A classification of hospital-acquired diagnoses for use with routine hospital data

Patient safety advocates have recently posed the question: “Is health care getting safer?”1 They conclude it is impossible to know, but in order to make progress toward the answer, health systems need to change focus “away from unsystematic voluntary reporting towards systematic measurement”. Their prescription is “a broad but manageable spectrum of indicators that are genuinely useful to the clinical teams that monitor quality and safety day to day”, using “local data that are relevant to clinical concerns . . . how a team is doing compared with last month and last year”.1

Most current approaches to systematic measurement of patient outcomes in hospital do not satisfy these criteria, instead relying on voluntary reporting, a relatively narrow range of diagnoses, or detailed, condition-specific profiles of comorbidities for risk adjustment (Box 1). To our knowledge, there has been only one attempt to use routinely recorded data on diagnosis codes to monitor the full range of hospital-acquired illness and injury — the Utah/Missouri Patient Safety Project16,17 (Box 1). This was limited by the need for expert clinical review to distinguish hospital-acquired diagnoses from comorbidities, eliminating many conditions that could also be community acquired.

Here, we describe the development of a tool to allow routinely coded inpatient data to be used to monitor a full range of hospital-acquired diagnoses (“complications”) to support quality improvement efforts by hospital-based clinical teams. This tool — the Classification of Hospital Acquired Diagnoses (CHADx) — was developed under the sponsorship of the Australian Commission on Safety and Quality in Health Care and builds on the Utah/Missouri project. To identify hospital-acquired diagnoses, it uses a “condition onset” flag that is now common in a number of jurisdictions18 and recorded in all Australian states. We termed these diagnoses “complications” in an attempt to find neutral terminology reflecting the lack of either risk adjustment or information on causation.

The classification is designed to provide a comprehensive overview of all complications as the basis for estimating total and relative per case expenditure by complication type.19 It is also intended to provide hospitals with a computerised tool to group the 4000 + valid diagnosis codes typically used with a hospital-acquired diagnosis-onset flag into a smaller set of clinically meaningful classes for routine monitoring of patient safety and safety improvement efforts.

We used 4345 unique codes to characterise hospital-acquired conditions; in the final CHADx these were grouped into 144 detailed subclasses and 17 major “roll-up” groups. These major groups can be routinely monitored by low-volume hospitals, and the subclasses by larger hospitals; the subclasses also support economic analysis.

The 17 major groups are shown by volume of diagnoses in 2005–06 in Box 3. CHADx 12 (labour and delivery) was the largest major group by volume (75 320 diagnoses), and CHADx 1 (postprocedural complications) was the largest by number of subclasses (23). Box 4 shows the top 20 CHADx subclasses by volume of diagnoses in 2005–06.

Five subclasses with particular relevance for efforts to improve patient safety were kept as separate CHADx categories despite their expected small numbers (< 100 cases in the sample of more than 2 million inpatient episodes). These were: 1.2 Gas embolism (3 cases); 3.4 Injury d/t assault (19); 1.6 Foreign body or substance left following procedure (46); 3.2 Falls with intracranial injury (67); and 2.17 Anaphylactic shock due to correct drug properly administered (88).

A complete list of the CHADx major groups and subclasses, along with the code sequences assigned to each category and the number of admissions from the 2005–06 VAED in each end class, is available on the website of the Australian Commission on Safety and Quality in Health Care (http://www.safetyandquality.gov.au/internet/safety/publishing.nsf/Content/PriorityProgram-08_CostHAD).

The CHADx is intended as a tool to help hospitals monitor rates of complications and the effect of patient safety interventions. In most Australian states, hospitals submit diagnosis abstracts on a monthly basis. Monthly use of the CHADx would allow hospitals to identify any changes associated with local patient safety strategies in near “real time”. Longitudinal measurement would provide information not available from methods that rely on periodic and costly intensive investigations, such as chart review. We also foresee its potential to help include cost in prioritising patient safety programs.

In contrast to performance indicators, the CHADx is not intended for external monitoring or holding hospitals to account. However, at a broad systems level, it might be useful for monitoring changes in rates of particular complication types. It does not employ risk adjustment, a technique that seeks to standardise the risk of adverse events in a patient population using information on severity or comorbidity. It avoids risk adjustment for two closely related reasons:

• the classification is not primarily intended to be comparative (a hospital’s casemix constitutes the context of its patient safety efforts, regardless of its risk profile); and

• risk adjustment may cultivate a therapeutic nihilism for a proportion of complications or particular patient groups (“old patients just get more complications”).

In reality, severity of illness and comorbidities do affect rates of complications. However, it is important as a tool for priority setting and for local efforts to improve patient safety to have the full picture across the patient population, regardless of the spectrum of risk and severity.

The number of end categories in the CHADx is designed according to the level of specificity required. The optimal granularity of the classification (and thus usefulness of the categories) will vary, depending on both hospital size and local depth of coding: fewer classes provide more robust cell sizes for monitoring, but may group unlike complications together. Detail has been highlighted as a critical feature of patient-event classifications.24 The tiered structure of the 17 major roll-up groups and 144 detailed and comprehensive subclasses is designed to suit a range of potential uses.

The development of any classification system using routine hospital data faces a number of challenges. The quality of both medical record entries and their abstraction varies both between institutions and between jurisdictions. This limits comparisons of data, at least until robust data audits are in place.

Current coding conventions may need to be reconsidered to better support use of routine morbidity data for patient safety. However, monitoring these routine data within institutions remains potentially useful for tracking change, even in the absence of the data audits that would support comparability between institutions. With appropriate quality control and external audits, hospitals may be able to identify peers (with a similar casemix) for comparison of rates of particular CHADx classes for particular procedures or patient groups. The specificity of most CHADx classes might also allow more standardised reporting of complications of care in clinical research.

Assignment of the condition-onset flag has not been audited, although the annual Victorian Department of Human Services inpatient data audit covered assignment of these flags for the first time in 2008.25 The usefulness of the source codes could be compromised if financial incentives were applied to hospitals reporting hospital-acquired illnesses and injuries in their data. For this reason, we argue against the use of the CHADx for public reporting or the application of financial incentives.

Research groups around the world are trialling ways to collect information on patient outcomes to inform efforts to reduce rates of hospital-acquired illness and injury. Routine data is underutilised in these efforts but has the advantage of being comprehensive, timely and available at no additional cost. Validity and reliability of these data will vary within and between health care systems, and only conditions specifically identified in the record can be coded. In Australia and elsewhere, diagnosis coding is subject to increasing scrutiny and formal evaluation.

Despite increased reporting of mortality rates and other measures of quality of care, individual hospitals have had few ways of systematically investigating rates and patterns of quality problems, focusing instead on incident investigations. The CHADx is designed to provide clinicians and hospitals with a computerised tool to group hospital-acquired diagnoses into smaller sets of clinically meaningful classes for routine monitoring of patient safety. It is premised on a “just culture” approach to improving patient safety (which recognises that competent professionals make mistakes, but has zero tolerance for reckless behaviour26), and also due attention to the organisational contexts in which clinicians work. It requires well documented medical charts and investment in training and supervision of coding staff, but does not rely on special-purpose collection of data. It supports local monitoring of complication rates over time, to focus efforts to improve patient outcomes by minimising their incidence. These complications may not be preventable in every patient but are amenable to systematic efforts to reduce their rates. The CHADx can also be used as the basis for setting priorities through supporting the estimation of relative per-case and total expenditure attributable to each CHADx class.

2 Logic for code assignment in the Classification of Hospital Acquired Diagnoses (CHADx)

C prefix = complications flag. M CHADx = major CHADx group. MRSA = methicillin-resistant Staphylococcus aureus.