CClinicalTrials.gg
CompletedNCT03451630ICUpdated Dec 9, 2024Results posted

Integrated Care (IC) Models for Patient-Centered Outcomes

An interventional study of High-Touch and High-Tech in Diabetes, Asthma and Chronic Obstructive Pulmonary Disease, sponsored by University of Pittsburgh. Completed at 1 site in United States. Open to participants aged 21 Years and older, including healthy volunteers. Per ClinicalTrials.gov, last updated 2024-12-09.

Sponsored by University of Pittsburgh · Not applicable, Interventional, and Health services research

Phase
Not applicable
Study type
Interventional
Enrollment
1,400
Allocation
Randomized
Ages
21 Years and older
Sex
All
01

Study summary

Multiple chronic conditions (MCC) are widely recognized as the U.S. public health challenge of the 21st century. These physical and behavioral health conditions take a large toll on those living with chronic diseases, including many who are publicly insured, as well as caregivers and society. While evidence-based integrated care models can improve outcomes for individuals with MCC, such models have not yet been widely implemented. Insurance providers/payers have innovative system features that can be used to deploy these models; however, the investigators do not yet know which of these features can best help to improve outcomes for individuals with MCC in general or high-need subgroups in particular. As a result, patients lack information to make important decisions about their health and health care, and system-level decision makers face ongoing challenges in effectively and efficiently supporting those with MCC.

This real-world study will provide useful information about available options for supporting individuals with MCC. Building on existing integrated care efforts, the investigators will enroll N=1,400 (a modified total N) adults with MCC at risk for repeated hospitalizations and assess the impact of three payer-led options (e.g. High-Touch, High-Tech, Standard Care/Optimal Discharge Planning (ODP)) on patient-centered outcomes, namely patient activation in health care, health status, and subsequent re-hospitalization. The investigators will also determine which option works best for whom under what circumstances by gathering information directly from individuals with MCC through self-report questionnaires, health care use data, and interviews.

Read the detailed description

Study aims. Given the documented need for valuable information about system-level features that can be used to effectively and efficiently support adults in living well with MCC, this study is designed to achieve the following aims:

Aim 1: Compare the effectiveness of High-Touch, High-Tech, and ODP on primary outcomes including hospital readmission, health status, and patient activation, and on several secondary outcomes including functional status, quality of life, care satisfaction, emergent care use, engagement in primary, specialty, and mental health care, and gaps in care.

Aim 2: Examine the differential effects of the interventions for patient subgroups, based on age, race, illness complexity, and comorbid behavioral health conditions to evaluate heterogeneity of treatment effects (HTE) and determine for whom and in what circumstances the interventions are most effective.

Aim 3: Examine perceived barriers and facilitators to efficient and effective implementation of High-Touch and High-Tech interventions for delivering evidence-based integrated care.

An individual-level randomized design along with a pragmatic, mixed-methods approach to compare system-level features for delivering evidence-based components of integrated care for Medicaid or dual-eligible adult members with MCC who reside in in Western, Central, or Eastern PA and are at high risk for rehospitalization has been selected for this study. This design, based on significant input from patient stakeholders and Drs. Kevin Kraemer (Scientific Co-I; health services researcher) and Doug Landsittel (Co-I; biostatistician/CER expert), accords fully with the PCORI Methodology Standards. Intervention effectiveness will be determined by examining the differential impact on outcomes that are most meaningful to patients in our target population and those delivering their care. The scope and duration of the study interventions and evaluation are sufficient to measure change in patient-centered outcomes.

High-Touch, High-Tech, and ODP will serve as the comparators for this study. ODP follows standardized procedures for patient engagement including when a patient is either hospitalized or transitioning from the hospital setting into ambulatory care for follow-up and condition management. Due to resources and other limitations, not all patients who are eligible for High-Touch/High-Tech enroll in these programs. Thus, the addition of the ODP arm will allow for a less intensive model to be examined and targeted to appropriate patient populations.

For Aims 1 and 2, an individual, stratified randomized trial design was selected to randomly assign each enrollee to one of the three interventions arms, minimizing and balancing for confounding variables. Individual-level randomization was selected as opposed to cluster randomization at a system level (e.g. practice-, hospital-level) because the interventions are delivered by a single payer and are not subject to within-practice contamination. Based on valuable system-level stakeholder feedback, an unequal randomization ratio of 2:2:1 for High-Touch, High-Tech, and ODP, respectively, was utilized. While the less resource intensive ODP may, in fact, improve meaningful outcomes for certain patient subgroups, the health care system has invested heavily in High-Touch and High-Tech as evidence-based solutions for chronic disease care. Additionally, stakeholders have indicated that they would like as many participants as possible to have a fully integrated care experience offered by High-Touch/High-Tech and would like to limit enrollment into ODP. The investigators will use a mixed-methods approach that incorporates both qualitative and quantitative data. The addition of qualitative data collection and analyses in Aim 3 will permit more comprehensive understanding of patient and staff experiences with the interventions and results will aide in dissemination of study findings in a manner that is most consistent with patient and other stakeholder perceptions and experiences. The overall, four-year study timeline includes three phases: Pre-Intervention (months 1-6), Intervention and Data Collection (months 7-40), and Data Analysis and Reporting (months 41-48). Note: a 19-month no cost extension was granted to the study team to complete enrollment and data collection, especially during workflow adaptations related to COVID-19 restrictions.

The study population includes Medicaid or dual-eligible (Medicare-Medicaid) adults age 21 years and older with MCC, including at least one physical health condition (e.g., cardiovascular disease, hypertension, COPD, diabetes) and at least one additional physical or behavioral health condition (e.g., depression, serious mental illness, substance abuse disorder) and at least one hospital discharge in the previous 30 days. These individuals will reside in PA and will be insured through physical and/or behavioral health payers within the UPMC Insurance Services Division (ISD). In addition, these individuals will have several comorbidities, will have been prescribed several medications, and/or will be predicted future high health care utilizers. Based on a 75% enrollment rate, we initially expected1,662 individuals to be randomized to either High-Tech (n=667), High-Touch (n=667) or ODP (n=328). However, our funder approved a sample size recalculation for an 90% retention rate for 1,400 consented individuals randomized to either High-Tech (n=448), High-Touch (n=448) or ODP (n=224).

The study will use web-based randomization to one of the three interventions for those individuals who consent to participate in the study. Once a member of the Community Team (CT), multidisciplinary community-based team of nurses, licensed social workers, and licensed professional counselors, determines eligibility, CT personnel will enter key identification information, and the system will then generate a Study ID (numeric identification number) along with assignment to an intervention arm. Randomization will be stratified by gender, type of insurance (Medicaid or Medicare-Medicaid), and technology/digital literacy, which will be assessed at time of enrollment and before randomization, to ensure that intervention arms are balanced with respect to these important variables. Within each stratum, random block sizes of 5 and 10 will be used to maximize balance between intervention groups while minimizing the ability to unmask investigators to the next treatment assignment, triggering an automated alert to CT staff regarding which intervention to implement for each participant and documented accordingly in HealthPlaNET, UPMC ISD's integrated health management software program. If a participant is unwilling to be randomized, they will be excluded from the study.

Each patient is assigned a care manager (CM) who provides comprehensive services for the duration of intervention implementation. Bilingual staff will be available to support native Spanish speaking participants. CMs are currently employed to develop and implement care plans with patients, coordinate healthcare services, work with the pharmacist to manage patient's medications, make home visits, and deliver telehealth care and remote monitoring.

Patients in both High-Touch and High-Tech will experience similar procedures at the start of their participation. A CM engages patients in a face-to-face assessment in-home or telephonically to dialogue about the social determinants affecting continued hospital readmissions and emergency department use. At the completion of the assessment, the study is presented to the member and if agreeable informed consent occurs. Individuals randomized to ODP will be provided with the transitional care services. High-Touch and High-Tech interventions are provided for four to twelve months following hospitalization, based on need, and ODP participants are transitioned to appropriate Health Plan or community resources within 14 to 30 days.

02

Conditions studied

  • Diabetes
  • Asthma
  • Chronic Obstructive Pulmonary Disease
  • Hypertension
  • Anxiety
  • Atrial Fibrillation
  • Congestive Heart Failure
  • Depression
  • Bipolar Disorder
  • Schizophrenia

Keywords

  • chronic conditions
  • care management
  • digital tools
03

Who can participate

Ages eligible
21 Years and older
Sexes eligible
All
Accepts healthy volunteers
Yes

Inclusion criteria

  1. Medicaid or dual-eligible (Medicare-Medicaid) adults, ages 21 years and older with Multiple Chronic Conditions (MCC).
  2. Have at least one physical health condition (e.g., cardiovascular disease, hypertension, COPD, diabetes).
  3. Have at least one additional physical or behavioral health condition (e.g., depression, serious mental illness, substance abuse disorder).
  4. Reside in Western, Central, or Eastern Pennsylvania.
  5. Be insured through physical and/or behavioral health payers within the UPMC ISD.
  6. Individuals will have several comorbidities, will have been prescribed several medications, and/or will be predicted future high health care utilizers.
  7. Must have at least one hospital discharge within 30 days of enrollment.
  8. Speak and read English or Spanish at a 4th grade level.

Exclusion criteria

Exclusion Criteria:

  1. Individuals receiving advanced levels of care, including:

    • Individuals who are pregnant.
    • Individuals in skilled nursing facilities or receiving hospice or palliative care.
    • Individuals on hemodialysis for kidney disease.
    • Individuals whose inpatient admission was related to active cancer treatment.
  2. Individuals currently enrolled in an RPM program.
  3. Individuals who have participated in High-Touch or High-Tech within the previous 12 months.
  4. Individuals who are unable to operate a smart phone due to limitations in literacy, vision, or dexterity.
04

Study design

Phase
Not applicable
Primary purpose
Health services research
Allocation
Randomized
Intervention model
Factorial assignment
Masking
None (open label)
Enrollment
1,400 participants (actual)

Study arms

  • Active comparator
    High-Touch

    Delivered primarily via face-to-face interactions, with telephonic interactions and information sharing that does not require access to mobile devices or the Internet. In-person support and/or telephonic interactions to occur at least four times over at least a four-month period.

    Behavioral: High-Touch

  • Active comparator
    High-Tech

    Delivered via a remote care management platform and digital health tools. Remote care support interactions to occur for at least a four-month period.

    Behavioral: High-Tech

  • Active comparator
    Optimal Discharge Planning

    Delivered via Health Plan support and resources within 14-30 days of an initial home or telephonic visit.

    Behavioral: Optimal Discharge Planning

Interventions

  • BehavioralHigh-Touch

    Intensive, in-person and/or telephonic support.

  • BehavioralHigh-Tech

    Remote care management and self-directed digital tools.

  • BehavioralOptimal Discharge Planning

    Transition to other Health Plan disease management programs and/or community resources.

05

What researchers measure

Primary outcomes

  1. Patient Activation

    Assessed using the Patient Activation Measure (PAM), a 13-item scale that gauges individual knowledge, skills, and confidence essential to managing one's own health. We assess a global score of the PAM measure, with scores ranging from 0 to 100; lower values represent a poor outcome while higher values represent a better outcome.

    Time frame: Baseline, 3-, 6-, and 12-months.

  2. Change in Health Status

    Assessed using the RAND 36-Item Short Form Survey 1.0 (SF-36). The SF-36 is a set of 36 health status and quality-of-life measures that are patient self-reported and measure functional health and well-being within eight domains, including physical functioning, role limitations due to physical health, role limitations due to emotional problems, energy/fatigue, emotional well-being, social functioning, pain, and general health. Values are recoded per the scoring key relating each item to the appropriate subscale. All items are scored so that a high score defines a more favorable health state. We assess a global scale with a 0 to 100 range with 0 being worst possible health status and 100 being the best possible health status.

    Time frame: Baseline, 3-, 6-, and 12-months.

  3. 90-Day Hospital Readmission Rate

    90-Day Readmissions will be measured using an all-cause readmission rate from inpatient claims for physical and behavioral health service use within 90 days following discharge from the qualifying inpatient admission prior to enrollment in the study.

    Time frame: 1 to 90 days

Secondary outcomes

  1. 30-Day Hospital Readmission Rate

    30-Day Readmissions will be measured using an all-cause readmission rate in claims for physical and behavioral health service use within 30 days following discharge from the qualifying inpatient admission prior to enrollment in the study.

    Time frame: 1 to 30 days

  2. Functional Status

    Assessed using the PROMIS Physical Function - Short Form 6b with six self-reported physical function measures to assess current function, including activities of daily living. Each question has five response options (a 5-point Likert scale) ranging from one to five with 5 being the highest level of physical function and 1 being the lowest. Per best practices, the instrument is scored by Health Measures Scoring Service, using item-level calibrations using responses to each item for each participant, producing a T-score. The highest possible T-score score is 59, indicating the highest level of physical function, and the lowest is 21, indicating the lowest level of physical function.

    Time frame: Baseline, 3-, 6-, and 12-months.

  3. Quality of Life

    Quality of Life will be assessed using the Quality of Life Enjoyment and Satisfaction Questionnaire - Short Form (Q-LES-Q-SF), which is a self-report measure consisting of 16 questions designed to enable investigators to easily obtain sensitive measures of the degree of enjoyment and satisfaction experienced by subjects in various areas of daily functioning during the past week. The scoring of the Q-LES-Q-SF involves summing only the first 14 items to yield a raw total score, ranging from 14 to 70. The raw total score is calculated into a maximum possible score using the following formula: (raw total score - minimum score)/(maximum possible raw score - minimum score). The minimum raw score on the Q-LES-Q-SF is 14, and the maximum score is 70. Thus, the formula for maximum score can also be written as: (raw score - 14)/56.

    Time frame: Baseline, 3-, 6-, and 12-months.

  4. Care Satisfaction

    Care satisfaction will be assessed using the Patient Assessment of Care for Chronic Conditions (PACIC) Survey. The PACIC Survey consists of 20-items that measures specific actions or qualities of care that patients report they have experienced in the care of their chronic conditions over the past 6 months. Each item is measured on a scale from 1-5 with 5 signifying higher patient satisfaction and 1 being the lowest. Scoring requires obtaining the mean of all 20 items.

    Time frame: Baseline, 3-, 6-, and 12-months.

  5. Emergent Care Use

    Emergent care use will be measured using existing behavioral and physical health claims data to determine the frequency of emergency department visits within 12-months from enrollment.

    Time frame: Assessed at baseline, 6- and 12-Months.

  6. Engagement in Primary Care

    Engagement in primary care will be measured using existing behavioral and physical health claims determining participant frequency of non-acute visits for participants in the 12 months following enrollment. Because clinical standards of care are 1 primary care (PCP) visit every 12 months, PCP visits are assessed as a Y/N variable at 12-Months.

    Time frame: Assessed at baseline, 6- and 12-Months.

  7. Engagement in Specialty Care

    Engagement in specialty care will be measured using existing behavioral and physical health claims data determining participant frequency of specialty provider visits for participants in the 12 months following enrollment. Specialty care is inclusive of any care provided outside of primary care, physical therapy, or occupational therapy.

    Time frame: Assessed at baseline, 6- and 12-Months.

  8. Inpatient Readmissions Over 12-Months

    Readmissions over 12 months will be measured using an all-cause readmission rate from inpatient claims for physical and behavioral health service use within one year following discharge from the qualifying inpatient admission prior to enrollment in the study. Inpatient readmissions were lower than hypothesized for the population. As such, we assessed a Y/N variable for inpatient readmissions at 12-Months.

    Time frame: Assessed at baseline, 6- and 12-Months.

  9. Mental Health Care Visits

    Assessed using existing behavioral health claims data determining frequency of mental health care visits for participants in the 12 months following enrollment. Because of the low frequency, we assess mental health care visits as a Y/N variable.

    Time frame: Assessed at baseline, 6- and 12-Months.

  10. Gaps in Care: Asthma

    Gaps in care will be assessed using Healthcare Effectiveness Data and Information Set (HEDIS) quality metrics. For asthma, we assess the percentage of members 21-64 years of age during the measurement year who were identified as having persistent asthma and were dispensed appropriate medications that they remained on during the treatment period. Two rates are reported: 1. The percentage of members who remained on an asthma controller medication for at least 50% of their treatment period (MMA-1a). 2. The percentage of members who remained on an asthma controller medication for at least 75% of their treatment period (MMA-1b).

    Time frame: Assessed at baseline, 6- and 12-Months

  11. Gaps in Care: Chronic Obstructive Pulmonary Disease (COPD)

    Gaps in care will be assessed using Healthcare Effectiveness Data and Information Set (HEDIS) quality metrics. For COPD, we assess the percentage of COPD exacerbations for members 40 years of age and older who had an acute inpatient discharge or ED encounter and who were dispensed appropriate medications. Two rates reported: 1. Dispensed a systemic corticosteroid within 14 days of the event (PCE-1) 2. Dispensed a bronchodilator within 30 days of the event (PCE-2)

    Time frame: Assessed at baseline, 6- and 12-Months

  12. Gaps in Care: Congestive Heart Failure (CHF)

    For Gaps in care related to CHF, we assess readmission rate within 30 days after discharge from inpatient stay for members with a diagnosis of CHF prior index hospitalization.

    Time frame: Assessed at 30-days from an index admission discharge.

  13. Gaps in Care: Cardiovascular Disease (CVD)

    Gaps in care will be assessed using Healthcare Effectiveness Data and Information Set (HEDIS) quality metrics. For CVD, we assess the percentage of males 21-75 years of age and females 40-75 years of age during the measurement year, who were identified as having clinical atherosclerotic cardiovascular disease (ASCVD) and met the following criteria. The following rates are reported: 1. Received Statin Therapy. Members who were dispensed at least one high-intensity or moderate-intensity statin medication during the measurement year (SPC-1). 2. Statin Adherence 80%. Members who remained on a high-intensity or moderate-intensity statin medication for at least 80% of the treatment period (SPC-2).

    Time frame: Assessed at baseline, 6- and 12-Months

  14. Gaps in Care: Diabetes

    Gaps in care will be assessed using Healthcare Effectiveness Data and Information Set (HEDIS) quality metrics. For diabetes, we assess the percentage of members 40-75 years of age during the measurement year with diabetes who do not have clinical atherosclerotic cardiovascular disease (ASCVD) who met the following criteria. Two rates are reported: 1. Received Statin Therapy. Members who were dispensed at least one statin medication of any intensity during the measurement year (SPD-1). 2. Statin Adherence 80%. Members who remained on a statin medication of any intensity for at least 80% of the treatment period (SPD-2).

    Time frame: Assessed at baseline, 6- and 12-Months

  15. Gaps in Care: Depression

    Gaps in care will be assessed using Healthcare Effectiveness Data and Information Set (HEDIS) quality metrics. For depression, we assess the percentage of members diagnosed with a new episode of major depression, treated with antidepressant medication, and who remained on an antidepressant medication for: 1. Effective Acute Phase Treatment - 84 days of continuous treatment during 114-day period following the Index Prescription Start Date (AMM-1). 2. Effective Continuation Phase Treatment - 180 days of continuous treatment during 231-day period following the Index Prescription Start Date (AMM-2).

    Time frame: Assessed at baseline, 6- and 12-Months

06

Results

Posted Dec 9, 2024
Limitations and caveats
Approximately 10% of our total sample was eligible for the gaps in care analysis using Healthcare Effectiveness Data and Information Set (HEDIS) data, and therefore, several HEDIS based outcomes were not adequately powered to demonstrate statistical significance. Due to privacy and data sharing policies, we recognize not all claims related substance use diagnoses or behavioral health were obtained for analysis.

Participant flow

Enrollment occurred between September 4, 2018 and November 4, 2021. Care Managers enrolled eligible individuals during an initial in-home or telephonic visit; a study team member conducted randomization.

Participant flow — Overall Study
MilestoneHigh-TouchHigh-TechOptimal Discharge Planning
Started562552286
Completed535529268
Not completed272318
Withdrew: Death151611
Withdrew: Lost to follow-up904
Withdrew: Withdrawal by subject030
Withdrew: Unable to confirm accurate eligibility criteria after randomization and intervention completion.343

Outcome measures

PrimaryPatient Activation

Assessed using the Patient Activation Measure (PAM), a 13-item scale that gauges individual knowledge, skills, and confidence essential to managing one's own health. We assess a global score of the PAM measure, with scores ranging from 0 to 100; lower values represent a poor outcome while higher values represent a better outcome.

Time frame:
Baseline, 3-, 6-, and 12-months.
Reported as:
Mean · score on a scale
Patient Activation
score on a scaleHigh-TouchHigh-TechOptimal Discharge Planning
Baseline61.87 ± 14.3663.73 ± 16.1063.82 ± 16.12
3-Months63.15 ± 15.5663.60 ± 16.6563.60 ± 15.98
6-Months62.55 ± 16.0362.15 ± 15.8464.76 ± 15.98
12-Months63.15 ± 15.0564.58 ± 15.4162.83 ± 15.75
Statistical analysis
  • High-Touch vs High-Tech vs Optimal Discharge Planning · Mixed Models Analysis · p = 0.0211 (Controlling for: age, sex, race, ethnicity, insurance, engagement at baseline, comfortability with technology, tech literacy (HINTS), social support at baseline (ISEL), health literacy (AAHLS), illness burden (CCI), and area deprivation index (ADI).)F-statistics 2.49 with degrees of freedom (6, 3152).
  • High-Touch vs Optimal Discharge Planning · Mixed Models Analysis · p = 0.0280 (Controlling for: age, sex, race, ethnicity, insurance, engagement at baseline, comfortability with technology, tech literacy (HINTS), social support at baseline (ISEL), health literacy (AAHLS), illness burden (CCI), and area deprivation index (ADI).) · Mean difference (final values): 2.69 · 95% CI 0.29 to 5.09F-statistics 4.83 with degrees of freedom (1, 3152).
  • High-Tech vs Optimal Discharge Planning · Mixed Models Analysis · p = 0.0935 (Controlling for: age, sex, race, ethnicity, insurance, engagement at baseline, comfortability with technology, tech literacy (HINTS), social support at baseline (ISEL), health literacy (AAHLS), illness burden (CCI), and area deprivation index (ADI).) · Mean difference (final values): 2.07 · 95% CI -0.35 to 4.48F-statistics 2.81 with degrees of freedom (1, 3152).
  • High-Touch vs High-Tech · Mixed Models Analysis · p = 0.5538 (Controlling for: age, sex, race, ethnicity, insurance, engagement at baseline, comfortability with technology, tech literacy (HINTS), social support at baseline (ISEL), health literacy (AAHLS), illness burden (CCI), and area deprivation index (ADI).) · Mean difference (final values): 0.62 · 95% CI -1.44 to 2.68F-statistics 0.35 with degrees of freedom (1, 3152).
PrimaryChange in Health Status

Assessed using the RAND 36-Item Short Form Survey 1.0 (SF-36). The SF-36 is a set of 36 health status and quality-of-life measures that are patient self-reported and measure functional health and well-being within eight domains, including physical functioning, role limitations due to physical health, role limitations due to emotional problems, energy/fatigue, emotional well-being, social functioning, pain, and general health. Values are recoded per the scoring key relating each item to the appropriate subscale. All items are scored so that a high score defines a more favorable health state. We assess a global scale with a 0 to 100 range with 0 being worst possible health status and 100 being the best possible health status.

Time frame:
Baseline, 3-, 6-, and 12-months.
Reported as:
Mean · score on a scale
Change in Health Status
score on a scaleHigh-TouchHigh-TechOptimal Discharge Planning
Baseline39.61 ± 18.3939.50 ± 18.6539.05 ± 17.80
3-Month42.12 ± 20.0642.03 ± 19.9041.31 ± 19.99
6-Month41.86 ± 19.8441.39 ± 19.8441.83 ± 20.84
12-Month42.68 ± 20.5042.27 ± 19.6340.85 ± 19.03
Statistical analysis
  • High-Touch vs High-Tech vs Optimal Discharge Planning · Mixed Models Analysis · p = 0.8505F-statistics 0.44 with degrees of freedom (6, 3154).
  • High-Touch vs High-Tech vs Optimal Discharge Planning · Mixed Models Analysis · p = <0.0001 (Controlling for: age, sex, race, ethnicity, insurance, engagement at baseline, comfortability with technology, tech literacy (HINTS), social support at baseline (ISEL), health literacy (AAHLS), illness burden (CCI), and area deprivation index (ADI).)F-statistics 16.97 with degrees of freedom (3, 3160).
  • High-Touch vs High-Tech vs Optimal Discharge Planning · Mixed Models Analysis · p = 0.8656 (Controlling for: age, sex, race, ethnicity, insurance, engagement at baseline, comfortability with technology, tech literacy (HINTS), social support at baseline (ISEL), health literacy (AAHLS), illness burden (CCI), and area deprivation index (ADI).)F-statistics 0.14 with degrees of freedom (2, 1229).
  • High-Touch vs Optimal Discharge Planning · Mixed Models Analysis · p = 0.4740 (Controlling for: age, sex, race, ethnicity, insurance, engagement at baseline, comfortability with technology, tech literacy (HINTS), social support at baseline (ISEL), health literacy (AAHLS), illness burden (CCI), and area deprivation index (ADI).) · Mean difference (final values): 0.93 · 95% CI -1.61 to 3.46F-statistics 0.51 with degrees of freedom (1, 3154)
  • High-Tech vs Optimal Discharge Planning · Mixed Models Analysis · p = 0.6017 (Controlling for: age, sex, race, ethnicity, insurance, engagement at baseline, comfortability with technology, tech literacy (HINTS), social support at baseline (ISEL), health literacy (AAHLS), illness burden (CCI), and area deprivation index (ADI).) · Mean difference (final values): 0.66 · 95% CI -1.81 to 3.13F-statistics 0.27 with degrees of freedom (1, 3154).
  • High-Touch vs High-Tech · Mixed Models Analysis · p = 0.7860 (Controlling for: age, sex, race, ethnicity, insurance, engagement at baseline, comfortability with technology, tech literacy (HINTS), social support at baseline (ISEL), health literacy (AAHLS), illness burden (CCI), and area deprivation index (ADI).) · Mean difference (final values): 0.27 · 95% CI -1.67 to 2.20F-statistics 0.07 with degrees of freedom (1, 3154).
Primary90-Day Hospital Readmission Rate

90-Day Readmissions will be measured using an all-cause readmission rate from inpatient claims for physical and behavioral health service use within 90 days following discharge from the qualifying inpatient admission prior to enrollment in the study.

Time frame:
1 to 90 days
Reported as:
Count of participants · Participants
90-Day Hospital Readmission Rate
ParticipantsHigh-TouchHigh-TechOptimal Discharge Planning
No readmission within 90 days472470240
At least one readmission within 90 days857141
Statistical analysis
  • High-Touch vs High-Tech vs Optimal Discharge Planning · Regression, Logistic · p = 0.59 (Controlling for: age, sex, race, ethnicity, insurance, engagement at baseline, comfortability with technology, tech literacy (HINTS), social support at baseline (ISEL), health literacy (AAHLS), illness burden (CCI), and area deprivation index (ADI).)Chi-squared statistics 0.08 with degrees of freedom (2).
  • High-Touch vs Optimal Discharge Planning · Regression, Logistic · p = 0.6692 (Controlling for: age, sex, race, ethnicity, insurance, engagement at baseline, comfortability with technology, tech literacy (HINTS), social support at baseline (ISEL), health literacy (AAHLS), illness burden (CCI), and area deprivation index (ADI).) · Odds ratio (or): 1.26 · 95% CI 0.76 to 2.11Chi-square statistics 0.8 with degrees of freedom (2).
  • High-Tech vs Optimal Discharge Planning · Regression, Logistic · p = 0.6692 (Controlling for: age, sex, race, ethnicity, insurance, engagement at baseline, comfortability with technology, tech literacy (HINTS), social support at baseline (ISEL), health literacy (AAHLS), illness burden (CCI), and area deprivation index (ADI).) · Odds ratio (or): 1.16 · 95% CI 0.70 to 1.93Chi-square statistics 0.80 with degrees of freedom (2).
  • High-Touch vs High-Tech · Regression, Logistic · p = 0.6692 (Controlling for: age, sex, race, ethnicity, insurance, engagement at baseline, comfortability with technology, tech literacy (HINTS), social support at baseline (ISEL), health literacy (AAHLS), illness burden (CCI), and area deprivation index (ADI).) · Odds ratio (or): 1.09 · 95% CI 0.75 to 1.59Chi-square statistics 0.8 with degrees of freedom (2).
Secondary30-Day Hospital Readmission Rate

30-Day Readmissions will be measured using an all-cause readmission rate in claims for physical and behavioral health service use within 30 days following discharge from the qualifying inpatient admission prior to enrollment in the study.

Time frame:
1 to 30 days
Reported as:
Count of participants · Participants
30-Day Hospital Readmission Rate
ParticipantsHigh-TouchHigh-TechOptimal Discharge Planning
No readmission within 30 days535528272
At least one readmission within 30 days241711
Statistical analysis
  • High-Touch vs High-Tech vs Optimal Discharge Planning · Regression, Logistic · p = 0.58 (Controlling for: age, sex, race, ethnicity, insurance, engagement at baseline, comfortability with technology, tech literacy (HINTS), social support at baseline (ISEL), health literacy (AAHLS), illness burden (CCI), and area deprivation index (ADI).)Chi-squared statistics 0.08 with degrees of freedom (2).
  • High-Touch vs Optimal Discharge Planning · Regression, Logistic · p = 0.7436 (Controlling for: age, sex, race, ethnicity, insurance, engagement at baseline, comfortability with technology, tech literacy (HINTS), social support at baseline (ISEL), health literacy (AAHLS), illness burden (CCI), and area deprivation index (ADI).) · Odds ratio (or): 1.13 · 95% CI 0.43 to 3.02Chi-squared statistics 0.59 with degrees of freedom (2).
  • High-Tech vs Optimal Discharge Planning · Regression, Logistic · p = 0.7436 (Controlling for: age, sex, race, ethnicity, insurance, engagement at baseline, comfortability with technology, tech literacy (HINTS), social support at baseline (ISEL), health literacy (AAHLS), illness burden (CCI), and area deprivation index (ADI).) · Odds ratio (or): 0.84 · 95% CI 0.31 to 2.25Chi-squared statistics 0.59 with degrees of freedom (2).
  • High-Touch vs High-Tech · Regression, Logistic · p = 0.7436 · Odds ratio (or): 1.36 · 95% CI 0.62 to 2.97Chi-squared statistics 0.59 with degrees of freedom (2).
SecondaryFunctional Status

Assessed using the PROMIS Physical Function - Short Form 6b with six self-reported physical function measures to assess current function, including activities of daily living. Each question has five response options (a 5-point Likert scale) ranging from one to five with 5 being the highest level of physical function and 1 being the lowest. Per best practices, the instrument is scored by Health Measures Scoring Service, using item-level calibrations using responses to each item for each participant, producing a T-score. The highest possible T-score score is 59, indicating the highest level of physical function, and the lowest is 21, indicating the lowest level of physical function.

Time frame:
Baseline, 3-, 6-, and 12-months.
Reported as:
Mean · T score
Functional Status
T scoreHigh-TouchHigh-TechOptimal Discharge Planning
Baseline36.75 ± 7.8936.29 ± 7.9835.78 ± 7.60
3-Month37.11 ± 7.6537.02 ± 7.9736.83 ± 8.20
6-Month37.30 ± 7.8736.85 ± 7.7637.24 ± 7.91
12-Month36.99 ± 8.6536.73 ± 8.1436.29 ± 7.66
Statistical analysis
  • High-Touch vs High-Tech vs Optimal Discharge Planning · Mixed Models Analysis · p = 0.5558 (Controlling for: age, sex, race, ethnicity, insurance, engagement at baseline, comfortability with technology, tech literacy (HINTS), social support at baseline (ISEL), health literacy (AAHLS), illness burden (CCI), and area deprivation index (ADI).)F-statistics 0.82 with degrees of freedom (6, 3057)
  • High-Touch vs High-Tech vs Optimal Discharge Planning · Mixed Models Analysis · p = 0.0002 (Controlling for: age, sex, race, ethnicity, insurance, engagement at baseline, comfortability with technology, tech literacy (HINTS), social support at baseline (ISEL), health literacy (AAHLS), illness burden (CCI), and area deprivation index (ADI).)F-statistics 6.74 with degrees of freedom (3, 3063).
  • High-Touch vs High-Tech vs Optimal Discharge Planning · Mixed Models Analysis · p = 0.7846 (Controlling for: age, sex, race, ethnicity, insurance, engagement at baseline, comfortability with technology, tech literacy (HINTS), social support at baseline (ISEL), health literacy (AAHLS), illness burden (CCI), and area deprivation index (ADI).)F-statistics 0.24 with degrees of freedom (2,1197).
  • High-Touch vs Optimal Discharge Planning · Mixed Models Analysis · p = 0.2444 (Controlling for: age, sex, race, ethnicity, insurance, engagement at baseline, comfortability with technology, tech literacy (HINTS), social support at baseline (ISEL), health literacy (AAHLS), illness burden (CCI), and area deprivation index (ADI).) · Mean difference (final values): -0.71 · 95% CI -1.92 to 0.49F-Statistics 1.36 with degrees of freedom (1, 3057).
  • High-Tech vs Optimal Discharge Planning · Mixed Models Analysis · p = 0.6480 (Controlling for: age, sex, race, ethnicity, insurance, engagement at baseline, comfortability with technology, tech literacy (HINTS), social support at baseline (ISEL), health literacy (AAHLS), illness burden (CCI), and area deprivation index (ADI).) · Mean difference (final values): -0.28 · 95% CI -1.48 to 0.92F-statistics 0.21 with degrees of freedom (1, 3057).
  • High-Touch vs High-Tech · Mixed Models Analysis · p = 0.3476 (Controlling for: age, sex, race, ethnicity, insurance, engagement at baseline, comfortability with technology, tech literacy (HINTS), social support at baseline (ISEL), health literacy (AAHLS), illness burden (CCI), and area deprivation index (ADI).) · Mean difference (final values): -0.44 · 95% CI -1.34 to 0.47F-statistics 0.88 with degrees of freedom (1, 3057).
SecondaryQuality of Life

Quality of Life will be assessed using the Quality of Life Enjoyment and Satisfaction Questionnaire - Short Form (Q-LES-Q-SF), which is a self-report measure consisting of 16 questions designed to enable investigators to easily obtain sensitive measures of the degree of enjoyment and satisfaction experienced by subjects in various areas of daily functioning during the past week. The scoring of the Q-LES-Q-SF involves summing only the first 14 items to yield a raw total score, ranging from 14 to 70. The raw total score is calculated into a maximum possible score using the following formula: (raw total score - minimum score)/(maximum possible raw score - minimum score). The minimum raw score on the Q-LES-Q-SF is 14, and the maximum score is 70. Thus, the formula for maximum score can also be written as: (raw score - 14)/56.

Time frame:
Baseline, 3-, 6-, and 12-months.
Reported as:
Mean · score on a scale
Quality of Life
score on a scaleHigh-TouchHigh-TechOptimal Discharge Planning
Baseline0.50 ± 0.190.51 ± 0.190.51 ± 0.21
3-Month0.52 ± 0.190.52 ± 0.190.52 ± 0.20
6-Month0.52 ± 0.200.52 ± 0.200.52 ± 0.21
12-Month0.54 ± 0.200.52 ± 0.190.53 ± 0.19
Statistical analysis
  • High-Touch vs High-Tech vs Optimal Discharge Planning · Mixed Models Analysis · p = 0.5199 (Controlling for: age, sex, race, ethnicity, insurance, engagement at baseline, comfortability with technology, tech literacy (HINTS), social support at baseline (ISEL), health literacy (AAHLS), illness burden (CCI), and area deprivation index (ADI).)F-statistics 0.86 with degrees of freedom (6, 3148)
  • High-Touch vs High-Tech vs Optimal Discharge Planning · Mixed Models Analysis · p = 0.0008 (Controlling for: age, sex, race, ethnicity, insurance, engagement at baseline, comfortability with technology, tech literacy (HINTS), social support at baseline (ISEL), health literacy (AAHLS), illness burden (CCI), and area deprivation index (ADI).)F-statistics 5.56 with degrees of freedom (3, 3154).
  • High-Touch vs High-Tech vs Optimal Discharge Planning · Mixed Models Analysis · p = 0.9897 (Controlling for: age, sex, race, ethnicity, insurance, engagement at baseline, comfortability with technology, tech literacy (HINTS), social support at baseline (ISEL), health literacy (AAHLS), illness burden (CCI), and area deprivation index (ADI).)F-statistics 0.01 with degrees of freedom (2,1229).
  • High-Touch vs Optimal Discharge Planning · Mixed Models Analysis · p = 0.8749 (Controlling for: age, sex, race, ethnicity, insurance, engagement at baseline, comfortability with technology, tech literacy (HINTS), social support at baseline (ISEL), health literacy (AAHLS), illness burden (CCI), and area deprivation index (ADI).) · Mean difference (final values): 0.00 · 95% CI -0.03 to 0.03F-statistics 0.02 with degrees of freedom (1, 3148).
  • High-Tech vs Optimal Discharge Planning · Mixed Models Analysis · p = 0.2216 (Controlling for: age, sex, race, ethnicity, insurance, engagement at baseline, comfortability with technology, tech literacy (HINTS), social support at baseline (ISEL), health literacy (AAHLS), illness burden (CCI), and area deprivation index (ADI).) · Mean difference (final values): -0.02 · 95% CI -0.05 to 0.01F-statistics 1.49 with degrees of freedom (1, 3148).
  • High-Touch vs High-Tech · Mixed Models Analysis · p = 0.0607 (Controlling for: age, sex, race, ethnicity, insurance, engagement at baseline, comfortability with technology, tech literacy (HINTS), social support at baseline (ISEL), health literacy (AAHLS), illness burden (CCI), and area deprivation index (ADI).) · Mean difference (final values): 0.02 · 95% CI 0.00 to 0.04F-statistics 3.52 with degrees of freedom (1, 3148).
SecondaryCare Satisfaction

Care satisfaction will be assessed using the Patient Assessment of Care for Chronic Conditions (PACIC) Survey. The PACIC Survey consists of 20-items that measures specific actions or qualities of care that patients report they have experienced in the care of their chronic conditions over the past 6 months. Each item is measured on a scale from 1-5 with 5 signifying higher patient satisfaction and 1 being the lowest. Scoring requires obtaining the mean of all 20 items.

Time frame:
Baseline, 3-, 6-, and 12-months.
Reported as:
Mean · score on a scale
Care Satisfaction
score on a scaleHigh-TouchHigh-TechOptimal Discharge Planning
Baseline2.96 ± 0.982.86 ± 0.942.96 ± 1.00
3-Month3.02 ± 1.002.99 ± 0.992.97 ± 0.97
6-Month3.03 ± 0.982.97 ± 1.012.93 ± 1.00
12-Month3.05 ± 1.013.03 ± 1.013.00 ± 0.99
Statistical analysis
  • High-Touch vs High-Tech vs Optimal Discharge Planning · Mixed Models Analysis · p = 0.1884 (Controlling for: age, sex, race, ethnicity, insurance, engagement at baseline, comfortability with technology, tech literacy (HINTS), social support at baseline (ISEL), health literacy (AAHLS), illness burden (CCI), and area deprivation index (ADI).)F-statistics 1.46 with degrees of freedom (6, 3138)
  • High-Touch vs High-Tech vs Optimal Discharge Planning · Mixed Models Analysis · p = 0.0090 (Controlling for: age, sex, race, ethnicity, insurance, engagement at baseline, comfortability with technology, tech literacy (HINTS), social support at baseline (ISEL), health literacy (AAHLS), illness burden (CCI), and area deprivation index (ADI).)F-statistics 3.87 with degrees of freedom (3, 3144).
  • High-Touch vs High-Tech vs Optimal Discharge Planning · Mixed Models Analysis · p = 0.2170 (Controlling for: age, sex, race, ethnicity, insurance, engagement at baseline, comfortability with technology, tech literacy (HINTS), social support at baseline (ISEL), health literacy (AAHLS), illness burden (CCI), and area deprivation index (ADI).)F-statistics 1.53 with degrees of freedom (2, 1227).
  • High-Touch vs Optimal Discharge Planning · Mixed Models Analysis · p = 0.1910 (Controlling for: age, sex, race, ethnicity, insurance, engagement at baseline, comfortability with technology, tech literacy (HINTS), social support at baseline (ISEL), health literacy (AAHLS), illness burden (CCI), and area deprivation index (ADI).) · Mean difference (final values): 0.11 · 95% CI -0.06 to 0.28F-statistics 1.71 with degrees of freedom (1, 3138).
  • High-Tech vs Optimal Discharge Planning · Mixed Models Analysis · p = 0.0229 (Controlling for: age, sex, race, ethnicity, insurance, engagement at baseline, comfortability with technology, tech literacy (HINTS), social support at baseline (ISEL), health literacy (AAHLS), illness burden (CCI), and area deprivation index (ADI).) · Mean difference (final values): 0.19 · 95% CI 0.03 to 0.35F-statistics 5.18 with degrees of freedom (1, 3138).
  • High-Touch vs High-Tech · Mixed Models Analysis · p = 0.2547 (Controlling for: age, sex, race, ethnicity, insurance, engagement at baseline, comfortability with technology, tech literacy (HINTS), social support at baseline (ISEL), health literacy (AAHLS), illness burden (CCI), and area deprivation index (ADI).) · Mean difference (final values): -0.08 · 95% CI -0.21 to 0.06F-statistics 1.30 with degrees of freedom (1, 3138).
SecondaryEmergent Care Use

Emergent care use will be measured using existing behavioral and physical health claims data to determine the frequency of emergency department visits within 12-months from enrollment.

Time frame:
Assessed at baseline, 6- and 12-Months.
Reported as:
Mean · visits
Emergent Care Use
visitsHigh-TouchHigh-TechOptimal Discharge Planning
Baseline2.83 ± 3.252.40 ± 3.362.39 ± 3.73
6-Month1.33 ± 2.081.31 ± 2.441.25 ± 2.02
12-Month2.41 ± 3.582.40 ± 4.322.29 ± 3.29
Statistical analysis
  • High-Touch vs High-Tech vs Optimal Discharge Planning · Mixed Models Analysis · p = 0.0413 (Controlling for: age, sex, race, ethnicity, insurance, engagement at baseline, comfortability with technology, tech literacy (HINTS), social support at baseline (ISEL), health literacy (AAHLS), illness burden (CCI), and area deprivation index (ADI).)F-statistics 2.49 with degrees of freedom (4, 3164).
  • High-Touch vs Optimal Discharge Planning · Mixed Models Analysis · p = 0.1433 (Controlling for: age, sex, race, ethnicity, insurance, engagement at baseline, comfortability with technology, tech literacy (HINTS), social support at baseline (ISEL), health literacy (AAHLS), illness burden (CCI), and area deprivation index (ADI).) · Mean difference (final values): -0.12 · 95% CI -0.28 to 0.04F-statistics 2.14 with degrees of freedom (1, 3164).
  • High-Tech vs Optimal Discharge Planning · Mixed Models Analysis · p = 0.4272 (Controlling for: age, sex, race, ethnicity, insurance, engagement at baseline, comfortability with technology, tech literacy (HINTS), social support at baseline (ISEL), health literacy (AAHLS), illness burden (CCI), and area deprivation index (ADI).) · Mean difference (final values): 0.07 · 95% CI -0.10 to 0.23F-statistics 0.63 with degrees of freedom (1, 3164).
  • High-Touch vs High-Tech · Mixed Models Analysis · p = 0.0037 (Controlling for: age, sex, race, ethnicity, insurance, engagement at baseline, comfortability with technology, tech literacy (HINTS), social support at baseline (ISEL), health literacy (AAHLS), illness burden (CCI), and area deprivation index (ADI).) · Mean difference (final values): -0.19 · 95% CI -0.31 to -0.06F-statistics 8.45 with degrees of freedom (1, 3164).
SecondaryEngagement in Primary Care

Engagement in primary care will be measured using existing behavioral and physical health claims determining participant frequency of non-acute visits for participants in the 12 months following enrollment. Because clinical standards of care are 1 primary care (PCP) visit every 12 months, PCP visits are assessed as a Y/N variable at 12-Months.

Time frame:
Assessed at baseline, 6- and 12-Months.
Reported as:
Count of participants · Participants
Engagement in Primary Care
ParticipantsHigh-TouchHigh-TechOptimal Discharge Planning
Baseline — At least one PCP visit451468224
Baseline — No PCP visit644130
Baseline — Missing Data443629
6-Months — At least one PCP visit467463242
6-Months — No PCP visit847232
6-Months — Missing Data8109
12-Months — At least one PCP visit467476238
12-Months — No PCP visit624422
12-Months — Missing Data302523
Statistical analysis
  • High-Touch vs High-Tech vs Optimal Discharge Planning · Mixed Models Analysis · p = 0.8231 (Controlling for: age, sex, race, ethnicity, insurance, engagement at baseline, comfortability with technology, tech literacy (HINTS), social support at baseline (ISEL), health literacy (AAHLS), illness burden (CCI), and area deprivation index (ADI).)F-statistics 0.38 with degrees of freedom (4, 3164).
  • High-Touch vs High-Tech vs Optimal Discharge Planning · Mixed Models Analysis · p = <0.0001 (Controlling for: age, sex, race, ethnicity, insurance, engagement at baseline, comfortability with technology, tech literacy (HINTS), social support at baseline (ISEL), health literacy (AAHLS), illness burden (CCI), and area deprivation index (ADI).)F-statistics 330.05 with degrees of freedom (2, 1948).
  • High-Touch vs High-Tech vs Optimal Discharge Planning · Mixed Models Analysis · p = 0.6061 (Controlling for: age, sex, race, ethnicity, insurance, engagement at baseline, comfortability with technology, tech literacy (HINTS), social support at baseline (ISEL), health literacy (AAHLS), illness burden (CCI), and area deprivation index (ADI).)F-statistics 0.50 with degrees of freedom (2 , 1948).
  • High-Touch vs Optimal Discharge Planning · Mixed Models Analysis · p = 0.7459 (Controlling for: age, sex, race, ethnicity, insurance, engagement at baseline, comfortability with technology, tech literacy (HINTS), social support at baseline (ISEL), health literacy (AAHLS), illness burden (CCI), and area deprivation index (ADI).) · Mean difference (final values): -0.02 · 95% CI -0.15 to 0.11F-statistics 0.11 with degrees of freedom (1, 3164).
  • High-Tech vs Optimal Discharge Planning · Mixed Models Analysis · p = 0.3169 (Controlling for: age, sex, race, ethnicity, insurance, engagement at baseline, comfortability with technology, tech literacy (HINTS), social support at baseline (ISEL), health literacy (AAHLS), illness burden (CCI), and area deprivation index (ADI).) · Mean difference (final values): -0.05 · 95% CI -0.18 to 0.08F-statistics 1.00 with degrees of freedom (1, 3164).
  • High-Touch vs High-Tech · Mixed Models Analysis · p = 0.4098 (Controlling for: age, sex, race, ethnicity, insurance, engagement at baseline, comfortability with technology, tech literacy (HINTS), social support at baseline (ISEL), health literacy (AAHLS), illness burden (CCI), and area deprivation index (ADI).) · Mean difference (final values): 0.04 · 95% CI -0.07 to 0.14F-statistics 0.68 with degrees of freedom (1, 3164).
SecondaryEngagement in Specialty Care

Engagement in specialty care will be measured using existing behavioral and physical health claims data determining participant frequency of specialty provider visits for participants in the 12 months following enrollment. Specialty care is inclusive of any care provided outside of primary care, physical therapy, or occupational therapy.

Time frame:
Assessed at baseline, 6- and 12-Months.
Reported as:
Mean · visits
Engagement in Specialty Care
visitsHigh-TouchHigh-TechOptimal Discharge Planning
Baseline7.29 ± 10.207.54 ± 8.897.20 ± 8.50
6-Month4.15 ± 5.344.51 ± 6.534.08 ± 5.16
12-Month7.80 ± 9.028.31 ± 10.397.84 ± 9.33
Statistical analysis
  • High-Touch vs High-Tech vs Optimal Discharge Planning · Mixed Models Analysis · p = 0.4732 (Controlling for: age, sex, race, ethnicity, insurance, engagement at baseline, comfortability with technology, tech literacy (HINTS), social support at baseline (ISEL), health literacy (AAHLS), illness burden (CCI), and area deprivation index (ADI).)F-statistics 0.88 with degrees of freedom (4, 1945).
  • High-Touch vs High-Tech vs Optimal Discharge Planning · Mixed Models Analysis · p = <0.0001 (Controlling for: age, sex, race, ethnicity, insurance, engagement at baseline, comfortability with technology, tech literacy (HINTS), social support at baseline (ISEL), health literacy (AAHLS), illness burden (CCI), and area deprivation index (ADI).)F-statistics 319.14 with degrees of freedom (2, 1948).
  • High-Touch vs High-Tech vs Optimal Discharge Planning · Mixed Models Analysis · p = 0.9628 (Controlling for: age, sex, race, ethnicity, insurance, engagement at baseline, comfortability with technology, tech literacy (HINTS), social support at baseline (ISEL), health literacy (AAHLS), illness burden (CCI), and area deprivation index (ADI).)F-statistics 0.04 with degrees of freedom (2, 1948).
  • High-Touch vs Optimal Discharge Planning · Mixed Models Analysis · p = 0.8438 (Controlling for: age, sex, race, ethnicity, insurance, engagement at baseline, comfortability with technology, tech literacy (HINTS), social support at baseline (ISEL), health literacy (AAHLS), illness burden (CCI), and area deprivation index (ADI).) · Mean difference (final values): 0.01 · 95% CI -0.16 to 0.19F-statistics 0.04 with degrees of freedom (1, 1945).
  • High-Tech vs Optimal Discharge Planning · Mixed Models Analysis · p = 0.7425 (Controlling for: age, sex, race, ethnicity, insurance, engagement at baseline, comfortability with technology, tech literacy (HINTS), social support at baseline (ISEL), health literacy (AAHLS), illness burden (CCI), and area deprivation index (ADI).) · Mean difference (final values): -0.02 · 95% CI -0.19 to 0.15F-statistics 0.11 with degrees of freedom (1, 1945).
  • High-Touch vs High-Tech · Mixed Models Analysis · p = 0.5044 (Controlling for: age, sex, race, ethnicity, insurance, engagement at baseline, comfortability with technology, tech literacy (HINTS), social support at baseline (ISEL), health literacy (AAHLS), illness burden (CCI), and area deprivation index (ADI).) · Mean difference (final values): 0.04 · 95% CI -0.10 to 0.17F-statistics 0.45 with degrees of freedom (1, 1945).
SecondaryInpatient Readmissions Over 12-Months

Readmissions over 12 months will be measured using an all-cause readmission rate from inpatient claims for physical and behavioral health service use within one year following discharge from the qualifying inpatient admission prior to enrollment in the study. Inpatient readmissions were lower than hypothesized for the population. As such, we assessed a Y/N variable for inpatient readmissions at 12-Months.

Time frame:
Assessed at baseline, 6- and 12-Months.
Reported as:
Count of participants · Participants
Inpatient Readmissions Over 12-Months
ParticipantsHigh-TouchHigh-TechOptimal Discharge Planning
Baseline — No inpatient admission342344170
Baseline — One or more inpatient admissions17316584
Baseline — Missing Data443629
6-Month — No inpatient admission412400201
6-Month — One or more inpatient admissions13913573
6-Month — Missing Data8109
12-Month — No inpatient admission337332170
12-Month — One or more inpatient admissions19218890
12-Month — Missing Data302523
Statistical analysis
  • High-Touch vs High-Tech vs Optimal Discharge Planning · Mixed Models Analysis · p = 0.9804 (Controlling for: age, sex, race, ethnicity, insurance, engagement at baseline, comfortability with technology, tech literacy (HINTS), social support at baseline (ISEL), health literacy (AAHLS), illness burden (CCI), and area deprivation index (ADI).)F-statistics 0.11 with degrees of freedom (4, 3164).
  • High-Touch vs High-Tech vs Optimal Discharge Planning · Mixed Models Analysis · p = <0.0001 (Controlling for: age, sex, race, ethnicity, insurance, engagement at baseline, comfortability with technology, tech literacy (HINTS), social support at baseline (ISEL), health literacy (AAHLS), illness burden (CCI), and area deprivation index (ADI).)F-statistics 21.80 with degrees of freedom (2, 3168).
  • High-Touch vs High-Tech vs Optimal Discharge Planning · Mixed Models Analysis · p = 0.9764 (Controlling for: age, sex, race, ethnicity, insurance, engagement at baseline, comfortability with technology, tech literacy (HINTS), social support at baseline (ISEL), health literacy (AAHLS), illness burden (CCI), and area deprivation index (ADI).)F-statistics 0.02 with degrees of freedom (2, 1211).
  • High-Touch vs Optimal Discharge Planning · Mixed Models Analysis · p = 0.9757 (Controlling for: age, sex, race, ethnicity, insurance, engagement at baseline, comfortability with technology, tech literacy (HINTS), social support at baseline (ISEL), health literacy (AAHLS), illness burden (CCI), and area deprivation index (ADI).) · Odds ratio (or): 1.01 · 95% CI 0.63 to 1.60T-test statistics 0.03.
  • High-Tech vs Optimal Discharge Planning · Mixed Models Analysis · p = 0.7958 (Controlling for: age, sex, race, ethnicity, insurance, engagement at baseline, comfortability with technology, tech literacy (HINTS), social support at baseline (ISEL), health literacy (AAHLS), illness burden (CCI), and area deprivation index (ADI).) · Odds ratio (or): 1.06 · 95% CI 0.67 to 1.68T-test statistics 0.26.
  • High-Touch vs High-Tech · Mixed Models Analysis · p = 0.7646 (Controlling for: age, sex, race, ethnicity, insurance, engagement at baseline, comfortability with technology, tech literacy (HINTS), social support at baseline (ISEL), health literacy (AAHLS), illness burden (CCI), and area deprivation index (ADI).) · Odds ratio (or): 0.95 · 95% CI 0.67 to 1.34T-statistics -0.30
SecondaryMental Health Care Visits

Assessed using existing behavioral health claims data determining frequency of mental health care visits for participants in the 12 months following enrollment. Because of the low frequency, we assess mental health care visits as a Y/N variable.

Time frame:
Assessed at baseline, 6- and 12-Months.
Reported as:
Count of participants · Participants
Mental Health Care Visits
ParticipantsHigh-TouchHigh-TechOptimal Discharge Planning
Baseline — No mental health care visits479476237
Baseline — At least one mental health care visit363317
Baseline — Missing Data443629
6-Months — No mental health care visits527506256
6-Months — At least one mental health care visit242918
6-Months — Missing Data8109
12-Months — No mental health care visits492484238
12-Months — At least one mental health care visit373622
12-Months — Missing Data302523
Statistical analysis
  • High-Touch vs High-Tech vs Optimal Discharge Planning · Mixed Models Analysis · p = 0.9622 (Controlling for: age, sex, race, ethnicity, insurance, engagement at baseline, comfortability with technology, tech literacy (HINTS), social support at baseline (ISEL), health literacy (AAHLS), illness burden (CCI), and area deprivation index (ADI).)F-statistics 0.15 with degrees of freedom (4, 3164).
  • High-Touch vs High-Tech vs Optimal Discharge Planning · Mixed Models Analysis · p = 0.0377 (Controlling for: age, sex, race, ethnicity, insurance, engagement at baseline, comfortability with technology, tech literacy (HINTS), social support at baseline (ISEL), health literacy (AAHLS), illness burden (CCI), and area deprivation index (ADI).)F-statistics 3.28 with degrees of freedom (2, 3168).
  • High-Touch vs High-Tech vs Optimal Discharge Planning · Mixed Models Analysis · p = 0.8300 (Controlling for: age, sex, race, ethnicity, insurance, engagement at baseline, comfortability with technology, tech literacy (HINTS), social support at baseline (ISEL), health literacy (AAHLS), illness burden (CCI), and area deprivation index (ADI).)F-statistic 0.19 with degrees of freedom (2, 1903).
  • High-Touch vs Optimal Discharge Planning · Mixed Models Analysis · p = 0.7507 (Controlling for: age, sex, race, ethnicity, insurance, engagement at baseline, comfortability with technology, tech literacy (HINTS), social support at baseline (ISEL), health literacy (AAHLS), illness burden (CCI), and area deprivation index (ADI).) · Odds ratio (or): 0.87 · 95% CI 0.38 to 2.00T-statistics -0.32
  • High-Tech vs Optimal Discharge Planning · Mixed Models Analysis · p = 0.8844 (Controlling for: age, sex, race, ethnicity, insurance, engagement at baseline, comfortability with technology, tech literacy (HINTS), social support at baseline (ISEL), health literacy (AAHLS), illness burden (CCI), and area deprivation index (ADI).) · Odds ratio (or): 0.94 · 95% CI 0.42 to 2.13T-statistics -0.15
  • High-Touch vs High-Tech · Mixed Models Analysis · p = 0.8227 (Controlling for: age, sex, race, ethnicity, insurance, engagement at baseline, comfortability with technology, tech literacy (HINTS), social support at baseline (ISEL), health literacy (AAHLS), illness burden (CCI), and area deprivation index (ADI).) · Odds ratio (or): 0.93 · 95% CI 0.49 to 1.77T-statistics -0.22
SecondaryGaps in Care: Asthma

Gaps in care will be assessed using Healthcare Effectiveness Data and Information Set (HEDIS) quality metrics. For asthma, we assess the percentage of members 21-64 years of age during the measurement year who were identified as having persistent asthma and were dispensed appropriate medications that they remained on during the treatment period. Two rates are reported: 1. The percentage of members who remained on an asthma controller medication for at least 50% of their treatment period (MMA-1a). 2. The percentage of members who remained on an asthma controller medication for at least 75% of their treatment period (MMA-1b).

Time frame:
Assessed at baseline, 6- and 12-Months
Reported as:
Count of participants · Participants
Gaps in Care: Asthma
ParticipantsHigh-TouchHigh-TechOptimal Discharge Planning
Baseline MMA-1a (50%) — Did not close gap in care633
Baseline MMA-1a (50%) — Closed gap in care2103
6-Month MMA-1a (50%) — Did not close gap in care231
6-Month MMA-1a (50%) — Closed gap in care282
12-Month MMA-1a (50%) — Did not close gap in care110
12-Month MMA-1a (50%) — Closed gap in care562
Baseline MMA-1b (75%) — Did not close gap in care693
Baseline MMA-1b (75%) — Closed gap in care243
6-Month MMA-1b (75%) — Did not close gap in care241
6-Month MMA-1b (75%) — Closed gap in care272
12-Month MMA-1b (75%) — Did not close gap in care140
12-Month MMA-1b (75%) — Closed gap in care532
Statistical analysis
  • High-Touch vs High-Tech vs Optimal Discharge Planning · Fisher Exact · p = 1.00Fisher's exact test for the null hypothesis of no association between each event and treatment group.
  • High-Touch vs High-Tech vs Optimal Discharge Planning · Fisher Exact · p = 0.242Fisher's exact test for the null hypothesis of no association between each event and treatment group.
SecondaryGaps in Care: Chronic Obstructive Pulmonary Disease (COPD)

Gaps in care will be assessed using Healthcare Effectiveness Data and Information Set (HEDIS) quality metrics. For COPD, we assess the percentage of COPD exacerbations for members 40 years of age and older who had an acute inpatient discharge or ED encounter and who were dispensed appropriate medications. Two rates reported: 1. Dispensed a systemic corticosteroid within 14 days of the event (PCE-1) 2. Dispensed a bronchodilator within 30 days of the event (PCE-2)

Time frame:
Assessed at baseline, 6- and 12-Months
Reported as:
Count of participants · Participants
Gaps in Care: Chronic Obstructive Pulmonary Disease (COPD)
ParticipantsHigh-TouchHigh-TechOptimal Discharge Planning
Baseline PCE-1 — Did not close gap in care431
Baseline PCE-1 — Closed gap in care202514
6-Month PCE-1 — Did not close gap in care821
6-Month PCE-1 — Closed gap in care495222
12-Month PCE-1 — Did not close gap in care213
12-Month PCE-1 — Closed gap in care333311
Baseline PCE-2 — Did not close gap in care843
Baseline PCE-2 — Closed gap in care162412
6-Month PCE-2 — Did not close gap in care783
6-Month PCE-2 — Closed gap in care504620
12-Month PCE-2 — Did not close gap in care571
12-Month PCE-2 — Closed gap in care302713
Statistical analysis
  • High-Touch vs High-Tech vs Optimal Discharge Planning · Fisher Exact · p = 0.1112Fisher's exact test for the null hypothesis of no association between each event and treatment group.
  • High-Touch vs High-Tech vs Optimal Discharge Planning · Fisher Exact · p = 0.4754Fisher's exact test for the null hypothesis of no association between each event and treatment group.
SecondaryGaps in Care: Congestive Heart Failure (CHF)

For Gaps in care related to CHF, we assess readmission rate within 30 days after discharge from inpatient stay for members with a diagnosis of CHF prior index hospitalization.

Time frame:
Assessed at 30-days from an index admission discharge.
Reported as:
Mean · Number of readmissions within 30 days
Gaps in Care: Congestive Heart Failure (CHF)
Number of readmissions within 30 daysHigh-TouchHigh-TechOptimal Discharge Planning
Baseline0.04 ± 0.170.04 ± 0.170.02 ± 0.11
6-Month0.02 ± 0.100.04 ± 0.150.03 ± 0.12
12-Month0.04 ± 0.130.04 ± 0.130.04 ± 0.12
Statistical analysis
  • High-Touch vs Optimal Discharge Planning · Regression, Logistic · p = 0.9079 (Controlling for: age, sex, race, ethnicity, insurance, engagement at baseline, comfortability with technology, tech literacy (HINTS), social support at baseline (ISEL), health literacy (AAHLS), illness burden (CCI), and area deprivation index (ADI).) · Odds ratio (or): 0.74 · 95% CI 0.13 to 4.28Chi-squared statistics 0.19 with degrees of freedom (2).
  • High-Tech vs Optimal Discharge Planning · Regression, Logistic · p = 0.9079 (Controlling for: age, sex, race, ethnicity, insurance, engagement at baseline, comfortability with technology, tech literacy (HINTS), social support at baseline (ISEL), health literacy (AAHLS), illness burden (CCI), and area deprivation index (ADI).) · Odds ratio (or): 0.68 · 95% CI 0.13 to 3.72Chi-squared statistics 0.19 with degrees of freedom (2).
  • High-Touch vs High-Tech · Regression, Logistic · p = 0.9079 (Controlling for: age, sex, race, ethnicity, insurance, engagement at baseline, comfortability with technology, tech literacy (HINTS), social support at baseline (ISEL), health literacy (AAHLS), illness burden (CCI), and area deprivation index (ADI).) · Odds ratio (or): 1.08 · 95% CI 0.34 to 3.45Chi-squared statistics 0.19 with degrees of freedom (2).
SecondaryGaps in Care: Cardiovascular Disease (CVD)

Gaps in care will be assessed using Healthcare Effectiveness Data and Information Set (HEDIS) quality metrics. For CVD, we assess the percentage of males 21-75 years of age and females 40-75 years of age during the measurement year, who were identified as having clinical atherosclerotic cardiovascular disease (ASCVD) and met the following criteria. The following rates are reported: 1. Received Statin Therapy. Members who were dispensed at least one high-intensity or moderate-intensity statin medication during the measurement year (SPC-1). 2. Statin Adherence 80%. Members who remained on a high-intensity or moderate-intensity statin medication for at least 80% of the treatment period (SPC-2).

Time frame:
Assessed at baseline, 6- and 12-Months
Reported as:
Count of participants · Participants
Gaps in Care: Cardiovascular Disease (CVD)
ParticipantsHigh-TouchHigh-TechOptimal Discharge Planning
Baseline SPC-1 — Did not close gap in care745
Baseline SPC-1 — Closed gap in care383822
6-Month SPC-1 — Did not close gap in care856
6-Month SPC-1 — Closed gap in care424926
12-Month SPC-1 — Did not close gap in care11107
12-Month SPC-1 — Closed gap in care486933
Baseline SPC-2 — Did not close gap in care1667
Baseline SPC-2 — Closed gap in care223215
6-Month SPC-2 — Did not close gap in care111711
6-Month SPC-2 — Closed gap in care313215
12-Month SPC-2 — Did not close gap in care142314
12-Month SPC-2 — Closed gap in care344619
Statistical analysis
  • High-Touch vs High-Tech vs Optimal Discharge Planning · Mixed Models Analysis · p = 0.9912 (Controlling for: age, sex, race, ethnicity, insurance, engagement at baseline, comfortability with technology, tech literacy (HINTS), social support at baseline (ISEL), health literacy (AAHLS), illness burden (CCI), and area deprivation index (ADI).)F-statistics 0.07 with degrees of freedom (4, 335).
  • High-Touch vs High-Tech vs Optimal Discharge Planning · Mixed Models Analysis · p = 0.8760 (Controlling for: age, sex, race, ethnicity, insurance, engagement at baseline, comfortability with technology, tech literacy (HINTS), social support at baseline (ISEL), health literacy (AAHLS), illness burden (CCI), and area deprivation index (ADI).)F-statistics 0.13 with degrees of freedom (2, 339).
  • High-Touch vs High-Tech vs Optimal Discharge Planning · Mixed Models Analysis · p = 0.6780 (Controlling for: age, sex, race, ethnicity, insurance, engagement at baseline, comfortability with technology, tech literacy (HINTS), social support at baseline (ISEL), health literacy (AAHLS), illness burden (CCI), and area deprivation index (ADI).)F-statistics 0.39 with degrees of freedom (2, 276).
  • High-Touch vs High-Tech vs Optimal Discharge Planning · Mixed Models Analysis · p = 0.1761 (Controlling for: age, sex, race, ethnicity, insurance, engagement at baseline, comfortability with technology, tech literacy (HINTS), social support at baseline (ISEL), health literacy (AAHLS), illness burden (CCI), and area deprivation index (ADI).)F-statistics 1.59 with degrees of freedom (4, 284).
  • High-Touch vs High-Tech vs Optimal Discharge Planning · Mixed Models Analysis · p = 0.3239 (Controlling for: age, sex, race, ethnicity, insurance, engagement at baseline, comfortability with technology, tech literacy (HINTS), social support at baseline (ISEL), health literacy (AAHLS), illness burden (CCI), and area deprivation index (ADI).)F-statistics 1.13 with degrees of freedom (2, 288).
  • High-Touch vs High-Tech vs Optimal Discharge Planning · Mixed Models Analysis · p = 0.7415 (Controlling for: age, sex, race, ethnicity, insurance, engagement at baseline, comfortability with technology, tech literacy (HINTS), social support at baseline (ISEL), health literacy (AAHLS), illness burden (CCI), and area deprivation index (ADI).)F-statistics 0.30 with degrees of freedom (2, 139).
SecondaryGaps in Care: Diabetes

Gaps in care will be assessed using Healthcare Effectiveness Data and Information Set (HEDIS) quality metrics. For diabetes, we assess the percentage of members 40-75 years of age during the measurement year with diabetes who do not have clinical atherosclerotic cardiovascular disease (ASCVD) who met the following criteria. Two rates are reported: 1. Received Statin Therapy. Members who were dispensed at least one statin medication of any intensity during the measurement year (SPD-1). 2. Statin Adherence 80%. Members who remained on a statin medication of any intensity for at least 80% of the treatment period (SPD-2).

Time frame:
Assessed at baseline, 6- and 12-Months
Reported as:
Count of participants · Participants
Gaps in Care: Diabetes
ParticipantsHigh-TouchHigh-TechOptimal Discharge Planning
Baseline SPD-1 — Did not close gap in care252415
Baseline SPD-1 — Closed gap in care809544
6-Month SPD-1 — Did not close gap in care282512
6-Month SPD-1 — Closed gap in care797933
12-Month SPD-1 — Did not close gap in care20199
12-Month SPD-1 — Closed gap in care686925
Baseline SPD-2 — Did not close gap in care193118
Baseline SPD-2 — Closed gap in care616426
6-Month SPD-2 — Did not close gap in care182711
6-Month SPD-2 — Closed gap in care615222
12-Month SPD-2 — Did not close gap in care14266
12-Month SPD-2 — Closed gap in care544319
Statistical analysis
  • High-Touch vs High-Tech vs Optimal Discharge Planning · Mixed Models Analysis · p = 0.9786 (Controlling for: age, sex, race, ethnicity, insurance, engagement at baseline, comfortability with technology, tech literacy (HINTS), social support at baseline (ISEL), health literacy (AAHLS), illness burden (CCI), and area deprivation index (ADI).)F-statistics 0.11 with degrees of freedom (4, 608).
  • High-Touch vs High-Tech vs Optimal Discharge Planning · Mixed Models Analysis · p = 0.4703 (Controlling for: age, sex, race, ethnicity, insurance, engagement at baseline, comfortability with technology, tech literacy (HINTS), social support at baseline (ISEL), health literacy (AAHLS), illness burden (CCI), and area deprivation index (ADI).)F-statistics 0.76 with degrees of freedom (2, 612).
  • High-Touch vs High-Tech vs Optimal Discharge Planning · Mixed Models Analysis · p = 0.8770 (Controlling for: age, sex, race, ethnicity, insurance, engagement at baseline, comfortability with technology, tech literacy (HINTS), social support at baseline (ISEL), health literacy (AAHLS), illness burden (CCI), and area deprivation index (ADI).)F-statistics 0.13 with degrees of freedom (2, 332).
  • High-Touch vs High-Tech vs Optimal Discharge Planning · Mixed Models Analysis · p = 0.6198 (Controlling for: age, sex, race, ethnicity, insurance, engagement at baseline, comfortability with technology, tech literacy (HINTS), social support at baseline (ISEL), health literacy (AAHLS), illness burden (CCI), and area deprivation index (ADI).)F-statistics 0.66 with degrees of freedom (4, 469).
  • High-Touch vs High-Tech vs Optimal Discharge Planning · Mixed Models Analysis · p = 0.6211 (Controlling for: age, sex, race, ethnicity, insurance, engagement at baseline, comfortability with technology, tech literacy (HINTS), social support at baseline (ISEL), health literacy (AAHLS), illness burden (CCI), and area deprivation index (ADI).)F-statistics 0.48 with degrees of freedom (2, 473).
  • High-Touch vs High-Tech vs Optimal Discharge Planning · Mixed Models Analysis · p = 0.1471 (Controlling for: age, sex, race, ethnicity, insurance, engagement at baseline, comfortability with technology, tech literacy (HINTS), social support at baseline (ISEL), health literacy (AAHLS), illness burden (CCI), and area deprivation index (ADI).)F-statistics 1.93 with degrees of freedom (2, 219).
SecondaryGaps in Care: Depression

Gaps in care will be assessed using Healthcare Effectiveness Data and Information Set (HEDIS) quality metrics. For depression, we assess the percentage of members diagnosed with a new episode of major depression, treated with antidepressant medication, and who remained on an antidepressant medication for: 1. Effective Acute Phase Treatment - 84 days of continuous treatment during 114-day period following the Index Prescription Start Date (AMM-1). 2. Effective Continuation Phase Treatment - 180 days of continuous treatment during 231-day period following the Index Prescription Start Date (AMM-2).

Time frame:
Assessed at baseline, 6- and 12-Months
Reported as:
Count of participants · Participants
Gaps in Care: Depression
ParticipantsHigh-TouchHigh-TechOptimal Discharge Planning
Baseline AMM-1 — Did not close gap in care241210
Baseline AMM-1 — Closed gap in care293513
6-Month AMM-1 — Did not close gap in care20146
6-Month AMM-1 — Closed gap in care353019
12-Month AMM-1 — Did not close gap in care22229
12-Month AMM-1 — Closed gap in care343725
Baseline AMM-2 — Did not close gap in care281916
Baseline AMM-2 — Closed gap in care25287
6-Month AMM-2 — Did not close gap in care26249
6-Month AMM-2 — Closed gap in care292016
12-Month AMM-2 — Did not close gap in care323114
12-Month AMM-2 — Closed gap in care242820
Statistical analysis
  • High-Touch vs High-Tech vs Optimal Discharge Planning · Mixed Models Analysis · p = 0.8247 (Controlling for: age, sex, race, ethnicity, insurance, engagement at baseline, comfortability with technology, tech literacy (HINTS), social support at baseline (ISEL), health literacy (AAHLS), illness burden (CCI), and area deprivation index (ADI).)F-statistics 0.38 with degrees of freedom (4, 280).
  • High-Touch vs High-Tech vs Optimal Discharge Planning · Mixed Models Analysis · p = 0.6651 (Controlling for: age, sex, race, ethnicity, insurance, engagement at baseline, comfortability with technology, tech literacy (HINTS), social support at baseline (ISEL), health literacy (AAHLS), illness burden (CCI), and area deprivation index (ADI).)F-statistics 0.41 with degrees of freedom (2, 284).
  • High-Touch vs High-Tech vs Optimal Discharge Planning · Mixed Models Analysis · p = 0.3441 (Controlling for: age, sex, race, ethnicity, insurance, engagement at baseline, comfortability with technology, tech literacy (HINTS), social support at baseline (ISEL), health literacy (AAHLS), illness burden (CCI), and area deprivation index (ADI).)F-statistics 1.07 with degrees of freedom (2, 218).
  • High-Touch vs High-Tech vs Optimal Discharge Planning · Mixed Models Analysis · p = 0.0847 (Controlling for: age, sex, race, ethnicity, insurance, engagement at baseline, comfortability with technology, tech literacy (HINTS), social support at baseline (ISEL), health literacy (AAHLS), illness burden (CCI), and area deprivation index (ADI).)F-statistics 2.07 with degrees of freedom (4, 280).
  • High-Touch vs High-Tech vs Optimal Discharge Planning · Mixed Models Analysis · p = 0.9695 (Controlling for: age, sex, race, ethnicity, insurance, engagement at baseline, comfortability with technology, tech literacy (HINTS), social support at baseline (ISEL), health literacy (AAHLS), illness burden (CCI), and area deprivation index (ADI).)F-statistics 0.03 with degrees of freedom (2, 284).
  • High-Touch vs High-Tech vs Optimal Discharge Planning · Mixed Models Analysis · p = 0.9396 (Controlling for: age, sex, race, ethnicity, insurance, engagement at baseline, comfortability with technology, tech literacy (HINTS), social support at baseline (ISEL), health literacy (AAHLS), illness burden (CCI), and area deprivation index (ADI).)F-statistics 0.06 with degrees of freedom (2, 200).

Adverse events

Collected over Adverse event data was collected for each participant 12 months following enrollment in the study.. Non-serious events are listed at a 0% frequency threshold.

Adverse event summary by group
GroupDeathsSeriousOther
High-Touch15/559 (2.7%)0/559 (0%)0/559 (0%)
High-Tech17/545 (3.1%)0/545 (0%)0/545 (0%)
Optimal Discharge Planning11/283 (3.9%)0/283 (0%)0/283 (0%)

Baseline characteristics

Three participants formally withdrew from the High-Tech arm and are therefore excluded from the analysis. Additionally, we could not confirm accurate eligibility criteria for 10 participants at the time of analysis, so they are also excluded.

Age, Continuous
Age, Continuous(years)High-TouchHigh-TechOptimal Discharge PlanningTotal
Mean52.87 ± 11.6853.59 ± 11.5953.67 ± 12.0853.32 ± 11.72
Sex: Female, Male
Sex: Female, Male(Participants)High-TouchHigh-TechOptimal Discharge PlanningTotal
Female341345188874
Male21820095513
Ethnicity (NIH/OMB)
Ethnicity (NIH/OMB)(Participants)High-TouchHigh-TechOptimal Discharge PlanningTotal
Hispanic or Latino1515939
Not Hispanic or Latino5445302741348
Unknown or Not Reported0000
Race (NIH/OMB)
Race (NIH/OMB)(Participants)High-TouchHigh-TechOptimal Discharge PlanningTotal
American Indian or Alaska Native75315
Asian1001
Native Hawaiian or Other Pacific Islander1304
Black or African American12212057299
White4143942041012
More than one race108927
Unknown or Not Reported4151029
Charlson Comorbidity Index (CCI)
Charlson Comorbidity Index (CCI)(units on a scale)High-TouchHigh-TechOptimal Discharge PlanningTotal
Mean4.94 ± 3.235.14 ± 3.075.16 ± 3.425.06 ± 3.21
Area Deprivation Index (ADI)
Area Deprivation Index (ADI)(units on a scale)High-TouchHigh-TechOptimal Discharge PlanningTotal
Mean109.64 ± 5.29109.45 ± 5.62109.60 ± 5.11109.56 ± 5.38
Comfort with Technology/ Digital Literacy
Comfort with Technology/ Digital Literacy(Participants)High-TouchHigh-TechOptimal Discharge PlanningTotal
Comfortable: Disagree Strongly33411690
Comfortable: Disagree857035190
Comfortable: Agree310296162768
Comfortable: Agree Strongly13113870339
Line of Business (Medicaid/ Medicaid-Medicare)
Line of Business (Medicaid/ Medicaid-Medicare)(Participants)High-TouchHigh-TechOptimal Discharge PlanningTotal
Medicare-Medicaid11810759284
Medicaid4414382241103

1 further baseline measures are reported on the registry.

07

Study locations

1 site
  • UPMC
    Pittsburgh, Pennsylvania 15219, United States
08

References and documents

Publications

  • Kearney SM, Williams K, Nikolajski C, Park MJ, Kraemer KL, Landsittel D, Kang C, Malito A, Schuster J. Stakeholder impact on the implementation of integrated care: Opportunities to consider for patient-centered outcomes research. Contemp Clin Trials. 2021 Feb;101:106256. doi: 10.1016/j.cct.2020.106256. Epub 2020 Dec 29. PubMed 33383229 ↗
  • Williams K, Markwardt S, Kearney SM, Karp JF, Kraemer KL, Park MJ, Freund P, Watson A, Schuster J, Beckjord E. Addressing Implementation Challenges to Digital Care Delivery for Adults With Multiple Chronic Conditions: Stakeholder Feedback in a Randomized Controlled Trial. JMIR Mhealth Uhealth. 2021 Feb 1;9(2):e23498. doi: 10.2196/23498. Erratum In: JMIR Mhealth Uhealth. 2021 Feb 26;9(2):e27996. doi: 10.2196/27996. PubMed 33522981 ↗

Study documents

  • Protocol and statistical analysis plan · Dec 1, 2022

Documents are hosted by the registry — open the source record to download them.

Individual participant data

Plan to share: No — Due to the sensitive nature of the questions asked in this study, survey respondents were assured raw data would remain confidential and would not be shared.

09

Registry details

Key details

Study ID
NCT03451630
Lead sponsor
University of Pittsburgh
Collaborators
Patient-Centered Outcomes Research Institute
Responsible party
Daniel Swayze (Vice President, Community Services for UPMC Health Plan, University of Pittsburgh) — Principal investigator
First posted
Mar 2, 2018
Start date
Sep 4, 2018
Primary completion
Nov 30, 2022
Completion
Nov 30, 2022
Results posted
Dec 9, 2024
Last update
Dec 9, 2024

Study contacts

Dan Swayze, DrPH, MBA
principal investigator · University of Pittsburgh

Oversight

Data monitoring committee
Yes
FDA-regulated drug
No
FDA-regulated device
No
View the source record on ClinicalTrials.gov ↗

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