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Automated-Entry Patient-Generated Health Data for Chronic Conditions: The Evidence on Health Outcomes

Technical Brief Draft

Open for comment through Jul 17, 2020

This report is available in PDF only (Draft Technical Brief [1.5 MB]; Draft Appendixes [2.1 MB]). For additional assistance, please contact us.

Structured Abstract

Background. Automated-entry consumer devices that collect and transmit patient-generated health data (PGHD) are currently being evaluated as potential tools to aid in the management of chronic diseases. The majority of consumer health technologies entering the U.S. market have not undergone FDA scrutiny. Manufacturers of non-FDA-regulated devices cannot legally make claims that their devices meet any stated performance/clinical standards, although they will often allude to the performance of their devices through carefully worded marketing. The need exists to evaluate the evidence regarding consumer PGHD technologies, particularly for devices that have not gone through FDA evaluation.

Purpose. To summarize the research related to automated-entry consumer health technologies that provide PGHD for the prevention or management of 11 chronic diseases.

Methods. The project scope was determined through discussions with Key Informants. KIs agreed with our proposal to focus on technologies available to consumers without a prescription that provide automated data capture, as well as our proposal to not require that data be automatically transmitted to health care staff. We searched MEDLINE and EMBASE (via EMBASE.com), In-Process MEDLINE and PubMed unique content (via PubMed.gov), and the Cochrane Database of Systematic Reviews for systematic reviews or controlled trials. We also searched ClinicalTrials.gov for ongoing studies. We used eligibility criteria to screen abstracts and full articles before study-level data abstraction. We assessed risk of bias and extracted data on health outcomes, surrogate outcomes, usability, sustainability, cost-effectiveness outcomes (quantifying the trade-offs between health effects and cost), process outcomes, and other characteristics related to PGHD technologies. To assess device similarity with devices currently marketed by the same manufacturer, device engineers used a 1–4 scale (1 being similar to current models, 2 being somewhat different to current models, 3 being very different to current models, and 4 being unable to reliably assess similarity to current models). For isolated effects on health outcomes, we classified the results in one of four categories: (1) likely no effect, (2) unclear, (3) possible positive effect, or (4) likely positive effect. When we categorized the data as "unclear" based solely on health outcomes, we then examined surrogate outcomes for that particular clinical condition. We then used these surrogate data, along with the direct effects on health outcomes, to determine which of the four categories was most appropriate.

Findings. We identified 111 unique studies that met inclusion criteria. The largest number of studies addressed patients with hypertension (50 studies) and obesity (43 studies). Eighty-three trials used a single PGHD device, 22 used 2 PGHD devices, and the other 6 used 3 or more PGHD devices. Pedometers, blood pressure (BP) monitors, and scales were commonly used in the same studies. Overall, we found a "possible positive effect" of PGHD interventions on health outcomes for hypertension, coronary artery disease, heart failure, and asthma. We rated PGHD interventions for obesity as having "likely no effect" on health outcomes. We considered the findings "unclear" regarding PGHD interventions for diabetes prevention, sleep apnea, cardiac arrhythmias or conduction abnormalites, stroke, Parkinson's disease, and chronic obstructive pulmonary disease. For these conditions, most studies lacked adequate statistical power to detect a clinically important between-group difference on health outcomes. Most studies did not report harms related to PGHD interventions; the relatively few harms reported were minor and transient, with event rates usually comparable to harms in the control groups. Few studies reported cost-effectiveness analyses, and only for PGHD interventions for hypertension, coronary artery disease and chronic obstructive pulmonary disease; the findings were variable across different chronic conditions and devices. Patient adherence to PGHD interventions was highly variable across studies, but patient acceptance/satisfaction and usability was generally fair to good. However, device engineers independently evaluated consumer wearable and handheld BP monitors and considered the user experience to be poor, while their assessment of smartphone-based ECG monitors found the user experience to be good. Student volunteers involved in device usability testing of the Weight Watchers Online app found it well-designed and relatively easy to use.

Implications. Multiple randomized controlled trials (RCTs) have evaluated some PGHD technologies (e.g., pedometers, scales, BP monitors), particularly for obesity and hypertension, but health outcomes were generally underreported. Despite this limitation, we found evidence suggesting a possible positive effect of PGHD interventions on health outcomes for 4 chronic conditions. Lack of reporting of health outcomes and insufficient statistical power to assess these outcomes comprise the main reasons we considered the effect of PGHD on health outcomes as "unclear" for some chronic conditions. In general, the majority of studies on PGHD technologies still focus on non-health-related outcomes, even among chronic conditions with the largest evidence bases. Future RCTs should focus on measuring the effects of these technologies on health outcomes in patients with chronic disease. Furthermore, many current RCTs did not isolate the effect of the PGHD intervention from other components in a multicomponent intervention. Future studies should be designed to isolate the effect of the PGHD intervention (e.g. PGHD + X versus X alone).

Evidence Summary

Main Points

  • 111 controlled trials on 11 chronic conditions studied the use of automated-entry consumer devices that capture patient generated health data (PGHD)
  • Possible positive effect of PGHD technologies for three chronic conditions (coronary artery disease, heart failure, and asthma), based on direct health outcomes data
  • Possible positive effect on hypertension health outcomes, based on consistent surrogate data (systolic blood pressure, diastolic blood pressure)
  • Likely no effect on obesity health outcomes, based on consistent surrogate data (BMI, weight)
  • Potential benefit was unclear for other conditions.
  • Patient adherence to PGHD interventions was highly variable and patient acceptance/satisfaction and usability was generally fair to good.
  • Future studies should measure long-term health outcomes and attempt to isolate the effect of PGHD technologies.

Background and Purpose

Automated-entry consumer devices that collect and transmit patient-generated health data (PGHD) are currently being evaluated as potential tools to aid in the management of chronic diseases. The majority of consumer health technologies entering the U.S. market have not undergone FDA scrutiny. While these technologies provide much information to patients and providers, we focused on whether they improve health outcomes for patients with chronic conditions (e.g., hypertension, obesity, coronary artery disease). In summary, we examined the evidence on health outcomes related to automated-entry consumer technologies that provide PGHD for the prevention or management of 11 chronic diseases.

Methods

We employed methods consistent with those outlined in the AHRQ EPC Program Methods Guidance, and we describe these in the full report. Our searches covered publication dates up to December 23, 2019. We determined whether each study had constructed comparisons group(s) that isolated the effect of the PGHD technology. For isolated effects on health outcomes, we classified the results in one of four categories: (1) likely no effect, (2) unclear, (3) possible positive effect, or (4) likely positive effect. If the results consistently demonstrate the lack of an effect (via narrow confidence intervals around a null effect), we coded it as "likely no effect." We examined key surrogate outcomes (e.g., blood pressure for hypertension, BMI for obesity) whenever the direct health outcome data were unclear. We also tabulated data on the frequency of device usage, ease of use, technical problems, and cost-effectiveness.

Results

Clinical Condition Results Categorization for Isolated Health Outcomes Comments
Obesity Likely no effect

3 of 43 included trials reported whether there were isolated effects on health outcomes (specifically, quality of life), and overall results were unclear.

14 trials reported whether there were isolated effects of device presence on surrogate outcomes (BMI or weight), and all 25 point estimates were less than the minimal important difference (5% body weight).

Diabetes prevention Unclear

None of the three trials reported whether there were isolated effects on health outcomes.

One trial reported a surrogate outcome (metabolic syndrome risk) and it found an advantage of PGHD, however it was at high risk of bias.

Sleep apnea Unclear

None of the three trials reported whether there were isolated effects on health outcomes.

One trial reported a surrogate outcome (number of days on which apnea events were witnessed) and it found no statistically significant difference and was at high risk of bias.

Hypertension Possible positive effect

Six of the 50 included studies reported whether there were isolated effects on health outcomes (including quality of life, mortality, and hospitalizations), and overall results were unclear.

Seventeen studies reported whether there were isolated effects of device presence on surrogate outcomes (SBP, DBP, and BP control), and results generally favored PGHD arms.

Coronary artery disease Possible positive effect Mortality was significantly lower in the PGHD arm in the only study that reported it. Re-hospitalization was also lower but did not reach statistical significance.
Heart failure Possible positive effect Different quality of life measures favored the PGHD intervention group in two studies that isolated the effect of PGHD.
Cardiac arrhythmias or conduction abnormalities Unclear There were no statistically significant between-group differences in health outcomes that favored the PGHD intervention. One low risk study found a higher rate of emergency room visits in the AliveCor group, but a positive effect of PGHD for time to arrhythmia detection. Overall, the effect of PGHD on health outcomes is unclear.
Stroke Unclear The single trial did not report whether there were isolated effects on health outcomes
Parkinson's Disease Unclear No studies met inclusion criteria
COPD Unclear 3 of 9 RCTs reported isolated effects on health outcomes, but data were unclear. Data on surrogate outcomes (e.g., lung function) were also unclear.
Asthma Possible positive effect 1 study met inclusion criteria (moderate risk of bias), and it found better symptom control in the PGHD group overall and in the pediatric population alone.

Also, student volunteers involved in usability testing of the Weight Watchers Online app found it well-designed and relatively easy to use. Device engineers independently evaluated consumer wearable and handheld BP monitors and considered the user experience to be poor, while their assessment of smartphone-based ECG monitors found the user experience to be good.

Strengths and Limitations

The above findings summarize studies that used an isolated-effect design (e.g., PGHD alone vs no intervention, or PGHD + X vs. X alone). Many other studies used multicomponent interventions (of which PGHD was one component), making it impossible to determine the impact of PGHD. Furthermore, many included studies reported only surrogate outcomes, or only followed patients for a short amount of time (e.g., 3 months).

Implications and Conclusions

Automated-entry consumer PGHD technologies provide a wealth of information for patients and providers, and for four chronic conditions, evidence suggests a possible positive effect on health outcomes. Clinicians might consider recommending that patients with these conditions use a consumer technology for self-monitoring, such as recommending a blood pressure monitor for patients with hypertension.

For obesity, we found consistent evidence of no important effect on either BMI or weight, suggesting that there is likely no effect on health outcomes. The most common devices in the obesity studies were accelerometers and pedometers, therefore measuring one's steps per day does not appear to reduce weight or improve health.

For many other conditions, however, the available evidence is unclear on the PGHD effect on health outcomes. More studies with an isolated-effect design, measuring health outcomes in the long term, may help reduce the uncertainty of the impact of PGHD technologies.