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Substance dependence (SD) is a chronic disease that requires specialty drug and alcohol treatment, primary care (PC), and management of related problems. Although patients with SD may be linked with specialty care and PC, their health care often remains episodic and fragmented, rather than longitudinal, comprehensive, integrated, and coordinated. As a result, adults with SD often enter addiction treatment later and require acute medical care, rather than entering the system earlier when interventions of lower intensity but longer duration might prevent catastrophes. Chronic disease management (CDM) is a collaborative, longitudinal approach to treatment of certain chronic medical illnesses proven to be more effective than routine care. CDM addresses individual patient and health systems barriers to receipt of needed treatment. However, the effectiveness of CDM for SD has not been tested. The objective of this Addiction Health Evaluation and Disease management (AHEAD) study, was to test the effectiveness of CDM for SD in PC.

Subject identification and recruitment occurred primarily at a local detoxification center, as well as by self and physician referral from the Boston Medical Center primary and ambulatory care clinics, emergency department, urgent care center, inpatient settings, and the community. The study enrolled 320 adults with drug dependence and 320 adults with alcohol dependence who were not in SD treatment, and randomized them to a SD CDM program (the AHEAD Clinic) integrated into a real-world PC clinic or to referral to standard PC. All subjects were assessed regarding SD diagnosis, substance use and problems, readiness to change, health-related quality of life, and medical and drug treatment utilization. Subjects were evaluated 3, 6, and 12 months later, and health services utilization data were collected for 2 years from a statewide database. Additionally, in order to better understand and explain the implementation and fidelity of the AHEAD Clinic, the primary care providers (PCPs) of AHEAD Clinic patients were surveyed. Each PCP was presented with a letter from the Principal Investigator explaining the purpose of the survey, the reason why s/he was being asked to complete the survey, compensation for completing the survey, and details about confidentiality and anonymity. The survey itself consisted of questions asking providers about their satisfaction and their attitudes towards caring for patients with alcohol and drug problems, their knowledge of services that the AHEAD Clinic provides, and their experience working with the AHEAD Clinic.

Primary outcomes were illicit drug use, alcohol use, substance-related problems, emergency department visits, and hospitalizations. The proposal's hypothesis was that compared with standard care, a health services delivery intervention (CDM for SD integrated in PC) would decrease alcohol and illicit drug use and related problems, and improve health care utilization patterns. Improved outcomes using the AHEAD approach would support the adoption of a health services delivery strategy, CDM, to better care for patients with SD.

• Dataset 1: 844 variables; 563 cases
• Dataset 2: 607 variables; 500 cases
• Dataset 3: 607 variables; 487 cases
• Dataset 4: 713 variables; 532 cases
• Dataset 5: 80 variables; 549 cases
• Dataset 6: 59 variables; 1,435 cases
• Dataset 7: 25 variables; 87 cases
• Dataset 8: 25 variables; 87 cases
• Dataset 9: 41 variables; 73 cases
• Dataset 10: 9 variables; 11,018 cases
• Dataset 11: 5 variables; 511 cases

Patient decision aids help people choose between two or more healthcare options based on what is most important to them. Involving users, such as patients and clinicians, in developing decision aids may make them more useful.

User-centered design is a way to get users involved in creating products. Learning from projects that apply user-centered design may suggest ways to involve users more in developing patient decision aids. In this study, the research team reviewed studies about developing decision aids and studies about user-centered design.

Asthma is one of the nation's most common and costly chronic conditions, affecting over 38 million Americans at some time in their lives. Managing asthma requires a long term, multifaceted approach, including patient education, behavior changes, asthma trigger avoidance, pharmacological therapy, and frequent medical follow-up. This study provides asthma data available at the state and local level to direct and evaluate interventions undertaken by asthma control programs located in the state health departments. Improved tracking for asthma is critical for planning and evaluating efforts to reduce the health burden from the disease.

The Behavioral Risk Factor Surveillance System (BRFSS) is a state-based system of health surveys that collects information on health risk behaviors, preventive health practices, and health care access primarily related to chronic disease and injury. For many states, the BRFSS is the only available source of timely, accurate data on health-related behaviors. BRFSS was established in 1984 by the Centers for Disease Control and Prevention (CDC); currently data are collected monthly in all 50 states, the District of Columbia, Puerto Rico, the United States Virgin Islands, and Guam. More than 350,000 adults are interviewed each year, making the BRFSS the largest telephone health survey in the world. States use BRFSS data to identify emerging health problems, establish and track health objectives, and develop and evaluate public health policies and programs. The BRFSS is a cross-sectional telephone survey conducted by state health departments with technical and methodological assistance provided by CDC. States conduct monthly telephone surveillance using a standardized questionnaire to determine the distribution of risk behaviors and health practices among adults. Responses are forwarded to CDC, where the monthly data are aggregated for each state, returned with standard tabulations, and published at the year's end by each state. The BRFSS questionnaire was developed jointly by CDC's Behavioral Surveillance Branch (BSB) and the states. Data derived from the questionnaire provide health departments, public health officials, and policymakers with necessary behavioral information. When combined with mortality and morbidity statistics, these data enable public health officials to establish policies and priorities and to initiate and assess health promotion strategies. Demographic variables include race, age, sex, education level, marital status, employment status, and income level.

This qualitative study was conducted in two United States health care systems. The research team conducted semi-structured interviews with medical assistants, physicians, and interpreters with experience collecting family history for Spanish-speaking patients and examined barriers and facilitators to family history collection.

This study comprises the second round of the physician survey component of the Community Tracking Study (CTS) sponsored by the Robert Wood Johnson Foundation. The CTS is a national study designed to track changes in the American health care system and the effects of the changes on care delivery and on individuals. Central to the design of the CTS is its community focus. Sixty sites (51 metropolitan areas and 9 nonmetropolitan areas) were randomly selected to form the core of the CTS and to be representative of the nation as a whole. As in the first round of the physician survey (COMMUNITY TRACKING STUDY PHYSICIAN SURVEY, 1996-1997: [UNITED STATES] (ICPSR 2597)), the second round was administered to physicians in the 60 CTS sites and to a supplemental national sample of physicians. The survey instrument collected information on physician supply and specialty distribution, practice arrangements and physician ownership of practices, physician time allocation, sources of practice revenue, level and determinants of physician compensation, provision of charity care, career satisfaction, physicians' perceptions of their ability to deliver care, views on care management strategies, and various other aspects of physicians' practice of medicine. In addition, primary care physicians (PCPs) were asked to recommend courses of action in response to some vignettes of clinical presentations for which there was no prescribed method of treatment.

Dataset 3, the Site and County Crosswalk Data File, identifies the counties that constitute each CTS site.

Dataset 4, the Physician Survey Summary File, contains site-level estimates and standard errors of the estimates for selected physician characteristics, e.g., the percentage of physicians who were foreign medical school graduates, the mean age of physicians, and the mean percentage of patient care practice revenue from Medicaid.

For people with serious chronic conditions, healthcare that defaults to all available treatments without considering patient preferences risks harms that may exceed benefits. Advance care planning (ACP) has the potential to align healthcare with what is important to patients and maximize quality of life. While primary care is where most people receive most of their care, engaging patients in ACP is not routine in primary care given competing demands and limited resources. Primary care clinicians, patients, and families agree that it is preferred to make plans before there is a medical crisis. The research team's goal was to make ACP routine in primary care and to "move it upstream" so that it included improving the quality of the last years of life as well as respecting wishes for end of life care.

This study included a comparative effectiveness trial of team-based versus individual clinician-focused ACP in primary care practices. The research team adapted Ariadne Labs' Serious Illness Care Program (SICP) and aimed to determine if a team approach produces better patient outcomes and explore factors influencing implementation of ACP across practices.

Seven practice-based research networks (PBRNs) in the United States and Canada randomized their primary care practices to team-based or individual clinician-focused versions of SICP. Team members and clinicians completed training, and implementation was supported through practice facilitation. Consented patient participants completed a baseline survey after initial conversations and follow-up surveys at 6 and 12 months later. Forty practices (21 team, 19 clinician) completed training and referred patients to the study. Half of the practices were rural, 80 percent were family medicine, and 33 percent were medical residency training sites. 535 healthcare staff completed training. Both arms trained primary care providers; the team arm also trained nurses, medical assistants, and other roles. 1,321 patients and care partners were referred; and 917 consented and were enrolled (455 from team practices, 462 from clinician). Data from 802 patients were included in the primary analyses. Qualitative implementation data was collected during practice facilitation and from practice interviews.

This collection includes quantitative data collected from primary care practices (DS1) and team members and clinicians (DS2) from study sites located in the United States.

The Comprehensive Post-Acute Stroke Services (COMPASS) Study is a pragmatic cluster-randomized clinical trial that evaluated the real-world effectiveness of the COMPASS transitional care (COMPASS-TC) model compared to usual care among adult stroke and transient ischemic attack (TIA) patients discharged home between 2016 and 2018. In Phase 1, 40 North Carolina hospital units were randomized 1:1 to the COMPASS-TC intervention or usual care, stratified by stroke patient volume and stroke center certification. In Phase 2, hospitals randomized to usual care crossed over to implement COMPASS-TC, and hospitals randomized to the intervention sustained COMPASS-TC. The intervention was patient-centered and assessed social and functional determinates of health to inform individualized care plans for secondary prevention, recovery, and referrals to services and community-based resources. COMPASS-TC was consistent with Centers for Medicare and Medicaid Services (CMS) TC management reimbursement requirements.

The primary outcome was functional status (Stroke Impact Scale-16; SIS-16) at 90 days; secondary outcomes were mortality, disability, medication adherence, depression, cognition, self-rated health, fatigue, care satisfaction, home blood pressure monitoring, falls, and caregiver strain. Telephone interviewers, blinded to treatment assignment, assessed these outcomes at 90 days.

The purpose of this study was to expand the research capacity for comparative effectiveness evaluations of patients with multiple chronic conditions. Researchers administered a generic Quality of Life (QOL) instrument, physical symptom assessment, patient health questionnaire, and a tobacco screen through audio computer-assisted self-interviews (ACASI) and linked the responses to their electronic medical records (EMR) data. Researchers also calculated two co-morbidity indices (Chronic Disease Score and Charlson Co-morbidity Index).

This interventional pilot study was conducted in a primary care clinic to determine if patients would become more engaged in their own health and ask more questions of their physicians if they were provided data about patients similar to themselves. The study was conducted with 150 patients with a diagnosis of hypertension who had scheduled appointments with one of three participating physicians in the clinic. When they arrived at the clinic for their appointment, the patients were shown de-identified clinical data about similar patients with hypertension on a computer screen, given a printout of this information, and then proceeded to visit their physician. After the physician visit the patients completed a short survey. Their answers to the survey questions are recorded in the data file together with additional information about them, such as age, gender, race, smoking status and comorbidities.

The three participating physicians completed a short survey at the end of the study. The results of that survey are summarized in a table provided with the technical documentation.

For this survey, respondents from three counties in the Detroit, Michigan, area were queried about their health, satisfaction with their health care, end of life decisions, policies about life and death decisions, and experiences with life and death decisions. The first set of questions asked respondents to rate their own health and to indicate whether they had seen a health care professional in the past five years as well as what type of health professional they had seen. They were also asked whether or not they trust the health care provider's judgment on medical decisions and whether they felt that a doctor or family members would follow the respondent's instructions for life sustaining procedures. The survey also explored how satisfied respondents were with the amount of time they spent with their doctor and the doctor's response to questions as well as their honesty and concern for their patient. Additional questions asked respondents how concerned HMO's are with costs and patient health and what their opinions were on how much money is spent on medical technology and care for terminally ill patients. Another set of questions sought respondent's opinions on terminating a patient's life support in a variety of different situations, including the treatment of critically ill infants. The survey also asked whether respondents or their family had ever experienced an end-of-life decision, whether they have discussed end-of-life decisions, and what types of methods they would consider. Respondents were also asked about their attitudes on the death penalty, abortion in certain situations, physician assisted suicide and the 1998 proposal to legalize physician assisted suicide. Background information includes marital status, employment, political orientation, and income.

Community-engaged research is an umbrella term for forms of research that have community and stakeholder engagement as a core principle, for example, patient-centered outcomes research (PCOR), participatory action research, and community-based participatory research. However, the implementation and category of community engagement can vary across a spectrum from minimal engagement to fully collaborative engagement. A major methodological gap is the assessment of stakeholder engagement from a stakeholder perspective. Evaluation of the impact of stakeholder engagement on research development, implementation, and outcomes requires the development and validation of tools that assess engagement. This study's objective was to develop and validate comprehensive and condensed versions of a survey instrument that will be completed by stakeholders and used to assess engagement in research studies from a stakeholder perspective.

Patient-reported outcome measures, or PROMs, ask patients how they feel and what activities they can do in daily life. Patients receiving cancer treatment, such as chemotherapy, often have side effects. PROMs can help cancer centers know if patients are getting high-quality care that helps manage their side effects.

In this study, the research team wanted to

• Learn from patients and clinicians, like doctors and nurses, what side effects are important to track during chemotherapy
• Create PROMs that can measure important side effects of chemotherapy

The research team also wanted to test the PROMs to see

• If patients find them easy to complete
• If the PROMs can detect differences in how well cancer centers control patients' treatment side effects

The way doctors communicate with patients during office visits can affect the quality of care. Studying conversations between doctors and patients can help doctors improve their communication skills.

To study conversations, researchers rely on written records, or transcripts, of office visits. They read the transcripts and give each conversation topic a label. For example, topics may include smoking or pain. But labeling topics in this way may take a lot of time.

In this project, the research team created and tested a new method to make this work easier using natural language processing, or NLP. With NLP, computer programs interpret written language. NLP methods use a process called machine learning, where computer programs use data to learn how to perform different tasks with little or no human input.

Purpose: Develop an easy-to-use data product to facilitate comparative effectiveness research involving complex patients.

Scope: Claims data can be difficult to use, requiring experience to most appropriately aggregate to the patient level and to create meaningful variables such as treatments, covariates, and endpoints. Easy to use data products will accelerate meaningful comparative effectiveness research (CER).

Methods: This project used data from the Medicare Chronic Condition Data Warehouse for patients hospitalized with acute myocardial infarction (AMI) or stroke in 2007 with two-year follow-up and one-year pre-admission baseline. The project joined over 100 raw data files per condition to create research-ready person- and service-level analytic files, code templates, and macros while at the same time adding uniformity in measures of comorbid conditions and other covariates. The data product was tested in a project on statin effectiveness in older patients with multiple comorbidities.

Results: A programmer/analyst with no administrative claims data experience was able to use the data product to create an analytic dataset with minimal support aside from the documentation provided. Analytic dataset creation used the conditions, procedures, and timeline macros provided. The data structure created for AMI adapted successfully for stroke. Complexity increased and statin treatment decreased with age. The two-year survival benefit of statins post-AMI increased with age.

Conclusion: Claims data can be made more user-friendly for CER research on complex conditions. The data product should be expanded by refreshing the cohort and increasing follow-up. Action is warranted to increase the rate of statin use among the oldest patients.

Data Access: These data are not available from ICPSR. The data cannot be made publicly available. Data are stored on University of Iowa College of Public Health secure servers, and may be used only for projects covered within the aims of the original research protocol and Centers for Medicare and Medicaid Services (CMS)-approved data use agreement. Data sharing is allowed only for research protocols approved under data re-use requests by the CMS privacy board. The CMS process for data re-use requests is described at Research Data Assistance Center (ResDac). Please note that as of May 2013, the DUA covering this work is set to expire February 1, 2014. Thereafter, per the terms of the DUA, datasets created for this project may not be available.

User guides are available from ICPSR for detailed descriptions of the data products, including a user guide for Acute Myocardial Infarction (AMI) Analytic Files and a user guide for Stroke and Transient Ischemic Attack (TIA) Analytic Files. Data dictionaries are available upon request. Please contact Nick Rudzianski ([email protected] or 319-335-9783) for more information.

Overview

Through electronic data collection and improving the efficiency of existing data processes to allow both more complete and specific identification of chronic illness, the study objectives included:

1. Greatly enhance the scope of existing algorithms to permit comprehensive identification of the 20 chronic conditions key to primary care.
2. Improve the specificity of the existing algorithms to permit more precise automated identification of chronic conditions, limiting the amount of human review required.
3. Revise the algorithms to permit identification of more than one condition in a text string.

The investigators developed advanced SAS text string search algorithms and developed a modified parsing table that included inclusion and exclusion patterns and resultant diagnoses. The automation searches through each input text string for the inclusion pattern that is not equivalent to the exclusion pattern and maps the string to the corresponding resultant diagnosis. This technique allows the search functions to be easily modified to include additional search criteria and scaled to encompass additional conditions.

Data Dictionary

A data dictionary for 24 chronic conditions was developed. The dictionary assigns ICD-9 diagnosis codes to problem list text in electronic health record data. The dictionary contains 78,458 records and exists in two forms, a Microsoft Access database and a SAS 9.2 dataset. The Microsoft Access database contains 24 tables, one for each condition. The SAS 9.2 dataset contains four fields. The 24 chronic conditions for which problem list text data were examined and assigned to ICD-9 codes. Conditions include Alcohol Use Disorder, Asthma and Allergic Rhinitis, Atherosclerosis, Atrial Fibrillation, Cerebrovascular Disease, Chronic Liver Disease, COPD, Chronic Renal Disease, Coronary Disease, Dementia, Depression, Diabetes Mellitus, Epilepsy, GERD, Heart Failure, Hyperlipidemia, Hypertension, Migraine Headache, Obesity, Osteoarthritis, Osteopenia/Osteoporosis, Parkinson's Disease, Peptic Ulcer Disease and Rheumatoid Arthritis.

Data Access

The data dictionary is not available from ICPSR. For use arrangements, please contact Ruth G. Jenkins, PhD ([email protected]) or Steven M. Ornstein, MD ([email protected]) at the Practice Partner Research Network (PPRNet), Medical University of South Carolina.

The Eurobarometer series is a unique cross-national and cross-temporal survey program conducted on behalf of the European Commission. These surveys regularly monitor public opinion in the European Union (EU) member countries and consist of standard modules and special topic modules. The standard modules address attitudes towards European unification, institutions and policies, measurements for general socio-political orientations, as well as respondent and household demographics. The special topic modules address such topics as agriculture, education, natural environment and resources, public health, public safety and crime, and science and technology.

This round of Eurobarometer surveys covered the following special topics: (1) Climate Change, (2) Agriculture, (3) Healthcare, and (4) Physical Activity. Respondents' opinions were collected regarding how serious an issue they considered climate change, who within the EU is responsible for addressing it, and what personal actions they have taken to fight climate change. Respondents were also questioned about the importance of agriculture in the EU, their opinions on agricultural policies such as the Common Agricultural Policy (CAP), the role of farmers in the EU, and the labeling of the place of origin for meat and dairy products. Additional questions were asked regarding patient safety, the quality of health care in the respondent's country compared to other countries, information sources used to assess the quality of hospitals, if the respondent or a family member had a surgical procedure, and whether the respondent or a family member experienced an adverse event when receiving health care. Lastly, respondents were queried about their level of physical activity, including how often and how vigorously they participated in activities, their opinions of exercise, how much time they spend sitting on an average day, any issues that prevent them from being physically active, and whether they volunteer in sporting activities.

Demographic and other background information collected includes age, gender, nationality, marital status, occupation, age when stopped full-time education, household composition, ownership of various goods, difficulties in paying bills, level in society, and Internet use. In addition, country-specific data includes type and size of locality, region of residence, and language of interview (select countries).

During the COVID-19 pandemic, telemedicine emerged as the primary method of providing outpatient care in many regions with shelter-in-place and social distancing policies. This study aimed understand the impact of this rapid and widespread transition from in-person to remote visits on disparities in access to primary care, especially in chronic disease where ongoing communication between providers and patients is essential.

The newly developed or expanded telemedicine programs varied widely, raising questions about the effect of these differences on uptake of telemedicine among different patient populations and on patient-centered outcomes. Leveraging a natural experiment approach, this study examined rapidly changing telemedicine and in-person models of care during and after the COVID-19 crisis to determine whether certain patients could safely choose to continue telemedicine or telemedicine-supplemented care, rather than return to in-person care.

A patient's preference for a treatment may affect how well the treatment works. For example, if patients prefer a specific medicine, they may be more likely to take that medicine.

Traditional randomized clinical trials can't tell how much patient preferences affect how well a treatment works. But a two-stage clinical trial might. In a two-stage trial, researchers assign patients by chance to one of two groups. In the first group, researchers assign patients by chance to get a specific treatment, regardless of their preference. In the second group, patients choose their treatment. In a two-stage trial, researchers can compare health outcomes for patients who choose their treatment with patients who don't. But few methods exist for researchers to design and analyze this type of trial.

In this project, the research team developed new statistical methods for two-stage trials. The team wanted to find out how many patients are needed for two-stage trials to provide accurate results. They also wanted to learn how to measure whether patient preference for a specific treatment affects patients' health outcomes.

To access the software, methods and R package, please visit the preference CRAN webpage and preference GitHub.

This study sought to evaluate the functional independence in children at a Centers for Pediatric Rehabilitation Teleton (CRIT) facility in Guanajuato, Mexico through the use of the WeeFIM Instrument (0-3 Module). The dataset in this collection was generated in May 2013 from electronic health records for secondary analysis of de-identified data. The goal of CRIT, that this research sought to evaluate, was to improve social integration for children with disabilities in Mexico through comprehensive rehabilitation services, including physical therapy, occupational therapy, neurotherapy, speech therapy, physical and rehabilitation medicine, psychology, social integration, and school for parents.

The collection includes one dataset (35 variables, 5,993 cases). Demographic variables included in the collection: Age, gender, and city of residence.

A learning health system, or LHS, is a health system that constantly looks for new ways to improve patient care. At an LHS, doctors and other hospital staff use learning activities to improve care, put what they've learned into practice, and share findings with other hospitals. Activities may include doing studies that compare treatments to see which one works better for which patients.

Governance refers to the way LHSs oversee learning activities. Governance includes people, committees, and policies that regulate learning activities. Including patients as partners in governance helps make sure learning activities address what's important to patients and protect patients' rights and interests. But LHSs don't always include patients in governance.

In this study, the research team wanted to learn how LHSs include patient partners in governance. The team interviewed patients and health system leaders to answer this question.

During care transitions, patients move from one care setting to another, such as from the hospital to home. If not done well, these care transitions can result in health problems for patients and the need for them to return to the hospital.

Healthcare organizations can use patient surveys to measure the success of care transitions. One survey about the quality of care transitions already exists. The survey was created with input from patients but with no input from caregivers and healthcare providers. In addition, the survey doesn't ask about topics that patients may find important, such as caregiver involvement and the time after care transitions.

In this study, the research team created and tested a new survey. To create the survey, the team asked for input from patients, caregivers, and healthcare providers. The team tested whether the survey was

• Valid, or able to correctly capture what it intends to measure
• Reliable, or able to get consistent answers

The BRITE study (Brain Injury Rehabilitation: Improving the Transition Experience) was a six-center, 1:1 randomized controlled pragmatic trial with masked outcome assessment that compared the effectiveness of two established approaches to managing transition from inpatient rehabilitation facility discharge to the next phase of care for individuals with moderate-to-severe traumatic brain injury (TBI). The two established transition methods were (1) a standardized version of existing discharge procedures used at all six sites and (2) a standardized remotely-delivered case management approach that extended beyond the point of discharge, based on the protocol used within the Veteran's Health Administration and enhanced with input from patient and family stakeholders. The sample was stratified by site and discharge location (skilled nursing facility vs. discharge to home/community) based on the relatively lower frequency of discharge to facility (22 percent across all six study sites in 2015) and the expectation of high impact of discharge destination on outcomes. When a caregiver was available for an enrolled patient, they were also approached for consent to be surveyed, with some patients having up to two caregivers enrolled to account for changes in primary caregiver.

The following key outcome domains were assessed: (1) ability of patients to participate in the home and community as independently as possible, (2) health-related quality of life, (3) access to appropriate healthcare and reduced emergent or urgent healthcare, and (4) caregiver outcomes. These outcomes were assessed at 3, 6, 9 and 12 months after discharge from inpatient care. Participants were also given the standard TBI Model Systems follow-up assessment one-year post-injury. Types of medical insurance coverage and satisfaction with healthcare were examined at 6 and 12 months post-discharge.