This is a quantitative, retrospective study of medical records within the framework of existing resources at DWMCS. We mapped gender, age, seasonal distribution for the medical visits, diagnostic groups, thirty most common primary diagnoses, therapeutics, ten most common drug treatments and referrals by studying all patients’ electronic records on DWMCS between 2014-04-01 and 2017-12-31. The time interval was determined based on the date when DWMCS first began using a computerized medical record system until the start of the study. Ethnicity and country of origin were not included because they were judged to be sensitive information andunreliable, and they may increase the possibility of identifying individual study participants. The medical record system at DWMCS was ProRenata version 2.142.0.
The research subjects consisted of all patients at the clinic who had an electronic medical record. Inclusion criteria were that there was a medical record note with age, date, gender and diagnosis according to the diagnosis manual ICPC-2. Exclusion criteria were whether there was a double record for the same patient or if the birth data for a record was filled in incorrectly. There were 796 patients (38%) excluded: 547 (69%) women, 240 (30%) men and 9 (1%) without a stated gender. The reasons for exclusion were lack of diagnosis (85.3%), no reception note (4.1%), dentist note without diagnosis (2.6%), double medical record (2.6%), incorrect birth data (2.1%), deleted or missing journal (1.5%), missing gender information (1.1%) and exercise journal (0.5%).
Patient data were extracted from the medical records by manual reading, entered into an Excel matrix and processed after anonymization. Anonymization took place using a code key. The code key was created by separating the subjects’ names and birth data from the other data in a separate Excel file after they were assigned a serial number. The code key was saved in a password-protected file on a USB memory stick. The serial numbers were also saved together with the data that was extracted and processed.
If there were several visits, only the first visit that met the inclusion criteria was included. If there were several diagnoses, only the primary diagnosis was included, i.e. the diagnosis that was first in the diagnosis list for the visit. The primary diagnoses were grouped according to ICPC-2 into either Symptoms / Complaints, Other diagnoses, Infections, Injuries, Tumors or Congenital malformations. If there was a defined therapeutic for the primary diagnosis, this was included. If there were several therapeutics indicated for the primary diagnosis, only the first mentioned was included. The therapeutics were grouped into either Pharmaceutical, Referral, Other treatment or No treatment. Pharmaceutical treatments were classified to a therapeutic subgroup according to the second level of the Anatomical Therapeutic Chemical Classification System (ATC). Referrals were categorized depending on the recipient to Health centers, Emergency rooms, Abortion clinics and Other recipients. Other recipients included dentists, maternity care, infection clinics and opticians. Due to regulations in the Swedish Health and Medical Care Act, follow-up information on primary diagnosis from referral clinics could not be collected.
Microsoft Excel version 16.16.18 was used for descriptive statistics and structuring of tables. Nominal data such as diagnostic groups, diagnoses, therapeutics, drug treatments and referrals were compiled as pivot tables. The size ratio between the number of patients who were women and the number who were men was described as a gender ratio by dividing the number of women by the number of men. The size ratio between the number of patients who sought help during the summer (April to September) and the winter (October to March) was described as a seasonal ratio by dividing the number of patients during the summer by the number of patients during the winter. Age as interval data was not normally distributed, the difference in median age was chosen as a comparative measure and calculated with the Mann-Whitney test. Two-group analysis of nominal data was performed with Monte Carlo simulations (MC) and chi square test´s (X2). MC and X2 requires independence of observations why only one outcome for each category of nominal data could be included for every patient. MC was chosen for analyses where there were outcomes with less than five patients and X2 was chosen when all outcomes had at least five patients. For two-group analysis of nominal data, outcomes with a very small proportion of total outcomes (<1%) were excluded and outcomes only possible for one gender, for example pregnancy and abortion, excluded that specific outcome. For all statistical calculations, the statistics program Past 3 version 3.24 was used. The significance level was determined to be 5% (p <0.05).