Assessment of extreme heat and hospitalizations to inform early warning systems.

Heat early warning systems and action plans use temperature thresholds to trigger warnings and risk communication. In this study, we conduct multistate analyses, exploring associations between heat and all-cause and cause-specific hospitalizations, to inform the design and development of heat-health early warning systems. We used a two-stage analysis to estimate heat-health risk relationships between heat index and hospitalizations in 1,617 counties in the United States for 2003-2012. The first stage involved a county-level time series quasi-Poisson regression, using a distributed lag nonlinear model, to estimate heat-health associations. The second stage involved a multivariate random-effects meta-analysis to pool county-specific exposure-response associations across larger geographic scales, such as by state or climate region. Using results from this two-stage analysis, we identified heat index ranges that correspond with significant heat-attributable burden. We then compared those with the National Oceanic and Atmospheric Administration National Weather Service (NWS) heat alert criteria used during the same time period. Associations between heat index and cause-specific hospitalizations vary widely by geography and health outcome. Heat-attributable burden starts to occur at moderately hot heat index values, which in some regions are below the alert ranges used by the NWS during the study time period. Locally specific health evidence can beneficially inform and calibrate heat alert criteria. A synchronization of health findings with traditional weather forecasting efforts could be critical in the development of effective heat-health early warning systems.

Association Between Outdoor Air Pollution Levels and Inpatient Outcomes in Pediatric Pneumonia Hospitalizations, 2007 to 2008.

OBJECTIVE: Pneumonia is a leading cause of pediatric admissions. Although air pollutants are associated with poor outcomes, few national studies have examined associations between pollutant levels and inpatient pediatric pneumonia outcomes. We examined the relationship between ozone (O3) and fine particulate matter with a diameter ≤2.5 µm (PM2.5) and outcomes related to disease severity. METHODS: In this cross-sectional study, we obtained discharge data from the 2007 to 2008 Nationwide Inpatient Sample and pollution data from the Air Quality System. Patients ≤18years with a principal diagnosis of pneumonia were included. Discharge data were linked to O3 and PM2.5 levels (predictors) from the patient's ZIP Code (not publicly available) from day of admission. Outcomes were mortality, intubation, length of stay (LOS), and total costs. We calculated weighted national estimates and performed multivariable analyses adjusting for sociodemographic and hospital factors. RESULTS: There were a total of 57,972 (278,871 weighted) subjects. Median PM2.5 level was 9.5 (interquartile range [IQR] 6.8-13.4) µg/m3. Median O3 level was 35.6 (IQR 28.2-45.2) parts per billion. Mortality was 0.1%; 0.75% of patients were intubated. Median LOS was 2 (IQR 2-4) days. Median costs were $3089 (IQR $2023-$5177). Greater levels of PM2.5 and O3 were associated with mortality, longer LOS, and greater costs. Greater O3 levels were associated with increased odds of intubation. CONCLUSIONS: Greater levels of O3 and PM2.5 were associated with more severe presentations of pneumonia. Future work should examine these relationships in more recent years and over a longer time period.

Trends in Opioid-related Inpatient Stays Shifted After the US Transitioned to ICD-10-CM Diagnosis Coding in 2015.

BACKGROUND: Trend analyses of opioid-related inpatient stays depend on the availability of comparable data over time. In October 2015, the US transitioned diagnosis coding from International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) to ICD-10-CM, increasing from ∼14,000 to 68,000 codes. This study examines how trend analyses of inpatient stays involving opioid diagnoses were affected by the transition to ICD-10-CM. SUBJECTS: Data are from Healthcare Cost and Utilization Project State Inpatient Databases for 14 states in 2015-2016, representing 26% of acute care inpatient discharges in the US. STUDY DESIGN: We examined changes in the number of opioid-related stays before, during, and after the transition to ICD-10-CM using quarterly ICD-9-CM data from 2015 and quarterly ICD-10-CM data from the fourth quarter of 2015 and the first 3 quarters of 2016. RESULTS: Overall, stays involving any opioid-related diagnosis increased by 14.1% during the ICD transition-which was preceded by a much lower 5.0% average quarterly increase before the transition and followed by a 3.5% average increase after the transition. In stratified analysis, stays involving adverse effects of opioids in therapeutic use showed the largest increase (63.2%) during the transition, whereas stays involving abuse and poisoning diagnoses decreased by 21.1% and 12.4%, respectively. CONCLUSIONS: The sharp increase in opioid-related stays overall during the transition to ICD-10-CM may indicate that the new classification system is capturing stays that were missed by ICD-9-CM data. Estimates of stays involving other diagnoses may also be affected, and analysts should assess potential discontinuities in trends across the ICD transition.

Identifying Increased Risk of Readmission and In-hospital Mortality Using Hospital Administrative Data: The AHRQ Elixhauser Comorbidity Index.

OBJECTIVE: We extend the literature on comorbidity measurement by developing 2 indices, based on the Elixhauser Comorbidity measures, designed to predict 2 frequently reported health outcomes: in-hospital mortality and 30-day readmission in administrative data. The Elixhauser measures are commonly used in research as an adjustment factor to control for severity of illness. DATA SOURCES: We used a large analysis file built from all-payer hospital administrative data in the Healthcare Cost and Utilization Project State Inpatient Databases from 18 states in 2011 and 2012. METHODS: The final models were derived with bootstrapped replications of backward stepwise logistic regressions on each outcome. Odds ratios and index weights were generated for each Elixhauser comorbidity to create a single index score per record for mortality and readmissions. Model validation was conducted with c-statistics. RESULTS: Our index scores performed as well as using all 29 Elixhauser comorbidity variables separately. The c-statistic for our index scores without inclusion of other covariates was 0.777 (95% confidence interval, 0.776-0.778) for the mortality index and 0.634 (95% confidence interval, 0.633-0.634) for the readmissions index. The indices were stable across multiple subsamples defined by demographic characteristics or clinical condition. The addition of other commonly used covariates (age, sex, expected payer) improved discrimination modestly. CONCLUSIONS: These indices are effective methods to incorporate the influence of comorbid conditions in models designed to assess the risk of in-hospital mortality and readmission using administrative data with limited clinical information, especially when small samples sizes are an issue.

Association Between the Opening of Retail Clinics and Low-Acuity Emergency Department Visits.

STUDY OBJECTIVE: We assess whether the opening of retail clinics near emergency departments (ED) is associated with decreased ED utilization for low-acuity conditions. METHODS: We used data from the Healthcare Cost and Utilization Project State Emergency Department Databases for 2,053 EDs in 23 states from 2007 to 2012. We used Poisson regression models to examine the association between retail clinic penetration and the rate of ED visits for 11 low-acuity conditions. Retail clinic "penetration" was measured as the percentage of the ED catchment area that overlapped with the 10-minute drive radius of a retail clinic. Rate ratios were calculated for a 10-percentage-point increase in retail clinic penetration per quarter. During the course of a year, this represents the effect of an increase in retail clinic penetration rate from 0% to 40%, which was approximately the average penetration rate observed in 2012. RESULTS: Among all patients, retail clinic penetration was not associated with a reduced rate of low-acuity ED visits (rate ratio=0.999; 95% confidence interval=0.997 to 1.000). Among patients with private insurance, there was a slight decrease in low-acuity ED visits (rate ratio=0.997; 95% confidence interval=0.994 to 0.999). For the average ED in a given quarter, this would equal a 0.3% reduction (95% confidence interval 0.1% to 0.6%) in low-acuity ED visits among the privately insured if retail clinic penetration rate increased by 10 percentage points per quarter. CONCLUSION: With increased patient demand resulting from the expansion of health insurance coverage, retail clinics may emerge as an important care location, but to date, they have not been associated with a meaningful reduction in low-acuity ED visits.

Identifying in-patient costs attributable to the clinical sequelae and comorbidities of alcoholic liver disease in a national hospital database.

BACKGROUND AND AIMS: The clinical sequelae and comorbidities of alcoholic liver disease (ALD) often require hospitalization. The aims of this study were to (1) compare the average costs of hospitalizations with ALD and the costs of hospitalizations with other alcohol-related diagnoses that do not involve the liver; and (2) estimate the percentage of the difference in costs between the ALD and non-ALD hospitalizations that may be attributed to ascites, protein-calorie malnutrition and other conditions. DESIGN: The 2012 National Inpatient Sample is a population-based cross-sectional database representing more than 94% of all discharges from community hospitals in the United States. SETTING: Community hospitals in the United States. PARTICIPANTS: The sample included 72 531 hospitalizations with ALD and 287 047 hospitalizations with other alcohol-related diagnoses. MEASUREMENTS: The dependent variable was total in-patient costs. We estimated the contribution of ascites, protein-calorie malnutrition and other conditions to the difference in costs between patients with ALD and patients with other diagnoses. FINDINGS: Average costs for ALD patients were $3188.4 higher than those for patients with other diagnoses ($13 543 versus $10 355; P < 0.001). Among all conditions in the analysis, protein-calorie malnutrition had the largest impact on costs [$6501; 95% confidence interval (CI) = 5956, 7045; P < 0.001] accounting for 12% of the higher costs of ALD stays. CONCLUSIONS: Costs of hospital care for patients with alcoholic liver disease are higher than those for patients with other alcohol-related diagnoses. These increased costs are associated with specific clinical sequelae and comorbidities, with protein-calorie malnutrition-a largely preventable condition-making a substantial contribution.

Trends in prevalence of diabetes among delivery hospitalizations, United States, 1993-2009.

To describe recent trends in prevalence of pre-existing diabetes mellitus (PDM) (i.e., type 1 or type 2 diabetes) and gestational diabetes mellitus (GDM) among delivery hospitalizations in the United States. Data on delivery hospitalizations from 1993 through 2009 were obtained from the Health Care Cost and Utilization Project (HCUP) Nationwide Inpatient Sample. Diagnosis-Related Group codes were used to identify deliveries and diagnosis codes on presence of diabetes. Rates of hospitalizations with diabetes were calculated per 100 deliveries by type of diabetes, hospital geographic region, patient's age, degree of urbanicity of patient's residence, categorized median household income for patient's ZIP Code, expected primary payer, and type of delivery. From 1993 to 2009, age-standardized prevalence of diabetes per 100 deliveries increased from 0.62 to 0.90 for PDM (trend p < 0.001) and from 3.09 to 5.57 for GDM (trend p < 0.001). In 2009, correlates of PDM at delivery included older age [40-44 vs. 15-24: odds ratio 6.45 (95 % CI 5.27-7.88)], Medicaid/Medicare versus private payment sources [1.77 (95 % CI 1.59-1.98)], patient's ZIP Code with a median household income in bottom quartile versus other quartiles [1.54 (95 % CI 1.41, 1.69)], and C-section versus vaginal delivery [3.36 (95 % CI 3.10-3.64)]. Correlates of GDM at delivery were similar. Among U.S. delivery hospitalizations, the prevalence of diabetes is increasing. In 2009, the prevalence of diabetes was higher among women in older age groups, living in ZIP codes with lower household incomes, or with public insurance.

Relationship between community prevalence of obesity and associated behavioral factors and community rates of influenza-related hospitalizations in the United States.

BACKGROUND: Findings from studies examining the association between obesity and acute respiratory infection are inconsistent. Few studies have assessed the relationship between obesity-related behavioral factors, such as diet and exercise, and risk of acute respiratory infection. OBJECTIVE: To determine whether community prevalence of obesity, low fruit/vegetable consumption, and physical inactivity are associated with influenza-related hospitalization rates. METHODS: Using data from 274 US counties, from 2002 to 2008, we regressed county influenza-related hospitalization rates on county prevalence of obesity (BMI ≥ 30), low fruit/vegetable consumption (<5 servings/day), and physical inactivity (<30 minutes/month recreational exercise), while adjusting for community-level confounders such as insurance coverage and the number of primary care physicians per 100,000 population. RESULTS: A 5% increase in obesity prevalence was associated with a 12% increase in influenza-related hospitalization rates [adjusted rate ratio (ARR) 1.12, 95% confidence interval (CI) 1.07, 1.17]. Similarly, a 5% increase in the prevalence of low fruit/vegetable consumption and physical inactivity was associated with an increase of 12% (ARR 1.12, 95% CI 1.08, 1.17) and 11% (ARR 1.11, 95% CI 1.07, 1.16), respectively. When all three variables were included in the same model, a 5% increase in prevalence of obesity, low fruit/vegetable consumption, and physical inactivity was associated with 6%, 8%, and 7% increases in influenza-related hospitalization rates, respectively. CONCLUSIONS: Communities with a greater prevalence of obesity were more likely to have high influenza-related hospitalization rates. Similarly, less physically active populations, with lower fruit/vegetable consumption, tended to have higher influenza-related hospitalization rates, even after accounting for obesity.

Variation in prevalence of gestational diabetes mellitus among hospital discharges for obstetric delivery across 23 states in the United States.

OBJECTIVE: To examine variability in diagnosed gestational diabetes mellitus (GDM) prevalence at delivery by race/ethnicity and state. RESEARCH DESIGN AND METHODS: We used data from the Healthcare Cost and Utilization Project State Inpatient Databases for 23 states of the United States with available race/ethnicity data for 2008 to examine age-adjusted and race-adjusted rates of GDM by state. We used multilevel analysis to examine factors that explain the variability in GDM between states. RESULTS: Age-adjusted and race-adjusted GDM rates (per 100 deliveries) varied widely between states, ranging from 3.47 in Utah to 7.15 in Rhode Island. Eighty-six percent of the variability in GDM between states was explained as follows: 14.7% by age; 11.8% by race/ethnicity; 5.9% by insurance; and 2.9% by interaction between race/ethnicity and insurance at the individual level; 17.6% by hospital level factors; 27.4% by the proportion of obese women in the state; 4.3% by the proportion of Hispanic women aged 15-44 years in the state; and 1.5% by the proportion of white non-Hispanic women aged 15-44 years in the state. CONCLUSIONS: Our results suggest that GDM rates differ by state, with this variation attributable to differences in obesity at the population level (or "at the state level"), age, race/ethnicity, hospital, and insurance.

Hospital burden of unintentional carbon monoxide poisoning in the United States, 2007.

BACKGROUND: Unintentional, non-fire-related (UNFR) carbon monoxide (CO) poisoning is a leading cause of poisoning in the United States, but the overall hospital burden is unknown. This study presents patient characteristics and the most recent comprehensive national estimates of UNFR CO-related emergency department (ED) visits and hospitalizations. METHODS: Data from the 2007 Nationwide Inpatient and Emergency Department Sample of the Hospitalization Cost and Utilization Project were analyzed. The Council of State and Territorial Epidemiologists' CO poisoning case definition was used to classify confirmed, probable, and suspected cases. RESULTS: In 2007, more than 230,000 ED visits (772 visits/million) and more than 22,000 hospitalizations (75 stays/million) were related to UNFR CO poisoning. Of these, 21,304 ED visits (71 visits/million) and 2302 hospitalizations (8 stays/million) were confirmed cases of UNFR CO poisoning. Among the confirmed cases, the highest ED visit rates were among persons aged 0 to 17 years (76 visits/million) and 18 to 44 years (87 visits/million); the highest hospitalization rate was among persons aged 85 years or older (18 stays/million). Women visited EDs more frequently than men, but men were more likely to be hospitalized. Patients residing in a nonmetropolitan area and in the northeast and midwest regions of the country had higher ED visit and hospitalization rates. Carbon monoxide exposures occurred mostly (>60%) at home. The hospitalization cost for confirmed CO poisonings was more than $26 million. CONCLUSION: Unintentional, non-fire-related CO poisonings pose significant economic and health burden; continuous monitoring and surveillance of CO poisoning are needed to guide prevention efforts. Public health programs should emphasize CO alarm use at home as the main prevention strategy.

Children's hospitalizations with a mood disorder diagnosis in general hospitals in the united states 2000-2006.

BACKGROUND: Mood disorders including depression and bipolar disorders are a major cause of morbidity in childhood and adolescence, and hospitalizations for mood disorders are the leading diagnosis for all hospitalizations in general hospitals for children age 13 to 17. We describe characteristics of these hospitalizations in the U.S. focusing on duration of stay, charges, and geographic variation. METHODS: The Kids' Inpatient Database was analyzed to calculate hospitalization rates for 2000, 2003, and 2006. For each year, information was available for over 2 million hospitalizations, representing 6.3 to 6.5 million hospital stays annually in acute care, non-psychiatric hospitals. RESULTS: The rate of pediatric hospitalizations with a principal diagnosis of a mood disorder was 12.4/10,000 in 2000, 13.0 in 2003, and 12.1 in 2006. In the same period, the incidence of hospitalizations for depressive disorders decreased from 9.1 to 6.4/10,000 children while the incidence of hospitalizations for bipolar disorders increased from 3.3 to 5.7/10,000 children. The mean length of stay increased from 7.1 to 7.7 days, while inflation-adjusted hospital charges increased from $10,600 in 2000, to $13,700 in 2003, to $16,300 in 2006. The proportion of mood disorder stays paid by government increased from 35.3% to 45.2%. The Western region experienced the lowest rates (9.9/10,000, 11.6 and 10.2 in 2000, 2003 and 2006) while the Midwest had the highest rates (26.4, 27.6, and 25.4). CONCLUSIONS: Mood disorders are a major reason for hospitalization during development, especially in adolescence. Mood disorder hospitalizations remained relatively constant from 2000-2006, but diagnoses of depressive disorders decreased while diagnoses of bipolar disorders increased. Hospitalization rates vary widely by region of the country.

Profile of inpatient operating room procedures in US hospitals in 2007.

OBJECTIVE: To provide an overview of inpatient operating room (OR) procedures in the United States. DESIGN, SETTING, AND PATIENTS: Healthcare Cost and Utilization Project 2007 Nationwide Inpatient Sample discharge data from a sample of US short-term, acute-care, nonfederal hospitals. MAIN OUTCOME MEASURES: National volume of OR procedures overall and by type of procedure, resource use and costs, most frequent and expensive procedures, and trends. RESULTS: Fifteen million OR procedures were performed in 2007 (495 procedures/10 000 population). Only 26.4% of hospitalizations involved an OR procedure; however, OR-related stays were responsible for 46.8% of hospital costs ($161 billion). Patients aged 65 years and older were 2 to 3 times more likely to experience OR procedures (eg, 1327 procedures/10 000 persons among those aged 65-84 years vs 626 procedures/10 000 persons for those aged 45-64 years). Compared with non-OR inpatients, OR patients were less severely ill (20.5% had the highest severity of illness vs 24.6% for non-OR patients) and used more resources ($2900/day for OR patients vs $1400/day for non-OR patients). The 15 most expensive procedures accounted for half of all procedure-related hospitalization costs and one-fourth of total hospital costs. Volumes for 4 of the most expensive procedures increased between 1997 and 2007: 20% for percutaneous transluminal coronary angioplasty, 46% for cesarean delivery, 46% for knee replacement, and 45% for spinal fusion. The volume of percutaneous transluminal coronary angioplasty declined 20% from 2006 to 2007, compared with a 56% increase in the prior decade. CONCLUSIONS: Procedures in the OR represent a large portion of hospital costs, and these costs are concentrated in few procedure types.

Testing the association between patient safety indicators and hospital structural characteristics in VA and nonfederal hospitals.

This study tested the association between hospital structural characteristics-teaching status, bedsize, and nurse staffing-and potentially preventable adverse events. The authors calculated 14 Agency for Healthcare Research and Quality Patient Safety Indicators (PSIs) and a PSI composite, using discharge databases from VA and nonfederal hospitals. This study compared the likelihood of PSI events in hospitals, controlling for structural and other characteristics, including patients' case-mix. Additional controls were employed to account for differences in VA versus nonfederal patients and data. The study found some associations, most notably a positive (unfavorable) association between status as a major teaching hospital and six PSIs. However, for most PSIs, the authors found no association between the structural characteristics tested and likelihood of PSI events. The study's findings extend previous research showing a lack of consistent relationship between structural characteristics and patient safety. However, the results also suggest continued need for examination of the relationship between teaching status and potentially preventable adverse events.

Sensitivity of household reported medical conditions in the medical expenditure panel survey.

INTRODUCTION: Accurate survey data on medical conditions are critical for health care researchers. Although medical condition data are complex and are subject to reporting error, little information exists on the quality of household reported condition data. METHODS: We used pooled data from 4 years (2002-2005) of the Medical Expenditure Panel Survey (MEPS) to estimate the extent to which household respondents may underreport 23 types of medical conditions. The medical expenditure panel survey is a nationally representative annual survey of approximately 15,000 households which collects medical condition information in 2 separate components-the Household Component (HC) and the Medical Provider Component (MPC). We computed sensitivity rates based on linked HC and MPC data under the assumption that if collection of medical conditions from household respondents was complete, then the conditions reported in the MPC would also be reported in the HC. RESULTS: Sensitivity rates ranged from a high of 93.8% to a low of 37.4% and were 75% or higher for 10 of the 23 conditions analyzed. The overall sensitivity rate for the 23 conditions combined was 74%. CONCLUSIONS: Household reports tended to be more accurate for conditions that are highly salient, cause pain, require hospitalization, require ongoing treatment, have specific recognizable treatment, alter lifestyle, and/or affect daily life (eg, pregnancy, diabetes, and kidney stones). In addition, reporting generally was better when conditions are classified in broader categories rather than in more detail.

Identification of hospital-acquired catheter-associated urinary tract infections from Medicare claims: sensitivity and positive predictive value.

BACKGROUND AND OBJECTIVE: Hospital-acquired catheter-associated urinary tract infection (CAUTI) is one of the first 6 conditions Medicare is targeting to reduce payment associated with hospital-acquired conditions under Congressional mandate. This study was to determine the positive predictive value (PPV) and sensitivity in identifying patients in Medicare claims who had urinary catheterization and who had hospital-acquired CAUTIs. RESEARCH DESIGN: CAUTIs identified by ICD-9-CM codes in Medicare claims were compared with those revealed by medical record abstraction in random samples of Medicare discharges in 2005 to 2006. Hospital discharge abstracts (2005) from the states of New York and California were used to estimate the potential impact of a present-on-admission (POA) indicator on PPV. RESULTS: ICD-9-CM procedure codes for urinary catheterization appeared in only 1.4% of Medicare claims for patients who had urinary catheters. As a proxy, claims with major surgery had a PPV of 75% and sensitivity of 48%, and claims with any surgical procedure had a PPV of 53% and sensitivity of 79% in identifying urinary catheterization. The PPV and sensitivity for identifying hospital-acquired CAUTIs varied, with the PPV at 30% and sensitivity at 65% in claims with major surgery. About 80% of the secondary diagnosis codes indicating UTIs were flagged as POA, suggesting that the addition of POA indicators in Medicare claims would increase PPV up to 86% and sensitivity up to 79% in identifying hospital-acquired CAUTIs. CONCLUSIONS: The validity in identifying urinary catheter use and CAUTIs from Medicare claims is limited, but will be increased substantially upon addition of a POA indicator.

Modifying ICD-9-CM coding of secondary diagnoses to improve risk-adjustment of inpatient mortality rates.

OBJECTIVE: To assess the effect on risk-adjustment of inpatient mortality rates of progressively enhancing administrative claims data with clinical data that are increasingly expensive to obtain. Data Sources. Claims and abstracted clinical data on patients hospitalized for 5 medical conditions and 3 surgical procedures at 188 Pennsylvania hospitals from July 2000 through June 2003. METHODS: Risk-adjustment models for inpatient mortality were derived using claims data with secondary diagnoses limited to conditions unlikely to be hospital-acquired complications. Models were enhanced with one or more of 1) secondary diagnoses inferred from clinical data to have been present-on-admission (POA), 2) secondary diagnoses not coded on claims but documented in medical records as POA, 3) numerical laboratory results from the first hospital day, and 4) all available clinical data from the first hospital day. Alternative models were compared using c-statistics, the magnitude of errors in prediction for individual cases, and the percentage of hospitals with aggregate errors in prediction exceeding specified thresholds. RESULTS: More complete coding of a few under-reported secondary diagnoses and adding numerical laboratory results to claims data substantially improved predictions of inpatient mortality. Little improvement resulted from increasing the maximum number of available secondary diagnoses or adding additional clinical data. CONCLUSIONS: Increasing the completeness and consistency of reporting a few secondary diagnosis codes for findings POA and merging claims data with numerical laboratory values improved risk adjustment of inpatient mortality rates. Expensive abstraction of additional clinical information from medical records resulted in little further improvement.

How often are potential patient safety events present on admission?

BACKGROUND: Data fields that capture whether diagnoses are present on admission (POA)--distinguishing comorbidities from potential in-hospital complications--became part of the Uniform Bill for hospital claims in 2007. The AHRQ Patient Safety Indicators (PSIs) were initially developed as measures of potential patient safety problems that use routine administrative data without POA information. The impact of adding POA information to PSIs was examined. METHODS: Data were used from California (CA) and New York (NY) Healthcare Cost and Utilization Project (HCUP) state inpatient databases for 2003, which include POA codes. Analysis was limited to 13 of 20 PSIs for which POA information was relevant, such as complications of anesthesia, accidental puncture, and sepsis. RESULTS: In New York, 17% of cases revealed suspect POA coding, compared with 1%-2% in California. After suspect records were excluded, 92%-93% of secondary diagnoses in both CA and NY were POA. After incorporating POA information, most cases of decubitus ulcer (86%-89%), postoperative hip fracture (74%-79%), and postoperative pulmonary embolism/deep vein thrombosis (54%-58%) were no longer considered in-hospital patient safety events. DISCUSSION: Three of 13 PSIs appear not to be valid measures of in-hospital patient safety events, but the remaining 10 appear to be potentially useful measures even in the absence of POA codes.

Using patient safety indicators to estimate the impact of potential adverse events on outcomes.

The authors estimated the impact of potentially preventable patient safety events, identified by Agency for Healthcare Research and Quality (AHRQ) Patient Safety Indicators (PSIs), on patient outcomes: mortality, length of stay (LOS), and cost. The PSIs were applied to all acute inpatient hospitalizations at Veterans Health Administration (VA) facilities in fiscal 2001. Two methods-regression analysis and multivariable case matching- were used independently to control for patient and facility characteristics while predicting the effect of the PSI on each outcome. The authors found statistically significant (p < .0001) excess mortality, LOS, and cost in all groups with PSIs. The magnitude of the excess varied considerably across the PSIs. These VA findings are similar to those from a previously published study of nonfederal hospitals, despite differences between VA and non-VA systems. This study contributes to the literature measuring outcomes of medical errors and provides evidence that AHRQ PSIs may be useful indicators for comparison across delivery systems.