Quantifying the Impact of Influenza Among Persons With Type 2 Diabetes Mellitus: A New Approach to Determine Medical and Physical Activity Impact.

BACKGROUND: We describe the impact of influenza on medical outcomes and daily activities among people with and without type 2 diabetes mellitus (T2DM). METHODS: Retrospective cohort analysis of a US health plan offering a digital wellness platform connecting wearable devices capable of tracking steps, sleep, and heart rate. For the 2016 to 2017 influenza season, we compared adults with T2DM to age and gender matched controls. Medical claims were used to define cohorts and identify influenza events and outcomes. Digital tracking data were aggregated at time slices of minute-, day-, week-, and year-level. A pre-post study design compared the peri-influenza period (two weeks before and four weeks after influenza diagnosis) to the six-week preceding period (baseline). RESULTS: A total of 54 656 T2DM and 113 016 non-DM controls were used for the study. People with T2DM had more influenza claims, vaccinations, and influenza antivirals per 100 people (1.96% vs 1.37%, 34.3% vs 24.3%, and 27.1 vs 22 respectively, P < .001). A total of 1086 persons with T2DM and 1567 controls had an influenza claim (47.4% male, median age 54, 6.4% vs 7.8% trackers, respectively). Glycemic events, pneumonia, and ischemic heart disease increased over baseline during the peri-influenza period for T2DM (1.74-, 7.4-, and 1.6-fold increase respectively, P < .01). In a device wearing subcohort, we observed 10 000 fewer steps surrounding the influenza event, with the lowest (5500 steps) two days postinfluenza. Average heart rate increased significantly (+5.5 beats per minute) one day prior to influenza. CONCLUSION: Influenza increases rates of pneumonia, heart disease, and abnormal glucose levels among people with T2DM, and negatively impacts daily activities compared to controls.

The importance of cholesterol medication adherence: the need for behavioral change intervention programs.

Lipid-lowering medications have been shown to be efficacious, but adherence is suboptimal. This is a narrative, perspective review of recently published literature in the field of medication adherence research for lipid-lowering medications. We provide an overview of the impact of suboptimal adherence and use a World Health Organization framework (patient, condition, therapy, socioeconomic, and health system-related systems) to discuss factors that influence hyperlipidemia treatment adherence. Further, the review involves an evaluation of intervention strategies to increase hyperlipidemia treatment adherence with a special focus on mHealth interventions, patient reminders on packaging labels, nurse- and pharmacist-led interventions, and health teams. It also highlights opportunities for pharmaceutical companies to support and scale such behavioral interventions. Medication adherence remains a challenge for the long-term management of chronic conditions, especially those involving asymptomatic disease such as hyperlipidemia. To engage patients and enhance motivation over time, hyperlipidemia interventions must be targeted to individual patients' needs, with sequencing and frequency of contact tailored to the various stages of behavioral change.

Patient-powered research networks aim to improve patient care and health research.

The era of big data, loosely defined as the development and analysis of large or complex data sets, brings new opportunities to empower patients and their families to generate, collect, and use their health information for both clinical and research purposes. In 2013 the Patient-Centered Outcomes Research Institute launched a large national research network, PCORnet, that includes both clinical and patient-powered research networks. This article describes these networks, their potential uses, and the challenges they face. The networks are engaging patients, family members, and caregivers in four key ways: contributing data securely, with privacy protected; including diverse and representative groups of patients in research; prioritizing research questions, participating in research, and disseminating results; and participating in the leadership and governance of patient-powered research networks. If technical, regulatory, and organizational challenges can be overcome, PCORnet will allow research to be conducted more efficiently and cost-effectively and results to be disseminated quickly back to patients, clinicians, and delivery systems to improve patient health.

High-quality health care: the essential route to eliminating disparities and achieving health equity.

In the past decade and a half, the United States has witnessed major advances in the recognition and reporting of health and health care disparities. Now is the time to move beyond describing these disparities to actually eliminating them. Because of the interlocking nature of disparities in health, disparities in health care, and the role of social determinants, there is a need to focus our efforts on one primary goal: achieving health equity by securing access for the entire population to the highest possible quality of health care. Access to high-quality care for populations of color can have the same impact as it has for majority populations: improving population health, improving patients' experiences of care, and reducing health care costs.

A review of the evidence for disparities in child vs adult health care: a disparity in disparities.

Racial and ethnic health disparities in primary care have been well documented in the US healthcare system. However, very little attention has been directed toward inequities in child health. The aim of this review is to provide context for the scope of the challenges associated with addressing pediatric health disparities in primary care by comparing the weight of evidence regarding racial/ethnic health disparities for children vs adults. A multisystem health disparities conceptual model will frame the search strategy and analysis of the review. This paper will: (1) identify knowledge deficits in the understanding of existing disparities in pediatric primary care relative to adult primary care; (2) assess root causes of disparities for children vs adults; and (3) propose recommendations for a research agenda and policy implementation to eliminate disparities in pediatric primary care.

Racial and ethnic disparities in indicators of a primary care medical home for children.

OBJECTIVE: Racial/ethnic disparities in access to care across a broad range of health services have been well established. In adults, having a medical home has been shown to reduce disparities. The objective of this study was to assess the extent to which children of different race/ethnicities receive primary care consistent with a medical home. METHODS: We conducted a secondary analysis of 84 101 children, ages 0-17, from the 2003-2004 National Survey of Children's Health, a nationwide household survey. The primary independent variable was race/ethnicity of the child. The main dependent variable was a medical home as defined by the American Academy of Pediatrics. Multiple logistic regression was conducted to investigate associations between race/ethnicity and having a medical home. RESULTS: The odds of having a medical home were lower for non-Hispanic black (odds ratio [OR] 0.76, 95% confidence interval [95% CI] 0.69-0.83), Hispanic (OR 0.80, 95% CI 0.72-0.89), and other (OR 0.77, 95% CI 0.69-0.87) children compared with non-Hispanic white children after adjusting for sociodemographic variables. Specific components of a medical home for which minority children had a lower odds (P < .01) of having compared with white children included having a personal provider, a provider who always/usually spent enough time with them, and a provider who always/usually communicated well. CONCLUSIONS: Minority children experienced multiple disparities compared with white children in having a medical home. Study of individual medical home components has the potential to identify specific areas to improve disparities.

Disparities in health care are driven by where minority patients seek care: examination of the hospital quality alliance measures.

BACKGROUND: Racial/ethnic disparities in health care are well documented, but less is known about whether disparities occur within or between hospitals for specific inpatient processes of care. We assessed racial/ethnic disparities using the Hospital Quality Alliance Inpatient Quality of Care Indicators. METHODS: We performed an observational study using patient-level data for acute myocardial infarction (5 care measures), congestive heart failure (2 measures), community-acquired pneumonia (2 measures), and patient counseling (4 measures). Data were obtained from 123 hospitals reporting to the University HealthSystem Consortium from the third quarter of 2002 to the first quarter of 2005. A total of 320,970 patients 18 years or older were eligible for at least 1 of the 13 measures. RESULTS: There were consistent unadjusted differences between minority and nonminority patients in the quality of care across 8 of 13 quality measures (from 4.63 and 4.55 percentage points for angiotensin-converting enzyme inhibitors for acute myocardial infarction and congestive heart failure [P<.01] to 14.58 percentage points for smoking cessation counseling for pneumonia [P=.02]). Disparities were most pronounced for counseling measures. In multivariate models adjusted for individual patient characteristics and hospital effect, the magnitude of the disparities decreased substantially, yet remained significant for 3 of the 4 counseling measures; acute myocardial infarction (unadjusted, 9.00 [P<.001]; adjusted, 3.82 [P<.01]), congestive heart failure (unadjusted, 8.45 [P=.02]; adjusted, 3.54 [P=.02]), and community-acquired pneumonia (unadjusted, 14.58 [P=.02]; adjusted, 4.96 [P=.01]). CONCLUSIONS: Disparities in clinical process of care measures are largely the result of differences in where minority and nonminority patients seek care. However, disparities in services requiring counseling exist within hospitals after controlling for site of care. Policies to reduce disparities should consider the underlying reasons for the disparities.

The changing face of race: risk factors for neonatal hyperbilirubinemia.

OBJECTIVES: Race is a predictor of health outcomes and risk for some clinical conditions, for example, mother's race predicts risk for hyperbilirubinemia in newborns, with blacks at lowest risk. Little is known about the correlation of race as recorded in medical records with self-reported race. Also, use of maternal race to predict newborn risk for hyperbilirubinemia has not been tested for multiracial mothers and newborns. We sought to examine how maternal race documented in medical records correlates with self-reported race and to examine the correlation between mothers' and newborns' race in the context of risk for neonatal hyperbilirubinemia, focusing on multiracial mothers and newborns. DESIGN: A cohort study with 3021 newborns at > or =35 weeks gestation discharged from normal nursery between January 2001 and October 2002 with a telephone survey of their mothers within 6 months of birth. SETTING: The study was conducted in the Neonatology Department of Henry Ford Hospital. PATIENTS: There were 1773 mothers (58%) with incorrect telephone numbers. Of 1248 mothers contacted, 866 (69%) completed the interview. OUTCOME MEASURES: We measured mother's race in hospital database and mother's reported race for herself, her newborn, and the father, allowing < or =5 responses for each. RESULTS: Of mothers documented in the medical record as white, 64% self-reported as white. Among mothers recorded as black, 70% self-reported as black. Mothers identified 93 newborns as > or =2 races with primary race matching both parents for 41%, father for 25%, mother for 23%, and neither parent for 11%. Of 70 newborns whose parents were not the same race, mothers identified 45 (64%) as > or =2 races. CONCLUSIONS: There is incomplete overlap between racial identification in medical records versus self-report. Given 1 choice, mothers of multiracial infants overselect black in their newborns' ancestry. Because black race is the lowest risk category for neonatal hyperbilirubinemia, this may lead to underestimating their risk.

Policies to reduce racial and ethnic disparities in child health and health care.

This paper reviews recent reports that demonstrate disparities in health care for children and current federal efforts to eliminate them. Instead of simply describing disparities, this paper also presents recommendations that can reduce disparities. By reviewing current problems, practices, and recommendations in health care coverage, quality, and provider training, the author maps out a plan for reducing disparities in child health that complements existing efforts. The fragmentation of current and proposed initiatives would benefit from an oversight body based at the U.S. Department of Health and Human Services that would monitor progress and coordinate efforts for eliminating disparities.

Correlates of use of specialty care.

OBJECTIVE: This study examines patterns of specialist use among children and adolescents by presence of a chronic condition or disability, insurance, and sociodemographic characteristics. DESIGN: Cross-sectional analysis of national survey data, describing rates of specialist use, with logistic regressions to examine associations with having a chronic condition or disability, insurance status, and sociodemographic variables. SETTING: The 1999 National Health Interview Survey, a nationally representative household survey. PARTICIPANTS: Children and adolescents 2 to 17 years old. OUTCOME: Parental/respondent reports of specialist visits based on reports of the child having seen or talked to a medical doctor who specializes in a particular medical disease or problem about the child's health during the last 12 months. RESULTS: Thirteen percent of US children were reported as seeing a specialist in the past year. Specialist-visit rates were twice as high for children with a chronic condition or disability (26% vs 10.2%). The specialist utilization rates for children without insurance were much lower than those for insured children, but among the children who have coverage (private, Medicaid, or other), specialist-utilization rates were similar (no statistically significant difference). Results of multivariate analyses predicting the use of specialists confirm the above-mentioned findings. Additionally, they show that use of specialist care was lower among children in the middle age group, minorities, children in families between 100% and 200% of the federal poverty level, and lower parental educational levels. We found no difference in specialist-visit rates between rural- and urban-dwelling children, by family status, or by gender. Differences in specialist use by gatekeeping status are found only among subgroups. CONCLUSIONS: The results showed that, overall, 13% of children used a specialist in a year. Among the insured, a slightly greater percentage of children used such care (15%). These numbers were slightly lower than the 18% to 28% of pediatric patients referred per year in 5 US health plans, although the sources of data and definitions of specialist use differ. Our results showed that 26% of children with a chronic condition or disability who were insured by Medicaid use a specialist. Although the data are not directly comparable, this is within the range of previous findings showing annual rates by condition of use between 24% and 59%. These findings are consistent also with greater use of many different types of health care by children with special health care needs. Medicaid-utilization rates presented here were similar also to the rates found among privately insured children and children with "other" insurance. In our earlier work examining use of specialists by children insured by Medicaid, we speculated that Medicaid-insured children might face particular difficulty with access (eg, due to transportation or language barriers). The findings presented here suggest that children insured by Medicaid had no different use of specialists than other insured children. We do not know, however, whether similar rates are appropriate. As predicted, sociodemographic differences were pronounced and followed patterns typically found for use of health services. Lower rates of specialist use by non-Hispanic blacks and Hispanics remains even, controlling for chronic condition/disability, status, insurance, and socioeconomic status. This is an important issue that not only needs to be addressed in using specialist care but also in many areas in health care. It is the near poor who seem to have difficulty accessing care (as is evidenced by lower use of specialists). In a study of access to care, similar results were found, with those between 125% and 200% of the federal poverty level being less likely to have a usual source of care. This is roughly the population targeted by the State Children's Health Insurance Programs. These findings cannot determine whether rates of use are too high or too low. Additional work on outcomes for children who do and do not use specialist care would further inform the work presented here. Extending that work to examine patterns of care including but not limited to specialists and generalists would be even better.

Quality measures for children's health care.

BACKGROUND: The ability to measure and improve the quality of children's health care is of national importance. Despite the existence of numerous health care quality measures, the collective ability of measures to assess children's health care quality is unclear. A review of existing health care quality measures for children is timely for both assessing the current state of quality measures for children and identifying areas requiring additional research and development. OBJECTIVES: To identify and collect current health care quality measures for child health and then to systematically categorize and classify measures and identify gaps in child health care quality measures requiring additional development. DESIGN/METHODS: We first identified child health care quality instruments with assistance from staff at the Agency for Healthcare Research and Quality, experts in the field, the Computerized Needs-oriented Quality Measurement Evaluation System, the Child and Adolescent Health Measurement Initiative, and a medical literature review. From these instruments, we then selected clinical performance measures applicable to children (aged 0-18 years). We categorized the individual measures into the Institute of Medicine's framework for the National Health Care Quality Report. The framework includes health care quality domains (patient safety, effectiveness, patient-centeredness, and timeliness) and patient-perspective domains (staying healthy, getting better, living with illness, and end-of-life care). We then determined the balance of the measures (how well they assess care for all children versus children with special health care needs) and their comprehensiveness (how well the measures apply to the developmental range of children). Finally, we analyzed the ability of the measures to assess equity in care. RESULTS: We identified 19 measure sets, and 396 individual measures were used to assess children's health care quality. The distribution of measures in the health care quality domains was: safety, 14.4%; effectiveness, 59.1%; patient-centeredness, 32.1%; and timeliness, 33.3%. The distribution of measures in the patient-perspective domains was: staying healthy, 24%; getting better, 40.2%; living with illness, 17.4%; end of life, 0%; and multidimensional, 23.5% (measures were multidimensional if they applied to >1 domain). Most of the measures were meant for use in the general pediatric population (81.1%), with a significant proportion designed for children with special health care needs (18.9%). The majority (>or=79%) of the measures could be applied to children across all age groups. However, there were relatively few measures designed specifically for each developmental stage. Regarding the use of measures to study equity in health care, 6 of the measure sets have been used in previous studies of equity. All the survey measure sets contain items that identify patients at risk for poor outcomes, and 4 are available in languages other than English. However, only 1 survey (Consumer Assessment of Health Plans) has undergone studies of cross-cultural validation. Among the measure sets based on administrative data, 3 included infant mortality, a well-known measure of health disparity. CONCLUSIONS: There are several instruments designed to measure health care quality for children. Despite this, we found relatively few measures for assessing patient safety and living with illness and none for end-of-life care. Few measures are designed for specific age categories among children. Although equity is an overarching concern in health care quality, the application of current measures to assess disparities has been limited. These areas need additional research and development for a more complete assessment of health care quality for children.

Breastfeeding advice given to African American and white women by physicians and WIC counselors.

OBJECTIVE: This study determined rates of breastfeeding advice given to African American and white women by medical providers and WIC nutrition counselors, and sought to determine whether racial differences in advice contributed to racial differences in rates of breastfeeding. METHODS: The study used data from the 1988 National Maternal and Infant Health Survey, a cross-sectional survey of a nationally representative sample of mothers with a live birth, infant death, or fetal death in 1988. The authors compared white women (n=3,966) and African American women (n=4,791) with a live birth in 1988 on self-reported rates of medical provider and WIC advice to breastfeed, WIC advice to bottlefeed, and breastfeeding. RESULTS: Self-reported racial identification did not predict medical provider advice. However, being African American was associated with less likelihood of breastfeeding advice and greater likelihood of bottlefeeding advice from WIC nutrition counselors. In multivariate analyses controlling for differences in advice, being African American was independently associated with lower breastfeeding rates (odds ratio [OR] = 0.41, 95% CI 0.32, 0.52). CONCLUSIONS: African American women were less likely than white women to report having received breastfeeding advice from WIC counselors and more likely to report having received bottlefeeding advice from WIC counselors. However, African American and white women were equally likely to report having received breastfeeding advice from medical providers. Lower rates of breastfeeding advice from medical or nutritional professionals do not account for lower rates of breastfeeding among African American women.

Generalist and subspecialist care for children with chronic conditions.

OBJECTIVE: To determine, among Medicaid-enrolled children with chronic conditions, associations of indicators of morbidity and expenditures with different patterns of generalist, subspecialist, and pediatric subspecialist use. DESIGN AND SETTING: Cross-sectional analysis of Medicaid claims, enrollment, and provider data from 4 states (California, Georgia, Michigan, and Tennessee). SAMPLE: All children enrolled in Supplemental Security Income (aged 0-21 years) and a sample of other Medicaid-enrolled children matched for age and gender. We included 11 chronic conditions, including both uncommon conditions (eg, spina bifida, hemophilia) and common ones (eg, asthma, attention deficit hyperactivity disorder). MAIN OUTCOME MEASURES: We determined the number of visits per year to generalists and subspecialists (pediatric and other), using only subspecialists relevant to that condition. We categorized patterns of care as generalist only, predominantly generalist, or predominantly subspecialist, and examined patterns by condition and an indicator of morbidity. Among children seeing subspecialists, we also compared morbidity by pediatric and other subspecialists. We used linear regression to determine per-year total expenditures, controlling for demographic characteristics and morbidity. RESULTS: Most children (60.7%) saw generalists only. Twenty-eight percent were in predominantly generalist arrangements, and 11% were in predominantly subspecialist arrangements. Children in predominantly generalist arrangements had higher morbidity than children in generalist-only or predominantly subspecialist arrangements. Among children seeing subspecialists, those seeing pediatric subspecialists had generally higher morbidity than those seeing other subspecialists. Mean yearly expenditures varied from 1306 dollars (attention deficit hyperactivity disorder) to 11,633 dollars (acquired immunodeficiency syndrome). Children who saw only generalists had significantly lower expenditures for 6 of the 11 conditions, after adjusting for morbidity. CONCLUSIONS: Medicaid-enrolled children in predominantly generalist arrangements appear to have more complicated conditions than children in generalist-only or predominantly subspecialist arrangements, engendering also higher expenditures. Although children who saw generalists only had lower expenditures than those seeing subspecialists, this finding may reflect unmeasured variations in morbidity.

Comparing a diagnosis list with a survey method to identify children with chronic conditions in an urban health center.

OBJECTIVE: To compare a diagnosis list to the Questionnaire for Identifying Children with Chronic Conditions (QuICCC) to assess their relative usefulness as measures for identifying children with chronic conditions. METHODS: Comparison of health encounter data and survey data for a cohort of 304 children aged 0-18 years at an urban health center affiliated with a teaching hospital. We used 2 strategies to identify children with a chronic condition: 1) identification by the existence of an encounter with an International Classification of Diseases, Ninth Revision code indicating a chronic condition and 2) identification by the QuICCC. We compared the characteristics of children identified by the diagnosis list with those of children identified by the QuICCC. RESULTS: This population had high rates of chronic conditions, with 44% identified by the diagnosis list and 36% identified by the QuICCC. These 2 methods jointly identified 66% of children, yet only half (53%) of the children who had a diagnosis of a chronic condition in the encounter data were identified by the QuICCC. Asthma, anorexia, developmental delay, and adjustment reaction were among the common chronic conditions for children identified by the diagnosis list approach only. CONCLUSIONS: We found only moderate concordance among the children identified as having chronic conditions by a diagnosis list and by the QuICCC in this high-risk urban population. These different results indicate that encounter data and survey approaches do not serve as simple substitutes for identifying children with chronic conditions for clinical or monitoring purposes.