Irrational pharmacotherapy and increasing pharmacy costs remain major concerns in healthcare systems. Pharmacists are expected to employ diagnosis-related group (DRG) data to analyse inpatient pharmacy utilization.
OBJECTIVE:
This project aimed to pilot an efficient pharmacist-led programme to analyse factors related to pharmacy expenses, evaluate the rational use of drugs in batch processing, and make further interventions based on DRG data.
METHODS:
Patients from the OB25 (caesarean section without comorbidities or complications) DRG were selected in 2018, and the most relevant factors were identified through statistical analysis. Interventions were implemented by sending monthly reports on prescribing data and drug review results for the same DRGs to the department starting in 2019. Pre–post comparisons were conducted to demonstrate changes in pharmacy costs and appropriateness at a tertiary teaching hospital with 2,300 beds in China.
RESULTS:
A total of 1,110 patients were identified from the OB25 DRG data in 2018. Multivariate linear analysis indicated that the number of items prescribed and wards substantially influenced pharmacy expenditure. Drugs labelled as vital, essential, and non-essential revealed that 46.6% of total pharmacy costs were spent on non-essential drugs, whereas 38.7% were spent on vital drugs. The use of inappropriate pharmaceuticals and drug items was substantially reduced, and the average pharmacy cost after intervention was 336.7 RMB in 2020. The benefit–cost ratio of the programme was 9.86.
CONCLUSION:
Interventions based on DRG data are highly efficient and feasible for reducing inpatient pharmacy costs and non-essential drug use.
KadaikunnanSVijayaragavanPRathiMABalamuralikrishnanBAlharbiNSGopalakrishnanVK, et al. Antibacterial and biofilm disruptive nonribosomal lipopeptides from Streptomyces parvulus against multidrug-resistant bacterial infections. J Infect Public Health.2024; 17(3): 450-456. doi: 10.1016/j.jiph.2024.01.001.
2.
OgajiDSNwaejikeDEbiekurajuO. Quality of Drug Prescribing and Dispensing Practices in Primary Healthcare Centres in an Urban Local Government Area in Nigeria. West Afr J Med.2023; 40(9): 925-934.
3.
CohenRGrimprelERybakAHauIMadhiFOuldaliN, et al. The principles of curative antibiotic treatments. Infect Dis Now.2023; 53(8S): 104780. doi: 10.1016/j.idnow.2023.104780.
4.
AAlfahmiAACurtainCMSalahudeenMS. Assessment of Knowledge, Attitude and Practices of the Hospital and Community Pharmacists in Saudi Arabia (Jeddah) towards Inappropriate Medication Use in Older Adults. Int J Environ Res Public Health.2023; 20(2): 1635. doi: 10.3390/ijerph20021635.
5.
WHO. Drugs and Therapeutics Committees – A Practical Guide. In: 2003.
6.
WangWHuangXZhangYWuJWangYLiL, et al. Transient Compression Injury Triggers Neuroinflammation in a New Rat Model of Acute Peripheral Neuropathic Pain. Pain Physician.2024; 27(1): E131-E145.
7.
ZengJQ. The pilot results of 47 148 cases of BJ-DRGs-based payment in China. Int J Health Plann Manage.2019; 34(4): 1386-1398. doi: 10.1002/hpm.2818.
8.
GrassFRoth-KleinerMDemartinesNAgriF. Day Admission Surgery Program in a Prospective Payment System: What Are the Financial Incentives? Health Serv Insights.2024; 17: 11786329231222970. doi: 10.1177/11786329231222970.
9.
WangHGaoCDantonaCHullBSunJ. DRG-LLaMA: tuning LLaMA model to predict diagnosis-related group for hospitalized patients. NPJ Digit Med.2024; 7(1): 16. doi: 10.1038/s41746-023-00989-3.
10.
MilsteinRSchreyöggJ. The end of an era? Activity-based funding based on diagnosis-related groups: A review of payment reforms in the inpatient sector in 10 high-income countries. Health Policy. 2024; 141: 104990. doi: 10.1016/j.healthpol.2023.104990.
11.
QuinnKBredfeldtC. The Revival of Us Hospital Care, 2004–2019. Med Care.2024. doi: 10.1097/MLR.0000000000.001967.
12.
SunXLZhangYTHuX. Thinking about the role of clinical pharmacists in the implementation of DRG. Chinese Licensed Pharmacist.2020; 17(8): 8-10.
13.
Ali JadooSAAljunidSMNurAMAhmedZVan DortD. Development of MY-DRG casemix pharmacy service weights in UKM Medical Centre in Malaysia. Daru.2015; 23(1): 14. doi: 10.1186/s40199-014-0075-4.
14.
DuckettSJ. Casemix funding for acute hospital inpatient services in Australia. Med J Aust.1998; 169: S17-21. doi: 10.5694/j.1326-5377.1998.tb123470.x.
15.
ASHP guidelines on a standardized method for pharmaceutical care. American Society of Health-System Pharmacists. Am J Health Syst Pharm.1996; 53(14): 1713-1716. doi: 10.1093/ajhp/53.14.1713.
16.
GoldsmithDJFitchK. The Normative Context of Advice as Social Support. Human Communication Research.1997; 23: 454-76.
17.
O’NealBCCouldryRJWilkinsonSTCannellaCAWilliamsCBScottLA, et al. Leveraging drug-utilization and external benchmarking data to drive change in prescribing behaviors. Am J Health Syst Pharm.2012; 69: 1916-1922. doi: 10.2146/ajhp110429.
18.
DenvirPBrewerJ. “How dare you question what I use to treat this patient”: Student pharmacists’ reflections on the challenges of communicating recommendations to physicians in interdisciplinary health care settings. Health Commun.2015; 30: 504-512. doi: 10.1080/10410236.2013.868858.
19.
AshworthMArmstrongDColwillSCohenABalazsJ. Motivating general practitioners to change their prescribing: the incentive of working together. J Clin Pharm Ther.2000; 25: 119-24. doi: 10.1046/j.1365-2710.2000.00270.x.
20.
SeeHQChanJNLingSJGanSCLeongCOMaiCW. Advancing Pharmacy Service using Big Data – Are We Fully Utilising the Big Data’s Potential Yet? J Pharm Pharm Sci.2018; 21(1): 217-221. doi: 10.18433/jpps29869.
21.
StokesLBRogersJWHertigJBWeberRJ. Big Data: Implications for Health System Pharmacy. Hosp Pharm.2016; 51: 599-603. doi: 10.1310/hpj5107-599.
22.
LiuHMChenFCLiZHZhuXSLiPLiC, et al. Effect of comprehensive management and control interventions for diagnosisi related groups paying in reducing the proportion of hospitalized medicines. Central South Pharmacy.2019; 17(6): 976-980. doi: 10.7539/j.issn.1672-2981.2019.06.044.
23.
NoormandiAKarimzadehIMirjaliliMKhaliliH. Clinical and economic impacts of clinical pharmacists’ interventions in Iran: a systematic review. Daru.2019; 27(1): 361-378. doi: 10.1007/s40199-019-00245-8.
24.
XiongLLiuHMLiCHuangLJZhuXSMaL, et al. Intervention effect analysis of the application of proton pump inhibitors in hospitalized patients in our hospital before and after carrying out prescription comments, medical insurance control costs and DRGs by clinical pharmacists. Chinese Journal of Hospital Pharmacy.2019; 39(4): 394-398. doi: 10.13286/j.cnki.chinhosppharmacyj.2019.04.18.
25.
AbushanabDAtchanMElajezRElshafeiMAbdelbariAAl HailM, et al. Economic impact of clinical pharmacist interventions in a general tertiary hospital in Qatar. PLoS One.2023; 18(6): e0286419. doi: 10.1371/journal.pone.0286419.
Al-JunidSMEzatWPSSuriantiS. Prescribing patterns and drug cost among cardiovascular patients in Hospital Universiti Kebangsaan Malaysia. Med J Malaysia.2007; 62: 59-65.
28.
VukovićDŠumarSDupovacSBadnjevićA. Cost Effectiveness Analysis of Medical Devices in Legal Metrology System. In: BadnjevićACifrekMMagjarevićRDžemićZ, editors. Inspection of Medical Devices. Series in Biomedical Engineering. Springer, Cham; 2024. pp. 399-415. doi: 10.1007/978-3-031-43444-0_16.
29.
BadnjevicAGurbetaLCifrekMPecchiaL. Pre-classification process symptom questionnaire based on fuzzy logic for pulmonary function test cost reduction. In: BadnjevicA, editors. CMBEBIH 2017. IFMBE Proceedings, vol 62. Springer, Singapore; 2017. pp. 608-616. doi: 10.1007/978-981-10-4166-2_92.
30.
GurbetaLVukovicDDžemicZBadnjevicA. Legal Metrology Procedures for Increasing Safety and Performance Characteristics with Cost Benefits Analysis: Case Study Dialysis Machines. In: LhotskaLSukupovaLLackovićIIbbottG, editors. World Congress on Medical Physics and Biomedical Engineering. IFMBE Proceedings, vol 68/2. Springer, Singapore; 2019. pp. 55-59. doi: 10.1007/978-981-10-9038-7_11.
