Table 1.

Characteristics of included publications.

Title	Authors	Quality	Year	Country	Patient Population	Provider Population	Caregiver Population	PGHD Types
Barriers and benefits to using mobile health technology after operation: a qualitative study	Abelson et al.43	4	2017	USA	800 Phone survey respondents	N/A	N/A	N/A
Beyond self-monitoring: understanding non-functional aspects of home-based healthcare technology	Gronvall and Verdezoto44	3	2013	Denmark	6 Pregnant women with complications 7 Older adults with heart conditions 6 Healthy self-monitoring older adults	1 midwife for pregnant patients Unknown number hospital nurses for patients with heart conditions	N/A	Pregnant women: Weight, blood pressure, pulse, CTG, urine protein levels, online questionnaire Heart condition patients: Weight, blood pressure, pulse, symptom survey, ECG data (subset of participants) Health older adults: Blood pressure
“My Doctor is Keeping an Eye on Me!”: exploring the clinical applicability of a mobile food logger	Kim et al.45	3	2016	South Korea	20 Patients with lifestyle diseases (e.g. hypertension, diabetes, heart disease)	otorhinolarynologist family medicine physicians 1 OBGYN 1 rehabilitation physician 1 urologist	N/A	Food intake, perceptions of post-meal fullness, meal contexts, meal time, activity levels, and activity trackers
Boundary negotiating artifacts in personal informatics: patient- provider collaboration with patient-generated data	Chung et al.46	3	2016	USA	21 1 Surveyed patients who were overweight, obese, or diagnosed with IBS Interviews: 7 Overweight/obese patients 2 Patients diagnosed with IBS 9 Overweight/obese patients diagnosed with IBS	family medicine physicians 5 gastroenterologists dieticians 1 behavioral psychologist 1 APRN 1 health navigator	N/A	Food intake, calorie intake, physical activity levels, weight, heart rates, sleep quality, pain levels, medication use, bowel movement, stress, fatigue, nausea.
Evaluation of a web-based asthma self-management system: a randomized controlled pilot trial	Wiecha et al.47	3	2015	USA	58 Children ages 9–17 diagnosed with persistent asthma	Unknown number of primary care providers Unknown number of asthma nurses or asthma specialists	Parent or guardian of children participants	Peak flow readings, symptoms (e.g. cough, wheeze, shortness of breath), contextual data (e.g. activity limitations, missed school, ED visits), medication use
Information technology supporting diabetes self-care: a pilot study	Halkoaho et al48	2	2007	Finland	3 Type 1 diabetics 6 Type 2 diabetics	3 nurses	N/A	Blood glucose levels and treatment goals
Yet another hypertension telehealth solution? the rules will tell you	Lehocki et al.49	2	2014	Slovakia	2 Patients diagnosed with hypertension and unspecified comorbidities	Unspecified providers	N/A	Blood pressure, pulse
Nurses’ and community support workers’ experience of telehealth: a longitudinal case study	Sharma and Clarke50	4	2014	United Kingdom	Patients diagnosed with asthma, diabetes, COPD, or CHF (not recruited for study participation)	Nurses treating patients with asthma, diabetes, COPD, or CHF Community support workers	N/A	Blood glucose level, weight, blood pressure, oxygen level and heart rate.
Using a mobile app to manage type 1 diabetes: the case of TreC diabetes	Miele et al.51	2	2015	Italy	15 Children aged 4–12 diagnosed with type 1 diabetes	Diabetes specialist	Parent or guardian of children participants	Blood glucose values, meal compostion, carbohydrate content, and physical activity levels
Improving diabetes management with a patient portal: a qualitative study of diabetes self-management portal	Urowitz et al.52	3	2012	Canada	1 Patient diagnosed with type 1 diabetes 6 Patients diagnosed with type diabetes	Unspecified number of: General practitioners Dieticians APRNS Diabetes educators	N/A	All participants recorded blood glucose levels Additional data collected at provider discretion on a per patient basis (e.g. weight, blood pressure)
Integrating patient-generated health data into clinical care settings or clinical decision-making: lessons learned from project HealthDesign	Cohen et al.53	3	2016	USA	Patients diagnosed with moderate-to-severe asthma Older adults at risk for cognitive decline Adolescent receiving behavioral health interventions Patient’s diagnosed with Crohn’s disease Premature infants with medical complications (not recruited for study participation)	Primary care providers Nurses Gastroenterologists High-risk infant case managers	Parent or guardian of infant participants (Not recruited for study participation)	Asthma patients: medication use, peak flow measurements, environmental factors Older adults: task completion (data not shared with provider) Adolescents: Food intake, physical activity, mood Crohn’s disease patients: Weight, physical activity, mood, relevant symptoms Premature infants: infant weight, food consumption, elimination patterns
Using patient-generated health data from mobile technologies for diabetes self-management support: provider perspectives from an academic medical center	Nundy et al.54	3	2014	USA	Unspecified number of type 1 or type 2 diabetic patients	Unspecified number of nursecare managers 10 primary care providers 2 endocrinologists & diabetes specialists	N/A	Medication use, blood glucose levels, barriers to diabetes self-care
More than telemonitoring: health provider use and nonuse of life-log data in irritable bowel syndrome and weight management	Chung et al.55	3	2015	USA	Patients who are overweight/ obese and/or diagnosed with IBS	family medicine physicians 5 gaste nterologists 1 APRN dieticians 1 behavioral psychologist 1 health navipator	N/A	Physical activity levels, food/diet data, stress logs, sleep logs, mood diaries

N/A: not applicable; APRN: Advanced practice registered nurse; CHF: Congestive heart failureCOPD: Chronic obstructive pulmonary disease; CTG: Cardiotocograph; ECG: Electrocardiogram; ED: Emergency department; IBS: Irritable bowel syndrome; OBGYN: Obstetrics and gynecology; PGHD: patient-generated health data.