Harnessing patient complaints to systematically monitoring healthcare concerns through disproportionality analysis

Author:

Bie Bogh Søren12ORCID,Fryd Birkeland Søren234,Maj-Britt Hansen Sebrina1,Alexandrovna Tchijevitch Olga1,Hallas Jesper5ORCID,Morsø Lars12

Affiliation:

1. Research Unit OPEN, Department of Clinical Research, University of Southern Denmark , J.B. Winsløws Vej 19,3, Odense, Syddanmark 5000, Denmark

2. Odense University Hospital, Region of Southern Denmark , J.B. Winsløws Vej 19,3, 5000, Denmark

3. Department of Regional Health Research, Faculty of Health Science, Forensic Mental Health Research Unit Middelfart (RFM), University of Southern Denmark , J.B. Winsløws Vej 19,3, Odense 5000, Denmark

4. Psychiatric Department Middelfart, Mental Health Services in the Region of Southern Denmark , Østre Hougvej 70, Middelfart 5500, Denmark

5. Department of Clinical Pharmacology, Pharmacy and Environmental Medicine, University of Southern Denmark , J.B. Winsløws Vej 19,3, Odense, Denmark

Abstract

Abstract Staff observations are the most common source of data for driving improvements in care. However, the patient perspective should also be considered, and healthcare complaints offer concrete details that health organizations might otherwise overlook and that can highlight areas for learning and improvement in the healthcare system. However, because of the diverse nature of patient complaints, systematic analyses can be challenging. This study aimed to identify and prioritize areas for improvement using a data-driven approach to analysing patient complaints. The Danish version of the Healthcare Complaints Analysis Tool was used to categorize the content of complaint letters. All complaints managed by the national complaints authority, compensation claims to the Patient Compensation Association, and locally managed complaints that were filed directly at Odense University Hospital from 2017 to 2021 were included. Proportional reporting ratios (PRRs) were used to measure and display the top five signals of disproportionality and rank them by excess complaints at the hospital level and when divided into department types. The study included 6366 complaints containing 13 156 problems (on average, 2.1 problems mentioned per complaint letter). Surgical departments had the highest number of complaints (3818), followed by medical (1059), service (439), and emergency departments (239). Signal 1 of disproportionality, relating to quality problems during ward procedures, had the highest excess reporting of 1043 complaints at the hospital level and a PRR of 1.61 and was present in all department types. Signal 2, relating to safety problems during the examination and diagnosis stage, had an excess reporting of 699 problems and a PRR of 1.86 and was also present in all department types. Signal 3, relating to institutional problems during admission, had the highest PRR of 3.54 and was found in most department types. Signals 4 and 5, relating to environmental problems during ward procedures and care on the ward, respectively, had PRRs of 1.5 and 1.84 and were present in most department types. The study found that analysing patient complaints can identify potential areas for hospital improvement. The study identified recurring issues in multiple departments, including quality problems during ward procedures, safety problems during the examination, institutional problems during admission, and environmental problems on the ward. The study highlights disproportionality analysis of complaints as a valuable tool to monitor patient concerns systematically.

Funder

Odense University Hospital

Publisher

Oxford University Press (OUP)

Subject

Public Health, Environmental and Occupational Health,Health Policy,General Medicine

Reference25 articles.

1. The incidence and nature of in-hospital adverse events: a systematic review;de Vries;Qual Saf Health Care,2008

2. Safety analysis over time: seven major changes to adverse event investigation;Vincent;Implement Sci,2017

3. The Danish unique personal identifier and the Danish Civil Registration System as a tool for research and quality improvement;Mainz;Int J Qual Health Care,2019

4. Patient complaints in healthcare systems: a systematic review and coding taxonomy;Reader;BMJ Qual Saf,2014

5. Optimizing patient involvement in quality improvement;Armstrong;Health Expect,2013

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