Thursday, June 27, 2013

Main applications of analytics and data mining in healthcare

Disease Management

Disease management concerns with predictive as well as descriptive aspects of specific disease. What is likely probability of specific disease outcome, and what are the factors associated with these outcomes with the focus on actionable factors. One has to separate effects of causes for specific disease, and that can be done by separating event period from period of input data collection. Disease management can involve specific aspect of the disease whose resolution can be beneficial to not only health-providers but more importantly to the patient. Descriptive component of disease management involves desirable as well as undesirable patterns – and auctioning on these patterns involves either supporting them or breaking them and then measuring effects of these actions for purpose of achieving specific disease management goals.

Some of the examples of disease management questions:
    • If surgical procedure "X" is done, then 45% of the time infection "Y" occurs within two weeks- Why, reasons, contributing factors?
    • What, if any seasonal patterns in emergency room nosocomial infections exist and contributing factors?
    • Why do some congestive heart failure (CHF) patients return to the heart clinic after bypass surgery for care within 3 moths, while others don't?
    • Compare and contrast high length of stay patient groups based upon bed location, nursing teams, and treatment modalities.
    • Compare and contrast treatment results or glucose levels for type II diabetic patients for a given time period, by physician, gender, age group, etc.
    • What practice patterns for managing primary mammogram candidates will yield the best outcomes in terms of survival rates or complication rates at the least cost?
    • What percentage of women in membership between the ages 40 - 60 have had a mammogram in the last 12 months?
    • What is the comparative mean value of hypertension levels within a certain group or population of patients and does it fall within acceptable statistical levels? Do variations in clinical practice patterns have a cause and effect relationship?  

Outcomes Analysis: Clinical and Financial

Clinical Outcomes
A Clinical Outcome is the result of medical or surgical intervention or nonintervention. It can refer to, but is not limited to the following:

  • Mortality
  • Morbidity
  • Re-admittance rates
  • Changes in birth and death rates for a global population, for example, residents of a state
  • The outcome of a given diagnostic procedure, lab result or medical test
  • The results for a patient after care, for example, how long it took to restore the patient's ability to walk, or to work, or how long and to what degree did the patient have pain
  • Did the patient recover, how long did it take
  • The patient's own perception of their care and progress.
It is thought that through a historical record of outcome experiences, caregivers will know better which treatment modalities result in consistently better outcomes for patients. Effective Outcomes Management often relies on a successful data warehousing strategy designed to track historical outcome experiences in many areas such as epidemiological studies, lab results, responses to treatments, mortality and morbidity rates, length of patient stay and clinical effectiveness measures.

Financial Outcomes

The definition of a financial outcome varies depending upon an organization's goals and overall strategy. As an example, financial outcomes might cover measures such as hospital length of stay, net margins, cost breakouts, number of ER visits and office visits - just to name a few.

 Fraud and Detection

It would be nice if we could develop some type of industry wrapper to data mining technology for the health care market specifically. But for now, this may be an area of opportunity for AEs because the industry has yet to spend many resources on Fraud detection and have not developed sophisticated tools and technologies for not only detecting fraud but for predicting and catching fraud before claims adjudication.
Fraud and Abuse is usually defined as "the intentional deception or misrepresentation that an individual knows to be false or does not believe to be true and makes, knowing that the deception could result in some unauthorized benefit to himself/herself or some other person". The most frequent kind of fraud arises from a false statement or misrepresentation made, or caused to be made, that is material to entitlement or payment.
Violators and perpetrators of fraud may include physicians or other practitioners, a hospital or other institutional provider, a clinical laboratory or other supplier, an employee of any provider, a billing service, beneficiary, Medicare carrier employee or any person in a position to file a claim for payment or benefits.

Types of abuses

  • Misrepresentation of medical necessity: For example, a physician who recommends that eye cataract surgery be performed on a healthy eye.
  • Billing errors: Encompasses everything from billing the wrong date of service to up-coding.
  • Over-provision of services: Providing medically unnecessary tests to generate a fee.
  • Misrepresentation of services provided.
  • Offering or acceptance of kickbacks, and/or a routine waiver of co-payments.

Fraud schemes range from those perpetrated by individuals acting alone to broad-based activities by institutions or groups of individuals, sometimes employing sophisticated telemarketing and other promotional techniques to lure consumers into serving as the unwitting tools in the schemes. Seldom do perpetrators target only one insurer or target the public or private sector exclusively. Rather, most are found to be defrauding several private and public sector victims simultaneously.


Medical Errors

The issue of reducing medical errors has been a heated political topic and will continue to be controversial in the next several years. It is believed the key to decreasing these errors will be to properly identify them, analyze the causes, and then change the system and/or processes to prevent them from happening in the future. A November 1999 study by the U. S. Institute of Medicine (IOM) cited 90,000 avoidable deaths, 3 million medical errors and 2.2 million avoidable injuries each year attributable to medical errors. That's the equivalent of having one jumbo jet crash per day with 200 people dying in each crash.
The IOM defines medical error as "the failure to complete a planned action as intended or the use of a wrong plan to achieve an aim. An adverse event is defined as an injury caused by medical management rather than by the underlying disease or condition of the patient. Some adverse events are not preventable and they reflect the risk associated with treatment, such as a life-threatening allergic reaction to a drug when the patient had no known allergies to it. However, the patient who receives an antibiotic to which he or she is known to be allergic, goes into anaphylactic shock, and dies, represents a preventable adverse event.
Most people believe that medical errors usually involve drugs, such as a patient getting the wrong prescription or dosage, or mishandled surgeries, such as amputation of the wrong limb. However, there are many other types of medical errors, including:

  • Diagnostic error, such as misdiagnosis leading to an incorrect choice of therapy, failure to use an indicated diagnostic test, misinterpretation of test results, and failure to act on abnormal results.
  • Equipment failure
  • Infections, such as nosocomial and post-surgical wound infections.
  • Blood transfusion-related injuries
  • Misinterpretation of medical orders
  • Incorrect medicines and/or prescriptions
  • Surgical errors
  • Lab reports errors.
Most errors result from problems created by today's complex health care system. But errors also happen when doctors and their patients have problems communicating. For example, a recent study supported by the Agency for Healthcare Research and Quality (AHRQ) found that doctors often do not do enough to help their patients make informed decisions. Uninvolved and uninformed patients are less likely to accept the doctor's choice of treatment and less likely to do what they need to do to make the treatment work.

Performance Management in Healthcare

 Healthcare provider organizations use performance management methodologies to focus on their key challenges:

·         How are our resources (employees, physicians, capital assets) helping us to accomplish our strategic goals?
·         How are we going to excel at key business (access, throughput, value of service to patients) processes?
·         How are we going to create loyalty (patient satisfaction, physician referrals, market share) with our key stakeholders?
·         How are we going to sustain our ability (have enough financial resources) to enhance the value of the organization?

Full service performance management programs address each of those four perspectives.