The Difference in Practice Expense Costs Between Telehealth and In-Office Care Could Serve as the Basis for Differential Reimbursement Structures.

Background: There has been much recent discussion about the reimbursement of telehealth virtual visits. Advocates argue strongly for payment parity with in-person encounters, whereas payers insist that telehealth visits should be reimbursed at a lower value. Methods: Using the Resource-Based Relative Value Scale structure as a guideline (where physician compensation is divided into categories: time/medical decision making/malpractice expense and practice expense), we developed a framework to examine the difference in practice expense of an in-person practice compared with a scaled virtual practice. Results: We found that for current procedural terminology (CPT) code 99213, the total relative value unit (RVU) for a virtual visit would be 1.62. The in-office RVU for CPT code 99213 is 2.09. This difference could serve as the basis for a rational discussion on differential reimbursement for virtual visits.

Beyond performance metrics: modeling outcomes and cost for clinical machine learning.

Advances in medical machine learning are expected to help personalize care, improve outcomes, and reduce wasteful spending. In quantifying potential benefits, it is important to account for constraints arising from clinical workflows. Practice variation is known to influence the accuracy and generalizability of predictive models, but its effects on cost-effectiveness and utilization are less well-described. A simulation-based approach by Misic and colleagues goes beyond simple performance metrics to evaluate how process variables may influence the impact and financial feasibility of clinical prediction algorithms.

A randomized trial examining the effect of predictive analytics and tailored interventions on the cost of care.

This two-arm randomized controlled trial evaluated the impact of a Stepped-Care intervention (predictive analytics combined with tailored interventions) on the healthcare costs of older adults using a Personal Emergency Response System (PERS). A total of 370 patients aged 65 and over with healthcare costs in the middle segment of the cost pyramid for the fiscal year prior to their enrollment were enrolled for the study. During a 180-day intervention period, control group (CG) received standard care, while intervention group (IG) received the Stepped-Care intervention. The IG had 31% lower annualized inpatient cost per patient compared with the CG (3.7 K, $8.1 K vs. $11.8 K, p = 0.02). Both groups had similar annualized outpatient costs per patient ($6.1 K vs. $5.8 K, p = 0.10). The annualized total cost reduction per patient in the IG vs. CG was 20% (3.5 K, $17.7 K vs. $14.2 K, p = 0.04). Predictive analytics coupled with tailored interventions has great potential to reduce healthcare costs in older adults, thereby supporting population health management in home or community settings.

Beyond the COVID Pandemic, Telemedicine, and Health Care.

This article reviews the current experience and the flaws encountered in the rush to deploy telemedicine as a substitute for in-person care in response to the raging coronavirus (COVID-19) pandemic; the preceding fault lines in the U.S. health care system that exacerbated the problem; and the importance of emerging from this calamity with a clear vision for necessary health care reforms. It starts with the premise that the precursors of catastrophes of this magnitude provide a valid basis for planning corrective measures, improved preparedness, and ultimately serious health reform. Such reform should include standardized protocols for proper deployment of telemedicine to triage patients to the appropriate level and source of care at the point of need, proper use of relevant technological innovations to deliver precision medicine, and the development of regional networks to coordinate and improve access to care while streamlining the care process. The other essential element is a universal payment system that puts the United States at par with the rest of the industrialized countries, regardless of variation among them. The ultimate goal is creating an efficient, effective, accessible, and equitable system of care. Although timing is uncertain, the pandemic will be brought under control. The path to a better future after the pandemic offers some consolation for the massive loss of life and treasure during this pandemic.

Evaluating the Impact of a Web-Based Risk Assessment System (CareSage) and Tailored Interventions on Health Care Utilization: Protocol for a Randomized Controlled Trial.

BACKGROUND: Soaring health care costs and a rapidly aging population, with multiple comorbidities, necessitates the development of innovative strategies to deliver high-quality, value-based care. OBJECTIVE: The goal of this study is to evaluate the impact of a risk assessment system (CareSage) and targeted interventions on health care utilization. METHODS: This is a two-arm randomized controlled trial recruiting 370 participants from a pool of high-risk patients receiving care at a home health agency. CareSage is a risk assessment system that utilizes both real-time data collected via a Personal Emergency Response Service and historical patient data collected from the electronic medical records. All patients will first be observed for 3 months (observation period) to allow the CareSage algorithm to calibrate based on patient data. During the next 6 months (intervention period), CareSage will use a predictive algorithm to classify patients in the intervention group as "high" or "low" risk for emergency transport every 30 days. All patients flagged as "high risk" by CareSage will receive nurse triage calls to assess their needs and personalized interventions including patient education, home visits, and tele-monitoring. The primary outcome is the number of 180-day emergency department visits. Secondary outcomes include the number of 90-day emergency department visits, total medical expenses, 180-day mortality rates, time to first readmission, total number of readmissions and avoidable readmissions, 30-, 90-, and 180-day readmission rates, as well as cost of intervention per patient. The two study groups will be compared using the Student t test (two-tailed) for normally distributed and Mann Whitney U test for skewed continuous variables, respectively. The chi-square test will be used for categorical variables. Time to event (readmission) and 180-day mortality between the two study groups will be compared by using the Kaplan-Meier survival plots and the log-rank test. Cox proportional hazard regression will be used to compute hazard ratio and compare outcomes between the two groups. RESULTS: We are actively enrolling participants and the study is expected to be completed by end of 2018; results are expected to be published in early 2019. CONCLUSIONS: Innovative solutions for identifying high-risk patients and personalizing interventions based on individual risk and needs may help facilitate the delivery of value-based care, improve long-term patient health outcomes and decrease health care costs. TRIAL REGISTRATION: ClinicalTrials.gov NCT03126565; https://clinicaltrials.gov/ct2/show/NCT03126565 (Archived by WebCite at http://www.webcitation.org/6ymDuAwQA).

Retail Outlets Using Telehealth Pose Significant Policy Questions For Health Care.

Telehealth will enable new models of care to emerge as health care continues to undergo significant changes. Health insurers, providers, and pharmacy benefit managers are merging, which will consolidate market share among fewer large companies. Recently, retail giants such as Walmart and Amazon have announced plans to compete in the health care industry. As these organizations seek to provide convenient and affordable access to care, telehealth will play a significant role in the competition for market share and will create new opportunities for innovation. Additionally, the increasing adoption of telehealth by retail outlets and vertically integrated health care organizations raises new policy questions in such areas as information access, privacy and security, the combination of health and consumer data, and ways to foster provider independence amid increasing consolidation.

Health Care Cost Analyses for Exploring Cost Savings Opportunities in Older Patients: Longitudinal Retrospective Study.

BACKGROUND: Half of Medicare reimbursement goes toward caring for the top 5% of the most expensive patients. However, little is known about these patients prior to reaching the top or how their costs change annually. To address these gaps, we analyzed patient flow and associated health care cost trends over 5 years. OBJECTIVE: To evaluate the cost of health care utilization in older patients by analyzing changes in their long-term expenditures. METHODS: This was a retrospective, longitudinal, multicenter study to evaluate health care costs of 2643 older patients from 2011 to 2015. All patients had at least one episode of home health care during the study period and used a personal emergency response service (PERS) at home for any length of time during the observation period. We segmented all patients into top (5%), middle (6%-50%), and bottom (51%-100%) segments by their annual expenditures and built cost pyramids based thereon. The longitudinal health care expenditure trends of the complete study population and each segment were assessed by linear regression models. Patient flows throughout the segments of the cost acuity pyramids from year to year were modeled by Markov chains. RESULTS: Total health care costs of the study population nearly doubled from US $17.7M in 2011 to US $33.0M in 2015 with an expected annual cost increase of US $3.6M (P=.003). This growth was primarily driven by a significantly higher cost increases in the middle segment (US $2.3M, P=.003). The expected annual cost increases in the top and bottom segments were US $1.2M (P=.008) and US $0.1M (P=.004), respectively. Patient and cost flow analyses showed that 18% of patients moved up the cost acuity pyramid yearly, and their costs increased by 672%. This was in contrast to 22% of patients that moved down with a cost decrease of 86%. The remaining 60% of patients stayed in the same segment from year to year, though their costs also increased by 18%. CONCLUSIONS: Although many health care organizations target intensive and costly interventions to their most expensive patients, this analysis unveiled potential cost savings opportunities by managing the patients in the lower cost segments that are at risk of moving up the cost acuity pyramid. To achieve this, data analytics integrating longitudinal data from electronic health records and home monitoring devices may help health care organizations optimize resources by enabling clinicians to proactively manage patients in their home or community environments beyond institutional settings and 30- and 60-day telehealth services.

Healthcare utilization in older patients using personal emergency response systems: an analysis of electronic health records and medical alert data : Brief Description: A Longitudinal Retrospective Analyses of healthcare utilization rates in older patients using Personal Emergency Response Systems from 2011 to 2015.

BACKGROUND: Personal Emergency Response Systems (PERS) are traditionally used as fall alert systems for older adults, a population that contributes an overwhelming proportion of healthcare costs in the United States. Previous studies focused mainly on qualitative evaluations of PERS without a longitudinal quantitative evaluation of healthcare utilization in users. To address this gap and better understand the needs of older patients on PERS, we analyzed longitudinal healthcare utilization trends in patients using PERS through the home care management service of a large healthcare organization. METHODS: Retrospective, longitudinal analyses of healthcare and PERS utilization records of older patients over a 5-years period from 2011-2015. The primary outcome was to characterize the healthcare utilization of PERS patients. This outcome was assessed by 30-, 90-, and 180-day readmission rates, frequency of principal admitting diagnoses, and prevalence of conditions leading to potentially avoidable admissions based on Centers for Medicare and Medicaid Services classification criteria. RESULTS: The overall 30-day readmission rate was 14.2%, 90-days readmission rate was 34.4%, and 180-days readmission rate was 42.2%. While 30-day readmission rates did not increase significantly (p = 0.16) over the study period, 90-days (p = 0.03) and 180-days (p = 0.04) readmission rates did increase significantly. The top 5 most frequent principal diagnoses for inpatient admissions included congestive heart failure (5.7%), chronic obstructive pulmonary disease (4.6%), dysrhythmias (4.3%), septicemia (4.1%), and pneumonia (4.1%). Additionally, 21% of all admissions were due to conditions leading to potentially avoidable admissions in either institutional or non-institutional settings (16% in institutional settings only). CONCLUSIONS: Chronic medical conditions account for the majority of healthcare utilization in older patients using PERS. Results suggest that PERS data combined with electronic medical records data can provide useful insights that can be used to improve health outcomes in older patients.

Teledermatology: from historical perspective to emerging techniques of the modern era: part I: History, rationale, and current practice.

Telemedicine is the use of telecommunications technology to support health care at a distance. Technological advances have progressively increased the ability of clinicians to care for diverse patient populations in need of skin expertise. Dermatology relies on visual cues that are easily captured by imaging technologies, making it ideally suited for this care model. Moreover, there is a shortage of medical dermatologists in the United States, where skin disorders account for 1 in 8 primary care visits and specialists tend to congregate in urban areas. Even in regions where dermatologic expertise is readily accessible, teledermatology may serve as an alternative that streamlines health care delivery by triaging chief complaints and reducing unnecessary in-person visits. In addition, many patients in the developing world have no access to dermatologic expertise, rendering it possible for teledermatologists to make a significant contribution to patient health outcomes. Teledermatology also affords educational benefits to primary care providers and dermatologists, and enables patients to play a more active role in the health care process by promoting direct communication with dermatologists.

Teledermatology: from historical perspective to emerging techniques of the modern era: part II: Emerging technologies in teledermatology, limitations and future directions.

Telemedicine is the use of telecommunications technology to support health care at a distance. Dermatology relies on visual cues that are easily captured by imaging technologies, making it ideally suited for this care model. Advances in telecommunications technology have made it possible to deliver high-quality skin care when patient and provider are separated by both time and space. Most recently, mobile devices that connect users through cellular data networks have enabled teledermatologists to instantly communicate with primary care providers throughout the world. The availability of teledermoscopy provides an additional layer of visual information to enhance the quality of teleconsultations. Teledermatopathology has become increasingly feasible because of advances in digitization of entire microscopic slides and robot-assisted microscopy. Barriers to additional expansion of these services include underdeveloped infrastructure in remote regions, fragmented electronic medical records, and varying degrees of reimbursement. Teleconsultants also confront special legal and ethical challenges as they work toward building a global network of practicing physicians.

Telehealth among US hospitals: several factors, including state reimbursement and licensure policies, influence adoption.

Telehealth is widely believed to hold great potential to improve access to, and increase the value of, health care. Gaining a better understanding of why some hospitals adopt telehealth technologies while others do not is critically important. We examined factors associated with telehealth adoption among US hospitals. Data from the Information Technology Supplement to the American Hospital Association's 2012 annual survey of acute care hospitals show that 42 percent of US hospitals have telehealth capabilities. Hospitals more likely to have telehealth capabilities are teaching hospitals, those equipped with additional advanced medical technology, those that are members of a larger system, and those that are nonprofit institutions. Rates of hospital telehealth adoption by state vary substantially and are associated with differences in state policy. Policies that promote private payer reimbursement for telehealth are associated with greater likelihood of telehealth adoption, while policies that require out-of-state providers to have a special license to provide telehealth services reduce the likelihood of adoption. Our findings suggest steps that policy makers can take to achieve greater adoption of telehealth by hospitals.

The future of Connected Health in preventive medicine.

Over the last decade, Connected Health (CH) has shown great value in the management of chronic disease (CD), but has limited application in preventing these diseases that remain a huge burden to the society. Technological advances have made determination of genetic predisposition to disease possible and have gained wide use in oncology to develop more effective and individualized treatment strategies-Personalized Medicine. There is growing interest in the application of these genetic tests in predicting risk for complex genetic diseases; even, direct-to-consumer tests are increasingly becoming available and affordable. CH has shown great potential in collecting phenotypic data, which can be overlaid on genomic data to deliver a more precise and personalized preventive care that better engages patients. The goal of a CH program that uses genetic data would be to monitor individuals' risk factors and predict the onset of CD. This prediction would be coupled with coaching to delay or prevent the onset of disease. However, the challenge remains that many CDs are due to complex interaction between genes and modifiable environmental risk factors that are still under-studied.

Implementing a web-based home monitoring system within an academic health care network: barriers and facilitators to innovation diffusion.

The practice of outpatient type 2 diabetes management is gradually moving from the traditional visit-based, fee-for-service model to a new, health information communication technology (ICT)-supported model that can enable non-visit-based diabetes care. To date, adoption of innovative health ICT tools for diabetes management has been slowed by numerous barriers, such as capital investment costs, lack of reliable reimbursement mechanisms, design defects that have made some systems time-consuming and inefficient to use, and the need to integrate new ICT tools into a system not primarily designed for their use. Effective implementation of innovative diabetes health ICT interventions must address local practice heterogeneity and the interaction of this heterogeneity with clinical care delivery. The Center for Connected Health at Partners Healthcare has implemented a new ICT intervention, Diabetes Connect (DC), a Web-based glucose home monitoring and clinical messaging system. Using the framework of the diffusion of innovation theory, we review the implementation and examine lessons learned as we continue to deploy DC across the health care network.

Remote assessment of acne: the use of acne grading tools to evaluate digital skin images.

Digital imaging of dermatology patients is a novel approach to remote data collection. A number of assessment tools have been developed to grade acne severity and to track clinical progress over time. Although these tools have been validated when used in a face-to-face setting, their efficacy and reliability when used to assess digital images have not been examined. The main purpose of this study was to determine whether specific assessment tools designed to grade acne during face-to-face visits can be applied to the evaluation of digital images. The secondary purpose was to ascertain whether images obtained by subjects are of adequate quality to allow such assessments to be made. Three hundred (300) digital images of patients with mild to moderate facial inflammatory acne from an ongoing randomized-controlled study were included in this analysis. These images were obtained from 20 patients and consisted of sets of 3 images taken over time. Of these images, 120 images were captured by subjects themselves and 180 were taken by study staff. Subjects were asked to retake their photographs if the initial images were deemed of poor quality by study staff. Images were evaluated by two dermatologists-in-training using validated acne assessment measures: Total Inflammatory Lesion Count, Leeds technique, and the Investigator's Global Assessment. Reliability of raters was evaluated using correlation coefficients and kappa statistics. Of the different acne assessment measures tested, the inter-rater reliability was highest for the total inflammatory lesion count (r = 0.871), but low for the Leeds technique (kappa = 0.381) and global assessment (kappa = 0.3119). Raters were able to evaluate over 89% of all images using each type of acne assessment measure despite the fact that images obtained by study staff were of higher quality than those obtained by patients (p < 0.001). Several existing clinical assessment measures can be used to evaluate digital images obtained from subjects with inflammatory acne lesions. The level of inter-rater agreement is highly variable across assessment measures, and we found the Total Inflammatory Lesion Count to be the most reliable. This measure could be used to allow a dermatologist to remotely track a patient's progress over time.