Linkage of ambulance service and accident and emergency department data: a study of assault patients in the west midlands region of the UK

[Linking Health Claims Data and Records of Emergency Medical Services: Building a Bridge via Patient's Health Insurance Number?]

INTRODUCTION

In Germany, Emergency Medical Services (EMS) were involved in a total of 7.3 million emergency cases in 2016/2017. Information on prehospital care is stored in several secondary data sources, yet combined analysis of these data at the level of individual patients or EMS cases happens rarely. Research is needed on which methods and variables are suitable for the linkage of these data sources.

METHODS

We linked EMS records from five Bavarian emergency service districts to health claims data belonging to ten statutory health insurers (data from 2016). Two linkage approaches at the level of individual patient's EMS case/reimbursement case were demonstrated. First, a deterministic linkage was conducted based on the patient's unique identifying health insurance number. The second linkage was probabilistic. As linkage variables, it comprised the only partially available health insurance number plus several non-unique key variables, the latter being a patient's health insurance provider, sex, year of birth and distance travelled. In order to verify the deterministic and the probabilistic linkages' quality, rates of accordance of several variables present in both data sources were calculated.

RESULTS

The starting point for our data linkage were 106,371 EMS records (independent of certain health insurance companies) and 432,693 EMS services reimbursed by health insurers (independent of specific EMS providers). 4,327 EMS records could be linked to health claims data - out of 5,921 EMS records that coded a health insurance company contributing claims data to Inno_RD. With a probabilistic linkage, it was possible to increase this number to a total of 5,379 linked EMS records. All checks carried out indicated a high linkage quality for both the deterministic and the probabilistic approach.

CONCLUSION

A linkage of EMS records with health claims data is possible. In Inno_RD, a probabilistic approach has proven a valuable alternative to deterministic linkage via health insurance number since EMS records can be linked meaningfully even if the health insurance number is unavailable or where a minority of non-unique key variables show non-accordance or missing values.

Linking Ambulance Trip and Emergency Department Surveillance Data on Opioid-Related Overdose, Massachusetts, 2017

OBJECTIVES

Studies describing linkage of ambulance trips and emergency department (ED) visits of patients with opioid-related overdose (ORO) are limited. We linked records of patients experiencing ORO from ambulance trip and ED visit records in Massachusetts during April 1-June 30, 2017.

METHODS

We estimated the positive predictive value of ORO-capturing definitions by examining the narratives and triage notes of a sample of OROs from each data source. Because of a lack of common unique identifiers, we deterministically linked OROs to records in the counter data set on date of birth, incident date, facility, and sex. To validate the linkage strategy, we compared ambulance trip narratives with ED triage notes and chief complaints for a sample of pairs.

RESULTS

Of 3203 ambulance trips for ORO and 3046 ED visits for ORO, 82% and 63%, respectively, matched a record in the counter data set on date of birth, incident date, facility, and sex. In 200 randomly selected linked pairs from a final linked data set of 3006 paired records, only 5 (3%) appeared to be false matches.

PRACTICE IMPLICATIONS

This exercise demonstrated the feasibility of linking ORO records between 2 data sets without a unique identifier. Future analyses of the linked data could produce insights not available from analyzing either data set alone. Linkage using 2 rapidly available data sets can actively inform the state's public health opioid overdose response and allow for de-duplicating counts of OROs treated by ambulance, in an ED, or both.

A data linkage study of suspected seizures in the urgent and emergency care system in the UK

INTRODUCTION

The urgent and emergency care (UEC) system is struggling with increased demand, some of which is clinically unnecessary. Patients suffering suspected seizures commonly present to EDs, but most seizures are self-limiting and have low risk of short-term adverse outcomes. We aimed to investigate the flow of suspected seizure patients through the UEC system using data linkage to facilitate the development of new models of care.

METHODS

We used a two-stage process of deterministic linking to perform a cross-sectional analysis of data from adults in a large region in England (population 5.4 million) during 2014. The core dataset comprised a total of 739 436 ambulance emergency incidents, 1 033 778 ED attendances and 362 358 admissions.

RESULTS

A high proportion of cases were successfully linked (86.9% ED-inpatient, 77.7% ED-ambulance). Suspected seizures represented 2.8% of all ambulance service incidents. 61.7% of these incidents led to dispatch of a rapid-response ambulance (8 min) and 72.1% were conveyed to hospital. 37 patients died before being conveyed to hospital and 24 died in the ED (total 61; 0.3%). The inpatient death rate was 0.4%. Suspected seizures represented 0.71% of ED attendances, 89.8% of these arrived by emergency ambulance, 45.4% were admitted and 44.5% of these admissions lasted under 48 hours.

CONCLUSIONS

This study confirms previously published data from smaller unlinked datasets, validating the linkage method, and provides new data for suspected seizures. There are significant barriers to realising the full potential of data linkage. Collaborative action is needed to create facilitative governance frameworks and improve data quality and analytical capacity.

Aggression and violence at ambulance attendances where alcohol, illicit and/or pharmaceutical drugs were recorded: A 5-year study of ambulance records in Victoria, Australia

BACKGROUND

This study describes the frequency and characteristics of aggression and/or violence in ambulance attendances involving alcohol, illicit and/or pharmaceutical drug use in Victoria, Australia between January 2012 and January 2017.

METHODS

Patient characteristics, context, and substance use involvement in ambulance attendances were examined to determine associations with attendances where aggression and/or violence was recorded.

RESULTS

There were 205,178 ambulance attendances where use of alcohol, pharmaceutical drugs or illicit substances contributed to the reason for the attendance. Paramedics recorded acts of aggression and/or violence in 11,813 (5.76 %) of these attendances. Aggression/violence was more likely to be recorded in certain contexts. Compared with attendances where aggression/violence was not recorded, attendances where aggression/violence was recorded were significantly more likely to involve younger and male patients, and occur on Friday and Saturday nights. Alcohol intoxication was involved in more than half of attendances where aggression/violence was recorded, and was almost twice as prevalent as those involving illicit drug use where aggression/violence was recorded. This pattern was consistent across all hours, high-alcohol hours only, by metropolitan/regional location, and by police co-attendance.

CONCLUSIONS

Aggression and violence are frequently recorded in ambulance attendances involving alcohol, pharmaceutical drugs or illicit substances, and, most often involve alcohol. This violence poses a recurring threat to the health and safety of paramedics, bystanders, and patients. Greater priority should be given to reducing alcohol-related violence through evidence-based policy measures targeting high-risk groups (e.g. young adult males) and contexts (e.g. weekends, late at night) where harm is most likely to occur.

Developing new ways of measuring the quality and impact of ambulance service care: the PhOEBE mixed-methods research programme

Background

Ambulance service quality measures have focused on response times and a small number of emergency conditions, such as cardiac arrest. These quality measures do not reflect the care for the wide range of problems that ambulance services respond to and the Prehospital Outcomes for Evidence Based Evaluation (PhOEBE) programme sought to address this.

Objectives

The aim was to develop new ways of measuring the impact of ambulance service care by reviewing and synthesising literature on prehospital ambulance outcome measures and using consensus methods to identify measures for further development; creating a data set linking routinely collected ambulance service, hospital and mortality data; and using the linked data to explore the development of case-mix adjustment models to assess differences or changes in processes and outcomes resulting from ambulance service care.

Design

A mixed-methods study using a systematic review and synthesis of performance and outcome measures reported in policy and research literature; qualitative interviews with ambulance service users; a three-stage consensus process to identify candidate indicators; the creation of a data set linking ambulance, hospital and mortality data; and statistical modelling of the linked data set to produce novel case-mix adjustment measures of ambulance service quality.

Setting

East Midlands and Yorkshire, England.

Participants

Ambulance services, patients, public, emergency care clinical academics, commissioners and policy-makers between 2011 and 2015.

Interventions

None.

Main outcome measures

Ambulance performance and quality measures.

Data sources

Ambulance call-and-dispatch and electronic patient report forms, Hospital Episode Statistics, accident and emergency and inpatient data, and Office for National Statistics mortality data.

Results

Seventy-two candidate measures were generated from systematic reviews in four categories: (1) ambulance service operations (n = 14), (2) clinical management of patients (n = 20), (3) impact of care on patients (n = 9) and (4) time measures (n = 29). The most common operations measures were call triage accuracy; clinical management was adherence to care protocols, and for patient outcome it was survival measures. Excluding time measures, nine measures were highly prioritised by participants taking part in the consensus event, including measures relating to pain, patient experience, accuracy of dispatch decisions and patient safety. Twenty experts participated in two Delphi rounds to refine and prioritise measures and 20 measures scored ≥ 8/9 points, which indicated good consensus. Eighteen patient and public representatives attending a consensus workshop identified six measures as important: time to definitive care, response time, reduction in pain score, calls correctly prioritised to appropriate levels of response, proportion of patients with a specific condition who are treated in accordance with established guidelines, and survival to hospital discharge for treatable emergency conditions. From this we developed six new potential indicators using the linked data set, of which five were constructed using case-mix-adjusted predictive models: (1) mean change in pain score; (2) proportion of serious emergency conditions correctly identified at the time of the 999 call; (3) response time (unadjusted); (4) proportion of decisions to leave a patient at scene that were potentially inappropriate; (5) proportion of patients transported to the emergency department by 999 emergency ambulance who did not require treatment or investigation(s); and (6) proportion of ambulance patients with a serious emergency condition who survive to admission, and to 7 days post admission. Two indicators (pain score and response times) did not need case-mix adjustment. Among the four adjusted indicators, we found that accuracy of call triage was 61%, rate of potentially inappropriate decisions to leave at home was 5–10%, unnecessary transport to hospital was 1.7–19.2% and survival to hospital admission was 89.5–96.4% depending on Clinical Commissioning Group area. We were unable to complete a fourth objective to test the indicators in use because of delays in obtaining data. An economic analysis using indicators (4) and (5) showed that incorrect decisions resulted in higher costs.

Limitations

Creation of a linked data set was complex and time-consuming and data quality was variable. Construction of the indicators was also complex and revealed the effects of other services on outcome, which limits comparisons between services.

Conclusions

We identified and prioritised, through consensus processes, a set of potential ambulance service quality measures that reflected preferences of services and users. Together, these encompass a broad range of domains relevant to the population using the emergency ambulance service. The quality measures can be used to compare ambulance services or regions or measure performance over time if there are improvements in mechanisms for linking data across services.

Future work

The new measures can be used to assess different dimensions of ambulance service delivery but current data challenges prohibit routine use. There are opportunities to improve data linkage processes and to further develop, validate and simplify these measures.

Funding

The National Institute for Health Research Programme Grants for Applied Research programme.

A Review of Data Quality Assessment in Emergency Medical Services

INTRODUCTION

Data quality is an important issue in emergency medicine. The unique characteristics of emergency care services, such as high turn-over and the speed of work may increase the possibility of making errors in the related settings. Therefore, regular data quality assessment is necessary to avoid the consequences of low quality data. This study aimed to identify the main dimensions of data quality which had been assessed, the assessment approaches, and generally, the status of data quality in the emergency medical services.

METHODS

The review was conducted in 2016. Related articles were identified by searching databases, including Scopus, Science Direct, PubMed and Web of Science. All of the review and research papers related to data quality assessment in the emergency care services and published between 2000 and 2015 (n=34) were included in the study.

RESULTS

The findings showed that the five dimensions of data quality; namely, data completeness, accuracy, consistency, accessibility, and timeliness had been investigated in the field of emergency medical services. Regarding the assessment methods, quantitative research methods were used more than the qualitative or the mixed methods. Overall, the results of these studies showed that data completeness and data accuracy requires more attention to be improved.

CONCLUSION

In the future studies, choosing a clear and a consistent definition of data quality is required. Moreover, the use of qualitative research methods or the mixed methods is suggested, as data users' perspectives can provide a broader picture of the reasons for poor quality data.

The methodology of the Australian Prehospital Outcomes Study of Longitudinal Epidemiology (APOStLE) Project

This paper describes the methodology of a large emergency medical services (EMS) data linkage research project currently under way in the statewide EMS system of New South Wales, Australia. The paper is intended to provide the reader with an understanding of how linkage techniques can be used to facilitate EMS research. This project, the Australian Prehospital Outcomes Study of Longitudinal Epidemiology (APOStLE) Project, links data from six statewide sources (computer-assisted dispatch, EMS patient health care reports, emergency department data, inpatient data, and two death registries) to enable researchers to examine the patient's entire journey through the health care system, from the emergency 0-0-0 call to the emergency department and inpatient setting, through to discharge or death, for approximately 2.6 million patients transported by the Ambulance Service of New South Wales to emergency departments between June 2006 and July 2009. Manual, deterministic, and probabilistic data linkages are described, and potential applications of linked data in EMS research are outlined.

A link to improve stroke patient care: a successful linkage between a statewide emergency medical services data system and a stroke registry

OBJECTIVES

regionalization of stroke care, including diversion to stroke centers, requires that emergency medical services (EMS) systems accurately identify acute stroke patients. A barrier to evaluating and improving EMS stroke patient identification is the inability to link EMS data with hospital data for individual patients. We sought to create and validate a linkage of the North Carolina EMS Data System (NC-EMS-DS) with data contained in the North Carolina Stroke Care Collaborative (NCSCC) Registry.

METHODS

all NCSCC Registry patients arriving to one of three hospitals by EMS in a 6-month period were matched against NC-EMS-DS. Records were deterministically matched on receiving hospital, hospital arrival date/time, age, and sex. We performed linkage validation by providing each site investigator with a stroke patient list derived from North Carolina Stroke Care Collaborative Registry (NC-EMS-DS), matched by individual patient to deidentified data in the NCSCCR. Each site investigator determined the set of true matches by comparing the matched list to a NCSCCR patient identifier key maintained at each site. Incorrect matches were reviewed by the research team to identify methods for future improvement in the matching logic.

RESULTS

for the three validation hospitals, 753 NCSCC Registry patients arrived by EMS. For these patients, 473 (63%) matches to local EMS records were identified, and 421 (89%) of the matches were verified using full patient identifiers. Most match verification failures were due to incorrect date/time stamp and inability to find a corresponding EMS record.

CONCLUSIONS

linking EMS records electronically to a stroke registry is feasible and leads to a large number of valid matches. This small validation is limited by EMS data quality. Matching may improve with better EMS documentation and standardized facility documentation.

The experience of linking Victorian emergency medical service trauma data

BACKGROUND

The linking of a large Emergency Medical Service (EMS) dataset with the Victorian Department of Human Services (DHS) hospital datasets and Victorian State Trauma Outcome Registry and Monitoring (VSTORM) dataset to determine patient outcomes has not previously been undertaken in Victoria. The objective of this study was to identify the linkage rate of a large EMS trauma dataset with the Department of Human Services hospital datasets and VSTORM dataset.

METHODS

The linking of an EMS trauma dataset to the hospital datasets utilised deterministic and probabilistic matching. The linking of three EMS trauma datasets to the VSTORM dataset utilised deterministic, probabilistic and manual matching.

RESULTS

There were 66.7% of patients from the EMS dataset located in the VEMD. There were 96% of patients located in the VAED who were defined in the VEMD as being admitted to hospital. 3.7% of patients located in the VAED could not be found in the VEMD due to hospitals not reporting to the VEMD. For the EMS datasets, there was a 146% increase in successful links with the trauma profile dataset, a 221% increase in successful links with the mechanism of injury only dataset, and a 46% increase with sudden deterioration dataset, to VSTORM when using manual compared to deterministic matching.

CONCLUSION

This study has demonstrated that EMS data can be successfully linked to other health related datasets using deterministic and probabilistic matching with varying levels of success. The quality of EMS data needs to be improved to ensure better linkage success rates with other health related datasets.

Monitoring the "tip of the iceberg'': ambulance records as a source of injury surveillance

AIMS

The aim of this study was to describe the epidemiology of moderate and severe injury morbidity in a defined population on the basis of ambulance records, and to validate ambulance records as a potential source of surveillance.

METHODS

A geographical target area was defined; the county of Värmland, Sweden. All ambulance attendances and hospitalizations for unintentional and intentional injury in 2002 were selected, analysed, and compared.

RESULTS

Ambulance data comprised 3,964 injury cases (14.5/1,000). Most injuries for which ambulance attention was sought occurred in road traffic areas (27%), followed by residential areas (20%), school and institutional areas (14%), and sports areas (8%). An ecological comparison between ambulance-based data and hospitalizations showed that ambulance services captured approximately the same amount of injury cases (3,235 ambulance reports, as compared to 3,456 hospital discharges) with a similar profile.

CONCLUSIONS

This study provides epidemiological support for ambulance services as a potential source of regular surveillance data on moderate and severe injuries. However, at a population level, our results indicate that ambulance data tend to overestimate some injury categories, and underestimate others, as compared to hospital data. The significance of these differences for preventive work, as well as other practical aspects of the feasibility of regular injury surveillance, will be analysed and discussed on the basis of general criteria for evaluation of surveillance systems in a forthcoming paper.