We have all experienced pain. But despite it being one of the most common symptoms people seek medical help for, it is also one of the most misunderstood and ineffectively treated.
Part of the reason is that one person’s experience of the same painful event can be significantly different from another’s. There is no one-size-fits-all approach.
Types of Pain
Pain is a general term that describes any kind of unpleasant or uncomfortable sensation in the body. There are many different types and causes of pain, and these can be grouped into eight different categories to help with pain management:
MeduPal with PEAK’s correlation of data derived from the personalized analytics between medication management, pain and emotion using P.E.A.K. based on psychology, empathy, anxiety and anxiety knowledge discovery and machine learning platform. Pain and pain chronification are incompletely understood and unresolved medical problems that continue to have a high prevalence. It has been accepted that pain is a complex phenomenon.
Integrated pain management is a specialty that has grown in recent years. Patient-reported outcomes and AI in pain management can provide insights to improve treatment plans. During each visit to a clinician, patients complete assessments to inform their provider about their current conditions. Each of these assessments creates a profile for the patient about their current and ongoing symptoms. Each of these patient-reported outcomes is extremely useful in tracking the success of a treatment plan. Recently, artificial intelligence (AI) has become an integral factor in learning more about these outcomes. AI can be trained to learn how different factors in a patient’s treatment plan affect their outcomes.
With pain management, it is essential to assess each patient’s pain symptoms frequently. By digitally recording responses to patient assessments, these patient-reported outcomes can be tracked more efficiently. To provide more effective treatment plans, pain management providers are using patient-reported outcomes and AI more often.
Many different healthcare specialties can use AI with patient-reported outcomes. However, pain management tends to include a myriad of external factors for each patient. Pain management can include patients with medication dependencies, behavioral health diagnoses, and chronic diseases.
Contemporary methods of computational science can use complex clinical and experimental data to better understand the complexity of pain. Among data science techniques, machine learning that can automatically detect patterns in data and then use the uncovered patterns to predict or classify future data, to observe structures such as subgroups in the data, or to extract information from the data suitable to derive new knowledge. Together with (bio)statistics, artificial intelligence, machine learning aimed at learning from the PEAK Platform data and offering to our partners the following system:
•Provides applicable conversational therapy support
•Monitors 24/7 patient PEAK system emotion anxiety data correlation, triggers and response to medications – “Red Flag Alerts”
•Screening, Collaboration and Monitoring tool for psychology professionals •Identifies emotional changes that may foreshadow adverse events
•Enables screening & intervention for addiction, depression and suicide
•Provides Objective aids in psychoactive medication selection
•Can shorten hospital recovery times - Bed Turns
•Can raises satisfaction scores and maintain high reimbursement rates
•Provides automated self-serve questionnaire system saves Drs and Clinics time •Provides valuable historical and real-time reports to help make group decisions
*Provides several options including our automated medication delivery system
MeduPal Pain Management Robot (Addiction and Mental Health plug-ins):
MeduPal Robot can guide and motivate patients for better health and pain management. MeduPal's alerts and automated medicine management can help patient stay on track and avoid addiction.
MeduPal Robots can help monitor, provide alerts and provide instruction and guidance information to minimize pain and manage medication to avoid addiction. MindHeart has worked for the last couple years with Dr. Shurman, Chairman of Pain Management for Sripps Health. Dr. Shurman has been recognized by his fellow Physicians as "Doctor of the Year" three times. Dr. Shurman specializes in pain management and addiction and has spoken at many national health events on that subject as it relates to digital health.
For the management of chronic pain, monthly monitoring and support from pain specialists can benefit primary care providers and their patients, according to a study published in Pain Medicine.
For clinicians, the support increased their confidence in prescribing opioids for pain, the rate of identifying patients at risk for opioid misuse, and their satisfaction regarding communication with pain specialists.
Patients reported increased opioid medication compliance and overall satisfaction with monthly monitoring.
The study included 56 primary care clinicians and 253 patients with chronic pain. At baseline, the researchers assessed the clinicians’ knowledge of opioids, concerns about pain medication prescriptions, practice behavior, and attitude about managing chronic pain patients; they also assessed each patient’s risk for opioid abuse. Every month for 6 months, patients were called to monitor their pain level and opioid compliance.
Clinicians were randomly assigned to either the experimental group or the control group.
In the experimental group, clinicians received monthly patient summary reports with information on their pain, mood, activity levels, healthcare use, and results of an opioid compliance checklist. In the control group, clinicians received baseline risk assessment for their patients but did not receive the summary reports.
After 1 year, all clinicians in the study reported improvements in managing chronic pain patients, especially those in the experimental group. However, some clinicians, especially younger ones, still expressed a reluctance to prescribe opioids for chronic non-cancer pain.
“This study demonstrates the benefits of careful monitoring of chronic pain patients and the need for pain management support within the primary care setting so that clinicians can make informed treatment decisions and gain confidence in addressing the risks of opioid abuse,” said Robert N. Jamison PhD, chief psychologist at the Pain Management Center at Brigham and Women’s Hospital. “There is also evidence that improved communication among practitioners can increase adherence among chronic pain patients.”
Monitoring of patients may decrease treatment costs and improve quality of care. Pain is the most common health problem that people seek help for in hospitals. Therefore, monitoring patients with pain may have significant impact in improving treatment. Several studies have studied factors affecting pain; however, no previous study has reviewed the contextual information that a monitoring system may capture to characterize a patient’s situation.
Post-Operative Pain Management
There are steps you can take to help your patients understand and effectively manage their post-op pain in today’s opioid-conscious environment. By monitoring and planning for patients’ expectations for pain relief and helping them reframe their goals, the robot can help them achieve them with minimal opioid use.
As prospective payment transitions to bundled reimbursement, many US hospitals are implementing protocols to shorten hospitalization after major surgery. These efforts could have unintended consequences and increase overall surgical episode spending if they induce more frequent postdischarge care use or readmissions.
The design of monitoring devices and interfaces for adults with pain must deal with the challenge of selecting relevant contextual information to understand the user’s situation, and not overburdening or inconveniencing users with information requests. A model of contextual information may be used by researchers to choose possible contextual information that may be monitored during studies on adults with pain. MindHeart AI and the robot can help provide meaningful data from machine learning.
MeduPal empowers home health providers to care for their high-risk patients at home, avoiding hospital readmission and improving patient outcomes:
Remote Patient Management (RPM) for Chronic Care Management strengthens a patient’s support system to keep them in optimal health. It provides an engagement and empowerment tool that optimizes community patient care. RPM provides the communication platform for patient and care teams to collaborate. It enables the ability to take preventive action, to reduce Emergency Department (ED) visits, hospitalizations and the average hospital length of stay, reducing the cost to the healthcare system. The RPM solution enables care providers to tailor a personalized monitoring plan for individual patients by offering the most complete set of tools and data connections to power effective virtual care across multiple settings.
As a comprehensive solution built on top of Orion Health Amadeus, RPM enables remote care of patient
Minimize contact from patient to caregivers and caregivers to patient. Deliver testing, food and medicine to patients. Everything needed to learn how to prepare family, test, report, track and receive results including text alerts and news updates. Includes emotional and anxiety AI software and calming portal.
Minimize and Eliminate Contact
•Free up paid employees and minimize patients and caregivers exposure to Covid-19
•Telehealth Telepresence with patients in hospital, at testing stations and at home (with our smallert MeduPal Robot).
•Free up paid employees, Increase Quality and Patient Satisfaction
(Handles repetitive non-critical tasks to free up paid employees)
•Telehealth Telepresence costs to be subsidized •Testing capabilities: associated costs may be subsidized
•Proactive care process •Personalized/communicative companion reduces anxiety •AI/design for anti-anxiety & depression due to stress of care & social isolation •Cloud data management, integration with existing data infrastructure (ie, Epic)
Improve Patient Satisfaction
•Bird's eye view of care process tracked in real time •Personalized/communicative companion functionality
•Proactive mental health management) through AI/design
•Reduces anxiety and depression due to stress of care and social isolation
•Remote patient management (RPM) with FDA approved devices
•RPM Integration into existing devices
•New communication channel with healthcare team
Generate Revenue And Save Labor (Insurance * CPT Codes)