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.
Keywords: FMEA, health insurance, medical record, problematic claims, receipts
Awareness of the importance of social security systems continues to grow 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. The inclusion of the social security system into the constitutional amendment, followed by the issuance of Law Number 40 of 2004 on the National Social Security System (NSSS), indicates that the government and the related stakeholders have a strong commitment to actualize social welfare for all its people.1 The implementation of the universal health coverage (UHC), managed by a nonprofit organization called Badan Penyelenggara Jaminan Sosial Kesehatan (BPJS-Kesehatan), is one of the activities of NSSS. In this system, primary care facilities are paid by a capitation system. On the other hand, secondary and tertiary care facilities are paid by a case mix/diagnosis-related group scheme (INA-CBGs).2
INA-CBGs stands for Indonesian Case Base Groups, an application used by secondary and tertiary healthcare hospitals for submitting payment claims to BPJS-Kesehatan for healthcare services they have delivered for BPJS-Kesehatan participants. INA-CBGs is a payment method for patient care based on relatively similar diagnoses or cases. Before the payment is made by the BPJS-Kesehatan to the hospitals, the submitted claims are verified. The verification process is conducted to assess the validity and eligibility of the submitted claims, as well as the completeness of supporting documents. Patients’ medical records are important documents in this process. The BPJS-Kesehatan cannot make payment for invalid, ineligible, and/or incomplete claims, which will be returned to the hospital, resulting in pending payments. The purposes of assessing claims are as follows: assess the cost of medical services being claimed, evaluate the insurance members’ benefits, and prevent both intentional and unintentional fraud.3
Data collected in a government tertiary hospital in Padang, Indonesia, showed that there were 5,897 pending claims among the 23,463 claims submitted in 2017 (approximately 25 percent). Risk register, a document containing risks that may occur in the unit based on the category and scope of risk management in the hospital, showed that these pending claims were mainly related to incomplete and inaccurate medical records. Medical records are important documents in claim verification because data written in the records are used by BPJS-Kesehatan to assess the validity and eligibility of claims. Moreover, medical records serve as the basis for making payment to the healthcare facilities. Pending payments potentially interfere with hospital finances and the quality of care they deliver for patients.
Failure mode and effects analysis (FMEA) is a technique applied to improve a system by predicting the potential failures in the system and their solutions. FMEA is a team-based, systematic, and proactive technique applied to prevent problems both on processes and products before they occur. FMEA can provide not only an overview of the problems that might occur but also the severity of the consequences.4 According to the Joint Commission International (JCI), the FMEA model consists of eight steps: 1) determining a high-risk process that needs improvement and forming a team; 2) describing the process flow; 3) brainstorming failure modes and their effects on the process flow; 4) scaling up the failure mode priority; 5) identifying the root cause of the failure mode; 6) redesigning the process; 7) analyzing and testing the new processes; and 8) monitoring the new process implementation.
In June 2017, FMEA was conducted in a Padang government tertiary hospital to solve the problem regarding 5,897 pending claims due to incomplete and inaccurate patient medical records. Furthermore, 25 percent of INA-CBGs claims were pending for the same reason. The incomplete and inaccurate medical records are due to the overlapping medical record flow factors (back and forth). This research aimed to evaluate the effectiveness of applying FMEA in managing medical record for the accuracy of INA-CBGs health insurance claims in a tertiary hospital in Indonesia. Using the FMEA model, together with the formation of a team in the redesign process, will help in the regularity, accuracy, efficiency, and effectiveness of medical record management.
Medical records include documents regarding patient identity, examination, treatment, actions, and other services that have been provided to patients.5 The filling out of medical records helps in the order of the administration and in improving the quality of health services in hospitals. To achieve this, at hospitals, medical records are filled out by doctors and nurses according to the results of the medical activities that have been carried out; therefore, medical records and documents should be completely filled out to produce accurate information and sustainability.6
The process of determining the INA-CBGs code and its rates begins when the patient is discharged from the hospital. The data that must be entered in the INA-CBGs software is variable data that can be taken from medical resumes and patient social data, both of which can be collected manually or through a hospital management information system (HMIS) for hospitals that already have a HMIS. After the variable data is entered into the INA-CBGs software, grouping is done to produce the INA-CBGs code along with the per-patient rate.7
According to Ilyas, the claim is defined as a request from one of two parties that have a bond, so that their rights are fulfilled. One of the two parties will submit their claim to the other party in accordance with the agreement or policy provisions agreed upon by both parties.8 The purpose of the claim is to pay all valid claims, identify the possibility of fraud, whether intentional (fraud) or unintentional (abuse) in making a claim, meeting government regulations, avoiding or preventing lawsuits, coordinating benefit, and controlling the cost of claims (claim cost).9
The definition of a claim not worth paying is refusing to pay a claim to a provider that does not follow the policies/procedures of the insurance company or is waiting for additional information.10 The NHI program is a guarantee system organized by the government through a social insurance mechanism that is provided to all Indonesians.
Meanwhile, FMEA is a systematic approach that implements a labeling method by determining modes of failure, causes of failure, and effects of these failures to help in the flow process. This approach is used by engineers to identify potential failure modes and their effects. FMEA is an evaluation technique that assesses the reliability of a system and determines the effects of the failure of the system. Failures are classified based on the impact they have on the success of a mission of a system. Therefore, to overcome this failure, FMEA is used by Dr. M. Djamil Central General Hospital in the flow process of inpatient medical record file.
Dr. M. Djamil Central General Hospital is the central general hospital in Padang, West Sumatera, Indonesia. The hospital has 800 beds and serves general patients, BPJS, and insurance. Admission of patients at the Polyclinic of Dr. M. Djamil Central General Hospital in 2017 consisted of 14,096 new visitors and 152,993 old visitors. In 2018, it consisted of 35,107 new visitors and 124,576 old visitors.
After the doctor’s approval, the patient returns home. Then, when the patient returns home, the hospital must immediately make a patient claim file. From the flow process above, patient claims are taken by the medical record unit to the verification and finance unit. The process of submitting this claim usually takes 20 days. This is due to flow factors (back and forth) between the medical record and verification units. Then, claims are forwarded to the finance unit and proceed again to the medical record unit. Therefore, applying FMEA can help hospitals by being verified by a mixed team of existing hospital cases.
In implementing changes in the flow of medical services, the authors found distinction in problematic claims in NHI inpatients at Dr. M. Djamil Padang Central General Hospital from 2017 to 2018. After the redesign, the not problematic 74 percent in 2017 increased to 87 percent in 2018, which is a very significant increase. The problematic claims in 2017 were 26 percent; after being fixed, it dropped to 13 percent in 2018, which is same as the unpaid claim in 2017 (25 percent), which became 17 percent in 2018. The 75 percent automatically paid claims in 2017 increased and became 83 percent in 2018. When the changes were implemented in the flow of medical record services, we obtained the differences in problematic claims at the Dr. M. Djamil Padang Central General Hospital during 2017 to 2018. In 2017, there were 74 percent non-problematic claims, which increased to 87 percent in 2018. Problematic claims decreased from 26 percent in 2017 to 13 percent in 2018. This was also accompanied by the decrease of non-problematic claims from 25 percent in 2017 to 17 percent in 2018, while paid claims increased from 75 percent in 2017 to 83 percent in 2018.
After the changes in the flow, claim file printing was made faster by hospitals. The claim files that are entered at the inpatient unit are directly processed by the case mix team. After processing, the claim files are directly given to the finance department within one day after the claim file is complete. Claim files that arrived at finance are first given to the BPJS verifier, which is then examined by the hospital fraud team.
In Iran, there are also those who have implemented FMEA, where the results of the research by Dastjerdi, HA., et al. (2017) showed that his research focused on processes carried out in pediatric and radiology wards as well as on nursing staff.11 His research also expresses all the steps of implementing the FMEA model and applies strategies and interventions and risk priority numbers to determine the level of effectiveness of the model.
Research results Vida, MA., et al. (2017) showed the results that there were 99 failure modes associated with 80 side effects and 129 identified causes in eight pharmacy areas/subhospital processes.12 The three areas with the highest percentage of failure modes are inpatient pharmaceutical care, pharmaceutical laboratories, and pharmaceutical technology and medication management. There are also 25 failure modes with an RPI score of 20 and 25 failure modes, with the highest frequency and criticality score classified as priority.
This study was conducted at Dr. M. Djamil Padang Central General Hospital from May 2019 to July 2019. This is comparative research that used a retrospective approach that compared the medical records of inpatient NHI in 2017 and 2018. The study sample included all NHI inpatient medical record documents submitted to BPJS in 2017 (29,424 files) and in 2018 (24,005 files). The study variables were the claim payment receipt and claims that were problematic. The medical record document included claim files by the hospital to BPJS. The BPJS will provide feedback on the claim submission document. We obtained data on the receipt of claims paid and claims that are problematic in accordance with those sent by BPJS.
To determine the frequency distribution of each variable, univariate analysis in the form of a frequency distribution table was used to evaluate the variable claim receipt paid and problematic claims of NHI inpatients. For the bivariate statistical analysis, the McNemar’s test was used, with a significance level of 95 percent (α = 0.05). In this study, the value of p < 0.05 means that there are significant differences.
In June 2017, the eight steps of the FMEA process were started as follows: 1) determining the topic and forming team, 2) describing the process flow, 3) brainstorming failure modes and their effects on the process flow, 4) scaling up the failure mode priority, 5) identifying the root cause of the failure modes, 6) redesigning the process, and (7–8) analyzing and testing the new process, and monitoring its implementation.
Finally, in conducting an evaluation by FMEA, we compared INA-CBGs’ claim data for 2017 and 2018 (before and after the implementation of the FMEA activity) to evaluate the effectiveness of the FMEA implementation. We collected data on the number of INA-CBGs’ claim paid or unpaid by the BPJS-Kesehatan and the total rupiahs received by the hospital for inpatient services provided for the BPJS-Kesehatan member. The McNemar’s statistical analysis was applied to see the difference between the two cohorts with a significance level of 95 percent.
Based on the results of the conducted research, we have obtained the modes, effects, and causes of failure. After brainstorming with medical records, we obtained the Risk Priority Number (RPN) and the recommended actions.
Based on Table 1, the highest RPN is 280 with a failure mode consisting of the following: a) incomplete medical records with claims, b) related to incomplete medical record factors, c) the diagnosis is not included in the BPJS/IKS coverage list category, and d) the overlapping membership between BPJS and in health. Related to this problem can happen at the hospital associated with hospitals related to patients commuting to work/emergency room, while judging from the lowest RPN with a value of 80 at the lowest rank has obtained failure mode consists of medical records that have retention which has not been broken out. This will affect the stacking of medical record files in the medical record storage room.
Figure 1 illustrates the preparation of medical records and INA-CBGs’ claim before being redesigned. The failure mode is also caused by the inpatient medical record service flow that is not optimal. The patient enters and is treated. The patient returns home after being declared cured. When the patient goes home, the patient’s claim file must be immediately made by the hospital. From the flow above, the patient's claim file is brought by the medical record to the verification and fund mobilization installation. The process of submitting this claim file usually takes 20 days; this is due to the factor of going back and forth between the medical record to the verification installation, then forwarded to the mobilization of funds and returned to the medical record. If the claim is rejected, it will be corrected by returning it to the case mix team, case manager, DPJP, nurse, or returning it to the inpatient unit in the same way. In this case, the hospital redesigned the medical record and preparation of INA-CBGs’ claims with FMEA activities. Figure 2 is a redesign chart that has been designed by Dr. M. Djamil Padang Central General Hospital.
Figure 2 illustrates the preparation of medical records and INA-CBGs’ claim after being redesigned. The patient enters the first time through the registration unit, an empty medical record file from the medical record unit is given to the registration unit, after completion of registration, it is then submitted to the inpatient unit. If the patient is finished being treated, the medical record file is returned by the inpatient unit to the medical record unit.
After a flow change occurs, the hospital can print claim files faster. Claim files that are entered at the inpatient installation are immediately processed by the case mix team at the inpatient installation. After processing, the claim file from the inpatient will be sent directly to the mobilization of funds (MD) within one day after the claim file is completed. The claim file that arrives at MD before being given to the BPJS verifier is first checked by the hospital fraud team so that the claim file can be marked accepted, rejected, or pending.
Based on the chart (before and after being redesigned), the flow process of the inpatient medical record service before the redesign occurred in two places, which causes failure mode; therefore, the service flow became unfocused and ineffective. After the redesign, the service flow was improved, and coding was only carried out by the case mix team in the inpatient room.
Since the implementation of the change in the flow of medical record services, we obtained the difference in problematic claims in NHI inpatients at Dr. M. Djamil Padang Central General Hospital in 2017–2018 (Table 2).
Table 2 shows that out of the 24,005 NHI claim documents, there were 3,074 (13 percent) reductions of problem claims in 2018 from 6252 in 2017 (26 percent). The analysis result shows that the p value of 0.000 means that there is statistically significant difference between NHI’s 2017 problematic claims and 2018.
Table 2 also shows that, from the 24.005 NHI claim documents, there was an increase in claim receipt in 2018, amounting to 21.834.679.98 USD (83 percent), from 2017 amounting to 20.531.494.82 USD (75 percent). The analysis result shows that the obtained p value of 0.000 means that there is a statistically significant difference between the 2017 NHI claim receipt rate and 2018; namely, the acceptance of an increase in claims receipt from 20.368.001.54 USD in 2017 to 21.830.972.01 USD in 2018.
Steps of Evaluation
Tooranloo and Saghafi, in their study titled “Assessing the risk of hospital information system implementation using IVIF FMEA approach,” concluded that applying FMEA encouraged managers and staﬀ to use the health information system to better manage data and information, upgraded the system to the current culture of the organization, and allocated funds to support and maintain the current upgraded systems that they used.13 In this study, we have also applied this method at Dr. M. Djamil Padang Central General Hospital by following these eight steps:
Step 1: Determine the topic and form a team.
One FMEA activity is carried out at the hospital every year. Hospital risk records compiled from the units’ risk registers guide the identification of a priority process for the annual FMEA activity. Risk registers are recordings of events that can be a potential threat to patient safety in every single component of the hospital system, including operational strategy, financial, compliance, types of patients, staff, facilities, environment, and business. In 2017, the risk register indicated that the INA-CBGs’ pending claims that resulted in the hospital’s financial difficulties were the priority threats that should be solved through the FMEA activity.
A multidisciplinary team for conducting the FMEA activity was formed and formalized via the issue of an assignment letter by the managing director of the hospital. The team consisted of 14 members. Identifying the right person for the job was very important. Team members must bring a diverse mix of knowledge bases to ensure that there were different points of view for the improvement process. The team members must be committed to performance improvement and had sufficient knowledge on the processes to be corrected. Representatives from areas that may be directly affected by changes (e.g., medical record department) were included within the team.
Step 2: Describe the process flow.
The next step in the FMEA activity was the reviewing of the process in full by describing or developing diagrams in a graphical format. The multidisciplinary participation of the FMEA team members and all stakeholders involved in the process was very important to identify every steps of the process in detail. The activity resulted in a more complex process flow description than what was actually being implemented. The team found that the process was too large and complicated to manage in one diagram. Thus, the team broke down the process into subcomponents and developed individual diagrams for each of them. Each team member had to truly understand the process and sub-process components, as well as the interrelationship between the chosen FMEA process (i.e., medical record management) and other related processes in the hospital system.
Step 3: Brainstorm failure modes and their effects on the process flow.
A small group discussion was conducted to identify potential failures in the process of medical record management to meet its objectives as an effective data source for the INA-CBGs’ claim. The discussion also explored the effect of failures on patients’ safety and satisfaction, including treatment delay, death, morbidity, tissue damage, violation of regulations, and financial loss.
Step 4: Scale up the failure mode priority.
An RPN was used to assess the priority scale of each identified potential failures. RPN was measured based on three scales: severity, occurrence, and detectability. Each scale has a value in the range of 0 to 10. The multidisciplinary team discussed and determined the value of the three scales for each potential failure identified. The RPN number for each failure was the multiplication of the three scales. For example, a potential failure had 6, 5, and 4 for the severity, occurrence, and detectability scale, respectively. Thus, the RPN number for the potential failure was 6 × 5 × 4, which was 120.14 The FMEA team decided that the cutoff point of the RPN for a potential failure to be explored was 80. The potential failure with the RPN below 80 would be explored if the time was available.
Step 5: Identify the root cause of the failure modes.
The FMEA team discussed the root cause of the failure modes through brainstorming activities and drawing cause-and-effect diagrams. The activities also explored how to prevent future failures. If future failures could not be prevented, strategies to protect patients from the impact of the failures should be identified.
Step 6: Redesign the process.
The FMEA team redesigned the process of medical record management for supporting an effective preparation of the INA-CBGs’ claim to eliminate the possibility of failure (to prevent failure), increase failure detection so that the failure could not reach patients, and mitigate the impact of errors that reach patients.
Steps 7 and 8: Analyze and test the new process, and monitor its implementation.
The revised process was implemented, and its effectiveness was monitored by collecting data of INA-CBGs’ claim accuracy and percentage of claims being paid before and after the implementation of the new process designed using the FMEA activities.
Meanwhile, in their article “dP-FMEA: An innovative Failure Mode and Effects Analysis for distributed manufacturing processes,” Maisano et al. have applied FMEA by the modification that is called distributed process (dp)-FMEA.15 This method helps in managing dozens of experts without requiring them to physically meet and make collective decisions; therefore, this method is a flexible response mode that does not force experts to make detailed judgments, even in case of hesitation. Moreover, the methodology can be easily implemented. The dp-FMEA method basically still applied the principles found in the traditional FMEA. The advantage is that the dp-FMEA has a wider scope, such as for the production and manufacturing processes. Different from Dr. M. Djamil Padang Central General Hospital, the hospital uses FMEA that has been recommended by the JCI. The recommended FMEA already has the conditions set.
Implication of FMEA Evaluation
As a reinforcement in the use of FMEA, the authors compare this study to that of Yanagisawa et al., in their research about health preparedness plan for dengue detection during the 2020 summer Olympic and Paralympic games in Tokyo.16 They used the FMEA method to prepare for future problem, of which the problem that they faced were outbreaks and other disease threats that have occurred in the area before. They used the FMEA method as a form of prevention to decrease the potential of future problems. The writer assumes that this method could be applied in Dr. M. Djamil Padang Central General Hospital to prevent problems in the future.
How did the use of the FMEA method in Dr. M. Djamil Padang Central General Hospital help in solving problems such as problematic and paid claims? The use of the FMEA method is very effective in solving this situation, especially claim problems. It can be seen in Table 2 that, in 2017, the number of patients with problem claims was 6,252, which then dropped to 3,074 patients in 2018.
In addition, in the study, “Evaluating the application of FMEA technology in hospital ward” by Dastjerdi et al., medical error is one of the greatest problems in any healthcare system. The best way to prevent such problems is by identifying error and their roots.17 The FMEA technique is a prospective risk analyses method. This study is a review of risk analyses using the FMEA technique in different hospital wards and department. This paper has systematically investigated the available databases. After selecting inclusion and exclusion criteria, the related studies were found. This selection was made in two steps. First, we investigated the abstract titles, and after omitting papers that did not meet the inclusion criteria, 22 papers were finally selected, and the text was thoroughly examined. At the end, the result was obtained. The results are the examined papers had focused mostly on the process and had been conducted in the pediatric ward and radiology department, and most of the participants were nursing staff. Many of these papers attempted to express almost all the steps of model implementation, and after implementing the strategies and intervention, the RPN was calculated to determine the degree of the technique’s effect. However, these papers have paid less attention to the identification of risk effect. As a conclusion, the study revealed that the small number of studies had failed to show the FMEA technique’s effect, but, in general, most of the studies recommended this technique and had considered it a useful and efficient method in reducing the number of risks and improving service quality. When we compared to the writer of the article, we can find that FMEA is really effective in reducing the number of risks and improving service quality.
In addition, another study by Saulino et al., titled “The application of failure modes and effects analysis methodology to intrathecal drug delivery for pain management,” utilized the FMEA method to transform clinical insights into a risk mitigation plan for intrathecal (IT) drug delivery in pain management.18 The FMEA methodology that has been used for quality improvement was adapted to the assess risks (effect analysis failure modes) associated with IT therapy. Ten experienced doctors at the hospital scored 77 failure modes in the following categories: patient selection for the initiation of therapy (efficacy and safety), patient safety during IT therapy, and product selection for IT therapy. Participants assign severity, probability, and detection scores for each failure mode, from which the risk priority figure is calculated. The failure modes with the highest RPN (i.e., most problematic) are discussed with the proposed strategy to reduce risk. The strategic discussion focused on the 17 failure modes with the most severe outputs, the highest probability of occurrence, and the most challenging detection.
The topic of the highest ranked failure mode (RPN= 144) was manufactured monotherapy versus compounded combination products. Addressing failure modes associated with appropriate patient and product selection was predicted to be clinically important for the success of IT therapy. In this study, Saulino et al. found that the FMEA method offers a systematic approach toward risk mitigation and strategic planning to prevent and manage failure.19 When we compare with our article, both of these articles found that FMEA works proportionally in reducing risk, unmet needs, and information gap.
Furthermore, the study titled “Application of failure mode and effect analysis in a Radiology Department” by Thornton et al. showed that FMEA permits the proactive identification of possible failures in complex processes and provides a basis for continuous improvement.18 With the increasing complexity of clinical radiology services, FMEA offers tools for predicting failure and implementing changes to prevent such failures from occurring in the future. In comparison with this article, both of these articles showed improved process and service quality in complex environment in the hospital. FMEA offers tools in predicting failure and implementing change for lack of process administration that will probably occur in the future. FMEA is a basis for continuous improvement and could proactively identify possible failure in the hospital environment.
From this study’s results, 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 BPJS patients; thus, it greatly affected hospital income.
Based on the results of the research, we can conclude that, by applying the FMEA method, there was a decrease in problematic claims from 26 percent to 13 percent and an increase in claim payments from 75 percent to 83 percent. Thus, the use of FMEA in Dr. M. Djamil Padang Central General Hospital is very helpful and needs to be continuously improved for the effectiveness and efficiency of hospital claim files. In addition, based on the results of this study, we recommend hospitals carry out ongoing evaluations of redesigns that have been made so that, in the future, it will experience continuous improvement. We also expect the commitment and consistency of all staff involved in the flow of medical record services that have been redesigned.
Conflicts of Interest
The authors declared the following potential conflicts of interest with respect to the research, authorship and/or publication of this article: No competing interests.
The authors disclosed receipt of the following financial support for the research, authorship and/or publication of this article: None
This research has received full support from the hospital, starting from the level of directors to the units in Dr. M. Djamil Padang Central General Hospital.
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Yahya Marpaung (email@example.com) is a doctoral candidate at Andalas University in Indonesia. His specialty is surgical polyclinic. He works at Dr. M. Djamil Padang Hospital.
Werry Darta Taifur is an Indonesian economist and professor who is currently serving as the rector of Andalas University in Indonesia.
Nur Afrainin Syah is a lecturer in the medical faculty at Andalas University in Indonesia.
Yusirwan Yusuf is a director at Dr. M. Djamil Padang Hospital.