Coordination of Health Behavior Counseling in Primary Care

Cohen, Deborah J.; Balasubramanian, Bijal A.; Isaacson, Nicole; Clark, Elizabeth; Etz, Rebecca; Crabtree, Benjamin F.

doi:10.1370/afm.1245

Cited by 42 publications

(45 citation statements)

References 44 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…9,23,24 This study shows that REACH also served as a key implementation measure. 7 When measured in conjunction with qualitative assessments of the implementation process, it generated important quality improvement lessons for practices and cross practice, transportable findings for the field in general.…”

Section: Discussionmentioning

confidence: 69%

REACH of Interventions Integrating Primary Care and Behavioral Health

Balasubramanian

Fernald

Dickinson

et al. 2015

The Journal of the American Board of Family Medicine

Self Cite

View full text Add to dashboard Cite

Purpose: This study reports REACH (the extent to which an intervention or program was delivered to the identified target population) of interventions integrating primary care and behavioral health implemented by real-world practices.Methods: Eleven practices implementing integrated care interventions provided data to calculate REACH as follows: 1) Screening REACH defined as proportion of target patients assessed for integrated care, and 2) Integrated care services REACH-defined as proportion of patients receiving integrated services of those who met specific criteria. Difference in mean REACH between practices was evaluated using t test.Results: Overall, 26.2% of target patients (n ‫؍‬ 24,906) were assessed for integrated care and 41% (n ‫؍‬ 836) of eligible patients received integration services. Practices that implemented systematic protocols to identify patients needing integrated care had a significantly higher screening REACH (mean, 70%; 95% CI [confidence interval], 46.6 -93.4%) compared with practices that used clinicians' discretion (mean, 7.9%; 95% CI, 0.6 -15.1; P ‫؍‬ .0014). Integrated care services REACH was higher among practices that used clinicians' discretion compared with those that assessed patients systematically (mean, 95.8 vs 53.8%; P ‫؍‬ .03).Conclusion: REACH of integrated care interventions differed by practices' method of assessing patients. Measuring REACH is important to evaluate the extent to which integration efforts affect patient care and can help demonstrate the impact of integrated care to payers and policy makers. (J Am Board Fam Med 2015;28:S73-S85.)

show abstract

Section: Discussionmentioning

confidence: 69%

REACH of Interventions Integrating Primary Care and Behavioral Health

Balasubramanian

Fernald

Dickinson

et al. 2015

The Journal of the American Board of Family Medicine

Self Cite

View full text Add to dashboard Cite

show abstract

“…21,29 Other Prescription for Health investigators noted that implementation of interventions were uneven and difficult in some networks. 30,31 Although the ability to implement an intervention is important to consider when evaluating the utility of an intervention in practices, it was not possible in this study to assess how implementation variance affected the outcomes or how to interpret positive findings.…”

Section: Methodsmentioning

confidence: 99%

Improving Multiple Health Risk Behaviors in Primary Care: Lessons from the Prescription for Health COmmon Measures, Better Outcomes (COMBO) Study

Fernald

Dickinson

Froshaug

et al. 2012

The Journal of the American Board of Family Medicine

Self Cite

View full text Add to dashboard Cite

Background: Four health behaviors-smoking, risky drinking, physical inactivity, and unhealthy diets-contribute substantially to health care burden and are common among primary care patients. However, there is insufficient evidence to recommend broadly brief interventions to address all 4 of these in frontline primary care. This study took advantage of a multinetwork initiative to reflect on health behavior outcomes and the challenges of using a common set of measures to assess health behavior-change strategies for multiple health behaviors in routine primary care practice.Methods: Standardized, brief practical health behavior and quality of life measures used across 7 practice-based research networks (PBRNs) with independent primary care interventions in 54 primary care practices between August 2005 and December 2007 were analyzed. Mixed-effects longitudinal models assessed whether intervention patients improved diet, physical activity, smoking, alcohol consumption, and unhealthy days over time. Separate analyses were conducted for each intervention.Results: Of 4463 adults, 2199 had follow-up data, and all available data were used in longitudinal analyses. Adjusting for age, race/ethnicity, education, and baseline body mass index where available, diet scores improved significantly in 5 of 7 networks (P < .02). Physical activity improved significantly in 2 networks but declined in one network (P < .024). The likelihood of being a current smoker was reduced in 2 of 5 networks (P < .0001), and average alcoholic drinks per day was reduced in 2 network s (P < .02). Participants reported fewer unhealthy days at follow-up in 3 of 7 networks (P < .01). Details of implementation and the limitations in instrumentation help contextualize these modest outcomes.Conclusions: Although some patients in these 7 PBRNs improved in several health behaviors and quality of life, the strength of evidence for field-ready methods to address multiple health risk behaviors remains elusive. The use of common measures to assess changes in 4 unhealthy behaviors was achieved practically in PBRNs testing diverse strategies to improve behaviors; however, variations in implementation, instrumentation performance, and some features of study design overwhelmed potential cross-PBRN comparisons. For common measures to be useful for comparisons across practices or PBRNs, greater standardization of study designs and careful attention to practicable implementation strategies are necessary. (J Am Board Fam Med 2012;25:701-711.)

show abstract

“…14 The practice questionnaire elicited information on practice characteristics (eg, size, ownership, staffing) and included the Change Process Capability Questionnaire (CPCQ). [15][16][17] Either the lead clinician or office manager completed the practice questionnaire. The practice member questionnaire assessed organizational culture and additional measures of practice capacity (eg, adaptive reserve, burnout) and was completed at baseline by all clinicians and staff in all enrolled practices.…”

Section: Study Instrumentsmentioning

confidence: 99%

Quality of Cardiovascular Disease Care in Small Urban Practices

et al. 2018

View full text Add to dashboard Cite

PURPOSE We wanted to describe small, independent primary care practices' performance in meeting the Million Hearts ABCSs (aspirin use, blood pressure control, cholesterol management, and smoking screening and counseling), as well as on a composite measure that captured the extent to which multiple clinical targets are achieved for patients with a history of arteriosclerotic cardiovascular disease (ASCVD). We also explored relationships between practice characteristics and ABCS measures. METHODSWe conducted a cross-sectional, bivariate analysis using baseline data from 134 practices in New York City. ABCS data were extracted from practices' electronic health records and aggregated to the site level. Practice characteristics were obtained from surveys of clinicians and staff at each practice. RESULTSThe proportion of at-risk patients meeting clinical goals for each of the ABCS measures was 73.0% for aspirin use, 69.6% for blood pressure, 66.7% for cholesterol management, and 74.2% screened for smoking and counseled. For patients with a history of ASCVD, only 49% were meeting all ABC (aspirin use, blood pressure control, cholesterol management) targets (ie, composite measure). Solo practices were more likely to meet clinical guidelines for aspirin (risk ratio [RR ] = 1.17, P = .007) and composite (RR = 1.29, P = .011) than practices with multiple clinicians.CONCLUSION Achieving targets for ABCS measures varied considerably across practices; however, small practices were meeting or exceeding Million Hearts goals (ie, 70% or greater). Practices were less likely to meet consistently clinical targets that apply to patients with a history of ASCVD risk factors. Greater emphasis is needed on providing support for small practices to address the complexity of managing patients with multiple risk factors for primary and secondary ASCVD. INTRODUCTIONC ardiovascular disease remains the number 1 cause of death in the United States.1 One-half of the US adult population has 1 or more preventable risk factors for arteriosclerotic cardiovascular disease (ASCVD), but less than one-half are meeting all of their clinical goals. 2Increasing the adoption of effective clinical preventive services that reduce ASCVD mortality, including treating hypertension and hyperlipidemia, would result in large improvements in population health. 3HealthyHearts New York City, 1 of 7 research cooperatives funded through the EvidenceNOW initiative, is studying the effectiveness of external practice facilitation to increase capacity among small, independent primary care practices to implement innovations in health care aimed at increasing adoption of the Million Hearts ABCS (aspirin use, blood pressure control, cholesterol management, and smoking cessation) guidelines.1,4 These guidelines include aspirin when indicated, blood pressure control, cholesterol management through guideline-recommended use of lipid-lowering medications, and both screening for tobacco use and offering smokers cessation interventions or counseling. S22There is a strong ...

show abstract

Coordination of Health Behavior Counseling in Primary Care

Cited by 42 publications

References 44 publications

REACH of Interventions Integrating Primary Care and Behavioral Health

REACH of Interventions Integrating Primary Care and Behavioral Health

Improving Multiple Health Risk Behaviors in Primary Care: Lessons from the Prescription for Health COmmon Measures, Better Outcomes (COMBO) Study

Quality of Cardiovascular Disease Care in Small Urban Practices

Contact Info

Product

Resources

About