Quality of Health Care for Children in Australia, 2012-2013.

Importance: The quality of routine care for children is rarely assessed, and then usually in single settings or for single clinical conditions. Objective: To estimate the quality of health care for children in Australia in inpatient and ambulatory health care settings. Design, Setting, and Participants: Multistage stratified sample with medical record review to assess adherence with quality indicators extracted from clinical practice guidelines for 17 common, high-burden clinical conditions (noncommunicable [n = 5], mental health [n = 4], acute infection [n = 7], and injury [n = 1]), such as asthma, attention-deficit/hyperactivity disorder, tonsillitis, and head injury. For these 17 conditions, 479 quality indicators were identified, with the number varying by condition, ranging from 9 for eczema to 54 for head injury. Four hundred medical records were targeted for sampling for each of 15 conditions while 267 records were targeted for anxiety and 133 for depression. Within each selected medical record, all visits for the 17 targeted conditions were identified, and separate quality assessments made for each. Care was evaluated for 6689 children 15 years of age and younger who had 15 240 visits to emergency departments, for inpatient admissions, or to pediatricians and general practitioners in selected urban and rural locations in 3 Australian states. These visits generated 160 202 quality indicator assessments. Exposures: Quality indicators were identified through a systematic search of local and international guidelines. Individual indicators were extracted from guidelines and assessed using a 2-stage Delphi process. Main Outcomes and Measures: Quality of care for each clinical condition and overall. Results: Of 6689 children with surveyed medical records, 53.6% were aged 0 to 4 years and 55.5% were male. Adherence to quality of care indicators was estimated at 59.8% (95% CI, 57.5%-62.0%; n = 160 202) across the 17 conditions, ranging from a high of 88.8% (95% CI, 83.0%-93.1%; n = 2638) for autism to a low of 43.5% (95% CI, 36.8%-50.4%; n = 2354) for tonsillitis. The mean adherence by condition category was estimated as 60.5% (95% CI, 57.2%-63.8%; n = 41 265) for noncommunicable conditions (range, 52.8%-75.8%); 82.4% (95% CI, 79.0%-85.5%; n = 14 622) for mental health conditions (range, 71.5%-88.8%); 56.3% (95% CI, 53.2%-59.4%; n = 94 037) for acute infections (range, 43.5%-69.8%); and 78.3% (95% CI, 75.1%-81.2%; n = 10 278) for injury. Conclusions and Relevance: Among a sample of children receiving care in Australia in 2012-2013, the overall prevalence of adherence to quality of care indicators for important conditions was not high. For many of these conditions, the quality of care may be inadequate.

Patient safety -- a balanced measurement framework.

Evidence of the unacceptably high incidence of patient harm associated with health care has resulted in patient safety becoming a major reform agenda. Despite significant investment by governments on strategies to reduce patient harm, confusion still exists on how to measure patient safety. While the goal of patient safety is harm prevention, most of the measurement focus has been on counting incident reports. The (ab)use of reported incident data to measure both technical safety performance (injury rates) and evaluate the effectiveness of safety improvement initiatives continues to confuse and mislead consumers, funders and providers of health care. This paper proposes a simple measurement framework for patient safety which balances the elements of: learning, action, performance, patient experience, and staff attitudes and behaviour. Application of this framework to current priority areas should be used as a basis for patient safety improvement at clinical unit, hospital, state and national levels.

CareTrack Kids-part 2. Assessing the appropriateness of the healthcare delivered to Australian children: study protocol for a retrospective medical record review.

INTRODUCTION: Australian and international clinical practice guidelines are available for common paediatric conditions. Yet there is evidence that there are substantial variations between the guidelines, recommendations (appropriate care) and the care delivered. This paper describes a study protocol to determine the appropriateness of the healthcare delivered to Australian children for 16 common paediatric conditions in acute and primary healthcare settings. METHODS AND ANALYSIS: A random sample of 6000-8000 medical records representing a cross-section of the Australian paediatric population will be reviewed for appropriateness of care against a set of indicators within three Australian states (New South Wales, Queensland and South Australia) using multistage, stratified sampling. Medical records of children aged <16 years who presented with at least one of the study conditions during 2012 and 2013 will be reviewed. ETHICS AND DISSEMINATION: Human Research Ethics Committee approvals have been received from the Sydney Children's Hospital Network, Children's Health Queensland Hospital and Health Service and Women's and Children's Hospital Network (South Australia). An application is under review for the Royal Australian College of General Practitioners. The authors will submit the results of the study to relevant journals and offer oral presentations to researchers, clinicians and policymakers at national and international conferences.

CareTrack Kids-part 1. Assessing the appropriateness of healthcare delivered to Australian children: study protocol for clinical indicator development.

INTRODUCTION: Despite the widespread availability of clinical guidelines, considerable gaps remain between the care that is recommended (appropriate care) and the care provided. This protocol describes a research methodology to develop clinical indicators for appropriate care for common paediatric conditions. METHODS AND ANALYSIS: We will identify conditions amenable to population-level appropriateness of care research and develop clinical indicators for each condition. Candidate conditions have been identified from published research; burden of disease, prevalence and frequency of presentation data; and quality of care priority lists. Clinical indicators will be developed through searches of national and international guidelines, and formatted with explicit criteria for inclusion, exclusion, time frame and setting. Experts will review the indicators using a wiki-based approach and modified Delphi process. A formative evaluation of the wiki process will be undertaken. ETHICS AND DISSEMINATION: Human Research Ethics Committee approvals have been received from Sydney Children's Hospital Network, Children's Health Queensland Hospital and Health Service, and the Women's and Children's Health Network (South Australia). Applications are under review with Macquarie University and the Royal Australian College of General Practitioners. We will submit the results of the study to relevant journals and offer national and international presentations.

Patient safety culture: factors that influence clinician involvement in patient safety behaviours.

OBJECTIVES: To develop an understanding of the factors that influence patient safety-related behaviours by nurses, doctors and allied health staff employed by Queensland Health, using a theory-driven behavioural model. DESIGN: Cross-sectional survey analysed with multiple logistic regression. SETTING: Metropolitan, regional and rural public hospitals in Queensland, Australia. PARTICIPANTS: 5294 clinical and managerial staff. MAIN OUTCOME MEASURES: The Theory of Planned Behaviour was used to develop behavioural models for high-level Patient Safety Behavioural Intent (PSBI) of senior and junior doctors, senior and junior nurses, and allied health professionals. Multiple logistic regression analysis was used to identify factors that significantly influenced PSBI between the five professional groups. RESULTS: The factors that influence high-level PSBI give rise to unique predictive models for each professional group. Two factors stand out as influencing high-level PSBI for all healthcare workers (HCWs): (1) Preventive Action Beliefs (adjusted OR 2.38), HCWs' belief that engaging in the target behaviours will lead to improved patient safety; and (2) Professional Peer Behaviour (adjusted OR 1.79), perceptions about the patient safety-related behaviours of one's professional colleagues. CONCLUSIONS: Professional peer-modelling behaviours and individuals' beliefs about the value of those behaviours in improving patient safety are important predictors of HCWs' patient safety behaviour. These findings may help explain the limitations of current knowledge-based educational approaches to patient safety reform. Use of the behavioural models developed in this study when designing future patient safety improvement initiatives may prove more effective in driving the behavioural change necessary for improved patient safety.

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

OBJECTIVE: To develop a tool to allow Australian hospitals to monitor the range of hospital-acquired diagnoses coded in routine data in support of quality improvement efforts. DESIGN AND SETTING: Secondary analysis of abstracted inpatient records for all episodes in acute care hospitals in Victoria for the financial year 2005-06 (n=2.032 million) to develop a classification system for hospital-acquired diagnoses; each record contains up to 40 diagnosis fields coded with the ICD-10-AM (International Classification of Diseases, 10th revision, Australian modification). MAIN OUTCOME MEASURE: The Classification of Hospital Acquired Diagnoses (CHADx) was developed by: analysing codes with a "complications" flag to identify high-volume code groups; assessing their salience through an iterative review by health information managers, patient safety researchers and clinicians; and developing principles to reduce double counting arising from coding standards. RESULTS: The dataset included 126,940 inpatient episodes with any hospital-acquired diagnosis (complication rate, 6.25%). Records had a mean of three flagged diagnoses; including unflagged obstetric and neonatal codes, 514,371 diagnoses were available for analysis. Of these, 2.9% (14,898) were removed as comorbidities rather than complications, and another 118,640 were removed as redundant codes, leaving 380,833 diagnoses for grouping into CHADx classes. We used 4345 unique codes to characterise hospital-acquired conditions; in the final CHADx these were grouped into 144 detailed subclasses and 17 "roll-up" groups. CONCLUSIONS: Monitoring quality improvement requires timely hospital-onset data, regardless of causation or "preventability" of each complication. The CHADx uses routinely abstracted hospital diagnosis and condition-onset information about in-hospital complications. Use of this classification will allow hospitals to track monthly performance for any of the CHADx indicators, or to evaluate specific quality improvement projects.