Objectives:Implementation of the International Statistical Classification of Disease and Related Health Problems, 10th Revision (ICD-10) coding system presents challenges for using administrative data. Recognizing this, we conducted a multistep process to develop ICD-10 coding algorithms to define C

https://czresearch.com/dropbox/Quan_MedCare_2005v43p1130.pdf

Coding algorithms for defining comorbidities in ICD-9-CM and ICD-10 administrative data.

With advances in the effectiveness of treatment and disease management, the contribution of chronic comorbid diseases (comorbidities) found within the Charlson comorbidity index to mortality is likely to have changed since development of the index in 1984. The authors reevaluated the Charlson index and reassigned weights to each condition by identifying and following patients to observe mortality within 1 year after hospital discharge. They applied the updated index and weights to hospital discharge data from 6 countries and tested for their ability to predict in-hospital mortality. Compared with the original Charlson weights, weights generated from the Calgary, Alberta, Canada, data (2004) were 0 for 5 comorbidities, decreased for 3 comorbidities, increased for 4 comorbidities, and did not change for 5 comorbidities. The C statistics for discriminating in-hospital mortality between the new score generated from the 12 comorbidities and the Charlson score were 0.825 (new) and 0.808 (old), respectively, in Australian data (2008), 0.828 and 0.825 in Canadian data (2008), 0.878 and 0.882 in French data (2004), 0.727 and 0.723 in Japanese data (2008), 0.831 and 0.836 in New Zealand data (2008), and 0.869 and 0.876 in Swiss data (2008). The updated index of 12 comorbidities showed good-to-excellent discrimination in predicting in-hospital mortality in data from 6 countries and may be more appropriate for use with more recent administrative data.

/pdf/updating-and-validating-the-charlson-comorbidity-index-and-u1djuhty32.pdf

Updating and Validating the Charlson Comorbidity Index and Score for Risk Adjustment in Hospital Discharge Abstracts Using Data From 6 Countries

The mission of the Agency for Healthcare Research and Quality is “to improve the quality, safety, efficiency, and effectiveness of health care for all Americans”. The organization and selected major activities of the Agency are briefly described.

The Agency for Healthcare Research and Quality

Methods: A cross-sectional analysis was conducted on a nationally random sample of 1217103 Medicare feefor-service beneficiaries aged 65 and older living in the United States and enrolled in both Medicare Part A and Medicare Part B during 1999. Multiple logistic regression was used to analyze the influence of age, sex, and number of types of chronic conditions on the risk of incurring inpatient hospitalizations for ambulatory care sensitive conditions and hospitalizations with preventable complications among aged Medicare beneficiaries. Results: In 1999, 82% of aged Medicare beneficiaries had 1 or more chronic conditions, and 65% had multiple chronic conditions. Inpatient admissions for ambulatory care sensitive conditions and hospitalizations with preventable complications increased with the number of chronic conditions. For example, Medicare beneficiaries with 4 or more chronic conditions were 99 times more likely than a beneficiary without any chronic conditions to have an admission for an ambulatory care sensitive condition (95% confidence interval, 86-113). Per capita Medicare expenditures increased with the number of types of chronic conditions from $211 among beneficiaries without a chronic condition to $13973 among beneficiaries with 4 or more types of chronic conditions. Conclusions: The risk of an avoidable inpatient admission or a preventable complication in an inpatient setting increases dramatically with the number of chronic conditions. Better primary care, especially coordination of care, could reduce avoidable hospitalization rates, especially for individuals with multiple chronic conditions.

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Prevalence, expenditures, and complications of multiple chronic conditions in the elderly

www.mobilehealthmap.org 617‐442‐3200 New research shows that mobile health clinics improve health outcomes for hard to reach populations in cost‐effective and culturally competent ways . A Harvard Medical School study determined that for every dollar invested in a mobile health clinic, the US healthcare system saves $30 on average. Mobile health clinics, which offer a range of services from preventive screenings to asthma treatment, leverage their mobility to treat people in the convenience of their own communities. For example, a mobile health clinic in Baltimore, MD, has documented savings of $3,500 per child seen due to reduced asthma‐related hospitalizations. The estimated 2,000 mobile health clinics across the country are providing similarly cost‐effective access to healthcare for a wide range of populations. Many successful mobile health clinics cite their ability to foster trusting relationships. Qualitative research in such mobile health clinics has found that patients value the informal, familiar environment in a convenient location, with staff who “are easy to talk to,” and that the staff’s “marriage of professional and personal discourses” provides patients the space to disclose information themselves. A communications academic argued that mobile health clinics’ unique use of space is important in facilitating these relationships. Mobile health clinics park in the heart of the community in familiar spaces, like shopping centers or bus stations, which lend themselves to the local community atmosphere.

Unequal Treatment: Confronting Racial and Ethnic Disparities in Health Care

Objectives.This study attempts to develop a comprehensive set of comorbidity measures for use with large administrative inpatient datasets.Methods.The study involved clinical and empirical review of comorbidity measures, development of a framework that attempts to segregate comorbidities from other

https://czresearch.com/dropbox/Elixhauser_MedCare_1998v36p8.pdf

Comorbidity measures for use with administrative data.

Background Some cerebrovascular events are not diagnosed promptly, potentially resulting in death or disability from missed treatments. We sought to estimate the frequency of missed stroke and examine associations with patient, emergency department (ED), and hospital characteristics. Methods Cross-sectional analysis using linked inpatient discharge and ED visit records from the 2009 Healthcare Cost and Utilization Project State Inpatient Databases and 2008-2009 State ED Databases across nine US states. We identified adult patients admitted for stroke with a treat-and-release ED visit in the prior 30 days, considering those given a non-cerebrovascular diagnosis as probable (benign headache or dizziness diagnosis) or potential (any other diagnosis) missed strokes. Results There were 23,809 potential and 2243 probable missed strokes representing 12.7% and 1.2% of stroke admissions, respectively. Missed hemorrhages (n = 406) were linked to headache while missed ischemic strokes (n = 1435) and transient ischemic attacks (n = 402) were linked to headache or dizziness. Odds of a probable misdiagnosis were lower among men (OR 0.75), older individuals (18-44 years [base]; 45-64:OR 0.43; 65-74:OR 0.28; ≥ 75:OR 0.19), and Medicare (OR 0.66) or Medicaid (OR 0.70) recipients compared to privately insured patients. Odds were higher among Blacks (OR 1.18), Asian/Pacific Islanders (OR 1.29), and Hispanics (OR 1.30). Odds were higher in non-teaching hospitals (OR 1.45) and low-volume hospitals (OR 1.57). Conclusions We estimate 15,000-165,000 misdiagnosed cerebrovascular events annually in US EDs, disproportionately presenting with headache or dizziness. Physicians evaluating these symptoms should be particularly attuned to the possibility of stroke in younger, female, and non-White patients.

/pdf/missed-diagnosis-of-stroke-in-the-emergency-department-a-4ro2jghw81.pdf

Missed diagnosis of stroke in the emergency department: a cross-sectional analysis of a large population-based sample

Background: Patient safety events that result from the happenstance of mistakes and errors should not occur systematically across racial, ethnic, or socioeconomic subgroups. Objective: To determine whether racial and ethnic differences in patient safety events disappear when income (a proxy for socioeconomic status) is taken into account. Research Design: This study analyzes administrative data from community hospitals in 16 states with reliable race/ethnicity measures in the 2000 Healthcare Cost and Utilization Project of the Agency for Healthcare Research and Quality (AHRQ), using the publicly available AHRQ patient safety indicators (PSIs). Results: Different indicators show different results for different racial/ethnic subgroups. Many events with higher rates for non-Hispanic blacks (compared with non-Hispanic whites) remain higher when income is taken into account, although such differences for Hispanics or Asian/Pacific Islanders (APIs) tend to disappear. Many events with lower rates for Hispanics and APIs remain lower than whites when income is taken into account, but for blacks, they disappear. Discussion: The higher rates for minorities that reflect the way health care is delivered raise troubling questions about potential racial/ethnic bias and discrimination in the US health care system, problems with cultural sensitivity and effective communication, and access to high-quality health care providers. Conclusions: The AHRQ PSIs are a broad screen for potential safety events that point to needed improvement in the quality of care for specific populations.

Racial, ethnic, and socioeconomic disparities in estimates of AHRQ patient safety indicators.

The presence of multiple chronic conditions (MCCs) complicates inpatient hospital care, leading to higher costs and utilization. Multimorbidity also complicates primary care, increasing the likelihood of hospitalization for ambulatory care sensitive conditions. The purpose of this study was to evaluate how MCCs relate to inpatient hospitalization costs and utilization for ambulatory care sensitive conditions. The 2012 Agency for Healthcare Research and Quality (AHRQ) Healthcare Cost and Utilization Project (HCUP) State Inpatient Databases (SID) provided data to carry out a cross-sectional analysis of 1.43 million claims related to potentially preventable hospitalizations classified by the AHRQ Prevention Quality Indicator (PQI) composites. Categories of MCCs (0–1, 2–3, 4–5, and 6+) were examined in sets of acute, chronic, and overall PQIs. Multivariate models determined associations between categories of MCCs and 1) inpatient costs per stay, 2) inpatient costs per day, and 3) length of inpatient hospitalization. Negative binomial was used to model costs per stay and costs per day. The most common category observed was 2 or 3 chronic conditions (37.8 % of patients), followed by 4 or 5 chronic conditions (30.1 % of patients) and by 6+ chronic conditions (10.1 %). Compared with costs for patients with 0 or 1 chronic condition, hospitalization costs per stay for overall ambulatory care sensitive conditions were 19 % higher for those with 2 or 3 (95 % confidence interval [CI] 1.19–1.20), 32 % higher for those with 4 or 5 (95 % CI 1.31–1.32), and 31 % higher (95 % CI 1.30–3.32) for those with 6+ conditions. Acute condition stays were 11 % longer when 2 or 3 chronic conditions were present (95 % CI 1.11–1.12), 21 % longer when 4 or 5 were present (95 % CI 1.20–1.22), and 27 % longer when 6+ were present (95 % CI 1.26–1.28) compared with those with 0 or 1 chronic condition. Similar results were seen within chronic conditions. Associations between MCCs and total costs were driven by longer stays among those with more chronic conditions rather than by higher costs per day. The presence of MCCs increased inpatient costs for ambulatory care sensitive conditions via longer hospital stays.

/pdf/the-effects-of-multiple-chronic-conditions-on-3b8rqd6dob.pdf

The effects of multiple chronic conditions on hospitalization costs and utilization for ambulatory care sensitive conditions in the United States: a nationally representative cross-sectional study

Spending for mental health and substance abuse (MHSA) treatment in the United States totaled $104 billion in 2001, representing 7.6 percent of all health care spending. The nominal MHSA annual spending growth rate from 1991 to 2001 was 5.6 per- cent, almost one percentage point below the growth rate for all health care (6.5 percent). During this period, Medicaid has increased to be the largest payer of mental health care, with prescription drugs the fastest-growing spending component. Private insurance pay- ment for substance abuse actually dropped in real dollars, increasing the public share of substance abuse spending.

Rosanna M. Coffey

Papers

Comorbidity measures for use with administrative data.

Missed diagnosis of stroke in the emergency department: a cross-sectional analysis of a large population-based sample

Racial, ethnic, and socioeconomic disparities in estimates of AHRQ patient safety indicators.

The effects of multiple chronic conditions on hospitalization costs and utilization for ambulatory care sensitive conditions in the United States: a nationally representative cross-sectional study

U.S. Spending For Mental Health And Substance Abuse Treatment, 1991-2001