Tech Impact on Healthcare Quality

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Tech Impact on Healthcare Quality

(Tech Impact on Healthcare Quality)

Question description

TYPE – Reflective Practitioner

Your Hamric, et al., Etext may give you some insight into ‘data mining’ and how it can be used to evaluate patient outcomes.The AHRQ is a great resource for evaluating how ‘technology’ can impact patient outcomes especially at the population level.

Here are a couple links that may be of value for you:

https://healthit.ahrq.gov/ahrq-funded-projects/current-health-it-priorities

https://integrationacademy.ahrq.gov/expert-insight/success-stories/health-it-case-studies

  • Describe how using information technology and data mining can affect the quality of health care.
  • Using two Quality Performance indicators, provide a comparison and contrast example of how information technology and data have changed patient care outcomes.

Post an initial substantive response of 250.Use APA format and in text citations.Provide at least 2 peer review journal.

Respond to each classmate post of 100 words. Be respectful and use APA format and in text citation.

Rebecca’s Post(Tech Impact on Healthcare Quality)

information Technology and Data Mining

Health care information technology is a broad term that describes the technology and infrastructure used to record, analyze, and share patient health data. Health information technology was created in order to provide better care for patients along with the ability to help achieve health equity. Health information technology is able to help support recordings of patient data to improve healthcare delivery and allow for analysis of this information for both healthcare practitioners and ministry of health and government agencies. This data is used for the implementation of policies in order to better treat and prevent the spread of diseases. Health information technology improves the quality of healthcare delivery, increases patient safety, decreases medical errors, and strengthens the interaction between patients and healthcare providers (OpenMRS, 2015).

Data mining is defined as the computer-assisted process of digging through and analyzing enormous sets of data and then extracting the meaning of data. With data mining, business organizations, such as health care facilities, are able to make more precise business decisions which ultimately allow the facility to gain more profits. Data mining holds great potential to improve health systems. It uses data and analytics to identify best practices that improve care and reduce costs allowing for an increase in the quality of patient health care (Rajkumar, 2015).

Quality Performance Indicators

One important quality performance indicator that can be monitored is the length of time patients must wait before being seen by a health care provider in the ER. It is a measure of performance and efficiency of care. ER wait times are a vital measure of performance and quality of care as they track one of the most sensitive areas of a hospital. Hospitals must constantly strive to reduce wait times in order to offer better procedures for quicker treatment. Measuring how long patients must wait reveals issues in the admissions process, the speed of treatment, and health care providers’ ability to provide quality care. Additionally, they can be measured in both immediate terms, or over longer periods of time to determine trends and allocate resources better to reduce workloads and stress. Data is collected by using information technology from admission soft ware and patient records and the facility is able to measure overall ER wait times (Farquhar, 2016). By using this data, the facility is able to see where improvements can be made in order to increase patient satisfaction and decrease overall waiting room times.

Another example of a quality performance indicator is the rates at which patients fall and incur injury during a hospital stay. Between 700,000 and 1 million patients suffer a fall in U.S. hospitals each year, according to the Agency for Healthcare Research and Quality. By tracking falls using information technology and data to chart where, when, and with whom falls are occurring, health care facilities are able to see exactly where they need to alter and tailor the health care facility to help prevent future falls. In the end, this would lead to improved patient care outcomes.

References(Tech Impact on Healthcare Quality)

OpenMRS. (2015). Role of Information Technology in Medical Science. Retrieved September 20, 2018, from https://www.asianhhm.com/articles/role-information-technology-medical sciences

Rajkumar, (2015, June 23). Useful applications of data mining. Retrieved September 20, 2018, from http://bigdata-madesimple.com/14-useful-applicatio…

Farquhar, M. (2016). AHRQ Quality Indicators. Retrieved September 23, 2018, from https://www.ncbi.nlm.nih.gov

Brooke’s Post

Information technology and data mining both have an impact on the quality of health care provided to the patient. Information technology allows the advanced practice nurse to research the best practice suggested for a diagnosis. It also is used to find available resources to help narrow down a proper diagnosis or to assist with educational material to provide to a patient so they can better understand their disease process or medications being prescribed. These are all examples of how the quality of health care being delivered is increased with information technology (Melnyk & Fineout-Overholt, 2014).

Data mining is examining a large set of data and finding patterns that exist. This information is then used to predict if the same patterns are likely to occur in the future, and if so, how often they will occur. This process is much easier and quicker now that electronic health records are so popular. Data mining impacts the quality of health care by providing accurate reports over a period of time that can be used to examine best practice trends (Hamric, Spross, Hanson, & Hamric, 2009).

One quality performance indicator well known in the health care field is patient satisfaction. Measuring patient satisfaction helps the company be more aware of their shortcomings and provides insight into what adjustments need to be made in order to assure high quality care is being provided. In order to maintain high patient satisfaction scores, employees must consistently provide excellent care to the patients. By doing so, this changes care outcomes for the better. Not only does the patient benefit from this but the organization does as well. One benefit to the organization is an increase in business due to being well known in the community for having a good reputation. Another benefit to the organization is a decrease in the amount of readmissions leading to better reimbursement percentages. Although there are benefits to the organization, studies have shown that this may not necessarily be of greatest benefit to the patient. In one article, high satisfaction scores led to a 44% increase in mortality rate (“Patient satisfaction: When a doctor’s judgment risks a poor rating – amednews.com”, 2016). Analyzing patient satisfaction data with information technology allows users to evaluate what is really best for the patient.

Another quality performance indicator used in healthcare is lab turnaround times. This has been shown to be extremely beneficial to the patient because the faster the results, the faster the patient gets the care they need. In contrast, this can also lead to unrealistic expectations by the healthcare team. Communication can be affected and crucial things can be missed. This also leads to a heavy reliance on technology which has been known to fail without notice. Measuring lab turnaround times also put increased pressure on the lab personnel which can lead to an increase in errors due to unrealistic expectations. Advancements in technology have allowed wireless uploading of lab results leading to an increase in turnaround times which has been known to have an effect on patient outcomes.

References(Tech Impact on Healthcare Quality)

Hamric, A., Spross, J., Hanson, C., & Hamric, A. (2009). Advanced practice nursing. St. Louis,

Mo.: Saunders/Elsevier.

Melnyk, B. & Fineout-Overholt, E., (2014). Evidence-Based Practice in Nursing & Healthcare:

A Guide to Best Practice, 3rd Edition. [VitalSource Bookshelf Online]. Retrieved from

https://online.vitalsource.com/#/books/9781469893334/

Patient satisfaction: When a doctor’s judgment risks a poor rating – amednews.com. (2016).

Amednews.com. Retrieved 24 September 2018, from

http://www.amednews.com/article/20121126/professio…

 
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