Health Care Database Analysis

Health information is a fundamental piece of data which represents a person, business, organization, or a community. This data is vital in monitoring and coordination of care for individuals and communities. It not only monitors and coordinates patient care, but reduces costly mistakes and prevent duplication of treatments as well as taking a pivotal role in preserving, securing, and protecting personal health information. Since, this information is extremely essential and sensitive, it must remain secure and safe to prevent frauds and cyber-attacks. First of all, this paper discusses vitality of the health information in regards to individuals, professionals, and organizations along with its benefits to improve overall quality of life. Secondly, it discusses the role of information technology in various aspects of the industry and the what the future holds within IT.

There is no doubt in that technology has multifaceted benefits but, at the same time, it has forced mankind to feel insecure. Every industry depends upon the data of the customers and the health industry is no more an exception here. The data of each patient is shared to facilitate health itself and for more rigorous and authentic research. Hence, protecting patient data is very important. It is so important that in 1996, the federal government introduced the Health Insurance

A computerized clinical database consists of clinical data for storing, retrieving, analyzing, and reporting of information (McCartney, 2012).

Along with the new technologies applying in healthcare, the documentation processes and storages also change from paper charts to computer-based electronic health records (EHR). Many healthcare organizations currently maintain patients’ health records in both formats of paper and electronic. The combination is known as hybrid health record system, which is used to assist in different methods that patients’ information is collected. Hybrid health records (HHR) contain specific patients’ health information. HHRs are stored manually and electronically in multiple places. Current patients’ health records usually contain both digital documents and handwritten notes. Patients’ data are electronically stored, such as laboratory, radiology tests,

Hospitals have put in place widespread security and privacy measures to protect patient health information. However, there are still errors being made in data security through the IT standpoint. Some of these errors or issues include:

Common within each of these four categories is the need to collect, collate, format, and submit required data. Manual data collection is an expensive and time consuming endeavor that clinicians often outsource to billing companies or other third-party vendors. Electronic Health Records (EHR) and Anesthesia Information Systems (AIMS) are better solutions to data collection and submission. According to Dr. Emily Richardson, M.D., Chair of the Committee on Practice Quality Improvement for the ASA, there are three tiers of data categories (Emily Richardson, 2017):Tier 1: Administrative/Claims/Billing/DemographicTier 2: Registry/gross clinical (QR/ QCDR)Tier 3: AIMS/ granular

LaTour, K. M., Eichenwald, S., & Oachs, P. K. (2013). Health Information Management (4th ed.). Chicago, Illinois: American

2. Provide a single, shareable, up to date, accurate, rapidly retrievable source of information, potentially available anywhere at any time (Electronic Medical Records, 2005).

There are many types of data collected, such as, Demographic, financial, socioeconomic, and clinical data are collected from patients so that the healthcare providers of services to the patient are able to assess the history of whatever disease the patients is suffering from and how is to be treated. Data collection in the facility is well organized in a way that promotes shared assessment, treatment and communication. Nurses and front row staffs collects raw data’s from the patient, and. The Heath Information Manager and team are the facility are responsible in analyzing and presenting the data collected in a meaning and easily understandable way to served the specific purposes for which it was collected. Examples of such data are, patient’s name, height, weight, gender, allergies, and third party

Studies have found that coded data collected with a sole focus on reimbursement can poorly affect the use of the data for other purposes. Coded data goes farther and does more than ever before, making it imperative that professionals stay up to date of many rapid changes. One of the biggest changes is the expansion of coding from its traditional role of translating narrative clinical text into diagnosis and procedure codes. Coded data are now used for purposes such as severity adjustment, quality of care assessment, patient safety evaluation, public health surveillance, and decision support process development. Coding must meet an emerging need to capture healthcare data in a standard format that has universal meaning and can be applied both at the individual and aggregate levels. With this expansion come additional new responsibilities, such as entry of health information into a database and the need to understand how the quality and accuracy of the data are

This article addresses the importance of collecting accurate and complete coded data along with using uniform coding standards. The collection of accurate and complete coded data is essential because it influences policy-making, public reporting, research, reimbursement, and healthcare delivery. Likewise, use of the uniform coding standards are crucial because they affect the quality of healthcare delivery by reducing administrative costs, and improving data quality and integrity.

Health information management involves the practice of maintaining and taking care of health records in hospitals, health insurance companies and other health institutions, by the use of electronic means (McWay 176). Storage of medical information is carried out by health information management and HIT professionals using information systems that suit the needs of these institutions. This paper answers four major questions concerning health information systems.

“Data is plural of datum, which is the dates, numbers, ages, symbols, letters, and words that represent basic facts and observations about people, processes, measurements, and conditions.” To be useful, data must be accurate.

In light of available security measures and their widespread acceptance within the information security community, there is no excuse for healthcare organizations to fail in fulfilling their duty to protect personal patient information. Guaranteeing the confidentiality and privacy of data in healthcare information is crucial in safeguarding the data of patients as there should be a legal responsibility to protect medical records from unauthorized access.

There exists many data coding standards in healthcare. The ICD is the international standard of the classification of diseases used by a multitude of healthcare professionals  (“International Classification of Diseases”, 2016). Its latest version, ICD-10, has numerous benefits including helping doctors more correctly report conditions and differentiate payment by treatment type, more efficient disease management, and helping to prevent fraudulent claims as a result (Schwartz, 2013). In terms of current use, more and more countries have used it for reporting morbidity. In the United States, it has been the official standard for death certificates since 1999 (Brouch, 2000). For the future, ICD-11 is stated to be released to include recent advancements in healthcare and medicine and will allow open access for editing (“International Classification of Diseases”, 2016). LOINC® is used to standardize data for laboratory and medical clinic measurements (McDonald et al., 2003). Benefits include helping separate lab systems interpret shared lab test data, improving the efficiency of ordering lab tests from many labs, and also aiding in generating public health clinical data (“3.2 Benefits of LOINC”). Current usage is categorized into three areas:  laboratory,  clinical, and HIPAA specific proposals. The majority of US federal agencies and public health departments like New York State