Degree of Worry as a Predictor for Utilization of Acute Health Care

Overview

The overall aim of the study is to construct a scale that systematically incorporates the callers' perspective in a "degree of worry - scale" and to explore the consequences for the actors in the system - caller, call-handler, and health care system. This will be done through four independent studies. 1. Is it possible to validate "the degree of worry" scale with the software system "Corti"? 2. Does callers' degree of worry relieve after telephone consultation? 3. Does call handlers' awareness of degree of worry affect triage outcome? 4. Is callers' degree of worry a predictor of illness severity?

Does call-handlers awareness of caller Degree-Of-Worry affect triage outcome in telephone consultation? - a randomized trial. Background When conducting a telephone consultation the call handler will make the decision of help needed on the basis of the dialog with the caller. The need of health care is difficult to estimate due to the lack of visual cues (Rothwell, Ellington, Planalp, \& Crouch, 2012) and might be complicated by factors related to the caller or the call handler herself (Lindström, Heikkilä, Bohm, Castrèn, \& Falk, 2014). Especially in cases of low-urgency and non-normative symptom description, as in the case of the majority of calls to the OOH, the call handlers' own health belief will have an impact on the triage outcome (Leprohon \& Patel, 1995; Ogden, 2011). Callers' Degree-Of-Worry (DOW) when contacting an Out-of-Hours service (OOH) has proven to be a valuable source of information of the callers' perception of the actual situation (not published). Call-handlers awareness of DOW can potentially increase the amount of telephone consultations terminated with advice of self-care or to seek General Practioner (GP) during office hours. Therefore, the present study seeks to investigate if call handlers' awareness of DOW affect triage outcome? Aim: Does call-handlers awareness of caller Degree-Of-Worry affect triage outcome in telephone consultation Methods Design The design of the study is a randomized controlled design blinding the call-handlers to callers' DOW in a computer assisted 1:1 ratio Eliglibility: all calls to hotline 1813 where informed consent is obtained. Intervention: blinding call-handlers to callers' DOW. Setting The acute care system within the Capital Region of Denmark is divided into two facilities. The Medical Emergency Service and the Out-Of-Hours services (OOH) (hotline 1813) (Wadmann, Kjellberg, \& Kjellberg, 2015). All acute contact to the health care system within the region is pre-assessed and triaged. The OOH handles approx. 1 million calls per year of which approx. 40% are triaged to either self-care or consultation at their general practitioner (GP). The call handler is a nurse or physician, who triages the caller to either home visit, clinic consultation, self-care or GP. Triage and determination of urgency is guided by criterion based triage tools. The triage tool used in the OOH has been locally developed and has not been validated. The present study is a part of a larger study which aims to construct a scale that systematically incorporates the callers' perspective in a "DOW" -scale" and to explore the consequences for the actors in the system - caller, call-handler, and health care system. Data collection The research questions (see above) will be answered through the analysis of carefully collected data material incorporating the state of art set up at the hotline 1813 and the Danish health registers. The data collection points are: * Datapoint 1: After calling the hotline 1813 before reaching the call handler (caller delivers data). * Datapoint 2: Right after call terminated (caller delivers data) * Datapoint 3: 48 hours after initial contact to the medical hotline 1813 (Danish Registers delivers data) Data will be collected at three different points during a call made to the hotline 1813. Participation in the study is voluntary. The data collection will be carried out as an automated telephone questionnaire. After the telephone consultation the caller will receive an automated call for further information. In case of non-response a text message will be sent after 30 and 60 minutes. The randomization data is generated by reviling caller DOW to the call-handlers. DOW will be shown as a part of the medical history template, alongside civil registration number, address. In order to assure the DOW is seen by the call-handler this will be presented on the medical history template in red, size 14 numbers. Triage outcome will be collected from the internal database at the hotline 1813. The data analysis within the RCT will be limited to triage response given by call-handlers. The plan of analysis is: Primary outcome Does call-handlers awareness of caller Degree-Of-Worry affect triage outcome in telephone consultation Chi2 test and OR of difference between intervention-and control group. Log regression on outcome in exposure (little, medium and very much worry) Sub-group of primary outcome (caller) Eksplorative outcomes- DOW in three groups (little, some, much) Is there a difference (intervention/control group) in triage outcome in the group of young children and old people, respectively? Chi2 test of difference between intervention-and control group Sub-group of primary outcome (call-handler) Eksplorative outcomes - Is there a difference (intervention/control group) in triage outcome in call-handler gender, years of experience, waiting time? Gender (chi2 test), Years of experience and waiting time Non-response analysis Is there a difference between age, sex, triage-response, criteria, time of day and weekday? (participants/non-participants) age, sex, triage response, Criteria, Time of day, Weekday (Descriptive - mean and %)