Skip to main content

Table 1 Overview of study methods by objective

From: Implementation of integration strategies between primary care units and a regional general hospital in Brazil to update and connect health care professionals: a quasi-experimental study protocol

Element Objective 1 Objective 2 Objective 3 Objective 4
Objective To implement and evaluate an Internet-based platform that links health providers at a public hospital to18 primary care units (PCU) to improve communication among health services To promote and evaluate a distance-learning course (DLC) to update health professionals on the clinical management of ambulatory care sensitive conditions (ACSC) To verify the impact of the two strategies (communication and course) on patients’ hospital outcomes (30-day readmission rateslength of stay and mortality) To verify the long-term impact of the two strategies (communication and course) through the follow-up of the patient cohort
Design Longitudinal study of communications among health services Cross-sectional study of the course evaluation and longitudinal study of enrolled health care providers Longitudinal study of patients with ACSC using hospital electronic medical records Longitudinal cohort study
Procedures 1. Platform development
2. Registration and training of professionals
3. Use the platform in the following ways:
 i. The hospital sends an admission warning and a structured questionnaire on patient’s information to the PCU
 ii. The PCU manager responds with information about the patient
 iii. Hospital nurses enter the information in the patient’s electronic medical record
 iv. The hospital sends the discharge summary to the PCU
The course consists of five modules and uses discussion forums, case studies, web conferences, and face-to-face meetings
Information is obtained from the students and the DLC platform
This phase uses patient data collected from hospital electronic medical records Selection of eligible patients among all ACSC hospitalized patients
Administration of questionnaires by the research team
1-year follow-up at the PCU or the patient’s home
Gathering of information from the PCU’s paper-based medical records, covering at least 1 year before and 1 year after the hospitalization.
Selection of eligible patients for telemedicine consultation
Training of all interviewers, inter-rater agreement analysis
Participants/ Research units Communications among the health providers and the research team Health care providers who signed the informed consent form agreeing to volunteer for this research All hospital admissions of adult patients who had at least one ACSC from 2013 to 2017 Adult patients admitted to the hospital with an ACSC who are registered at any PCU enrolled in the study and are able to respond to questionnaires and sign the informed consent form
Measures Frequencies of alerts sent by the hospital, answers sent by the PCU, patients’ information being included in the electronic medical record, discharge summaries being sent by the hospital to the PCU
Duration of time between each of these steps
DLC: Frequencies of students’ access to didactic materials, participation in forums and face-to-face meetings
Professionals: sociodemographic characteristics, quality of life, mindfulness, clinical types of burnout, and primary care attention attributes.
Patients: Main and secondary diagnoses, address, length of stay, discharge type, readmissions, episodes in the emergency department, reference PCU
Medical record audits: Content quality of diagnosis, anamnesis, physical exam, lab exams, discharge summary, nurse registers
Patients’ information at inclusion: Sociodemographic characteristics, quality of life, primary care attention attributes.
Patients’ information at follow-up: Same as in inclusion, plus PCU medical record information, geographical location of residence, consultations, medications taken, main outcomes (therapeutic plan adherence, disease complications, health services access, mortality, readmission in any hospital)
Telemedicine: Reason for telemedicine request, use of diagnosis or treatment information to help with decision making, patients’ obtained outcomes
PCU medical record audits: Content quality of registered information
Sample size Not applicable All health care providers who accept enrollment in the DLC, of eligible health care providers from the hospital and PCU health teams All eligible patients during the study period. In total, 3422 patients with at least one ACSC were admitted from 2013 to 2014 560 patients, based on the observed incidence of 16 % readmission within 30 days, fitting a valid logistic model with up to nine covariates. Each interviewer will collect data from at least 10 patients and will be paired with another interviewer to assess inter-rater agreement
Data analysis Absolute and relative frequencies and median and interquartile ranges with 95 % confidence intervals. Chi-square and Mann–Whitney tests to compare measures among implementation phases
Social network analysis for assessing the communication structure
DLC: Absolute and relative frequencies, chi-square tests to compare measures from each module
Professionals’ information: Summary measures with 95 % confidence intervals, generalized linear models to assess possible associations, generalized estimating equations to compare results over time
Patients: Summary measures with 95 % confidence intervals, generalized estimating equations for length of stay, logistic models for mortality, kernel density to assess geographical location through patients’ addresses
Audits: Frequencies of adequacy of registered information with 95 % confidence intervals, chi-square tests for comparisons over time, inter-rater reliability of auditors by percent agreement and Gwet’s agreement coefficient
Baseline information: Summary measures with 95 % confidence intervals, hypothesis tests and/or generalized linear models to assess possible associations in the collected data
Main outcomes (readmission rates): Summary measures with 95 % confidence intervals, generalized linear models to assess associations, generalized estimating equations to compare results over time
Inter-rater agreement: Percent agreement and Gwet agreement coefficient