Preventive visit among older adults with Medicare's introduction of Annual Wellness Visit: Closing gaps in underutilization.

Preventive visit rates are low among older adults in the United States. We evaluated changes in preventive visit utilization with Medicare's introduction of Annual Wellness Visits (AWVs) in 2011. We further assessed how coverage expansion differentially affected older adults who were previously underutilizing the service. The study included Medicare beneficiaries aged 65 to 85 from a mixed-payer multispecialty outpatient healthcare organization in northern California between 2007 and 2016. Data from the electronic health records were used, and the unit of analysis was patient-year (N = 456,281). Multivariable logistic regression models were used to assess determinants of "any preventive visit" use. Prior to the AWV coverage (2007-2010), Medicare beneficiaries who were older, with serious chronic conditions, and with a fee-for-services (FFS) plan underutilized preventive visits such that odds ratio (OR) for age groups (vs. age 65-69) ranges from 0.826 (age 70-74) to 0.522 (age 80-85); for Charlson comorbidity index (CCI) (vs. 0 CCI) ranges from 0.77 (1 CCI) to 0.65 (≥2 CCI); and for FFS (vs. HMO) is 0.236. With the Medicare coverage (2011-2016), the age-based gap reduced substantially, but the difference persisted, e.g., OR for age 80-85 (vs. 65-69) is 0.628, and FFS (vs. HMO) beneficiaries still have far lower odds of using a preventive visit (OR = 0.278). The gap based on comorbidity was not reduced. Medicare's coverage expansion facilitated the use of preventive visit particularly for older adults with more advanced age or with FFS, thereby reducing disparities in preventive visit use.

Beyond Consent: Building Trusting Relationships With Diverse Populations in Precision Medicine Research.

With the growth of precision medicine research on health data and biospecimens, research institutions will need to build and maintain long-term, trusting relationships with patient-participants. While trust is important for all research relationships, the longitudinal nature of precision medicine research raises particular challenges for facilitating trust when the specifics of future studies are unknown. Based on focus groups with racially and ethnically diverse patients, we describe several factors that influence patient trust and potential institutional approaches to building trustworthiness. Drawing on these findings, we suggest several considerations for research institutions seeking to cultivate long-term, trusting relationships with patients: (1) Address the role of history and experience on trust, (2) engage concerns about potential group harm, (3) address cultural values and communication barriers, and (4) integrate patient values and expectations into oversight and governance structures.

New recommendation and coverage of low-dose computed tomography for lung cancer screening: uptake has increased but is still low.

BACKGROUND: In 2013, the US Preventive Services Task Force (USPSTF) issued recommendations for low-dose computed tomography for lung cancer screening (LDCT-LCS), but there continues to be a dearth of information on the adoption of LDCT-LCS in healthcare systems. Using a multilevel perspective, our study aims to assess referrals for LDCT-LCS and identify facilitators and barriers to adoption following recent policy changes. METHODS: A retrospective analysis of electronic medical record data from patients aged 55-80 years with no history of lung cancer who visited a primary care provider in a large healthcare system in California during 2010-2016 (1,572,538 patient years). Trends in documentation of smoking history, number of eligible patients, and lung cancer screening orders were assessed. Using Hierarchical Generalized Linear Models, we also evaluated provider-level and patient-level factors associated with lung cancer screening orders among 970 primary care providers and 12,801 eligible patients according to USPSTF guidelines between January 1st, 2014 and December 31st, 2016. RESULTS: Documentation of smoking history to determine eligibility (59.2% in 2010 to 77.8% in 2016) and LDCT-LCS orders (0% in 2010 to 7.3% in 2016) have increased since USPSTF guidelines. Patient factors associated with increased likelihood of lung cancer screening orders include: younger patient age (78-80 vs. 55-64 years old: OR, 0.4; 95% CI, 0.3-0.7), Asian race (vs. Non-Hispanic White: OR, 1.6; 95% CI, 1.1-2.4), reported current smoking (vs. former smoker: OR, 1.7; 95% CI, 1.4-2.0), no severe comorbidity (severe vs. no major comorbidity: OR = 0.2, 95% CI = 0.1-0.3; moderate vs. no major comorbidity: OR = 0.5; 95% CI = 0.4-0.7), and making a visit to own primary care provider (vs. other primary care providers: OR, 2.4; 95% CI, 1.7-3.4). Appropriate referral for lung cancer screening varies considerably across primary care providers. Provider factors include being a female physician (vs. male: OR, 1.6; 95% CI, 1.1-2.3) and receiving medical training in the US (foreign vs. US medical school graduates: OR = 0.4, 95% CI = 0.3-0.7). CONCLUSIONS: Future interventions to improve lung cancer screening may be more effective if they focus on accurate documentation of smoking history and target former smokers who do not regularly see their own primary care providers.

Collecting Practice-level Data in a Changing Physician Office-based Ambulatory Care Environment: A Pilot Study Examining the Physician induction interview Component of the National Ambulatory Medical Care Survey.

Objective This report examines ways to improve National Ambulatory Medical Care Survey (NAMCS) data on practice and physician characteristics in multispecialty group practices. Methods From February to April 2013, the National Center for Health Statistics (NCHS) conducted a pilot study to observe the collection of the NAMCS physician interview information component in a large multispecialty group practice. Nine physicians were randomly sampled using standard NAMCS recruitment procedures; eight were eligible and agreed to participate. Using standard protocols, three field representatives conducted NAMCS physician induction interviews (PIIs) while trained ethnographers observed and audio recorded the interviews. Transcripts and field notes were analyzed to identify recurrent issues in the data collection process. Results The majority of the NAMCS items appeared to have been easily answered by the physician respondents. Among the items that appeared to be difficult to answer, three themes emerged: (a) physician respondents demonstrated an inconsistent understanding of "location" in responding to questions; (b) lack of familiarity with administrative matters made certain questions difficult for physicians to answer; and (c) certain primary care­oriented questions were not relevant to specialty care providers. Conclusions Some PII survey questions were challenging for physicians in a multispecialty practice setting. Improving the design and administration of NAMCS data collection is part of NCHS' continuous quality improvement process.

Evaluating the healthiness of chain-restaurant menu items using crowdsourcing: a new method.

OBJECTIVE: To develop a technology-based method for evaluating the nutritional quality of chain-restaurant menus to increase the efficiency and lower the cost of large-scale data analysis of food items. DESIGN: Using a Modified Nutrient Profiling Index (MNPI), we assessed chain-restaurant items from the MenuStat database with a process involving three steps: (i) testing 'extreme' scores; (ii) crowdsourcing to analyse fruit, nut and vegetable (FNV) amounts; and (iii) analysis of the ambiguous items by a registered dietitian. RESULTS: In applying the approach to assess 22 422 foods, only 3566 could not be scored automatically based on MenuStat data and required further evaluation to determine healthiness. Items for which there was low agreement between trusted crowd workers, or where the FNV amount was estimated to be >40 %, were sent to a registered dietitian. Crowdsourcing was able to evaluate 3199, leaving only 367 to be reviewed by the registered dietitian. Overall, 7 % of items were categorized as healthy. The healthiest category was soups (26 % healthy), while desserts were the least healthy (2 % healthy). CONCLUSIONS: An algorithm incorporating crowdsourcing and a dietitian can quickly and efficiently analyse restaurant menus, allowing public health researchers to analyse the healthiness of menu items.

Effect of long-term antibiotic use on weight in adolescents with acne.

OBJECTIVES: Antibiotics increase weight in farm animals and may cause weight gain in humans. We used electronic health records from a large primary care organization to determine the effect of antibiotics on weight and BMI in healthy adolescents with acne. METHODS: We performed a retrospective cohort study of adolescents with acne prescribed ≥4 weeks of oral antibiotics with weight measurements within 18 months pre-antibiotics and 12 months post-antibiotics. We compared within-individual changes in weight-for-age Z-scores (WAZs) and BMI-for-age Z-scores (BMIZs). We used: (i) paired t-tests to analyse changes between the last pre-antibiotics versus the first post-antibiotic measurements; (ii) piecewise-constant-mixed models to capture changes between mean measurements pre- versus post-antibiotics; (iii) piecewise-linear-mixed models to capture changes in trajectory slopes pre- versus post-antibiotics; and (iv) χ(2) tests to compare proportions of adolescents with ≥0.2 Z-scores WAZ or BMIZ increase or decrease. RESULTS: Our cohort included 1012 adolescents with WAZs; 542 also had BMIZs. WAZs decreased post-antibiotics in all analyses [change between last WAZ pre-antibiotics versus first WAZ post-antibiotics = -0.041 Z-scores (P < 0.001); change between mean WAZ pre- versus post-antibiotics = -0.050 Z-scores (P < 0.001); change in WAZ trajectory slopes pre- versus post-antibiotics = -0.025 Z-scores/6 months (P = 0.002)]. More adolescents had a WAZ decrease post-antibiotics ≥0.2 Z-scores than an increase (26% versus 18%; P < 0.001). Trends were similar, though not statistically significant, for BMIZ changes. CONCLUSIONS: Contrary to original expectations, long-term antibiotic use in healthy adolescents with acne was not associated with weight gain. This finding, which was consistent across all analyses, does not support a weight-promoting effect of antibiotics in adolescents.

Breast cancer treatment across health care systems: linking electronic medical records and state registry data to enable outcomes research.

BACKGROUND: Understanding of cancer outcomes is limited by data fragmentation. In the current study, the authors analyzed the information yielded by integrating breast cancer data from 3 sources: electronic medical records (EMRs) from 2 health care systems and the state registry. METHODS: Diagnostic test and treatment data were extracted from the EMRs of all patients with breast cancer treated between 2000 and 2010 in 2 independent California institutions: a community-based practice (Palo Alto Medical Foundation; "Community") and an academic medical center (Stanford University; "University"). The authors incorporated records from the population-based California Cancer Registry and then linked EMR-California Cancer Registry data sets of Community and University patients. RESULTS: The authors initially identified 8210 University patients and 5770 Community patients; linked data sets revealed a 16% patient overlap, yielding 12,109 unique patients. The percentage of all Community patients, but not University patients, treated at both institutions increased with worsening cancer prognostic factors. Before linking the data sets, Community patients appeared to receive less intervention than University patients (mastectomy: 37.6% vs 43.2%; chemotherapy: 35% vs 41.7%; magnetic resonance imaging: 10% vs 29.3%; and genetic testing: 2.5% vs 9.2%). Linked Community and University data sets revealed that patients treated at both institutions received substantially more interventions (mastectomy: 55.8%; chemotherapy: 47.2%; magnetic resonance imaging: 38.9%; and genetic testing: 10.9% [P < .001 for each 3-way institutional comparison]). CONCLUSIONS: Data linkage identified 16% of patients who were treated in 2 health care systems and who, despite comparable prognostic factors, received far more intensive treatment than others. By integrating complementary data from EMRs and population-based registries, a more comprehensive understanding of breast cancer care and factors that drive treatment use was obtained.

Patients' body mass index and blood pressure over time: diagnoses, treatments, and the effects of comorbidities.

BACKGROUND: A national strategic framework to address multiple chronic conditions has called for further research on disease trajectories of patients with comorbidities. METHODS: An observational study using multilevel models to analyze electronic health record data from a multispecialty practice from 2003 to 2010 to examine disease trajectories of patients with at least 2 of 3 common chronic conditions: overweight/obese, hypertension, and depression. Using longitudinal data on up to 110,000 patients, the effects of comorbidities on the probability of having a diagnosis for overweight/obesity or hypertension and on the trajectories of body mass index (BMI) and blood pressure (BP) over time were examined. RESULTS: From 2003 to 2010, the percentage of patients with high BMI receiving an overweight/obesity diagnosis grew from 5.0% to 18.7%, and the percentage of patients with high BP having a hypertension diagnosis rose from 39.9% to 51.7%. The effect of time for patients with high BMI and depression was less than the effect of time for high BMI only patients (P<0.01) in receiving overweight/obesity diagnoses. Co-occurring depression and high BMI was positively associated with BMI trajectory (coefficient=0.06, P<0.01), whereas high BP and high BMI (coefficient=-0.07, P<0.01) or high BP and high BMI and depression (coefficient=-0.05, P<0.01) were negatively associated with BMI trajectories. CONCLUSIONS: Although physicians' recording of diagnoses for patients with high BMI and high BP has improved, significant gaps remain. Some co-occurrence patterns of these 3 conditions not only affected the recognition of overweight/obesity and hypertension over time, but also BMI trajectories over time. Quality improvement efforts should target patients with co-occurring depression and overweight/obesity.

From small area variations to accountable care organizations: how health services research can inform policy.

Much of health services research seeks to inform particular policy choices and is best characterized as policy-driven research. The reverse, research-driven policy, occurs when studies alter how people perceive reality, which eventually leads to new policy. An example of the latter is nearly four decades of work by John Wennberg and colleagues. Observing variations in practice across small geographic areas led to the notion that some care is preference sensitive, whereas other care is supply constrained. For the former, patient, rather than physician, preferences should be honored, after acquiring and effectively communicating the best available information on the benefits and risks of treatment options. Finding that areas with high use of services have no better quality or outcomes than do areas with lower use led to the notion of accountable care organizations (ACOs). Eventually, both patient engagement and ACOs were written into the Affordable Care Act of 2010.

Commentary: Protecting human subjects and their data in multi-site research.

Comparative effectiveness research is sometimes best done using routinely collected data from multiple real world settings. This raises important issues with respect to the authorizations to use the data, dealing with the multiple IRBs that may have oversight authority, and protecting it from breaches. Careful delineation of what is quality improvement vs. research-driven interventions can help with IRB reviews, especially for low-risk projects. It is impossible to totally de-identify data without markedly reducing its value for research, but creative strategies can markedly reduce the risk of advertent disclosures of patient identities.

Incidence of Lung Cancer Among Never-Smoking Asian American, Native Hawaiian, and Pacific Islander Females.

BACKGROUND: Although lung cancer incidence rates according to smoking status, sex, and detailed race/ethnicity have not been available, it is estimated that more than half of Asian American, Native Hawaiian, and Pacific Islander (AANHPI) females with lung cancer have never smoked. METHODS: We calculated age-adjusted incidence rates for lung cancer according to smoking status and detailed race/ethnicity among females, focusing on AANHPI ethnic groups, and assessed relative incidence across racial/ethnic groups. We used a large-scale dataset that integrates data from electronic health records from 2 large health-care systems-Sutter Health in Northern California and Kaiser Permanente Hawai'i-linked to state cancer registries for incident lung cancer diagnoses between 2000 and 2013. The study population included 1 222 694 females (n = 244 147 AANHPI), 3297 of which were diagnosed with lung cancer (n = 535 AANHPI). RESULTS: Incidence of lung cancer among never-smoking AANHPI as an aggregate group was 17.1 per 100 000 (95% confidence interval [CI] = 14.9 to 19.4) but varied widely across ethnic groups. Never-smoking Chinese American females had the highest rate (22.8 per 100 000, 95% CI = 17.3 to 29.1). Except for Japanese American females, incidence among every never-smoking AANHPI female ethnic group was higher than that of never-smoking non-Hispanic White females, from 66% greater among Native Hawaiian females (incidence rate ratio = 1.66, 95% CI = 1.03 to 2.56) to more than 100% greater among Chinese American females (incidence rate ratio = 2.26, 95% CI = 1.67 to 3.02). CONCLUSIONS: Our study revealed high rates of lung cancer among most never-smoking AANHPI female ethnic groups. Our approach illustrates the use of innovative data integration to dispel the myth that AANHPI females are at overall reduced risk of lung cancer and demonstrates the need to disaggregate this highly diverse population.

Integrating Electronic Health Record, Cancer Registry, and Geospatial Data to Study Lung Cancer in Asian American, Native Hawaiian, and Pacific Islander Ethnic Groups.

BACKGROUND: A relatively high proportion of Asian American, Native Hawaiian, and Pacific Islander (AANHPI) females with lung cancer have never smoked. We used an integrative data approach to assemble a large-scale cohort to study lung cancer risk among AANHPIs by smoking status with attention to representation of specific AANHPI ethnic groups. METHODS: We leveraged electronic health records (EHRs) from two healthcare systems-Sutter Health in northern California and Kaiser Permanente Hawai'i-that have high representation of AANHPI populations. We linked EHR data on lung cancer risk factors (i.e., smoking, lung diseases, infections, reproductive factors, and body size) to data on incident lung cancer diagnoses from statewide population-based cancer registries of California and Hawai'i for the period between 2000 and 2013. Geocoded address data were linked to data on neighborhood contextual factors and regional air pollutants. RESULTS: The dataset comprises over 2.2 million adult females and males of any race/ethnicity. Over 250,000 are AANHPI females (19.6% of the female study population). Smoking status is available for over 95% of individuals. The dataset includes 7,274 lung cancer cases, including 613 cases among AANHPI females. Prevalence of never-smoking status varied greatly among AANHPI females with incident lung cancer, from 85.7% among Asian Indian to 14.4% among Native Hawaiian females. CONCLUSION: We have developed a large, multilevel dataset particularly well-suited to conduct prospective studies of lung cancer risk among AANHPI females who never smoked. IMPACT: The integrative data approach is an effective way to conduct cancer research assessing multilevel factors on cancer outcomes among small populations.

Toward a 21st-century health care system: recommendations for health care reform.

The coverage, cost, and quality problems of the U.S. health care system are evident. Sustainable health care reform must go beyond financing expanded access to care to substantially changing the organization and delivery of care. The FRESH-Thinking Project (www.fresh-thinking.org) held a series of workshops during which physicians, health policy experts, health insurance executives, business leaders, hospital administrators, economists, and others who represent diverse perspectives came together. This group agreed that the following 8 recommendations are fundamental to successful reform: 1. Replace the current fee-for-service payment system with a payment system that encourages and rewards innovation in the efficient delivery of quality care. The new payment system should invest in the development of outcome measures to guide payment. 2. Establish a securely funded, independent agency to sponsor and evaluate research on the comparative effectiveness of drugs, devices, and other medical interventions. 3. Simplify and rationalize federal and state laws and regulations to facilitate organizational innovation, support care coordination, and streamline financial and administrative functions. 4. Develop a health information technology infrastructure with national standards of interoperability to promote data exchange. 5. Create a national health database with the participation of all payers, delivery systems, and others who own health care data. Agree on methods to make de-identified information from this database on clinical interventions, patient outcomes, and costs available to researchers. 6. Identify revenue sources, including a cap on the tax exclusion of employer-based health insurance, to subsidize health care coverage with the goal of insuring all Americans. 7. Create state or regional insurance exchanges to pool risk, so that Americans without access to employer-based or other group insurance could obtain a standard benefits package through these exchanges. Employers should also be allowed to participate in these exchanges for their employees' coverage. 8. Create a health coverage board with broad stakeholder representation to determine and periodically update the affordable standard benefit package available through state or regional insurance exchanges.

Smoking-Cessation Interventions After Lung Cancer Screening Guideline Change.

INTRODUCTION: Recent guideline changes for lung cancer screening with low-dose computed tomography recommend smoking-cessation interventions be done in parallel with screening. The purpose of this study is to determine the post-guideline rates of smoking-cessation interventions among patients eligible and ineligible for lung cancer screening. METHODS: Using electronic health records collected from a large ambulatory care system in northern California between 2010 and 2017, authors identified new patients who were current smokers aged 55-80 years visiting a primary care provider, and grouped patients into lung cancer screening-eligible heavy smokers, screening-ineligible moderate smokers, and screening-ineligible light smokers. Screening-eligible smokers versus screening-ineligible smokers were compared in receipt of smoking-cessation interventions before (2010-2013) and after (2014-2017) the guideline change, overall and by intervention type (formal counseling, informal counseling, pharmacotherapy) using hierarchical generalized linear models. Analyses were conducted in 2018-2019. RESULTS: After the guideline change, the likelihood of receiving any smoking-cessation intervention (OR=1.44, 95% CI=1.28, 1.61, p<0.05), informal counseling (OR=1.29, 95% CI=1.15, 1.46, p<0.05), and pharmacotherapy (OR=1.24, 95% CI=1.02, 1.50, p<0.05) during a new patient visit significantly increased, with the increase not varying by level of smoking. For formal counseling, the post-guideline increase was greater for screening-eligible heavy smokers (OR=3.15, 95% CI=1.18, 8.36, p<0.05) and moderate smokers (OR=3.58, 95% CI=1.29, 9.95, p<0.05) relative to light smokers. CONCLUSIONS: Smoking-cessation interventions increased after new lung cancer screening guidelines. Given the sizable adverse impacts of smoking on morbidity and mortality, small increases in the implementation of smoking-cessation interventions could have substantial public health benefits.

Primary care physician practice styles and quality, cost, and productivity.

OBJECTIVES: To assess quality, cost, physician productivity, and patient experience for 2 primary care physician (PCP) practice styles: the focused, who typically address only the patient's acute problem, versus the max-packers, who typically address additional conditions also. STUDY DESIGN: Retrospective observational study using administrative data, electronic health record (EHR) data, and patient surveys. Data represent 285 PCPs (779 PCP-years) in a large, multispecialty group practice during 2011, 2012, and 2013. METHODS: PCPs were ranked each year by their number of additional conditions addressed during acute care visits. The top one-third (max-packers) addressed 25.4% more "other problems" than expected, while focused PCPs (bottom one-third) addressed 20.3% fewer than expected. Outcomes were resource use, clinical quality metrics, patient-reported experience, physician time using the EHR, and physician productivity. All measures were risk-adjusted to account for patient mix. T tests were used to compare measures. RESULTS: Relative to a focused pattern of care, max-packing was associated with 3.4% lower overall resource use, consistently better scores for the available clinical quality metrics, and comparable patient experience (except for worse wait time ratings). Patients of focused PCPs used 7.3% more specialist services, in terms of costs, than patients of max-packers ($1218 vs $1136; P <.001). Max-packers spent 40 minutes more per clinical day using the EHR. PCPs with less appointment availability and who used a mix of appointment slots were more likely to be max-packers. CONCLUSIONS: Max-packing behavior yields desirable outcomes at lower overall cost but involves more conventionally uncompensated PCP time. Alternatives to compensation just for face-to-face visits and using more flexible scheduling may be needed to support max-packing.

Population-Based Registry Linkages to Improve Validity of Electronic Health Record-Based Cancer Research.

BACKGROUND: There is tremendous potential to leverage the value gained from integrating electronic health records (EHR) and population-based cancer registry data for research. Registries provide diagnosis details, tumor characteristics, and treatment summaries, while EHRs contain rich clinical detail. A carefully conducted cancer registry linkage may also be used to improve the internal and external validity of inferences made from EHR-based studies. METHODS: We linked the EHRs of a large, multispecialty, mixed-payer health care system with the statewide cancer registry and assessed the validity of our linked population. For internal validity, we identify patients that might be "missed" in a linkage, threatening the internal validity of an EHR study population. For generalizability, we compared linked cases with all other cancer patients in the 22-county EHR catchment region. RESULTS: From an EHR population of 4.5 million, we identified 306,554 patients with cancer, 26% of the catchment region patients with cancer; 22.7% of linked patients were diagnosed with cancer after they migrated away from our health care system highlighting an advantage of system-wide linkage. We observed demographic differences between EHR patients and non-EHR patients in the surrounding region and demonstrated use of selection probabilities with model-based standardization to improve generalizability. CONCLUSIONS: Our experiences set the foundation to encourage and inform researchers interested in working with EHRs for cancer research as well as provide context for leveraging linkages to assess and improve validity and generalizability. IMPACT: Researchers conducting linkages may benefit from considering one or more of these approaches to establish and evaluate the validity of their EHR-based populations.See all articles in this CEBP Focus section, "Modernizing Population Science."

Translating medical effectiveness research into policy: lessons from the California Health Benefits Review Program.

CONTEXT: Legislatures and executive branch agencies in the United States and other nations are increasingly using reviews of the medical literature to inform health policy decisions. To clarify these efforts to give policymakers evidence of medical effectiveness, this article discusses the California Health Benefits Review Program (CHBRP). This program, based at the University of California, analyzes the medical effectiveness of health insurance benefit mandate bills for the California legislature, as well as their impact on cost and public health. METHODS: This article is based on the authors' experience reviewing benefit mandate bills for CHBRP and findings from evaluations of the program. General observations are illustrated with examples from CHBRP's reports. Information about efforts to incorporate evidence into health policymaking in other states and nations was obtained through a review of published literature. FINDINGS: CHBRP produces reports that California legislators, legislative staff, and other major stakeholders value and use routinely in deliberations about benefit mandate bills. Where available, the program relies on previously published meta-analyses and systematic reviews to streamline the review of the medical literature. Faculty and staff responsible for the medical effectiveness sections of CHBRP's reports have learned four major lessons over the course of the program's six-year history: the need to (1) recognize the limitations of the medical literature, (2) anticipate the need to inform legislators about the complexity of evidence, (3) have realistic expectations regarding the impact of medical effectiveness reviews, and (4) understand the consequences of the reactive nature of mandated benefit reviews. CONCLUSIONS: CHBRP has demonstrated that it is possible to produce useful reviews of the medical literature within the tight time constraints of the legislative process. The program's reports have provided state legislators with independent analyses that allow them to move beyond sifting through conflicting information from proponents and opponents to consider difficult policy choices and their implications.

Economic incentives to promote innovation in healthcare delivery.

Economics influences how medical care is delivered, organized, and progresses. Fee-for-service payment encourages delivery of services. Fee-for-individual-service, however, offers no incentives for clinicians to efficiently organize the care their patients need. Global capitation provides such incentives; it works well in highly integrated practices but not for independent practitioners. The failures of utilization management in the 1990s demonstrated the need for a third alternative to better align incentives, such as bundling payment for an episode of care. Building on Medicare's approach to hospital payment, one can define expanded diagnosis-related groups that include all hospital, physician, and other costs during the stay and appropriate preadmission and postdischarge periods. Physicians and hospitals voluntarily forming a new entity (a care delivery team) would receive such bundled payments along with complete flexibility in allocating the funds. Modifications to gainsharing and antikickback rules, as well as reforms to malpractice liability laws, will facilitate the functioning of the care delivery teams. The implicit financial incentives encourage efficient care for the patient; the episode focus will facilitate measuring patient outcomes. Payment can be based on the resources used by those care delivery teams achieving superior outcomes, thereby fostering innovation improving outcomes and reducing waste.