Evidence map›Paper›PMID 36373874›Full record

ArticleInternational journal for quality in health care : journal of the International Society for Quality in Health Care2022

Application of DRGs in hospital medical record management and its impact on service quality.

Qin Zhang, Xiaodong Li

Abstract read
In one paragraph

Article in International journal for quality in health care : journal of the International Society for Quality in Health Care, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

12 citing papers in PubMed, 1 synthesis or guideline pooled it.

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4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Qin ZhangDepartment of Medical Records Statistics, Western Hospital of Beijing Chaoyang Hospital Affiliated to Capital Medical University, No. 5, Jingyuan Road, Shijingshan District, Beijing 100043, China.
Xiaodong LiDepartment of Medical Records Statistics, Western Hospital of Beijing Chaoyang Hospital Affiliated to Capital Medical University, No. 5, Jingyuan Road, Shijingshan District, Beijing 100043, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTo explore the application of diagnosis-related groups (DRGs) in hospital medical record management and the impact on service quality.

objectiveThis study introduced DGRs management into hospital medical record management in order to improve the quality of hospital medical record management.

methodThe medical record management of our hospital was analysed retrospectively between August 2020 and April 2021. A total of 7263 cases without DRG management before January 2021 were included in a control group, and 7922 cases with DRG management after January 2021 were included in a study group. The error rate of medical records, the specific error items and the scores of service capability, service efficiency and service quality were compared along with the comprehensive scores of the two groups.

resultsThe error rate of medical records in the study group was significantly lower than that in the control group (19.35% vs. 31.24%, P < 0.05). The error rates in terms of diagnosis on admission, surgical procedures, main diagnosis and other diagnoses in the study group were significantly lower than those in the control group. The scores for service ability, service efficiency and service quality were significantly higher in the study group than in the control group (P < 0.05). The comprehensive evaluation score of the study group was significantly higher than that of the control group (P < 0.01).

conclusionApplying DRGs in the hospital medical record management can effectively reduce the error rate of medical records and improve the quality of hospital services.

Indexed as

Diagnosis-Related GroupsMedical RecordsHospitalizationHospitalsHumansRetrospective Studiescase–control studydiagnosis-related groupshospital medical record managementmedical service qualityretrospective study

Identifiers

PMID36373874
PMCPMC9718026

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.