Evidence map›Paper›PMID 36035333›Full record

ArticlePerspectives in health information managemen2022

Application of Failure Mode and Effects Analysis in Managing Medical Records for Accuracy of INA-CBGs Health Insurance Claims in a Tertiary Hospital in Indonesia.

Yahya Marpaung, Werry Darta Taifur, Nur Afrainin Syah, Yusirwan Yusuf

Open access · greenAbstract read
In one paragraph

Article in Perspectives in health information managemen, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
1.0field-weighted citation impact, top 22% of its field
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

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed, 5 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

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

4 authors.

Yahya Marpaung
Werry Darta Taifur
Nur Afrainin Syah
Yusirwan Yusuf

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: Awareness of the importance of social security systems continues to grow in Indonesia, as mandated by the amendment of the 1945 Indonesian Constitution Article 34 paragraph 2, which states the obligation of the Indonesian government to develop and implement a social security system for all Indonesian people. This study aims to evaluate the effectiveness of applying failure modes and effects analysis (FMEA) in managing inpatient medical records at the Dr. M. Djamil Padang Central General Hospital. Material Methods: This is a comparative research study that uses a retrospective approach and compares the data between 2017 and 2018 inpatient National Health Insurance (NHI) patient medical records. Study samples include randomly selected 24,005 files. Results: The results showed a decrease in problematic claims by 13 percent and an increase in receipt of claims paid by 87 percent. There is a significant difference between the data in 2017 and 2018 in problematic claim decrease (p=0.000) and claim acceptance increase (p=0.000). Discussion: It was found that the redesign process of the formation of hospital claims will make hospitals more organized, precise, effective, and efficient, therefore positively impacting hospital income. In addition, the redesign was carried out because of the large number of Social Security Administrator for Health patients; thus, it greatly affected hospital income. Implication for Health Policies: The FMEA medical record flow process is very effective and can thus be implemented in hospitals.

Indexed as

Healthcare Failure Mode and Effect AnalysisHumansIndonesiaInsurance, HealthMedical RecordsRetrospective StudiesTertiary Care CentersFMEAhealth insurancemedical recordproblematic claimsreceipts

Identifiers

PMID36035333
PMCPMC9335167
OpenAlexW4293677846

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.