Game-based learning to improve diagnostic accuracy: a pilot randomized-controlled trial.

OBJECTIVES: Perform a pilot study of online game-based learning (GBL) using natural frequencies and feedback to teach diagnostic reasoning. METHODS: We conducted a multicenter randomized-controlled trial of computer-based training. We enrolled medical students, residents, practicing physicians and nurse practitioners. The intervention was a 45 min online GBL training vs. control education with a primary outcome of score on a scale of diagnostic accuracy (composed of 10 realistic case vignettes, requesting estimates of probability of disease after a test result, 0-100 points total). RESULTS: Of 90 participants there were 30 students, 30 residents and 30 practicing clinicians. Of these 62 % (56/90) were female and 52 % (47/90) were white. Sixty were randomized to GBL intervention and 30 to control. The primary outcome of diagnostic accuracy immediately after training was better in GBL (mean accuracy score 59.4) vs. control (37.6), p=0.0005. The GBL group was then split evenly (30, 30) into no further intervention or weekly emails with case studies. Both GBL groups performed better than control at one-month and some continued effect at three-month follow up. Scores at one-month GBL (59.2) GBL plus emails (54.2) vs. control (33.9), p=0.024; three-months GBL (56.2), GBL plus emails (42.9) vs. control (35.1), p=0.076. Most participants would recommend GBL to colleagues (73 %), believed it was enjoyable (92 %) and believed it improves test interpretation (95 %). CONCLUSIONS: In this pilot study, a single session with GBL nearly doubled score on a scale of diagnostic accuracy in medical trainees and practicing clinicians. The impact of GBL persisted after three months.

Clinician Testing and Treatment Thresholds for Management of Urinary Tract Infection.

Greater understanding of clinical decision thresholds may improve inappropriate testing and treatment of urinary tract infection (UTI). We used a survey of clinicians to examine UTI decision thresholds. Although overestimates of UTI occurred, testing and treatment thresholds were generally rational, were lower than previously reported, and differed by type of clinician.

The Impact of Universal Glove and Gown Use on Clostridioides Difficile Acquisition: A Cluster-Randomized Trial.

BACKGROUND: Clostridioides difficile is the most common cause of healthcare-associated infections in the United States. It is unknown whether universal gown and glove use in intensive care units (ICUs) decreases acquisition of C. difficile. METHODS: This was a secondary analysis of a cluster-randomized trial in 20 medical and surgical ICUs in 20 US hospitals from 4 January 2012 to 4 October 2012. After a baseline period, ICUs were randomized to standard practice for glove and gown use versus the intervention of all healthcare workers being required to wear gloves and gowns for all patient contact and when entering any patient room (contact precautions). The primary outcome was acquisition of toxigenic C. difficile determined by surveillance cultures collected on admission and discharge from the ICU. RESULTS: A total of 21 845 patients had both admission and discharge perianal swabs cultured for toxigenic C. difficile. On admission, 9.43% (2060/21 845) of patients were colonized with toxigenic C. difficile. No significant difference was observed in the rate of toxigenic C. difficile acquisition with universal gown and glove use. Differences in acquisition rates in the study period compared with the baseline period in control ICUs were 1.49 per 100 patient-days versus 1.68 per 100 patient-days in universal gown and glove ICUs (rate difference, -0.28; generalized linear mixed model, P = .091). CONCLUSIONS: Glove and gown use for all patient contact in medical and surgical ICUs did not result in a reduction in the acquisition of C. difficile compared with usual care. CLINICAL TRIALS REGISTRATION: NCT01318213.

Impact of psychological resilience on walking capacity in older adults following hip fracture.

BACKGROUND: Community-dwelling older adults experiencing hip fracture often fail to achieve adequate walking capacity following surgery and rehabilitation. Effects of psychological factors on post-fracture walking capacity are poorly understood. Accordingly, this paper investigates effects of psychological resilience on observed walking capacity measures in older adults following hip fracture, controlling for important covariates. METHODS: Data were drawn from the Community Ambulation Project, a clinical trial of 210 community-dwelling adults aged ≥60 years who experienced a minimal trauma hip fracture and were randomized to one of two 16-week home-based physical therapist-guided interventions. Psychological resilience was measured at study baseline using the 6-item Brief Resilience Scale (BRS); scores were classified into groups in order to distinguish levels of self-reported resilience. Walking capacity was assessed at study baseline and 16 weeks later using 4-Meter Gait Speed (4MGS), 50-Foot Walk Test (50FWT), and 6-Minute Walk Distance (SMWD). In multivariate analyses of covariance in which 16-week follow-up values of each walking measure were outcomes, covariates included clinical trial arm, gender, age, and baseline values of: walking measure corresponding to the outcome; body mass index; depressive symptom severity; degree of psychological optimism; cognitive status; informal caregiver need; and days from hospital admission to randomization. RESULTS: Increases between baseline and 16 weeks later in mean gait speed in meters/sec (m/s) and walking distance in meters (m) in 4MGS, 50FWT and SMWD were 0.06 m/s (p = 0.061), 0.11 m/s (p < 0.01), and 25.5 m (p = 0.056) greater, respectively, in the most resilient BRS group compared to the least resilient BRS group. CONCLUSION: Higher levels of psychological resilience were associated with greater walking speed and distance. Psychological resilience represents a potentially clinically important pathway and intervention target, toward the goal of improving walking capacity among older adults known to have substantial residual disability following hip fracture.

Exploration of Primary Care Clinician Attitudes and Cognitive Characteristics Associated With Prescribing Antibiotics for Asymptomatic Bacteriuria.

Importance: Antibiotic treatment for asymptomatic bacteriuria is not recommended in guidelines but is a major driver of inappropriate antibiotic use. Objective: To evaluate whether clinician culture and personality traits are associated with a predisposition toward inappropriate prescribing. Design, Setting, and Participants: This survey study involved secondary analysis of a previously completed survey. A total of 723 primary care clinicians in active practice in Texas, the Mid-Atlantic, and the Pacific Northwest, including physicians and advanced practice clinicians, were surveyed from June 1, 2018, to November 26, 2019, regarding their approach to a hypothetical patient with asymptomatic bacteriuria. Clinician culture was represented by training background and region of practice. Attitudes and cognitive characteristics were represented using validated instruments to assess numeracy, risk-taking preferences, burnout, and tendency to maximize care. Data were analyzed from November 8, 2021, to March 29, 2022. Interventions: The survey described a male patient with asymptomatic bacteriuria and changes in urine character. Clinicians were asked to indicate whether they would prescribe antibiotics. Main Outcomes and Measures: The main outcome was self-reported willingness to prescribe antibiotics for asymptomatic bacteriuria. Willingness to prescribe antibiotics was hypothesized to be associated with clinician characteristics, background, and attitudes, including orientation on the Medical Maximizer-Minimizer Scale. Individuals with a stronger orientation toward medical maximizing prefer treatment even when the value of treatment is ambiguous. Results: Of the 723 enrolled clinicians, 551 (median age, 32 years [IQR, 29-44 years]; 292 [53%] female; 296 [54%] White) completed the survey (76% response rate), including 288 resident physicians, 202 attending physicians, and 61 advanced practice clinicians. A total of 303 respondents (55%) were from the Mid-Atlantic, 136 (25%) were from Texas, and 112 (20%) were from the Pacific Northwest. A total of 392 clinicians (71% of respondents) indicated that they would prescribe antibiotic treatment for asymptomatic bacteriuria in the absence of an indication. In multivariable analyses, clinicians with a background in family medicine (odds ratio [OR], 2.93; 95% CI, 1.53-5.62) or a high score on the Medical Maximizer-Minimizer Scale (indicating stronger medical maximizing orientation; OR, 2.06; 95% CI, 1.38-3.09) were more likely to prescribe antibiotic treatment for asymptomatic bacteriuria. Resident physicians (OR, 0.57; 95% CI, 0.38-0.85) and clinicians in the Pacific Northwest (OR, 0.49; 95% CI, 0.33-0.72) were less likely to prescribe antibiotics for asymptomatic bacteriuria. Conclusions and Relevance: The findings of this survey study suggest that most primary care clinicians prescribe inappropriate antibiotic treatment for asymptomatic bacteriuria in the absence of risk factors. This tendency is more pronounced among family medicine physicians and medical maximizers and is less common among resident physicians and clinicians in the US Pacific Northwest. Clinician characteristics should be considered when designing antibiotic stewardship interventions.

Prediction of treatment nonadherence among older adults with chronic obstructive pulmonary disease using Medicare real-world data.

BACKGROUND: Suboptimal maintenance medication (MM) adherence remains a clinical problem among Medicare beneficiaries with chronic obstructive pulmonary disease (COPD). OBJECTIVE: To inform risk-based personalized decision-making, this study sought to develop and validate prediction models of nonadherence to COPD MMs for Medicare beneficiaries. METHODS: This was a retrospective cohort study of beneficiaries aged 65 years and older with COPD and inhaled MMs. Nonadherence (proportion of days covered < 0.8) was measured in 12 months following the first MM fill after COPD diagnosis. Logistic and least absolute shrinkage selector operator regressions were implemented, and area under the receiver operating characteristic curve (AUROC) evaluated model accuracy, as well as positive predictive values and negative predictive values. Our models evaluated different sets of predictors for two cohorts: those with an MM prescription before COPD diagnosis (prevalent users) and those without (new users). RESULTS: Among 16,157 prevalent and 40,279 new users of MMs, 11,271 (69.8%) and 34,009 (84.4%), respectively, were nonadherent. The best-performing logistic models achieved AUROCs of 0.8714 and 0.881, positive predictive values of 0.881 and 0.881, and negative predictive values of 0.559 and 0.578, respectively, for prevalent and new users. The least absolute shrinkage selector operator models had similar accuracy. Models with baseline-only predictors had average performance (AUROC < 0.72). The most important predictors were initial MM adherence, short-acting bronchodilator use, and asthma. CONCLUSIONS: To our knowledge, this study is the first to develop predictive models of nonadherence to COPD MMs. Generated models achieved good discrimination and underlined the importance of early adherence. Well-performed models can be useful for care decision-making and interventions to improve COPD medication adherence after the first critical few months following a treatment episode. DISCLOSURES: All authors declared no conflicts of interest.

Clinician Attitudes and Beliefs Associated with More Aggressive Diagnostic Testing.

BACKGROUND: Variation in clinicians' diagnostic test utilization is incompletely explained by demographics and likely relates to cognitive characteristics. We explored clinician factors associated with diagnostic test utilization. METHODS: We used a self-administered survey of attitudes, cognitive characteristics, and reported likelihood of test ordering in common scenarios; frequency of lipid and liver testing in patients on statin therapy. Participants were 552 primary care physicians, nurse practitioners, and physician assistants from practices in 8 US states across 3 regions, from June 1, 2018 to November 26, 2019. We measured Testing Likelihood Score: the mean of 4 responses to testing frequency and self-reported testing frequency in patients on statins. RESULTS: Respondents were 52.4% residents, 36.6% attendings, and 11.0% nurse practitioners/physician assistants; most were white (53.6%) or Asian (25.5%). Median age was 32 years; 53.1% were female. Participants reported ordering tests for a median of 20% (stress tests) to 90% (mammograms) of patients; Testing Likelihood Scores varied widely (median 54%, interquartile range 43%-69%). Higher scores were associated with geography, training type, low numeracy, high malpractice fear, high medical maximizer score, high stress from uncertainty, high concern about bad outcomes, and low acknowledgment of medical uncertainty. More frequent testing of lipids and liver tests was associated with low numeracy, high medical maximizer score, high malpractice fear, and low acknowledgment of uncertainty. CONCLUSIONS: Clinician variation in testing was common, with more aggressive testing consistently associated with low numeracy, being a medical maximizer, and low acknowledgment of uncertainty. Efforts to reduce undue variations in testing should consider clinician cognitive drivers.

Antibiotic Use and Bacterial Infection among Inpatients in the First Wave of COVID-19: a Retrospective Cohort Study of 64,691 Patients.

Hospitalized patients with SARS-CoV-2 infection (COVID-19) often receive antibiotics for suspected bacterial coinfection. We estimated the incidence of bacterial coinfection and secondary infection in COVID-19 using clinical diagnoses to determine how frequently antibiotics are administered when bacterial infection is absent. We performed a retrospective cohort study of inpatients with COVID-19 present on admission to hospitals in the Premier Healthcare Database between April and June 2020. Bacterial infections were defined using ICD-10-CM diagnosis codes and associated "present on admission" coding. Coinfections were defined by bacterial infection present on admission, while secondary infections were defined by bacterial infection that developed after admission. Coinfection and secondary infection were not mutually exclusive. A total of 18.5% of 64,961 COVID-19 patients (n = 12,040) presented with bacterial infection at admission, 3.8% (n = 2,506) developed secondary infection after admission, and 0.9% (n = 574) had both; 76.3% (n = 49,551) received an antibiotic while hospitalized, including 71% of patients who had no diagnosis of bacterial infection. Secondary bacterial infection occurred in 5.7% of patients receiving steroids in the first 2 days of hospitalization, 9.9% receiving tocilizumab in the first 2 days of hospitalization, and 10.3% of patients receiving both. After adjusting for patient and hospital characteristics, bacterial coinfection (adjusted relative risk [aRR], 1.15; 95% confidence interval [CI], 1.11 to 1.20) and secondary infection (aRR 1.93; 95% CI, 1.82 to 2.04) were both independently associated with increased mortality. Although 1 in 5 inpatients with COVID-19 presents with bacterial infection, secondary infections in the hospital are uncommon. Most inpatients with COVID-19 receive antibiotic therapy, including 71% of those not diagnosed with bacterial infection.

Prevalence and Newly Diagnosed Rates of Multimorbidity in Older Medicare Beneficiaries with COPD.

Few studies have quantified the multimorbidity burden in older adults with chronic obstructive pulmonary disease (COPD) using large and generalizable data. Such evidence is essential to inform evidence-based research, clinical care, and resource allocation. This retrospective cohort study used a nationally representative sample of Medicare beneficiaries aged 65 years or older with COPD and 1:1 matched (on age, sex, and race) non-COPD beneficiaries to: (1) quantify the prevalence of multimorbidity at COPD onset and one-year later; (2) quantify the rates [per 100 person-years (PY)] of newly diagnosed multimorbidity during in the year prior to and in the year following COPD onset; and (3) compare multimorbidity prevalence in beneficiaries with and without COPD. Among 739,118 eligible beneficiaries with and without COPD, the average number of multimorbidity was 10.0 (SD = 4.7) and 1.0 (SD = 3.3), respectively. The most prevalent multimorbidity at COPD onset and at one-year after, respectively, were hypertension (70.8% and 80.2%), hyperlipidemia (52.2% and 64.8%), anemia (42.1% and 52.0%), arthritis (39.8% and 47.7%), and congestive heart failure (CHF) (31.3% and 38.8%). Conditions with the highest newly diagnosed rates before and following COPD onset, respectively, included hypertension (39.8 and 32.3 per 100 PY), hyperlipidemia (22.8 and 27.6), anemia (17.8 and 20.3), CHF (16.2 and 13.2), and arthritis (12.9 and 13.2). COPD was significantly associated with increased odds of all measured conditions relative to non-COPD controls. This study updates existing literature with more current, generalizable findings of the substantial multimorbidity burden in medically complex older adults with COPD-necessary to inform patient-centered, multidimensional care.Supplemental data for this article is available online at https://doi.org/10.1080/15412555.2021.1968815 .

Clinician Conceptualization of the Benefits of Treatments for Individual Patients.

Importance: Knowing the expected effect of treatment on an individual patient is essential for patient care. Objective: To explore clinicians' conceptualizations of the chance that treatments will decrease the risk of disease outcomes. Design, Setting, and Participants: This survey study of attending and resident physicians, nurse practitioners, and physician assistants was conducted in outpatient clinical settings in 8 US states from June 2018 to November 2019. The survey was an in-person, paper, 26-item survey in which clinicians were asked to estimate the probability of adverse disease outcomes and expected effects of therapies for diseases common in primary care. Main Outcomes and Measures: Estimated chance that treatments would benefit an individual patient. Results: Of 723 clinicians, 585 (81%) responded, and 542 completed all the questions necessary for analysis, with a median (interquartile range [IQR]) age of 32 (29-44) years, 287 (53%) women, and 294 (54%) White participants. Clinicians consistently overestimated the chance that treatments would benefit an individual patient. The median (IQR) estimated chance that warfarin would prevent a stroke in the next year was 50% (5%-80%) compared with scientific evidence, which indicates an absolute risk reduction (ARR) of 0.2% to 1.0% based on a relative risk reduction (RRR) of 39% to 50%. The median (IQR) estimated chance that antihypertensive therapy would prevent a cardiovascular event within 5 years was 30% (10%-70%) vs evidence of an ARR of 0% to 3% based on an RRR of 0% to 28%. The median (IQR) estimated chance that bisphosphonate therapy would prevent a hip fracture in the next 5 years was 40% (10%-60%) vs evidence of ARR of 0.1% to 0.4% based on an RRR of 20% to 40%. The median (IQR) estimated chance that moderate-intensity statin therapy would prevent a cardiovascular event in the next 5 years was 20% (IQR 5%-50%) vs evidence of an ARR of 0.3% to 2% based on an RRR of 19% to 33%. Estimates of the chance that a treatment would prevent an adverse outcome exceeded estimates of the absolute chance of that outcome for 60% to 70% of clinicians. Clinicians whose overestimations were greater were more likely to report using that treatment for patients in their practice (eg, use of warfarin: correlation coefficient, 0.46; 95% CI, 0.40-0.53; P < .001). Conclusions and Relevance: In this survey study, clinicians significantly overestimated the benefits of treatment to individual patients. Clinicians with greater overestimates were more likely to report using treatments in actual patients.

Accuracy of Practitioner Estimates of Probability of Diagnosis Before and After Testing.

Importance: Accurate diagnosis is essential to proper patient care. Objective: To explore practitioner understanding of diagnostic reasoning. Design, Setting, and Participants: In this survey study, 723 practitioners at outpatient clinics in 8 US states were asked to estimate the probability of disease for 4 scenarios common in primary care (pneumonia, cardiac ischemia, breast cancer screening, and urinary tract infection) and the association of positive and negative test results with disease probability from June 1, 2018, to November 26, 2019. Of these practitioners, 585 responded to the survey, and 553 answered all of the questions. An expert panel developed the survey and determined correct responses based on literature review. Results: A total of 553 (290 resident physicians, 202 attending physicians, and 61 nurse practitioners and physician assistants) of 723 practitioners (76.5%) fully completed the survey (median age, 32 years; interquartile range, 29-44 years; 293 female [53.0%]; 296 [53.5%] White). Pretest probability was overestimated in all scenarios. Probabilities of disease after positive results were overestimated as follows: pneumonia after positive radiology results, 95% (evidence range, 46%-65%; comparison P < .001); breast cancer after positive mammography results, 50% (evidence range, 3%-9%; P < .001); cardiac ischemia after positive stress test result, 70% (evidence range, 2%-11%; P < .001); and urinary tract infection after positive urine culture result, 80% (evidence range, 0%-8.3%; P < .001). Overestimates of probability of disease with negative results were also observed as follows: pneumonia after negative radiography results, 50% (evidence range, 10%-19%; P < .001); breast cancer after negative mammography results, 5% (evidence range, <0.05%; P < .001); cardiac ischemia after negative stress test result, 5% (evidence range, 0.43%-2.5%; P < .001); and urinary tract infection after negative urine culture result, 5% (evidence range, 0%-0.11%; P < .001). Probability adjustments in response to test results varied from accurate to overestimates of risk by type of test (imputed median positive and negative likelihood ratios [LRs] for practitioners for chest radiography for pneumonia: positive LR, 4.8; evidence, 2.6; negative LR, 0.3; evidence, 0.3; mammography for breast cancer: positive LR, 44.3; evidence range, 13.0-33.0; negative LR, 1.0; evidence range, 0.05-0.24; exercise stress test for cardiac ischemia: positive LR, 21.0; evidence range, 2.0-2.7; negative LR, 0.6; evidence range, 0.5-0.6; urine culture for urinary tract infection: positive LR, 9.0; evidence, 9.0; negative LR, 0.1; evidence, 0.1). Conclusions and Relevance: This survey study suggests that for common diseases and tests, practitioners overestimate the probability of disease before and after testing. Pretest probability was overestimated in all scenarios, whereas adjustment in probability after a positive or negative result varied by test. Widespread overestimates of the probability of disease likely contribute to overdiagnosis and overuse.

Comorbidity and severity-of-illness risk adjustment for hospital-onset Clostridioides difficile infection using data from the electronic medical record.

OBJECTIVE: To determine whether electronically available comorbidities and laboratory values on admission are risk factors for hospital-onset Clostridioides difficile infection (HO-CDI) across multiple institutions and whether they could be used to improve risk adjustment. PATIENTS: All patients at least 18 years of age admitted to 3 hospitals in Maryland between January 1, 2016, and January 1, 2018. METHODS: Comorbid conditions were assigned using the Elixhauser comorbidity index. Multivariable log-binomial regression was conducted for each hospital using significant covariates (P < .10) in a bivariate analysis. Standardized infection ratios (SIRs) were computed using current Centers for Disease Control and Prevention (CDC) risk adjustment methodology and with the addition of Elixhauser score and individual comorbidities. RESULTS: At hospital 1, 314 of 48,057 patient admissions (0.65%) had a HO-CDI; 41 of 8,791 patient admissions (0.47%) at community hospital 2 had a HO-CDI; and 75 of 29,211 patient admissions (0.26%) at community hospital 3 had a HO-CDI. In multivariable regression, Elixhauser score was a significant risk factor for HO-CDI at all hospitals when controlling for age, antibiotic use, and antacid use. Abnormal leukocyte level at hospital admission was a significant risk factor at hospital 1 and hospital 2. When Elixhauser score was included in the risk adjustment model, it was statistically significant (P < .01). Compared with the current CDC SIR methodology, the SIR of hospital 1 decreased by 2%, whereas the SIRs of hospitals 2 and 3 increased by 2% and 6%, respectively, but the rankings did not change. CONCLUSIONS: Electronically available patient comorbidities are important risk factors for HO-CDI and may improve risk-adjustment methodology.

Acquisition of Antibiotic-Resistant Gram-negative Bacteria in the Benefits of Universal Glove and Gown (BUGG) Cluster Randomized Trial.

BACKGROUND: The Benefits of Universal Glove and Gown (BUGG) cluster randomized trial found varying effects on methicillin-resistant Staphylococcus aureus and vancomycin-resistant Enterococcus and no increase in adverse events. The aim of this study was to assess whether the intervention decreases the acquisition of antibiotic-resistant gram-negative bacteria. METHODS: This was a secondary analysis of a randomized trial in 20 hospital intensive care units. The intervention consisted of healthcare workers wearing gloves and gowns when entering any patient room compared to standard care. The primary composite outcome was acquisition of any antibiotic-resistant gram-negative bacteria based on surveillance cultures. RESULTS: A total of 40 492 admission and discharge perianal swabs from 20 246 individual patient admissions were included in the primary outcome. For the primary outcome of acquisition of any antibiotic-resistant gram-negative bacteria, the intervention had a rate ratio (RR) of 0.90 (95% confidence interval [CI], .71-1.12; P = .34). Effects on the secondary outcomes of individual bacteria acquisition were as follows: carbapenem-resistant Enterobacteriaceae (RR, 0.86 [95% CI, .60-1.24; P = .43), carbapenem-resistant Acinetobacter (RR, 0.81 [95% CI, .52-1.27; P = .36), carbapenem-resistant Pseudomonas (RR, 0.88 [95% CI, .55-1.42]; P = .62), and extended-spectrum ß-lactamase-producing bacteria (RR, 0.94 [95% CI, .71-1.24]; P = .67). CONCLUSIONS: Universal glove and gown use in the intensive care unit was associated with a non-statistically significant decrease in acquisition of antibiotic-resistant gram-negative bacteria. Individual hospitals should consider the intervention based on the importance of these organisms at their hospital, effect sizes, CIs, and cost of instituting the intervention. CLINICAL TRIALS REGISTRATION: NCT01318213.

Dental care utilization and retirement.

OBJECTIVE: The authors examine the relationship of dental care coverage, retirement, and utilization in an aging population using data from the Health and Retirement Study (HRS). METHODS: The authors estimate dental care use as a function of dental care coverage status, retirement, and individual and household characteristics. They also estimate a multivariate model controlling for potentially confounding variables. RESULTS: The authors show that that the loss of income and dental coverage associated with retirement may lead to lower use rates but this effect may be offset by other unobserved aspects of retirement including more available free time leading to an overall higher use rate. CONCLUSIONS: The authors conclude from this study that full retirement accompanied by reduced income and dental insurance coverage produces lower utilization of dental services. However, they also show that retirement acts as an independent variable, whereas income, coverage, and free time (unobserved) act as intervening variables.

Dental care expenditures and retirement.

OBJECTIVES: To examine the relationship of dental care coverage, retirement, and out-of-pocket (OOP) dental expenditures in an aging population, using data from the Health and Retirement Study (HRS). METHODS: We estimate OOP dental expenditures among individuals who have dental utilization as a function of dental care coverage status, retirement, and individual and household characteristics. We also estimate a multivariate model controlling for potentially confounding variables. RESULTS: Overall, mean OOP dental expenditures among those with any spending were substantially larger for those without coverage than for those with coverage. However, controlling for coverage shows that there is little difference in spending by retirement status. CONCLUSIONS: Although having dental coverage is a key determinant of the level of OOP expenditures on dental care; spending is higher among those without coverage than those who have dental insurance. We also found that while retirement has no independent effect on OOP dental expenditures once controlling for coverage, dental coverage rates are much lower among retirees.

Dental care coverage and retirement.

OBJECTIVES: To examine the convergence of an aging population and a decreased availability of dental care coverage using data from the Health and Retirement Study (HRS). METHODS: We calculate national estimates of the number and characteristics of those persons age 51 years and above covered by dental insurance by labor force, retirement status, and source of coverage. We also estimate a multivariate model controlling for potentially confounding variables. RESULTS: We show that being in the labor force is a strong predictor of having dental coverage. For older retired adults not in the labor force, the only source for dental coverage is either a postretirement health benefit or spousal coverage. CONCLUSIONS: Dental care, generally not covered in Medicare, is an important factor in the decision to seek dental care. It is important to understand the relationship between retirement and dental coverage in order to identify the best ways of improving oral health and access to care among older Americans.

Dental care coverage transitions.

OBJECTIVE: To examine dental insurance transition dynamics in the context of changing employment and retirement status. STUDY DESIGN: Data from the Health and Retirement Study (HRS) were analyzed for individuals 51 years and older between the 2004 and 2006 waves of the HRS. METHODS: The primary focus of the analysis is the relationship between retirement and transitions in dental care coverage. We calculate and present bivariate relationships between dental coverage and retirement status transitions over time and estimate a multivariable model of dental coverage controlling for retirement and other potentially confounding covariates. RESULTS: Older adults are likely to lose their dental coverage on entering retirement compared with those who remain in the labor force between waves of the HRS. While more than half of those persons in the youngest group (51-64 years) were covered over this entire period, two-thirds of those in the oldest group (>or=75 years) were without coverage over the same period. We observe a high percentage of older persons flowing into and out of dental coverage over the period of our study, similar to flows into and out of poverty. CONCLUSIONS: Dental insurance is an important factor in the decision to seek dental care. Yet, no dental coverage is provided by Medicare, which provides medical insurance for almost all Americans 65 years and older. This loss of coverage could lead to distortions in the timing of when to seek care, ultimately leading to worse oral and overall health.

Health of community-dwelling adults with mobility limitations in the United States: incidence of secondary health conditions. Part II.

OBJECTIVE: To compare incident health conditions that occurred over a 2-year period in nationally representative groups of adults with mobility, nonmobility, and no limitations. DESIGN: Data were collected prospectively from a probability subsample of households that represent the civilian, noninstitutionalized U.S. population. SETTING: Five rounds of household interviews were conducted over 2 years. PARTICIPANTS: Data were analyzed on the same respondents from the 1996-1997 Medical Expenditure Panel Survey (MEPS) and the 1995 National Health Interview Survey Disability Supplement. Respondents were categorized into 3 groups for analysis; those with mobility limitations, nonmobility limitations, and no limitations. The analytic sample included 12,302 MEPS adults (>/=18y). INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: Number, types, and 2-year incidence of self-reported health conditions compared across groups. RESULTS: The mean number of incident conditions (95% confidence intervals [CIs]) over the 2-year period was greatest in adults with mobility limitations (mean, 4.7; 95% CI, 4.4-4.9) compared with those with nonmobility limitations (mean, 3.9; 95% CI, 3.7-4.2) or no limitations (mean, 2.6; 95% CI, 2.5-2.7). Incident conditions affected most major body systems. CONCLUSIONS: Because secondary conditions are potentially preventable, determining factors that influence their occurrence is an important public health issue requiring specific action.

Health of community-dwelling adults with mobility limitations in the United States: prevalent health conditions. Part I.

OBJECTIVE: To characterize the extent and types of prevalent health conditions among nationally representative groups of adults with mobility, nonmobility, and no limitations. DESIGN: Data were collected during 5 rounds of household interviews from a probability subsample of households that represent the civilian, noninstitutionalized U.S. population. With some exceptions, round 1 variables were used for this analysis. SETTING: Community. PARTICIPANTS: Data were analyzed on the same respondents from the 1996 to 1997 Medical Expenditure Panel Survey (MEPS) and the 1995 National Health Interview Survey Disability Supplement. Respondents were categorized into 3 groups for analysis: those with mobility limitations, nonmobility limitations; and no limitations. The analytic sample included 13,897 MEPS adults (> or =18y). INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: Number, types, and prevalence of self-reported health conditions compared across groups. RESULTS: On average, adults with mobility limitations had significantly more prevalent conditions (3.6) than those with nonmobility limitations (2.4), or no limitations (1.3). Greater comorbidity existed in the context of fewer personal resources and more than half of adults with mobility limitations were working age. CONCLUSIONS: Determining factors that influence the health of adults with mobility limitations is a critical public health issue.