National findings regarding health IT use and participation in health care delivery reform programs among office-based physicians

The Impact of Delivery Reform on Health Information Exchange with Behavioral Health Providers: Results from a National Representative Survey of Ambulatory Physicians

Health information exchange (HIE) is an effective way to coordinate care, but HIE between health and behavioral health providers is limited. Recent delivery reform models, including the Accountable Care Organization (ACO) and Patient Centered Medical Home (PCMH) prioritize interprofessional collaboration, but little is known about their impact on behavioral health HIE. This study explores whether delivery reform participation affects behavioral health HIE among ambulatory health providers using pooled 2015-2019 data from the National Electronic Health Record Survey, a nationally representative survey of ambulatory physicians' technology use (n = 8,703). The independent variable in this analysis was provider participation in ACO, PCMH, Hybrid ACO-PCMH, or standard care. The dependent variable was HIE with behavioral health providers. Chi square analysis estimated unweighted rates of behavioral health HIE across reform models. Logistic regression estimated the impact of delivery reform participation on rates of behavioral health HIE. Unweighted estimates indicated that Hybrid ACO-PCMH providers had the highest rates of HIE (n = 330, 33%). In the fully adjust model, rates of HIE were higher among ACO (AOR = 2.66, p < .01), PCMH (AOR = 4.73, p < .001) and Hybrid ACO-PCMH participants (AOR = 5.55, p < .001) compared to standard care, but they did not significantly vary between delivery models. Physicians infrequently engage in HIE with behavioral health providers. Compared to standard care, higher rates of HIE were found across all models of delivery reform. More work is needed to identify common elements of delivery reform models that are most effective in supporting this behavior.

Longitudinal participation in delivery and payment reform programs among US Primary Care Organizations

OBJECTIVE

To assess longitudinal primary care organization participation patterns in large-scale reform programs and identify organizational characteristics associated with multiprogram participation.

DATA SOURCES

Secondary data analysis of national program participation data over an eight-year period (2009-2016).

STUDY DESIGN

We conducted a retrospective, observational study by creating a unique set of data linkages (including Medicare and Medicaid Meaningful Use and Medicare Shared Savings Program Accountable Care Organization (MSSP ACO) participation from CMS, Patient-Centered Medical Home (PCMH) participation from the National Committee for Quality Assurance, and organizational characteristics) to measure longitudinal participation and identify what types of organizations participate in one or more of these reform programs. We used multivariate models to identify organizational characteristics that differentiate those that participate in none, one, or two-to-three programs.

DATA EXTRACTION METHODS

We used Medicare claims to identify organizations that delivered primary care services (n = 56 ,287) and then linked organizations to program participation data and characteristics.

PRINCIPAL FINDINGS

No program achieved more than 50% participation across the 56,287 organizations in a given year, and participation levels flattened or decreased in later years. 36% of organizations did not participate in any program over the eight-year study period; 50% participated in one; 13% in two; and 1% in all three. 14.31% of organizations participated in five or more years of Meaningful Use while 3.84% of organizations participated in five years of the MSSP ACO Program and 0.64% participated in at least five years of PCMH. Larger organizations, those with younger providers, those with more primary care providers, and those with larger Medicare patient panels were more likely to participate in more programs.

CONCLUSIONS AND RELEVANCE

Primary care transformation via use of voluntary programs, each with their own participation requirements and approach to incentives, has failed to broadly engage primary care organizations. Those that have chosen to participate in multiple programs are likely those already providing high-quality care.

Association of Primary Care Engagement in Value-Based Reform Programs With Health Services Outcomes: Participation and Synergies

Importance

Policy makers envision synergistic benefits from primary care reform programs that advance infrastructure and processes in the context of a supportive payment environment. However, these programs have been operationalized and implemented separately, raising the question of whether synergies are achieved.

Objective

To evaluate associations between primary care engagement in voluntary delivery system and/or payment reform programs and health services outcomes.

Design Setting and Participants

This was an observational longitudinal analysis of US ambulatory primary care organizations (PCOs) with attributed Medicare fee-for-service beneficiaries (1.6-1.9 million unique beneficiaries annually) using data for 2009, 2010, and 2015 to 2017; PCOs included multispecialty practices that delivered primary care. Data analyses were performed from January 2020 to December 2021.

Exposures

Annual PCO participation in or recognition by (1) the Centers for Medicare & Medicaid's meaningful use (MU) program, (2) the National Committee for Quality Assurance's Patient-Centered Medical Home (PCMH) program, and/or (3) the Medicare Shared Savings Program (MSSP), an Accountable Care Organizations program.

Main Outcomes and Measures

Independent and joint associations between an additional year of participation by a PCO in each of the 3 reform programs, and 3 types of outcomes: (1) hospital utilization (all-cause admissions, ambulatory care sensitive admissions, all-cause readmissions, all-cause emergency department visits); (2) evidence-based diabetes guideline adherence (≥1 annual glycated hemoglobin test, low-density lipoprotein cholesterol test, nephropathy screening, and eye examination); and (3) Medicare spending (total, acute inpatient, and skilled nursing facility).

Results

The study sample comprised 47 880 unique PCOs (size ≤10 beneficiaries, 50%; ≤1-2 clinicians, 65%) and approximately 5.61 million unique Medicare beneficiaries (mean [SD] age, 71.4 [12.7] years; 3 207 568 [57.14%] women; 4 474 541 [79.71%] non-Hispanic White individuals) across the study years (2009, 2010, 2015-2017). Of the hospital utilization measures, only ambulatory care sensitive admission was associated with improved performance, showing a statistically significant marginal effect size for joint participation in MU and MSSP (-0.0002; 95% CI, -0.0005 to 0.0000) and MSSP alone (-0.0003; 95% CI, -0.0005 to -0.0001). For diabetes adherence, joint participation in PCMH and MU was associated with 0.06 more measures met (95% CI, 0.03 to 0.10) while participation in all 3 programs was associated with 0.05 more measures met (95% CI, 0.02 to 0.09). Stand-alone PCMH and stand-alone MU participation were also associated with improved performance. Joint participation in MU and MSSP was associated with $33.89 lower spending (95% CI, -$65.79 to -$1.99) as was stand-alone MSSP participation (-$37.04; 95% CI, -$65.73 to -$8.35).

Conclusions and Relevance

This longitudinal observational study found that participation by PCOs in single or multiple reform programs was associated with better performance for only a subset of health services outcomes. More consistent and larger synergies may be realized with improved alignment of program requirements and goals.

Health Information Technology and Accountable Care Organizations: A Systematic Review and Future Directions

Background:

Since the inception of Accountable Care Organizations (ACOs), many have acknowledged the potential synergy between ACOs and health information technology (IT) in meeting quality and cost goals.

Objective:

We conducted a systematic review of the literature in order to describe what research has been conducted at the intersection of health IT and ACOs and identify directions for future research.

Methods:

We identified empirical studies discussing the use of health IT via PubMed search with subsequent snowball reference review. The type of health IT, how health IT was included in the study, use of theory, population, and findings were extracted from each study.

Results:

Our search resulted in 32 studies describing the intersection of health IT and ACOs, mainly in the form of electronic health records and health information exchange. Studies were divided into three streams by purpose; those that considered health IT as a factor for ACO participation, health IT use by current ACOs, and ACO performance as a function of health IT capabilities. Although most studies found a positive association between health IT and ACO participation, studies that address the performance of ACOs in terms of their health IT capabilities show more mixed results.

Conclusions:

In order to better understand this emerging relationship between health IT and ACO performance, we propose future research should consider more quasi-experimental studies, the use of theory, and merging health, quality, cost, and health IT use data across ACO member organizations.

Adding Social Determinants in the Electronic Health Record in Clinical Care in Hawai'i: Supporting Community-Clinical Linkages in Patient Care

Social and behavioral determinants of health, such as poverty, homelessness, and limited social support, account for an estimated 40% of health burdens and predict critical health outcomes. Many clinical-community linkages specifically focus on addressing such challenges. Given its distinctive history, culture, and location, Hawai'i has unique social factors impacting population health. Local health systems are striving to address these issues to meet their patients' health needs. Yet the evidence on precisely how health care systems and communities may work together to achieve these goals are limited both generally and specifically in the Hawai'i context. This article describes real-world efforts by 3 local health care delivery systems that integrate the identification of social needs into clinical care using the electronic health record (EHR). One health care system collects and assesses social challenges and interpersonal needs to improve the care for its frail seniors (aged 65 and older). Another system added key data fields around social support and inpatient mobility in the EHR to identify whether patients needed additional help during hospitalization and post-discharge. A third added a social needs screening tool (eg, housing instability, food insecurity, transportation needs) to its EHR to ensure that patient-specific needs can be appropriately addressed by the care team. Successful integration of this information into the EHR can identify, direct, and support clinical-community linkages and integrate such relationships into the care team. Many lessons can be learned from the implementation of these programs, including the importance of clinical relevance and ensuring capacity for social work liaisons trained for this work to address identified needs.

The patient-centered dental home: A standardized definition for quality assessment, improvement, and integration

OBJECTIVE

To develop the first standardized definition of the patient-centered dental home (PCDH).

DATA SOURCES/STUDY SETTING

Primary data from a 55-member national expert panel and public comments.

STUDY DESIGN

We used a modified Delphi process with three rounds of surveys to collect panelists' ratings of PCDH characteristics and open-ended comments. The process was supplemented with a 1-month public comment period.

DATA COLLECTION/EXTRACTION METHODS

We calculated median ratings, analyzed consensus using the interpercentile range adjusted for symmetry, and qualitatively evaluated comments.

PRINCIPAL FINDINGS

Forty-nine experts (89%) completed three rounds and identified eight essential PCDH characteristics, resulting in the following definition: "The patient-centered dental home is a model of care that is accessible, comprehensive, continuous, coordinated, patient- and family-centered, and focused on quality and safety as an integrated part of a health home for people throughout the life span."

CONCLUSIONS

This PCDH definition provides the foundation for developing measures for research, care improvement, and accreditation and is aligned with the patient-centered medical home. Consensus among a broad national expert panel-including provider, payer, and accreditation stakeholder organizations and experts in medicine, dentistry, and quality measurement-supports the definition's usability and its potential to facilitate medical-dental primary care integration.

Primary Care Practices' Abilities And Challenges In Using Electronic Health Record Data For Quality Improvement

Federal value-based payment programs require primary care practices to conduct quality improvement activities, informed by the electronic reports on clinical quality measures that their electronic health records (EHRs) generate. To determine whether EHRs produce reports adequate to the task, we examined survey responses from 1,492 practices across twelve states, supplemented with qualitative data. Meaningful-use participation, which requires the use of a federally certified EHR, was associated with the ability to generate reports-but the reports did not necessarily support quality improvement initiatives. Practices reported numerous challenges in generating adequate reports, such as difficulty manipulating and aligning measurement time frames with quality improvement needs, lack of functionality for generating reports on electronic clinical quality measures at different levels, discordance between clinical guidelines and measures available in reports, questionable data quality, and vendors that were unreceptive to changing EHR configuration beyond federal requirements. The current state of EHR measurement functionality may be insufficient to support federal initiatives that tie payment to clinical quality measures.

Practice Facilitator Strategies for Addressing Electronic Health Record Data Challenges for Quality Improvement: EvidenceNOW

PURPOSE

Practice facilitators ("facilitators") can play an important role in supporting primary care practices in performing quality improvement (QI), but they need complete and accurate clinical performance data from practices' electronic health records (EHR) to help them set improvement priorities, guide clinical change, and monitor progress. Here, we describe the strategies facilitators use to help practices perform QI when complete or accurate performance data are not available.

METHODS

Seven regional cooperatives enrolled approximately 1500 small-to-medium-sized primary care practices and 136 facilitators in EvidenceNOW, the Agency for Healthcare Research and Quality's initiative to improve cardiovascular preventive services. The national evaluation team analyzed qualitative data from online diaries, site visit field notes, and interviews to discover how facilitators worked with practices on EHR data challenges to obtain and use data for QI.

RESULTS

We found facilitators faced practice-level EHR data challenges, such as a lack of clinical performance data, partial or incomplete clinical performance data, and inaccurate clinical performance data. We found that facilitators responded to these challenges, respectively, by using other data sources or tools to fill in for missing data, approximating performance reports and generating patient lists, and teaching practices how to document care and confirm performance measures. In addition, facilitators helped practices communicate with EHR vendors or health systems in requesting data they needed. Overall, facilitators tailored strategies to fit the individual practice and helped build data skills and trust.

CONCLUSION

Facilitators can use a range of strategies to help practices perform data-driven QI when performance data are inaccurate, incomplete, or missing. Support is necessary to help practices, particularly those with EHR data challenges, build their capacity for conducting data-driven QI that is required of them for participating in practice transformation and performance-based payment programs. It is questionable how practices with data challenges will perform in programs without this kind of support.