Risk-adjusted comparison of blood pressure and low-density lipoprotein (LDL) noncontrol in primary care offices

The Affordable Care Act: Effects of Insurance on Diabetes Biomarkers

OBJECTIVE

We sought to understand how Affordable Care Act (ACA) Medicaid expansion insurance coverage gains are associated with changes in diabetes-related biomarkers.

RESEARCH DESIGN AND METHODS

This was a retrospective observational cohort study using electronic health record data from 178 community health centers (CHCs) in the ADVANCE (Accelerating Data Value Across a National Community Health Center Network) network. We assessed changes in diabetes-related biomarkers among adult patients with diabetes in 10 Medicaid expansion states (n = 25,279), comparing newly insured with continuously insured, discontinuously insured, and continuously uninsured patients pre- to post-ACA expansion. Primary outcomes included changes from 24 months pre- to 24 months post-ACA in glycosylated hemoglobin (HbA_1c), systolic (SBP) and diastolic (DBP) blood pressure, and LDL cholesterol levels.

RESULTS

Newly insured patients exhibited a reduction in adjusted mean HbA_1c levels (8.24% [67 mmol/mol] to 8.17% [66 mmol/mol]), which was significantly different from continuously uninsured patients, whose HbA_1c levels increased (8.12% [65 mmol/mol] to 8.29% [67 mmol/mol]; difference-in-differences [DID] -0.24%; P < 0.001). Newly insured patients showed greater reductions than continuously uninsured patients in adjusted mean SBP (DID -1.8 mmHg; P < 0.001), DBP (DID -1.0 mmHg; P < 0.001), and LDL (DID -3.3 mg/dL; P < 0.001). Among patients with elevated HbA_1c in the 3 months prior to expansion, newly insured patients were more likely than continuously uninsured patients to have a controlled HbA_1c measurement by 24 months post-ACA (hazard ratio 1.25; 95% CI 1.02-1.54].

CONCLUSIONS

Post-ACA, newly insured patients had greater improvements in diabetes-related biomarkers than continuously uninsured, discontinuously insured, or continuously insured patients. Findings suggest that health insurance gain via ACA facilitates access to appropriate diabetes care, leading to improvements in diabetes-related biomarkers.

Disparities in Biomarkers for Patients With Diabetes After the Affordable Care Act

BACKGROUND

Racial and ethnic minorities are disproportionately affected by diabetes and at greater risk of experiencing poor diabetes-related outcomes compared with non-Hispanic whites. The Affordable Care Act (ACA) was implemented to increase health insurance coverage and reduce health disparities.

OBJECTIVE

Assess changes in diabetes-associated biomarkers [hemoglobin A1c (HbA1c) and low-density lipoprotein] 24 months pre-ACA to 24 months post-ACA Medicaid expansion by race/ethnicity and insurance group.

RESEARCH DESIGN

Retrospective cohort study of community health center (CHC) patients.

SUBJECTS

Patients aged 19-64 with diabetes living in 1 of 10 Medicaid expansion states with ≥1 CHC visit and ≥1 HbA1c measurement in both the pre-ACA and the post-ACA time periods (N=13,342).

METHODS

Linear mixed effects and Cox regression modeled outcome measures.

RESULTS

Overall, 33.5% of patients were non-Hispanic white, 51.2% Hispanic, and 15.3% non-Hispanic black. Newly insured Hispanics and non-Hispanic whites post-ACA exhibited modest reductions in HbA1c levels, similar benefit was not observed among non-Hispanic black patients. The largest reduction was among newly insured Hispanics versus newly insured non-Hispanic whites (P<0.05). For the subset of patients who had uncontrolled HbA1c (HbA1c≥9%) within 3 months of the ACA Medicaid expansion, non-Hispanic black patients who were newly insured gained the highest rate of controlled HbA1c (hazard ratio=2.27; 95% confidence interval, 1.10-4.66) relative to the continuously insured group.

CONCLUSIONS

The impact of the ACA Medicaid expansion on health disparities is multifaceted and may differ across racial/ethnic groups. This study highlights the importance of CHCs for the health of minority populations.

New approaches to measuring the comprehensiveness of primary care physicians

OBJECTIVE

To develop claims-based measures of comprehensiveness of primary care physicians (PCPs) and summarize their associations with health care utilization and cost.

DATA SOURCES AND STUDY SETTING

A total of 5359 PCPs caring for over 1 million Medicare fee-for-service beneficiaries from 1404 practices.

STUDY DESIGN

We developed Medicare claims-based measures of physician comprehensiveness (involvement in patient conditions and new problem management) and used a previously developed range of services measure. We analyzed the association of PCPs' comprehensiveness in 2013 with their beneficiaries' emergency department, hospitalizations rates, and ambulatory care-sensitive condition (ACSC) admissions (each per 1000 beneficiaries per year), and Medicare expenditures (per beneficiary per month) in 2014, adjusting for beneficiary, physician, practice, and market characteristics, and clustering.

PRINCIPAL FINDINGS

Each measure varied across PCPs and had low correlation with the other measures-as intended, they capture different aspects of comprehensiveness. For patients whose PCPs' comprehensiveness score was at the 75th vs 25th percentile (more vs less comprehensive), patients had lower service use (P < 0.05) in one or more measures: involvement with patient conditions: total Medicare expenditures, -$17.4 (-2.2 percent); hospitalizations, -5.5 (-1.9 percent); emergency department (ED) visits, -16.3 (-2.4 percent); new problem management: total Medicare expenditures, -$13.3 (-1.7 percent); hospitalizations, -7.0 (-2.4 percent); ED visits, -19.7 (-2.9 percent); range of services: ED visits, -17.1 (-2.5 percent). There were no significant associations between the comprehensiveness measures and ACSC admission rates.

CONCLUSIONS

These measures demonstrate strong content and predictive validity and reliability. Medicare beneficiaries of PCPs providing more comprehensive care had lower hospitalization rates, ED visits, and total Medicare expenditures.

The use of Electronic Health Records to Support Population Health: A Systematic Review of the Literature

Electronic health records (EHRs) have emerged among health information technology as "meaningful use" to improve the quality and efficiency of healthcare, and health disparities in population health. In other instances, they have also shown lack of interoperability, functionality and many medical errors. With proper implementation and training, are electronic health records a viable source in managing population health? The primary objective of this systematic review is to assess the relationship of electronic health records' use on population health through the identification and analysis of facilitators and barriers to its adoption for this purpose. Authors searched Cumulative Index of Nursing and Allied Health Literature (CINAHL) and MEDLINE (PubMed), 10/02/2012-10/02/2017, core clinical/academic journals, MEDLINE full text, English only, human species and evaluated the articles that were germane to our research objective. Each article was analyzed by multiple reviewers. Group members recognized common facilitators and barriers associated with EHRs effect on population health. A final list of articles was selected by the group after three consensus meetings (n = 55). Among a total of 26 factors identified, 63% (147/232) of those were facilitators and 37% (85/232) barriers. About 70% of the facilitators consisted of productivity/efficiency in EHRs occurring 33 times, increased quality and data management each occurring 19 times, surveillance occurring 17 times, and preventative care occurring 15 times. About 70% of the barriers consisted of missing data occurring 24 times, no standards (interoperability) occurring 13 times, productivity loss occurring 12 times, and technology too complex occurring 10 times. The analysis identified more facilitators than barriers to the use of the EHR to support public health. Wider adoption of the EHR and more comprehensive standards for interoperability will only enhance the ability for the EHR to support this important area of surveillance and disease prevention. This review identifies more facilitators than barriers to using the EHR to support public health, which implies a certain level of usability and acceptance to use the EHR in this manner. The public-health industry should combine their efforts with the interoperability projects to make the EHR both fully adopted and fully interoperable. This will greatly increase the availability, accuracy, and comprehensiveness of data across the country, which will enhance benchmarking and disease surveillance/prevention capabilities.

Active Use of Electronic Health Records (EHRs) and Personal Health Records (PHRs) for Epidemiologic Research: Sample Representativeness and Nonresponse Bias in a Study of Women During Pregnancy

Introduction:

With the growing use of electronic medical records, electronic health records (EHRs), and personal health records (PHRs) for health care delivery, new opportunities have arisen for population health researchers. Our objective was to characterize PHR users and examine sample representativeness and nonresponse bias in a study of pregnant women recruited via the PHR.

Design:

Demographic characteristics were examined for PHR users and nonusers. Enrolled study participants (responders, n=187) were then compared with nonresponders and a representative sample of the target population.

Results:

PHR patient portal users (34 percent of eligible persons) were older and more likely to be White, have private health insurance, and develop gestational diabetes than nonusers. Of eligible persons (all PHR users), 11 percent (187/1,713) completed a self-administered PHR based questionnaire. Participants in the research study were more likely to be non-Hispanic White (90 percent versus 79 percent) and married (85 percent versus 77 percent), and were less likely to be Non-Hispanic Black (3 percent versus 12 percent) or Hispanic (3 percent versus 6 percent). Responders and nonresponders were similar regarding age distribution, employment status, and health insurance status. Demographic characteristics were similar between responders and nonresponders.

Discussion:

Demographic characteristics of the study population differed from the general population, consistent with patterns seen in traditional population-based studies. The PHR may be an efficient method for recruiting and conducting observational research with additional benefits of efficiency and cost-cost-effectiveness.

A cluster randomized trial on the effect of a multifaceted intervention improved the technical quality of diabetes care by primary care physicians: The Japan Diabetes Outcome Intervention Trial-2 (J-DOIT2)

AIMS

To evaluate the effect of multifaceted interventions using the Achievable Benchmark of Care (ABC) method for improving the technical quality of diabetes care in primary care settings.

METHODS

We conducted a 1-year cluster randomized controlled trial in 22 regions divided into an intervention group (IG) or control group (CG). Physicians in the IG received a monthly report of their care quality, with the top 10% quality of diabetes care scores for all physicians being the achievable benchmark. The change in quality-of-care scores between the IG and CG during follow-up was analysed using a generalized linear model considering clustering.

RESULTS

A total of 2199 patients were included. Their mean (sd) age was 56.5 ± 5.9 years and the mean (sd) HbA1c level was 56.4 ± 13.3 mmol/mol (7.4 ± 1.2%). The quality-of-care score in the CG changed from 50.2%-point at baseline to 51%-point at 12 months, whereas the IG score changed from 49.9%-point to 69.6%-point, with statistically significant differences between the two groups during follow-up [the effect of intervention was 19.0%-point (95% confidence interval 16.7%- to 21.3%-point; P < 0.001)].

CONCLUSIONS

Multifaceted intervention, measuring quality-of-care indicators and providing feedback regarding the quality of diabetes care to physicians with ABC, was effective for improving the technical quality of care in patients with Type 2 diabetes in primary care settings. (

TRIAL REGISTRATION

umin.ac.jp/ctr as UMIN000002186).

Measuring Comprehensiveness of Primary Care: Challenges and Opportunities

Comprehensiveness of primary care (the extent to which the clinician, as part of the primary care team, recognizes and meets the majority of each patient's physical and mental health care needs) is an important element of primary care, but seems to be declining in the U.S. This is concerning, because more comprehensive primary care is associated with greater equity and efficiency in health care, improved continuity, less care fragmentation and better health outcomes. Without measurement and support for its improvement, comprehensiveness may further decline as other measured aspects of primary care (e.g. access, coordination) improve. To track, support and improve comprehensiveness, it is useful to have valid and reliable ways to measure it. This paper discusses challenges to measuring comprehensiveness for a primary care team's patient panel, presents survey and claims-based measures of comprehensiveness, and provides suggestions for future research.