Manual Data Entry: The weak link in automated Systems
Data entry tasks tend to be low on the totem pole in terms of business operational priorities. However, data entry is still one of the most critical day-to-day operations for companies across the industry. Everything from customer and sales data to financial information relies heavily on data entry, meaning a single error can have huge ramifications for your company.
Even with the broad applications of operational automation, many data entry positions are still held by humans. Unfortunately, wherever a company employs people, there’s the potential for human error, and data entry errors are some of the costliest errors to companies.
Common Data Entry Errors
No matter how much your employees double-check their work, mistakes always slip through the cracks. Though your staff should understand the importance of accuracy for your company’s operational efficiency, fatigue or simple slip-ups can result in the occasional error. The most common of these mistakes are transcription and transposition errors:
- Transcription errors: These types of errors occur when information is input the wrong way and tends to be more common when transcribing words rather than numerical data. This kind of mistake includes typos, repetition and deletion. Transcription is an especially common problem when employees type quickly — if they hit the wrong key, it’s too easy for them not to notice. This kind of error is also common in word processing programs that automatically correct words within certain contexts, such as Microsoft Word.
- Transposition Errors: This type of mistake occurs when information is input in the wrong order and tends to happen when people type numbers rather than words. For example, instead of typing 123, the employee types 132. Again, this is a frequent error for employees who type too quickly to notice mistakes as they go.
Although most employees make these mistakes in good faith, their errors can still result in severe consequences for your organization. Inaccurate data can take time and resources to correct, and if left uncorrected can lead to lost profits, lost business and even lawsuits. With your organization planning strategies around your data, it’s more important than ever to reduce human error in data entry.
You can automate this process too
Entering data manually is expensive in both labor and company resource allocation. Additionally, the monotony of the work makes it a highly error-prone job with a high turnover rate. To help combat the costs associated with manual data entry tasks.
Fortunately, there’s a better way to manage these important records with intelligent data capture software that can automatically capture bio data information from Identification documents and update Electronic Patient Records without having to enter the data manually. This approach eliminates transcription errors and reduces the time it takes critical patient information.
Automating data capture can help your employees in the work they already do, while complete data entry automation packages can replace some of your data entry workers altogether. With these automated systems, you remove the human factor, reducing errors, labor costs and long-term risks to your organization.
A Case Study.
A leading Nairobi based hospital recently procured a new Health Information System. The system is part of the hospital’s plan to modernize its Technical Management Systems particularly management of patient records. The overarching objective is to;
- Improve the quality of data collected at patient registration process
- Reduce patient onboarding and processing process
- Improve customer and user experience
- Reduce data cleanup and validation cost and time.
Challenges in Management of Patient Records
The new system inherits an existing database of over 1 million records. The records are however very unclean. Several gaps on the records were cited by the hospital. Some include;
- Records belonging to same individuals are duplicated in multiple instances
- Several records lack key data such as missing names or other important bio data
- There are multiple errors in existing records (wrong gender, date of birth, Misspelt names etc)
Human errors were identified as the key root cause of the errors that exist on the database. This has necessitated an additional process of data verification and clean up. It was however noted that human errors also inflicts this process thus not fully effective.
In order to address the challenge above, the hospital resolved to create a new patient records database from scratch concurrently with the rollout of the new HMIS it also consulted accepted a proposal by Identigate integrated solutions limited to integrate an automated data capture module with the new HMIS.
The scope of the project involved the supply of ID scanning hardware and Integration Software (middleware) that would interface with the Hospital Management System and allow for automatic filling of customer data on the HMIS.
The following process is used by end users during patient registration processes.
- An end user uses the provided document reader to scan and automatically collect Bio data from National IDs and passports provided by a patient/customer.
- The system uploads the collected data via an API (Application Programming Interface) securely integrated to the HMIS Database.
- The HMIS system automatically fills the patient Registration Window with patient data on one click
HMIS engineer integrated the system with scripts and API provided by Identigate to the patient registration module of the system
By now, the many benefits of automating data capture should be clear. This solution can be implemented across multiple sectors with high customer throughput in public and private operations across financial, healthcare, telecommunications among others.
Just call us today at +254 -798 335-732 or contact us online. We’ll show you just what we’ve got so you can make the right choice today