The present document relates to systems and methods for a rehabilitation dashboard, and in particular to a rehabilitation dashboard for use of patient data in the field of physical medicine and rehabilitation.
Physical medicine and rehabilitation (“PM&R”) is a branch of medicine focused on enhancing and restoring the functional ability and quality of life to individuals with physical impairments or disabilities. PM&R clinicians serve wide range of patient populations, including patients with pulmonary disease, heart failure, stroke, spinal cord injury, geriatrics, fibromyalgia, multiple sclerosis, and Parkinson's disease. Clinicians in the PM&R field include physicians, speech therapists, occupational therapists, psychologists, social workers, and nurses. PM&R clinicians utilize a variety of measures to assess patient outcomes in different areas of rehabilitation, such as physical therapy or nursing. Various tools for measuring health outcomes are also known in the different areas of the field of rehabilitation.
Existing software programs allow for the retrieval and display of data stored in databases. One such software program is Dundas Dashboard from Dundas Data Visualization, Inc. (Toronto, Calif.), a web-based platform that enables users to create their own dashboards that pull data from different databases.
Herein is described a rehabilitation dashboard system and method for the display of information relating to the treatment and care of a patient in a rehabilitation setting.
Corresponding reference characters indicate corresponding elements among the view of the drawings. The headings used in the figures should not be interpreted to limit the scope of the claims.
One aspect of the embodiments of the dashboard system described herein is that it simplifies the clinical discussion and reporting of patient outcomes. Using embodiments of the dashboard system, clinicians, patients and others can monitor clinician-documented outcomes, patient-reported outcomes, a patient's activity level, and other measures in a single display.
Another aspect of the dashboard system described herein is that the rehabilitation data displayed on the dashboard is received in response to a query to the patient medical record in an electronic health record (“EHR”) or other existing data sources, thereby allowing the displayed data to be updated automatically as additional information is collected and entered into the EHR.
Another aspect of the dashboard system described herein is that in various embodiments, research data, clinical data, and patient data are all integrated into a single rehabilitation dashboard.
In one embodiment, the system includes an main outcomes page that displays measurements from a plurality of different disciplines, including physical medicine and rehabilitation, nursing, physical therapy, occupational therapy, speech language pathology, and research.
One section of the main outcomes page may display patient information. Patient information may include rehabilitation measures such as estimated discharge data, financial class, clinical service, isolation status, Morse Fall Scale, and FIM scores and goals. Another section of the main outcomes page may display nursing information. Nursing information may include rehabilitation measures such as pain level, sleep, and bowel and bladder functions. Another section of the main outcomes page may display physical therapy information. Physical therapy information may include rehabilitation measures such as the Berg Balance, Sit-to-Stand, Gait Speed, and Six Minute Walk tests, along with selected FIM items. Another section of the main outcomes page may display occupational therapy information, including selected occupational therapy measures. Another section of the main outcomes page may display speech language pathology information, including selected speech language pathology measures. Another section of the rehabilitation home page may display patient-reported outcomes information. Patient-reported outcomes information may include measures from a patient-reported measures (PROMIS) instrument, such as depression, fatigue, pain interference, positive and negative psychosocial impact of illness, or sleep disturbance. Another section of the main outcomes page may display patient activity level information. Data from the patient activity level may be generated from an accelerometer worn or otherwise used by a patient.
Specific measures related to that rehabilitation category are displayed under each rehabilitation category. For instance, under the SLP category, “speech intelligibility” and “cognitive accuracy” measurements are displayed. Next to each measurement are one or more values that reflect a patient's score in that measurement. In the embodiment displayed in
In yet another embodiment, both normalized and natural values could be shown. Also displayed near each measurement listing is an indicator that is used to compare the Current value in that measurement to the Admit value. In one embodiment, the indicator may be different colors, including green, yellow, and red, to reflect different levels of patient improvement. As a result, a clinician (or team of clinicians) can quickly review the home page to focus on those measurements of clinical interest.
Another embodiment of the home page is displayed at
In the embodiment of the main outcomes page displayed in
In one embodiment of the main outcomes page, only rehabilitation measures that have one or more values are displayed. For instance, if the patient has not provided information to determine Pain Intensity values, then the Pain Intensity measure would not appear on the main outcomes page. In another embodiment of the main outcomes page, clicking on the rehabilitation category name or another column heading on a chart causes the chart to sort in increasing or decreasing order of the values in that column.
The title bar of each rehabilitation category is hyperlinked to open another page when clicked. When a user of the home page clicks on a category title (such as “PROMIS” or “SLP” shown in
Patient reported measures may include those reported by the PROMIS Computer Adapted Tests (CATs). In one embodiment, values for such measures are rescaled so that the average of the U.S. general population is 50 and its standard deviation (SD) is 10. Thus, a person who has a PROMIS score of 40 is one SD below the U.S. average. For negatively-worded concepts like fatigue, a T-score of 60 is one SD worse than average (more fatigue), and a score of 40 is one SD better than average (less fatigue). For positively-worded concepts like Positive Psychosocial Illness Impact, a score of 60 is one SD better than average. In one embodiment, PROMIS domains are assessed over the prior seven days.
Fatigue is one patient reported measure that may be displayed on a dashboard page. In one embodiment, fatigue is determined using the fatigue item bank from PROMIS, which evaluates a range of self-reported symptoms, from mild subjective feelings of tiredness to an overwhelming, debilitating, and sustained sense of exhaustion that likely decreases one's ability to execute daily activities and function normally in family or social roles. Fatigue is divided into the experience of fatigue (frequency, duration, and intensity) and the impact of fatigue on physical, mental, and social activities. The fatigue short form is generic rather than disease-specific. A fatigue T-score of 50 is average for the U.S. population, with a T-score of less than 50 reflecting less fatigue than average and a T-score of greater than 50 reflecting more fatigue than average.
Depression is another patient reported measure that may be displayed on a dashboard page. In one embodiment, depression is determined using the depression item bank from PROMIS, which assesses self-reported negative mood (sadness, guilt), views of self (self-criticism, worthlessness), and social cognition (loneliness, interpersonal alienation), as well as decreased positive affect and engagement (loss of interest, meaning, and purpose). Somatic symptoms, such as changes in appetite or sleeping patterns, are not included, which eliminates consideration of these items' confounding effects when assessing patients with comorbid physical conditions. A depression T-score of 50 is average for the U.S. population, with a T-score of less than 50 reflecting less depression than average and a T-score of greater than 50 reflecting more depression than average.
Sleep disturbance is another patient reported measure that may be displayed on a dashboard page. In one embodiment, sleep disturbance is determined using the sleep disturbance item bank from PROMIS, which assesses self-reported perceptions of sleep quality, sleep depth, and restoration associated with sleep. This includes perceived difficulties and concerns with getting to sleep or staying asleep, as well as perceptions of the adequacy of and satisfaction with sleep. Sleep disturbance does not focus on symptoms of specific sleep disorders, nor does it provide subjective estimates of sleep quantities (total amount of sleep, time to fall asleep, amount of wakefulness during sleep). The sleep disturbance short form is generic rather than disease specific. A sleep disturbance T-score of 50 is average for the U.S. population, with a T-score of less than 50 reflecting less sleep disturbance than average and a T-score of greater than 50 reflecting more sleep disturbance than average.
Pain interference is another patient reported measure that may be displayed on a dashboard page. In one embodiment, pain interference is determined using the pain interference item bank from PROMIS, which measures the self-reported consequences of pain on relevant aspects of the patient's life. This includes the extent to which pain hinders engagement with social, cognitive, emotional, physical, and recreational activities. Pain interference also incorporates items probing sleep and enjoyment in life. The pain interference short form is generic rather than disease-specific. A pain interference T-score of 50 is average for the U.S. population, with a T-score of less than 50 reflecting less pain interference than average and a T-score of greater than 50 reflecting more pain interference than average.
In one embodiment, fatigue, depression, sleep disturbance, and pain interference measures may be the only patient-reported measures reported on the rehabilitation dashboard. In other embodiments, additional measures may be utilized.
Embodiments of the system disclosed herein may display data collected by a personal computing device, such as a smartphone. In these embodiments, the personal computing device may comprise an accelerometer (a device that measures movement in three dimensions). When the patient moves, the accelerometer records those movements and stores them in memory of the patient computing device. Movement information may be collected by the accelerometer multiple times each second and is periodically transmitted to an accelerometer database. In one embodiment, the data is transmitted from the personal computing device to a secure server when a wireless connection, such as an 802.11b connection, is available.
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It should be understood that the activity level values may change depending on the placement of the personal computing device on the patient. For instance, the personal computing device may be placed near a patient's torso, for instance on a belt. If so placed, certain activities like biking will not register with an equivalent level of activity, as the accelerometer in the personal computing device does not recognize the patient's lower-body movement. It may be appropriate for a clinician to readjust the position of the personal computing device for the system to accurately collect activity levels.
In
The embodiments of the present disclosure described herein are implemented as logical steps in one or more computer systems. The logical operations of the present disclosure are implemented (1) as a sequence of processor-implemented steps executing in one or more computer systems and (2) as interconnected machine or circuit engines within one or more computer systems. The implementation is a matter of choice, dependent on the performance requirements of the computer system implementing aspects of the present disclosure. Accordingly, the logical operations making up the embodiments of the disclosure described herein are referred to variously as operations, steps, objects, or engines. Furthermore, it should be understood that logical operations may be performed in any order, unless explicitly claimed otherwise or a specific order is inherently necessitated by the claim language.
It should be understood that the embodiments described herein do not rely on dashboard programs from a particular software provider or a particular computer platform to implement the dashboard system, and that any dashboard software or computer platform with similar features could be utilized to realize embodiments of the rehabilitation dashboard disclosed herein.
The present application claims benefit to U.S. provisional patent application Ser. No. 61/869,472 filed on Aug. 23, 2013 and is herein incorporated by reference in its entirety.
Number | Date | Country | |
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61869472 | Aug 2013 | US |