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Use of Data-Driven Methods to Predict Long-term Patterns of Health Care Spending for Medicare Patients.

ABSTRACT: Importance:Current approaches to predicting health care costs generally rely on a single composite value of spending and focus on short time horizons. By contrast, examining patients' spending patterns using dynamic measures applied over longer periods may better identify patients with different spending and help target interventions to those with the greatest need. Objective:To classify patients by their long-term, dynamic health care spending patterns using a data-driven approach and assess the ability to predict spending patterns, particularly using characteristics that are potentially modifiable through intervention. Design, Setting, and Participants:This cohort study used a retrospective cohort design from a random nationwide sample of Medicare fee-for-service administrative claims data to identify beneficiaries aged 65 years or older with continuous eligibility from 2011 to 2013. Statistical analysis was performed from August 2018 to December 2019. Main Outcomes and Measures:Group-based trajectory modeling was applied to the claims data to classify the Medicare beneficiaries by their total health care spending patterns over a 2-year period. The ability to predict membership in each trajectory spending group was assessed using generalized boosted regression, a data mining approach to model building and prediction, with split-sample validation. Models were estimated using (1) prior-year predictors and (2) prior-year predictors potentially modifiable through intervention measured in the claims data. These models were evaluated using validated C-statistics. The relative influence of individual predictors in the models was evaluated. Results:Among the 329?476 beneficiaries, the mean (SD) age was 76.0 (7.2) years and 190?346 (57.8%) were female. This final 5-group model included a minimal-user group (group 1, 37 572 individuals [11.4%]), a low-cost group (group 2, 48 575 individuals [14.7%]), a rising-cost group (group 3, 24 736 individuals [7.5%]), a moderate-cost group (group 4, 83 338 individuals [25.3%]), and a high-cost group (group 5, 135 255 individuals [41.2%]). Potentially modifiable characteristics strongly predicted these patterns (C-statistics range: 0.68-0.94). For groups with progressively increasing spending in particular, the most influential factors were number of medications (relative influence: 29.2), number of office visits (relative influence: 30.3), and mean medication adherence (relative influence: 33.6). Conclusions and Relevance:Using a data-driven approach, distinct spending patterns were identified with high accuracy. The potentially modifiable predictors of membership in the rising-cost group represent important levers for early interventions that may prevent later spending increases. This approach could be adapted by organizations to target quality improvement interventions, particularly because numerous health care organizations are increasingly using these routinely collected data.

SUBMITTER: Lauffenburger JC

PROVIDER: S-EPMC7573679 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature

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Use of Data-Driven Methods to Predict Long-term Patterns of Health Care Spending for Medicare Patients.

Lauffenburger Julie C JC Mahesri Mufaddal M Choudhry Niteesh K NK

JAMA network open 20201001 10

<h4>Importance</h4>Current approaches to predicting health care costs generally rely on a single composite value of spending and focus on short time horizons. By contrast, examining patients' spending patterns using dynamic measures applied over longer periods may better identify patients with different spending and help target interventions to those with the greatest need.<h4>Objective</h4>To classify patients by their long-term, dynamic health care spending patterns using a data-driven approac ...[more]

PMID: 33074324

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Project description:Background and objectivesDespite representing 1% of the population, beneficiaries on long-term dialysis account for over 7% of Medicare's fee-for-service spending. Because of their focus on care coordination, Accountable Care Organizations may be an effective model to reduce spending inefficiencies for this population. We analyzed Medicare data to examine time trends in long-term dialysis beneficiary alignment to Accountable Care Organizations and differences in spending for those who were Accountable Care Organization aligned versus nonaligned.Design, setting, participants, & measurementsIn this retrospective cohort study, beneficiaries on long-term dialysis between 2009 and 2016 were identified using a 20% random sample of Medicare beneficiaries. Trends in alignment to an Accountable Care Organization were compared with alignment of the general Medicare population from 2012 to 2016. Using an interrupted time series approach, we examined the association between Accountable Care Organization alignment and the primary outcome of total spending for long-term dialysis beneficiaries from prior to Accountable Care Organization implementation (2009-2011) through implementation of the Comprehensive ESRD Care model in October 2015. We fit linear regression models with generalized estimating equations to adjust for patient characteristics.ResultsDuring the study period, 135,152 beneficiaries on long-term dialysis were identified. The percentage of long-term dialysis beneficiaries aligned to an Accountable Care Organization increased from 6% to 23% from 2012 to 2016. In the time series analysis, spending on Accountable Care Organization-aligned beneficiaries was $143 (95% confidence interval, $5 to $282) less per beneficiary-quarter than spending for nonaligned beneficiaries. In analyses stratified by whether beneficiaries received care from a primary care physician, savings by Accountable Care Organization-aligned beneficiaries were limited to those with care by a primary care physician ($235; 95% confidence interval, $73 to $397).ConclusionsThere was a substantial increase in the percentage of long-term dialysis beneficiaries aligned to an Accountable Care Organization from 2012 to 2016. Moreover, in adjusted models, Accountable Care Organization alignment was associated with modest cost savings among long-term dialysis beneficiaries with care by a primary care physician.

Project description:BackgroundThe Centers for Medicare & Medicaid Services launched the 4-year Comprehensive Primary Care Initiative (CPC Classic) in 2012 and its 5-year successor, CPC Plus (CPC+), in 2017 to test whether improving primary care delivery in five areas-and providing practices with financial and technical support-reduced spending and improved quality. This is the first study to examine long-term effects of a primary care practice transformation model.ObjectiveTo test whether long-term primary care transformation-the 4-year CPC Classic and the first 2 years of its successor, CPC+-reduced hospitalizations, emergency department (ED) visits, and spending over 6 years.DesignWe used a difference-in-differences analysis to compare outcomes for beneficiaries attributed to CPC Classic practices with outcomes for beneficiaries attributed to comparison practices during the year before and 6 years after CPC Classic began.ParticipantsThe study involved 565,674 Medicare fee-for-service beneficiaries attributed to 502 CPC Classic practices and 1,165,284 beneficiaries attributed to 908 comparison practices, with similar beneficiary-, practice-, and market-level characteristics as the CPC Classic practices.InterventionsThe interventions required primary care practices to improve 5 care areas and supported their transformation with substantially enhanced payment, data feedback, and learning support and, for CPC+, added health information technology support.Main measuresHospitalizations (all-cause), ED visits (outpatient and total), and Medicare Part A and B expenditures.Key resultsRelative to comparison practices, beneficiaries in intervention practices experienced slower growth in hospitalizations-3.1% less in year 5 and 3.5% less in year 6 (P < 0.01) and roughly 2% (P < 0.1) slower growth each year in total ED visits during years 3 through 6. Medicare Part A and B expenditures (excluding care management fees) did not change appreciably.ConclusionsThe emergence of favorable effects on hospitalizations in years 5 and 6 suggests primary care transformation takes time to translate into lower hospitalizations. Longer tests of models are needed.

Project description:ImportanceMedicare Part B drug expenditures have increased in recent years. This trend is likely to persist given the increased use and availability of biologics.ObjectivesTo assess the extent to which Medicare Part B spending growth was associated with changes in price vs quantity, and how these trends interacted with entry of new drugs into the marketplace.Design, setting, and participantsThis cross-sectional study quantified the degree of spending concentration and the association between price and use of Part B drugs among fee-for-service Medicare beneficiaries. Data on use and spending for separately payable Part B drugs were included. Source data were aggregated to the drug-year level and reported from 2016 to 2020. Descriptive decomposition and index analyses quantified the relative association of price and use changes separately for existing single-source drugs, existing drugs that faced competition, and new drugs that entered the market. Data analysis was performed from June to December 2022.Main outcomes and measuresPart B drug spending by the fee-for-service Medicare program and beneficiaries, as well as use, defined as dosage units and beneficiaries using the drugs.ResultsThe study included 535 unique Part B drug products. From 2016 to 2020, 15 or fewer products comprised half of all Part B drug expenditures. The set of 7 drugs that comprised the top 25% of spending was very consistent over time, and all were biologics. Part B drug products that cost $1.85 or less per administration accounted for more than half of the doses administered in 2020. Spending on Part B drugs increased by $15 billion from 2016 to 2020. The entry of new, nonbiosimilar drugs during this period accounted for $12 billion of this increased spending (80%), while shifts in use and price increases among existing single-source brand drugs accounted for the remaining increase in spending. Part B spending decreased among the subset of existing drugs facing generic or biosimilar competition. Among single-source drugs on the market in 2016, the index that varied dosage units exceeded the index that varied price in all years, confirming that changes in use were associated more with spending growth for those drugs.Conclusions and relevanceIn this cross-sectional study of Medicare Part B drug expenditures, spending was found to be concentrated among a small number of drugs. The entry of new products was a key factor associated with recent increases in Part B drug spending. These findings suggest that policies targeting top-selling drugs may have greater potential to curb Part B drug spending than those targeting price growth.

Project description:Importance:Despite a growing recognition of the increased mortality risk among sepsis survivors, little is known about the patterns of end-of-life care among this population. Objective:To describe patterns of end-of-life care among a national sample of sepsis survivors and identify factors associated with long-term mortality risk and hospice use. Design, Setting, and Participants:This cohort study assessed sepsis survivors who were Medicare fee-for-service beneficiaries discharged to home health care using national Medicare administrative, claims, and home health assessment data from 2013 to 2014. The initial and final primary analyses were conducted in July 2017 and from July to August 2019, respectively. Exposures:Sepsis hospital discharge and 1 or more home health assessments within 1 week. Main Outcomes and Measures:Outcomes were 1-year mortality among all sepsis survivors and hospitalization in the last 30 days of life, death in an acute care hospital, and hospice use among decedents. Multivariate logistic regression was used to identify factors associated with 1-year mortality and hospice use. Results:Among 87 581 sepsis survivors who were Medicare fee-for-service beneficiaries discharged to home health care, 49 323 (56.3%) were aged 75 years or older, 69 499 (79.4%) were non-Hispanic white, and 48 472 (55.3%) were female. Among the total survivors, 24 423 (27.9%) people died within 1 year of discharge, with a median (interquartile range) survival time of 119 (51-220) days. Among these decedents, 16 684 (68.2%) were hospitalized in the last 30 days of life, 6560 (26.8%) died in an acute care hospital, and 12 573 (51.4%) were enrolled in hospice, with 5729 (45.6%) using hospice for 7 or fewer days. Several factors were associated with 1-year mortality, including a cancer diagnosis (odds ratio [OR], 3.66; 95% CI, 3.50-3.83; P < .001), multiple dependencies of activities of daily living or instrumental activities of daily living (OR, 2.80; 95% CI, 2.57-3.05; P < .001), and an overall poor health status (OR, 2.21; 95% CI, 2.01-2.44; P < .001) documented on home health assessment. Among the decedents, cancer was associated with hospice use (OR, 2.25; 95% CI, 2.11-2.41; P < .001), patients aged 85 years or older (OR, 1.49; 95% CI, 1.37-1.61; P < .001), and living in an assisted living setting (OR, 1.93; 95% CI, 1.69-2.19; P < .001). Conclusions and Relevance:The findings of this study suggest that death within 1 year after sepsis discharge may be common among Medicare beneficiaries discharged to home health care. Although 1 in 2 decedents used hospice, aggressive care near the end of life and late hospice referral were common. Readily identifiable risk factors suggest opportunities to target efforts to improve palliative and end-of-life care among high-risk sepsis survivors.

Project description:The Medicare accountable care organization (ACO) programs rely on delivery system integration and health care provider risk sharing to lower spending while improving quality of care.To compare spending and quality between larger and smaller provider groups and examine how size-related differences vary by 2 factors considered central to ACO performance: group primary care orientation and financial risk sharing by health care providers.Using 2009 Medicare claims and linked American Medical Association Group Practice data, we assigned 4.29 million beneficiaries to health care provider groups based on primary care use. We categorized group size according to eligibility thresholds for the Shared Savings (?5000 assigned beneficiaries) and Pioneer (?15,000) ACO programs and distinguished hospital-based from independent groups. We assessed the primary care orientation of larger groups' specialty mix and used health maintenance organization market penetration and data from the Community Tracking Study to measure the extent of financial risk accepted by different types of provider groups in different areas for managed care patients. We estimated linear regression models comparing spending and quality between larger and smaller health care provider groups, allowing size-related differences to vary by measures of group primary care orientation and risk sharing. Spending and quality measures included total medical spending, spending by type of service, 5 process measures of quality, and 30-day readmissions, all adjusted for sociodemographic and clinical characteristics.Compared with smaller groups, larger hospital-based groups had higher total per-beneficiary spending in 2009 (mean difference, +$849), higher 30-day readmission rates (+1.3 percentage points), and similar performance on 4 of 5 process measures of quality. In contrast, larger independent physician groups performed better than smaller groups on all process measures and exhibited significantly lower per-beneficiary spending in counties where risk sharing by these groups was more common (-$426). Among all groups sufficiently large to participate in ACO programs, a strong primary care orientation was associated with lower spending, fewer readmissions, and better quality of diabetes care.Spending was lower and quality of care better for Medicare beneficiaries served by larger independent physician groups with strong primary care orientations in environments where health care providers accepted greater risk.

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Use of Data-Driven Methods to Predict Long-term Patterns of Health Care Spending for Medicare Patients.

Publications

Use of Data-Driven Methods to Predict Long-term Patterns of Health Care Spending for Medicare Patients.

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