Innovative methods for parents and clinics to create tools for kids' care (IMPACCT Kids' Care) study protocol

Combining Nonclinical Determinants of Health and Clinical Data for Research and Evaluation: Rapid Review

Background

Nonclinical determinants of health are of increasing importance to health care delivery and health policy. Concurrent with growing interest in better addressing patients’ nonmedical issues is the exponential growth in availability of data sources that provide insight into these nonclinical determinants of health.

Objective

This review aimed to characterize the state of the existing literature on the use of nonclinical health indicators in conjunction with clinical data sources.

Methods

We conducted a rapid review of articles and relevant agency publications published in English. Eligible studies described the effect of, the methods for, or the need for combining nonclinical data with clinical data and were published in the United States between January 2010 and April 2018. Additional reports were obtained by manual searching. Records were screened for inclusion in 2 rounds by 4 trained reviewers with interrater reliability checks. From each article, we abstracted the measures, data sources, and level of measurement (individual or aggregate) for each nonclinical determinant of health reported.

Results

A total of 178 articles were included in the review. The articles collectively reported on 744 different nonclinical determinants of health measures. Measures related to socioeconomic status and material conditions were most prevalent (included in 90% of articles), followed by the closely related domain of social circumstances (included in 25% of articles), reflecting the widespread availability and use of standard demographic measures such as household income, marital status, education, race, and ethnicity in public health surveillance. Measures related to health-related behaviors (eg, smoking, diet, tobacco, and substance abuse), the built environment (eg, transportation, sidewalks, and buildings), natural environment (eg, air quality and pollution), and health services and conditions (eg, provider of care supply, utilization, and disease prevalence) were less common, whereas measures related to public policies were rare. When combining nonclinical and clinical data, a majority of studies associated aggregate, area-level nonclinical measures with individual-level clinical data by matching geographical location.

Conclusions

A variety of nonclinical determinants of health measures have been widely but unevenly used in conjunction with clinical data to support population health research.

Building Meaningful Patient Engagement in Research: Case Study From ADVANCE Clinical Data Research Network

BACKGROUND

Strategies to engage patients to improve and enhance research and clinical care are increasingly being implemented in the United States, yet little is known about best practices for or the impacts of meaningful patient engagement.

OBJECTIVE

We describe and reflect on our patient stakeholder groups, engagement framework, experiences, and lessons learned in engaging patients in research, from generating proposal ideas to disseminating findings.

SETTING

The ADVANCE (Accelerating Data Value Across a National Community Health Center Network) clinical data research network is the nation's largest clinical dataset on the safety net, with outpatient clinical data from 122 health systems (1109 clinics) in 23 states.

RESULTS

Patients stakeholders codeveloped the ADVANCE engagement framework and its implementation in partnership with network leaders. In phase I of ADVANCE, patients were involved with designing studies (input on primary outcome measures and methods) and usability testing (of the patient portal). In phase II, the network is prioritizing research training, dissemination opportunities, an "ambassador" program to pair more experienced patient stakeholders with those less experienced, and evaluation of engagement activities and impacts.

DISCUSSION

The ADVANCE framework for patient engagement has successfully involved a diverse group of patients in the design, implementation, and interpretation of comparative effectiveness research. Our experience and framework can be used by other organizations and research networks to support patient engagement activities.

Innovative Implementation Studies Conducted in US Safety Net Health Care Settings: A Systematic Review

Little is known about dissemination and implementation in safety net settings. The authors conducted a literature review of innovation/implementation studies in US safety net health care settings between 2008 and 2017. Each article was coded for (1) intervention characteristics, (2) implementation stage, (3) internal versus external ownership, and (4) prespecified implementation outcomes (eg, acceptability and fidelity). Twenty studies were identified; the majority were implemented within community clinics or integrated safety net systems (15 articles), most involved care process improvements (13 articles), and most were internally developed (13 articles). The internally developed innovations reported fewer barriers to acceptability among staff/providers, higher leadership involvement and organizational alignment, greater amounts of customization to the local setting, and better sustainment. Future work should harness the high levels of alignment and acceptability in implementation research within safety net settings, with an eye toward maintaining fidelity to facilitate dissemination across sites.

Electronic health record tools to assist with children's insurance coverage: a mixed methods study

Background

Children with health insurance have increased access to healthcare and receive higher quality care. However, despite recent initiatives expanding children’s coverage, many remain uninsured. New technologies present opportunities for helping clinics provide enrollment support for patients. We developed and tested electronic health record (EHR)-based tools to help clinics provide children’s insurance assistance.

Methods

We used mixed methods to understand tool adoption, and to assess impact of tool use on insurance coverage, healthcare utilization, and receipt of recommended care. We conducted intent-to-treat (ITT) analyses comparing pediatric patients in 4 intervention clinics (n = 15,024) to those at 4 matched control clinics (n = 12,227). We conducted effect-of-treatment-on-the-treated (ETOT) analyses comparing intervention clinic patients with tool use (n = 2240) to intervention clinic patients without tool use (n = 12,784).

Results

Tools were used for only 15% of eligible patients. Qualitative data indicated that tool adoption was limited by: (1) concurrent initiatives that duplicated the work associated with the tools, and (2) inability to obtain accurate insurance coverage data and end dates. The ITT analyses showed that intervention clinic patients had higher odds of gaining insurance coverage (adjusted odds ratio [aOR] = 1.32, 95% confidence interval [95%CI] 1.14–1.51) and lower odds of losing coverage (aOR = 0.77, 95%CI 0.68–0.88), compared to control clinic patients. Similarly, ETOT findings showed that intervention clinic patients with tool use had higher odds of gaining insurance (aOR = 1.83, 95%CI 1.64–2.04) and lower odds of losing coverage (aOR = 0.70, 95%CI 0.53–0.91), compared to patients without tool use. The ETOT analyses also showed higher rates of receipt of return visits, well-child visits, and several immunizations among patients for whom the tools were used.

Conclusions

This pragmatic trial, the first to evaluate EHR-based insurance assistance tools, suggests that it is feasible to create and implement tools that help clinics provide insurance enrollment support to pediatric patients. While ITT findings were limited by low rates of tool use, ITT and ETOT findings suggest tool use was associated with better odds of gaining and keeping coverage. Further, ETOT findings suggest that use of such tools may positively impact healthcare utilization and quality of pediatric care.

Trial registration

ClinicalTrials.gov, NCT02298361; retrospectively registered on November 5, 2014.

Electronic supplementary material

The online version of this article (10.1186/s12913-018-3159-x) contains supplementary material, which is available to authorized users.

A new role for primary care teams in the United States after "Obamacare:" Track and improve health insurance coverage rates

Maintaining continuous health insurance coverage is important. With recent expansions in access to coverage in the United States after "Obamacare," primary care teams have a new role in helping to track and improve coverage rates and to provide outreach to patients. We describe efforts to longitudinally track health insurance rates using data from the electronic health record (EHR) of a primary care network and to use these data to support practice-based insurance outreach and assistance. Although we highlight a few examples from one network, we believe there is great potential for doing this type of work in a broad range of family medicine and community health clinics that provide continuity of care. By partnering with researchers through practice-based research networks and other similar collaboratives, primary care practices can greatly expand the use of EHR data and EHR-based tools targeting improvements in health insurance and quality health care.