Data processing: financial – business practice – management – or co – Automated electrical financial or business practice or... – Health care management
Reexamination Certificate
1998-07-30
2003-07-01
Smith, Jeffrey A. (Department: 3625)
Data processing: financial, business practice, management, or co
Automated electrical financial or business practice or...
Health care management
C705S002000
Reexamination Certificate
active
06587829
ABSTRACT:
FIELD OF THE INVENTION
The present invention relates to disease management in general and, more particularly, to methods and apparatus for improving patients' compliance with prescriptions for medication that they are given to improve a disease condition.
BACKGROUND OF THE INVENTION
It is quite common in the treatment of a disease condition for a health care provider to prescribe certain medications for the treatment of the condition. The medications must be taken in specific doses at particular times of day over a course of time in order to insure that they have the maximum effect on the health condition of the patient. In addition, the doctor or other health care provider may prescribe other courses of conduct to effect the disease or condition, e.g., diets, exercise or lifestyle changes. Thus, “compliance” as used herein, is interchangeable with adherence, and means the extent to which a person's behavior in terms of medications, following diets, or executing lifestyle changes coincides with medical and health advice.
The patient is usually responsible for compliance with the prescription. If the patient fails to comply with the prescription, it is likely that the condition will not improve, or at least not improve as quickly as possible. This, of course, results in an adverse consequence for the patient and his family. Also, the continued poor health condition of the patient has a negative effect on the patient's employer, which in turn has a negative effect on the economy in general because the patient may not be able to work at all, or to work as efficiently.
Failure to take the medication as prescribed is typically due to the fact that the patient has not filled the prescription at a pharmacy. This results in a loss of income to the pharmacy. If the patient takes only part of the prescribed medication, the results may not be satisfactory, and the patient and health care provider may assume that the medication is ineffective. If this view is shared with others, it can have a negative impact on the sale of the medication, which could harm the manufacturer of the medication unfairly.
Patients who do not take their prescribed medication also place additional burdens on the health care system in which the patient is enrolled because they stay ill longer, which increases the medical services that must be provided to the patient and the attendant cost. The health care system may be a private medical.plan, perhaps supported by an employer, or the government. Where the medical plan is a managed care organization (“MCOs”) , such as an HMO, a PPOs, etc., this burden may be critical, because such organizations are required to manage care in a cost effective and high quality way to be competitive. Also, when a patient remains ill longer than necessary, they may get worse and require emergency room treatment, which is perhaps the most expensive way to handle a disease condition. Further the ineffectively treated condition may lead to other and more serious complications, which again reduces the quality of life of the patient, reduces the patient's ability to contribute work effort to his employer, and generally increases costs for treatment.
It is estimated by the National Association of Chain Drug Stores (“NACDS”) that 50% of all prescriptions dispensed in the U.S. are not taken correctly, and that non-compliance with prescription medications costs Americans between $50 billion and $100 billion each year in increased hospitalization and long-term health complications. The NACDS also notes that pharmacist intervention improves compliance and outcomes, and consequently lowers health care costs.
Disease Management is a new area of medicine which focuses on organizing the treatment of patients according to the disease or condition the patient may have so that services are delivered to the patient in a way that is most effective, and utilizes the most appropriate and cost effective service delivered by the most appropriate health care provider needed at the time. One aspect of disease management is to assure, as best as possible, that the patient complies with the prescription. However, in most cases, because the patient has the primary responsibility for this, it is difficult to track this compliance and intervene, e.g. when a course of medication is not being followed. Thus, it would be helpful if indications of lack of compliance were available, so interventions could be effective to get a person to comply with his prescription.
One indication of lack of compliance is whether a patient refills a prescription on time. This information is known to the pharmacy where the prescription was first filled, but may not be generally to the health care system in which the patient is involved. Even if known, there is not a well known system for utilizing this information to obtain patient compliance, except perhaps for the individual pharmacy to send the patient a notice when he does not return on time to fill the prescription.
It would be a great benefit in assuring compliance with medication prescriptions if a particular patient's behavior in this regard could be predicted at some time well before too much.time has passed since the due date for the refill of the prescription. It would be of even more benefit if a prediction of compliance were effective in cases where only a single prescription is required, and there is no intent to refill the prescription. Then some intervention could be taken at the time the medication is prescribed in order to improve the likelihood that the patient will take the medication as prescribed. It would also be beneficial to know which of several interventions are most effective in terms of encouraging compliance.
SUMMARY OF THE INVENTION
The present invention is directed to improving the ability of organizations to improve the compliance of patients with prescriptions by predicting, based on information available upon the filling of the prescription, which type of intervention will be most effective at getting patients to follow their prescriptions. As a result, the organization can intervene with the proper type of intervention very early. Further, one aspect of the invention is directed to predicting which patients are most likely to fail to comply with their prescription, so that intervention can be directed at these patients that are at high risk of non-compliance at the time the prescription is given. The intervention may be in the form of educational information, reminders, etc. Further, by being able to predict those most likely not to comply, the organization can focus its compliance intervention activities on those patients. This allows for efficient use of the organization's resources, since interventions do not have to be sent to those who are very likely to comply anyway. Further, various intervention techniques can be employed and their effectiveness tracked with the present invention, in a “champion-challenger” scenario, so that compliance efforts can be improved over time.
According to the present invention, the predictions of the interventions that will be most effective are made by creating electronic records for each patient and appending additional demographic information to each record. This information is obtained from commercial databases. Typically, the information includes the demographic information and can also include (1) pharmacy information, e.g., information typically received by a pharmacy when a prescription is placed; (2) clinical information about the patient, e.g., information from examinations conducted by health care providers (such as blood pressure, body temperature, pulse rate, respiration rate, height, weight, EKG, etc.); (3) patient reports, e.g., questions asked of patients by the health care provider or derived from surveys of patients by any number of organizations; and (4) medical records of diagnoses and treatment (e.g., associated ICD 9 codes, CPT-4 codes, etc.) With this information a model of patient response to various intervention messages is formed using regression analysis in whic
Camarda Leonard T.
Hanson Gregory K.
Schectman Stephen B.
Wilbur Curtis S.
Darby & Darby
Schering Corporation
Smith Jeffrey A.
Thampoe Immac J.
Thompson, Jr. Forest O.
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