The global transition toward value-based healthcare has catalyzed widespread adoption of prospective payment systems, including Diagnosis-Related Groups (DRGs) and Diagnosis-Intervention Packet (DIP) models.1 In 2019, China’s National Healthcare Security Administration initiated a nationwide pilot program for DRG payment reform, designating selected cities to advance scientific, refined, and informatized healthcare management.2 By bundling costs for specific diagnoses, these payment models incentivize hospitals to optimize resource allocation, shifting focus from volume-driven to outcome-oriented care.3
The implementation of DRG/DIP reforms has profoundly influenced hospital informatization, as robust data infrastructure is essential for accurate disease coding, cost accounting, and performance monitoring.4 However, primary healthcare institutions face systemic challenges under these policies, including severe pharmacist shortages, limited technological access, and financial constraints.5 A 2022 survey revealed that over 60% of primary hospitals in China operate with fewer than three full-time pharmacists, hindering manual prescription audits and medication reconciliation.6 These workforce limitations are particularly pronounced in low- and middle-income countries (LMICs), where clinical pharmacy services remain underdeveloped.7
Pharmaceutical information management systems (PIMS) offer a potential solution by leveraging real-time clinical decision support, automated drug utilization alerts, and multidisciplinary collaboration.8 Systematic reviews have demonstrated that health information technology (HIT) interventions can improve medication safety and reduce prescribing errors in various healthcare settings.9,10 Clinical decision support systems (CDSS) have shown particular promise in antimicrobial stewardship, with evidence suggesting improved guideline adherence and reduced inappropriate antibiotic prescribing.11,12
Despite these advances, evidence remains scarce on the applicability of PIMS in resource-limited primary hospitals, where workflow integration and staff adaptability pose unique barriers.13 While tertiary hospitals in high-income countries have successfully implemented comprehensive antimicrobial stewardship programs (ASPs),14 primary care settings in LMICs face distinct challenges including inadequate human resources, limited access to specialists, and insufficient information technology infrastructure.15
This study evaluates a multifaceted intervention incorporating PIMS within a multidisciplinary framework in a primary hospital setting. We hypothesized that this integrated approach would improve rational drug use and financial performance under DRG/DIP payment models. By examining implementation outcomes in a resource-constrained environment, we aim to contribute evidence on scalable intervention models for healthcare systems undergoing similar payment reforms.
Methods
Study design and setting
A quasi-experimental study with historical controls was conducted at Guangyuan First People’s Hospital, a primary-level maternal and child health institution in Sichuan Province, China. Data were collected from January 2022 to December 2023, with the pre-intervention period (January-December 2022) serving as the control and the post-intervention period (January-December 2023) as the intervention phase.
We initially planned an interrupted time-series (ITS) design, which is widely recognized as the strongest quasi-experimental design for evaluating policy interventions.16,17 However, due to data aggregation at the monthly hospital level rather than individual patient level, segmented regression analysis accounting for level and slope changes, autocorrelation, and seasonality was not feasible.18 Consequently, we employed independent t-tests for pre-post comparisons of monthly aggregated data. This analytical approach has significant limitations: it does not account for underlying time trends, secular changes, or concurrent events that may have influenced outcomes independently of the intervention.19,20
Intervention components
The intervention was a bundled package implemented in July 2022, comprising five integrated components:
(1) Multidisciplinary Team (MDT) Framework: A Pharmaceutical Administration Committee coordinated pharmacists, clinicians, nurses, IT specialists, and medical insurance administrators to optimize drug selection and cost control.
(2) Real-Time Decision Support: A pre-review knowledge base with automated alerts for non-formulary drugs, tiered warnings for irrational prescriptions (critical/moderate/minor), and hospital information system (HIS) integration with sales limit alerts.
(3) Clinical Pharmacist Activities: Ward rounds, consultations, prescription interception, and provider education.
(4) Training and Feedback: Monthly DRG-focused workshops and Plan-Do-Check-Act (PDCA) cycles analyzing insurance rejections.
(5) Clinical Pathway Optimization: Standardized drug order templates aligned with DRG cost benchmarks.
It is important to note that effects cannot be attributed solely to PIMS, as the intervention comprised multiple concurrent components operating synergistically.
Data sources and outcome measures
Drug utilization data were extracted from electronic health records (EHR) and pharmacy management systems. Outcomes included: (1) drug costs per outpatient and inpatient encounter; (2) antimicrobial use intensity (DDD/100 bed-days), calculated according to World Health Organization (WHO) guidelines; (3) prescription rationality rates assessed via blinded peer review by two senior pharmacists using hospital-approved criteria, with inter-rater reliability of 0.89 (Kappa statistic); and (4) DRG settlement balance.
Statistical analysis
Data were analyzed using SPSS version 22.0 (IBM Corp., Armonk, NY, USA). Continuous variables are expressed as mean ± standard deviation and compared via independent t-tests. Normality of data distribution was confirmed using Shapiro-Wilk tests. Statistical significance was set at p<0.05 (two-tailed). We acknowledge that this approach does not adjust for potential confounders including case-mix changes, seasonal variation, or concurrent policy reforms implemented during the study period.
Results
Drug utilization outcomes
Post-intervention, average outpatient drug costs decreased significantly (33.48±3.67 vs. 39.29±5.52 yuan, p=0.006), representing a 15.3% reduction. Inpatient drug costs also declined (524.29±48.09 vs. 572.78±50.14 yuan, p=0.024). The proportion of drug costs in total treatment expenses decreased for both outpatients (12.19% vs. 14.04%, p=0.036) and inpatients (15.61% vs. 16.63%, p=0.199).
Essential drug utilization rates increased significantly for outpatients (43.31% vs. 37.28%, p<0.001) and inpatients (72.79% vs. 69.35%, p=0.008). Centralized procurement drug utilization also improved. Antimicrobial use intensity among inpatients declined from 48.97±6.02 to 43.71±3.06 DDD/100 bed-days (p=0.013). Table 1 summarizes the key drug utilization outcomes.
Prescription rationality
Prescription review compliance improved significantly from 93.67±2.49% to 97.50±1.13% (p<0.001), and medical order review compliance increased from 90.67±4.58% to 94.86±2.96% (p=0.014). The proportion of problem prescriptions decreased from 9.48% to 6.48% hospital-wide, with the most substantial reductions observed in ENT (18.17 percentage point decrease) and Anesthesiology (18.09 percentage point decrease) departments (Table 2).
Financial Outcomes
DRG settlement improved from a loss of ¥394,800 in 2022 to a surplus of ¥198,700 in 2023. The proportion of drug-related insurance claim rejections decreased from 0.13% to 0.02%. However, these financial results are presented as absolute figures without standardization by DRG weight, case volume, or inflation adjustment, limiting comparability (Table 3).
Discussion
This study evaluated a multifaceted intervention incorporating PIMS within a multidisciplinary framework in a primary hospital setting. The findings indicate improvements in drug utilization indicators, prescription rationality, and financial performance following intervention implementation. However, several methodological limitations must be acknowledged when interpreting these results.
The primary limitation concerns internal validity. Although described as a quasi-experimental study, the analysis relied on simple pre-post comparisons without accounting for underlying time trends, seasonality, or autocorrelation. A true interrupted time-series analysis would have modeled changes in level and slope, but this was precluded by data aggregation at the hospital level.18,19
Furthermore, we could not adjust for potential confounders including: (1) case-mix changes between 2022 and 2023; (2) concurrent policy reforms implemented in 2023; (3) seasonal variation in patient volumes; and (4) staffing changes. Without such adjustments, attributing observed improvements solely to the intervention is problematic. The single-hospital design also limits generalizability to other settings.
The intervention was a bundled package comprising MDT restructuring, real-time alerts, pharmacist rounds, training, PDCA cycles, formulary enforcement, and pathway optimization. It is therefore misleading to attribute effects solely to PIMS. The relative contribution of each component remains unknown, and synergistic effects between components may exist. This complexity is consistent with findings from systematic reviews of antimicrobial stewardship programs, which have identified that multifaceted interventions tend to be more effective than single-component approaches.11,12,21
The observed improvements in essential drug utilization and antimicrobial use intensity align with findings from previous studies demonstrating that pharmacist-led interventions combined with decision support systems can improve prescribing practices.9,10 The reduction in drug costs without compensatory increases in other cost categories suggests that savings were achieved through optimization rather than indiscriminate cost-cutting.
Limitations
Prescription rationality assessment relied on blinded peer review by hospital pharmacists using institution-specific criteria. While inter-rater reliability was acceptable (Kappa=0.89), the criteria may not be generalizable to other settings. Antimicrobial use intensity calculations did not account for patient acuity or disease severity changes. Financial outcomes were not standardized by DRG weight or case volume, potentially reflecting case-mix shifts rather than true efficiency gains.
Implications for policy and practice
Despite these limitations, the findings suggest that integrated interventions combining PIMS with pharmacist-led activities may support rational drug use in resource-constrained primary care settings. For policymakers, this highlights the potential of health information technology to complement limited pharmacy workforce capacity, a challenge particularly relevant in LMICs.7,15 The cost-efficiency of the intervention—with upfront costs offset by long-term savings from reduced insurance rejections and DRG penalties—supports scalability in similar settings.
The findings also contribute to the growing body of evidence on DRG/DIP payment reform impacts in China.1,16,17 As China continues to expand DRG/DIP coverage to over 90% of cities by 2025, scalable, software-driven models offer a viable strategy to ensure fiscal sustainability without compromising care quality.
Future research directions
Future research should employ more rigorous quasi-experimental designs across multiple sites, with patient-level data enabling segmented regression analysis and adjustment for case-mix and confounding factors.18,19 Long-term follow-up is needed to assess the sustainability of observed effects and potential unintended consequences. Economic evaluations incorporating implementation costs and societal perspectives would strengthen the evidence base for policy decisions.
Conclusions
This multifaceted intervention incorporating PIMS within a multidisciplinary framework was associated with improved drug use indicators and financial performance in a primary hospital setting. However, methodological limitations—including the inability to conduct segmented regression analysis, lack of case-mix adjustment, and single-site design—preclude strong causal inference. These preliminary findings suggest potential benefits of integrating PIMS with pharmacist-led interventions in resource-constrained primary care settings and support further evaluation using more robust study designs.
Acknowledgements
All authors appreciatively acknowledge the We are grateful to all participants and staff involved in this study. the Sichuan Hospital Association (No. 22055) and Scientific Researching Fund of The First People’s Hospital of Guangyuan.
Ethics statement
Informed consent was obtained from all participants, and the study protocol was approved by the scientific ethical committee of The First People’s Hospital of Guangyuan, Sichuan, China. All methods were carried out in accordance with relevant guidelines and regulations.
All the authors gave unanimous consent for publication.
Data availability
The data of our research are shown in this paper, which were used under permit for this study.
Funding
The 2022 Young Pharmacists Research Special Fund Project of Sichuan Hospital Association (No. 22055) and Scientific Researching Fund of The First People’s Hospital of Guangyuan.
Authors’ contributions
Song Zhang and Gang Ma conceived and designed the study. Yuanyuan Pu, Nanping Xiao, Yue Zhao and Hanjun He acted as principal investigators at study sites, performed the experiments, recruited patients, and collected data. Song Zhang wrote the paper.Yuanyuan Pu reviewed and edited the manuscript. All authors reviewed and approved the final manuscript.
Disclosure of interest
The authors completed the ICMJE Disclosure of Interest Form (available upon request from the corresponding author) and disclose no relevant interests.
Correspondence to:
Gang Ma
Department of Pharmacy, Guangyuan First People’s Hospital
Guangyuan 628017, Sichuan, China
377699921@qq.com