Back in June, I suggested self-service might be an approach for facilitating behavior change for risk factors linked to healthcare spending (e.g., depression, weight, tobacco use, alcohol). The approach may also have value to manage chronic disease. Self-service could be initial support for patients with clear diagnoses linked to low-risk interventions that could improve their quality of life before engaging with a licensed healthcare worker. Telemedicine and face-to-face interactions could then serve as progressively higher levels of support for more complex cases. Cardiovascular disease (including diabetes and chronic kidney disease), some mental health conditions, and musculoskeletal conditions managed with non-pharmacologic interventions might be suitable for self-service. Other conditions that have reached a “steady-state” (cancer in remission, chronic neurological conditions, inflammatory bowel disease) may also benefit from self-service.
For chronic disease self-service to make a meaningful impact on overall chronic disease management, the approach would need to:
- Support assessments without a provider encounter, including patient surveys, laboratory testing and/or imaging procedures for disease monitoring without a provider encounter,
- Manage handoffs to and from the patient’s regular treatment team for periods where the patient needs additional assistance, and
- Coordinate chronic disease management with other healthcare team members who are not part of the patient’s regular during acute health events (e.g., hospitalizations, planned procedures),
- Calibrate treatment goals against the patient’s other priorities over time (e.g., transition to hospice)
The Global Observatory for eHealth of the World Health Organization (WHO) defined mobile health (mHealth) as “medical and public health practice supported by mobile devices, such as mobile phones, patient monitoring devices, personal digital assistants and other wireless devices.” The group included short messaging service (SMS), 3rd and 4th generation mobile telecommunications (3G and 4G), global positioning system and Bluetooth technology within mHealth. The Global Health Data Exchange identified these conditions as contributing the most Disability-Adjusted Life Years (DALYs) across the world and in the United States in 2017:
|1. Neonatal disorders||Maybe||No||1. Ischemic heart disease||Yes||Yes|
|2. Ischemic heart disease||Yes||Yes||2. Drug use disorders||No||Maybe (monitoring)|
|3. Stroke||Yes||Yes||3. Chronic obstructive pulmonary disease||Yes||Yes|
|4. Lower respiratory infections||No||No||4. Low back pain||Yes||Yes|
|5. Chronic obstructive pulmonary disease||Yes||Yes||5. Diabetes mellitus||Yes||Yes|
|6. Diarrheal diseases||No||No||6. Tracheal, bronchus, and lung cancer||Yes||Yes (surveillance)|
|7. Diabetes mellitus||Yes||Yes||7. Stroke||Yes||Yes|
|8. Road injuries||No||No||8. Headache disorders||No||Yes|
|9. Low back pain||Yes||Yes||9. Road injuries||No||No|
|10. Congenital birth defects||No||No||10. Alzheimer’s disease and other dementias||No||No|
Some conditions not listed (e.g., hypertensive heart disease, chronic kidney disease, depressive disorders, age-related and other hearing loss) probably contribute to conditions on these lists (e.g., ischemic heart disease, Alzheimer’s disease and other dementias). Those conditions might also benefit from a self-service approach. Savings from managing conditions after a diagnosis appears to be easier to attribute to self-service interventions than preventing diagnoses in the first place. The 2017 US Preventive Services Task Forces systemic review was unable to identify an effect on all-cause or cardiovascular disease mortality with high-intensity diet-only interventions. The review did find some quality of life improvements over 6-12 months in groups assigned to physical activity interventions, but the improvements were not consistently better than the control groups. Both diet and exercise interventions were associated with improvements in diet intake and physical activity, respectively.
Published Research for Treatment & Surveillance
Margolius et al. found home blood pressure monitoring, weekly health coaching (by university employees and volunteers with bachelor’s degrees) and home titration of blood pressure medications did not lower blood pressure more than home blood pressure monitoring and health coaching without home titration of blood pressure medications. The home titration group did have about one fewer office visit every six months. The study investigators noted that participants with more health coach encounters had greater reductions in systolic blood pressure. Chen et al. published a meta-analysis of four studies with a medication-titration intervention with home blood pressure control earlier this year. They found the medication-titration intervention did reduce blood pressure (6.86/3.03 mm Hg), but did not signficantly affect quality of life (measured by EQ-5D scores). In December 2018, Fisher et al. published their results of an entirely remote, non-physician led hypertension management program showing over 80% of enrolled patients with a clinic blood pressure of >=140/90 reached a blood pressure goal of <135/85 mmg Hg with a nurse practitioner and pharmacists adjusting blood pressure medications per their protocol. A 2017 systematic review and individual patient data meta-analysis of self-monitoring of blood pressure found progressively higher rates of blood pressure reduction when self-monitoring was paired with web/phone feedback (mean systolic blood pressure [SBP] reduction 1.98 mm Hg), web/phone feedback with education (mean SBP reduction 4.42 mm Hg) and counseling/telecounseling (mean SBP reduction 6.10 mm Hg) compared to self-monitoring without feedback (mean SBP reduction 1.02 mm Hg [not significant]).
Mobile phone apps have been shown to reduce glycated hemoglobin among patients with type 2 diabetes, but not type 1 diabetes or pre-diabetes. The apps included modules for lifestyle modification monitoring, health education, medication or insulin adjustment, logging of clinical measurements and health management feedback. Only three of the 13 apps provided adjustment support for medications and none of the aps had an insulin bolus calculator.
In September 2018, Choudhry et al. published a cluster randomized controlled trial testing a multicomponent intervention with telephone-delivered behavioral interviewing by trained clinical pharmacists, text messaging, pillboxes and mailed progress reports to patients with suboptimal hyperlipidemia, hypertension or diabetes disease control. The researchers found an increase in medication adherence without a change in any measure of disease control, hospitalization or office visit frequency.
- COPD – an eHealth platform improved symptoms, but had no effect on the patients’ functional state due to an increase in anxiety and depression from the intervention.
- Heart failure – in an Iraninan 2019 study, telemonitoring improved self-care behaviors, but did not reduce readmission rates. A 2015 overview of home telemonitoring intervention systemic reviews classified home telemonitoring interventions into: automated device-based telemonitoring, telemonitoring of vital signs, telemonitoring of vital signs and symptoms, mobile telemonitoring, interactive voice response, video consultation with vital signs monitoring and all types combined. Of these seven variations, only automated device-based telemonitoring and telemonitoring of vital signs had a significant reduction in all-cause mortality when compared to usual care, but the authors admit none of the evidence is high-quality.
- Mental health – telephone and remote medication monitoring for treatment adherence to reduce symptom severity and inpatient days, but telehealth’s outcomes on addressing severe mental health (for this systemic review, schizophrenia, schizoaffective disorder, psychotic disorder and bipolar disorder) were inconsistent.
Increasing Patient/Caregiver Engagement
A recent qualitative review of seven telemedicine trials including blood pressure, diabetes, COPD and heart failure identified four main themes:
- Data use
- Patient measurement of blood pressure was more likely to lead to increased medication adherence, other behavior change and higher levels of engagement,
- Blood sugar tracking was not associated with more aggressive medication titration by healthcare professionals as they would wait for A1C results instead, but the measurements did prompt improvements in dietary choices and medication adherence,
- Pulse oximetry for COPD patients did not change medication adherence, but some patients reported feeling more confident after seeing high oxygen saturation readings without pulmonary symptoms.
- Empowering patients – patients reported they were more able to participate actively in consultations and manage their health with at-home readings (although a small number felt more anxious),
- Adjusting the model of care – provider offices may not be staffed to monitor large volumes of patient-generated health data, and
- System design – the absence of ad-hoc messaging hindered the ability for patients and healthcare professionals to discuss abnormal measurements in real-time.
Patients with chronic diseases who do not engage with self-service tools to manage their conditions may have a higher risk of missing follow-up interactions if they do not engage with the self-service tools. Patients who receive feedback about their measurements may be more likely to engage with home monitoring programs.
Self-service for healthy behaviors and chronic disease management could liberate patients and caregivers from relying on licensed healthcare providers to manage these phenomena that imply long-term assessment. Independent ordering providers would need to focus their efforts on confirming diagnoses detected incidentally or making diagnoses for patients wtih unexplained symptoms. Provider quality metrics would shift to focus on diagnostic ability and communication skills to help patients manage their own condition. The literature suggests more work needs to be done to refine the interventions and how their interact with the traditional healthcare system to maximize effectiveness while simultanenously making a meangingful improvement in healthcare value to patients.