Comparison of risk adjusters for medicaid-enrolled children with and without chronic health conditions

Clinical Documentation for Intensivists: The Impact of Diagnosis Documentation

OBJECTIVES

The aim of this review is to describe the interaction of clinical documentation with patient care, measures of patient acuity, quality metrics, research database accuracy, and healthcare reimbursement in order to highlight potential areas of improvement for intensivists.

DATA SOURCES

An online search of PubMed was undertaken as well as review of resources published by the American Academy of Pediatrics, the Society of Critical Care Medicine, the American Medical Association, and the Association of Clinical Documentation Improvement Specialists.

STUDY SELECTION

Selected publications included those that described coding, medical record documentation, healthcare reimbursement, quality metrics, administrative databases, Clinical Documentation Improvement programs, medical scribe programs, and various payment models.

DATA EXTRACTION

Relevant information was extracted to highlight the impact of diagnosis documentation on patient care, perceived patient severity of illness, quality metrics, and healthcare reimbursement. Query data from our hospital's Clinical Documentation Improvement program were reviewed to highlight areas of improvement within our own Division of Critical Care Medicine. Additionally, interventions to improve clinical documentation were incorporated into this review.

DATA SYNTHESIS

Available data in the literature indicate that documentation of precise diagnoses in the medical record has a positive impact on quality metrics, accuracy of administrative databases, hospital reimbursement, and perceived patient complexity. However, there is insufficient data to make conclusions regarding documentation of specific diagnoses and effects on patient care. Administrative responsibilities associated with documentation have been increasing, especially with the introduction of electronic medical records.

CONCLUSIONS

Documentation of specific diagnoses in the medical record is important in the broad context of our existing medical system but there is an associated burden in doing so. Widespread implementation of electronic medical record systems has inadvertently led to clinician dissatisfaction and burnout. Research is needed to further evaluate the impact of documentation on patient care as well as steps to decrease the associated burden.

Breast Cancer Survivorship Care Variations Between Adjuvant Chemotherapy Regimens

BACKGROUND

Treatment-related toxicity can vary substantially between chemotherapy regimens. In this study we evaluated the frequency of outpatient office visits among a cohort of early stage breast cancer survivors after completion of 4 different adjuvant chemotherapy regimens to better understand how differences in toxicities between regimens might affect health care use.

MATERIALS AND METHODS

We analyzed administrative claims data from a US commercial insurance database (OptumLabs) to identify women who received adjuvant doxorubicin/cyclophosphamide (AC), AC followed or preceded by docetaxel or paclitaxel (AC-T), AC concurrent with docetaxel or paclitaxel (TAC), or docetaxel/cyclophosphamide (TC) between 2008 and 2014. We compared mean numbers of visits per patient (adjusted for age, race/ethnicity, region, year, surgery type, radiation, chronic conditions, and previous hospitalizations) across the different regimens (TC = reference) for 12 months, starting 4 months after the end of chemotherapy.

RESULTS

In 6247 eligible patients, the mean adjusted number of outpatient visits per patient was significantly higher in patients who received AC-T (8.1) or TAC (7.3) than TC (6.5) or AC (6.0; P < .001 for comparisons of AC-T and TAC with TC), primarily because of differences in Medical Oncology visits. Approximately 40% did not see a primary care provider at all during this time frame.

CONCLUSIONS

AC-T and TAC are associated with more subsequent outpatient visits than TC. Visits to primary care providers are infrequent during the year after completion of chemotherapy.

Socioeconomic Background and Commercial Health Plan Spending

BACKGROUND

Risk-adjustment algorithms typically incorporate demographic and clinical variables to equalize compensation to insurers for enrollees who vary in expected cost, but including information about enrollees' socioeconomic background is controversial.

METHODS

We studied 1 182 847 continuously insured 0 to 19-year-olds using 2008-2012 Blue Cross Blue Shield of Massachusetts and American Community Survey data. We characterized enrollees' socioeconomic background using the validated area-based socioeconomic measure and calculated annual plan payments using paid claims. We evaluated the relationship between annual plan payments and geocoded socioeconomic background using generalized estimating equations (γ distribution and log link). We expressed outcomes as the percentage difference in spending and utilization between enrollees with high and low socioeconomic backgrounds.

RESULTS

Geocoded socioeconomic background had a significant, positive association with annual plan payments after applying standard adjusters. Every 1 SD increase in socioeconomic background was associated with a 7.8% (95% confidence interval, 7.2% to 8.3%; P < .001) increase in spending. High socioeconomic background enrollees used higher-priced outpatient and pharmacy services more frequently than their counterparts from low socioeconomic backgrounds (eg, 25% more outpatient encounters annually; 8% higher price per encounter; P < .001), which outweighed greater emergency department spending among low socioeconomic background enrollees.

CONCLUSIONS

Higher socioeconomic background is associated with greater levels of pediatric health care spending in commercially insured children. Including socioeconomic information in risk-adjustment algorithms may address concerns about adverse selection from an economic perspective, but it would direct funds away from those caring for children and adolescents from lower socioeconomic backgrounds who are at greater risk of poor health.

Is there one measure-of-fit that fits all? A taxonomy and review of measures-of-fit for risk-equalization models

This study provides a taxonomy of measures-of-fit that have been used for evaluating risk-equalization models since 2000 and discusses important properties of these measures, including variations in analytic method. It is important to consider the properties of measures-of-fit and variations in analytic method, because they influence the outcomes of evaluations that eventually serve as a basis for policymaking. Analysis of 81 eligible studies resulted in the identification of 71 unique measures that were divided into 3 categories based on treatment of the prediction error: measured based on squared errors, untransformed errors, and absolute errors. We conclude that no single measure-of-fit is best across situations. The choice of a measure depends on preferences about the treatment of the prediction error and the analytic method. If the objective is measuring financial incentives for risk selection, the only adequate evaluation method is to assess the predictive performance for non-random groups.

Access to leave benefits for primary caregivers of children with special health care needs: a double bind

OBJECTIVE

Family leave benefits are a key tool that allow parents to miss work to care for their ill children. We examined whether access to benefits varies by level of childcare responsibilities among employed parents of children with special health care needs (CSHCN).

METHODS

We conducted telephone interviews with 3 successive cohorts of employed parents of CSHCN, randomly sampled from a California children's hospital. At Wave 1 (November 2003 to January 2004), we conducted 372 parent interviews. At Wave 2 (November 2005 to January 2006), we conducted 396 parent interviews. At Wave 3 (November 2007 to January 2008), we conducted 393 parent interviews. We pooled these samples for bivariate and multivariate regression analyses by using wave indicators and sample weights.

RESULTS

Parents with more childcare responsibilities (primary caregivers) reported less access to sick leave/vacation (65% vs 82%, P < .001), access to paid leave outside of sick leave/vacation (41% vs 51%, P < .05), and eligibility for Family and Medical Leave Act benefits (28% vs 44%, P < .001) than secondary caregivers. Part-time employment and female gender largely explained 2 of the 3 associations between more childcare responsibilities and less access to leave benefits. Even in the context of part-time employment, however, primary caregivers were just as likely as secondary caregivers both to miss work due to their child's illness and to report being unable to miss work when they needed to.

CONCLUSIONS

Due in part to employment and gender differences, leave benefits among parents of CSHCN are skewed away from primary caregivers and toward secondary caregivers. Thus, primary caregivers may face particularly difficult choices between employment and childcare responsibilities. Reducing this disparity in access to benefits may improve the circumstances of CSHCN and their families.

Effect of fear-avoidance beliefs of physical activities on a model that predicts risk-adjusted functional status outcomes in patients treated for a lumbar spine dysfunction

STUDY DESIGN

Retrospective analysis of a prospective, longitudinal cohort study of 30 858 patients being treated for a lumbar spine dysfunction in outpatient physical therapy.

OBJECTIVES

To determine effect of adding a single-item screening variable classifying patients with elevated versus not-elevated scores of fear-avoidance beliefs of physical activities at intake, on a model predicting risk-adjusted functional status (FS) outcomes.

BACKGROUND

Outcomes must be risk-adjusted before making meaningful interpretations. Elevated fear-avoidance beliefs scores have been predictive of poor outcomes. But the importance of elevated fear-avoidance scores in a multivariable model predicting FS outcomes needs further study.

METHODS

Using retrospective analyses, predictive ability (R2) of multivariable linear regression models of discharge FS with and without classification by elevated versus not-elevated fear-avoidance scores were compared, while controlling for intake FS, age, symptom acuity, surgical history, gender, number of comorbidities, and payer. Percent variance controlled and beta coefficients (95% confidence intervals) of each variable in both models were compared. A split-half design was used for model cross-validation. Predictive ratios (predicted FS, divided by actual discharge FS) were assessed.

RESULTS

Adding fear-avoidance beliefs classification to the discharge FS model improved (P<.001) model predictive ability but only slightly (R2 without, and with, fear-avoidance classification, 0.2997 and 0.3010, respectively). Variables impacted models similarly (95% confidence intervals not different). Fear-avoidance classification added 0.2% data variance control to the existing model. Cross-validation was supported. Predictive ratios were 1.09 and 1.10, without and with fear-avoidance, respectively.

CONCLUSION

Although screening for elevated fear-avoidance beliefs of physical activities significantly improves the FS outcomes predictive model, the amount of additional meaningful interpretation of FS outcomes was minimal. Exploration of other clinically relevant variables designed to improve outcomes prediction is warranted.

LEVEL OF EVIDENCE

Prognosis, level 2c.

Risk-adjusted capitation rates for children: how useful are the survey-based measures?

OBJECTIVE

Despite the recognition by some experts that survey measures have the potential to improve capitation rates for those with chronic conditions, few studies have examined risk-adjustment models for children, and fewer still have focused on survey measures. This study evaluates the performance of risk-adjustment models for children and examines the potential of survey-based measures for improving capitation rates for children.

DATA SOURCES

The study sample includes 8,352 Medicaid children who were followed up for 2 years by the Medical Expenditure Panel Survey in 2000-2005.

STUDY METHODS

Children's information in 1 year was used to predict their expenditures in the next year. Five models were estimated, including one each that used demographic characteristics, subjectively rated health status, survey measures about children with special health care needs (CSHCN), prior year expenditures, and Hierarchical Condition Category (HCC), which is a diagnosis-based model. The models were tested at the individual level using multiple regression methods and at the group level using split-half validation to evaluate their impact on expenditure predictions for CSHCN.

PRINCIPAL FINDINGS

The CSHCN information explained higher proportion of the variance in annual expenditures than the subjectively rated health status, but less than HCC measures and prior expenditures. Adding the CSHCN information into demographic factors as adjusters would remarkably increase capitation rates for CSHCN.

CONCLUSIONS

Survey measures, such as the CSHCN information, can improve risk-adjustment models, and their inclusion into capitation adjustment may help provide appropriate payments to managed-care plans serving this vulnerable group of children.

High-deductible health plans: are vulnerable families enrolled?

OBJECTIVE

There is concern that high-deductible health plans may have negative effects on vulnerable groups. The objective of this study was to compare the characteristics of families who have children and switch to high-deductible health plans with those who stay in traditional plans.

METHODS

This double-cohort study included families who had children aged <18 years and were enrolled in a Massachusetts health plan through employers who did not offer a choice of health plans. We identified families who had traditional health maintenance organization plans for a 12-month baseline period between 2001 and 2004 and compared families whose coverage was then switched to a high-deductible health plan by their employers with similar families whose employer chose to remain in the traditional plan (controls). Data came from health plan enrollment and claims datasets and census data. We used multivariate logistic regression models to compare the characteristics of families who were switched to high-deductible health plans with controls.

RESULTS

We identified 839 families who had children and whose employer switched them to high-deductible health plans and 5133 controls. Among families with large employers, the adjusted odds of the employer switching to a high-deductible health plan were higher for families living in high-poverty neighborhoods. Among families with small employers, the adjusted odds of the employer switching to a high-deductible health plan were lower for families with more children, above-average family morbidity, and baseline total expenditures >$7000.

CONCLUSIONS

Among families with large employers offering a single health plan, those from low-income neighborhoods are more likely to be switched to high-deductible health plans. In contrast, families with small employers offering a single plan are more likely to be switched to high-deductible health plans if they are healthier and have lower baseline costs. These findings suggest that families with children in high-deductible plans may represent two distinct groups, one with higher-risk characteristics and another with lower-risk characteristics compared with those in traditional plans.

Perceived effects of leave from work and the role of paid leave among parents of children with special health care needs

OBJECTIVES

We examined the perceived effects of leave from work among employed parents of children with special health care needs.

METHODS

Telephone interviews were conducted from November 2003 to January 2004 with 585 parents who had missed 1 or more workdays for their child's illness in the previous year.

RESULTS

Most parents reported positive effects of leave on their child's physical (81%) and emotional (85%) health; 57% reported a positive effect on their own emotional health, although 24% reported a negative effect. Most parents reported no effect (44%) or a negative effect (42%) on job performance; 73% reported leave-related financial problems. In multivariate analyses, parents receiving full pay during leave were more likely than were parents receiving no pay to report positive effects on child physical (odds ratio [OR] = 1.85) and emotional (OR = 1.68) health and parent emotional health (OR = 1.70), and were less likely to report financial problems (OR = 0.20).

CONCLUSIONS

Employed parents believed that leave-taking benefited the health of their children with special health care needs and their own emotional health, but compromised their job performance and finances. Parents who received full pay reported better consequences across the board. Access to paid leave, particularly with full pay, may improve parent and child outcomes.

Awareness and use of California's Paid Family Leave Insurance among parents of chronically ill children

CONTEXT

In 2004, California's Paid Family Leave Insurance Program (PFLI) became the first state program to provide paid leave to care for an ill family member.

OBJECTIVE

To assess awareness and use of the program by employed parents of children with special health care needs, a population likely to need leave.

DESIGN, SETTING, AND PARTICIPANTS

Telephone interviews with successive cohorts of employed parents before (November 21, 2003-January 31, 2004; n = 754) and after (November 18, 2005-January 31, 2006; n = 766) PFLI began, randomly sampled from 2 children's hospitals, one in California (with PFLI) and the other in Illinois (without PFLI). Response rates were 82% before and 81% after (California), and 80% before and 74% after (Illinois).

MAIN OUTCOME MEASURES

Taking leave, length of leave, unmet need for leave, and awareness and use of PFLI.

RESULTS

Similar percentages of parents at the California site reported taking at least 1 day of leave to care for their ill child before (295 [81%]) and after (327 [79%]) PFLI, taking at least 4 weeks before (64 [21%]) and after (74 [19%]) PFLI, and at least once in the past year not missing work despite believing their child's illness necessitated it before (152 [41%]) and after (156 [41%]) PFLI. Relative to Illinois, parents at the California site reported no change from before to after PFLI in taking at least 1 day of leave (difference of differences, -3%; 95% confidence interval [CI], -13% to 7%); taking at least 4 weeks of leave (1%; 95% CI, -9% to 10%); or not missing work, despite believing their child's illness necessitated it (-1%; 95% CI, -13% to 10%). Only 77 parents (18%) had heard of PFLI approximately 18 months after the program began, and only 20 (5%) had used it. Even among parents without other access to paid leave, awareness and use of PFLI were minimal.

CONCLUSIONS

Parents of children with special health care needs receiving care at a California hospital were generally unaware of PFLI and rarely used it. Among parents of children with special health care needs, taking leave in California did not increase after PFLI implementation compared with Illinois.

Need for and use of family leave among parents of children with special health care needs

OBJECTIVE

Parents of children with special health care needs are especially vulnerable to work-family conflicts that family leave benefits might help resolve. We examined leave-taking among full-time-employed parents of children with special health care needs.

METHODS

We identified all children with special health care needs in 2 large inpatient/outpatient systems in Chicago, Illinois, and Los Angeles, California, and randomly selected 800 per site. From November 2003 to January 2004, we conducted telephone interviews with 1105 (87% of eligible and successfully contacted) parents. Among the sample's 574 full-time-employed parents, we examined whether leave benefits predicted missing any work for child illness, missing >4 weeks for child illness, and ability to miss work whenever their child needed them.

RESULTS

Forty-eight percent of full-time-employed parents qualified for federal Family and Medical Leave Act benefits; 30% reported employer-provided leave benefits (not including sick leave/vacation). In the previous year, their children averaged 20 missed school/child care days, 12 doctor/emergency department visits, and 1.7 hospitalizations. Although 81% of parents missed work for child illness, 41% reported not always missing work when their child needed them, and 40% of leave-takers reported returning to work too soon. In multivariate regressions, parents who were eligible for Family and Medical Leave Act benefits and aware of their eligibility had 3.0 times greater odds of missing work for child illness than ineligible parents. Parents with >4 weeks of employer-provided leave benefits had 4.7 times greater odds of missing >4 weeks than parents without benefits. Parents with paid leave benefits had 2.8 times greater odds than other parents of missing work whenever their child needed them.

CONCLUSIONS

Full-time-employed parents of children with special health care needs experience severe work-family conflicts. Although most have leave benefits, many report unmet need for leave. Access to Family and Medical Leave Act benefits and employer-provided leave may greatly affect leave-taking.

Short-term persistence of high health care costs in a nationally representative sample of children

OBJECTIVES

Little is known about the persistence of health care costs in children. Determining whether children with high health expenses continue to have high expenses over time can help in the development of targeted programs and policies to decrease costs, plan equitable health insurance strategies, and provide insights into the effects of costly conditions on families. The objectives of this study were to (1) identify the characteristics of children who are in the top 10th percentile for health costs, (2) investigate whether those in the top percentiles for costs in 1 year continue in the same percentiles the next year, and (3) identify factors that predict whether a child stays in the top percentiles.

METHODS

Data from 2 consecutive years (2000-2001) of the Medical Expenditure Panel Survey were analyzed. Changes in a child's position in the expenditure distribution were examined. An estimated multivariate model conditional on insurance was developed to predict the true resource costs of providing services. Statistical analyses, including logistic-regression and multivariate linear-regression modeling, were done to account for the weighted sampling used in Medical Expenditure Panel Survey.

RESULTS

A total of 2938 children were included in the survey for both years. In 2000, the top 10% of the children accounted for 54% of all costs. They had a mean total expenditure of 6422 dollars with out-of-pocket expenditures of 1236 dollars; 49% of the children in the top decile in 2000 persisted in the top decile in 2001, whereas 12% dropped into the bottom half. Children who had been in the top 10% in 2000 were 10 times more likely than other children to be in the top 10% for 2001. Other characteristics in 2000 that predicted membership in the top decile for 2001 included age (11-15 and 16-17 years), having any insurance (public and private), being positive on the standardized Children With Special Health care Need screener, and having a functional limitation.

CONCLUSIONS

Almost half of the children in the top 10% for costs in 2000 persisted in the top 10% in 2001. Older children, children with special health care needs, and children with functional limitations were more likely to be in the top decile. These findings do not support the belief that black and Latino children who are on Medicaid account for a disproportionate share of costs or expenditures. Because the children who were among the top 10% used health care services in a variety of inpatient, emergency department, outpatient, and ancillary venues, providing care coordination throughout the entire health care system is important to address both the cost and the quality aspects of health care for the most costly children. Targeted programs to decrease expenditures for those with the greatest costs have the potential to save future health care dollars. Assessment of the factors that predict persistence of high expenditures can be used to help in the planning of equitable health insurance strategies such as catastrophic care, carve-outs, reinsurance, and risk adjustment. Clinicians should review regularly the extent of care coordination that they are providing for their high-need and high-cost patients, especially preteens and adolescents. Studies that examine the persistence of expenditures over longer periods and include assessment of quality of care are needed.

Pharmacy- and Diagnosis-Based Risk Adjustment for Children With Medicaid

BACKGROUND

Risk adjustment is useful for adjusting health care payments based on patients' health status.

OBJECTIVE

This work seeks to examine how well pharmacy- and diagnosis-based risk adjusters predict child health expenditures in Medicaid populations.

RESEARCH DESIGN

We used 1994-1995 Medicaid claims files for all children ages 0-18 years who were not covered by managed care in 3 states: Georgia, New Jersey, and Wisconsin. We examined separately 6 risk adjustment methods, 2 pharmacy-based and 4 diagnosis-based. We compared predictive accuracy of the methods for the whole sample and stratified by state and Medicaid enrollment category.

FINDINGS

Models with risk adjustment (either diagnosis- or pharmacy-based) had better predictive accuracy than demographic models. The pharmacy and diagnosis-based models had similar predictive accuracy. Risk adjuster performance differed by Medicaid enrollment category and state. Risk-adjusted models generally underpredict expenditures in populations with worse health status (eg, those in the Supplemental Security Income program [SSI]). The pharmacy-based models performed well for children in SSI relative to children in foster care.

CONCLUSIONS

Both pharmacy- and diagnosis-based risk adjustment improved the prediction of health expenditures compared models without risk adjustment. No single risk adjuster performed best in all situations, suggesting that optimal choices of risk adjusters may differ by purpose and context.

Identification and recall of children with chronic medical conditions for influenza vaccination

OBJECTIVES

Despite long-standing recommendations to provide annual influenza vaccination to children with chronic medical conditions, immunization rates are <10% in most primary care settings. Many obstacles impede implementation of these recommendations, including the challenge of identifying targeted children and the need to immunize yearly in a short time interval. The objective of this study was to assess the accuracy of billing data for identifying children who have high-risk conditions (HRCs) and need influenza vaccination and 2) to evaluate the efficacy of reminder/recall for children with HRCs.

METHODS

The study was conducted in 4 private pediatric practices in metropolitan Denver, Colorado, that share a computerized billing system and also participate in an immunization registry. For all children aged 6 to 72 months, registry records were linked with the billing database. Patients with >or=1 encounters for an HRC in the previous 24 months were selected, with HRCs identified from International Classification of Diseases, Ninth Revision, Clinical Modification diagnostic codes. Using medical records as the "gold standard," we reviewed 327 randomly selected records to determine the sensitivity, specificity, and accuracy of billing data for identifying HRCs. For children with an HRC, we then conducted a randomized, controlled trial of reminder/recall for influenza vaccination. The primary outcome of the recall trial was receipt of influenza vaccine.

RESULTS

Billing data had a sensitivity of 72% (95% confidence interval [CI]: 48%-95%), specificity of 95% (95% CI: 90%-100%), and overall accuracy of 90% (95% CI: 84%-96%) in determining which children had an HRC. Of the 17,273 patients aged 6 to 72 months, 2007 had >or=1 HRCs (12% overall; range: 9%-14% per practice). Asthma/reactive airways disease accounted for 87% of all HRCs. Reminder/recall significantly increased influenza immunization in children with HRCs, with a vaccination rate of 42% in those recalled, compared with 25% in control subjects. Recalled subjects were more likely to have an office visit (68% vs 60%) and less likely to have a missed opportunity to immunize (28% vs 37%) compared with control subjects.

CONCLUSIONS

Diagnosis-based billing data accurately identified children who had HRCs and needed annual influenza vaccination, and registry-driven reminder/recall significantly increased influenza immunization in targeted children.

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.