Estimates Of Health Care Utilization Research Articles

Diarrhea Case Surveillance in the Enterics for Global Health Shigella Surveillance Study: Epidemiologic Methods.

Shigella is a leading cause of acute watery diarrhea, dysentery, and diarrhea-attributed linear growth faltering, a precursor to stunting and lifelong morbidity. Several promising Shigella vaccines are in development and field efficacy trials will require a consortium of potential vaccine trial sites with up-to-date Shigella diarrhea incidence data. The Enterics for Global Health (EFGH) Shigella surveillance study will employ facility-based enrollment of diarrhea cases aged 6-35 months with 3 months of follow-up to establish incidence rates and document clinical, anthropometric, and financial consequences of Shigella diarrhea at 7 country sites (Mali, Kenya, The Gambia, Malawi, Bangladesh, Pakistan, and Peru). Over a 24-month period between 2022 and 2024, the EFGH study aims to enroll 9800 children (1400 per country site) between 6 and 35 months of age who present to local health facilities with diarrhea. Shigella species (spp.) will be identified and serotyped from rectal swabs by conventional microbiologic methods and quantitative polymerase chain reaction. Shigella spp. isolates will undergo serotyping and antimicrobial susceptibility testing. Incorporating population and healthcare utilization estimates from contemporaneous household sampling in the catchment areas of enrollment facilities, we will estimate Shigella diarrhea incidence rates. This multicountry surveillance network will provide key incidence data needed to design Shigella vaccine trials and strengthen readiness for potential trial implementation. Data collected in EFGH will inform policy makers about the relative importance of this vaccine-preventable disease, accelerating the time to vaccine availability and uptake among children in high-burden settings.

Use of Open Claims vs Closed Claims in Health Outcomes Research.

Background: Closed claims are frequently used in outcomes research studies. Lately, the availability of open claims has increased the possibility of obtaining information faster and on a larger scale. However, because of the possibility of missing claims and duplications, these data sets have not been highly utilized in medical research. Objective: To compare frequently used healthcare utilization measures between closed claims and open claims to analyze if the possibility of missing claims in open claims data creates a downward bias in the estimates. Methods: We identified 18 different diseases using 2022 data from 2 closed claims data sets (MarketScan® and PharMetrics® Plus) and 1 open claims database (Kythera). After applying an algorithm that removes possible duplications from open claims data, we compared healthcare utilizations such as inpatient, emergency department, and outpatient use and length of stay among these 3 data sets. We applied standardized differences to compare the medians for each outcome. Results: The sample size of the open claims data sets was 10 to 65 times larger than closed claims data sets depending on disease type. For each disease, the estimates of healthcare utilization were similar between the open claims and closed claims data. The difference was statistically insignificant. Conclusions: Open claims data with a bigger sample size and more current available information provide essential advantages for healthcare outcomes research studies. Therefore, especially for new medications and rare diseases, open claims data can provide information much earlier than closed claims, which usually have a time lag of 6 to 8 months.

Use of Open Claims vs Closed Claims in Health Outcomes Research

Background: Closed claims are frequently used in outcomes research studies. Lately, the availability of open claims has increased the possibility of obtaining information faster and on a larger scale. However, because of the possibility of missing claims and duplications, these data sets have not been highly utilized in medical research. Objective: To compare frequently used healthcare utilization measures between closed claims and open claims to analyze if the possibility of missing claims in open claims data creates a downward bias in the estimates. Methods: We identified 18 different diseases using 2022 data from 2 closed claims data sets (MarketScan® and PharMetrics® Plus) and 1 open claims database (Kythera). After applying an algorithm that removes possible duplications from open claims data, we compared healthcare utilizations such as inpatient, emergency department, and outpatient use and length of stay among these 3 data sets. We applied standardized differences to compare the medians for each outcome. Results: The sample size of the open claims data sets was 10 to 65 times larger than closed claims data sets depending on disease type. For each disease, the estimates of healthcare utilization were similar between the open claims and closed claims data. The difference was statistically insignificant. Conclusions: Open claims data with a bigger sample size and more current available information provide essential advantages for healthcare outcomes research studies. Therefore, especially for new medications and rare diseases, open claims data can provide information much earlier than closed claims, which usually have a time lag of 6 to 8 months.

Did the poor gain from India\u2019s health policy interventions? Evidence from benefit-incidence analysis, 2004\u20132018

BackgroundHealth policy interventions were expected to improve access to health care delivery, provide financial risk protection, besides reducing inequities that underlie geographic and socio-economic variation in population access to health care. This article examines whether health policy interventions and accelerated health investments in India during 2004–2018 could close the gap in inequity in health care utilization and access to public subsidy by different population groups. Did the poor and socio-economically vulnerable population gain from such government initiatives, compared to the rich and affluent sections of society? And whether the intended objective of improving equity between different regions of the country been achieved during the policy initiatives? This article attempts to assess and provide robust evidence in the Indian context.MethodsEmploying Benefit-Incidence Analysis (BIA) framework, this paper advances earlier evidence by highlighting estimates of health care utilization, concentration and government subsidy by broader provider categories (public versus private) and across service levels (outpatient, inpatient, maternal, pre-and post-natal services). We used 2 waves of household surveys conducted by the National Sample Survey Organisation (NSSO) on health and morbidity. The period of analysis was chosen to represent policy interventions spanning 2004 (pre-policy) and 2018 (post-policy era). We present this evidence across three categories of Indian states, namely, high-focus states, high-focus north eastern states and non-focus states. Such categorization facilitates quantification of reform impact of policy level interventions across the three groups.ResultsUtilisation of healthcare services, except outpatient care visits, accelerated significantly in 2018 from 2004. The difference in utilisation rates between poor and rich (between poorest 20% and richest 20%) had significantly declined during the same period. As far as concentration of healthcare is concerned, the Concentrate Index (CI) underlying inpatient care in public sector fell from 0.07 in 2004 to 0.05 in 2018, implying less pro-rich distribution. The CI in relation to pre-natal, institutional delivery and postnatal services in government facilities were pro-poor both in 2004 and 2018 in all 3 groups of states. The distribution of public subsidy underscoring curative services (inpatient and outpatient) remained pro-rich in 2004 but turned less pro-rich in 2018, measured by CIs which declined sharply across all groups of states for both outpatient (from 0.21 in 2004 to 0.16 in 2018) and inpatient (from 0.24 in 2004 to 0.14 in 2018) respectively. The CI for subsidy on prenatal services declined from approximately 0.01 in 2004 to 0.12 in 2018. In respect to post-natal care, similar results were observed, implying the subsidy on prenatal and post-natal services was overwhelmingly received by poor. The CI underscoring subsidy for institutional delivery although remained positive both in 2018 and 2004, but slightly increased from 0.17 in 2004 to 0.28 in 2018.ConclusionsImprovement in infrastructure and service provisioning through NHM route in the public facilities appears to have relatively benefited the poor. Yet they received a relatively smaller health subsidy than the rich when utilising inpatient and outpatient health services. Inequality continues to persist across all healthcare services in private health sector. Although the NHM remained committed to broader expansion of health care services, a singular focus on maternal and child health conditions especially in backward regions of the country has yielded desired results.

Population-Based Estimates of Health Care Utilization and Expenditures by Adults During the Last 2 Years of Life in Canada’s Single-Payer Health System

Measuring health care utilization and costs before death has the potential to initiate health care improvement. To examine population-level trends in health care utilization and expenditures in the 2 years before death in Canada's single-payer health system. This population-based cohort included 966 436 deaths among adult residents of Ontario, Canada, from January 2005 to December 2015, linked to health administrative and census data. Data for deaths from 2005 to 2013 were analyzed from November 1, 2016, through January 31, 2017. Analyses were updated from May 1, 2019, to June 15, 2019, to include deaths from 2014 and 2015. Sociodemographic exposures included age, sex, and neighborhood income quintiles, which were obtained by linking decedents' postal codes to census data. Aggregated Diagnosis Groups were used as a general health service morbidity-resource measure. Health care services accessed for the last 2 years of life, including acute hospitalization episodes of care, intensive care unit visits, and emergency department visits. Total health care costs were calculated using a person-centered costing approach. The association of area-level income with high resource use 1 year before death was analyzed with Poisson regression analysis, controlling for age, sex, and Aggregated Diagnosis Groups. Among 966 436 decedents (483 038 [50.0%] men; mean [SD] age, 76.4 [14.96] years; 231 634 [24.0%] living in the lowest neighborhood income quintile), health care expenditures increased in the last 2 years of life during the study period (CAD$5.12 billion [US $3.83 billion] in 2005 vs CAD$7.84 billion [US $5.86 billion] in 2015). In the year before death, 758 770 decedents (78.5%) had at least 1 hospitalization episode of care, 266 987 (27.6%) had at least 1 intensive care unit admission, and 856 026 (88.6%) had at least 1 emergency department visit. Overall, deaths in hospital decreased from 37 984 (45.6%) in 2005 to 39 474 (41.5%) in 2015. Utilization in the last 2 years, 1 year, 180 days, and 30 days of life varied by resource utilization gradients. For example, the proportion of individuals visiting the emergency department was slightly higher among the top 5% of health care users compared with other utilization groups in the last 2 years of life (top 5%, 45 535 [94.2%]; top 6%-50%, 401 022 [92.2%]; bottom 50%, 409 469 [84.7%]) and 1 year of life (top 5%, 43 007 [89.0%]; top 6%-50%, 381 732 [87.8%]; bottom 50%, 380 859 [78.8%]); however, in the last 30 days of life, more than half of individuals in the top 6% to top 50% (223 262 [51.3%]) and bottom 50% (288 480 [59.7%]) visited an emergency department, compared with approximately one-third of individuals in the top 5% (16 916 [35.0%]). No meaningful associations were observed in high resource use between individuals in the highest income quintile compared with the lowest income quintile (rate ratio, 1.02; 95% CI, 0.99-1.05) after adjusting for relevant covariates. In this study, health care use and spending in the last 2 years of life in Ontario were high. These findings highlight a trend in hospital-centered care before death in a single-payer health system.

Estimates of healthcare utilisation and deaths from waterborne pathogen exposure in Ontario, Canada.

Burden of disease analyses can quantify the relative impact of different exposures on population health outcomes. Gastroenteritis where the causative pathogen was not determined and respiratory illness resulting from exposure to opportunistic pathogens transmitted by water aerosols have not always been considered in waterborne burden of disease estimates. We estimated the disease burden attributable to nine enteric pathogens, unspecified pathogens leading to gastroenteritis, and three opportunistic pathogens leading primarily to respiratory illness, in Ontario, Canada (population ~14 million). Employing a burden of disease framework, we attributed a fraction of annual (year 2016) emergency department (ED) visits, hospitalisations and deaths to waterborne transmission. Attributable fractions were developed from the literature and clinical input, and unattributed disease counts were obtained using administrative data. Our Monte Carlo simulation reflected uncertainty in the inputs. The estimated mean annual attributable rates for waterborne diseases were (per 100 000 population): 69 ED visits, 12 hospitalisations and 0.52 deaths. The corresponding 5th-95th percentile estimates were (per 100 000 population): 13-158 ED visits, 5-22 hospitalisations and 0.29-0.83 deaths. The burden of disease due to unspecified pathogens dominated these rates: 99% for ED visits, 63% for hospitalisations and 40% for deaths. However, when a causative pathogen was specified, the majority of hospitalisations (83%) and deaths (97%) resulted from exposure to the opportunistic pathogens Legionella spp., non-tuberculous mycobacteria and Pseudomonas spp. The waterborne disease burden in Ontario indicates the importance of gastroenteritis not traced back to a particular pathogen and of opportunistic pathogens transmitted primarily through contact with water aerosols.

Venous thromboembolism in chronic pediatric heart disease is associated with substantial health care burden and expenditures

BackgroundVenous thromboembolism (VTE) is a complication in children with chronic pediatric heart disease (CPHD). The influence of acute VTE risk factors and the health care burden associated with VTE in CPHD is unknown. MethodsChildren <18 years of age with a CPHD diagnostic code were identified from the 2003‐2013 MarketScan Commercial Databases. VTE diagnoses were identified either concomitantly with initial CPHD diagnoses or during a 6‐month follow‐up. The associations between demographic and clinical characteristics and VTE among children with CPHD, stratified by recent cardiac surgery, were assessed by multivariable logistic regression models. Estimates of health care utilization were compared using Wilcoxon rank‐sum tests. ResultsVTE events occurred in 957 of 120 884 children with CPHD (0.8%). In‐hospital mortality was significantly higher in children with VTE. Single‐ventricle physiology had the highest VTE rate (2.3%). All comorbid conditions were significantly associated with VTE, but the prevalence was highest in children with recent cardiac (11.1%) or noncardiac surgery (7.8%). The magnitude of association between noncardiac comorbidities and acquired acute cardiovascular conditions and VTE were larger for children without a recent cardiac surgery. Children with VTE had significantly higher health care utilization. ConclusionsVTE in CPHD is associated with significantly increased health care resource utilization and in‐hospital mortality. All of the comorbid conditions examined were significantly associated with VTE, but a recent surgical procedure, especially cardiac surgery, conferred the highest VTE risk. Although confounding inherently limits observational studies, these findings provide practical information about the health care costs among patients with CPHD and VTE.Unlabelled Box

Healthcare utilization and cost trajectories post-stroke: role of caregiver and stroke factors

BackgroundIt is essential to study post-stroke healthcare utilization trajectories from a stroke patient caregiver dyadic perspective to improve healthcare delivery, practices and eventually improve long-term outcomes for stroke patients. However, literature addressing this area is currently limited. Addressing this gap, our study described the trajectory of healthcare service utilization by stroke patients and associated costs over 1-year post-stroke and examined the association with caregiver identity and clinical stroke factors.MethodsPatient and caregiver variables were obtained from a prospective cohort, while healthcare data was obtained from the national claims database. Generalized estimating equation approach was used to get the population average estimates of healthcare utilization and cost trend across 4 quarters post-stroke.ResultsFive hundred ninety-two stroke patient and caregiver dyads were available for current analysis. The highest utilization occurred in the first quarter post-stroke across all service types and decreased with time. The incidence rate ratio (IRR) of hospitalization decreased by 51, 40, 11 and 1% for patients having spouse, sibling, child and others as caregivers respectively when compared with not having a caregiver (p = 0.017). Disability level modified the specialist outpatient clinic usage trajectory with increasing difference between mildly and severely disabled sub-groups across quarters. Stroke type and severity modified the primary care cost trajectory with expected cost estimates differing across second to fourth quarters for moderately-severe ischemic (IRR: 1.67, 1.74, 1.64; p = 0.003), moderately-severe non-ischemic (IRR: 1.61, 3.15, 2.44; p = 0.001) and severe non-ischemic (IRR: 2.18, 4.92, 4.77; p = 0.032) subgroups respectively, compared to first quarter.ConclusionHighlighting the quarterly variations, we reported distinct utilization trajectories across subgroups based on clinical characteristics. Caregiver availability reducing hospitalization supports revisiting caregiver’s role as potential hidden workforce, incentivizing their efforts by designing socially inclusive bundled payment models for post-acute stroke care and adopting family-centered clinical care practices.

Abstract P6-11-02: Hospitalizations and costs during Implementation of a lay navigation program for older patients with breast cancer in the deep south

Abstract Background: Patient-centered strategies are needed to enhance the value of cancer care particularly at the end of life. Lay navigators (LN) can be trained to provide an extra layer of support for cancer patients from diagnosis through survivorship or end of life. We hypothesized that integrating LNs into the care team would reduce healthcare utilization and cost for patients with cancer, including those with breast cancer. Methods: A prospective, observational study of Medicare claims data was conducted of beneficiaries ≥ 65 years old diagnosed with cancer after 2008 who received care within the UAB Health System Cancer Community Network (12 cancer centers of varying size located in AL, MS, TN, GA, and FL). The first breast cancer (BC) patient was enrolled in navigation in April 2013, and ∼18% of BC patients were navigated by the end of 2014. For this analysis, we report on the subset of patients with BC. The outcomes of interest were calculated per quarter from 2012-2014: (1) the proportion of patients with at least 1 hospitalization, (2) the proportion of the 492 deceased BC patients with a hospitalization in the last 30 and 14 days of life and (3) the Total costs for Medicare, excluding prescription drug costs. We used general linear models to evaluate changes in both health care utilization and cost over time, adjusting for age, sex, cancer stage, phase of care, and navigation group. Differential effects for navigated and non-navigated groups were tested with a group*time interaction. Healthcare utilization estimates are presented as Incidence Rate Ratios (IRR), and costs for Medicare as parameter estimates (β) in terms of dollar amounts. Results: 4835 BC patients received care from 2012-2014: 622 received navigation services. 14.2 % of navigated BC patients were stage III/IV, compared to 9.33% of non-navigated patients. The proportion of hospitalizations trended downward from 7.9% in quarter 1 (Q1) 2012 to 5.7% in Q4 of 2014 (IRR 0.965, p =0.14), with similar decreases for navigated and non-navigated patients (IRR= 1.00, p &amp;gt; 0.05). Hospitalization in the last 30 days and last 14 days of life were 49.7% and 29.3%, respectively, with no between groups difference. Costs per beneficiary per quarter decreased overall from $4,161 in Q1 2012 to $3,010 in Q4 2014 (p &amp;lt;0.0001). In adjusted analysis, the navigated patients had an average $577 greater decline per quarter than the non-navigated patients (βNavigated=-$636; βnon-Navigated=-$59; p&amp;lt;0.0001). Conclusions: Medicare costs declined during implementation of a lay navigation program, with greater reductions for navigated patients than non-navigated BC patients. Overall hospitalizations also declined, yet rates remain high for breast cancer patients at the end of life. Integration of LNs should be considered by health systems aiming to transition to value-based healthcare delivery. The project described was supported by Grant Number 1C1CMS331023 from the Department of Health and Human Services, Centers for Medicare &amp; Medicaid Services. The contents of this abstract are solely the responsibility of the authors and do not necessarily represent the official views of the U.S. Department of Health and Human Services or any of its agencies. Citation Format: Rocque GB, Kvale EA, Jackson BE, Kenzik K, Lisovicz N, Demark-Wahnefried W, Meneses KM, Taylor RA, Acemgil A, Chambless C, Li Y, Martin M, Fouad M, Pisu M, Partridge EE. Hospitalizations and costs during Implementation of a lay navigation program for older patients with breast cancer in the deep south. [abstract]. In: Proceedings of the Thirty-Eighth Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2015 Dec 8-12; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2016;76(4 Suppl):Abstract nr P6-11-02.

Palliative care needs in patients hospitalized with heart failure (PCHF) study: rationale and design.

AimsThe primary aim of this study is to provide data to inform the design of a randomized controlled clinical trial (RCT) of a palliative care (PC) intervention in heart failure (HF). We will identify an appropriate study population with a high prevalence of PC needs defined using quantifiable measures. We will also identify which components a specific and targeted PC intervention in HF should include and attempt to define the most relevant trial outcomes.MethodsAn unselected, prospective, near‐consecutive, cohort of patients admitted to hospital with acute decompensated HF will be enrolled over a 2‐year period. All potential participants will be screened using B‐type natriuretic peptide and echocardiography, and all those enrolled will be extensively characterized in terms of their HF status, comorbidity, and PC needs. Quantitative assessment of PC needs will include evaluation of general and disease‐specific quality of life, mood, symptom burden, caregiver burden, and end of life care. Inpatient assessments will be performed and after discharge outpatient assessments will be carried out every 4 months for up to 2.5 years. Participants will be followed up for a minimum of 1 year for hospital admissions, and place and cause of death. Methods for identifying patients with HF with PC needs will be evaluated, and estimates of healthcare utilisation performed.ConclusionBy assessing the prevalence of these needs, describing how these needs change over time, and evaluating how best PC needs can be identified, we will provide the foundation for designing an RCT of a PC intervention in HF.

Building Wave Response Rates in a Longitudinal Survey

In national health care surveys, significant amounts of resources are allocated to obtaining the participation of households that constitute the last 5–10% of the overall survey response rate. This study examines the implications of a reduction in targeted first-round response rates in the Medical Expenditure Panel Survey (MEPS), a national health care survey designed to produce estimates of health care utilization, expenditures, and insurance coverage. The potential impact of this modification on annual and overall longitudinal survey response rates, survey estimates, and costs is determined and compared with an alternative approach that subsamples these difficult to field cases. Study findings revealed nonuniform results when evaluating the capacity of these alternative design strategies to achieve precision targets while simultaneously satisfying data collection budget constraints for a variety of medical care expenditure estimates. Based on these results, it was determined that additional experimentation was necessary prior to implementing design modifications.

Accounting for the Hierarchical Structure in Veterans Health Administration Data: Differences in Healthcare Utilization between Men and Women Veterans.

Women currently constitute 15% of active United States of America military service personnel, and this proportion is expected to double in the next 5 years. Previous research has shown that healthcare utilization and costs differ in women US Veterans Health Administration (VA) patients compared to men. However, none have accounted for the potential effects of clustering on their estimates of healthcare utilization. US Women Veterans are more likely to serve in specific military branches (e.g. Army), components (e.g. National Guard), and ranks (e.g. officer) than men. These factors may confer different risk and protection that can affect subsequent healthcare needs. Our study investigates the effects of accounting for the hierarchical structure of data on estimates of the association between gender and VA healthcare utilization. The sample consisted of data on 406,406 Veterans obtained from VA's Operation Enduring Freedom/Operation Iraqi Freedom roster provided by Defense Manpower Data Center - Contingency Tracking System Deployment File. We compared three statistical models, ordinary, fixed and random effects hierarchical logistic regression, in order to assess the association of gender with healthcare utilization, controlling for branch of service, component, rank, age, race, and marital status. Gender was associated with utilization in ordinary logistic and, but not in fixed effects hierarchical logistic or random effects hierarchical logistic regression models. This point out that incomplete inference could be drawn by ignoring the military structure that may influence combat exposure and subsequent healthcare needs. Researchers should consider modeling VA data using methods that account for the potential clustering effect of hierarchy.

Official statistics and claims data records indicate non-response and recall bias within survey-based estimates of health care utilization in the older population

BackgroundThe validity of survey-based health care utilization estimates in the older population has been poorly researched. Owing to data protection legislation and a great number of different health care insurance providers, the assessment of recall and non-response bias is challenging to impossible in many countries. The objective of our study was to compare estimates from a population-based study in older German adults with external secondary data.MethodsWe used data from the German KORA-Age study, which included 4,127 people aged 65–94 years. Self-report questions covered the utilization of long-term care services, inpatient services, outpatient services, and pharmaceuticals. We calculated age- and sex-standardized mean utilization rates in each domain and compared them with the corresponding estimates derived from official statistics and independent statutory health insurance data.ResultsThe KORA-Age study underestimated the use of long-term care services (−52%), in-hospital days (−21%) and physician visits (−70%). In contrast, the assessment of drug consumption by postal self-report questionnaires yielded similar estimates to the analysis of insurance claims data (−9%).ConclusionSurvey estimates based on self-report tend to underestimate true health care utilization in the older population. Direct validation studies are needed to disentangle the impact of recall and non-response bias.

Assessing Healthcare Utilization for Influenza-like Illness at an Emergency Department and a Student Health Service during the 2009-2010 H1N1 Pandemic.

Estimates of healthcare utilization during an influenza pandemic are needed in order to plan for the allocation of staff and resources. The aim of this study was to assess the number, age, and arrival time of patients with influenza-like-illness (ILI), and associations between their symptoms during the 2009–2010 H1N1 pandemic. We conducted a cross-sectional analysis of electronic health records from the student health service (SHS) and an emergency department (ED) in Morgantown, West Virginia, between January 2009 and December 2010. During the 2009–2010 H1N1 pandemic, patient arrivals at SHS and ED varied over the week. SHS patients arrived early in the week and primarily in the afternoon. ED patient arrivals were more evenly distributed, with busier evenings and weekends. Those with fever were more likely to experience cough, sore throat, vomiting/nausea, chills, congestion, headache, and body-ache. These results can assist health professionals in preparing for an influenza pandemic.

The utility of the integrated design of the Medical Expenditure Panel Survey to inform mortality related studies\footnotemark

The analytic capacity of surveys can be dramatically enhanced through the linkage to existing secondary data sources at higher levels of aggregation as well as through direct matches to additional health and socio-economic measures acquired for the same set of sample units from other sources of survey specific or administrative data. In this presentation, the capacity of an integrated survey design to enhance longitudinal analyses focused on mortality studies is discussed. Examples are drawn from the Medical Expenditure Panel Survey (MEPS), designed to produce estimates of health care utilization, expenditures, sources of payment, and insurance coverage of the US population. Analyses are conducted to examine differentials in pre-dispositional factors that distinguish a representative sample of decedents from their surviving counterparts and to assess the relationship between antecedent health and health care related factors and mortality. The relationship between medical expenditure levels over time and mortality is also examined to illustrate the enhanced set of longitudinal analyses that can be undertaken. The views expressed are those of the author and no official endorsement by the Agency for Healthcare Research and Quality or the Department of Health and Human Services is intended or should be inferred. All tables can be obtained from the author upon request.

An assessment of the impact of two distinct survey design modifications on health care utilization estimates in the medical expenditure panel survey

The Medical Expenditure Panel Survey (MEPS) is one of the core health care surveys that are a primary source for essential national healthcare utilization estimates. In 2007, the survey experienced two dominant survey design modifications: a new sample design attributable to the sample redesign of the National Health Interview Survey, and an upgrade to the Computer Assisted Personal Interview (CAPI) platform for the survey instrument, moving from a DOS to a Windows based environment. This study examines the impact of these survey design modifications on the national health care utilization estimates. Particular attention is given to assessing the level of convergence in utilization estimates based on the alternative designs as well as the alignment of model based analyses that discern which factors are associated with health care use. The paper concludes with a discussion of strategies that may yield additional improvements in the accuracy for these policy relevant survey estimates.

Trends in Health Care Expenditures, Utilization, and Health Status Among US Adults With Spine Problems, 1997–2006

Analysis of nationally representative survey data for spine-related health care expenditures, utilization and self-reported health status. To study trends from 1997 to 2006 in per-user expenditures for spine-related inpatient, outpatient, pharmacy, and emergency services; and to compare these trends to changes in health status. Although prior work has shown overall spine-related expenditures accounted for $86 billion in 2005, increasing 65% since 1997, the study did not report per-user expenditures. Understanding population-level per-user expenditure for specific services relative to changes in the health status may help assess the value of these services. We analyzed data from the Medical Expenditure Panel Survey, a multistage survey sample designed to produce unbiased national estimates of health care utilization and expenditure. Spine-related hospitalizations, outpatient visits, prescription medications and emergency department visits were identified using ICD-9-CM diagnosis codes. Regression analyses controlling for age, sex, comorbidity, and time (years) were used to examine trends from 1997 to 2006 in inflation-adjusted per-user expenditures, and utilization, and self-reported health status. An average of 1774 respondents with spine problems was surveyed per year; the proportion suggested an increase in the number of people who sought treatment for spine problems in the United States from 14.8 million in 1997 to 21.9 million in 2006. From 1997 to 2006, the mean adjusted per-user expenditures were the largest component of increasing total costs for inpatient hospitalizations, prescription medications, andemergency department visits, increasing 37% (from $13,040 in 1997 to $17,909 in 2006), 139% (from $166 to $397), and 84% (from $81 to $149), respectively. A 49% increase in the number of patients seeking spine-related care (from 12.2 million in 1997 to 18.2 million in 2006) was the largest contributing factor to increased outpatient expenditures. Population measures of mental health and work, social, and physical limitations worsened over time among people with spine problems. Expenditure increases for spine-related inpatient, prescription, and emergency services were primarily the result of increasing per-user expenditures, while those related to outpatient visits were primarily due to an increase in the number of users of ambulatory services.

The effect of non-response on estimates of health care utilisation: linking health surveys and registers

Non-response in health surveys may lead to bias in estimates of health care utilisation. The magnitude, direction and composition of the bias are usually not well known. When data from health surveys are merged with data from registers at the individual level, analyses can reveal non-response bias. Our aim was to estimate the composition, direction and magnitude of non-response bias in the estimation of health care costs in two types of health interview surveys. The surveys were (1) a national personal interview survey of 22 484 Danes (2) a telephone interview survey of 5000 Danes living in Funen County. Data were linked with register information on health care utilisation in hospitals and primary care. Health care utilisation was estimated for respondents and non-respondents, and the difference was explained by a decomposition method of bias components. The surveys produced the same pattern of non-response, but with slight differences in non-response bias. Response rates for the interview and telephone surveys were 75 and 69%, respectively. Refusal was the most frequent reason for non-response (22 and 20% of those sampled, respectively), whereas illness, non-contact, and other reasons were less frequent. Respondents used 3-6% less health care than non-respondents at the aggregate level, but the opposite was true for some specific types of health care. Non-response due to illness was the main contributor to non-response bias. Different types of non-response have different bias effects. However, the magnitude of the bias encourages the continued use of interview health surveys.

COPD as a multicomponent disease: Inventory of dyspnoea, underweight, obesity and fat free mass depletion in primary care

To describe the distribution of COPD disease severity in primary care based on airway obstruction, and to assess the extent to which dyspnoea scores, body mass index (BMI) and fat free mass (FFM) index contribute to the distribution of COPD severity in primary care. Cross sectional population-based study. 317 patients with COPD were recruited from an outpatient disease management programme. Prevalence of moderate to severe dyspnoea, underweight, obesity and FFM depletion by GOLD stage were measured. According to GOLD guidelines, 29% of patients had mild COPD, 48% moderate, 17% severe and 5% very severe. A substantial number of patients classified as GOLD stage 2 reported severe dyspnoea (28.1%) and/or suffered from FFM depletion (16.3%). Prevalence of low body weight strongly increased in GOLD stage 4. Prevalence of obesity is highest in GOLD stages 1 and 2. The use of a multidimensional grading system, taking into account dyspnoea as well as the nutritional status of COPD patients, is likely to influence the distribution of disease severity in a primary care population. This might have implications for prevention, non-medical treatment, and estimates of health care utilisation in primary care.

Integrated survey designs: A framework for nonresponse bias reduction

The quality and data content of household specific health surveys are often enhanced through integrated designs which include the conduct of follow back surveys to medical providers and facilities that have provided care to household respondents. In terms of data quality, household reported medical conditions can be evaluated for accuracy relative to provider specific records on medical conditions for the same patient and specific health events. With respect to health care expenditures collected from household respondents for their reported health care events, available linked medical provider level data is a more accurate source of information. The availability of such supplemental data on use and expenditures allows for the conduct of methodological studies to evaluate the accuracy of household reported data and informs adjustment strategies to household data in the absence of provider specific data to reduce bias attributable to response error. In this paper, the capacity of integrated survey designs to achieve reductions in bias attributable to survey nonresponse is discussed. Examples are drawn from the Medical Expenditure Panel Survey (MEPS), an ongoing longitudinal panel survey designed to produce estimates of health care utilization, expenditures, sources of payment, and insurance coverage of the US civilian non-institutionalized population.