ISPOR Code of Ethics 2017 (4th Edition).

As the leading health economics and outcomes research (HEOR) professional society, ISPOR has a responsibility to establish a uniform, harmonized international code for ethical conduct. ISPOR has updated its 2008 Code of Ethics to reflect the current research environment. This code addresses what is acceptable and unacceptable in research, from inception to the dissemination of its results. There are nine chapters: 1 - Introduction; 2 - Ethical Principles respect, beneficence and justice with reference to a non-exhaustive compilation of international, regional, and country-specific guidelines and standards; 3 - Scope HEOR definitions and how HEOR and the Code relate to other research fields; 4 - Research Design Considerations primary and secondary data related issues, e.g., participant recruitment, population and research setting, sample size/site selection, incentive/honorarium, administration databases, registration of retrospective observational studies and modeling studies; 5 - Data Considerations privacy and data protection, combining, verification and transparency of research data, scientific misconduct, etc.; 6 - Sponsorship and Relationships with Others (roles of researchers, sponsors, key opinion leaders and advisory board members, research participants and institutional review boards (IRBs) / independent ethics committees (IECs) approval and responsibilities); 7 - Patient Centricity and Patient Engagement new addition, with explanation and guidance; 8 - Publication and Dissemination; and 9 - Conclusion and Limitations.

Geographic variation in cesarean delivery in the United States by payer.

BACKGROUND: The rate of cesarean delivery in the United States is variable across geographic areas. The aims of this study are two-fold: (1) to determine whether the geographic variation in cesarean delivery rate is consistent for private insurance and Medicaid (2) to identify the patient, population, and market factors associated with cesarean rate and determine if these factors vary by payer. METHODS: We used the Healthcare Cost and Utilization Project (HCUP) State Inpatient Databases (SID) to measure the cesarean rate at the Core-Based Statistical Area (CBSA) level. We linked the hospitalization data to data from other national sources to measure population and market characteristics. We calculated unadjusted and risk-adjusted CBSA cesarean rates by payer. For the second aim, we estimated a hierarchical logistical model with the hospitalization as the unit of analysis to determine the factors associated with cesarean delivery. RESULTS: The average CBSA cesarean rate for women with private insurance was higher (18.9 percent) than for women with Medicaid (16.4 percent). The factors predicting cesarean rate were largely consistent across payers, with the following exceptions: women under age 18 had a greater likelihood of cesarean section if they had Medicaid but had a greater likelihood of vaginal birth if they had private insurance; Asian and Native American women with private insurance had a greater likelihood of cesarean section but Asian and Native American women with Medicaid had a greater likelihood of vaginal birth. The percent African American in the population predicted increased cesarean rates for private insurance only; the number of acute care beds per capita predicted increased cesarean rate for women with Medicaid but not women with private insurance. Further we found the number of obstetricians/gynecologists per capita predicted increased cesarean rate for women with private insurance only, and the number of midwives per capita predicted increased vaginal birth rate for women with private insurance only. CONCLUSIONS: Factors associated with geographic variation in cesarean delivery, a frequent and high-resource inpatient procedure, vary somewhat by payer. Using this information to identify areas for intervention is key to improving quality of care and reducing healthcare costs.

Association between the unemployment rate and inpatient cost per discharge by payer in the United States, 2005-2010.

BACKGROUND: Several reports have linked the 2007-2009 Great Recession in the United States with a slowdown in health care spending and decreased utilization. However, little is known regarding how the recent economic downturn affected hospital costs per inpatient stay for different segments of the population. The purpose of this study was to examine the association between changes in the unemployment rate and inpatient cost per discharge for Medicare and commercial discharges. METHODS: We used retrospective data at the Core Based Statistical Area (CBSA)-level from 46 states that contributed to the Healthcare Cost and Utilization Project State Inpatient Databases from 2005 to 2010. Unemployment data was derived from the American Community Survey. An instrumental variable two-stage least squares approach with fixed- or random-effects was used to examine the association between unemployment rate and inpatient cost per discharge by payer because of potential endogeneity. RESULTS: The marginal effect of unemployment was associated with an increase in inpatient cost per discharge for both payers. A one percentage point increase in the unemployment rate was associated with a $37 increase for commercial discharges and a $49 increase for Medicare discharges. CONCLUSIONS: We find evidence that the inpatient cost per discharge is countercyclical across different segments of the population. The underlying mechanisms by which unemployment affects hospital resource use however, might differ between payer groups.

The impact of methodological approach on cost findings in comparison of epoetin alfa with darbepoetin alfa.

BACKGROUND: Two erythropoiesis-stimulating agents (ESAs), epoetin alfa and darbepoetin alfa, are approved for the treatment of chemotherapy-induced anemia in patients with cancer. Randomized controlled trials indicate that the drugs are similarly efficacious, but that the duration of clinical benefit (DCB) ranges from 2 to 7 days for epoetin alfa and from 7 to 21 days for darbepoetin alfa, depending on dose. Given equivalent efficacy, payers are increasingly interested in understanding the cost differences for these 2 drugs. OBJECTIVE: To examine the impact of different methodological approaches on the cost comparison between epoetin alfa and darbepoetin alfa users, with cancer from a payer perspective. METHODS: Episodes of care (episode) were constructed for cancer patients treated with ESAs, using MarketScan claims data. Episodes started with the first ESA claim and ended on the last ESA claim or the claim before a 42-day or longer gap in ESA therapy. Each episode was augmented with an estimated DCB based on the last dose in the episode. Cost was reimbursed amount observed in the claims database. Adjusted weekly cost was estimated using generalized linear models to control for difference in clinical and demographic differences across epoetin alfa and darbepoetin alfa episodes. RESULTS: Episodes were created in 324 darbepoetin alfa and 342 epoetin alfa users. Darbepoetin alfa users tended to be younger, had more comorbidities, and had advanced cancer (all p < 0.001). After accounting for DCB, the average weekly cost of darbepoetin alfa was significantly lower than that of epoetin alfa ($619 vs $940; p < 0.001). After multivariate adjustment, darbepoetin alfa had lower costs than epoetin alfa in the base case and all alternative approaches. CONCLUSIONS: To reduce the risk of potential bias, DCB and different patient characteristics should be taken into account when using retrospective claims data to conduct cost comparisons between agents that have significant differences in dosing schedule.

A four-system comparison of patients with chronic illness: the Military Health System, Veterans Health Administration, Medicaid, and commercial plans.

We compared chronic care utilization in four major health systems in the U.S.: the military health system (TRICARE), the Department of Veterans Affairs (VA), Medicaid, and employer-sponsored commercial plans. Prevalence rates and key performance indicators were constructed from administrative data in federal fiscal year 2003 for eight chronic conditions: hypertension, major depression, diabetes, tobacco dependence, ischemic heart disease, severe mental illness, persistent asthma, and stroke. Continuously enrolled beneficiaries under 65 years old were studied: TRICARE (N = 2,963,987), VA (N = 2,114,739), Medicaid enrollees in five states (N = 5,554,974), and commercial insurance (N = 5,212,833). Condition-specific adjusted prevalence rates and measures were compared using the standardized rate ratio. For the majority of the conditions, the estimated prevalence rates were highest in the VA and Medicaid populations. Prevalence rates were generally lower in TRICARE and commercial plans. Medicaid beneficiaries had the highest hospitalization rates in four of the six conditions where hospitalization rates were measured. These results provide empirical evidence of differences in chronically ill patient populations in several of the major U.S. health insurance systems.

Impact of Health System Affiliation on Hospital Resource Use Intensity and Quality of Care.

OBJECTIVE: To assess the impact of hospital affiliation, centralization, and managed care plan ownership on inpatient cost and quality. DATA SOURCES: Inpatient discharges from 3,957 community hospitals in 44 states and American Hospital Association Annual Survey data from 2010 to 2012. STUDY DESIGN: We conducted a retrospective longitudinal regression analysis using hierarchical modeling of discharges clustered within hospitals. DATA COLLECTION: Detailed discharge data including costs, length of stay, and patient characteristics from the Healthcare Cost and Utilization Project State Inpatient Databases were merged with hospital survey data from the American Hospital Association. PRINCIPAL FINDINGS: Hospitals affiliated with health systems had a higher cost per discharge and better quality of care compared with independent hospitals. Centralized systems in particular had the highest cost per discharge and longest stays. Independent hospitals with managed care plans had a higher cost per discharge and better quality of care compared with other independent hospitals. CONCLUSIONS: Increasing prevalence of health systems and hospital managed care ownership may lead to higher quality but are unlikely to reduce hospital discharge costs. Encouraging participation in innovative payment and delivery reform models, such as accountable care organizations, may be more powerful options.

Multiple chronic conditions: prevalence, health consequences, and implications for quality, care management, and costs.

Persons with multiple chronic conditions are a large and growing segment of the US population. However, little is known about how chronic conditions cluster, and the ramifications of having specific combinations of chronic conditions. Clinical guidelines and disease management programs focus on single conditions, and clinical research often excludes persons with multiple chronic conditions. Understanding how conditions in combination impact the burden of disease and the costs and quality of care received is critical to improving care for the 1 in 5 Americans with multiple chronic conditions. This Medline review of publications examining somatic chronic conditions co-occurring with 1 or more additional specific chronic illness between January 2000 and March 2007 summarizes the state of our understanding of the prevalence and health challenges of multiple chronic conditions and the implications for quality, care management, and costs.

Mortality rate in veterans with multiple chronic conditions.

BACKGROUND: Among patients with multiple chronic conditions, there is increasing appreciation of the complex interrelatedness of diseases. Previous studies have focused on the prevalence and economic burden associated with multiple chronic conditions, much less is known about the mortality rate associated with specific combinations of multiple diseases. OBJECTIVE: Measure the mortality rate in combinations of 11 chronic conditions. DESIGN: Cohort study of veteran health care users. PARTICIPANTS: Veterans between 55 and 64 years that used Veterans Health Administration health care services between October 1999 and September 2000. MEASUREMENTS: Patients were identified as having one or more of the following: COPD, diabetes, hypertension, rheumatoid arthritis, osteoarthritis, asthma, depression, ischemic heart disease, dementia, stroke, and cancer. Mutually exclusive combinations of disease based on these conditions were created, and 5-year mortality rates were determined. RESULTS: There were 741,847 persons included. The number in each group by a count of conditions was: none = 217,944 (29.34%); 1 = 221,111 (29.8%); 2 = 175,228 (23.6%); 3 = 86,447 (11.7%); and 4+ = 41,117 (5.5%). The 5-year mortality rate by the number of conditions was: none = 4.1%; 1 = 6.0%; 2 = 7.8%; 3 = 11.2%; 4+ = 16.7%. Among combinations with the same number of conditions, there was significant variability in mortality rates. CONCLUSIONS: Patients with multiple chronic conditions have higher mortality rates. Because there was significant variation in mortality across clusters with the same number of conditions, when studying patients with multiple coexisting illnesses, it is important to understand not only that several conditions may be present but that specific conditions can differentially impact the risk of mortality.

Discharge Planning and Hospital Readmissions.

This study examines the association between the quality of hospital discharge planning and all-cause 30-day readmissions and same-hospital readmissions. The sample included adults aged 18 years and older hospitalized in 16 states in 2010 or 2011 for acute myocardial infarction, heart failure, pneumonia, or total hip or joint arthroplasty. Data from the Hospital Consumer Assessment of Healthcare Providers and Systems measured discharge-planning quality at the hospital level. A generalized linear mixed model was used to estimate the contribution of patient and hospital characteristics to 30-day all-cause and same-hospital readmissions. Discharge-planning quality was associated with (a) lower rates of 30-day hospital readmissions and (b) higher rates of same-hospital readmissions for heart failure, pneumonia, and total hip or joint replacement. These results suggest that by improving inpatient discharge planning, hospitals may be able to influence their 30-day readmissions and increase the likelihood that readmissions will be to the same hospital.

The Relationship between Local Economic Conditions and Acute Myocardial Infarction Hospital Utilization by Adults and Seniors in the United States, 1995-2011.

OBJECTIVE: To assess the association between aggregate unemployment and hospital discharges for acute myocardial infarction (AMI) among adults and seniors, 1995-2011. DATA SOURCES/STUDY SETTING: Community hospital discharge data from states collected for the Healthcare Cost and Utilization Project (HCUP) State Inpatient Databases (SID) and economic data from the Bureau of Labor Statistics, 1995-2011. STUDY DESIGN: Quarterly time series study of unemployment and aggregate hospital discharges in local areas using fixed effects to control for differences between local areas. DATA COLLECTION/EXTRACTION METHODS: Secondary data on inpatient stays and unemployment rates aggregated to micropolitan and metropolitan areas. PRINCIPAL FINDINGS: For both adults and seniors, a 1 percentage point increase in the contemporaneous unemployment rate was associated with a statistically significant 0.80 percent (adults) to 0.96 percent (seniors) decline in AMI hospitalization during the first half of the study but was unrelated to the economic cycle in the second half of the study period. CONCLUSIONS: The study found evidence that the aggregate relationship between health and the economy may be shifting for cardiovascular events, paralleling recent research that has shown a similar shift for some types of mortality (Ruhm 2013), self-reported health, and inpatient use among seniors (McInerney and Mellor 2012).

The use of disease-modifying new drugs for multiple sclerosis treatment in private-sector health plans.

OBJECTIVES: The aims of this study were to estimate the effects of demographics, location, severity of multiple sclerosis (MS), comorbidities, plan type, coinsurance levels, and time of entry into the sample on the use of disease-modifying agents. METHODS: A retrospective analysis of medical claims data from 1996 through 2000 was conducted with a sample of MS patients covered by self-insured, employer-sponsored health plans. Proportional hazard analysis with the SAS procedure for proportional hazards regression was used to estimate the impact of the factors of interest on the use of disease-modifying agents. A simulation was conducted to assess the impact of changing drug copayments on the use of disease-modifying agents for MS. RESULTS: The sample included 1807 patients. Patients were followed for as long as possible, but most were observed for <3 years; the mean (SD) follow-up time was 972.88 (440.59) days. Most factors associated with the use of disease-modifying agents were immutable. They included the following: high severity of illness (only marginally related; P = NS); history of seizures (P = 0.03), depression (P < 0.01), or heart disease (P = 0.01); census region of location (P < 0.01); union membership or association with a union member (P < 0.01); drug copayment requirements (P < 0.05); and year of entry into the sample (P < 0.01). In the simulation, a 50% reduction in drug copayments was associated with an increase of the proportion of patients treated with disease-modifying drugs from 41.2% to 54.7%. Patients' and physicians' preferences for treatment could not be measured directly. The true onset of MS may be unknown for many patients, but this would be the case even if medical records or other data were used for this study. CONCLUSIONS: Our analyses showed an association between copayments and the use of disease-modifying drugs for MS. Insurance policies can be tailored to influence the use of disease-modifying drugs, enhancing the quality of care for MS patients and reducing price-related barriers to beneficial treatment. Future research should test whether reducing copayments for MS treatment would reduce the use of other health care services (via better MS treatment that modifies the course of illness), or whether the use of disease-modifying drugs would increase total costs to the plan, resulting in slightly higher premiums.

Variation in hospital inpatient prices across small geographic areas.

OBJECTIVES: To examine whether market competition may influence the difference in the inpatient price per discharge between public (Medicare) and private payers across small geographic areas. STUDY DESIGN: Retrospective multivariate analysis. METHODS: Data came from the 2006 Healthcare Cost and Utilization Project (HCUP) State Inpatient Databases (SIDs) in 162 counties from 6 states where an HCUP price-to-charge ratio (PCR) was available. The SIDs were linked with the Area Resource File, American Hospital Association Annual Survey Database, and US Census Bureau data files. Hospital inpatient prices were estimated by applying the HCUP PCR to total hospital charges. Payer-specific price comparisons were made for all discharges, an acute condition (acute myocardial infarction), and an elective condition (knee arthroplasty). Ordinary least squares models were used to examine the effect of market competition on the inpatient price per discharge by payer. RESULTS: Greater geographic variation was found in the inpatient price per discharge among private than public payers for most hospital services. Hospitals in more concentrated markets were associated with a higher price per discharge among knee arthroplasty discharges for both payers. CONCLUSIONS: Hospitals charged significantly higher prices to private than public payers. Because the payment policies from Medicare ultimately affect private payers, public policy efforts that take into consideration market-based approaches or payment reform may help to reduce price variations.

Medicare and commercial inpatient resource use: impact of hospital competition.

OBJECTIVES: To examine the influence of hospital competition on small-area inpatient resource use by payer. METHODS: We measured hospital competition and inpatient resource use using data from the 2008 Healthcare Cost and Utilization Project State Inpatient Databases. Generalized linear models adjusted for patient, population, and market characteristics were used to assess the relationship between inpatient resource use and hospital competition. RESULTS: Hospital competition had a similar influence on inpatient resource intensity for Medicare and privately insured patients. Hospitals in more competitive markets had significantly lower costs per discharge for both Medicare and privately insured patients. Hospital competition was not significantly associated with length of stay per discharge for either payer. CONCLUSION: Findings suggest that policies or incentives that promote or encourage competition in less competitive markets may reduce variation in resource use for both Medicare and private payers.

Geographic variation: a view from the hospital sector.

Efforts to characterize geographic variation in health care utilization and spending have focused on patterns observed with Medicare data. The authors analyzed the Healthcare Cost and Utilization Project national all-payer data for inpatient stays to assess variation in hospitalizations by age groups and, consequently, to understand how utilization of the Medicare population may differ from the population of other payers. The authors found that the correlation between inpatient discharges and costs per capita for the Medicare-eligible population over 65 and younger age groups increased from moderate to strong with age. These findings suggest examining Medicare inpatient data alone may provide a useful but not comprehensive understanding how hospital utilization and costs vary for the total population.

Transforming mental health and substance abuse data systems in the United States.

State efforts to improve mental health and substance abuse service systems cannot overlook the fragmented data systems that reinforce the historical separateness of systems of care. These separate systems have discrete approaches to treatment, and there are distinct funding streams for state mental health, substance abuse, and Medicaid agencies. Transforming mental health and substance abuse services in the United States depends on resolving issues that underlie separate treatment systems--access barriers, uneven quality, disjointed coordination, and information silos across agencies and providers. This article discusses one aspect of transformation--the need for interoperable information systems. It describes current federal and state initiatives for improving data interoperability and the special issue of confidentiality associated with mental health and substance abuse treatment data. Some achievable steps for states to consider in reforming their behavioral health data systems are outlined. The steps include collecting encounter-level data; using coding that is compliant with the Health Insurance Portability and Accountability Act, including national provider identifiers; forging linkages with other state data systems and developing unique client identifiers among systems; investing in flexible and adaptable data systems and business processes; and finding innovative solutions to the difficult confidentiality restrictions on use of behavioral health data. Changing data systems will not in itself transform the delivery of care; however, it will enable agencies to exchange information about shared clients, to understand coordination problems better, and to track successes and failures of policy decisions.