Bibliographic record
Abstract
In this issue, Liddy et al. [ 1 ] report their findings regarding improving access to chronic pain services through the use of telehealth e-consultative services. Dr. Liddy and her colleagues tackled a common problem of access to pain medicine consultative services in North America and found that e-consultative services greatly improved access to patient care in the Ottawa health care system. Using these services, patient information was reviewed in a median response time of less than 2 days, compared with an average wait time of 6 months or greater (up to 2.5 years) with a conventional referral and in-person consultation. Although this is significantly longer than the anticipated wait times in the United States (US), it does mirror the challenges of prompt access to care, particularly for patients in rural settings or those of lower socioeconomic status that rely on state or indigent care programs, which may further limit their access to care. The referring primary care physicians greatly valued the service in >90% of cases, citing benefits provided to both patients and themselves, and including avoidance of unnecessary in-person referrals. Unfortunately the study did not capture the patient-perceived value in the e-consultative service. The format of their intervention, a case review between the pain medicine physician and the referring provider, resembles that of pain medicine services previously reported [ 2–4 ]. The authors correctly describe their form of telemedicine as asynchronous, or “store and forward” technology as opposed to synchronous or “real-time” communication between the provider and patient. As described, these asynchronous e-consultative services do not meet requirements for Center for Medicare & Medicaid Services (CMS) payment in most US settings [ 5 ]. Although the authors have demonstrated perceived value, telemedicine services have been limited in the United States at least in part due to limitations with payment in the traditional fee-for-service (FFS) model. The use of telemedicine, technology to deliver health care services at a distance, has expanded from rural communities and select federal programs to involve specialty and subspecialty care. Enabled by dramatic technical innovations, telehealth can bridge geographic distance and improve quality of care when access to pain medicine specialists is limited. Telehealth pain medicine services have been previously reviewed [ 6 ] and hold the potential to improve access to care [ 1 ], result in significant opioid discontinuation rates [ 7 ], provide superior pain improvement in cancer patients [ 8 ], improve psychosocial outcomes in patients with fibromyalgia [ 9 ], improve patient satisfaction, and decrease health care costs [ 10 ]. Similar benefits have been demonstrated throughout medicine, leading to policy statements of support for telemedicine from the American Medical Association (AMA) [ 11 ] and the American College of Physicians (ACP) [ 12 ]. Moving forward, it is anticipated that telemedicine services can be of great benefit to patients with chronic pain conditions, which affect approximately 100 million Americans with costs of $600 billion each year and an estimated 200 million lost work days [ 13 ]. Delayed access to pain medicine specialists results in significant burden to the patient, employer, and health care system. The International Association for the Study of Pain (IASP) has declared that access to specialty pain medicine care should occur within 8 weeks from onset of symptoms [ 14 ]. Indeed, delays in treatment greater than 6 months, as was standard in the Ottawa health care system, have resulted in decrements in mood and increases in disability that adversely affect quality of life [ 15 ]. Although there are several reasons for delay in referral to pain medicine specialists, only some can be improved through the use of telemedicine. For instance, telemedicine pain medicine services might be expected to: 1) improve availability of qualified pain medicine providers; 2) span geographical distances; 3) bypass functional disability and mobility limitations; 4) avoid treatment-related stigmata of seeing a pain medicine physician; 5) reduce economic limitations [time-consuming and expensive, including indirect costs of transportation, childcare, parking, and time-off-work]; and 6) improve educational barriers. For telehealth services to be integrated into our health care model, they must be economically viable. The 2016 Final Rule Medicare Telemedicine Services [ 5 ] include the requirement that the service must be on the list of Medicare telehealth services and meet the following additional requirements. The service must be furnished: Via an interactive telecommunications system By a physician or other authorized practitioner To an eligible telehealth individual The individual receiving the service must be located in a telehealth-originating site. Neither the system described by Liddy and colleagues, nor other published protocols [ 2–4 ] fulfills these requirements. Therefore, as proposed, these initiatives are likely unsustainable in US clinical pain medicine practices that use the traditional FFS model. Future pain care studies on telemedicine should conform to CMS guidelines for reimbursement, including the use of synchronous communication between the patient and pain medicine physician. Simultaneously, CMS and other payers must recognize the demonstrated value of telemedicine, including asynchronous services, and reimburse appropriately. Although the savings for physicians and hospitals are potentially enormous, overcoming the high telemedicine implementation costs may appear insurmountable for many pain medicine practices. Physicians who implement telemedicine will flourish in the future, finding new ways to provide pain medicine services that were previously unattainable. As stated by Asch, “The innovation that telemedicine promises is not just doing the same thing remotely that used to be done face to face but awakening us to the many things that we thought required face-to-face contact but actually do not”[ 16 ]. Concordant with the declaration of 2016 as the “year of telemedicine,” there is an expanding drive to foster telehealth initiatives with efforts being made to define [ 17 ] and reimburse [ 5 ] these services. Successful pain medicine practices will identify the most efficient means of providing high quality, comprehensive care—and this may likely include bringing themselves to the patient through the use of telemedicine. Telemedicine will improve pain medicine care—will your practice lead its implementation?
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.024 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.016 | 0.020 |
| Insufficient payload (model declined to judge) | 0.007 | 0.004 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".