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The prevalence of potentially preventable deaths in an acute care hospital: A retrospective cohort.

ABSTRACT: Studies estimate that 6% to 27% of deaths in hospitals might be prevented with higher quality care. These estimates may be inaccurate because they fail to account for the uncertainty associated with classifying preventability. The purpose of this study was to measure the prevalence of preventable deaths, accounting for the uncertainty in preventability ratings.We created standardized structured case abstracts for all deaths at a multisite academic teaching hospital over a 3-month period. Each case abstract was evaluated independently by 4 reviewers who rated death preventability on a 100-point scale ranging from 0 ("Definitely not preventable") to 100 ("Definitely preventable"). Ratings were categorized into a 4-level ordinal scale and latent class analysis was used to measure the prevalence of each preventability class and estimate the probability that deaths in each class were preventable.There were 480 deaths (3.4% of all admissions) during the study period. The latent class model (LCM) found that 91.6% (95% CI: 88.4-94.8%) of deaths were "nonpreventable" and 8.4% (5.2-11.6%) were "possibly preventable." "Possibly preventable" deaths could be identified with 90% certainty, but due to error in reviewer ratings, a "possibly preventable" death had a 50% probability of being receiving a rating of less than 25/100 by any single reviewer. Only 5 of 31 deaths classified as a "possibly preventable" (1.0% of all deaths) were judged to likely be alive in 3 months with perfect care.After accounting for uncertainty associated with rating the preventability of hospital deaths, we found that 8.4% of deaths were deemed possibly preventable. There was only moderate probability that these deaths were truly preventable.

SUBMITTER: Kobewka DM

PROVIDER: S-EPMC5569428 | biostudies-literature | 2017 Feb

REPOSITORIES: biostudies-literature

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The prevalence of potentially preventable deaths in an acute care hospital: A retrospective cohort.

Kobewka Daniel M DM van Walraven Carl C Taljaard Monica M Ronksley Paul P Forster Alan J AJ

Medicine 20170201 8

Studies estimate that 6% to 27% of deaths in hospitals might be prevented with higher quality care. These estimates may be inaccurate because they fail to account for the uncertainty associated with classifying preventability. The purpose of this study was to measure the prevalence of preventable deaths, accounting for the uncertainty in preventability ratings.We created standardized structured case abstracts for all deaths at a multisite academic teaching hospital over a 3-month period. Each ca ...[more]

PMID: 28225500

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Project description:BackgroundPatients with multimorbidities have the greatest healthcare needs and generate the highest expenditure in the health system. There is an increasing focus on identifying specific disease combinations for addressing poor outcomes. Existing research has identified a small number of prevalent "clusters" in the general population, but the limited number examined might oversimplify the problem and these may not be the ones associated with important outcomes. Combinations with the highest (potentially preventable) secondary care costs may reveal priority targets for intervention or prevention. We aimed to examine the potential of defining multimorbidity clusters for impacting secondary care costs.Methods and findingsWe used national, Hospital Episode Statistics, data from all hospital admissions in England from 2017/2018 (cohort of over 8 million patients) and defined multimorbidity based on ICD-10 codes for 28 chronic conditions (we backfilled conditions from 2009/2010 to address potential undercoding). We identified the combinations of multimorbidity which contributed to the highest total current and previous 5-year costs of secondary care and costs of potentially preventable emergency hospital admissions in aggregate and per patient. We examined the distribution of costs across unique disease combinations to test the potential of the cluster approach for targeting interventions at high costs. We then estimated the overlap between the unique combinations to test potential of the cluster approach for targeting prevention of accumulated disease. We examined variability in the ranks and distributions across age (over/under 65) and deprivation (area level, deciles) subgroups and sensitivity to considering a smaller number of diseases. There were 8,440,133 unique patients in our sample, over 4 million (53.1%) were female, and over 3 million (37.7%) were aged over 65 years. No clear "high cost" combinations of multimorbidity emerged as possible targets for intervention. Over 2 million (31.6%) patients had 63,124 unique combinations of multimorbidity, each contributing a small fraction (maximum 3.2%) to current-year or 5-year secondary care costs. Highest total cost combinations tended to have fewer conditions (dyads/triads, most including hypertension) affecting a relatively large population. This contrasted with the combinations that generated the highest cost for individual patients, which were complex sets of many (6+) conditions affecting fewer persons. However, all combinations containing chronic kidney disease and hypertension, or diabetes and hypertension, made up a significant proportion of total secondary care costs, and all combinations containing chronic heart failure, chronic kidney disease, and hypertension had the highest proportion of preventable emergency admission costs, which might offer priority targets for prevention of disease accumulation. The results varied little between age and deprivation subgroups and sensitivity analyses. Key limitations include availability of data only from hospitals and reliance on hospital coding of health conditions.ConclusionsOur findings indicate that there are no clear multimorbidity combinations for a cluster-targeted intervention approach to reduce secondary care costs. The role of risk-stratification and focus on individual high-cost patients with interventions is particularly questionable for this aim. However, if aetiology is favourable for preventing further disease, the cluster approach might be useful for targeting disease prevention efforts with potential for cost-savings in secondary care.

Project description:ObjectiveAcute respiratory distress syndrome is a common complication of critical illness, with high mortality and limited treatment options. Preliminary studies suggest that potentially preventable hospital exposures contribute to acute respiratory distress syndrome development. We aimed to determine the association between specific hospital exposures and the rate of acute respiratory distress syndrome development among at-risk patients.DesignPopulation-based, nested, Matched case-control study.PatientsConsecutive adults who developed acute respiratory distress syndrome from January 2001 through December 2010 during their hospital stay (cases) were matched to similar-risk patients without acute respiratory distress syndrome (controls). They were matched for 6 baseline characteristics.InterventionsNone.Measurements and main resultsTrained investigators blinded to outcome of interest reviewed medical records for evidence of specific exposures, including medical and surgical adverse events, inadequate empirical antimicrobial treatment, hospital-acquired aspiration, injurious mechanical ventilation, transfusion, and fluid and medication administration. Conditional logistic regression was used to calculate the risk associated with individual exposures. During the 10-year period, 414 patients with hospital-acquired acute respiratory distress syndrome were identified and matched to 414 at-risk, acute respiratory distress syndrome-free controls. Adverse events were highly associated with acute respiratory distress syndrome development (odds ratio, 6.2; 95% CI, 4.0-9.7), as were inadequate antimicrobial therapy, mechanical ventilation with injurious tidal volumes, hospital-acquired aspiration, and volume of blood products transfused and fluids administered. Exposure to antiplatelet agents during the at-risk period was associated with a decreased risk of acute respiratory distress syndrome. Rate of adverse hospital exposures and prevalence of acute respiratory distress syndrome decreased during the study period.ConclusionsPrevention of adverse hospital exposures in at-risk patients may limit the development of acute respiratory distress syndrome.

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The prevalence of potentially preventable deaths in an acute care hospital: A retrospective cohort.

Publications

The prevalence of potentially preventable deaths in an acute care hospital: A retrospective cohort.

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