-management model was associated with significant improvements in consumables-management performance within the stomatology department. Following implementation, delivery-error rates decreased substantially, delivery time was reduced, staff workload associated with consumables management declined, and service-satisfaction scores improved. Inventory capital occupation also de...

Materials

List of materials used in this article

Name	Company	Catalog Number	Comments
Barcode scanner	Zebra Technologies	DS2208	Used to scan item barcodes during dispensing and stock reconciliation
Computer workstation	Lenovo	ThinkCentre M720	Used for SPD system access, data entry, and monitoring
Hospital Information System (HIS)	Hospital Information Technology Department	N/A	Integrated with SPD platform for bidirectional synchronization of requisitions, billing, and inventory data
Medical-grade refrigerator	Haier Biomedical	HYC-390	Temperature-monitored refrigerator for storage of temperature-sensitive medical consumables
R statistical software	R Foundation for Statistical Computing	Version 4.3.1	Used for statistical analysis including regression and interrupted time series analysis
Smart storage cabinet	HoloTech Medical Systems	SC-200	Barcode-enabled cabinet used for point-of-care storage and automated stock deduction
SPD logistics management software platform	Hospital Information Technology Department	N/A	Software used for inventory management, requisition processing, and dispensing transaction recording
Staff workload and satisfaction survey questionnaire	Department of Stomatology	N/A	Weekly survey instrument used to collect staff workload hours and satisfaction scores