Whatare some pros and cons to data mining? Provide an example of when datamining was used and the outcome provided an incorrect assumption orissue. How can these types of situations be avoided in the future?

reply to two peers:

Savanna Bullard posted Apr 1, 2020 5:21 PM

Data mining extracts knowledge and determines interesting and usefulpatterns. This information is used to improve different aspects ofhealthcare. Some pro’s of data mining are higher quality of care, earlyintervention, and fraud detection. Some con’s of data mining are privacyand replacing doctors.

A situation that I recently dealt with during my internship is we hada new administrator and he had to use data mining to find discrepanciesin the allotted monthly budget for the facility. The facility was goingover budget every month for the past few months under the oldadministrator. Using data mining he found a bunch of checks written outto the old administrator with no explanation as to why. So he had cometo the conclusion that the money was being stolen from the company bythe old administrator. This was wrong. The old administrator was writingchecks to cover personal items for the residents from the stores but,he did not keep a receipt or put in a reason for writing the checks.This can be avoided in the future by having a policy in place statingthat if checks are written there has to always be a reason along with anattached receipt. That way when data mining is being used on the budgetit is seen that the extra money was spent on the residents and it won’tlook like the money is being stolen.

ȚĂRANU, I. (2015). Data mining in healthcare: decision making and precision. Database Systems Journal, 6(4), 33-40.

Alva Alvarez Gonzalez posted Apr 1, 2020 12:06 PM

This page automatically marks posts as read as you scroll.

Adjust automatic marking as read setting

Datamining is the process of finding patterns in data sets to predictoutcomes. In healthcare, laboratory tests are essential in assistingdoctors to diagnose and treat a patient for underlining issues, thatmight otherwise be missed during a medical assessment. Doing so improvespatient safety and outcomes, something hospital administrationinvestigates to increase job performance and efficiencies. Cons of datamining in healthcare are a lack of privacy by accessing patient medicalrecords or sensitive information. Although there are laws set in stonerelating to the privacy of medical records, according to some laws thisdoesn’t always apply to data sharing (Singer, 2020).

TheDepartment of Health and Human Services released a new system thatwould allow patients to manage their healthcare records throughthird-party apps. They stated patients will be able to access anythird-party application they choose to connect to the applicationprogramming interface to integrate a health plan’s information to theirelectronic health record (The U.S. Department of Health and HumanServices, 2020). Though this can become an issue in the future becauseit can heighten risks to patient privacy. I do not trust third-partyapps and though this is great for patients to access their health caredata this also means third parties acquiring patient information.Situations like this can be avoided if healthcare facilities would stopwithholding patient’s information and charging them from trying toaccess it.

Singer,N. (2020, March 9). New Data Rules Could Empower Patients but UndermineTheir Privacy. Retrieved from The New York Times:https://www.nytimes.com/2020/03/09/technology/medi…

TheU.S. Department of Health and Human Services. (2020, March 9). HHSFinalizes Historic Rules to Provide Patients More Control of TheirHealth Data. Retrieved from The U.S. Department of Health and HumanServices:https://www.hhs.gov/about/news/2020/03/09/hhs-fina…