HIM-650: Health Care Data Management.

 

This HIM-650: Health Care Data Management course examines health care information resources and their impact on administrative functions, interfaces, data security and integrity, and business processes. Topics that are studied within HIM-650: Health Care Data Management include:

  • Use of relational database management software to construct tables, develop forms, create and execute queries,
  • Design and deploy reports,
  • Advance database concepts to automate contemporary business processes.

Moreover, learners are able to distinguish between various network hardware technologies and associated data communications protocols in order to direct how organizations design and implement data networks.

What is health care data management?

Health Data Management (HDM) or Health Information Management (HIM) is the systematic organization of health data in digital form. Therefore, health data includes but is not limited to:

  • Patient demographics
  • Medical notes
  • Laboratory test results
  • Procedures and surgeries
  • Imaging, like x-rays, computerized tomography (CT), and MRI
  • Referrals and other communication
  • Provider information, etc.

Most importantly, health data management aims to organize medical data as well as to integrate it and enable its analysis to make patient care more efficient. This will help by deriving insights that can improve medical outcomes while protecting the privacy and security of the data.

Health Care Data Management

Advantages of health care data management.

Healthcare organizations, medical staff, and patients can get significant benefits from health data management. Some of these benefits include:

  • Health care data management helps to create a comprehensive view of patients, households, and patient groups. These composite profiles provide status and enable predictions.
  • Healthcare data management improves patient engagement. For instance, by using target patients with reminders and care suggestions that can be relevant for them, based on predictive modeling.
  • It helps to improve health outcomes. This may involve tracking health trends in certain areas or among specific populations, predicting new trends, and suggesting proactive measures to counter rising health issues.
  • It also helps in business decision-making. Health care data management enables healthcare providers to make better data-driven decisions, such as which types of medical professionals to recruit, what equipment to invest in, or which types of patients to focus on in marketing efforts.
  • Health care data management is used to analyze physician activity. The analysis of data on medical practitioners such as success rates, time invested in different treatments and medical decisions, and aligning physicians with the goals of the healthcare organization may help in improving health outcomes.

Challenges that may face healthcare data management.

There are 3 common setbacks that may face healthcare data management. These challenges are namely:

  1. Fragmented data.
  2. Changes to data.
  3. Regulations and compliance.

Fragmented data.

Medical data can be structured in many ways such as spreadsheets, databases, images, videos, digital documents, scanned paper documents, or maybe stored in specialized formats such as the DICOM format used for MRI scans. It is also widely duplicated, collected multiple times, and stored in different versions by healthcare providers, public health organizations, insurance bodies, pharmacies, and patients themselves. Thus, there is no one source of truth for information on patient wellbeing.

Changes to data.

Typically, medical data is regularly changing as do the names, professions, locations, and conditions of patients and physicians. Additionally, patients undergo numerous tests and are administered many types of treatment over the years, and the treatments and medications themselves advance with time. Hence, leading to the creation of new types of data from these new types of medical treatment, such as telehealth models.

Regulations and compliance.

Medical data is very sensitive. Additionally, they must follow the government regulations, such as the USA Health Insurance Portability and Accountability Act (HIPAA). Healthcare organizations face challenges in data discovery and poor data quality. Thus, making it difficult to perform the required audits and meet regulatory requirements. Moreover, it limits the diversity of data healthcare providers and how they can use the medical data for the benefit of patients.

 

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