Study Design and Setting
The present study was performed in the central laboratory of Çukurova University Teaching Hospital, Adana, Turkey. This hospital has approximately 1000 beds. The laboratory has been accredited by the Joint Commission International since 2006, making it the first accredited clinical laboratory in a university hospital in Turkey. This research project was conducted in Imam Reza Hospital complex (IRHC) that is a tertiary care teaching hospital with 1000 beds located in Mashhad, Iran. The IRHC provides care to around 6,000 inpatients and 19,000 emergency patients monthly. The study used a quasi-experimental two-group pretest-posttest design and was designed to reduce patient discharge time.
To select the wards of intervention and control groups, a team was formed consisting of ward secretaries (n=2), head nurses with at least 10 years of work experience(n=2), hospital quality improvement officer, hospital admission and medical records officer, as well as hospital billing officer and faculty members of health system management and health information management (n=3). The participants were contacted via phone calls and were asked to attend the meeting after explaining the study objectives and introducing the researchers. Moreover, the faculty members of health system management were invited to ensure more widespread coverage of the issue.
Four wards were selected during a meeting based on the following criteria: 1) the same discharge time or a maximum of 15% standard deviation with the total discharge time of the hospital, 2) the same LOS with a maximum of one-day difference. Accordingly, wards of general surgery, orthopedics, heart-1, and heart-2 were selected. Thereafter, general surgery and heart-1 were selected as the intervention group and orthopedics and heart-2 as the control group. The study was approved by the IRHC administration in accordance with the quality assurance policy.
Intervention
The hospital throughput project was conducted at IRHC from July-October 2017 with ongoing key performance metrics monitoring, following a process improvement framework developed using Six Sigma principles. Six Sigma relies on a structured approach to uncover the root cause of a problem using the Define, Measure, Analyze, Improve and Control (DMAIC) method by defining the problem, measuring the defect, analyzing the causes, improving the process by removing major causes, and controlling the process to ensure that defects do not recur( 18).
A multidisciplinary team (value team) was formed at the outset, including a physician, chief medical resident, director of bed management, manager of billing, patient care unit manager, head nurses of wards, unit clerk representative, assistant director of health information management, and manager of the transport services. The hospital administrator was the assigned Six Sigma expert responsible for team building and project management. Following the DMAIC approach, the team set out to define the scope of the project and decided to focus on the improvement of the administrative processes that contributed to delayed discharge. To identify the hospital discharge process and define the problem, the discharge process was broken down into seven logical sub-processes called seven stations.
A time study (stopwatch) was used to measure each step in the process to determine the time consumed by each of the seven sub-processes to prepare the discharge summary, and the discharge process of 140 patients was measured. In the next step, to discuss the solutions and approve the new discharge process, the method of expert discussion and focused group discussion was used. The team, through extensive discussions, completed a root cause analysis for delayed discharge. Moreover, they outlined barriers and wastes and proposed changes from the perspective of each stakeholder, and interventions were implemented according to Table 1.
Data gathering and Measurements
Dataset for hospital inpatients' analyses included 140 patients in the pre-intervention phase (November 2016-February 2016) and 140 patients post-intervention (July 2017-March2020). The stratified random sampling was employed in this study. patients were randomly selected from each ward in the intervention and control groups in different months. Data related to patient discharge time (time from discharge order to patient leaving the hospital) was examined.
The inclusion criteria for patients were the medical records of patients who were discharged from the selected wards during the study period. On the other hand, the exclusion criteria entailed: patients who died and those who were discharged from the hospital without settlement. For all patients, the start and end time points of each station in the discharge process were checked and recorded in a data table. The main sources of data for the extraction of the start and end times of each station were the hospital information management system and the patient's physical medical record. In addition, to check data accuracy, the original data was matched with other medical record documents, such as the date and time in the physician order, nursing report sheet, and summary sheets. verbal consent was obtained from participamts that was approved by the ethics committee. In addition to the ethical approval, all methods were performed in accordance declaration of Helsinki.
Statistical Analysis
Categorical variables were summarized by number and percent, while continuous variables were described as mean and standard deviation. The comparability of the intervention and control groups was assessed by comparing some characteristics of their patients using the Chi-Square test for categorical variables and independent t-tests for continuous variables. Outcome variables (waiting times) before and after the intervention in each group were compared using an independent t-test since the patients were different before and after the intervention. In each group, the mean difference and its 95% confidence interval were calculated for all stations. Intervention and control groups were considered statistically significantly different in any station if their confidence intervals exclude each other. All statistical analyses were carried out using Stata software (version 14.1), and the level of statistical significance was set at 0.05.
Individual control chart was used to analyze trends in average daily discharge time, special cause variations (non-routine events), and common cause variations (routine events), and assess the process for stability (statistical control). To further assess variation in the process, the following were also measured: six sigma scores (number of short-term standard deviations between the center of a process and the closest specification limit), yield (percentage of discharge times meeting team goal of 212 min), defects per million (number of times that discharge time exceeded the target per million discharge opportunities).
Table 1. Barrier, Waste, and Change from the Perspective of Different Stakeholders
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Patient feedbacks
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Accounting and medical records staff
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HIM(health information management)
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Nurse/head nurse
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Physician
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Barriers
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Lack of response and information about the discharge process and the necessary documents
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Shortage of personnel in the accounting and medical record units
Lack of staff knowledge about the volume of discharged patients per day
Lack of coordination and organization of medical records sent by the wards to the medical records and accounting unit
Numerous shortages and defects of medical records and frequent contact of accounting personnel with the department to eliminate defects
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Lack of clear and specialized job descriptions
Lack of access to specialized officials in connection with the elimination of file defects in a professional manner
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Lack of familiarity with the discharge process
Need to have a specialist confirm the patient's discharge
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Unavailability of test results, as well as diagnostic and therapeutic measures
Lack of access to physicians to approve some medical records shits
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Wastes (misuse and
overuse)
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Waiting for a physician to be present regarding discharge
Waiting for discharge
order to be written
Waiting to receive care service reports
Waiting time for discharge (At different stations from ward to department of medical records and accounting)
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Waiting for insurance carriers
to financially clear patient (in the inpatient ward)
Waiting for medical records to be completed (in the inpatient ward)
Waiting to be present with the patient
Waiting for the medical records to be completed (in the department of medical records)
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Waiting for the doctor to record the discharge order and fill out the nursing report
Waiting to receive action reports.
Waiting for insurance, expert approval, and patient identity
Waiting for the presence of an escort to settle the account
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Waiting for the doctor to be present at ward
Waiting for the drug list to be approved by the pharmacy
Waiting to receive the medication needed by the patient to be prescribed before discharge
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Waiting for the results of tests and diagnostic tests that provide unnecessary care
Patient rounding before the available medical results leads to fragmented care and rework.
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Corrections and Interventions
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Separation of patient movement ,from physics of medical record movement, in the discharge process and removal of some stations in the discharge process for patients
Creating electronic pending charge report to facilitate charging
Electronic performance of the discharge process
Coordination with an insurance expert to receive approval for insurance in the wards
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Changing the ward secretary to HIM experts (The multi-threaded tasks)
Providing discharge process for patients by HIM staff
The HIM can control, code the medical record, and provide the Billing at the ward
Starting the preparation of the documents required for discharge before the patient's discharge time (even days before)
Accurate use of hospital information system to update and prepare action reports
Changing the patient discharge process and transferring the coding station and preparing reports after the patient leaves
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Replacement of inpatient ward secretaries whose fields were not health information technology.
Training of HIM experts in all units related to the discharge process (Through on job training-OJT).
The performance score of the HIM expert is determined by the head nurse (40%), the head of the health information management department (30%), and the head of the accounting unit(30%).
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Communicating the electronic discharge process to the head nurses to familiarize the staff and doctors to correct the visit time
Emphasis on pharmacy personnel and setting hours to specify for drug delivery
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Requesting a discharge order Until 9 A.M. every day
Determining the criteria for discharge at different times
Notifying physicians to prioritize the registration of discharge records
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