Systemic Falls Investigative Method

The Systemic Falls Investigative Method is a data collection and integration tool that is divided into six steps (Zecevic et al., 2009). The first two steps involve a continuous, iterative process of reflexivity, triangulation, and generation of further questions. This process continues until the data collected has sufficient depth and detail to provide an accurate summary of the event, represented in a sequence of events. The six steps of the SFIM are as follows:

Step one: Completion of a semi-structured interview at the location where the fall occurred (acute care stroke unit, stroke rehabilitation unit, home of the faller or long-term care facility where faller resides). The initial interview was conducted with the faller and/or the care provider. If a participant was cognitively impaired and unable to provide information or recall the circumstances accurately, additional interviews were conducted with healthcare staff and family members. Additionally, information was always confirmed by reviewing patient charts where all adverse events had to be documented. This provided us with some details surrounding the fall such as the location and specific time of the incident.

The objective of the interview was to collect data using the F-SHEL framework:

F—facts about the fallers; includes their physical, physiological, psychological and psychosocial characteristics;

S—software; includes training, policies and procedures, manuals, and/or checklists that were in place, either for the care procedures of the faller or for any equipment that was in use;

H—hardware; includes equipment used, mobility aids, transfer aids, bath aids, layout of items, display screens, and footwear used by individuals involved at the time of the fall;

E—faller’s environment; includes internal conditions such as lighting, temperature, noise, floor conditions and external environment such as weather, and community conditions/particularities;

L—liveware surrounding the faller; includes the other people involved, witnesses, healthcare providers and agencies, other family members, peoples’ attitudes, social networks, and communication.

All interviews were audio recorded unless the person being interviewed requested not to be recorded. In addition, photos were taken of the environment where the fall took place and any pertinent aids used at the time. All information gathered from the interviews and chart reviews was taken back to the research office where two researchers recreated the event. Initial interviews with any identified participant took an average of 30-120 minutes. During step one, the faller’s past medical history, medications, and any other relevant information pertaining to the fall was also collected.

Step two: Develop the sequence of events that led up to the event. This step was initiated by the researcher who was assigned to each case (cases were divided amongst four research assistants). A chronological hypothesis of the sequence of events that led to the fall was developed after the initial gathering of information. The preliminary sequence of events was presented to the SFIM research group at the weekly meetings, where researchers worked together to establish more questions and hypotheses and identify gaps in the sequence of events.

The sequence of events was then revised and confirmed through additional data collection, and the events that were safety-significant were identified. Safety significant events (SSEs) were acts and decisions that directly contributed to the adverse event. SSEs were determined by answering the following questions about each event in the sequence:

• Was this task undesirable? • Was this task non-standard?

• Was this task linked or potentially linked to another undesirable event? • Was this task one of alternative actions or options available?

If the answer was ‘yes’ to any of the questions, the act was classified as a SSE. Each SSE was then examined more closely by asking further questions regarding the “why”. For example: Why was this task undesirable? The “why” questions uncovered further need for data collection and led to interviews with additionally identified secondary participants, further observations, or further review of additional data sources, such as written materials on policies or medical records. Follow-up interviews were completed at the hospitals, over the phone, or by email, depending on the participants’ preferences and the nature of the information required. Once additional information was collected and the sequence of events clarified, the SFIM research group reviewed the description of the final sequence of events for thoroughness and depth. The description of the sequence of events was reviewed by the research group an average of two times, but often times three to four times, before all members were satisfied. A narrative

summary of the fall was then written by the investigator and the de-identified data were entered into the SFIM database. Data in the SFIM database is de-identified and stripped of any personal identifiers and assigned a unique code. The SSEs were further analyzed in step three.

Step three: Generic Error Modeling System (GEMS). In the SFIM, unsafe acts and decisions are analyzed further using the Generic Error Modeling System (GEMS) (Reason, 1987). This system of modeling human error was used to determine:

• the mindset of the person at the time of the event

• if the error was skill-based, rule-based, or knowledge-based

• which failure mode corresponded to a skill-based slip or lapse: inattention or over- attention

• which failure mode corresponded to a rule-based or knowledge-based mistake: misapplication of good rules, application of a bad rule, biases, or heuristics?

• which failure modes corresponded to a knowledge-based adaptation: biases or heuristics? More detailed description of GEMS analysis is available in Reason (1987). The GEMS analysis was completed by A. Zecevic for all cases as part of a larger study, and the results will not be presented in this study.

Step four: Swiss cheese Model of Accident Causation analysis. The fourth step of the SFIM puts the contributing factors identified in step two into context of the Swiss Cheese Model of Accident Causation developed by Reason (1990) and adapted for the SFIM by Zecevic et al. (2007). The four levels of this model include: unsafe acts and decisions, preconditions, supervision factors, and organizational factors. According to Reason (1990), most accidents can be traced back to one or more of the four levels of failure: unsafe acts, preconditions, unsafe supervision or organizational factors. In this model, the slices of Swiss cheese represent an organization’s defenses against failure, and the holes represent weaknesses in each of the four levels of defense. These weaknesses or ‘holes’ in the Swiss cheese are continually varying in position and/or size, and only when the holes in the cheese momentarily align, does an accident or failure, such as a fall, occur (Zecevic et al., 2007).

Figure 3 Adapted Version of the Swiss cheese Model of Accident Causation for SFIM © Aleksandra Zecevic 2007

Step five: Identifying Safety Deficiencies and Risk Assessment. A within-case study analysis was conducted to identify the unsafe conditions and underlying factors.

Step six: Development of safety actions. The final step in SFIM investigative process is to develop safety actions. The job of the SFIM investigator was to find what went wrong and inform those directly involved with patient safety either in the hospital setting (Quality care control team or unit managers) or community service providers (Community Care Access Centre and Community Stroke Rehabilitation Team). Knowledge translation activities involve the sharing of the comprehensive SFIM reports with these patient safety teams.

2.4.1

SFIM Database

All information collected as part of the falls investigation was de-identified and entered into a web-based database. Information entered into the database included facts about the faller and the fall, as well as a chronological sequence of events. Information about the faller and the fall was inputted into appropriate boxes. Several variables and rating scales (normally found in the fallers’ medical records) were also part of the data input process (e.g., MoCA scores, FIM scores, MMSE scores, and rate of falls). The database automatically generates sequence of events diagrams based on the

information provided by the investigators and full case reports which include the Swiss cheese tables. Full case reports can be seen in Appendix K.