Data Quality Management : The Business Processes That Ensure The Integrity Of An Organization Essay

Healthcare has evolved over past decades and continues to remain an issue of concern for individuals everywhere. Effectively managing data is important to improving the performance in the health care system. Accumulating, evaluating, deciphering and acting on data for particular performance measures allow health professionals to identify shortcomings and make the necessary adjustment, and track the outcome.

Apply accurate, complete, and consistent coding practices for the production of high-quality of healthcare data.

A data set is a collection of data that is defined using uniform definitions. The two purposes of data sets are to first identify the information collected and then to provide a uniform definition for the common terms used. Data sets make information comparable from multiple organizations. The uniform hospital discharge data set was developed in order to define common, uniform data elements and are then collected from inpatient records to be stored in a national database. The uniform ambulatory care data set was developed to track patients that received medical and surgical care and were discharged the same day. The resident assessment instrument and minimum data set is used to collect patient demographics and clinical data for every resident

In 1974, the federal government adopted the Uniform Hospital Discharge Data Set (UHDDS) as the standard to help improve the uniformity and comparability of hospital discharge data, the principal diagnosis, and other diagnoses for hospital procedures; including comparable data that could help to determine which hospitals were best at treating patients and for reporting inpatient data in acute care, short-term care, and long-term care hospitals. This dataset works towards a standardized system of reimbursement for the federal government nationwide which in turn could lower costs, UHDDS helps in collecting general information pertaining the patient and the specific care including the age, sex, and race of the patient. The data elements are collected

What is HEDIS? This abbreviation stands for the Healthcare Effectiveness Data and Information Set. This information set has morphed in its usefulness since 1991, where it was first termed the “HMO Employer Data and Information Set” (AHRQ, 2010). Since its inception, this information has been used by a majority of the country’s health care plans to evaluate performance. Today, the data sets allow for evaluation and more fluid comparison of certain areas of care and service. Furthermore, HEDIS comprises eighty-one measures that spans over five domains of care. Due to this amount of information gathered, stakeholders are given the opportunity to compare different plans in similar terms. In addition, the healthcare plans have the availability to view their own rankings to make necessary adjustments. The data sets are also examined to assess which plan is best for employers and employees based on specific needs. This data is also utilized when seeking accreditation and is now a powerful reimbursement tool. The HEDIS results are accessible for stakeholders via Quality Compass, which is a web-based tool that allows one to view and compare benchmark information (HEDIS, 2015).

Quality management is essential to the success of the quality improvement of the health care industry. “Management uses management and planning tools to organize the decision making process and create a hierarchy when faced with competing priorities “( Ransom, et al., 2008). Quality measures should have these goals: effective, safe, efficient, patient-centered, equitable, and timely care (Quality Measures, Center for Medicare & Medicaid Services, 2011).

A current problem with SNOMED CT is concept ID. Concept IDs give a medical term (Patient or Scalpel) an ID. This language can be confusing, and when there is confusion, quality of care and higher costs of health care can occur. When concept IDs are created, there needs to be a hierarchy so that each version can be kept track of the specific relation. Commonalities in the concept IDs can create a problem with SNOMED CT; the new concept model was created to figure out how to solve the issue or make it explicit. In addition to Concept IDs, uninformative codes are another problem with SNOMED CT.

Quality Improvement (QI) is an organizational approach that leads to the quality of patient care and services through use of specific set of guidelines, principles, and methodology. This is so that there is assurance that quality care is provided for every patient. Principles of quality improvement focus on measurements. These measurements involve data collection used to improve the quality of care, and patient outcomes. Any good quality improvement program ensures strengthening the systems through analyzes and processes.

The International Classification of Diseases, Tenth Revision (ICD-10) has been in development since 1983 to replace the outdated Ninth Revision (ICD-9) that has been in use in the U.S. for over 35 years (Giannangelo, 2015). Due to the Health Insurance Portability and Accountability Act (HIPAA) Administrative Simplification regulation published in 2009, the Clinical Modification (ICD-10-CM) will replace ICD-9-CM Volumes 1 and 2, and the Procedure Coding System (ICD-10-PCS) will replace ICD-9-CM Volume 3 for all HIPAA transactions effective October 2015 (Giannangelo, 2015). These new code sets accommodate new procedures and diagnoses and allow for greater specificity in clinical documentation (Centers for Medicare & Medicaid Services [CMS],

When dealing with healthcare organizations such as hospitals; evaluating the quality of care is essential. This will help to know what needs to be done to improve the quality of healthcare. There are a few different measures

For instance, in nursing homes, the quality measures come from resident assessment data that is routinely collected. Those measures are then combined to form a quality benchmark and standards program. For instance, short stay measures include:

Quality measures are strategies that gauge, evaluate or compute health care processes, results, discernments, patient insight, and administrative structure. In addition, quality measures are frameworks that are connected with the capacity to deliver first-class health care and/or that are able to identify with one or more quality objectives for medicinal services. These objectives include: compelling, protected, effective, quiet focused, impartial, and opportune consideration. Quality measures can be used to measure quality improvement, public reporting, and pay-for-reporting programs specific for health care providers (CMS.gov, 2016). There are an assortment of quality measures in which health care organizations can use to determine the status of the care they are delivering. Many are appropriate, but few are chosen for this research paper. Among them are: National Health Care Surveys, Hospital IQR Programs, Scorecards, and Political, Power, and Perception/Data for Decision-making tools.

Quality indicators enable the health care system to identify inferior care in both process or outcome and structure while enhancing quality improvement in health care (De Vos et. al, 2009, p.1).

There is an accentuation on the need for quality of coded data with the use of computer-assisted coding in healthcare organizations to assure compliance is being met with regards to the increasingly multifaceted quality reporting requirements.

The first quality initiative that could increase patient satisfaction and potentially reduce healthcare cost is the national data warehouse. According to Brennan, Cafarella, Kocot, McKethan, Morrison, Nguyen, Shepard & Williams II (2009), “this type of quality analysis needs to be valuable to both payers and consumers. For payers, quality analysis helps them potentially understand payment mechanisms, quality providers, regional differences and medical management techniques. For consumers, there is a better understanding of practice and potentially cost differences of providers. So, the primary purpose for creating a national data warehouse will be to develop key quality measures that all parties can agree on.” The second quality initiative that could increase patient satisfaction and potentially reduce healthcare cost is creating one common contract between all health plans and providers (Brennan et al., 2009). According to Brennan et al., (2009), “to accomplish this, a national group comprised of government personnel and knowledgeable provider contractors from the health plans will set national guidelines. Regional contracting groups will be entirely made up of current health plan contractors and will do the local contracting under