1. Field of the Invention
This application relates generally to a method and system for managing a chronic medical condition and, more specifically, to method and system for remotely advising a patient afflicted with chronic obstructive pulmonary disease over a communication network regarding treatment options to address an exacerbation.
2. Description of Related Art
In all classes of medical subspecialties, there are chronic illnesses that, by definition, have no “cure” and over time cause gradual or progressive deterioration to a patient's health, wellbeing, and quality of life. In addition to the continuous challenges posed by the underlying chronic disease, patients with chronic illness can occasionally experience acute exacerbations in which their symptoms temporarily worsen. These acute exacerbations can lead to emergency room visits, hospitalization, progression of the underlying disease, and even death. In many cases, acute exacerbations can be prevented (or at least their adverse impact can be diminished) when patients and their healthcare providers receive adequate advance notice regarding any changes to the patient's symptoms. A significant challenge in managing and monitoring changes to a patient's chronic condition—and subsequently identifying impending exacerbations—stems from the absence of a reference that adequately and accurately represents a patient's “normal” health. In other words, because of the effects of chronic illness, patients with chronic conditions are not normally healthy as would be defined in the general population. In addition, the “new normal” or “typical” health profile of each chronic illness patient is highly individualized, due to variations in the presentation of chronic disease as well as various co-morbidities. The absence of a “normal” or “typical” profile for comparison purposes is particularly problematic in the treatment of such patients as clinicians observing a patient's symptoms at a particular point in time have difficulty discerning whether the patient is in fact experiencing (1) a “normal” variation that is typical to the patient, (2) a degradation of that patient's overall chronic condition, or (3) an (impending or occurring) acute exacerbation.
For one of the most prevalent examples of chronic pulmonary illnesses, chronic obstructive pulmonary disease (“COPD”) exacerbations are the primary cause of hospitalization of patients with COPD. Not only do patients with COPD have a high rate of hospitalization due to COPD, about 1 in 5 patients are readmitted within 30 days of being discharged from the hospital. For example, in FY 2009, 33,477 Pennsylvanian residents were admitted for COPD exacerbation; 22.7% were readmitted within 30 days of hospital discharge. Exacerbations increase morbidity and mortality, and transiently or permanently worsen the quality of life of patients suffering from COPD. In addition, exacerbations precipitate a decline in exercise capacity and hasten the progressive loss of lung function. Exacerbations consume the majority of COPD costs, with expenditures related to exacerbations reaching $49.9 in 2010. Because such exacerbations can be frightening to the patient, it is common for patients experiencing an exacerbation to immediately seek medical attention at an emergency room or other healthcare provider. However, not all exacerbations are severe enough to warrant a visit to an emergency room or a personal visit to a physician. Exacerbations resulting in unnecessary visits to an emergency room or physician can be costly to the patient and the insurance providers, requiring them to pay for the costs of treating mild exacerbations that, although unpleasant, are not uncommon for the patient's then-current medical condition and did not warrant in-person medical attention.
In light of the above issues, a method and system for managing chronic illnesses is desired that can establish a patient specific baseline health profile, remotely determine the severity of the patient's exacerbations, and remotely propose a treatment for the patient.
A simplified summary is provided herein to help enable a basic or general understanding of various aspects of exemplary, non-limiting embodiments that follow in the more detailed description and the accompanying drawings. This summary is not intended, however, as an extensive or exhaustive overview. Instead, the sole purpose of the summary is to present some concepts related to some exemplary non-limiting embodiments in a simplified form as a prelude to the more detailed description of the various embodiments that follow.
In one aspect, the method and system described herein relate to determining a reference baseline for use in assessing the condition of patients with a chronic illness. The baseline acts as a measurement of the severity of a chronic patient's “normal” symptoms, against which an exacerbation can be compared.
In another aspect, the method and system described herein relate to determining a patient's exacerbation score. That is, a patient may answer a series of questions regarding severity of symptoms related to their chronic illness. These answers are compared to the baseline score. The patient's answers and comparison to the baseline score can then be used to determine an exacerbation score. These scores may be determined during periods of exacerbation, on a periodic basis, or the like. Severity of symptoms may also be recorded directly by sensors, manual input, or the like.
In a further aspect, the method and system described herein relate to the treatment of a patient based in part on their particular exacerbation score. The exacerbation score may be reported to a central location, for example, a triage center, thereby preventing a costly physical visit to a physician or clinician's office by the patient unless necessary.
According to one example, the disclosure herein describes a method for managing a chronic medical condition, comprising the steps of generating a baseline symptom severity score for a patient; recording, by the patient, an exacerbation severity for each of a plurality of symptoms related to the medical condition; weighting at least one of the recorded exacerbation severities according to a predetermined weighting factor corresponding to the symptom associated with the recorded exacerbation severity; determining an exacerbation score relative to the baseline score based at least in part on at least one of the recorded or weighted exacerbation severities; assigning the exacerbation score to a category; publishing the exacerbation score and assigned category for review by a physician or medical professional; and transmitting a treatment plan to the patient, the treatment plan being prescribed by a physician and based at least in part on the exacerbation score and/or assigned category.
According to other examples of the above method, the predetermined weighting factors are customized by a physician; the step of adjusting the baseline symptom severity score at least in part on a plurality of determined exacerbation scores; further comprises the step of performing triage based on the exacerbation score and/or assigned category; at least one sensor is used to determine an exacerbation severity; the medical condition is chronic obstructive pulmonary disorder; the above steps are performed periodically; and the plurality of symptoms related to the medical condition include at least one from the group consisting of: breathlessness, sputum quantity, sputum color, sputum consistency, peak expiration flow, and temperature.
According to another example, the disclosure herein describes a system for managing a chronic medical condition, comprising: a computer configured to: receive input from a patient related to an exacerbation severity for each of a plurality of symptoms related to the medical condition; weight at least one of the exacerbation severities according to a predetermined weighting factor corresponding to the symptom associated with the exacerbation severity; determine an exacerbation score relative to a baseline symptom severity score based at least in part on at least one of the inputted or weighted exacerbation severities; assign the exacerbation score to a category; publish the exacerbation score and/or the assigned category related to the patient; and receive and report a treatment plan to the patient; and a triage center for evaluating the published exacerbation scores, wherein the triage center prescribes the treatment plan for the patient based at least in part on the published exacerbation score and/or assigned category and communicates the treatment plan to the computer for review by the patient.
According to other examples of the above system, the predetermined weighting factors are customized by a physician or clinician. Alternately, the baseline symptom severity score can be adjusted at least in part on a plurality of determined exacerbation scores; at least one sensor is operatively connected to the computer and used to determine an exacerbation severity; the medical condition is chronic obstructive pulmonary disorder; the computer receives input from a patient periodically; and the plurality of symptoms related to the medical condition include at least one from the group consisting of: breathlessness, sputum quantity, sputum color, sputum consistency, peak expiration flow, and temperature.
These and other embodiments are described in more detail below.
The invention may take physical form in certain parts and arrangement of parts, embodiments of which will be described in detail in this specification and illustrated in the accompanying drawings which form a part hereof and wherein:
Certain terminology is used herein for convenience only and is not to be taken as a limitation on the present invention. Relative language used herein is best understood with reference to the drawings, in which like numerals are used to identify like or similar items. Further, in the drawings, certain features may be shown in somewhat schematic form.
It is also to be noted that the phrase “at least one of”, if used herein, followed by a plurality of members herein means one of the members, or a combination of more than one of the members. For example, the phrase “at least one of a first widget and a second widget” means in the present application: the first widget, the second widget, or the first widget and the second widget. Likewise, “at least one of a first widget, a second widget and a third widget” means in the present application: the first widget, the second widget, the third widget, the first widget and the second widget, the first widget and the third widget, the second widget and the third widget, or the first widget and the second widget and the third widget.
The method and system described herein involves the timely treatment of chronic illness exacerbations. In one aspect, such treatment uses telemedicine combined with a management program. Telemedicine combined with a management program can decrease the frequency and severity of exacerbations that would otherwise occur without the combination of a telemedicine and management program, and improve daily symptom control, lung function, dyspnea, and improved peak flow and daily activity status. Telemedicine combined with a management program works by facilitating early recognition and timely treatment of impending acute exacerbations, as well as by monitoring the duration and severity of acute exacerbations. For example, incorporating daily telemedicine-based symptom reporting through a management program could decrease hospitalizations, mortality, and reduce the frequency and severity of acute exacerbations in high risk patients.
It should be noted that for simplicity, chronic obstructive pulmonary disorder (COPD) is used throughout as an example chronic illness for use with the method and system described herein. However, any chronic illness, including other chronic pulmonary illnesses, is envisioned to be within the scope of the present disclosure, and the use of COPD is not intended to be a limiting use.
Additionally, it should be noted that for simplicity a “diary” application on a patient's computer or mobile device is used herein as a telemedicine management program. However, any management mechanism generally used by the patient remotely with respect to a physician or clinician is envisioned within the scope of the present disclosure. For example, the patient may record daily symptoms in a record book at home and report them to a doctor by phone or mail. Therefore, a diary application should not be viewed as a limiting embodiment.
One aspect of the present method and system described herein relates to determining a reference baseline for use in assessing the condition of patients with a chronic illness. The baseline, as used herein, is a measurement of the severity of a chronic patient's “normal” symptoms, against which an exacerbation can be compared. That is, the definition of exacerbation as used herein is a worsening in a patient's symptoms compared to their baseline, not the traditional definition used in many COPD interventional trials denoted by the use of antibiotics, steroids or both.
Turning now to the figures,
After a baseline score has been generated, a patient may then begin recording exacerbation severities for a plurality of symptoms 102, for example, on a regular basis or during periods of acute exacerbation. Once a patient's symptom severities have been recorded 102, the scores are weighted according to a predetermined algorithm 104. The effect of weighting scores is to give particular symptoms, for example, those that may be better or worse indicators of an acute exacerbation, an appropriate factor when determining the severity of the patient's current health state. As described in more detail below, these weighting factors may be customizable by an end user, such as a physician who is overseeing, or is otherwise involved in providing healthcare to individual patients. The weighting factors (e.g., the contribution of each factor that is determined by the physician to be attributed toward the baseline and/or exacerbation scores) can be customizable by each physician, optionally to be unique to each of a plurality of patients, or otherwise established under the direction of the physician to be specific to one, or any number of patients. The weighting factors can be made customizable on a per-physician basis (e.g., each patient under the care of a specific physician can be assigned a set of one or more weighting factors) to generate the baseline and/or exacerbation scores. According to alternate embodiments, the weighting factors can be customizable on a per-patient basis (e.g., established specifically for each patient). According to other embodiments, the weighting factors can be established on a per-facility basis, where a general policy regarding the weighting factors to be utilized is established for all patients and/or physicians practicing at a specific healthcare institution and/or facility.
Next, an exacerbation score is determined 106 using the weighted symptom severities and according to a predetermined algorithm. In many embodiments, this algorithm determines a score relative to the patient's baseline score. Again, the algorithm is described in more detail below and may be customizable. Next, the score may be assigned to a category 108 in order to classify the severity of the patient's exacerbation. The patient's score and exacerbation category can then be published to a physician 110, located remotely, for example, for further review and determination of a treatment plan. The treatment plan may then be transmitted back to the patient 112.
In one or more embodiments, the above method is performed using a diary application (hereinafter “the app”), representing a telemedicine management application, accessible by the patient. A new patient may enroll in the app by establishing user data (e.g., username, password, patient history, demographic information, etc.) corresponding to that patient and downloading the app onto their computer or mobile device. The app serves to simplify the patient's recording of the severity of their symptoms and subsequent transmission of this data to a physician or clinician. Each set of data entries regarding symptom severity is herein referred to as a “check-in”. Once downloaded, the patient may then, for example, use their email/username and password, or the like, to login. As previously discussed, the app is used herein as an example of a telemedicine management application, and should not be seen as a limiting embodiment. Other telemedicine management programs may include website (server-side) applications, hand written diaries, and the like.
In one or more embodiments, a baseline is established during the first 14 days in an enrollment/baseline establishment phase. In other embodiments, this phase may be less than or greater than 14 days. In other embodiments, a baseline may be established after a set amount of data is recorded, rather than a set period of time. In still other embodiments, the baseline may be established prior to or during the patient's enrollment based on previously recorded and/or observed data.
During the enrollment phase, the app operates as it normally would by accepting data entry from the patient regarding their symptom severities; however, no exacerbation determinations are ultimately made. Rather, each time the patient checks-in, the data is recorded for establishing a baseline. In one or more embodiments, patients may complete any number of check-ins during the establish baseline phase, but only the first check-in from each day may be used to calculate the patient's baseline. Each check-in can appear in the patient's check-in history. A check-in preview and detail can further include the number of days into the establish baseline phase (and/or days remaining)—e.g. Day 3 of 14 of establish baseline phase or 11 Days of establish baseline remaining—with a progress bar (e.g. 14 bars with an additional bar shaded each day). Once the system obtains a first check-in on the final day of the establish baseline phase, the app can determine the patient's baseline. The app then shifts to a check-in and algorithm phases according to another aspect of the method and system described herein.
This check-in and algorithm related aspect is directed to determining a patient's exacerbation score. In or more embodiments, the exacerbation score is determined on a periodic basis, for example, daily. In one or more embodiments, the exacerbation score determination is based in part on data submitted by the patient and/or recorded from the patient (i.e., from sensors). Examples of sensors that may be used within the present disclosure include, but are not limited to, spirometers, thermometers, pulse oximeters, or the like.
During the check-in phase, the patient may log in to the app and record the severity of symptoms associated with their chronic illness. In one or more embodiments, patients may log in periodically, for example, daily. In other embodiments, patients may log in only when they believe their symptoms to be exacerbated or are suffering acute attacks. During the check-in procedure, patients answer questions regarding the severity of various symptoms they may be experiencing. In some embodiments, certain symptoms may require that a sensor be used to measure and/or quantify a symptom. Depending on the symptom, more than one sensor reading may be required for a particular symptom. In these cases, the app may record all of the readings, an average of all readings, only the most extreme readings, or some other variation known to those skilled in the art. In still other embodiments, the app may likewise use one or more of the readings in determining a patient's exacerbation score, independent of the number of actual recordings.
As shown in
When the user selects “Check-In” 302, they may begin reporting symptom severities in a series of screens related to each symptom analyzed as part of the method and system. In the example described herein, the user is first taken to a screen for reporting their breathlessness, as shown in
It should also be noted that through the check-in process, a progress bar 604 may be shown to illustrate the user's progress. Although located along the bottom edge of the screen in the present example, the progress bar could be located anywhere on the screen or be of any form. For example, other forms of progress indicators could show the number of screens remaining, the number of screens completed with respect to the total number of screens, a percentage of the total symptoms reported, or the like. Upon selecting a proper response to the indicated symptom, the app may automatically advance to the next screen. Other embodiments, however, may highlight, or otherwise indicated, the selected response and wait for the user to select a “Next” option 606. Likewise, the user may select “Previous” 608 to return to the previous screen for reviewing or modifying a response (if available). A user may also cancel 610 the check-in process at any time.
Next, the user is asked to indicate their sputum quantity for the past 24 hours, as shown in
As shown in
A screen corresponding to peak flow measurements is shown in
Next, as shown in
After indicating which minor symptoms were experienced, the user may be taken to a summary screen, as in
It is to be noted that the above example of symptoms to be reported are not intended to be limiting, rather they are but a single example of symptoms that could be used with respect to COPD. Furthermore, in addition to individual symptoms, the app may ask a user questions relating to their overall health and/or quality of life. For example, the app could seek to establish the patient's dyspnea (modified Borg Score) and/or the Duke Activity Status Index (DASI). It should also be noted that the check-in process is envisioned to be highly customizable. For example, the check-in process could be customized between physicians or clinicians. The check-in process may also be customizable between chronic illnesses.
After a patient has answered all questions related to the severity of their symptoms, and the check-in is successfully completed, the app shifts to an algorithm phase wherein an algorithm is applied to the check-in data. That is, the applied algorithm determines an exacerbation score for the patient's symptoms by comparing the data values for that check-in to the patient's baseline score and adding points (starting with zero) based on changes from the baseline values. It is important to note that any algorithm may be used to calculate an exacerbation score. For example, in some embodiments, symptoms may be given more weight than the same symptoms in other embodiments. Each physician or clinician may weight symptoms as they see fit. In some embodiments, weighting is performed by associating different score values with a given symptom if the severity of that symptom increases above a certain threshold. In other embodiments, weighting may be performed by altering the threshold(s) according which points are assigned. In still other embodiments, a physician or clinician may wish to alter both the score and threshold values. Various embodiments may also perform any mathematical operation on the scores associated with each symptom. Still other algorithms that assign scores based on reported symptom severities to determine an overall exacerbation score are envisioned to be within the scope of the present disclosure.
For purposes of this disclosure, the following example of an algorithm is described herein. In the following example, a positive score value is associated with each symptom if the severity of the symptom matches a particular condition. The sum of all points per the calculation below is the exacerbation score. In one example, scores for each symptom are tabulated as follows:
After the above scores are summed to determine an exacerbation score, the exacerbation score may then be categorized as falling into one of four severity categories: None (0-0.5); Mild (1.0-1.5); Moderate (2.0-2.5); and Severe (≧3.0). Interventions and treatments may be determined based upon the severity category of the exacerbation score for the patient's current check-in. A score equal to or greater than 1 is considered an exacerbation requiring an intervention. The exacerbation scores may also be color coded according to their severity.
Still another aspect of the present method and system described herein relates to the treatment of a patient based in part on their particular exacerbation score. In one or more embodiments, treatment methods may be automated or determined by a physician. In some embodiments, a triage center may facilitate determining treatment plans for a plurality of patient's based on their exacerbation scores.
If the algorithm phase determines that the check-in does not require an intervention, the app can return to the check-in phase for that user. However, if the algorithm phase determines that the check-in does require an intervention, the app can flag the check-in and move to the intervention phase for that user.
It should be noted that while the treatment plans may be automated, in many embodiments, it may be desirable for a physician or clinician to review the symptom severity reports and/or exacerbation score, along with the patient's history and current treatment, and design a custom treatment for that patient. In some embodiments, this may be performed via a central location. That is, the user may submit their report automatically through the app (or manually via phone, external computer, website, or the like) to a triage center. The triage center may then manage the incoming reports to determine which patients have the greatest need. For example, patients with reported severe exacerbations may be tended to first. The triage center may then forward the reports to physicians or clinicians working within the triage center or remotely for immediate review and treatment prescription.
Once a treatment plan has been prescribed, it may be presented to the user. In some embodiments, the plan may be “pushed” to the user via a notification by the app. In some embodiments, the patient may receive a phone call alerting them of a plan. Such phone calls could also be made to the patient following prescribing a treatment plan, for example, 24 and 96 hours after the intervention. In severe cases, an ambulance or similar emergency response may be initiated by the triage center on behalf of the patient.
The scoring algorithm relies on baseline values to provide a meaningful COPD Pilot score. New patients performing their initial check in reports do not have a baseline, so one must be established for them. Additionally, a patient's disease may deteriorate over time or a clinician may want to instruct the system to recalculate a baseline, so existing baseline values for patients need to be recalibrated. One of the objectives of the COPD PILOT program is to reduce hospital readmissions. The PILOT program may be prescribed to a new patient who is being discharged from the hospital after being stabilized from an exacerbation. These types of patients require a fast track approach to have an baseline calculated for them as waiting for 14 days may be too long without adjustment of medications and cause the patient to readmit himself or herself. The COPD application must then handle this situation as a special case.
This section of the document provides Application Programming Interface (API) logic to provide an automatic baseline calculation and a manual baseline calculation. The API Call should accept parameters that specify how many days of patient check-in reports to use for the calculation, and whether to include scores that require interventions in the calculations. The baseline calculation will calculate the MODE for all categorical baseline values and the MEAN(AVERAGE) for discrete baseline values. The results of this baseline calculation will be placed into a new baseline table that will hold current baseline, past historical baselines and Newly calculated baselines. The current baseline information from the User table will be moved to the new table and removed from the Users records. Affected API logic must be changed to access the current baseline information from this new table when necessary. Calculated baselines will need to be approved by a clinician prior to the calculated baseline being used as a current baseline.
Users Perspective—Patient APP, New Patients with No Baseline Values, Check In
When a new patient checks in with no baseline, the application will record the check in, not show any score indication, and thank the user for checking in. After prescribed number of checkins (specified in system settings table) the scoring engine will proceed to calculate a baseline for the user. The calculated baseline will be added to the baseline table with a status to indicate it is a calculated baseline and waiting clinician approval. Until the clinican approved the calculated baseline the patients check ins will proceed with no scoring until the calculated baseline becomes the current baseline.
Users Perspective—Clinician APP, New Patients with No Anchor Check In
Clinicians that review a new patients check in reports in history will see the non-scored reports along with an empty baseline report to show the user has no established baseline baseline as shown below. The baseline column remains locked when scrolling reports. If Approve is selected, the Clinician app will make an API call that will make the calculated baseline the current baseline, timestamp the entry, record the user performing the approval, update the baseline ID in users table, remove the calculated baseline ID from the users record. Then the clinical app should force a poll, that will in turn, remove the icon from users panel (because user object has no calculated ID present, and will redisplay the reports columns with the new baseline.
Users Perspective—Clinician APP, Existing Patients with a Baseline Calibration
When the Server has performed a baseline calibration it will establish the users and basline database entries accordingly. The recalibration will be seemless to the patient, the Scoring engine will continue to use the current baseline as referenced in the Users table current baseline id column. The clinician must then approve the calibrated baseline to make it current and active. Based on the settings in the user table and baseline table the reports API will pass back the baseline and possibly calculated baseline as part of the patient reports structure coming back, these columns will be locked and not scrollable. Below represents a screen view when a patient does not have a calibrated baseline waiting for approval.
There may be times when the clinician wants to manually calculate the baseline for a patient. Even if there is already a calculated unapproved baseline present. The user can do this by selecting the current baseline column from the history screen. If user selects the New Baseline column the system will hide notes section and display a button at the bottom of the column to allow the user to recalibrate the current baseline.
When the system performs a baseline calculation it will use the identified user reports sample set and perform calculations on the sample set to arrive at the calculated values to be used as baselines. The calculation method will be to take the average of all discrete data points (breathlessness and peak flow), and the MODE of all categorical elements. Below shows an example of the sample set and the resulting calculations for baseline using data from reports table. The yellow values represent a users most recent 21 reports, the green recalc row represents what values were calculated and would be inserted into a new baseline row to represent a system calculated but not yet approved row.
Note when calculated the MODE of the categorical elements it is possible that the result is bi-modal (two mode values equally appear, or multi-modal) in these cases, if the calculation method was calced by system for automated calculation. The system will then perform a new calculation because the automatic conditions will still dictate a multi-modal calculation at the patients next check-in.
The Scoring Thresholds option allows the clinician to set certain criteria within the baseline calculation system. For example, the options in the settings can allow the clinician to either set the Severity Level Thresholds or set the Symptom Level Thresholds. The Severity Level Thresholds are the aggregate scores that determine the severity of an exacerbation—how the system interprets the symptom score, and allow the clinician to adjust how the system interprets and reacts to a Daily Check In score. Symptom Level Thresholds are how each answer in the Daily Check In is weighted, and allow the clinician to adjust and edit how many points should be attributed to each symptom question answer.
Severity Level Thresholds
The system will calculate a score based on the patient's answers scored from the Symptom Level Thresholds and then categorize the score based upon the Severity Level Thresholds. The clinician can adjust the ranges for the severity level as well as adjust how the system reacts to a certain score. Moreover, depending on the score the clinician can choose to be notified via alerts of high scores requiring intervention and/or the recommended medical treatment for a severity score.
For example:
Normal—The Normal score range is determined to be between 0 to 0.5 in the default settings with Intervention Alerts and Medical Treatment recommendations OFF.
Mild—The Mild score range is determined to be between 1.0 to 1.5 in the default settings with Intervention Alerts and Medical treatment recommendations ON
Moderate—The Moderate score range is determined to be between 2.0 to 2.5 in the default settings with Intervention Alerts and Medical treatment recommendations ON
Severe—The Severe score range is determined to be between 3.0 to higher in the default settings with Intervention Alerts and Medical treatment recommendations ON
Normal Level Thresholds—The following options can be constant throughout each Severity Level Threshold option:
Minimum Score Range—The lowest this option can be for any category is 0.0
Maximum Score Range Selector—By sliding this button, the maximum score range will be determined. The highest a maximum score range can be is 5.0
Maximum Score Range—This text window corresponds directly to the Maximum Score Range Selector.
Intervention Alert—Through selecting ON or OFF, the clinician can choose to be notified via alert if they would like to be notified of a Severity Level
Medical Treatment—Through selecting ON or OFF, the clinician can choose to receive suggested Medical Treatments for a Severity Level.
Symptom Level Thresholds
As noted earlier, the Symptom Level Thresholds is how each answer in the Check In is weighted. The clinician has the option to manually adjust the weights of the patient answers to their liking in this window. For example:
Symptom—The Check In symptom category that is being asked.
Points to Be Awarded—The amount of points that can be awarded for each symptom answer can be adjusted in this column.
Condition Threshold—The points will be awarded to the score only if the conditional threshold requirement criteria is met for the questions.
According to alternate embodiments of the clinical settings, optionally alongside the Severity Level Thresholds, additional features can include:
The ability to turn ON/OFF drug escalation/de-escalation recommendations for the clinician;
The ability to turn ON/OFF educational content to give feedback to patients; and/or
The ability to turn ON/OFF the pre-script.
1. Drug Escalation/De-Escalation
When a patient's symptoms are worsening indicating an acute exacerbation, it is possible to improve a patient's status via medication. The types of medications that can be prescribed to the patient by the physician to speed up recovery are short-acting bronchodilators, corticosteroids, and antibiotics. The use of each of these different medications is prescribed if only certain symptoms are recognized in the individual. For example, antibiotics can be prescribed if the patient indicates purulent (colored) sputum. Thus, it is of utmost importance the prevention of exacerbations is addressed in a timely and efficient collaboration between clinician and the patient.
Such embodiments convert a patient's divergence from baseline health into a reactionary software system that translates the baseline divergence into recommended medication treatment. Depending on the value of divergence, the system will react accordingly to the value in the graded difference through varied degrees of prescription medication escalation. Furthermore, the system has the ability to analyze the specific symptoms that are accelerating in a patient and calculate the necessary treatment the patient should receive pertaining to those specific accelerating symptoms.
To maintain this method of efficacy, it may be necessary for the clinician to monitor the patient's daily symptoms, medications, and allergens from the point of registration of patient into said system, to divergence from baseline, to automated recommendation of medications, to the return of patient to their reference baseline. Such embodiments can be thought of as converting the compiled baseline information into a dosage calculator that has significant advantages over systems that only track or monitor patient daily symptoms.
Accordingly, such a method and system can be utilized by a clinician caring for a patient with a chronic illness to establish an automated system that can assess symptoms associated with a chronic illness following an exacerbation intervention, that will reset the patient to their baseline symptoms and de-escalate elevated medication or terminate newly prescribed medication base upon symptoms or timeframe determined by the clinician.
2. Educational Content/Patient Feedback/Coaching
This feature allows the system to send back automated responses back to the patient that has educational content and patient feedback. The system sends the content or feedback depending on the Severity Level Threshold and the Symptom Level Thresholds.
3. Pre-Script
The ability for the system to take the check-in data and to automatically prescribe patient medication based upon the Severity Level Threshold. The medication pathway the Pre-Script functionality follows is the same as the Drug Escalation/De-escalation, but with the Pre-Script function ON, the system bypasses clinician approval and prescribes the necessary treatment medication.
Illustrative embodiments have been described, hereinabove. It will be apparent to those skilled in the art that the above devices and methods may incorporate changes and modifications without departing from the general scope of this invention. It is intended to include all such modifications and alterations within the scope of the present invention. Furthermore, to the extent that the term “includes” is used in either the detailed description or the claims, such term is intended to be inclusive in a manner similar to the term “comprising” as “comprising” is interpreted when employed as a transitional word in a claim.
This application claims the benefit of U.S. Provisional Patent Application Ser. No. 61/768,105 filed Feb. 22, 2013, which is incorporated in its entirety herein by reference.
Filing Document | Filing Date | Country | Kind |
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PCT/US2014/018013 | 2/24/2014 | WO | 00 |
Number | Date | Country | |
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61768105 | Feb 2013 | US |