Anxiety, Asthma, Atrial Fibrillation, Bipolar Disorder, Chronic Obstructive Pulmonary Disease, Congestive Heart Failure, Depression, Diabetes, Hypertension, Schizophrenia
Conditions
Keywords
chronic conditions, care management, digital tools
Brief 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.
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.
Interventions
Intensive, in-person and/or telephonic support.
Remote care management and self-directed digital tools.
Transition to other Health Plan disease management programs and/or community resources.
Sponsors
Study design
Intervention model description
We chose an individual, stratified randomized trial design to randomly assign each enrollee to one of the three interventions arms, minimizing and balancing confounding variables. We will utilize an unequal randomization ratio of 2:2:1 for High-Touch, High-Tech, and ODP, respectively. While the less resource intensive ODP, in fact, improve meaningful outcomes for certain patient subgroups, our health care system has invested heavily in High-Touch and High-Tech as evidence-based solutions for chronic disease care. We will use a mixed-methods approach that incorporates both qualitative and quantitative data.
Eligibility
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
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.
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Patient Activation | Baseline, 3-, 6-, and 12-months. | 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. |
| Change in Health Status | Baseline, 3-, 6-, and 12-months. | 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. |
| 90-Day Hospital Readmission Rate | 1 to 90 days | 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. |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Care Satisfaction | Baseline, 3-, 6-, and 12-months. | 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. |
| Emergent Care Use | Assessed at baseline, 6- and 12-Months. | 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. |
| Engagement in Primary Care | Assessed at baseline, 6- and 12-Months. | 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. |
| Engagement in Specialty Care | Assessed at baseline, 6- and 12-Months. | 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. |
| Inpatient Readmissions Over 12-Months | Assessed at baseline, 6- and 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. |
| Mental Health Care Visits | Assessed at baseline, 6- and 12-Months. | 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. |
| 30-Day Hospital Readmission Rate | 1 to 30 days | 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. |
| Gaps in Care: Chronic Obstructive Pulmonary Disease (COPD) | Assessed at baseline, 6- and 12-Months | 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) |
| Gaps in Care: Congestive Heart Failure (CHF) | Assessed at 30-days from an index admission discharge. | 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. |
| Gaps in Care: Cardiovascular Disease (CVD) | Assessed at baseline, 6- and 12-Months | 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). |
| Gaps in Care: Diabetes | Assessed at baseline, 6- and 12-Months | 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). |
| Gaps in Care: Depression | Assessed at baseline, 6- and 12-Months | 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). |
| Gaps in Care: Asthma | Assessed at baseline, 6- and 12-Months | 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). |
| Functional Status | Baseline, 3-, 6-, and 12-months. | 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. |
| Quality of Life | Baseline, 3-, 6-, and 12-months. | 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. |
Countries
United States
Participant flow
Recruitment details
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.
Participants by arm
| Arm | Count |
|---|---|
| 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.
High-Touch: Intensive, in-person and/or telephonic support. | 559 |
| 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.
High-Tech: Remote care management and self-directed digital tools. | 545 |
| Optimal Discharge Planning Delivered via Health Plan support and resources within 14-30 days of an initial home or telephonic visit.
Optimal Discharge Planning: Transition to other Health Plan disease management programs and/or community resources. | 283 |
| Total | 1,387 |
Withdrawals & dropouts
| Period | Reason | FG000 | FG001 | FG002 |
|---|---|---|---|---|
| Overall Study | Death | 15 | 16 | 11 |
| Overall Study | Lost to Follow-up | 9 | 0 | 4 |
| Overall Study | Unable to confirm accurate eligibility criteria after randomization and intervention completion. | 3 | 4 | 3 |
| Overall Study | Withdrawal by Subject | 0 | 3 | 0 |
Baseline characteristics
| Characteristic | High-Tech | Total | High-Touch | Optimal Discharge Planning |
|---|---|---|---|---|
| Age, Continuous | 53.59 years STANDARD_DEVIATION 11.59 | 53.32 years STANDARD_DEVIATION 11.72 | 52.87 years STANDARD_DEVIATION 11.68 | 53.67 years STANDARD_DEVIATION 12.08 |
| Area Deprivation Index (ADI) | 109.45 units on a scale STANDARD_DEVIATION 5.62 | 109.56 units on a scale STANDARD_DEVIATION 5.38 | 109.64 units on a scale STANDARD_DEVIATION 5.29 | 109.60 units on a scale STANDARD_DEVIATION 5.11 |
| Charlson Comorbidity Index (CCI) | 5.14 units on a scale STANDARD_DEVIATION 3.07 | 5.06 units on a scale STANDARD_DEVIATION 3.21 | 4.94 units on a scale STANDARD_DEVIATION 3.23 | 5.16 units on a scale STANDARD_DEVIATION 3.42 |
| Comfort with Technology/ Digital Literacy Comfortable: Agree | 296 Participants | 768 Participants | 310 Participants | 162 Participants |
| Comfort with Technology/ Digital Literacy Comfortable: Agree Strongly | 138 Participants | 339 Participants | 131 Participants | 70 Participants |
| Comfort with Technology/ Digital Literacy Comfortable: Disagree | 70 Participants | 190 Participants | 85 Participants | 35 Participants |
| Comfort with Technology/ Digital Literacy Comfortable: Disagree Strongly | 41 Participants | 90 Participants | 33 Participants | 16 Participants |
| Engagement at Baseline No | 213 Participants | 674 Participants | 215 Participants | 246 Participants |
| Engagement at Baseline Yes | 332 Participants | 713 Participants | 344 Participants | 37 Participants |
| Ethnicity (NIH/OMB) Hispanic or Latino | 15 Participants | 39 Participants | 15 Participants | 9 Participants |
| Ethnicity (NIH/OMB) Not Hispanic or Latino | 530 Participants | 1348 Participants | 544 Participants | 274 Participants |
| Ethnicity (NIH/OMB) Unknown or Not Reported | 0 Participants | 0 Participants | 0 Participants | 0 Participants |
| Line of Business (Medicaid/ Medicaid-Medicare) Medicaid | 438 Participants | 1103 Participants | 441 Participants | 224 Participants |
| Line of Business (Medicaid/ Medicaid-Medicare) Medicare-Medicaid | 107 Participants | 284 Participants | 118 Participants | 59 Participants |
| Race (NIH/OMB) American Indian or Alaska Native | 5 Participants | 15 Participants | 7 Participants | 3 Participants |
| Race (NIH/OMB) Asian | 0 Participants | 1 Participants | 1 Participants | 0 Participants |
| Race (NIH/OMB) Black or African American | 120 Participants | 299 Participants | 122 Participants | 57 Participants |
| Race (NIH/OMB) More than one race | 8 Participants | 27 Participants | 10 Participants | 9 Participants |
| Race (NIH/OMB) Native Hawaiian or Other Pacific Islander | 3 Participants | 4 Participants | 1 Participants | 0 Participants |
| Race (NIH/OMB) Unknown or Not Reported | 15 Participants | 29 Participants | 4 Participants | 10 Participants |
| Race (NIH/OMB) White | 394 Participants | 1012 Participants | 414 Participants | 204 Participants |
| Sex: Female, Male Female | 345 Participants | 874 Participants | 341 Participants | 188 Participants |
| Sex: Female, Male Male | 200 Participants | 513 Participants | 218 Participants | 95 Participants |
Adverse events
| Event type | EG000 affected / at risk | EG001 affected / at risk | EG002 affected / at risk |
|---|---|---|---|
| deaths Total, all-cause mortality | 15 / 559 | 17 / 545 | 11 / 283 |
| other Total, other adverse events | 0 / 559 | 0 / 545 | 0 / 283 |
| serious Total, serious adverse events | 0 / 559 | 0 / 545 | 0 / 283 |
Outcome results
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
Population: 8 participants (0.57%) have missing readmission data. Since 31 participants had more than one admission within 90 days, a binary indicator of readmission within 90 days was generated and used as a primary outcome.
| Arm | Measure | Category | Value (COUNT_OF_PARTICIPANTS) |
|---|---|---|---|
| High-Touch | 90-Day Hospital Readmission Rate | No readmission within 90 days | 472 Participants |
| High-Touch | 90-Day Hospital Readmission Rate | At least one readmission within 90 days | 85 Participants |
| High-Tech | 90-Day Hospital Readmission Rate | No readmission within 90 days | 470 Participants |
| High-Tech | 90-Day Hospital Readmission Rate | At least one readmission within 90 days | 71 Participants |
| Optimal Discharge Planning | 90-Day Hospital Readmission Rate | No readmission within 90 days | 240 Participants |
| Optimal Discharge Planning | 90-Day Hospital Readmission Rate | At least one readmission within 90 days | 41 Participants |
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.
Population: Includes all individuals who completed the measure at least one timepoint.
| Arm | Measure | Group | Value (MEAN) | Dispersion |
|---|---|---|---|---|
| High-Touch | Change in Health Status | Baseline | 39.61 score on a scale | Standard Deviation 18.39 |
| High-Touch | Change in Health Status | 3-Month | 42.12 score on a scale | Standard Deviation 20.06 |
| High-Touch | Change in Health Status | 6-Month | 41.86 score on a scale | Standard Deviation 19.84 |
| High-Touch | Change in Health Status | 12-Month | 42.68 score on a scale | Standard Deviation 20.5 |
| High-Tech | Change in Health Status | 12-Month | 42.27 score on a scale | Standard Deviation 19.63 |
| High-Tech | Change in Health Status | Baseline | 39.50 score on a scale | Standard Deviation 18.65 |
| High-Tech | Change in Health Status | 6-Month | 41.39 score on a scale | Standard Deviation 19.84 |
| High-Tech | Change in Health Status | 3-Month | 42.03 score on a scale | Standard Deviation 19.9 |
| Optimal Discharge Planning | Change in Health Status | 12-Month | 40.85 score on a scale | Standard Deviation 19.03 |
| Optimal Discharge Planning | Change in Health Status | 3-Month | 41.31 score on a scale | Standard Deviation 19.99 |
| Optimal Discharge Planning | Change in Health Status | 6-Month | 41.83 score on a scale | Standard Deviation 20.84 |
| Optimal Discharge Planning | Change in Health Status | Baseline | 39.05 score on a scale | Standard Deviation 17.8 |
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.
Population: Includes all individuals who completed the measure at least one timepoint.
| Arm | Measure | Group | Value (MEAN) | Dispersion |
|---|---|---|---|---|
| High-Touch | Patient Activation | 12-Months | 63.15 score on a scale | Standard Deviation 15.05 |
| High-Touch | Patient Activation | Baseline | 61.87 score on a scale | Standard Deviation 14.36 |
| High-Touch | Patient Activation | 3-Months | 63.15 score on a scale | Standard Deviation 15.56 |
| High-Touch | Patient Activation | 6-Months | 62.55 score on a scale | Standard Deviation 16.03 |
| High-Tech | Patient Activation | 3-Months | 63.60 score on a scale | Standard Deviation 16.65 |
| High-Tech | Patient Activation | 12-Months | 64.58 score on a scale | Standard Deviation 15.41 |
| High-Tech | Patient Activation | 6-Months | 62.15 score on a scale | Standard Deviation 15.84 |
| High-Tech | Patient Activation | Baseline | 63.73 score on a scale | Standard Deviation 16.1 |
| Optimal Discharge Planning | Patient Activation | 12-Months | 62.83 score on a scale | Standard Deviation 15.75 |
| Optimal Discharge Planning | Patient Activation | Baseline | 63.82 score on a scale | Standard Deviation 16.12 |
| Optimal Discharge Planning | Patient Activation | 3-Months | 63.60 score on a scale | Standard Deviation 15.98 |
| Optimal Discharge Planning | Patient Activation | 6-Months | 64.76 score on a scale | Standard Deviation 15.98 |
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
Population: Since only 2 participants had more than one admission (2 admissions) within 30 days, a binary indicator of readmission within 30 days was generated and used as the outcome.
| Arm | Measure | Category | Value (COUNT_OF_PARTICIPANTS) |
|---|---|---|---|
| High-Touch | 30-Day Hospital Readmission Rate | No readmission within 30 days | 535 Participants |
| High-Touch | 30-Day Hospital Readmission Rate | At least one readmission within 30 days | 24 Participants |
| High-Tech | 30-Day Hospital Readmission Rate | No readmission within 30 days | 528 Participants |
| High-Tech | 30-Day Hospital Readmission Rate | At least one readmission within 30 days | 17 Participants |
| Optimal Discharge Planning | 30-Day Hospital Readmission Rate | No readmission within 30 days | 272 Participants |
| Optimal Discharge Planning | 30-Day Hospital Readmission Rate | At least one readmission within 30 days | 11 Participants |
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.
Population: Includes all individuals who completed the measure at least one timepoint.
| Arm | Measure | Group | Value (MEAN) | Dispersion |
|---|---|---|---|---|
| High-Touch | Care Satisfaction | Baseline | 2.96 score on a scale | Standard Deviation 0.98 |
| High-Touch | Care Satisfaction | 3-Month | 3.02 score on a scale | Standard Deviation 1 |
| High-Touch | Care Satisfaction | 6-Month | 3.03 score on a scale | Standard Deviation 0.98 |
| High-Touch | Care Satisfaction | 12-Month | 3.05 score on a scale | Standard Deviation 1.01 |
| High-Tech | Care Satisfaction | 12-Month | 3.03 score on a scale | Standard Deviation 1.01 |
| High-Tech | Care Satisfaction | Baseline | 2.86 score on a scale | Standard Deviation 0.94 |
| High-Tech | Care Satisfaction | 6-Month | 2.97 score on a scale | Standard Deviation 1.01 |
| High-Tech | Care Satisfaction | 3-Month | 2.99 score on a scale | Standard Deviation 0.99 |
| Optimal Discharge Planning | Care Satisfaction | 12-Month | 3.00 score on a scale | Standard Deviation 0.99 |
| Optimal Discharge Planning | Care Satisfaction | 3-Month | 2.97 score on a scale | Standard Deviation 0.97 |
| Optimal Discharge Planning | Care Satisfaction | 6-Month | 2.93 score on a scale | Standard Deviation 1 |
| Optimal Discharge Planning | Care Satisfaction | Baseline | 2.96 score on a scale | Standard Deviation 1 |
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.
Population: For each timepoint, participants who were eligible for Medicaid/Medicaid-Medicare with available claims data during at least 9 months (non-continuous) of the past 12 months.
| Arm | Measure | Group | Value (MEAN) | Dispersion |
|---|---|---|---|---|
| High-Touch | Emergent Care Use | 6-Month | 1.33 visits | Standard Deviation 2.08 |
| High-Touch | Emergent Care Use | Baseline | 2.83 visits | Standard Deviation 3.25 |
| High-Touch | Emergent Care Use | 12-Month | 2.41 visits | Standard Deviation 3.58 |
| High-Tech | Emergent Care Use | 6-Month | 1.31 visits | Standard Deviation 2.44 |
| High-Tech | Emergent Care Use | Baseline | 2.40 visits | Standard Deviation 3.36 |
| High-Tech | Emergent Care Use | 12-Month | 2.40 visits | Standard Deviation 4.32 |
| Optimal Discharge Planning | Emergent Care Use | Baseline | 2.39 visits | Standard Deviation 3.73 |
| Optimal Discharge Planning | Emergent Care Use | 12-Month | 2.29 visits | Standard Deviation 3.29 |
| Optimal Discharge Planning | Emergent Care Use | 6-Month | 1.25 visits | Standard Deviation 2.02 |
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.
Population: For each timepoint, participants who were eligible for Medicaid/Medicaid-Medicare with available claims data during at least 9 months (non-continuous) of the past 12 months.
| Arm | Measure | Group | Category | Value (COUNT_OF_PARTICIPANTS) |
|---|---|---|---|---|
| High-Touch | Engagement in Primary Care | 6-Months | At least one PCP visit | 467 Participants |
| High-Touch | Engagement in Primary Care | 12-Months | Missing Data | 30 Participants |
| High-Touch | Engagement in Primary Care | 6-Months | Missing Data | 8 Participants |
| High-Touch | Engagement in Primary Care | 6-Months | No PCP visit | 84 Participants |
| High-Touch | Engagement in Primary Care | Baseline | At least one PCP visit | 451 Participants |
| High-Touch | Engagement in Primary Care | 12-Months | No PCP visit | 62 Participants |
| High-Touch | Engagement in Primary Care | Baseline | Missing Data | 44 Participants |
| High-Touch | Engagement in Primary Care | Baseline | No PCP visit | 64 Participants |
| High-Touch | Engagement in Primary Care | 12-Months | At least one PCP visit | 467 Participants |
| High-Tech | Engagement in Primary Care | 6-Months | No PCP visit | 72 Participants |
| High-Tech | Engagement in Primary Care | Baseline | At least one PCP visit | 468 Participants |
| High-Tech | Engagement in Primary Care | Baseline | No PCP visit | 41 Participants |
| High-Tech | Engagement in Primary Care | Baseline | Missing Data | 36 Participants |
| High-Tech | Engagement in Primary Care | 6-Months | At least one PCP visit | 463 Participants |
| High-Tech | Engagement in Primary Care | 6-Months | Missing Data | 10 Participants |
| High-Tech | Engagement in Primary Care | 12-Months | At least one PCP visit | 476 Participants |
| High-Tech | Engagement in Primary Care | 12-Months | No PCP visit | 44 Participants |
| High-Tech | Engagement in Primary Care | 12-Months | Missing Data | 25 Participants |
| Optimal Discharge Planning | Engagement in Primary Care | Baseline | Missing Data | 29 Participants |
| Optimal Discharge Planning | Engagement in Primary Care | Baseline | At least one PCP visit | 224 Participants |
| Optimal Discharge Planning | Engagement in Primary Care | 12-Months | At least one PCP visit | 238 Participants |
| Optimal Discharge Planning | Engagement in Primary Care | Baseline | No PCP visit | 30 Participants |
| Optimal Discharge Planning | Engagement in Primary Care | 12-Months | Missing Data | 23 Participants |
| Optimal Discharge Planning | Engagement in Primary Care | 6-Months | No PCP visit | 32 Participants |
| Optimal Discharge Planning | Engagement in Primary Care | 6-Months | At least one PCP visit | 242 Participants |
| Optimal Discharge Planning | Engagement in Primary Care | 12-Months | No PCP visit | 22 Participants |
| Optimal Discharge Planning | Engagement in Primary Care | 6-Months | Missing Data | 9 Participants |
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.
Population: For each timepoint, participants who were eligible for Medicaid/Medicaid-Medicare with available claims data during at least 9 months (non-continuous) of the past 12 months.
| Arm | Measure | Group | Value (MEAN) | Dispersion |
|---|---|---|---|---|
| High-Touch | Engagement in Specialty Care | 6-Month | 4.15 visits | Standard Deviation 5.34 |
| High-Touch | Engagement in Specialty Care | Baseline | 7.29 visits | Standard Deviation 10.2 |
| High-Touch | Engagement in Specialty Care | 12-Month | 7.80 visits | Standard Deviation 9.02 |
| High-Tech | Engagement in Specialty Care | 6-Month | 4.51 visits | Standard Deviation 6.53 |
| High-Tech | Engagement in Specialty Care | Baseline | 7.54 visits | Standard Deviation 8.89 |
| High-Tech | Engagement in Specialty Care | 12-Month | 8.31 visits | Standard Deviation 10.39 |
| Optimal Discharge Planning | Engagement in Specialty Care | Baseline | 7.20 visits | Standard Deviation 8.5 |
| Optimal Discharge Planning | Engagement in Specialty Care | 12-Month | 7.84 visits | Standard Deviation 9.33 |
| Optimal Discharge Planning | Engagement in Specialty Care | 6-Month | 4.08 visits | Standard Deviation 5.16 |
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.
Population: Includes all individuals who completed the measure at least one timepoint.
| Arm | Measure | Group | Value (MEAN) | Dispersion |
|---|---|---|---|---|
| High-Touch | Functional Status | Baseline | 36.75 T score | Standard Deviation 7.89 |
| High-Touch | Functional Status | 3-Month | 37.11 T score | Standard Deviation 7.65 |
| High-Touch | Functional Status | 6-Month | 37.30 T score | Standard Deviation 7.87 |
| High-Touch | Functional Status | 12-Month | 36.99 T score | Standard Deviation 8.65 |
| High-Tech | Functional Status | 12-Month | 36.73 T score | Standard Deviation 8.14 |
| High-Tech | Functional Status | Baseline | 36.29 T score | Standard Deviation 7.98 |
| High-Tech | Functional Status | 6-Month | 36.85 T score | Standard Deviation 7.76 |
| High-Tech | Functional Status | 3-Month | 37.02 T score | Standard Deviation 7.97 |
| Optimal Discharge Planning | Functional Status | 12-Month | 36.29 T score | Standard Deviation 7.66 |
| Optimal Discharge Planning | Functional Status | 3-Month | 36.83 T score | Standard Deviation 8.2 |
| Optimal Discharge Planning | Functional Status | 6-Month | 37.24 T score | Standard Deviation 7.91 |
| Optimal Discharge Planning | Functional Status | Baseline | 35.78 T score | Standard Deviation 7.6 |
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
Population: Only a very small portion of our total sample size was eligible for Gaps in Care analyses.
| Arm | Measure | Group | Category | Value (COUNT_OF_PARTICIPANTS) |
|---|---|---|---|---|
| High-Touch | Gaps in Care: Asthma | Baseline MMA-1a (50%) | Did not close gap in care | 6 Participants |
| High-Touch | Gaps in Care: Asthma | Baseline MMA-1a (50%) | Closed gap in care | 2 Participants |
| High-Touch | Gaps in Care: Asthma | 6-Month MMA-1a (50%) | Did not close gap in care | 2 Participants |
| High-Touch | Gaps in Care: Asthma | 6-Month MMA-1a (50%) | Closed gap in care | 2 Participants |
| High-Touch | Gaps in Care: Asthma | 12-Month MMA-1a (50%) | Did not close gap in care | 1 Participants |
| High-Touch | Gaps in Care: Asthma | 12-Month MMA-1a (50%) | Closed gap in care | 5 Participants |
| High-Touch | Gaps in Care: Asthma | Baseline MMA-1b (75%) | Did not close gap in care | 6 Participants |
| High-Touch | Gaps in Care: Asthma | Baseline MMA-1b (75%) | Closed gap in care | 2 Participants |
| High-Touch | Gaps in Care: Asthma | 6-Month MMA-1b (75%) | Did not close gap in care | 2 Participants |
| High-Touch | Gaps in Care: Asthma | 6-Month MMA-1b (75%) | Closed gap in care | 2 Participants |
| High-Touch | Gaps in Care: Asthma | 12-Month MMA-1b (75%) | Did not close gap in care | 1 Participants |
| High-Touch | Gaps in Care: Asthma | 12-Month MMA-1b (75%) | Closed gap in care | 5 Participants |
| High-Tech | Gaps in Care: Asthma | 12-Month MMA-1b (75%) | Closed gap in care | 3 Participants |
| High-Tech | Gaps in Care: Asthma | Baseline MMA-1a (50%) | Did not close gap in care | 3 Participants |
| High-Tech | Gaps in Care: Asthma | Baseline MMA-1b (75%) | Did not close gap in care | 9 Participants |
| High-Tech | Gaps in Care: Asthma | 6-Month MMA-1b (75%) | Did not close gap in care | 4 Participants |
| High-Tech | Gaps in Care: Asthma | Baseline MMA-1a (50%) | Closed gap in care | 10 Participants |
| High-Tech | Gaps in Care: Asthma | 12-Month MMA-1a (50%) | Closed gap in care | 6 Participants |
| High-Tech | Gaps in Care: Asthma | 12-Month MMA-1b (75%) | Did not close gap in care | 4 Participants |
| High-Tech | Gaps in Care: Asthma | 6-Month MMA-1a (50%) | Did not close gap in care | 3 Participants |
| High-Tech | Gaps in Care: Asthma | Baseline MMA-1b (75%) | Closed gap in care | 4 Participants |
| High-Tech | Gaps in Care: Asthma | 12-Month MMA-1a (50%) | Did not close gap in care | 1 Participants |
| High-Tech | Gaps in Care: Asthma | 6-Month MMA-1a (50%) | Closed gap in care | 8 Participants |
| High-Tech | Gaps in Care: Asthma | 6-Month MMA-1b (75%) | Closed gap in care | 7 Participants |
| Optimal Discharge Planning | Gaps in Care: Asthma | 6-Month MMA-1a (50%) | Closed gap in care | 2 Participants |
| Optimal Discharge Planning | Gaps in Care: Asthma | 12-Month MMA-1a (50%) | Did not close gap in care | 0 Participants |
| Optimal Discharge Planning | Gaps in Care: Asthma | 6-Month MMA-1b (75%) | Closed gap in care | 2 Participants |
| Optimal Discharge Planning | Gaps in Care: Asthma | 12-Month MMA-1a (50%) | Closed gap in care | 2 Participants |
| Optimal Discharge Planning | Gaps in Care: Asthma | Baseline MMA-1b (75%) | Did not close gap in care | 3 Participants |
| Optimal Discharge Planning | Gaps in Care: Asthma | Baseline MMA-1b (75%) | Closed gap in care | 3 Participants |
| Optimal Discharge Planning | Gaps in Care: Asthma | 12-Month MMA-1b (75%) | Did not close gap in care | 0 Participants |
| Optimal Discharge Planning | Gaps in Care: Asthma | Baseline MMA-1a (50%) | Did not close gap in care | 3 Participants |
| Optimal Discharge Planning | Gaps in Care: Asthma | Baseline MMA-1a (50%) | Closed gap in care | 3 Participants |
| Optimal Discharge Planning | Gaps in Care: Asthma | 6-Month MMA-1b (75%) | Did not close gap in care | 1 Participants |
| Optimal Discharge Planning | Gaps in Care: Asthma | 6-Month MMA-1a (50%) | Did not close gap in care | 1 Participants |
| Optimal Discharge Planning | Gaps in Care: Asthma | 12-Month MMA-1b (75%) | Closed gap in care | 2 Participants |
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
Population: Only a very small portion of the total sample was eligible for CVD Gaps in Care analyses.
| Arm | Measure | Group | Category | Value (COUNT_OF_PARTICIPANTS) |
|---|---|---|---|---|
| High-Touch | Gaps in Care: Cardiovascular Disease (CVD) | Baseline SPC-1 | Did not close gap in care | 7 Participants |
| High-Touch | Gaps in Care: Cardiovascular Disease (CVD) | Baseline SPC-1 | Closed gap in care | 38 Participants |
| High-Touch | Gaps in Care: Cardiovascular Disease (CVD) | 6-Month SPC-1 | Did not close gap in care | 8 Participants |
| High-Touch | Gaps in Care: Cardiovascular Disease (CVD) | 6-Month SPC-1 | Closed gap in care | 42 Participants |
| High-Touch | Gaps in Care: Cardiovascular Disease (CVD) | 12-Month SPC-1 | Did not close gap in care | 11 Participants |
| High-Touch | Gaps in Care: Cardiovascular Disease (CVD) | 12-Month SPC-1 | Closed gap in care | 48 Participants |
| High-Touch | Gaps in Care: Cardiovascular Disease (CVD) | Baseline SPC-2 | Did not close gap in care | 16 Participants |
| High-Touch | Gaps in Care: Cardiovascular Disease (CVD) | Baseline SPC-2 | Closed gap in care | 22 Participants |
| High-Touch | Gaps in Care: Cardiovascular Disease (CVD) | 6-Month SPC-2 | Did not close gap in care | 11 Participants |
| High-Touch | Gaps in Care: Cardiovascular Disease (CVD) | 6-Month SPC-2 | Closed gap in care | 31 Participants |
| High-Touch | Gaps in Care: Cardiovascular Disease (CVD) | 12-Month SPC-2 | Did not close gap in care | 14 Participants |
| High-Touch | Gaps in Care: Cardiovascular Disease (CVD) | 12-Month SPC-2 | Closed gap in care | 34 Participants |
| High-Tech | Gaps in Care: Cardiovascular Disease (CVD) | 12-Month SPC-2 | Closed gap in care | 46 Participants |
| High-Tech | Gaps in Care: Cardiovascular Disease (CVD) | Baseline SPC-1 | Did not close gap in care | 4 Participants |
| High-Tech | Gaps in Care: Cardiovascular Disease (CVD) | Baseline SPC-2 | Did not close gap in care | 6 Participants |
| High-Tech | Gaps in Care: Cardiovascular Disease (CVD) | 6-Month SPC-2 | Did not close gap in care | 17 Participants |
| High-Tech | Gaps in Care: Cardiovascular Disease (CVD) | Baseline SPC-1 | Closed gap in care | 38 Participants |
| High-Tech | Gaps in Care: Cardiovascular Disease (CVD) | 12-Month SPC-1 | Closed gap in care | 69 Participants |
| High-Tech | Gaps in Care: Cardiovascular Disease (CVD) | 12-Month SPC-2 | Did not close gap in care | 23 Participants |
| High-Tech | Gaps in Care: Cardiovascular Disease (CVD) | 6-Month SPC-1 | Did not close gap in care | 5 Participants |
| High-Tech | Gaps in Care: Cardiovascular Disease (CVD) | Baseline SPC-2 | Closed gap in care | 32 Participants |
| High-Tech | Gaps in Care: Cardiovascular Disease (CVD) | 12-Month SPC-1 | Did not close gap in care | 10 Participants |
| High-Tech | Gaps in Care: Cardiovascular Disease (CVD) | 6-Month SPC-1 | Closed gap in care | 49 Participants |
| High-Tech | Gaps in Care: Cardiovascular Disease (CVD) | 6-Month SPC-2 | Closed gap in care | 32 Participants |
| Optimal Discharge Planning | Gaps in Care: Cardiovascular Disease (CVD) | 6-Month SPC-1 | Closed gap in care | 26 Participants |
| Optimal Discharge Planning | Gaps in Care: Cardiovascular Disease (CVD) | 12-Month SPC-1 | Did not close gap in care | 7 Participants |
| Optimal Discharge Planning | Gaps in Care: Cardiovascular Disease (CVD) | 6-Month SPC-2 | Closed gap in care | 15 Participants |
| Optimal Discharge Planning | Gaps in Care: Cardiovascular Disease (CVD) | 12-Month SPC-1 | Closed gap in care | 33 Participants |
| Optimal Discharge Planning | Gaps in Care: Cardiovascular Disease (CVD) | Baseline SPC-2 | Did not close gap in care | 7 Participants |
| Optimal Discharge Planning | Gaps in Care: Cardiovascular Disease (CVD) | Baseline SPC-2 | Closed gap in care | 15 Participants |
| Optimal Discharge Planning | Gaps in Care: Cardiovascular Disease (CVD) | 12-Month SPC-2 | Did not close gap in care | 14 Participants |
| Optimal Discharge Planning | Gaps in Care: Cardiovascular Disease (CVD) | Baseline SPC-1 | Did not close gap in care | 5 Participants |
| Optimal Discharge Planning | Gaps in Care: Cardiovascular Disease (CVD) | Baseline SPC-1 | Closed gap in care | 22 Participants |
| Optimal Discharge Planning | Gaps in Care: Cardiovascular Disease (CVD) | 6-Month SPC-2 | Did not close gap in care | 11 Participants |
| Optimal Discharge Planning | Gaps in Care: Cardiovascular Disease (CVD) | 6-Month SPC-1 | Did not close gap in care | 6 Participants |
| Optimal Discharge Planning | Gaps in Care: Cardiovascular Disease (CVD) | 12-Month SPC-2 | Closed gap in care | 19 Participants |
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
Population: Only a very small portion of the total sample was eligible for COPD Gaps in Care analyses.
| Arm | Measure | Group | Category | Value (COUNT_OF_PARTICIPANTS) |
|---|---|---|---|---|
| High-Touch | Gaps in Care: Chronic Obstructive Pulmonary Disease (COPD) | Baseline PCE-1 | Did not close gap in care | 4 Participants |
| High-Touch | Gaps in Care: Chronic Obstructive Pulmonary Disease (COPD) | Baseline PCE-1 | Closed gap in care | 20 Participants |
| High-Touch | Gaps in Care: Chronic Obstructive Pulmonary Disease (COPD) | 6-Month PCE-1 | Did not close gap in care | 8 Participants |
| High-Touch | Gaps in Care: Chronic Obstructive Pulmonary Disease (COPD) | 6-Month PCE-1 | Closed gap in care | 49 Participants |
| High-Touch | Gaps in Care: Chronic Obstructive Pulmonary Disease (COPD) | 12-Month PCE-1 | Did not close gap in care | 2 Participants |
| High-Touch | Gaps in Care: Chronic Obstructive Pulmonary Disease (COPD) | 12-Month PCE-1 | Closed gap in care | 33 Participants |
| High-Touch | Gaps in Care: Chronic Obstructive Pulmonary Disease (COPD) | Baseline PCE-2 | Did not close gap in care | 8 Participants |
| High-Touch | Gaps in Care: Chronic Obstructive Pulmonary Disease (COPD) | Baseline PCE-2 | Closed gap in care | 16 Participants |
| High-Touch | Gaps in Care: Chronic Obstructive Pulmonary Disease (COPD) | 6-Month PCE-2 | Did not close gap in care | 7 Participants |
| High-Touch | Gaps in Care: Chronic Obstructive Pulmonary Disease (COPD) | 6-Month PCE-2 | Closed gap in care | 50 Participants |
| High-Touch | Gaps in Care: Chronic Obstructive Pulmonary Disease (COPD) | 12-Month PCE-2 | Did not close gap in care | 5 Participants |
| High-Touch | Gaps in Care: Chronic Obstructive Pulmonary Disease (COPD) | 12-Month PCE-2 | Closed gap in care | 30 Participants |
| High-Tech | Gaps in Care: Chronic Obstructive Pulmonary Disease (COPD) | 12-Month PCE-2 | Closed gap in care | 27 Participants |
| High-Tech | Gaps in Care: Chronic Obstructive Pulmonary Disease (COPD) | Baseline PCE-1 | Did not close gap in care | 3 Participants |
| High-Tech | Gaps in Care: Chronic Obstructive Pulmonary Disease (COPD) | Baseline PCE-2 | Did not close gap in care | 4 Participants |
| High-Tech | Gaps in Care: Chronic Obstructive Pulmonary Disease (COPD) | 6-Month PCE-2 | Did not close gap in care | 8 Participants |
| High-Tech | Gaps in Care: Chronic Obstructive Pulmonary Disease (COPD) | Baseline PCE-1 | Closed gap in care | 25 Participants |
| High-Tech | Gaps in Care: Chronic Obstructive Pulmonary Disease (COPD) | 12-Month PCE-1 | Closed gap in care | 33 Participants |
| High-Tech | Gaps in Care: Chronic Obstructive Pulmonary Disease (COPD) | 12-Month PCE-2 | Did not close gap in care | 7 Participants |
| High-Tech | Gaps in Care: Chronic Obstructive Pulmonary Disease (COPD) | 6-Month PCE-1 | Did not close gap in care | 2 Participants |
| High-Tech | Gaps in Care: Chronic Obstructive Pulmonary Disease (COPD) | Baseline PCE-2 | Closed gap in care | 24 Participants |
| High-Tech | Gaps in Care: Chronic Obstructive Pulmonary Disease (COPD) | 12-Month PCE-1 | Did not close gap in care | 1 Participants |
| High-Tech | Gaps in Care: Chronic Obstructive Pulmonary Disease (COPD) | 6-Month PCE-1 | Closed gap in care | 52 Participants |
| High-Tech | Gaps in Care: Chronic Obstructive Pulmonary Disease (COPD) | 6-Month PCE-2 | Closed gap in care | 46 Participants |
| Optimal Discharge Planning | Gaps in Care: Chronic Obstructive Pulmonary Disease (COPD) | 6-Month PCE-1 | Closed gap in care | 22 Participants |
| Optimal Discharge Planning | Gaps in Care: Chronic Obstructive Pulmonary Disease (COPD) | 12-Month PCE-1 | Did not close gap in care | 3 Participants |
| Optimal Discharge Planning | Gaps in Care: Chronic Obstructive Pulmonary Disease (COPD) | 6-Month PCE-2 | Closed gap in care | 20 Participants |
| Optimal Discharge Planning | Gaps in Care: Chronic Obstructive Pulmonary Disease (COPD) | 12-Month PCE-1 | Closed gap in care | 11 Participants |
| Optimal Discharge Planning | Gaps in Care: Chronic Obstructive Pulmonary Disease (COPD) | Baseline PCE-2 | Did not close gap in care | 3 Participants |
| Optimal Discharge Planning | Gaps in Care: Chronic Obstructive Pulmonary Disease (COPD) | Baseline PCE-2 | Closed gap in care | 12 Participants |
| Optimal Discharge Planning | Gaps in Care: Chronic Obstructive Pulmonary Disease (COPD) | 12-Month PCE-2 | Did not close gap in care | 1 Participants |
| Optimal Discharge Planning | Gaps in Care: Chronic Obstructive Pulmonary Disease (COPD) | Baseline PCE-1 | Did not close gap in care | 1 Participants |
| Optimal Discharge Planning | Gaps in Care: Chronic Obstructive Pulmonary Disease (COPD) | Baseline PCE-1 | Closed gap in care | 14 Participants |
| Optimal Discharge Planning | Gaps in Care: Chronic Obstructive Pulmonary Disease (COPD) | 6-Month PCE-2 | Did not close gap in care | 3 Participants |
| Optimal Discharge Planning | Gaps in Care: Chronic Obstructive Pulmonary Disease (COPD) | 6-Month PCE-1 | Did not close gap in care | 1 Participants |
| Optimal Discharge Planning | Gaps in Care: Chronic Obstructive Pulmonary Disease (COPD) | 12-Month PCE-2 | Closed gap in care | 13 Participants |
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.
Population: Only a small portion of the total sample was eligible for CHF Gaps in Care analyses.
| Arm | Measure | Group | Value (MEAN) | Dispersion |
|---|---|---|---|---|
| High-Touch | Gaps in Care: Congestive Heart Failure (CHF) | 6-Month | 0.02 Number of readmissions within 30 days | Standard Deviation 0.1 |
| High-Touch | Gaps in Care: Congestive Heart Failure (CHF) | Baseline | 0.04 Number of readmissions within 30 days | Standard Deviation 0.17 |
| High-Touch | Gaps in Care: Congestive Heart Failure (CHF) | 12-Month | 0.04 Number of readmissions within 30 days | Standard Deviation 0.13 |
| High-Tech | Gaps in Care: Congestive Heart Failure (CHF) | 6-Month | 0.04 Number of readmissions within 30 days | Standard Deviation 0.15 |
| High-Tech | Gaps in Care: Congestive Heart Failure (CHF) | Baseline | 0.04 Number of readmissions within 30 days | Standard Deviation 0.17 |
| High-Tech | Gaps in Care: Congestive Heart Failure (CHF) | 12-Month | 0.04 Number of readmissions within 30 days | Standard Deviation 0.13 |
| Optimal Discharge Planning | Gaps in Care: Congestive Heart Failure (CHF) | Baseline | 0.02 Number of readmissions within 30 days | Standard Deviation 0.11 |
| Optimal Discharge Planning | Gaps in Care: Congestive Heart Failure (CHF) | 12-Month | 0.04 Number of readmissions within 30 days | Standard Deviation 0.12 |
| Optimal Discharge Planning | Gaps in Care: Congestive Heart Failure (CHF) | 6-Month | 0.03 Number of readmissions within 30 days | Standard Deviation 0.12 |
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
Population: Only a very small portion of the total sample was eligible for Depression Gaps in Care analyses.
| Arm | Measure | Group | Category | Value (COUNT_OF_PARTICIPANTS) |
|---|---|---|---|---|
| High-Touch | Gaps in Care: Depression | Baseline AMM-1 | Did not close gap in care | 24 Participants |
| High-Touch | Gaps in Care: Depression | Baseline AMM-1 | Closed gap in care | 29 Participants |
| High-Touch | Gaps in Care: Depression | 6-Month AMM-1 | Did not close gap in care | 20 Participants |
| High-Touch | Gaps in Care: Depression | 6-Month AMM-1 | Closed gap in care | 35 Participants |
| High-Touch | Gaps in Care: Depression | 12-Month AMM-1 | Did not close gap in care | 22 Participants |
| High-Touch | Gaps in Care: Depression | 12-Month AMM-1 | Closed gap in care | 34 Participants |
| High-Touch | Gaps in Care: Depression | Baseline AMM-2 | Did not close gap in care | 28 Participants |
| High-Touch | Gaps in Care: Depression | Baseline AMM-2 | Closed gap in care | 25 Participants |
| High-Touch | Gaps in Care: Depression | 6-Month AMM-2 | Did not close gap in care | 26 Participants |
| High-Touch | Gaps in Care: Depression | 6-Month AMM-2 | Closed gap in care | 29 Participants |
| High-Touch | Gaps in Care: Depression | 12-Month AMM-2 | Did not close gap in care | 32 Participants |
| High-Touch | Gaps in Care: Depression | 12-Month AMM-2 | Closed gap in care | 24 Participants |
| High-Tech | Gaps in Care: Depression | 12-Month AMM-2 | Closed gap in care | 28 Participants |
| High-Tech | Gaps in Care: Depression | Baseline AMM-1 | Did not close gap in care | 12 Participants |
| High-Tech | Gaps in Care: Depression | Baseline AMM-2 | Did not close gap in care | 19 Participants |
| High-Tech | Gaps in Care: Depression | 6-Month AMM-2 | Did not close gap in care | 24 Participants |
| High-Tech | Gaps in Care: Depression | Baseline AMM-1 | Closed gap in care | 35 Participants |
| High-Tech | Gaps in Care: Depression | 12-Month AMM-1 | Closed gap in care | 37 Participants |
| High-Tech | Gaps in Care: Depression | 12-Month AMM-2 | Did not close gap in care | 31 Participants |
| High-Tech | Gaps in Care: Depression | 6-Month AMM-1 | Did not close gap in care | 14 Participants |
| High-Tech | Gaps in Care: Depression | Baseline AMM-2 | Closed gap in care | 28 Participants |
| High-Tech | Gaps in Care: Depression | 12-Month AMM-1 | Did not close gap in care | 22 Participants |
| High-Tech | Gaps in Care: Depression | 6-Month AMM-1 | Closed gap in care | 30 Participants |
| High-Tech | Gaps in Care: Depression | 6-Month AMM-2 | Closed gap in care | 20 Participants |
| Optimal Discharge Planning | Gaps in Care: Depression | 6-Month AMM-1 | Closed gap in care | 19 Participants |
| Optimal Discharge Planning | Gaps in Care: Depression | 12-Month AMM-1 | Did not close gap in care | 9 Participants |
| Optimal Discharge Planning | Gaps in Care: Depression | 6-Month AMM-2 | Closed gap in care | 16 Participants |
| Optimal Discharge Planning | Gaps in Care: Depression | 12-Month AMM-1 | Closed gap in care | 25 Participants |
| Optimal Discharge Planning | Gaps in Care: Depression | Baseline AMM-2 | Did not close gap in care | 16 Participants |
| Optimal Discharge Planning | Gaps in Care: Depression | Baseline AMM-2 | Closed gap in care | 7 Participants |
| Optimal Discharge Planning | Gaps in Care: Depression | 12-Month AMM-2 | Did not close gap in care | 14 Participants |
| Optimal Discharge Planning | Gaps in Care: Depression | Baseline AMM-1 | Did not close gap in care | 10 Participants |
| Optimal Discharge Planning | Gaps in Care: Depression | Baseline AMM-1 | Closed gap in care | 13 Participants |
| Optimal Discharge Planning | Gaps in Care: Depression | 6-Month AMM-2 | Did not close gap in care | 9 Participants |
| Optimal Discharge Planning | Gaps in Care: Depression | 6-Month AMM-1 | Did not close gap in care | 6 Participants |
| Optimal Discharge Planning | Gaps in Care: Depression | 12-Month AMM-2 | Closed gap in care | 20 Participants |
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
Population: Only a very small portion of the total sample was eligible for Diabetes Gaps in Care analyses.
| Arm | Measure | Group | Category | Value (COUNT_OF_PARTICIPANTS) |
|---|---|---|---|---|
| High-Touch | Gaps in Care: Diabetes | Baseline SPD-1 | Did not close gap in care | 25 Participants |
| High-Touch | Gaps in Care: Diabetes | Baseline SPD-1 | Closed gap in care | 80 Participants |
| High-Touch | Gaps in Care: Diabetes | 6-Month SPD-1 | Did not close gap in care | 28 Participants |
| High-Touch | Gaps in Care: Diabetes | 6-Month SPD-1 | Closed gap in care | 79 Participants |
| High-Touch | Gaps in Care: Diabetes | 12-Month SPD-1 | Did not close gap in care | 20 Participants |
| High-Touch | Gaps in Care: Diabetes | 12-Month SPD-1 | Closed gap in care | 68 Participants |
| High-Touch | Gaps in Care: Diabetes | Baseline SPD-2 | Did not close gap in care | 19 Participants |
| High-Touch | Gaps in Care: Diabetes | Baseline SPD-2 | Closed gap in care | 61 Participants |
| High-Touch | Gaps in Care: Diabetes | 6-Month SPD-2 | Did not close gap in care | 18 Participants |
| High-Touch | Gaps in Care: Diabetes | 6-Month SPD-2 | Closed gap in care | 61 Participants |
| High-Touch | Gaps in Care: Diabetes | 12-Month SPD-2 | Did not close gap in care | 14 Participants |
| High-Touch | Gaps in Care: Diabetes | 12-Month SPD-2 | Closed gap in care | 54 Participants |
| High-Tech | Gaps in Care: Diabetes | 12-Month SPD-2 | Closed gap in care | 43 Participants |
| High-Tech | Gaps in Care: Diabetes | Baseline SPD-1 | Did not close gap in care | 24 Participants |
| High-Tech | Gaps in Care: Diabetes | Baseline SPD-2 | Did not close gap in care | 31 Participants |
| High-Tech | Gaps in Care: Diabetes | 6-Month SPD-2 | Did not close gap in care | 27 Participants |
| High-Tech | Gaps in Care: Diabetes | Baseline SPD-1 | Closed gap in care | 95 Participants |
| High-Tech | Gaps in Care: Diabetes | 12-Month SPD-1 | Closed gap in care | 69 Participants |
| High-Tech | Gaps in Care: Diabetes | 12-Month SPD-2 | Did not close gap in care | 26 Participants |
| High-Tech | Gaps in Care: Diabetes | 6-Month SPD-1 | Did not close gap in care | 25 Participants |
| High-Tech | Gaps in Care: Diabetes | Baseline SPD-2 | Closed gap in care | 64 Participants |
| High-Tech | Gaps in Care: Diabetes | 12-Month SPD-1 | Did not close gap in care | 19 Participants |
| High-Tech | Gaps in Care: Diabetes | 6-Month SPD-1 | Closed gap in care | 79 Participants |
| High-Tech | Gaps in Care: Diabetes | 6-Month SPD-2 | Closed gap in care | 52 Participants |
| Optimal Discharge Planning | Gaps in Care: Diabetes | 6-Month SPD-1 | Closed gap in care | 33 Participants |
| Optimal Discharge Planning | Gaps in Care: Diabetes | 12-Month SPD-1 | Did not close gap in care | 9 Participants |
| Optimal Discharge Planning | Gaps in Care: Diabetes | 6-Month SPD-2 | Closed gap in care | 22 Participants |
| Optimal Discharge Planning | Gaps in Care: Diabetes | 12-Month SPD-1 | Closed gap in care | 25 Participants |
| Optimal Discharge Planning | Gaps in Care: Diabetes | Baseline SPD-2 | Did not close gap in care | 18 Participants |
| Optimal Discharge Planning | Gaps in Care: Diabetes | Baseline SPD-2 | Closed gap in care | 26 Participants |
| Optimal Discharge Planning | Gaps in Care: Diabetes | 12-Month SPD-2 | Did not close gap in care | 6 Participants |
| Optimal Discharge Planning | Gaps in Care: Diabetes | Baseline SPD-1 | Did not close gap in care | 15 Participants |
| Optimal Discharge Planning | Gaps in Care: Diabetes | Baseline SPD-1 | Closed gap in care | 44 Participants |
| Optimal Discharge Planning | Gaps in Care: Diabetes | 6-Month SPD-2 | Did not close gap in care | 11 Participants |
| Optimal Discharge Planning | Gaps in Care: Diabetes | 6-Month SPD-1 | Did not close gap in care | 12 Participants |
| Optimal Discharge Planning | Gaps in Care: Diabetes | 12-Month SPD-2 | Closed gap in care | 19 Participants |
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.
Population: For each timepoint, participants who were eligible for Medicaid/Medicaid-Medicare with available claims data during at least 9 months (non-continuous) of the past 12 months.
| Arm | Measure | Group | Category | Value (COUNT_OF_PARTICIPANTS) |
|---|---|---|---|---|
| High-Touch | Inpatient Readmissions Over 12-Months | 6-Month | No inpatient admission | 412 Participants |
| High-Touch | Inpatient Readmissions Over 12-Months | 12-Month | Missing Data | 30 Participants |
| High-Touch | Inpatient Readmissions Over 12-Months | 6-Month | Missing Data | 8 Participants |
| High-Touch | Inpatient Readmissions Over 12-Months | 6-Month | One or more inpatient admissions | 139 Participants |
| High-Touch | Inpatient Readmissions Over 12-Months | Baseline | No inpatient admission | 342 Participants |
| High-Touch | Inpatient Readmissions Over 12-Months | 12-Month | One or more inpatient admissions | 192 Participants |
| High-Touch | Inpatient Readmissions Over 12-Months | Baseline | Missing Data | 44 Participants |
| High-Touch | Inpatient Readmissions Over 12-Months | Baseline | One or more inpatient admissions | 173 Participants |
| High-Touch | Inpatient Readmissions Over 12-Months | 12-Month | No inpatient admission | 337 Participants |
| High-Tech | Inpatient Readmissions Over 12-Months | 6-Month | One or more inpatient admissions | 135 Participants |
| High-Tech | Inpatient Readmissions Over 12-Months | Baseline | No inpatient admission | 344 Participants |
| High-Tech | Inpatient Readmissions Over 12-Months | Baseline | One or more inpatient admissions | 165 Participants |
| High-Tech | Inpatient Readmissions Over 12-Months | Baseline | Missing Data | 36 Participants |
| High-Tech | Inpatient Readmissions Over 12-Months | 6-Month | No inpatient admission | 400 Participants |
| High-Tech | Inpatient Readmissions Over 12-Months | 6-Month | Missing Data | 10 Participants |
| High-Tech | Inpatient Readmissions Over 12-Months | 12-Month | No inpatient admission | 332 Participants |
| High-Tech | Inpatient Readmissions Over 12-Months | 12-Month | One or more inpatient admissions | 188 Participants |
| High-Tech | Inpatient Readmissions Over 12-Months | 12-Month | Missing Data | 25 Participants |
| Optimal Discharge Planning | Inpatient Readmissions Over 12-Months | Baseline | Missing Data | 29 Participants |
| Optimal Discharge Planning | Inpatient Readmissions Over 12-Months | Baseline | No inpatient admission | 170 Participants |
| Optimal Discharge Planning | Inpatient Readmissions Over 12-Months | 12-Month | No inpatient admission | 170 Participants |
| Optimal Discharge Planning | Inpatient Readmissions Over 12-Months | Baseline | One or more inpatient admissions | 84 Participants |
| Optimal Discharge Planning | Inpatient Readmissions Over 12-Months | 12-Month | Missing Data | 23 Participants |
| Optimal Discharge Planning | Inpatient Readmissions Over 12-Months | 6-Month | One or more inpatient admissions | 73 Participants |
| Optimal Discharge Planning | Inpatient Readmissions Over 12-Months | 6-Month | No inpatient admission | 201 Participants |
| Optimal Discharge Planning | Inpatient Readmissions Over 12-Months | 12-Month | One or more inpatient admissions | 90 Participants |
| Optimal Discharge Planning | Inpatient Readmissions Over 12-Months | 6-Month | Missing Data | 9 Participants |
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.
Population: For each timepoint, participants who were eligible for Medicaid/Medicaid-Medicare with available claims data during at least 9 months (non-continuous) of the past 12 months.
| Arm | Measure | Group | Category | Value (COUNT_OF_PARTICIPANTS) |
|---|---|---|---|---|
| High-Touch | Mental Health Care Visits | 6-Months | No mental health care visits | 527 Participants |
| High-Touch | Mental Health Care Visits | 12-Months | Missing Data | 30 Participants |
| High-Touch | Mental Health Care Visits | 6-Months | Missing Data | 8 Participants |
| High-Touch | Mental Health Care Visits | 6-Months | At least one mental health care visit | 24 Participants |
| High-Touch | Mental Health Care Visits | Baseline | No mental health care visits | 479 Participants |
| High-Touch | Mental Health Care Visits | 12-Months | At least one mental health care visit | 37 Participants |
| High-Touch | Mental Health Care Visits | Baseline | Missing Data | 44 Participants |
| High-Touch | Mental Health Care Visits | Baseline | At least one mental health care visit | 36 Participants |
| High-Touch | Mental Health Care Visits | 12-Months | No mental health care visits | 492 Participants |
| High-Tech | Mental Health Care Visits | 6-Months | At least one mental health care visit | 29 Participants |
| High-Tech | Mental Health Care Visits | Baseline | No mental health care visits | 476 Participants |
| High-Tech | Mental Health Care Visits | Baseline | At least one mental health care visit | 33 Participants |
| High-Tech | Mental Health Care Visits | Baseline | Missing Data | 36 Participants |
| High-Tech | Mental Health Care Visits | 6-Months | No mental health care visits | 506 Participants |
| High-Tech | Mental Health Care Visits | 6-Months | Missing Data | 10 Participants |
| High-Tech | Mental Health Care Visits | 12-Months | No mental health care visits | 484 Participants |
| High-Tech | Mental Health Care Visits | 12-Months | At least one mental health care visit | 36 Participants |
| High-Tech | Mental Health Care Visits | 12-Months | Missing Data | 25 Participants |
| Optimal Discharge Planning | Mental Health Care Visits | Baseline | Missing Data | 29 Participants |
| Optimal Discharge Planning | Mental Health Care Visits | Baseline | No mental health care visits | 237 Participants |
| Optimal Discharge Planning | Mental Health Care Visits | 12-Months | No mental health care visits | 238 Participants |
| Optimal Discharge Planning | Mental Health Care Visits | Baseline | At least one mental health care visit | 17 Participants |
| Optimal Discharge Planning | Mental Health Care Visits | 12-Months | Missing Data | 23 Participants |
| Optimal Discharge Planning | Mental Health Care Visits | 6-Months | At least one mental health care visit | 18 Participants |
| Optimal Discharge Planning | Mental Health Care Visits | 6-Months | No mental health care visits | 256 Participants |
| Optimal Discharge Planning | Mental Health Care Visits | 12-Months | At least one mental health care visit | 22 Participants |
| Optimal Discharge Planning | Mental Health Care Visits | 6-Months | Missing Data | 9 Participants |
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.
Population: Includes all individuals who completed the measure at least one timepoint.
| Arm | Measure | Group | Value (MEAN) | Dispersion |
|---|---|---|---|---|
| High-Touch | Quality of Life | 12-Month | 0.54 score on a scale | Standard Deviation 0.2 |
| High-Touch | Quality of Life | 6-Month | 0.52 score on a scale | Standard Deviation 0.2 |
| High-Touch | Quality of Life | Baseline | 0.50 score on a scale | Standard Deviation 0.19 |
| High-Touch | Quality of Life | 3-Month | 0.52 score on a scale | Standard Deviation 0.19 |
| High-Tech | Quality of Life | Baseline | 0.51 score on a scale | Standard Deviation 0.19 |
| High-Tech | Quality of Life | 3-Month | 0.52 score on a scale | Standard Deviation 0.19 |
| High-Tech | Quality of Life | 6-Month | 0.52 score on a scale | Standard Deviation 0.2 |
| High-Tech | Quality of Life | 12-Month | 0.52 score on a scale | Standard Deviation 0.19 |
| Optimal Discharge Planning | Quality of Life | 6-Month | 0.52 score on a scale | Standard Deviation 0.21 |
| Optimal Discharge Planning | Quality of Life | Baseline | 0.51 score on a scale | Standard Deviation 0.21 |
| Optimal Discharge Planning | Quality of Life | 3-Month | 0.52 score on a scale | Standard Deviation 0.2 |
| Optimal Discharge Planning | Quality of Life | 12-Month | 0.53 score on a scale | Standard Deviation 0.19 |