Mitchell Tang

Remote patient monitoring (RPM) is a promising tool for improving chronic disease management. Use of RPM for hypertension monitoring is growing rapidly, raising concerns about increased spending. However, the effects of RPM are still unclear. To estimate RPM's effect on hypertension care and spending. Matched observational study emulating a longitudinal, cluster randomized trial. After matching, effect estimates were derived from a regression analysis comparing changes in outcomes from 2019 to 2021 for patients with hypertension at high-RPM practices versus those at matched control practices with little RPM use. Traditional Medicare. Patients with hypertension. Receipt of care at a high-RPM practice. Primary outcomes included hypertension medication use (medication fills, adherence, and unique medications received), outpatient visit use, testing and imaging use, hypertension-related acute care use, and total hypertension-related spending. 192 high-RPM practices (with 19 978 patients with hypertension) were matched to 942 low-RPM control practices (with 95 029 patients with hypertension). Compared with patients with hypertension at matched low-RPM practices, patients with hypertension at high-RPM practices had a 3.3% (95% CI, 1.9% to 4.8%) relative increase in hypertension medication fills, a 1.6% (CI, 0.7% to 2.5%) increase in days' supply, and a 1.3% (CI, 0.2% to 2.4%) increase in unique medications received. Patients at high-RPM practices also had fewer hypertension-related acute care encounters (-9.3% [CI, -20.6% to 2.1%]) and reduced testing use (-5.9% [CI, -11.9% to 0.0%]). However, these patients also saw increases in primary care physician outpatient visits (7.2% [CI, -0.1% to 14.6%]) and a $274 [CI, $165 to $384]) increase in total hypertension-related spending. Lacked blood pressure data; residual confounding. Patients in high-RPM practices had improved hypertension care outcomes but increased spending. National Institute of Neurological Disorders and Stroke.

Background: The use of digital health measurement tools has grown substantially in recent years. However, there are concerns that the promised benefits from these products will not be shared equitably. Underserved populations, such as those with lower education and income, racial and ethnic minorities, and those with disabilities, may find such tools poorly suited for their needs. Because underserved populations shoulder a disproportionate share of the US disease burden, they also represent a substantial share of digital health companies’ target markets. Incorporating inclusive principles into the product development process can help ensure that the resulting tools are broadly accessible and effective. In this context, inclusivity not only maximizes societal benefit but also leads to greater commercial success. Objective: A critical element in fostering inclusive product development is building the business case for why it is worthwhile. The Digital Health Measurement Collaborative Community (DATAcc) Market Opportunity Calculator was developed as an open-access resource to enable digital health measurement product developers to build a business case for incorporating inclusive practices into their research and development processes. Methods: The DATAcc Market Opportunity Calculator combines data on population demographics and disease prevalence and health status from the US Census Bureau and the US Centers for Disease Control and Prevention (CDC). Together, these data are used to calculate the share of US adults with specific conditions (eg, diabetes) falling into various population segments along key “inclusion vectors” (eg, race and ethnicity). Results: A free and open resource, the DATAcc Market Opportunity Calculator can be accessed from the DATAcc website. Users first select the target health condition addressed by their product, and then an inclusion vector to segment the patient population. The calculator displays each segment as a share of the overall US adult population and its share specifically among adults with the target condition, quantifying the importance of underserved patient segments to the target market. The calculator also estimates the value of improvements to product inclusivity by modeling the downstream impact on the accessible market size. For example, simplifying prompts on a hypertension-focused product to make it more accessible for adults with lower educational attainment is shown by the calculator to increase the target market by 2 million people and the total addressable market opportunity by US $200 million. Conclusions: Digital health measurement is still in its infancy. Now is the time to establish a precedent for inclusive product development to maximize societal benefit and build sustainable commercial returns. The Market Opportunity Calculator can help build the business case for “why”—showing how inclusivity can translate to financial opportunity. Once the decision has been made to pursue inclusive design, other components of the broader DATAcc toolkit for inclusive product development can support the “how.”

BACKGROUND The use of digital health measurement tools has grown substantially in recent years. However, there are concerns that the promised benefits from these products will not be shared equitably. Underserved populations, such as those with lower education and income, racial and ethnic minorities, and those with disabilities, may find such tools poorly suited for their needs. Because underserved populations shoulder a disproportionate share of the US disease burden, they also represent a substantial share of digital health companies’ target markets. Incorporating inclusive principles into the product development process can help ensure that the resulting tools are broadly accessible and effective. In this context, inclusivity not only maximizes societal benefit but also leads to greater commercial success. OBJECTIVE A critical element in fostering inclusive product development is building the business case for why it is worthwhile. The Digital Health Measurement Collaborative Community (DATAcc) Market Opportunity Calculator was developed as an open-access resource to enable digital health measurement product developers to build a business case for incorporating inclusive practices into their research and development processes. METHODS The DATAcc Market Opportunity Calculator combines data on population demographics and disease prevalence and health status from the US Census Bureau and the US Centers for Disease Control and Prevention (CDC). Together, these data are used to calculate the share of US adults with specific conditions (eg, diabetes) falling into various population segments along key “inclusion vectors” (eg, race and ethnicity). RESULTS A free and open resource, the DATAcc Market Opportunity Calculator can be accessed from the DATAcc website. Users first select the target health condition addressed by their product, and then an inclusion vector to segment the patient population. The calculator displays each segment as a share of the overall US adult population and its share specifically among adults with the target condition, quantifying the importance of underserved patient segments to the target market. The calculator also estimates the value of improvements to product inclusivity by modeling the downstream impact on the accessible market size. For example, simplifying prompts on a hypertension-focused product to make it more accessible for adults with lower educational attainment is shown by the calculator to increase the target market by 2 million people and the total addressable market opportunity by US $200 million. CONCLUSIONS Digital health measurement is still in its infancy. Now is the time to establish a precedent for inclusive product development to maximize societal benefit and build sustainable commercial returns. The Market Opportunity Calculator can help build the business case for “why”—showing how inclusivity can translate to financial opportunity. Once the decision has been made to pursue inclusive design, other components of the broader DATAcc toolkit for inclusive product development can support the “how.”

Policy Points: Current telehealth policy discussions are focused on synchronous video and audio telehealth visits delivered by traditional providers and have neglected the growing number of alternative telehealth offerings. These alternative telehealth offerings range from simply supporting traditional brick‐and‐mortar providers to telehealth‐only companies that directly compete with them. We describe policy challenges across this range of alternative telehealth offerings in terms of using the appropriate payment model, determining the payment amount, and ensuring the quality of care.

The COVID-19 pandemic changed clinician electronic health record (EHR) work in a multitude of ways. To evaluate how, we measure ambulatory clinician EHR use in the United States throughout the COVID-19 pandemic. We use EHR meta-data from ambulatory care clinicians in 366 health systems using the Epic EHR system in the United States from December 2019 to December 2020. We used descriptive statistics for clinician EHR use including active-use time across clinical activities, time after-hours, and messages received. Multivariable regression to evaluate total and after-hours EHR work adjusting for daily volume and organizational characteristics, and to evaluate the association between messages and EHR time. Clinician time spent in the EHR per day dropped at the onset of the pandemic but had recovered to higher than prepandemic levels by July 2020. Time spent actively working in the EHR after-hours showed similar trends. These differences persisted in multivariable models. In-Basket messages received increased compared with prepandemic levels, with the largest increase coming from messages from patients, which increased to 157% of the prepandemic average. Each additional patient message was associated with a 2.32-min increase in EHR time per day (P < .001). Clinicians spent more total and after-hours time in the EHR in the latter half of 2020 compared with the prepandemic period. This was partially driven by increased time in Clinical Review and In-Basket messaging. Reimbursement models and workflows for the post-COVID era should account for these demands on clinician time that occur outside the traditional visit.