INTRODUCTION-WHAT IS A DATA MART?
A data mart is a collection of data in a customized format in a data warehouse focused on a specific report or functional area such as hospital’s census, hospital’s charge activity, labor and delivery outcomes, or Nursing quality measures. (Oracle, 2012) Data marts are usually build by department of information services or an EHR vendor. Data marts usually draw data from more than one source. These data sources can be internal systems used by operational units or external sources. The internal source doesn’t always have to be an internal operational system; it can be another internal data warehouse. The data contained in a data mart is single-subject focused, can vary in sizes and complexity, although it would be limited in scope. (Oracle, 2012)
Data marts are classified in two categories. Dependent data marts draw data from a center data warehouse, sometimes known as enterprise data warehouse, where as independent data marts draw data from operational systems or external sources. For the purpose of this presentation, we are promoting the use of dependent data marts because of the benefits of the Extraction-Transformation-and Loading (ETL) process is much similar in that the data is already clean, summarized, and loaded into the data warehouse. The ETL process consists of mainly identification of the subset of relevant data and moving it to the data mart. With independent data marts on the other hand, the ELT process has to be managed in its entirety, meaning that the data has to be staged every time to be normalized, integrated, and in dimensional formats. (Ariyachandra & Watson, 2012) For these reasons, I am advocating building dependent data marts to maximize performance and to increa...
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...rovider can combine hospital data with clinic visit data via automated systems that populates the data marts. The data can be used for comparative purposes for individuals utilize provider’s clinic sites and hospital units for the episode of care. Relevant health activities are captured and used to analyze the frequency of ED visits, hospitalization, and clinic visits to see PCPs. This data is collected in a uniform format that is readily accessible and identifiable for your organization’s asthma patients or patients with other chronic illnesses. Data marts can be utilized for health care system utilization review, access to care, clinical outcomes measures, business trend analysis, and other operational uses. Data usage from deployment of data marts is with undefined limits in learning of population and processes for improved efficiency and coordination of care.
Generally, the development and adoption of Clinical Decision Support (CDS) systems is based on the necessity and essence of technical standards in enhancing healthcare. However, the various health IT tools must comply with some data interchange standards in order to enhance access to clinical records, lessen clinical errors and risks to patient safety, and promote innovation in “individual-based” care (Hammond, Jaffe & Kush, 2009, p.44). The need for compliance with standards is fueled by their role in enabling aggregation of informa...
For years now, the healthcare system in the United States have managed patient’s health records through paper charting, this has since changed for the better with the introduction of an electronic medical record (EMR) system. This type of system has helped healthcare providers, hospitals and other ambulatory institutions extract data from a patient’s chart to help expedite clinical diagnosis and providing necessary care. Although this form of technology shows great promise, studies have shown that this system is just a foundation to the next evolution of health technology. The transformation of EMR to electronic heath record system (EHR) is the ultimate goal of the federal government.
ETL is a three-step process which stands for Extract-Transform-Load. This process comprises of: extracting the desired data from a source, transforming the extracted data into a specific format, and loading the transformed data into a destination such as a data warehouse (Haag & Cummings, 2013). After the ETL process is performed, data-mining tools can be used to turn this data into useful information. For the first three questions, the database would need to capture each checkout price, how many items are purchased, the individual price of each item, and if the item is discounted or full MSRP. This specific data will likely originate from a customer oriented database that will then flow into the data warehouse for full ETL. For YTD profits, the database would need to capture all purchases, sales, profits, and expenses from the current year. Sport T’s company data will originate from an in-company database which focuses on business expenses and profits. In solving customer satisfaction, the KPIs to consider would be survey questions and answers from responding customers as well as customer opinion on what can be improved. For customer surveys, we will ask
Many new technologies are being used in health organizations across the nations, which are being utilized to help improve the quality of health care. Electronic Health Records (EHRs) play a critical role in improving access, quality and efficiency of healthcare ("Electronic health records," 2014). In order to assist in expanding the use of EHR’s, in 2011 The Centers for Medicaid and Medicare Services (CMS), instituted a EHR incentive program called the Meaningful use Program. This program was instituted to encourage and expand the use of the HER, by providing health professional and health organizations yearly incentive payments when they demonstrate meaningful use of the EHR ("Medicare and medicaid," 2014). The Meaningful use program will be explored including its’ implications for nurses, nursing, national policy, how the population health data relates to Meaningful use data collection in various stages and finally recommendations for beneficial improvement for patient outcomes and population health and more.
To be considered meaningful users of the EMR, the qualified applicant must use clinical content that is consistent and standardized across systems and healthcare settings, use decision support tools such as alerts and reminders, have the ability to collect and store raw data from documentation that can be used for reporting purposes, collect and report data to the state. Reporting of data will help to improve public health and awareness and provide sharing of information between systems (Tripathi,
Unfortunately, the quality of health care in America is flawed. Information technology (IT) offers the potential to address the industry’s most pressing dilemmas: care fragmentation, medical errors, and rising costs. The leading example of this is the electronic health record (EHR). An EHR, as explained by HealthIT.gov (n.d.), is a digital version of a patient’s paper chart. It includes, but is not limited to, medical history, diagnoses, medications, and treatment plans. The EHR, then, serves as a resource that aids clinicians in decision-making by providing comprehensive patient information.
Healthcare professionals associated with medical billing and coding know the progress the technology has made so far. In the last few decades, medical billing and coding has switched from being a paper-based system to a computerized format. Under HIPAA laws, medical practitioners had to develop new software in order to send out electronic bills. With the advent of electronic medical records (EMR), with one touch of a button, doctors, Nurse Practitioners and PAs can gain access to all the care a patient has ever received from every healthcare facility the patients visited previously and can figure out possible illnesses. This enables statistical documentation of the population as a whole as well. EMR can also make the healthcare system more transparent and allow integration with reimbursement data. As the healthcare system changes, this will prevent unnecessary costs and make it easier to get the reimbursements needed to treat a patient.
Traditional business intelligence tools are being replaced by data discovery software. The data discovery software has numerous capabilities that are dominating purchase requirements for larger distribution. A challenge remaining is the ability to meet the dual demands of enterprise IT and business users.
Extant data analysis: documents and records such as sales reports, customer surveys, safety reports and concentrating on performance outcomes.
Currently, Kaiser Permanente, a nonprofit organization has already begun to implement the practice of electronic medical records. Kaiser Permanente patients have the privilege of sharing their medical history with each medical provider seen during their Kaiser membership. Depending on the level and type of information needed, every healthcare professional patients have encounters with within their geographical region will have access to notes, prescriptions, procedures, and diagnostic tests at the click of a mouse, to effectively and proficiently render care. All medical documentation provided to Kaiser Permanente from othe...
"(Davenport, 2006) Data is compiled to enhance business practices. When samples are taken, they are used to examine research and understand how to solve problems or why situations are as they are. Furthermore, in this article, Thomas Davenport discusses analytics from a business
A data warehouse comprised of disparate data sources enables the “single version of truth” through shared data repositories and standards and also provides access to the data that will expand frequency and depth of data analysis. Due to these reasons, data warehouse is the foundation for business intelligence.
A rising concern with informatics and public health is the barrier between data sharing. A major challenge for public health informatics is facilitating the improved exchange of information between public health and clinical care. Many of the data in public health information systems still come from forms filled out by hand, which are later computer-coded. Some reports are electronic but the initial data still have to be entered manually, this results in serious underreporting of data. Information silos typically do not share priorities, goals or even the same tools. Departments operate as individual units; silos occur due to an organization structure. Silos make it difficult to share information, agencies store same information in multiple places. Furthermore, silos increase health agency cost.
Prior to the start of the Information Age in the late 20th century, businesses had to collect data from non-automated sources. Businesses then lacked the computing resources necessary to properly analyze the data, and as a result, companies often made business d...
Data can be organized a specific way for each business to be able to get the best use. Employees can also access the system at the same time but in different ways. For example, the customer service team can pull up documents and keep track of complaints at the same time that the marketing team is in a