John Billings

Importance  Given higher reimbursement rates, hospitals primarily serving privately insured patients may invest more in intensive coding than hospitals serving publicly insured patients. This may lead these hospitals to code more diagnoses for all patients.

Objective  To estimate whether, for the same Medicaid enrollee with multiple hospitalizations, a hospital’s share of privately insured patients is associated with the number of diagnoses on claims.

Design, Setting, and Participants  This cross-sectional study used patient-level fixed effects regression models on inpatient Medicaid claims from Medicaid enrollees with at least 2 admissions in at least 2 different hospitals in New York State between 2010 and 2017. Analyses were conducted from 2019 to 2021.

Exposures  The annual share of privately insured patients at the admitting hospital.

Main Outcomes and Measures  Number of diagnostic codes per admission. Probability of diagnoses being from a list of conditions shown to be intensely coded in response to payment incentives.

Results  This analysis included 1 614 630 hospitalizations for Medicaid-insured patients (mean [SD] age, 48.2 [20.1] years; 829 684 [51.4%] women and 784 946 [48.6%] men). Overall, 74 998 were Asian (4.6%), 462 259 Black (28.6%), 375 591 Hispanic (23.3%), 486 313 White (30.1%), 128 896 unknown (8.0%), and 86 573 other (5.4%). When the same patient was seen in a hospital with a higher share of privately insured patients, more diagnoses were recorded (0.03 diagnoses per percentage point [pp] increase in share of privately insured; 95% CI, 0.02-0.05; P < .001). Patients discharged from hospitals in the bottom quartile of privately insured patient share received 1.37 more diagnoses when they were subsequently discharged from hospitals in the top quartile, relative to patients whose admissions were both in the bottom quartile (95% CI, 1.21-1.53; P < .001). Those going from hospitals in the top quartile to the bottom had 1.67 fewer diagnoses (95% CI, −1.84 to −1.50; P < .001). Diagnoses in hospitals with a higher private payer share were more likely to be for conditions sensitive to payment incentives (0.08 pp increase for each pp increase in private share; 95% CI, 0.06-0.10; P < .001). These findings were replicated in 2016 to 2017 data.

Conclusions and Relevance  In this cross-sectional study of Medicaid enrollees, admission to a hospital with a higher private payer share was associated with more diagnoses on Medicaid claims. This suggests payment policy may drive differential investments in infrastructure to document diagnoses. This may create a feedback loop that exacerbates resource inequity.

Background: Longitudinal follow-up, resource utilization, and health disparities are top congenital heart research and care priorities. Medicaid claims include longitudinal data on inpatient, outpatient, emergency, pharmacy, rehabilitation, home health utilization, and social determinants of health-including mother-infant pairs.

Objectives: The New York Congenital Heart Surgeons Collaborative for Longitudinal Outcomes and Utilization of Resources linked robust clinical details from locally held state and national registries from 10 of 11 New York congenital heart centers to Medicaid claims, building a novel, statewide mechanism for longitudinal assessment of outcomes, expenditures, and health inequities.

Methods: The authors included all children <18 years of age undergoing cardiac surgery in The Society of Thoracic Surgeons Congenital Heart Surgery Database or the New York State Pediatric Congenital Cardiac Surgery Registry from 10 of 11 New York centers, 2006 to 2019. Data were linked via iterative, ranked deterministic matching on direct identifiers. Match rates were calculated and compared. Proportions of the linked cohort trackable over 3, 5, and 10 years were described.

Results: Of 14,097 registry cases, 59% (n = 8,322) reported Medicaid use. Of these, 7,414 were linked to New York claims, at an 89% match rate. Of matched cases, the authors tracked 79%, 74%, and 65% of children over 3, 5, and 10 years when requiring near-continuous Medicaid enrollment. Allowing more lenient enrollment criteria, the authors tracked 86%, 82%, and 76%, respectively. Mortality over this time was 7.7%, 8.4%, and 10.0%, respectively. Manual validation revealed ∼100% true matches.

Conclusions: This establishes a novel statewide data resource for assessment of longitudinal outcome, health expenditure, and disparities for children with congenital heart disease.

Keywords: Medicaid; congenital heart surgery; disparities; outcomes; registry.

Research Objective

People with a history of incarceration have high rates of physical and behavioral health conditions as well as increased hospitalizations and emergency department visits. This research extends the existing literature about the health profile of individuals with a history of justice involvement by examining patterns of Medicaid utilization and costs.

Study Design

We linked New York State Medicaid and New York City Department of Correction Data from 2012–2016 and examined patterns of jail utilization, health care utilization (including inpatient, emergency department, and outpatient use) and health care cost by categories of service, as well as the prevalence of chronic physical and mental health disorders. We selected two sets of comparisons, any jail contact vs. no jail contact and high jail contact vs. low jail contact.

Population Studied

Individuals with at least one jail admission in 2012 were defined as having any jail contact. Individuals with only one jail admission between 2012–2016 are defined as having low jail contact. Those who were in the top 10 percentile of number of jail admissions are defined as having high jail contact. The no jail contact group is defined as Medicaid recipients matched with individuals with any jail contact on age, sex, race/ethnicity, Medicare status and number of Medicaid enrollment months.

Principal Findings

Comparing to individuals with no jail contact, any jail contact was associated with a higher prevalence of both chronic physical and mental health conditions; those with any jail contact had a doubling in the risks of mortality and of health care resource use; the average number of hospitalizations was 4 times higher among people with any jail contact; people with jail contact had Medicaid costs that were 3 to 7 times greater, with inpatient costs largely driving these differences for people with the most frequent jail contact. Compared to individuals with low jail contact, individuals with high jail contact had drastically higher prevalence of both chronic physical and mental health conditions, triple the number of hospitalizations, and quadruple the number of emergency department visits. The annual inpatient expenditure of an individual with high jail contact is $12 k higher than that of an individual with low jail contact; total Medicaid expenditures of high contact individuals averages over $33 k per year and are twice as high as those of low contact individuals.

Conclusions

The prevalence of physical and mental health conditions was very high among individuals with high jail contact, as were their health care costs. Only a small fraction of costs for this group were for outpatient primary care, behavioral health treatment, and case management that could help to address these needs and prevent hospitalization.

Implications for Policy or Practice

These findings highlight the need for more effective health care engagement strategies for people with a history of incarceration. Specifically, preventative, primary care and behavioral health care services — particularly outpatient substance use services — that are tailored to the needs of this population could lead to more effective health care engagement, reduced health care costs, and improved health and well-being for individuals who have had some contact with NYC jails.

Primary Funding Source

The Robert Wood Johnson Foundation.

Urban legend has often characterized frequent emergency department (ED) patients as mentally ill substance users who are a costly drain on the health care system and who contribute to ED overcrowding because of unnecessary visits for conditions that could be treated more efficiently elsewhere. This study of Medicaid ED users in New York City shows that behavioral health conditions are responsible for a small share of ED visits by frequent users, and that ED use accounts for a small portion of these patients’ total Medicaid costs. Frequent ED users have a substantial burden of disease, and they have high rates of primary and specialty care use. They also have linkages to outpatient care that are comparable to those of other ED patients. It is possible to use predictive modeling to identify who will become a repeat ED user and thus to help target interventions. However, policy makers should view reducing frequent ED use as only one element of more-comprehensive intervention strategies for frequent health system users.

Objectives To develop an algorithm for identifying inpatients at high risk of re-admission to a National Health Service (NHS) hospital in England within 30 days of discharge using information that can either be obtained from hospital information systems or from the patient and their notes.

Design Multivariate statistical analysis of routinely collected hospital episode statistics (HES) data using logistic regression to build the predictive model. The model's performance was calculated using bootstrapping.

Setting HES data covering all NHS hospital admissions in England.

Participants The NHS patients were admitted to hospital between April 2008 and March 2009 (10% sample of all admissions, n=576 868).

Main outcome measures Area under the receiver operating characteristic curve for the algorithm, together with its positive predictive value and sensitivity for a range of risk score thresholds.

Results The algorithm produces a ‘risk score’ ranging (0–1) for each admitted patient, and the percentage of patients with a re-admission within 30 days and the mean re-admission costs of all patients are provided for 20 risk bands. At a risk score threshold of 0.5, the positive predictive value (ie, percentage of inpatients identified as high risk who were subsequently re-admitted within 30 days) was 59.2% (95% CI 58.0% to 60.5%); representing 5.4% (95% CI 5.2% to 5.6%) of all inpatients who would be re-admitted within 30 days (sensitivity). The area under the receiver operating characteristic curve was 0.70 (95% CI 0.69 to 0.70).

Conclusions We have developed a method of identifying inpatients at high risk of unplanned re-admission to NHS hospitals within 30 days of discharge. Though the models had a low sensitivity, we show how to identify subgroups of patients that contain a high proportion of patients who will be re-admitted within 30 days. Additional work is necessary to validate the model in practice.

Objective: To assess the effect of home based telehealth interventions on the use of secondary healthcare and mortality.

Design: Pragmatic, multisite, cluster randomised trial comparing telehealth with usual care, using data from routine administrative datasets. General practice was the unit of randomisation. We allocated practices using a minimisation algorithm, and did analyses by intention to treat.

Setting: 179 general practices in three areas in England.

Participants: 3230 people with diabetes, chronic obstructive pulmonary disease, or heart failure recruited from practices between May 2008 and November 2009.

Interventions: Telehealth involved remote exchange of data between patients and healthcare professionals as part of patients’ diagnosis and management. Usual care reflected the range of services available in the trial sites, excluding telehealth.

Main outcome measure: Proportion of patients admitted to hospital during 12 month trial period.

Results: Patient characteristics were similar at baseline. Compared with controls, the intervention group had a lower admission proportion within 12 month follow-up (odds ratio 0.82, 95% confidence interval 0.70 to 0.97, P=0.017). Mortality at 12 months was also lower for intervention patients than for controls (4.6% v 8.3%; odds ratio 0.54, 0.39 to 0.75, P<0.001). These differences in admissions and mortality remained significant after adjustment. The mean number of emergency admissions per head also differed between groups (crude rates, intervention 0.54 v control 0.68); these changes were significant in unadjusted comparisons (incidence rate ratio 0.81, 0.65 to 1.00, P=0.046) and after adjusting for a predictive risk score, but not after adjusting for baseline characteristics. Length of hospital stay was shorter for intervention patients than for controls (mean bed days per head 4.87 v 5.68; geometric mean difference −0.64 days, −1.14 to −0.10, P=0.023, which remained significant after adjustment). Observed differences in other forms of hospital use, including notional costs, were not significant in general. Differences in emergency admissions were greatest at the beginning of the trial, during which we observed a particularly large increase for the control group.

Conclusions: Telehealth is associated with lower mortality and emergency admission rates. The reasons for the short term increases in admissions for the control group are not clear, but the trial recruitment processes could have had an effect.

Objective
To test whether two hospital-avoidance interventions altered rates of hospital use: “intermediate care” and “integrated care teams.”

Data Sources/Study Setting
Linked administrative data for England covering the period 2004 to 2009.

Study Design
This study was commissioned after the interventions had been in place for several years. We developed a method based on retrospective analysis of person-level data comparing health care use of participants with that of prognostically matched controls.

Data Collection/Extraction Methods
Individuals were linked to administrative datasets through a trusted intermediary and a unique patient identifier.

Principal Findings
Participants who received the intermediate care intervention showed higher rates of unscheduled hospital admission than matched controls, whereas recipients of the integrated care team intervention showed no difference. Both intervention groups showed higher rates of mortality than did their matched controls.

Conclusions
These are potentially powerful techniques for assessing impacts on hospital activity. Neither intervention reduced admission rates. Although our analysis of hospital utilization controlled for a wide range of observable characteristics, the difference in mortality rates suggests that some residual confounding is likely. Evaluation is constrained when performed retrospectively, and careful interpretation is needed.

Substance use (SU) disorders adversely impact health status and contribute to inappropriate health services use. This qualitative study sought to determine SU-related factors contributing to repeated hospitalizations and to identify opportunities for preventive interventions. Fifty Medicaid-insured inpatients identified by a validated statistical algorithm as being at high-risk for frequent hospitalizations were interviewed at an urban public hospital. Patient drug/alcohol history, experiences with medical, psychiatric and addiction treatment, and social factors contributing to readmission were evaluated. Three themes related to SU and frequent hospitalizations emerged: (a) barriers during hospitalization to planning long-term treatment and follow-up, (b) use of the hospital as a temporary solution to housing/family problems, and (c) unsuccessful SU aftercare following discharge. These data indicate that homelessness, brief lengths of stay complicating discharge planning, patient ambivalence regarding long-term treatment, and inadequate detox-to-rehab transfer resources compromise substance-using patients' likelihood of avoiding repeat hospitalization. Intervention targets included supportive housing, detox-to-rehab transportation, and postdischarge patient support.

Patients with frequent hospitalizations generate a disproportionate share of hospital visits and costs. Accurate determination of patients who might benefit from interventions is challenging: most patients with frequent admissions in 1 year would not continue to have them in the next. Our objective was to employ a validated regression algorithm to case-find Medicaid patients at high-risk for hospitalization in the next 12 months and identify intervention-amenable characteristics to reduce hospitalization risk. We obtained encounter data for 36,457 Medicaid patients with any visit to an urban public hospital from 2001 to 2006 and generated an algorithm-based score for hospitalization risk in the subsequent 12 months for each patient (0 = lowest, 100 = highest). To determine medical and social contributors to the current admission, we conducted in-depth interviews with high-risk hospitalized patients (scores >50) and analyzed associated Medicaid claims data. An algorithm-based risk score >50 was attained in 2,618 (7.2%) patients. The algorithm’s positive predictive value was equal to 0.67. During the study period, 139 high-risk patients were admitted: 60 met inclusion criteria and 50 were interviewed. Fifty-six percent cited the Emergency Department as their usual source of care or had none. Sixty-eight percent had >1 chronic medical conditions, and 42% were admitted for conditions related to substance use. Sixty percent were homeless or precariously housed. Mean Medicaid expenditures for the interviewed patients were $39,188 and $84,040 per patient for the years immediately prior to and following study participation, respectively. Findings including high rates of substance use, homelessness, social isolation, and lack of a medical home will inform the design of interventions to improve community-based care and reduce hospitalizations and associated costs.

This paper offers some reflections on the grant-making process from a former foundation executive. Some of the opportunities, challenges, and pitfalls inherent in the foundation world are described, and one approach to grant making, the "call for proposals," is examined as an example of the need for greater attention to and investment in the science of grant making itself, to maximize the potential return from philanthropy.

The article discusses the improvement of care management for high-cost Medicaid patients. It explores on Medicaid budgets which have prompted policymakers to redouble efforts to explore ways of boosting efficiency in care delivery, particularly for people with high-cost and chronic conditions. It also illustrates John Billings and Tod Mijanovich's article which examines the cost-effectiveness of care management for chronic disease patients treated in fee-for-service practice. The authors present an algorithm that identifies patients at high risk of future hospitalizations and offer a business-case analysis about the rate of reduction in future hospitalization and the cost of the intervention.

Although many public health initiatives have been implemented through collaborations with faith-based institutions, little is known about best practices for developing such programs. Using a community-based participatory approach, this case study examines the implementation of an initiative in the Bronx, New York, that is designed to educate community members about health promotion and disease management and to mobilize church members to seek equal access to health care services. The study used qualitative methods, including the collaborative development of a logic model for the initiative, focus groups, interviews, analysis of program reports, and participant observation. The paper examines three key aspects of the initiative’s implementation: (1) the engagement of the church leadership; (2) the use of church structures as venues for education and intervention; and (3) changes in church policies. Key findings include the importance of pre-existing relationships within the community and the prominent agenda-setting role played by key pastors, and the strength of the Coalition’s dual focus on health behaviors and health disparities. Given the churches’ demonstrated ability to pull people together, to motivate and to inspire, there is great potential for faith-based interventions, and models developed through such interventions, to address health disparities.

This study seeks to understand the perspective of Black and Hispanic/Latino residents of the South Bronx, New York, on the causes of persistent racial and ethnic disparities in health outcomes. In particular, it focuses on how people who live in this community perceive and interact with the health care system. Findings from 9 focus groups with 110 participants revealed a deep and pervasive distrust of the health care system and a sense of being disrespected, exacerbated by difficulties that patients experience in communicating with their providers. The paper suggests how health care institutions might respond to these perceptions.

Program funders and managers are increasingly interested in fostering changes in the policies, practices, and procedures of organizations participating in community-based initiatives. But little is know about what factors contribute to the institutionalization of change. In this study, we assess whether the organizational members of the Bronx Health REACH Coalition have begun to change their functioning and role with regard to their clients, their staff, and in the broader community, apart from their implementation of the funded programs for which they are responsible. The study identifies factors that seemed to contribute to or hinder such institutional change, and suggests several strategies for coalitions and funders that are seeking to promote and sustain organizational change.

How do we understand and also assess the health care of America? Where is health care provided? What are the characteristics of those institutions which provide it? Over the short term, how are changes in health care provisions affecting the health of the population, the cost of care, and access to care? Health Care Delivery in the United States, 8 th Edition discusses these and other core issues in the field. Under the editorship of Dr. Kovner and with the addition of Dr. James Knickman, Senior VP of Evaluation, Robert Wood Johnson Foundation, leading thinkers and practitioners in the field examine how medical knowledge creates new healthcare services. Emerging and recurrent issues from wide perspectives of health policy and public health are also discussed. With an easy to understand format and a focus on the major core challenges of the delivery of health care, this is the textbook of choice for course work in health care, the handbook for administrators and policy makers, and the standard for in-service training programs.

High cost patients account for a large share of Medicaid costs (20 percent of patients account for 70 to 80 percent of expenditures). This study analyzes expenditures, patterns of utilization, and diagnostic characteristics of the most costly of these patients.

The usefulness of patient decision aids (PtDAs) is well documented, yet they are not in widespread use. Barriers include assuring balance and fairness (auspices matter), the cost of producing and maintaining them, and getting them into the hands of patients at the right time. The Foundation for Informed Medical Decision Making and its for-profit partner, Health Dialog, have developed a creative business model that helps overcome these barriers and has greatly expanded the reach of decision aids.

Although many community-based initiatives employ community residents to undertake door-to-door surveys as a form of community mobilization or for purposes of needs assessment or evaluation, very little has been published on the strengths and weaknesses of this approach. This article discusses our experience in undertaking such a survey in collaboration with a coalition of community-based organizations (CBOs) in the South Bronx, New York. Although resource constraints limited the already-strained capacity of the CBOs to provide supervision, the CBOs and community surveyors helped us gain access to neighborhood buildings and to individuals who might otherwise have been inaccessible. The survey process also contributed to the coalition's community outreach efforts and helped to link the CBO leadership and staff more closely to the coalition and its mission. Many of the surveyors enhanced their knowledge and skills in ways that have since benefited them or the coalition directly. The participating CBOs continue to be deeply engaged in the coalition's work, and many of the surveyors are active as community health advocates and have taken leadership roles within the coalition.

Tools for Monitoring the Health Care Safety Net offers strategies and concrete tools for assessing local health care safety nets. With topics ranging from estimating the size of local uninsured populations to using administrative data to presenting information to policymakers, it can assist state and local health officials, planners, and analysts in assessing the capacity and viability of their existing safety net providers as well as understand the characteristics and health outcomes for the populations served.

One of the challenges in monitoring the Nation's health care safety net is that safety net services are provided in a myriad of different configurations, largely at the local level. Book 1. Data for Metropolitan Areas presents data from 90 metropolitan areas in 30 States and the District of Columbia, including 354 counties and 171 cities. The data describe the health care safety net where 80 percent of Americans with family incomes below the Federal poverty line live.

It is becoming increasingly apparent that over the next several years the majority of Medicaid patients in many states will become enrolled in managed care plans, some voluntarily, but most as the result of mandatory initiatives. An important issue related to this development is the extent to which this movement to managed care is accompanied by serious selection effects, either across the board during the phase in or among individual plans or plan types with full-scale implementation. This paper examines selection effects in New York City between 1993 and 1997 during the voluntary enrollment period prior to implementation of mandatory enrollment pursuant to a Section 1115 waiver. No substantial selection bias was documented between patients entering managed care and those remaining in the fee-for-service system among the largest rate groups, although some selection effect was found among plans and plan types (with investor-owned plans enrolling patients with lower prior utilization and expenses).

Explores the concept of evidence-based management, demonstrates how it can enhance health management practice, and introduces an organizational structure for promoting the evidence-based approach. Challenge of making better-informed strategic decisions; Management research in healthcare; Approaches related to evidence-based management; Evidence-based management decision making; Case vignettes.

In the absence of universal coverage and an effective primary care delivery system for vulnerable populations, hospital emergency departments (EDs) are the ultimate safety net for many patients. This is especially true in New York City, where nearly 75 percent of ED visits in 1998 were for nonemergent care, or for emergent care that could have been treated in a doctor's office.1 Another 7 percent of visits required care in the ED, but were for potentially preventable conditions such as acute flare-ups of asthma or diabetes. New Yorkers who rely on EDs lack continuity in their health care and end up using costlier services. Why do so many patients depend on hospital emergency departments for primary care? Do they seek emergency care immediately, or do they have time and opportunity to obtain care at a doctor's office or neighborhood clinic? Do these patients have a usual source of care other than the ED? Do they have any contact with the health care system prior to their ED visit? Does insurance status, race, ethnicity, national origin, or gender have an influence on ED use?

To answer these questions, the Center for Health and Public Service Research at New York University conducted face-to-face interviews with 669 emergency department patients ages 18 to 55 at four hospitals in the Bronx.

For the uninsured and many low-income people, hospital emergency departments (EDs) are a crucial entryway to the health care system. New York City's uninsured-27 percent of the nonelderly population in 1998, up from 20 percent in 1990-rely heavily on the ED for their medical care. Residents who regularly get their health care at an ED do not have regular doctors or continuity in their care, use costlier services, and often receive treatment that could have been avoided. Low-income New Yorkers may be depending on emergency department care even more as Medicaid enrollment declines and physician reimbursement rates are cut. This Issue Brief describes patterns of ED use throughout
New York City and discusses some of the ways to improve the availability of primary care services and reduce ED dependency.

The inability of the nation's health care delivery system to assure access to basic primary care services for large segments of the population has meant that hospital emergency departments (EDs) are the providers of first and last resort for millions of Americans. Individuals who cannot afford the cost of an office visit, or who are unwilling to wait for care in overcrowded and understaffed community clinics or hospital outpatient departments, rely on EDs for primary care. But reliance on the ED means patients lack continuity in their health care and use costlier services. Moreover, economic constraints cause many of the uninsured to delay seeking treatment until their medical condition has seriously worsened. Had they received treatment earlier in an ambulatory care setting, the trip to the ED might have been avoided.

Thoroughly presents today's health care system, its administration and its dissemination.

This book is a collection of 18 essays by health services researchers that analyze Medicaid managed care, its historical context, its implementation in several states, its applicability to disabled and other special needs populations, and its potential for monitoring quality and provider performance.

Reports on the rates of preventable hospital admissions among low-income populations in the United States even with the efforts of improving primary health care. Comparison of low-income populations health outcomes between U.S. and Canada; Implications of results for U.S. policy makers.

The objective is to examine whether the higher hospital admission rates for chronic medical conditions such as asthma, hypertension, congestive heart failure, chronic obstructive pulmonary disease, and diabetes in low-income communities resulted from community differences in access to care, prevalence of the diseases, propensity to seek care, or physician admitting style.