Association between severe acute respiratory syndrome coronavirus 2 antibody status and reinfection: A case-control study nested in a Colorado-based prospective cohort study.

The association between the presence of detectable antibodies to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and SARS-CoV-2 reinfection is not well established. The objective of this study was to determine the association between antibody seronegativity and reinfection. METHODS: Participants in Colorado, USA, were recruited between June 15, 2020, and March 28, 2021, and encouraged to complete SARS-CoV-2 molecular ribonucleic acid (RNA) and serology testing for antibodies every 28 days for 10 months. Participants with reinfections (positive SARS-CoV-2 RNA test ≥ 90 days after the first positive RNA test) were matched to controls without reinfections by age, sex, date of the first positive RNA test, date of the last serology test, and serology test type. Using conditional logistic regression, case patients were compared to control patients on the last serologic test result, with adjustment for demographic and clinical confounders. RESULTS: The cohort (n = 4,235) included 2,033 participants with ≥ 1 positive RNA test, of whom 120 had reinfection. Among the 80 case patients who could be matched, the last serologic test was negative in 12 of the cases (15.0 %) whereas the last serologic test was negative in 77 of 1,034 (7.5 %) controls. Seronegativity (adjusted OR [aOR] 2.24; 95 % CI 1.07, 4.68), Hispanic ethnicity (aOR 1.87; 95 % 1.10, 3.18), and larger household size (aOR 1.15; 95 % 1.01, 1.30 for each additional household member) were associated with reinfection. CONCLUSIONS: Seronegative status, Hispanic ethnicity, and increasing household size were associated with reinfection. Serologic testing could be considered to reduce vaccine hesitancy in higher risk populations.

Factors Associated With Opting Out of Automated Text and Telephone Messages Among Adult Members of an Integrated Health Care System.

Importance: Health care systems deliver automated text or telephone messages to remind patients of appointments and to provide health information. Patients who receive multiple messages may demonstrate message fatigue by opting out of future messages. Objective: To assess whether the volume of automated text or interactive voice response (IVR) telephone messages is associated with the likelihood of patients requesting to opt out of future messages. Design, Setting, and Participants: This retrospective cohort study was conducted at Kaiser Permanente Colorado (KPCO), an integrated health care system. All adult members who received 1 or more automated text or IVR message between October 1, 2018, and September 30, 2019, were included. Exposures: Receipt of automated text or IVR messages. Main Outcomes and Measures: Message volume and opt-out rates obtained from messaging systems over 1 year. Results: Of the 428 242 adults included in this study, 59.7% were women, and 66.5% were White; the mean (SD) age was 52.3 (17.7) years. During the study period, 84.1% received 1 or more text messages (median, 4 messages; interquartile range, 2-8 messages) and 67.8% received 1 or more IVR messages (median, 3 messages; interquartile range, 1-6 messages). A total of 8929 individuals (2.5%) opted out of text messages, and 4392 (1.5%) opted out of IVR messages. In multivariable analyses, individuals who received 10 to 19.9 or 20 or more text messages per year had higher opt-out rates for text messages compared with those who received fewer than 2 messages per year (adjusted odds ratio [aOR]: 10-19.9 vs <2 messages, 1.27 [95% CI, 1.17-1.38]; ≥20 vs <2 messages, 3.58 [95% CI, 3.28-3.91]), whereas opt-out rates increased progressively in association with IVR message volume, with the highest rates among individuals who received 10.0 to 19.9 messages (aOR, 11.11; 95% CI, 9.43-13.08) or 20.0 messages or more (aOR, 49.84; 95% CI, 42.33-58.70). Individuals opting out of text messages were more likely to opt out of IVR messages (aOR, 4.07; 95% CI, 3.65-4.55), and those opting out of IVR messages were more likely to opt out of text messages (aOR, 5.92; 95% CI, 5.29-6.61). Conclusions and Relevance: In this cohort study among adult members of an integrated health care system, requests to discontinue messages were associated with greater message volume. These findings suggest that, to preserve the benefits of automated outreach, health care systems should use these messages judiciously to reduce message fatigue.

Geospatial Monitoring of Body Mass Index: Use of Electronic Health Record Data Across Health Care Systems.

OBJECTIVES: The Colorado BMI Monitoring System was developed to assess geographic (ie, census tract) patterns of obesity prevalence rates among children and adults in the Denver-metropolitan region. This project also sought to assess the feasibility of a surveillance system that integrates data across multiple health care and governmental organizations. MATERIALS AND METHODS: We extracted data on height and weight measures, obtained through routine clinical care, from electronic health records (EHRs) at multiple health care sites. We selected sites from 5 Denver health care systems and collected data from visits that occurred between January 1, 2013, and December 31, 2015. We produced shaded maps showing observed obesity prevalence rates by census tract for various geographic regions across the Denver-metropolitan region. RESULTS: We identified clearly distinguishable areas by higher rates of obesity among children than among adults, with several pockets of lower body mass index. Patterns for adults were similar to patterns for children: the highest obesity prevalence rates were concentrated around the central part of the metropolitan region. Obesity prevalence rates were moderately higher along the western and northern areas than in other parts of the study region. PRACTICE IMPLICATIONS: The Colorado BMI Monitoring System demonstrates the feasibility of combining EHRs across multiple systems for public health and research. Challenges include ensuring de-duplication across organizations and ensuring that geocoding is performed in a consistent way that does not pose a risk for patient privacy.

Estimating Childhood Obesity Prevalence in Communities Through Multi-institutional Data Sharing.

CONTEXT: Although local childhood obesity prevalence estimates would be valuable for planning and evaluating obesity prevention efforts in communities, these data are often unavailable. OBJECTIVE: The primary objective was to create a multi-institutional system for sharing electronic health record (EHR) data to produce childhood obesity prevalence estimates at the census tract level. A secondary objective was to adjust obesity prevalence estimates to population demographic characteristics. DESIGN/SETTING/PARTICIPANTS: The study was set in Denver County, Colorado. Six regional health care organizations shared EHR-derived data from 2014 to 2016 with the state health department for children and adolescents 2 to 17 years of age. The most recent height and weight measured during routine care were used to calculate body mass index (BMI); obesity was defined as BMI of 95th percentile or more for age and sex. Census tract location was determined using residence address. Race/ethnicity was imputed when missing, and obesity prevalence estimates were adjusted by sex, age group, and race/ethnicity. MAIN OUTCOME MEASURE(S): Adjusted obesity prevalence estimates, overall, by demographic characteristics and by census tract. RESULTS: BMI measurements were available for 89 264 children and adolescents in Denver County, representing 73.9% of the population estimate from census data. Race/ethnicity was missing for 4.6%. The county-level adjusted childhood obesity prevalence estimate was 13.9% (95% confidence interval, 13.6-14.1). Adjusted obesity prevalence was higher among males, those 12 to 17 years of age, and those of Hispanic race/ethnicity. Adjusted obesity prevalence varied by census tract (range, 0.4%-24.7%). Twelve census tracts had an adjusted obesity prevalence of 20% or more, with several contiguous census tracts with higher childhood obesity occurring in western areas of the city. CONCLUSIONS: It was feasible to use a system of multi-institutional sharing of EHR data to produce local childhood obesity prevalence estimates. Such a system may provide useful information for communities when implementing obesity prevention programs.

Improvements in access and care through the Affordable Care Act.

OBJECTIVES: To examine the impact of enrolling in a healthcare plan through the Affordable Care Act (ACA) healthcare exchanges on self-reported access to care. STUDY DESIGN: Cohort study using self-reported data of patients newly enrolled in Kaiser Permanente California and Kaiser Permanente Colorado through the ACA healthcare exchanges for coverage beginning January 1, 2014. METHODS: Baseline and follow-up surveys conducted via mail and telephone, with response rates of 45% and 51%, respectively. RESULTS: We found significant increases in the percentage of people who reported having a personal healthcare provider (59% vs 73%; P <.01) and significant decreases in those who reported delaying needed medical care due to costs (37% vs 25%; P <.01) before and after ACA enrollment. There was also a significant increase in the percentage of patients who reported receiving a flu shot during the prior year (41% vs 52%; P <.01). Among the people who reported having less than 4 months of healthcare coverage in 2013, these improvements were even more pronounced. This group also showed significant increases in the percentages who felt they had a place to go when they needed medical care (43% vs 56%; P <.01) and who reported they received advice to quit smoking or using tobacco (46% vs 72%; P <.05). CONCLUSIONS: These findings are an important addition to the evidence base that the ACA is improving the healthcare experience and reducing barriers due to costs for individuals obtaining insurance coverage through the healthcare exchanges.

The Spatial Distribution of Adult Obesity Prevalence in Denver County, Colorado: An Empirical Bayes Approach to Adjust EHR-Derived Small Area Estimates.

OBJECTIVES: Measuring obesity prevalence across geographic areas should account for environmental and socioeconomic factors that contribute to spatial autocorrelation, the dependency of values in estimates across neighboring areas, to mitigate the bias in measures and risk of type I errors in hypothesis testing. Dependency among observations across geographic areas violates statistical independence assumptions and may result in biased estimates. Empirical Bayes (EB) estimators reduce the variability of estimates with spatial autocorrelation, which limits the overall mean square-error and controls for sample bias. METHODS: Using the Colorado Body Mass Index (BMI) Monitoring System, we modeled the spatial autocorrelation of adult (≥ 18 years old) obesity (BMI ≥ 30 kg m2) measurements using patient-level electronic health record data from encounters between January 1, 2009, and December 31, 2011. Obesity prevalence was estimated among census tracts with >=10 observations in Denver County census tracts during the study period. We calculated the Moran's I statistic to test for spatial autocorrelation across census tracts, and mapped crude and EB obesity prevalence across geographic areas. RESULTS: In Denver County, there were 143 census tracts with 10 or more observations, representing a total of 97,710 adults with a valid BMI. The crude obesity prevalence for adults in Denver County was 29.8 percent (95% CI 28.4-31.1%) and ranged from 12.8 to 45.2 percent across individual census tracts. EB obesity prevalence was 30.2 percent (95% CI 28.9-31.5%) and ranged from 15.3 to 44.3 percent across census tracts. Statistical tests using the Moran's I statistic suggest adult obesity prevalence in Denver County was distributed in a non-random pattern. Clusters of EB obesity estimates were highly significant (alpha=0.05) in neighboring census tracts. Concentrations of obesity estimates were primarily in the west and north in Denver County. CONCLUSIONS: Statistical tests reveal adult obesity prevalence exhibit spatial autocorrelation in Denver County at the census tract level. EB estimates for obesity prevalence can be used to control for spatial autocorrelation between neighboring census tracts and may produce less biased estimates of obesity prevalence.

Applying Sequential Analytic Methods to Self-Reported Information to Anticipate Care Needs.

PURPOSE: Identifying care needs for newly enrolled or newly insured individuals is important under the Affordable Care Act. Systematically collected patient-reported information can potentially identify subgroups with specific care needs prior to service use. METHODS: We conducted a retrospective cohort investigation of 6,047 individuals who completed a 10-question needs assessment upon initial enrollment in Kaiser Permanente Colorado (KPCO), a not-for-profit integrated delivery system, through the Colorado State Individual Exchange. We used responses from the Brief Health Questionnaire (BHQ), to develop a predictive model for cost for receiving care in the top 25 percent, then applied cluster analytic techniques to identify different high-cost subpopulations. Per-member, per-month cost was measured from 6 to 12 months following BHQ response. RESULTS: BHQ responses significantly predictive of high-cost care included self-reported health status, functional limitations, medication use, presence of 0-4 chronic conditions, self-reported emergency department (ED) use during the prior year, and lack of prior insurance. Age, gender, and deductible-based insurance product were also predictive. The largest possible range of predicted probabilities of being in the top 25 percent of cost was 3.5 percent to 96.4 percent. Within the top cost quartile, examples of potentially actionable clusters of patients included those with high morbidity, prior utilization, depression risk and financial constraints; those with high morbidity, previously uninsured individuals with few financial constraints; and relatively healthy, previously insured individuals with medication needs. CONCLUSIONS: Applying sequential predictive modeling and cluster analytic techniques to patient-reported information can identify subgroups of individuals within heterogeneous populations who may benefit from specific interventions to optimize initial care delivery.

Characteristics of Newly Enrolled Members of an Integrated Delivery System after the Affordable Care Act.

Of 89,289 newly enrolled non-Medicare members, 25.3% completed the Brief Health Questionnaire between 1/1/2014, and 8/31/2014. Of these, 3593 respondents were insured through Medicaid, 9434 through the individual health exchange, and 9521 through primarily commercial plans. Of Medicaid, exchange, and commercial members, 19.5%, 7.1%, and 5.3%, respectively, self-reported fair or poor health; 12.9%, 2.0%, and 3.3% of each group self-reported 2 or more Emergency Department visits during the previous year; and 8.1%, 4.3%, and 4.4% self-reported an inpatient admission during the previous year.

Parents' acceptance of adolescent immunizations outside of the traditional medical home.

PURPOSE: Numerous barriers to vaccination exist for adolescents. Using the medical home as the sole source of adolescent vaccination has potential limitations. The objectives of the present study were to examine parents' acceptance of adolescent vaccination outside of the medical home and parents' preferred setting for adolescent vaccination. METHODS: A standardized, pilot-tested telephone survey was administered to a stratified random sample (n = 1,998) of Colorado households between August 2007 and February 2008. Households with English-speaking parents and adolescent(s) aged 11-17 years were eligible. RESULTS: Survey response rate was 43%; there were no significant differences between respondents and nonrespondents for three known demographic variables. Although most parents (78%) preferred a doctor's office for adolescent vaccination, a majority were also definitively or probably accepting of vaccination in public health clinics (74%), school health clinics (70%), obstetrics and gynecology clinics (69%; asked for females only), and emergency departments (67%). Parents were less accepting of vaccination in family planning clinics (41%) and retail-based clinics (36%). Perceived convenience and adolescents' comfort in the setting were positively associated with vaccination acceptance in most settings; concern with keeping track of vaccines given outside of the medical home was negatively associated with acceptance. Parents in rural areas were more likely than parents in urban areas to identify a setting outside of the medical home as the preferred "best" setting for vaccination. CONCLUSIONS: Most parents assessed a doctors' office as the best setting for adolescent vaccination. However, vaccination in certain settings outside of the medical home seems to be acceptable to many parents.

Influenza vaccine delivery delays from the perspective of primary care physicians.

BACKGROUND: The effects of delayed influenza vaccine delivery on primary practices are currently unknown. PURPOSE: To describe, among primary care physicians nationally regarding the 2006-2007 influenza season: (1) how physicians defined influenza vaccine delay; (2) the extent of reported vaccine delays; and (3) the perceived effects of vaccine delays. METHODS: Between March and June 2007, a total of 1268 primary care physicians nationally were surveyed. RESULTS: Survey response was 74% (n=940). The majority of physicians (79%) defined "influenza vaccine delay" as not receiving vaccine by November 1. Fifty-three percent reported a vaccine delay. Providers reported the following as effects of delays: reduced satisfaction of patients or parents in the practice (72%); decreased percentage in their practice who received the vaccination (65%); disruption of scheduling influenza clinics (55%); increased referral of patients elsewhere for vaccination (55%); and negative financial impact caused by unused vaccine (46%). Those who reported experiencing delays more often reported not meeting demand for vaccine (adjusted risk ratio [ARR]=1.83, 95% CI=1.64, 2.07); that grocery stores, retail outlets, or pharmacies had vaccine before their practices did (ARR=1.82, 95% CI=1.53, 2.26); not receiving all vaccine that was ordered (ARR=1.19, 95% CI=1.06, 1.36); and having leftover vaccine (ARR=1.17, 95% CI=1.04, 1.32). CONCLUSIONS: During the 2006-2007 influenza season, a non-shortage season, the majority of respondents reported experiencing an influenza vaccine delivery delay. Experiencing a delay was thought to decrease vaccination use, increase referrals elsewhere, and have a negative financial impact on practices. Delayed delivery of influenza vaccine is disruptive for primary care practices, and it consequently may affect vaccination coverage.

Physician practices regarding adult hepatitis B vaccination: a national survey.

BACKGROUND: Less than 50% of adults with risk factors for hepatitis B infection have been vaccinated. Although primary care settings typically serve an important role in immunization delivery, little is known about adult hepatitis B vaccination practices in primary care, including the use of strategies such as standing orders to improve immunization rates. The objectives of this study were to assess, among family physicians and general internists, current approaches to assessing adult patients for hepatitis B risk factors, reported hepatitis B vaccination practices, and attitudes about standing orders for hepatitis B vaccination. METHODS: From September to November 2006, a national sample of 433 family physicians and 420 general internists were surveyed. Results were analyzed in 2007 and 2008. RESULTS: Response rates were 65% for family physicians and 79% for general internists. Thirty-one percent of physicians reported assessing most or all adult patients for hepatitis B risk factors and vaccinating patients identified as high risk. Perceived barriers to hepatitis B vaccination included patients not disclosing high-risk behaviors, lack of adequate reimbursement for vaccination, and feeling too pressed for time to assess risk factors. Most surveyed physicians were very (47%) or somewhat (38%) supportive of using standing orders for hepatitis B vaccination in their practices. However, staff time constraints and patient unwillingness to disclose sensitive information to staff were perceived as barriers to using standing orders by a majority of respondents. CONCLUSIONS: In a national survey, less than one third of primary care physicians reported routinely assessing for and vaccinating adults with hepatitis B risk factors. This finding suggests that new strategies for adult hepatitis B vaccination in primary care settings are needed. Most physicians supported using standing orders for vaccination, but barriers were anticipated.