Biomedical subjects

John L Adams

Publications and source records attributed to John L Adams.

At least 19 recordsLinked to original sources

PubMed2006

Who is at greatest risk for receiving poor-quality health care?

BACKGROUND: American adults frequently do not receive recommended health care. The extent to which the quality of health care varies among sociodemographic groups is unknown. METHODS: We used data from medical records and telephone interviews of a random sample of people living in 12 communities to assess the quality of care received by those who had made at least one visit to a health care provider during the previous two years. We constructed aggregate scores from 439 indicators of the quality of care for 30 chronic and acute conditions and for disease prevention. We estimated the rates at which members of different sociodemographic subgroups received recommended care, with adjustment for the number of chronic and acute conditions, use of health care services, and other sociodemographic characteristics. RESULTS: Overall, participants received 54.9 percent of recommended care. Even after adjustment, there was only moderate variation in quality-of-care scores among sociodemographic subgroups. Women had higher overall scores than men (56.6 percent vs. 52.3 percent, P<0.001), and participants below the age of 31 years had higher scores than those over the age of 64 years (57.5 percent vs. 52.1 percent, P<0.001). Blacks (57.6 percent) and Hispanics (57.5 percent) had slightly higher scores than whites (54.1 percent, P<0.001 for both comparisons). Those with annual household incomes over 50,000 dollars had higher scores than those with incomes of less than 15,000 dollars (56.6 percent vs. 53.1 percent, P<0.001). CONCLUSIONS: The differences among sociodemographic subgroups in the observed quality of health care are small in comparison with the gap for each subgroup between observed and desirable quality of health care. Quality-improvement programs that focus solely on reducing disparities among sociodemographic subgroups may miss larger opportunities to improve care.

Adolescent↗

PubMed2006

What is the concordance between the medical record and patient self-report as data sources for ambulatory care?

BACKGROUND: The validity of quality of care assessments relies upon data quality, yet little is known about the relative completeness and validity of data sources for evaluating the quality of care. OBJECTIVES: We evaluated concordance between ambulatory medical record and patient survey data. Levels of concordance, variations by type of item, sources of disagreement between data sources, and implications for quality of care assessment efforts are discussed. DESIGN AND SUBJECTS: This was an observational study that included 1270 patients sampled from 39 West Coast medical organizations with at least 1 of the following: diabetes, ischemic heart disease, asthma or chronic obstructive pulmonary disease, or low back pain. MEASURES: Items from both data sources were grouped into 4 conceptual domains: diagnosis, clinical services delivered, counseling and referral, and medication use. We present total agreement, kappa, sensitivity, and specificity at the item and domain-levels and for all items combined. RESULTS: We found good concordance between survey and medical records overall, but there was substantial variation within and across domains. The worst concordance was in the counseling and referrals domain, the best in the medication use domain. Patients were able to report with good sensitivity on memorable items. CONCLUSIONS: Quality ratings are likely to vary in differing directions, depending on the data source used. The most appropriate data source for analyses of components of and overall quality of care must be considered in light of study objectives and resources. We recommend data collection from multiple sources to most accurately portray the patient and provider experience of medical care.

Adolescent↗

PubMed2006

Evaluating disease management programme effectiveness: an introduction to the regression discontinuity design.

Although disease management (DM) has been in existence for over a decade, there is still much uncertainty as to its effectiveness in improving health status and reducing medical cost. The main reason is that most programme evaluations typically follow weak observational study designs that are subject to bias, most notably selection bias and regression to the mean. The regression discontinuity (RD) design may be the best alternative to randomized studies for evaluating DM programme effectiveness. The most crucial element of the RD design is its use of a 'cut-off' score on a pre-test measure to determine assignment to intervention or control. A valuable feature of this technique is that the pre-test measure does not have to be the same as the outcome measure, thus maximizing the programme's ability to use research-based practice guidelines, survey instruments and other tools to identify those individuals in greatest need of the programme intervention. Similarly, the cut-off score can be based on clinical understanding of the disease process, empirically derived, or resource-based. In the RD design, programme effectiveness is determined by a change in the pre-post relationship at the cut-off point. While the RD design is uniquely suitable for DM programme evaluation, its success will depend, in large part, on fundamental changes being made in the way DM programmes identify and assign individuals to the programme intervention.

Disease Management↗

PubMed2006

Strengthening the case for disease management effectiveness: un-hiding the hidden bias.

As is the case with most health care program evaluations, disease management (DM) programs typically follow an observational study design, indicating that randomization to treatment or control was not performed. The foremost limitation of observational studies, compared to randomized studies, is that the only biases that can be controlled for are those associated with observed variables. Hidden bias refers to all those unobserved covariates that may distort the conclusions of the study. This paper introduces a sensitivity analysis that is used to determine the magnitude of hidden bias necessary to alter the conclusion that a DM program intervention was indeed effective.

Bias↗

PubMed2006

Evaluating disease management programme effectiveness: an introduction to instrumental variables.

This paper introduces the concept of instrumental variables (IVs) as a means of providing an unbiased estimate of treatment effects in evaluating disease management (DM) programme effectiveness. Model development is described using zip codes as the IV. Three diabetes DM outcomes were evaluated: annual diabetes costs, emergency department (ED) visits and hospital days. Both ordinary least squares (OLS) and IV estimates showed a significant treatment effect for diabetes costs (P = 0.011) but neither model produced a significant treatment effect for ED visits. However, the IV estimate showed a significant treatment effect for hospital days (P = 0.006) whereas the OLS model did not. These results illustrate the utility of IV estimation when the OLS model is sensitive to the confounding effect of hidden bias.

Data Interpretation, Statistical↗

PubMed2006

Evaluating program effectiveness using the regression point displacement design.

Most health care initiatives are evaluated using observational study designs in lieu of randomized controlled trials (RCT) due primarily to resource limitations. However, although observational studies are less expensive to implement and evaluate, they are also more problematic in determining causality than the RCT. This trade off is most apparent in the initial planning stage of program development. An RCT is generally preferred though the cost of implementing a pilot program using the RCT might outstrip the potential benefit if the desired results are not obtained. This article describes a simple quasi-experimental model called the regression point displacement (RPD) design, which compares the prepost results of a single or multiple treatment groups to that of a control population. This design has shown great potential in evaluating health care pilot programs or demonstration projects-especially those that are community based-due to its relative ease of implementation and low cost of analysis.

Humans↗

PubMed2006

The quality of obstructive lung disease care for adults in the United States as measured by adherence to recommended processes.

BACKGROUND: The extent to which patients with obstructive lung disease receive recommended processes of care is largely unknown. We assessed the quality of care delivered to a national sample of the US population. METHODS: We extracted medical records for 2 prior years from consenting participants in a random telephone survey in 12 communities and measured the quality of care provided with 45 explicit, process-based quality indicators for asthma and COPD developed using the modified Delphi expert panel methodology. Multivariate logistic regression evaluated effects of patient demographics, insurance, and other characteristics on the quality of health care. RESULTS: We identified 2,394 care events among 260 asthma participants and 1,664 events among 169 COPD participants. Overall, participants received 55.2% of recommended care for obstructive lung disease. Asthma patients received 53.5% of recommended care; routine management was better (66.9%) than exacerbation care (47.8%). COPD patients received 58.0% of recommended care but received better exacerbation care (60.4%) than routine care (46.1%). Variation was seen in mode of care with considerable deficits in documenting recommended aspects of medical history (41.4%) and use of diagnostic studies (40.1%). Modeling demonstrated modest variation between racial groups, geographic areas, insurance types, and other characteristics. CONCLUSIONS: Americans with obstructive lung disease received only 55% of recommended care. The deficits and variability in the quality of care for obstructive lung disease present ample opportunity for quality improvement. Future endeavors should assess reasons for low adherence to recommended processes of care and assess barriers in delivery of care.

Adult↗

PubMed2005

Quality of care is associated with survival in vulnerable older patients.

BACKGROUND: Although assessment of the quality of medical care often relies on measures of process of care, the linkage between performance of these process measures during usual clinical care and subsequent patient outcomes is unclear. OBJECTIVE: To examine the link between the quality of care that patients received and their survival. DESIGN: Observational cohort study. SETTING: Two managed care organizations. PATIENTS: Community-dwelling high-risk patients 65 years of age or older who were continuously enrolled in the managed care organizations from 1 July 1998 to 31 July 1999. MEASUREMENTS: Quality of care received by patients (as measured by a set of quality indicators covering 22 clinical conditions) and their survival over the following 3 years. RESULTS: The 372 vulnerable older patients were eligible for a mean of 21 quality indicators (range, 8 to 54) and received, on average, 53% of the care processes prescribed in quality indicators (range, 27% to 88%). Eighty-six (23%) persons died during the 3-year follow-up. There was a graded positive relationship between quality score and 3-year survival. After adjustment for sex, health status, and health service use, quality score was not associated with mortality for the first 500 days, but a higher quality score was associated with lower mortality after 500 days (hazard ratio, 0.64 [95% CI, 0.49 to 0.84] for a 10% higher quality score). LIMITATIONS: The observational design limits causal inference regarding the effect of quality of care on survival. CONCLUSIONS: Better performance on process quality measures is strongly associated with better survival among community-dwelling vulnerable older adults.

Aged↗

PubMed2005

Imputation of SF-12 health scores for respondents with partially missing data.

OBJECTIVE: To create an efficient imputation algorithm for imputing the SF-12 physical component summary (PCS) and mental component summary (MCS) scores when patients have one to eleven SF-12 items missing. STUDY SETTING: Primary data collection was performed between 1996 and 1998. STUDY DESIGN: Multi-pattern regression was conducted to impute the scores using only available SF-12 items (simple model), and then supplemented by demographics, smoking status and comorbidity (enhanced model) to increase the accuracy. A cut point of missing SF-12 items was determined for using the simple or the enhanced model. The algorithm was validated through simulation. DATA COLLECTION: Thirty-thousand-three-hundred and eight patients from 63 physician groups were surveyed for a quality of care study in 1996, which collected the SF-12 and other information. The patients were classified as "chronic" patients if they reported that they had diabetes, heart disease, asthma/chronic obstructive pulmonary disease, or low back pain. A follow-up survey was conducted in 1998. PRINCIPAL FINDINGS: Thirty-one percent of the patients missed at least one SF-12 item. Means of variance of prediction and standard errors of the mean imputed scores increased with the number of missing SF-12 items. Correlations between the observed and the imputed scores derived from the enhanced models were consistently higher than those derived from the simple model and the increments were significant for patients with > or =6 missing SF-12 items (p<.03). CONCLUSION: Missing SF-12 items are prevalent and lead to reduced analytical power. Regression-based multi-pattern imputation using the available SF-12 items is efficient and can produce good estimates of the scores. The enhancement from the additional patient information can significantly improve the accuracy of the imputed scores for patients with > or =6 items missing, leading to estimated scores that are as accurate as that of patients with <6 missing items.

Adult↗

PubMed2004

Sociodemographic differences in use of preventive services by women enrolled in Medicare+Choice plans.

BACKGROUND: We examined the effect of sociodemographic factors on the receipt of mammography, colorectal cancer screening, and influenza vaccinations by women enrolled in two Medicare+Choice health plans. METHODS: Administrative and survey data for 2,698 female health plan members was analyzed using multivariate logistic and ordinal logistic regression to assess the effects of enrollee characteristics on use of preventive services. RESULTS: Age, race and wealth were associated with the receipt of one or more preventive services. Older women were less likely to receive mammograms, wealthier women were more likely to receive mammograms and CRC screening, and Black women were more likely to receive CRC screening but less likely to receive influenza vaccinations. Wealthier women received a greater number of preventive services, other things equal, while older women received fewer preventive services. CONCLUSIONS: Race and wealth continue to be important factors in the receipt of preventive services by elderly women, though not always consistent with historical trends. Medicare+Choice plans should consider strategies to further reduce racial and wealth disparities in the use of preventive services.

Aged↗

PubMed2004

Using an empirical method for establishing clinical outcome targets in disease management programs.

The disease management (DM) industry is being scrutinized now more than ever before, with programs being asked to demonstrate improvement in clinical quality in addition to the expected reduction in medical costs. In healthcare, clinical improvement targets are often set at levels considered to be clinically meaningful. This difference may or may not be statistically significant. The term "effect size" refers to the smallest difference that could be detected statistically. This paper proposes a simple empirical method for determining the minimum expected improvement level for DM clinical outcome measures in which two proportions are being compared. This method is useful in situations where the outcome measure does not lend itself to be determined by the subjective judgment of medical expertise. Graphical displays are provided for the reader to use to help determine appropriate effect sizes for studies in lieu of, or in addition to, the statistical calculations.

Cost Control↗

PubMed2004

Evaluating disease management program effectiveness: an introduction to survival analysis.

Currently, the most widely used method in the disease management industry for evaluating program effectiveness is the "total population approach." This model is a pretest-posttest design, with the most basic limitation being that without a control group, there may be sources of bias and/or competing extraneous confounding factors that offer plausible rationale explaining the change from baseline. Survival analysis allows for the inclusion of data from censored cases, those subjects who either "survived" the program without experiencing the event (e.g., achievement of target clinical levels, hospitalization) or left the program prematurely, due to disenrollement from the health plan or program, or were lost to follow-up. Additionally, independent variables may be included in the model to help explain the variability in the outcome measure. In order to maximize the potential of this statistical method, validity of the model and research design must be assured. This paper reviews survival analysis as an alternative, and more appropriate, approach to evaluating DM program effectiveness than the current total population approach.

Disease Management↗

PubMed2004

Use of preventive services by men enrolled in Medicare+Choice plans.

OBJECTIVES: We examined the effect of demographic and socioeconomic factors on use of preventive services (prostate-specific antigen testing, colorectal cancer screening, and influenza vaccination) among elderly men enrolled in 2 Medicare+Choice health plans. METHODS: Data were derived from administrative files and a survey of 1915 male enrollees. We used multivariate logistic regression to assess the effects of enrollee characteristics on preventive service use. RESULTS: Age, marital status, educational attainment, and household wealth were associated with receipt of one or more preventive services. However, the effects of these variables were substantially attenuated relative to earlier studies of Medicare. CONCLUSIONS: Some Medicare HMOs have been successful in attenuating racial and socioeconomic disparities in the use of preventive services by older men.

Aged↗

PubMed2004

Generalizing disease management program results: how to get from here to there.

For a disease management (DM) program, the ability to generalize results from the intervention group to the population, to other populations, or to other diseases is as important as demonstrating internal validity. This article provides an overview of the threats to external validity of DM programs, and offers methods to improve the capability for generalizing results obtained through the program. The external validity of DM programs must be evaluated even before program selection and implementation are begun with a prospective new client. Any fundamental differences in characteristics between individuals in an established DM program and in a new population/environment may limit the ability to generalize.

Disease Management↗

PubMed2003

Patterns of care for open-angle glaucoma in managed care.

OBJECTIVES: To describe patterns of care for primary open-angle glaucoma (POAG) and assess conformance with the American Academy of Ophthalmology's Preferred Practice Pattern (PPP). METHODS: We obtained administrative, survey, and eye care records data on 395 working-age patients with POAG enrolled in 6 managed care plans between 1997 and 1999. We assessed processes of care at the initial and follow-up visits, control of intraocular pressure (IOP), intervals between visits and visual field tests, and adjustments in therapy. RESULTS: We found high rates of performance on most recommended processes during initial evaluations, although only 53% of patients received an optic nerve head photograph or drawing and only 1% had a target IOP level documented. Recommended processes were performed at 80% to 97% of follow-up visits. Using loose criteria for control, IOP was controlled in 66% of follow-up visits for patients with mild glaucoma and 52% of visits for patients with moderate to severe glaucoma. Intervals between visits and visual field tests were generally consistent with PPP recommendations. Adjustments in therapy were more likely with worse control of IOP, although adjustments occurred in only half of visits where the IOP was 30 mm Hg or higher. CONCLUSIONS: Our study suggests that, in many respects, patients with POAG are receiving care that is consistent with the PPP. However, care is falling short on several key aspects, and POAG may be undertreated relative to standards for IOP control established in recent clinical trials.

Antihypertensive Agents↗

PubMed2003

An assessment of the total population approach for evaluating disease management program effectiveness.

A key challenge currently facing the disease management industry is accurately demonstrating program effectiveness at controlling utilization of services and medical costs of populations with chronic disease. The most common method used in the disease management industry to date for determining financial outcomes is referred to as the "total population approach." This model is a pretest-posttest design, which is a relatively weak research and evaluation technique. This paper describes the "total population approach," details many of the biases and confounding factors that may influence outcomes using this method, and illustrates the potential consequences of these factors.

Bias↗

PubMed2003

Evaluating disease management program effectiveness: an introduction to time-series analysis.

Currently, the most widely used method in the disease management (DM) industry for evaluating program effectiveness is referred to as the "total population approach." This model is a pretest-posttest design, with the most basic limitation being that without a control group, there may be sources of bias and/or competing extraneous confounding factors that offer a plausible rationale explaining the change from baseline. Furthermore, with the current inclination of DM programs to use financial indicators rather than program-specific utilization indicators as the principal measure of program success, additional biases are introduced that may cloud evaluation results. This paper presents a non-technical introduction to time-series analysis (using disease-specific utilization measures) as an alternative, and more appropriate, approach to evaluating DM program effectiveness than the current total population approach.

Disease Management↗

PubMed2003

Practice characteristics and HMO enrollee satisfaction with specialty care: an analysis of patients with glaucoma and diabetic retinopathy.

BACKGROUND: The specialist's role in caring for managed care patients is likely to grow. Thus, assessing the correlates of patient satisfaction with specialty care is essential. OBJECTIVE: To examine the association between characteristics of eye care practices and satisfaction with eye care among working age patients with open-angle glaucoma (OAG) or diabetic retinopathy (DR). SUBJECTS/STUDY SETTING: A total of 913 working age patients with OAG or DR enrolled in six commercial managed care health plans. The patients were treated in 144 different eye care practices. STUDY DESIGN: We used a patient survey to obtain information on patient characteristics and satisfaction with eye care, measured by scores on satisfaction subscales of the 18-item Patient Satisfaction Questionnaire. We used a survey of eye care practices to obtain information on practice characteristics, including provider specialties, practice organization, financial features, and utilization and quality management systems. We estimated logistic regression models to assess the association of patient and practice characteristics with high levels of patient satisfaction. PRINCIPAL FINDINGS: Treatment in a practice with a glaucoma specialist (for OAG patients) or a retina specialist (for DR patients) was associated with higher satisfaction, whereas treatment in a practice that obtained a high proportion of its revenues from capitation payments or in a group practice where providers obtained a high proportion of their incomes from bonuses was associated with lower satisfaction. CONCLUSIONS: Many eye care patients prefer to be treated by specialists with expertise in their conditions. Financial arrangement features of eye care practices also are associated with patient satisfaction with care. The most likely mechanisms underlying these associations are effects on provider behavior and satisfaction, which in turn influence patient satisfaction. Managed care plans and provider groups should aim to minimize the negative impact of managed care features on patient satisfaction.

Diabetic Retinopathy↗