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Use of a Preventive Index to Examine Clinic-Level Factors Associated With Delivery of Preventive Care.

ABSTRACT: INTRODUCTION:There is an increasing need for the development of new methods to understand factors affecting delivery of preventive care. This study applies a new measurement approach and assesses clinic-level factors associated with preventive care delivery. METHODS:This retrospective longitudinal cohort study of 94 community health centers used electronic health record data from the OCHIN community health information network, 2014-2015. Clinic-level preventive ratios (time covered by a preventive service/time eligible for a preventive service) were calculated in 2017 for 12 preventive services with A or B recommendations from the U.S. Preventive Services Task Force along with an aggregate preventive index for all services combined. For each service, multivariable negative binomial regression modeling and calculated rate ratios assessed the association between clinic-level variables and delivery of care. RESULTS:Of ambulatory community health center visits, 59.8% were Medicaid-insured and 10.4% were uninsured. Ambulatory community health centers served 16.9% patients who were Hispanic, 13.1% who were nonwhite, and 68.7% who had household incomes <138% of the federal poverty line. Clinic-level preventive ratios ranged from 3% (hepatitis C screening) to 93% (blood pressure screening). The aggregate preventive index including all screening measures was 47% (IQR, 42%-50%). At the clinic level, having a higher percentage of uninsured visits was associated with lower preventive ratios for most (7 of 12) preventive services. CONCLUSIONS:Approaches that use individual preventive ratios and aggregate prevention indices are promising for understanding and improving preventive service delivery over time. Health insurance remains strongly associated with access to needed preventive care, even for safety net clinic populations.

SUBMITTER: Hatch BA

PROVIDER: S-EPMC6684138 | biostudies-literature | 2019 Aug

REPOSITORIES: biostudies-literature

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Use of a Preventive Index to Examine Clinic-Level Factors Associated With Delivery of Preventive Care.

Hatch Brigit A BA Tillotson Carrie J CJ Huguet Nathalie N Hoopes Megan J MJ Marino Miguel M DeVoe Jennifer E JE

American journal of preventive medicine 20190801 2

<h4>Introduction</h4>There is an increasing need for the development of new methods to understand factors affecting delivery of preventive care. This study applies a new measurement approach and assesses clinic-level factors associated with preventive care delivery.<h4>Methods</h4>This retrospective longitudinal cohort study of 94 community health centers used electronic health record data from the OCHIN community health information network, 2014-2015. Clinic-level preventive ratios (time covere ...[more]

PMID: 31326008

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Project description:ImportanceThe COVID-19 pandemic caused significant declines in the quality of preventive and chronic disease care. The Veterans Health Administration (VHA) used the Preventive Health Inventory (PHI), a multicomponent care management intervention, to catch up on care disrupted by the pandemic.ObjectiveTo identify key factors associated with PHI use.Design, setting, and participantsThis cohort study of veterans receiving primary care used administrative data from national VHA primary care clinics for February 1, 2021, through February 1, 2022.ExposurePatient PHI receipt.Main outcomes and measuresThe main outcomes were patient, practitioner, and clinic factors associated with PHI receipt. Binomial generalized linear models with fixed effects for clinic were used to analyze factors associated with receipt of PHI. Least absolute shrinkage and selection operator procedures were used for variable selection.ResultsA total of 4 358 038 veterans (mean [SD] age, 63.7 [16.0] years; 90% male; 76% non-Hispanic White) formed the study cohort, of whom 389 757 (9%) received the PHI. Veterans who received the PHI had higher mean Care Assessment Need (CAN) scores, which indicate the likelihood of hospitalization or death within 1 year (mean [SD], 51.9 [28.6] vs 47.2 [28.6]; standardized mean difference [SMD], -0.16). They were also more likely to live in urban areas (77% vs 64%; SMD, 0.28) and have a shorter drive distance to primary care (mean [SD], 13.2 [12.4] vs 15.7 [14.6] miles; SMD, 0.19). The mean outpatient use was higher among PHI recipients compared with non-PHI recipients (mean [SD], 18.4 [27.8] vs 15.1 [24.1] visits; SMD, -0.13). In addition, veterans with primary care practitioners with higher caseloads were more likely to receive the PHI (mean [SD], 778 [231] vs 744 [249] patients; SMD, -0.14), and they were more likely to be seen at larger clinics (mean [SD], 9670 [6876] vs 8786 [6892] patients; SMD, -0.13). Prior outpatient use and CAN score were associated with PHI receipt in the final model.Conclusions and relevanceIn this cohort study of the VHA's PHI, patients with higher CAN scores and more outpatient use in the previous year were more likely to receive the PHI. This study identifies potential intervention points to improve care coordination for veterans.

Project description:BackgroundIdentifying the factors that predict non-adherence to recommended preventive pediatric care is necessary for the development of successful interventions to improve compliance.PurposeGiven the substantial decline in well-child visits and influenza vaccinations, we sought to examine sociodemographic (i.e., parent age, education, employment status, child age, insurance coverage, household size, race and ethnicity, income, COVID-19 incidence in state) and psychosocial (i.e., child temperament, parent mental health, parent personality traits) factors associated with preventative pediatric care (well-child visits, influenza vaccines) during the COVID-19 pandemic.MethodsAs part of a larger, ongoing study, 1875 parents (96% mothers, 65% age 35 or younger, 58% with a college degree) reported whether they had missed any recommended or scheduled well-child visits since the pandemic and whether they had vaccinated their child against the flu. Using data collected during fall 2020, we examine differences in these health outcomes across social/demographic factors and psychological profiles. In addition, we use lasso logistic regression models to (1) estimate the accuracy with which we can predict adherence from these characteristics and (2) identify factors most strongly, independently associated with adherence.ResultsParent psychological factors were associated with outcomes above and beyond known demographic and social factors. For example, parent industriousness and orderliness were associated with greater likelihoods of attending well-child visits and vaccinating children, while parent conservatism and creativity were associated with lower rates. We also replicate prior work documenting that health insurance, income, and household size are major factors in receiving adequate pediatric care.ConclusionsAdherence to preventive pediatric care varies as a function of psychological factors, suggesting that the current system of pediatric care favors some psychological profiles over others. However, the specific traits associated with non-adherence point to potentially fruitful interventions, specifically around increasing functional proximity.

Project description:IntroductionThe Veterans Choice Program expanded Veteran access to community care. The Veterans Choice Program may negatively impact the receipt of preventive care services owing to care fragmentation. This study assesses 10 measures of preventive care in Veterans with the Department of Veterans Affairs coverage before and after the Veterans Choice Program.MethodsThe study population included Veterans who responded to the National Health Interview Survey during the 2 time periods before and after Veterans Choice Program implementation: January 2011-October 2014 and November 2015-December 2018. Outcomes were preventive care services categorized as cardiovascular risk reduction (cholesterol monitoring, blood pressure monitoring, aspirin use), infectious disease prevention (influenza vaccination and HIV testing), and diabetes care (fasting blood glucose monitoring, podiatry visits, ophthalmology visits, influenza vaccination, and pneumonia vaccination). Two different analyses were conducted: (1) unadjusted and multivariable-adjusted pre-post analysis and (2) difference-in-differences analyses. Analyses were conducted in 2019.ResultsMeasures of cardiovascular risk reduction and influenza vaccination were not statistically different before and after Veterans Choice Program implementation using the 2 different analytic approaches. In unadjusted pre-post analysis, after Veterans Choice Program implementation, Veterans with Veterans Affairs coverage had increased HIV testing (66.1%‒75.4%, p=0.008), podiatry visits (22.4%‒38.3%, p=0.01), and ophthalmology visits (62.2%‒77.2%, p=0.02). Using multivariable adjustment for participant sociodemographic factors, Veterans Choice Program implementation was associated with higher odds of podiatry visits (AOR=2.28, 95% CI=1.24, 4.20, p=0.009) and ophthalmology visits (AOR=2.11, 95% CI=1.13, 3.94, p=0.02) among Veterans with diabetes. In difference-in-differences analyses, Veterans Choice Program implementation was associated with increased podiatry visits (AOR=2.95, 95% CI=1.49, 5.83, p=0.002) among Veterans with diabetes and Veterans Affairs coverage compared with that among those with other coverage types, but no statistically significant effect was observed for ophthalmology visits.ConclusionsVeterans with Veterans Affairs coverage and diabetes had an increase in podiatry visits after Veterans Choice Program implementation. There was no evidence that Veterans Choice Program implementation had a negative impact on the receipt of preventive care services among Veterans with Veterans Affairs coverage.

Project description:BackgroundDue to concerns of inadequate primary care access, national agencies like the Health Resources and Services Administration (HRSA) support primary care (PC) residencies. Recent research demonstrates that up to 35% of PC alumni lost interest in PC during residency. These alumni who lost interest noted that their continuity clinic experience influenced their career choice. The purpose of this study was to identify the specific aspects of PC residency experience that influenced career choice.MethodsWe conducted a cross-sectional electronic survey of a PC internal medicine alumni cohort (2000-2015) from a large, academic residency. Our primary predictor was PC career and our primary outcome was influential factors on career choice. We performed chi-squared or Fisher's exact tests for categorical variables and t tests for continuous variables.ResultsOf the 317 PC alumni in the last 15 years, 305 were contacted. One hundred seventy-two (56%) responded with 94 (55%) reporting current careers in PC and 78 (45%) in non-PC fields. Ninety-four percent of respondents expressed interest prior to residency, while only 68% remained interested at the conclusion of residency. Sixty-one percent of PC alumni rated the overall clinic experience as the most influential factor towards their ultimate career choice. The patient-physician relationship was the most frequently endorsed positively influential factor in career choice in both groups (95% of PC alumni, 76% non-PC). There was no difference among all alumni in common frustrations of clinic including clerical duties, encounter documentation, or visit length. Similarly, resident debt did not differ between groups.ConclusionsStrong interpersonal relationships with patients and clinic mentors were associated with a PC career. These factors may compensate for the reported frustrations of clinic. Enhancing patient and mentor relationships may increase the retention of PC residents in ambulatory careers and may help address the current and projected shortage of primary care physicians.

Project description:ImportancePrimary care physicians have limited time to discuss preventive care, but it is unknown how they prioritize recommended services.ObjectiveTo understand primary care physicians' prioritization of preventive services.Design, setting, and participantsThis online survey was administered to primary care physicians in a large health care system from March 17 to May 12, 2017. Physicians were asked whether they prioritize preventive services and which factors contribute to their choice (5-point Likert scale). Results were analyzed from July 8, 2017, to September 19, 2019.ExposuresA 2 × 2 factorial design of 2 hypothetical patients: (1) a 50-year-old white woman with hypertension, type 2 diabetes, hyperlipidemia, obesity, a 30-pack-year history of smoking, and a family history of breast cancer; and (2) a 45-year-old black man with hypertension, hyperlipidemia, obesity, a 30-pack-year history of smoking, and a family history of colorectal cancer. Two visit lengths (40 minutes vs 20 minutes) were given. Each patient was eligible for at least 11 preventive services.Main outcomes and measuresPhysicians rated their likelihood of discussing each service during the visit and reported their top 3 priorities for patients 1 and 2. Physician choices were compared with the preventive services most likely to improve life expectancy, using a previously published mathematical model.ResultsOf 241 physicians, 137 responded (57%), of whom 74 (54%) were female and 85 (62%) were younger than 50 years. Physicians agreed they prioritized preventive services (mean score, 4.27 [95% CI, 4.12-4.42] of 5.00), mostly by ability to improve quality (4.56 [95% CI, 4.44-4.68] of 5.00) or length (4.53 [95% CI, 4.40-4.66] of 5.00) of life. Physicians reported more prioritization in the 20- vs 40-minute visit, indicating that they were likely to discuss fewer services during the shorter visit (median, 5 [interquartile range {IQR}, 3-8] vs 11 [IQR, 9-13] preventive services for patient 1, and 4 [IQR, 3-6] vs 9 [IQR, 8-11] for patient 2). Physicians reported similar top 3 priorities for both patients: smoking cessation, hypertension control, and glycemic control for patient 1 and smoking cessation, hypertension control, and colorectal cancer screening for patient 2. Physicians' top 3 priorities did not usually include diet and exercise or weight loss (ranked in their top 3 recommendations for either patient by only 48 physicians [35%]), although these were among the 3 preventive services most likely to improve life expectancy based on the mathematical model.Conclusions and relevanceIn this survey study, physicians prioritized preventive services under time constraints, but priorities did not vary across patients. Physicians did not prioritize lifestyle interventions despite large potential benefits. Future research should consider whether physicians and patients would benefit from guidance on preventive care priorities.

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Use of a Preventive Index to Examine Clinic-Level Factors Associated With Delivery of Preventive Care.

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Use of a Preventive Index to Examine Clinic-Level Factors Associated With Delivery of Preventive Care.

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