Systemwide provider performance in a Medicaid program. Profiling the care of patients with chronic illnesses

Analysis of Affordable Health Care

BACKGROUND

Lack of affordable health care affects the uninsured, commercially insured, and Medicare beneficiaries. Yet, the wide variation in providers' prices and practice styles suggests that more affordable care already may be available and data on low value and wasteful care suggest that lower cost care need not come at the expense of better quality. Although price variation has received the most attention in the literature and legislation, total cost of care is a function of both unit prices (fees) and the quantity of services.

OBJECTIVE

To partition provider-specific variation in total annual risk-adjusted per capita expenditures on health care services into variation in unit prices (fees) versus quantities of services, and to explore the relationship between low value, avoidable, discretionary, and recommended care to total health expenditures. The analysis is important because both prices and quantities of services can affect affordability and reductions in prices versus quantities have very different effects on providers' profits.

SETTING

2018 data from the Minnesota State Employees Group Insurance Program (SEGIP) that offers a tiered cost-sharing health insurance benefit design to 130,000 State employees and their dependents (SEGIP "members").

EXPOSURE

Each year during open enrollment, SEGIP members choose a primary care clinic (PCC). The PCC can make decisions regarding both unit prices and prescribed services. PCCs are placed in one of four cost-sharing tiers based on the total annual risk-adjusted per capita health expenditures for the SEGIP members who choose their clinic. Members choosing higher cost PCCs face higher deductibles, copayments, and maximum out-of-pocket spending limits.

MEASURES

Overall prices and use of inpatient, outpatient hospital, professional, and pharmaceutical services, total and avoidable use of emergency department visits and inpatient admissions, low value care, testing for patients with pneumonia, and recommended preventive care.

RESULTS

Differences in total risk-adjusted annual per capita health expenditures across the care systems were substantial. Higher cost providers had both higher unit prices and higher use of services. Variation in the quantity of health care services explained more of the variance in total spending than variation in prices. Prices for professional services and use of inpatient, outpatient hospital, and pharmaceutical services, and ambulatory care sensitive admissions, contributed significantly to high total expenditures. Lower cost PCCs in the lowest cost-sharing tier had higher rates of low value care and lower emergency department visits per capita. Neither the number of investigations for patients with pneumonia nor the receipt of recommended mammography screening varied systematically by tier.

CONCLUSIONS

Efforts to identify and expand sources of affordable care, including improved information and incentives for consumers, need to account for variation in both prices and quantities of services. Efforts to encourage more efficient use of health care services by providers need to consider the effect of those efforts on the provider's internal costs and thus their profits.

A Quantitative Observational Study of Physician Influence on Hospital Costs

Physicians serve as the nexus of treatment decision-making in hospitalized patients; however, little empirical evidence describes the influence of individual physicians on hospital costs. In this study, we examine the extent to which hospital costs vary across physicians and physician characteristics. We used all-payer data from 2 states representing 15 237 physicians and 2.5 million hospital visits. Regression analysis and propensity score matching were used to understand the role of observable provider characteristics on hospital costs controlling for patient demographics, socioeconomic characteristics, clinical risk, and hospital characteristics. We used hierarchical models to estimate the amount of variation attributable to physicians. We found that the average cost of hospital inpatient stays registered to female physicians was consistently lower across all empirical specifications when compared with male physicians. We also found a negative association between physicians’ years of experience and the average costs. The average cost of hospital inpatient stays registered to foreign-trained physicians was lower than US-trained physicians. We observed sizable variation in average costs of hospital inpatient stays across medical specialties. In addition, we used hierarchical methods and estimated the amount of remaining variation attributable to physicians and found that it was nonnegligible (intraclass correlation coefficient [ICC]: 0.33 in the full sample). Historically, most physicians have been reimbursed separately from hospitals, and our study shows that physicians play a role in influencing hospital costs. Future policies and practices should acknowledge these important dependencies. This study lends further support for alignment of physician and hospital incentives to control costs and improve outcomes.

Developing a dashboard to help measure and achieve the triple aim: a population-based cohort study

BACKGROUND

Health system planners aim to pursue the three goals of Triple Aim: 1) reduce health care costs; 2) improve population health; and 3) improve the care experience. Moreover, they also need measures that can reliably predict future health care needs in order to manage effectively the health system performance. Yet few measures exist to assess Triple Aim and predict future needs at a health system level. The purpose of this study is to explore the novel application of a case-mix adjustment method in order to measure and help improve the Triple Aim of health system performance.

METHODS

We applied a case-mix adjustment method to a population-based analysis to assess its usefulness as a measure of health system performance and Triple Aim. The study design was a retrospective, cohort study of adults from Ontario, Canada using administrative databases: individuals were assigned a predicted illness burden score using a case-mix adjustment system from diagnoses and health utilization data in 2008, and then followed forward to assess the actual health care utilization and costs in the following year (2009). We applied the Johns Hopkins Adjusted Clinical Group (ACG) Case-Mix System to categorize individuals into 60 levels of healthcare need, called ACGs. The outcomes were: 1) Number of individuals per ACG; 2) Total system costs per ACG; and 3) Mean cost per person per ACG, which together formed a health system "dashboard".

RESULTS

We identified 11.4 million adults. 16.1% were aged 65 or older, 3.2 million (28%) did not use health care services that year, and 45,000 (0.4%) were in the highest acuity ACG category using 12 times more than an average adult. The sickest 1%, 5% and 15% of the population use about 10%, 30% and 50% of total health system costs respectively. The dashboard measures 2 dimensions of Triple Aim: 1) reduced costs: when total system costs per ACG or when average costs per person is reduced; and 2) improved population health: when more people move into healthier rather than sicker ACGs. It can help to achieve the third aim, improved care experience, when ACG utilization predictions are reported to providers to proactively develop care plans.

CONCLUSIONS

The dashboard, developed via case-mix methods, measures 2 of the Triple Aim goals and can help health system planners better manage their health delivery systems.

Rate of and Risk Factors for Reoperations After Open Reduction and Internal Fixation of Midshaft Clavicle Fractures: A Population-Based Study in Ontario, Canada

BACKGROUND

Reoperation rates following open reduction and internal fixation (ORIF) of midshaft clavicle fractures have been described, but reported rates of nonunion, malunion, infection, and implant removal have varied. We sought to establish baseline rates of, and risk factors for, reoperations following clavicle ORIF in a large population cohort.

METHODS

Administrative databases were used to identify patients sixteen to sixty years of age who had undergone an ORIF of a closed, midshaft clavicle fracture from April 2002 to April 2010. The primary outcome was a reoperation within two years (isolated implant removal, irrigation and debridement [deep infection], pseudarthrosis reconstruction [nonunion], or clavicle osteotomy [malunion]). The secondary outcome was rare perioperative complications, including pneumothorax, subclavian vasculature injury, and brachial plexus injury. A multivariable logistic regression analysis was performed to determine the influence of patient and provider factors on these outcomes.

RESULTS

We identified 1350 patients who underwent midshaft clavicle ORIF (median age, thirty-two years [interquartile range, twenty-one to forty-four years]; 81.3% male). One in four patients (24.6%) underwent at least one clavicle reoperation. The most common procedure was isolated implant removal (18.8%), and females were at highest risk (odds ratio [OR], 1.7; p = 0.002). The median time to implant removal was twelve months. A reoperation secondary to nonunion, deep infection, and malunion occurred in 2.6%, 2.6%, and 1.1% of the patients after a median of six, five, and fourteen months, respectively. Risk factors for clavicle nonunion included female sex (OR, 2.2; p = 0.04) and a high comorbidity score (OR, 2.8; p = 0.009). For surgeons, fewer years in practice was associated with a small risk of the patient developing an infection (OR, 1.1; p < 0.001). Sixteen pneumothoraces (1.2%) were identified; however, brachial plexus and subclavian vessel injuries were each found in five or fewer patients.

CONCLUSIONS

Following clavicle ORIF, one in four patients underwent a reoperation. The most common procedure was implant removal, and although the rates of reoperations secondary to nonunion, malunion, and infection were low they were higher than previously reported. Pneumothoraces and neurovascular injuries were infrequent and should continue to be considered rare complications of clavicle ORIF.

LEVEL OF EVIDENCE

Prognostic Level IV. See Instructions for Authors for a complete description of levels of evidence.

Long-term impact of environmental public health disaster on health system performance: experiences from the Graniteville, South Carolina chlorine spill

OBJECTIVES

In the aftermath of an environmental public health disaster (EPHD) a healthcare system may be the least equipped entity to respond. Preventable visits for ambulatory care-sensitive conditions (ACSCs) may be used as a population-based indicator to monitor health system access postdisaster. The objective of this study was to examine whether ACSC rates among vulnerable subpopulations are sensitive to the impact of a disaster.

METHODS

We conducted a retrospective analysis on the 2005 chlorine spill in Graniteville, South Carolina using a Medicaid claims database. Poisson regression was used to calculate change in monthly ACSC visits at the disaster site in the postdisaster period compared with the predisaster period after adjusting for parallel changes in a control group.

RESULTS

The adjusted rate of a predisaster ACSC hospital visit for the direct group was 1.68 times the rate for the control group (95% confidence interval [CI] 1.47-1.93), whereas the adjusted ACSC hospital rate postdisaster for the direct group was 3.10 times the rate for the control group (95% CI 1.97-5.18). For ED ACSC visits, the adjusted rate among those directly affected predisaster were 1.82 times the rate for the control group (95% CI 1.61-2.08), whereas the adjusted ACSC rate postdisaster was 2.81 times the rate for the control group (95% CI 1.92-5.17).

CONCLUSIONS

Results revealed that an increased demand on the health system altered health services delivery for vulnerable populations directly affected by a disaster. Preventable visits for ACSCs may advance public health practice by identifying healthcare disparities during disaster recovery.

Clinical care and health disparities

Health disparities, also known as health inequities, are systematic and potentially remediable differences in one or more aspects of health across population groups defined socially, economically, demographically, or geographically. This topic has been the subject of research stretching back at least decades. Reports and studies have delved into how inequities develop in different societies and, with particular regard to health services, in access to and financing of health systems. In this review, we consider empirical studies from the United States and elsewhere, and we focus on how one aspect of health systems, clinical care, contributes to maintaining systematic differences in health across population groups characterized by social disadvantage. We consider inequities in clinical care and the policies that influence them. We develop a framework for considering the structural and behavioral components of clinical care and review the existing literature for evidence that is likely to be generalizable across health systems over time. Starting with the assumption that health services, as one aspect of social services, ought to enhance equity in health care, we conclude with a discussion of threats to that role and what might be done about them.

Multimorbidity and its measurement

Multimorbidity is increasing in frequency. It can be quantitatively measured and is a major correlate of high use of health services resources of all types, especially over time. The ACG System for characterizing multimorbidity is the only widely used method that is based on combinations of different TYPES of diagnoses over time, rather than the presence or absence of particular conditions or numbers of conditions. It incorporates administrative data (as from claims forms or medical records) on all types of encounters and is not limited to diagnoses captured during hospitalizations or other places of encounter. It can be employed in any one or combination of analytic models, and can incorporate medication use if desired. It is being used in clinical care, management of health services resources, in health services research to control for degree of morbidity, and in understanding morbidity patterns over time. In addition to its research uses, it is being employed in many countries in various applications as a policy to better understand health needs of populations and tailor health services resources to health needs.

Lapses in Medicaid coverage: impact on cost and utilization among individuals with diabetes enrolled in Medicaid

BACKGROUND

Gaps in Medicaid coverage can result in inadequate access to care. This can be particularly detrimental to those with a chronic disease such as diabetes.

OBJECTIVE

To assess whether a lapse in Medicaid coverage is associated with an increase in expenditures, and acute care utilization upon reenrollment among beneficiaries with diabetes.

RESEARCH DESIGN

Using multivariate regression analyses, we compared pre- versus post-expenditures and utilization among 2102 individuals with diabetes who had experienced at least one 1-month lapse in their Medicaid coverage.

MEASURES

Dependent variables were the number of inpatient episodes, total length of stay, total number of emergency room visits, total expenditure, and pharmaceutical expenditures. These were aggregated over 3-month spans that either immediately preceded or immediately followed a lapse in coverage. Key predictor variables included a variable that identified the span as occurring pre-lapse or post-lapse in coverage, and a continuous variable identifying the length of the lapse. Predicted expenditure and utilization were calculated.

RESULTS

Overall total program expenditures were higher for post-lapse periods compared with pre-lapse periods. Total expenditures were estimated to increase by $239 per member per month for the 3-month period. The likelihood of having any expenditure was actually lower in the post-lapse period. However inpatient and emergency room use was higher.

CONCLUSIONS

The results from this study suggest that interruptions in Medicaid coverage are associated with overall greater program expenditures in the post-lapse periods. However, this increase in expenditures seems to be driven by a subset of individuals whose greater use of inpatient and emergency room services increased overall program costs.

Regression tree boosting to adjust health care cost predictions for diagnostic mix

OBJECTIVE

To assess the ability of regression tree boosting to risk-adjust health care cost predictions, using diagnostic groups and demographic variables as inputs. Systems for risk-adjusting health care cost, described in the literature, have consistently employed deterministic models to account for interactions among diagnostic groups, simplifying their statistical representation, but sacrificing potentially useful information. An alternative is to use a statistical learning algorithm such as regression tree boosting that systematically searches the data for consequential interactions, which it automatically incorporates into a risk-adjustment model that is customized to the population under study.

DATA SOURCE

Administrative data for over 2 million enrollees in indemnity, preferred provider organization (PPO), and point-of-service (POS) plans from Thomson Medstat's Commercial Claims and Encounters database.

STUDY DESIGN

The Agency for Healthcare Research and Quality's Clinical Classification Software (CCS) was used to sort 2001 diagnoses into 260 diagnosis categories (DCs). For each plan type (indemnity, PPO, and POS), boosted regression trees and main effects linear models were fitted to predict concurrent (2001) and prospective (2002) total health care cost per patient, given DCs and demographic variables.

PRINCIPAL FINDINGS

Regression tree boosting explained 49.7-52.1 percent of concurrent cost variance and 15.2-17.7 percent of prospective cost variance in independent test samples. Corresponding results for main effects linear models were 42.5-47.6 percent and 14.2-16.6 percent.

CONCLUSIONS

The combination of regression tree boosting and a diagnostic grouping scheme, such as CCS, represents a competitive alternative to risk-adjustment systems that use complex deterministic models to account for interactions among diagnostic groups.

Estimating physician effects on glycemic control in the treatment of diabetes: methods, effects sizes, and implications for treatment policy

OBJECTIVE

Researchers have only just begun to investigate physician-related effects on medical outcomes. Such research is necessary for developing empirically informed practice guidelines and policy. The primary goal of this study was to investigate whether glucose management in type 2 diabetes varies by randomly assigned physicians over the course of a year in treatment. A second goal of the study was to investigate whether physician-related effects vary across differential patient characteristics. A tertiary goal was to investigate potential patient-level effects on glucose management.

RESEARCH DESIGN AND METHODS

Hierarchical linear models were used to investigate A1C among 1,381 patients, nested within 42 randomly assigned primary care physicians at a Veterans Affairs medical center in the southeastern U.S. The primary outcome measure was change in A1C over the course of 1 year in treatment. On average, each study physician had 33 patients with diabetes.

RESULTS

Overall, physician-related factors were associated with statistically significant but modest variability in A1C change (2%), whereas patient-level factors accounted for the majority of variation in A1C change (98%). Physician effects varied by patient characteristics, mattering more for black patients, patients aged 65 years, and patients whose glucose management improved over the treatment year.

CONCLUSIONS

The results of this study indicate that differential physician effects have minimal impact on glycemic control. Results suggest that it is logical to support policies encouraging the development of patient-level behavioral interventions because that is the level that accounts for the majority of variance in glycemic control.

Explanatory ability of the ACG system regarding the utilization and expenditure of the national health insurance population in Taiwan--a 5-year analysis

BACKGROUND

The adjusted clinical group (ACG) is a diagnosis-based case-mix adjustment system, which has been widely evaluated in several countries other than Taiwan. The aim of this study was to assess the performance of the ACG system on the National Health Insurance (NHI) population in Taiwan.

METHODS

We conducted longitudinal data analysis using the claims data of 1% of randomly sampled NHI enrollees from 2000 to 2004. The ACG software was used to assign each individual to 1 ACG category based on age, gender and aggregating diagnoses in each year from 2000 to 2004, respectively. The ACG distribution patterns and their relationships to expenditure were examined. Explanatory ability as measured by adjusted R2 of the ACG system for same-year and next-year ambulatory and inpatient expenditure were examined by multivariate regression models for each year.

RESULTS

The quality of NHI claim data was satisfactory in that 98.1% of the population could be assigned to ACG categories. The population's ACG patterns were substantially consistent but unequally distributed across the 5 years. Eighty percent of NHI expenditure were spent on people assigned to 21 ACGs. The explanatory abilities of individual's ACG and its components with respect to the variance of same-year and next-year 99% truncated visits, ambulatory expenditure, inpatient expenditure, and total NHI expenditure were quite consistent across years and were superior to age and gender. The explanatory performance was better for ambulatory than inpatient expenditure and was comparable to the statistics demonstrated in other countries.

CONCLUSION

The ACG system worked well for Taiwanese ambulatory visits and expenditure across years. Health care authorities can introduce the ACG system to quantify the population's morbidity burdens and medical needs.

Comparative Effectiveness of Health Centers as Regular Source of Care

A 4-state (Alabama, California, Georgia, Pennsylvania) retrospective analysis of claims data from 1.6 million Medicaid beneficiaries to assess the performance of community health centers compared with other Medicaid providers (office-based and hospital-based practices) served as a regular source of care to Medicaid beneficiaries, each with at least one diagnosed ambulatory care-sensitive condition (ACSC). The health centers compared with the other Medicaid providers experienced one third fewer sentinel ACS events: 5.7 and 8.2 ACS admissions and 26.1 and 37.7 ACS emergency visits, respectively, per 100 persons. Controlling for case mix and other factors, the logistic regression results for sentinel events indicated that Medicaid beneficiaries who relied on health centers for primary care were significantly less likely to experience an ACS admission (OR = 0.89, P < .0001) or an ACS emergency visit (OR = 0.81, P < .0001) than the Medicaid beneficiaries who relied on other Medicaid providers. Sentinel ACS events can serve as efficient measures for assessing provider performance and comparing effectiveness of regular sources for primary care.

Decreased attendance at cystic fibrosis centers by children covered by managed care insurance

OBJECTIVE

The evolution of managed care has raised concerns about differential access to care for children with cystic fibrosis (CF). We tested the hypothesis that children with CF with managed care attended CF centers less frequently compared with children with non-managed care.

METHODS

We conducted a prospective cohort study by telephone every 4 months to measure access to care at CF centers among 630 randomly selected patients aged 6-18 years from 15 US CF centers. We analyzed data with unconditional logistic regression and generalized estimating equations.

RESULTS

Attendance at CF centers was significantly reduced among children with managed care (odds ratio [OR] = 0.74; 95% confidence interval [CI] = 0.57, 0.98; P=0.03) and among girls (OR=0.68; 95% CI=0.48, 0.97; P=0.04).

CONCLUSIONS

Children with CF with managed care attended CF centers significantly less frequently than those with non-managed care. These findings suggest that children with CF with managed care may not have equal access to experts in CF as children with non-managed care. Families should consider this when selecting their medical insurance plan. These findings may apply to other children with special health care needs.

Identifying hypertension-related comorbidities from administrative data: what's the optimal approach?

The objective was to determine the best strategy for identifying outpatients with hypertension-related diagnoses using Veterans Affairs (VA) administrative databases. We reviewed 1176 outpatient charts from 10 VA sites in 1999, taking the presence of 11 diagnoses relevant to hypertension management as the "gold standard" for identifying the comorbidity. We calculated agreement, sensitivity, and specificity for the chart versus several administrative data-based algorithms. Using 1999 data and requiring 1 administrative diagnosis, observed agreement ranged from 0.98 (atrial fibrillation) to 0.85 (hyperlipidemia), and kappas were generally high. Sensitivity varied from 38% (tobacco use) to 97% (diabetes); specificity exceeded 91% for 10 of 11 diagnoses. Requiring 2 years of data and 2 diagnoses improved most measures, with minimal sensitivity decrease. Agreement between the database and charts was good. Administrative data varied in its ability to identify all patients with a given diagnosis but identified accurately those without. The best strategy for case-finding required 2 diagnoses in a 2-year period.

Validation of diagnostic codes within medical services claims

OBJECTIVES

Few studies have attempted to validate the diagnostic information contained within medical service claims data, and only a small proportion of these have attempted to do so using the medical chart as a gold standard. The goal of this study is to determine the sensitivity and specificity of medical services claims diagnoses for surveillance of 14 drug disease contraindications used in drug utilization review, the Charlson comorbidity index and the Johns Hopkins Adjusted Care Group Case-Mix profile (ADGs).

STUDY DESIGN AND SETTING

Diagnoses were abstracted from the medical charts of 14,980 patients, and were used as the "gold standard," against which diagnoses obtained from the administrative database for the same patients were compared.

RESULTS

Conditions associated with drug disease contraindications with the exception of hypertension and chronic obstructive pulmonary disease (COPD) showed a specificity of 90% or higher. Sensitivity of claims data was substantially lower, with glaucoma, hypertension, and diabetes being the most sensitive conditions at 76, 69, and 64%, respectively. Each of the 18 disease conditions contained in the Charlson comorbidity index showed high specificity, but sensitivity was more variable among conditions as well as by coding definitions. Although ADG specificity was also high, the vast majority of ADGs had sensitivities of less than 60%.

CONCLUSION

The administrative data was found to have diagnoses and conditions that were highly specific but that vary greatly by condition in terms of sensitivity. To appropriately obtain diagnostic profiles, it is recommended that data pertaining to all physician billings be used.

Evaluating diagnosis-based risk-adjustment methods in a population with spinal cord dysfunction

OBJECTIVE

To examine performance of models in predicting health care utilization for individuals with spinal cord dysfunction.

DESIGN

Regression models compared 2 diagnosis-based risk-adjustment methods, the adjusted clinical groups (ACGs) and diagnostic cost groups (DCGs). To improve prediction, we added to our model: (1) spinal cord dysfunction-specific diagnostic information, (2) limitations in self-care function, and (3) both 1 and 2.

SETTING

Models were replicated in 3 populations.

PARTICIPANTS

Samples from 3 populations: (1) 40% of veterans using Veterans Health Administration services in fiscal year 1997 (FY97) (N=1,046,803), (2) veteran sample with spinal cord dysfunction identified by codes from the International Statistical Classification of Diseases, 9th Revision, Clinical Modifications (N=7666), and (3) veteran sample identified in Veterans Affairs Spinal Cord Dysfunction Registry (N=5888).

INTERVENTIONS

Not applicable.

MAIN OUTCOME MEASURES

Inpatient, outpatient, and total days of care in FY97.

RESULTS

The DCG models (R(2) range,.22-.38) performed better than ACG models (R(2) range,.04-.34) for all outcomes. Spinal cord dysfunction-specific diagnostic information improved prediction more in the ACG model than in the DCG model (R(2) range for ACG,.14-.34; R(2) range for DCG,.24-.38). Information on self-care function slightly improved performance (R(2) range increased from 0 to.04).

CONCLUSIONS

The DCG risk-adjustment models predicted health care utilization better than ACG models. ACG model prediction was improved by adding information.

Predicting Resource Utilization in a Veterans Health Administration Primary Care Population

BACKGROUND

Valid methods of predicting resource utilization in primary care populations are needed. We compared the predictive validity of a method based on diagnoses from administrative data (Adjusted Clinical Groups [ACGs]) and a method using medication profiles (Chronic Disease Index [CDI]).

METHODS

This retrospective cohort study included 31,212 primary care patients in a Veterans Health Administration (VA) network who received outpatient medication prescriptions in 1999 and who had VA utilization in 1999 and 2000. ACG and CDI classifications were determined using 1999 data. Analyses compared the predictive validity with respect to outpatient clinic visits and days of hospital care.

RESULTS

Both ACGs and CDI explained a higher proportion of the variance in outpatient visits than demographic data alone. However, explained variance was higher for ACGs. For example, ACGs explained 30.2% of the variance in total visits in 1999, compared with 8.8% for the CDI. Results were similar for 2000, although the explained variance declined for both methods (eg, 16.3% and 5.7%, respectively, for total visits). Results were similar in analyses examining the discrimination of the 2 methods to predict hospital use; for example, c statistics for ACGs and CDI scores were 0.86 versus 0.70, respectively (P <0.05), for 1999 and 0.72 and 0.65, respectively (P <0.05), for 2000.

CONCLUSION

Among VA patients, ACGs had superior predictive validity than the CDI, a newer nonproprietary method based on pharmacy data. The findings suggest that diagnosis-based measures could be preferable for ambulatory case-mix adjustment and are valid across a wide range of populations.

Impact of provider continuity on quality of care for persons with diabetes mellitus

BACKGROUND

Many patients with diabetes fail to receive recommended monitoring tests. One reason might be inadequate continuity of care. This study examined the association between provider continuity and completion of monitoring tests for patients with diabetes mellitus.

METHODS

A cross-sectional analysis was conducted on claims data from a private national health plan for 1 year (January 1, 1999, through December 31, 1999). Participants had a diagnosis of diabetes mellitus and at least 2 outpatient visits during the study year (N = 1,795). The association was measured between continuity of care with an individual provider and completion of 3 diabetes monitoring tests: a glycosylated hemoglobin test, a lipid profile, and an eye examination.

RESULTS

Eighty-one percent of patients had a glycosylated hemoglobin test, 66% had a lipid profile, and 28% had an eye examination during the study year. After controlling for demographics, number of diabetes visits, case mix, and diabetes complications, provider continuity was not significantly associated with the receipt of a glycosylated hemoglobin test (odds ratio [OR] = 0.61, 95% confidence interval [CI], 0.32-1.16), a lipid profile (OR = 0.97, 95% CI, 0.57-1.64) or an eye examination (OR = 0.60, 95% CI, 0.30-1.19). When continuity was measured only among primary care providers, there was no significant association for receipt of a glycosylated hemoglobin test (OR = 0.73, 95% CI, 0.41-1.33), a lipid profile (OR = 0.88, 95% CI, 0.53-1.47) or an eye examination (OR = 0.70, 95% CI, 0.35-1.36).

CONCLUSIONS

This study found no association between provider continuity and completion of diabetes monitoring tests in a national privately insured population. Whereas continuity might benefit other aspects of health care, it does not appear to benefit improved monitoring for diabetes.

Comparing asthma care provided to Medicaid-enrolled children in a Primary Care Case Manager plan and a staff model HMO

OBJECTIVE

To examine differences in selected processes of asthma care provided to Medicaid-enrolled children in a state-administered Primary Care Case Manager (PCCM) plan and a staff model health maintenance organization (HMO).

METHODS

Retrospective cohort study assessing performance on 6 claims-based processes of care measures that reflect aspects of pediatric asthma care recommended in national guidelines. Analyzed Medicaid and HMO claims and encounter data for 2365 children with asthma in the Massachusetts Medicaid program in 1994.

RESULTS

There were no plan differences in asthma primary care visits, asthma pharmacotherapy or follow-up care after asthma hospitalization. Children in the HMO were only 54% as likely (confidence interval [CI]: 0.37-0.80; P<.01) as those in the PCCM plan to experience an asthma emergency department (ED) visit or hospitalization. HMO-enrolled children were only half as likely (CI: 0.38-0.64; P<.001) to meet the National Committee for Quality Assurance (NCQA) definition for persistent asthma and only 32% as likely (CI: 0.19-0.56; P<.001) to have prior asthma ED visits or hospitalizations relative to children in the PCCM plan. Controlling for case mix and other covariates, children in the HMO were 2.9 times as likely (CI: 1.09-7.78; P<.05) as children in the PCCM plan to receive timely follow-up care (within 5 days) after an asthma ED visit and 1.8 times as likely (CI: 1.05-3.01; P<.05) as those in the PCCM plan to receive a specialist visit during the year.

CONCLUSIONS

In this study, the HMO served a less sick pediatric asthma population. After controlling for case mix, the staff model HMO provided greater access to asthma specialists and more timely follow-up care after asthma ED visits relative to providers in the state-administered PCCM plan. Further understanding of the impact of these differences on clinical outcomes could guide asthma improvement efforts.

Do different case-mix measures affect assessments of provider efficiency? Lessons from the Department of Veterans Affairs

Although case-mix adjustment is critical for provider profiling, little is known regarding whether different case-mix measures affect assessments of provider efficiency. We examine whether two case-mix measures, Adjusted Clinical Groups (ACGs) and Diagnostic Cost Groups (DCGs), result in different assessments of efficiency across service networks within the Department of Veterans Affairs (VA). Three profiling indicators examine variation in resource use. Although results from the ACGs and DCGs generally agree on which networks have greater or lesser efficiency than average, assessments of individual network efficiency vary depending upon the case-mix measure used. This suggests that caution should be used so that providers are not misclassified based on reported efficiency.

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.

Assessing population health care need using a claims-based ACG morbidity measure: a validation analysis in the Province of Manitoba

OBJECTIVES

To assess the ability of an Adjusted Clinical Group (ACG)-based morbidity measure to assess the overall health service needs of populations. Data Sources/Study Setting. Three population-based secondary data sources: registration and health service utilization data from fiscal year 1995-1996; mortality data from vital statistics reports from 1996-1999; and Canadian census data. The study included all continuously enrolled residents in the universal health care plan in Manitoba.

STUDY DESIGN

Using 60 small geographic areas as the units of analysis, we compared a population-based "ACG morbidity index," derived from individual ACG assignments in fiscal year 1995-1996, with the standardized mortality ratio (ages < 75 years) for 1996-1999. Key variables included a population-based socioeconomic status measure and age- and sex-standardized physician utilization ratios.

DATA EXTRACTION METHODS

The ACGs were assigned based on the complement of diagnoses assigned to persons on physician claims and hospital separation abstracts. The ACG index was created by weighting the ACGs using average health care expenditures.

PRINCIPAL FINDINGS

The ACG morbidity index had a strong positive linear relationship with the subsequent rate of premature death in the small areas of Manitoba. The ACG index was able to explain the majority of the relationships between mortality and both socioeconomic status and physician utilization.

CONCLUSIONS

In Manitoba, ACGs are closely related to premature mortality, commonly accepted as the best single indicator for health service need in populations. Issues in applying ACGs in settings where needs adjustment is a primary objective are discussed.

Developing a reliable, valid, and feasible plan for quality-of-care measurement for cancer: how should we measure?

BACKGROUND

Recent changes in the US health care delivery system have raised expectations that the medical marketplace will compete on quality and cost of care. This effort will require a systematic evaluation of the measurement of quality of care as it applies to cancer and other critical conditions.

OBJECTIVES

To articulate the components of the design of quality-of-care measurement systems that must be considered and optimally manipulated to generate feasible, reliable, and valid data pertinent to patients with cancer.

RESEARCH DESIGN

A synthesis of information obtained from literature reviews and experience.

MEASURES

Four key areas of design that influence quality-of-care measurement scores are discussed: case identification, data source, data-collection strategies, and the quality of the care-measurement model.

RESULTS

Challenges associated with these design and measurement strategies are defined and discussed.

CONCLUSIONS

Policy analyses vary as a function of measurement domains. The design of a quality-of-care measurement system should consider trade-offs between validity and burden by considering the intricate relations between domains of measurement.

Characteristics of patients with a regular source of care

This study was designed to describe patient characteristics associated with having a regular source of care among all patients who received care from large urban clinics in Manitoba over a three-year period (N = 298,222). Using administrative data, patients were classified as having a regular source of care if they made 75% or more of their total ambulatory visits to the same clinic. Overall, 44.2% of patients had a regular source of care. A logistic regression showed that children and adults aged 45 and older were more likely to have a regular source of care than patients aged 18-44. Moreover, patients with a regular source of care tended to live in more affluent neighbourhoods and were healthier than individuals with no regular source of care. Systemic changes might be needed to enhance continuity of care (e.g., mechanisms to enhance access) among vulnerable segments of the population like the poor.

Ambulatory care sensitive hospitalizations and emergency visits: experiences of Medicaid patients using federally qualified health centers

BACKGROUND

Federally Qualified Health Centers (FQHCs) serve as regular sources of preventive and primary care for low-income families within their communities and are key parts of the health care safety net.

OBJECTIVES

Compare admissions and emergency room visits for ambulatory care sensitive conditions (ACSCs) among Medicaid beneficiaries relying on FQHCs to other Medicaid beneficiaries.

RESEARCH DESIGN

Retrospective analysis of 1992 Medicaid claims data for 48,738 Medicaid beneficiaries in 24 service areas across five states.

SUBJECTS

Medicaid beneficiaries receiving more than 50% of their preventive and primary care services from FQHCs are compared with Medicaid beneficiaries receiving outpatient care from other providers in the same areas. Exclusions-managed care enrollees, beneficiaries more than age 65, dual eligibles (Medicaid and Medicare), and institutionalized populations.

MEASURES

Admissions and emergency room (ER) visits for a set of chronic and acute conditions, known in the literature as ambulatory care sensitive conditions (ACSCs).

RESULTS

Medicaid beneficiaries receiving outpatient care from FQHCs were less likely to be hospitalized (1.5% vs. 1.9%, P < 0.007) or seek ER care (14.9% vs. 15.7%, P < 0.02) for ACSCs than the comparison group. Controlling for case mix and other demographic variables, the odds ratios were, for hospitalizations, OR, 0.80; 95% CI, 0.67 to 0.95; P < 0.01, and for ER visits, OR, 0.87; 95% CI, 0.82 to 0.92; P < 0.001.

CONCLUSIONS

Having a regular source of care such as FQHCs can significantly reduce the likelihood of hospitalizations and ER visits for ACSCs. If the reported differentials in ACSC admissions and ER visits were consistently achieved for all Medicaid beneficiaries, substantial savings might be realized.

Performance of the ACG case-mix system in two Canadian provinces

BACKGROUND

While the adjusted clinical group (ACG) system has been extensively validated in the United States, its use in other developed nations has been limited. This article examines the performance of the system in 2 Canadian provinces and assesses the extent to which ACGs can account for same-year and next-year health care expenditures.

METHODS

The study population included all residents of Manitoba and British Columbia who were continuously enrolled in the provincial health plans from April 1, 1995, to March 31, 1997. ACGs were assigned through diagnoses from fee-for-service physician claims and hospital separation records. "Physician" costs were calculated from the fee-for-service tariffs, and for Manitobans, "total" costs were also computed by combining physician and hospital costs. Linear regression was used to examine the ability of the ACG system to explain variation in individual costs (truncated at the 99th percentile).

RESULTS

The British Columbia and Manitoba data were generally acceptable, with fewer than 2% rejected diagnoses. Higher costs were associated with both the accumulation of morbidities and their relative severity. For physician costs, the ACG system explained approximately 50% and approximately 25% of the variation in same-year and next-year truncated costs, respectively. For total costs, the system explained approximately 40% and approximately 14% of these respective costs.

CONCLUSIONS

The application of ACGs in Canada is feasible using existing data. The ability of the ACG system to explain variation in costs is similar to that found in US health systems. While application of ACGs in Canada shows promise, further research is required to examine how closely they reflect population morbidity burdens and health care needs.

Cost implications for the use of inhaled anti-inflammatory medications in the treatment of asthma

OBJECTIVE

To compare the expected costs of treating patients with asthma with versus without inhaled anti-inflammatory medications, adjusting for other factors that also influence medical care expenditures.

DESIGN

Nonlinear exponential regression analyses were used to estimate relationships between medical care expenditures and treatment with inhaled corticosteroids, sodium cromoglycate (cromolyn) or nedocromil. The regressions adjusted for differences in patients' demographics, location, plan type and severity of illness.

SETTING

Large, self-insured, corporate-sponsored medical plans represented in MarketScan database.

PATIENTS AND PARTICIPANTS

7466 continuously enrolled patients with asthma.

INTERVENTIONS

Treatment with inhaled corticosteroids, sodium cromoglycate or nedocromil.

MAIN OUTCOME MEASURES

(i) Total inpatient, outpatient and pharmaceutical expenditures; and (ii) asthma-related expenditures in the 1996 calendar year.

RESULTS

If all patients had been treated with inhaled anti-inflammatory drugs, total expenditures would be expected to be about $US944.82 per patient lower, on average, than would be the case if no patients received these drugs. Asthma-related expenditures would be about $US498.74 per patient higher, on average, if all patients were treated with these drugs.

CONCLUSIONS

Using inhaled anti-inflammatory agents would be associated with higher asthma-related expenditures but lower total expenditures. Treatment with inhaled anti-inflammatory drugs may represent an investment in better care that pays off with better health and lower total medical care expenditures.

Influence of patient education on profiles of physician practices

BACKGROUND

Few data are available about the effect of patient socioeconomic status on profiles of physician practices.

OBJECTIVE

To determine the ways in which adjustment for patients' level of education (as a measure of socioeconomic status) changes profiles of physician practices.

DESIGN

Cross-sectional survey of patients in physician practices.

SETTING

Managed care organization in western New York State.

PARTICIPANTS

A random sample of 100 primary care physicians and 50 consecutive patients seen by each physician.

MEASUREMENTS

Ranks of physicians for patient physical and mental health (Short Form 12-Item Health Survey) and satisfaction (Patient Satisfaction Questionnaire), adjusted for patient age, sex, morbidity, and education.

RESULTS

Physicians whose patients had a lower mean level of education had significantly better ranks for patient physical and mental health status after adjustment for patients' level of education level than they did before adjustment (P < 0.001); this result was not seen for patient satisfaction. After adjustment for patients' level of education, each 1-year decrease in mean educational level was associated with a rank that improved by 8.1 (95% CI, 6.6 to 9.6) for patient physical health status and by 4.9 (CI, 3.9 to 5.9) for patient mental health status. Adjustment for education had similar effects for practices with more educated patients and those with less educated patients.

CONCLUSIONS

Profiles of physician practices that base ratings of physician performance on patients' physical and mental health status are substantially affected by patients' level of education. However, these results do not suggest that physicians who care for less educated patients provide worse care. Physician profiling should account for differences in patients' level of education.

Patient race and ethnicity in primary care management of child behavior problems: a report from PROS and ASPN. Pediatric Research in Office Settings. Ambulatory Sentinel Practice Network

BACKGROUND

Minority persons have less access to many specialty treatments and services, possibly because of clinician biases. It is not clear whether any such biases exist in primary care settings, especially for children with psychosocial problems.

OBJECTIVES

The objective was to compare primary care recognition and treatment of pediatric psychosocial problems among African American, Hispanic American and European American patients.

DESIGN

A survey was made of parents and respective clinicians in primary care offices in two large practice-based research networks (PROS and ASPN) from 44 states, Canada, and Puerto Rico. Mixed regression analyses were employed to control for patient, clinician, and practice effects.

SUBJECTS

The subjects were 14,910 children aged 4 to 15 years seen consecutively for non-emergent care by 286 primary care clinicians in office-based practice.

MEASURES

Measures were parents' report for sociodemographics and behavioral symptoms using the Pediatric Symptom Checklist, and clinicians' report of psychosocial problems, type, management, and severity.

RESULTS

Of the sample, 8.0% were African American youth, 9.5% were Hispanic American youth, and 82.5% were European American youth. After controlling for other factors, race and ethnicity were not associated with any differences in psychotropic drug prescribing, counseling, referral, or recognition of psychosocial problems. Clinicians reported spending slightly more time with minority patients.

CONCLUSION

Race and ethnic status were not related to receipt of mental health services for children in primary care offices, suggesting that clinician biases may not be the primary cause of the racial differences in services noted earlier research. Improving services for minority youth may require increasing access to office-based primary care.

Identifying persons with diabetes using Medicare claims data

The objective of this study was to develop and validate a method for identifying Medicare beneficiaries with diabetes by using Medicare claims data. We used self-reports of diabetes status from participants in the Medicare Current Beneficiary Survey to determine disease status, and then we examined these participants' Medicare claims. Using self-reported diabetes status as the "gold standard," we determined the sensitivity, specificity, and reliability of claims data in identifying beneficiaries with diabetes. We found that to construct a method that is adequately sensitive (> or = 70%), highly specific (> or = 97.5%), and reliable (kappa > or = 0.80), researchers must combine information from different types of Medicare claims files, use 2 years of data to identify cases, and require at least 2 diagnoses of diabetes among claims involving ambulatory care. Since these criteria are met by more than one method, the choice of method should be governed by the goals of the research as well as more practical concerns.

Ambulatory care sensitive hospitalization rates in the aged Medicare population in Utah, 1990 to 1994: a rural-urban comparison

The objective of this study is to compare the likelihood of hospitalization for conditions that are related to the adequacy and use of ambulatory health care services for Medicare beneficiaries residing in rural and urban regions in Utah. The Health Care Financing Administration's (HCFA) hospital discharge database (Utah hospitals: 1990 to 1994) was used to estimate hospitalization rates (with adjustment for out-of-state admissions) for ambulatory care sensitive conditions. Population estimates were obtained from HCFA beneficiary files. Regional hospitalization rates were obtained through ZIP code matching of the hospital discharge and beneficiary files. Medicare beneficiaries aged 65 and older residing in Utah during 1990 to 1994 are the subjects for the study. The main outcome measures include age and sex-adjusted hospitalization rates by region for the entire state and rate ratio estimates for nonurban regions. The results of the study show that Medicare beneficiaries residing in two rural-frontier regions were more likely than urban beneficiaries to be hospitalized for ambulatory care sensitive conditions. Rate ratio estimates were greater than 1.4 for both regions during the study period. These findings suggest a pattern of an increased burden of avoidable secondary complications and disease progression among Utah Medicare beneficiaries residing in some rural regions. This increased burden may be the result of limitations in the ambulatory care system, medical care provider supply, and/or beneficiary propensity to seek care. Variation in disease prevalence or hospital use patterns for these conditions also may be responsible for all or part of the observed variation in ambulatory care sensitive admission rates.

Application of the ambulatory care groups in the primary care of a European national health care system: does it work?

BACKGROUND

Ambulatory Care Groups (ACGs), a US case-mix system that uses the patient as the unit of analysis, is particularly appropriate for health care systems in which physicians serve a defined list of patients.

OBJECTIVE

To determine the extent to which the categorization of patients according to ACGs would account for the utilization of primary care services in a national health care system within the European Union.

METHODS

Of all subjects continuously assigned to 9 physicians from public primary health care centers in Bizkaia, Basque Country (Spain) over a 12-month period, those visited at least once (n = 9,093) were included. According to the subject's age, sex, and ICD-9-CM diagnoses assigned during a year of patient-provider encounters, patients were classified by means of the ACGs system.

RESULTS

Multiple linear regression analyses indicated that age and sex did not explain more than 7.1% of the variance in annual visits made by adults and 25.7% by children to primary care physicians. However, the r2 adjusted to the ACGs model was 50% and 48%, respectively, and even higher, that is 58% and 64% for another component of the system, the Ambulatory Diagnostic Groups (ADGs).

CONCLUSIONS

Those results support the inadequacy of using the patient's age and sex alone to estimate physicians' workload in the primary health setting and the need to consider morbidity categories. The ACGs case-mix system is a useful tool for incorporating patients' morbidity in the explanation of the use of primary health care services in a European national health system.

A comparison of ambulatory Medicaid claims to medical records: a reliability assessment

This study compares the documentation of ambulatory care visits and diagnoses in Medicaid paid claims and in medical records. Data were obtained from Maryland Medicaid's 1988 paid claims files for 2407 individuals who were continuously enrolled for the fiscal year, had at least one billed visit for one of six indicator conditions, and had received the majority of their care from one provider. The patients sampled were also stratified on the basis of the case-mix adjusted cost of their usual source of care. The medical records for these individuals as maintained by their usual source of care were abstracted by trained nurse reviewers to compare claims and record information. Linked claim and medical record data for sampled patients were used to calculate: (i) the percent of billed visits documented in the record, (ii) the percent of medical record visits where both the date and the diagnosis agreed with the claims data, and (iii) the ratio of medical record visits to visits from billed claims. Included in the analysis were independent variables specifying place of residence, type and costliness of usual care source, level of patient utilization, and indicator condition on which patient was sampled. Ninety percent of the visits chronicled in the paid claims were documented in the medical record with 82% agreeing on both date and diagnosis. Compared to the medical records kept by private physicians and community health centers, a significantly lower percent of hospital medical records agreed with the claims data. Total volume of visits was 2.6% higher in the medical records than in the claims. Claims data substantially understated visits in the medical record by 25% for low cost providers and by 41% for patients with low use rates (based on claims information). Conversely, medical records substantially understated billed visits by 19% for rural patients and by 10% for persons with high visit rates. Although Medicaid claims are relatively accurate and useful for examining average ambulatory use patterns, they are subject to significant biases when comparing subgroups of providers classified by case-mix adjusted cost and patients classified by utilization rates. Medicaid programs are using claims data for profiling and performance assessment need to understand the limitations of administrative data.

The organizational structure of medical group practices in a managed care environment

This article analyzes the organizational structures of 155 medical group practices providing services in the highly competitive managed care environment in the upper midwest. The structure of the group practices and the methods of physicians' payment are analyzed in terms of the proportion of revenue obtained from financial risk-sharing managed care payment systems and the length of time involved with those systems.

Health services research and the endocrinologist

This article highlights the importance of health services research to endocrinologists. The content and goals of health services research are defined, and, with examples related to endocrinology, the field's focus and key themes are described and its methods and sources of data delineated. Considerations that informed readers should keep in mind when reading this literature are illustrated, with a recent example that has important implications for the role of endocrinologists in the management of diabetic patients.