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Table 2 Description of health services utilization indicators

From: Use of health outcome and health service utilization indicators as an outcome of access to medicines in Brazil: perspectives from a literature review

Name Definition Calculation Source of Data Interpretation/ Scale
Emergency
 Use of emergency services [13] Dichotomy Count: dichotomy CMS Medicaid Analytical Extract database NI
 Number of visits to the emergency department related to the DM [14] Visits related to diabetes when ICD was the primary, second or third diagnosis NI NI NI
 Change in the annual number of emergency care [15] NI NI Administrative database Hypothesis: the copayment increase will not increase the use of medical and non-pharmaceutical services
 Number of visits to the emergency department [12, 16,17,18] Frequency of visits to the emergency department in the year after discharge [16] NI Administrative database [16] NI
NI [17] Medical Expenditure Panel Survey (MEPS)1 [17, 18]
Annual number of visits [18] NI [12]
Treat and release only [12]
 Proportion of visits to the emergency [19] NI. It is not clear, however the name leads to a presumption that it is the proportion of the studied patients that had a visit to the emergency NI Administrative base of individual data linked to the registry of cancer from 1999 to 2004 of Georgia, South Caroline and Texas Hypothesis: although the treatments directly related to cancer are exempt of copayment, the patients need other medicines that are subject to cost sharing.
 Emergency admission [20] Emergency hospital admission for any reason Emergency hospital admissions/1000 patient-year PharmaNet database NI
Hospitalization
 Hospitalization [14, 20, 21] Visits related to DM when ICD was the primary, second or third diagnosis [14] NI NI [14] NI
Emergency hospitalization when the primary reason was a chronic and obstructive pulmonary disease bronchitis, asthma or emphysema [20] PharmaNet database [20]
Mean number of visits [21] U.S. Renal Data System (USRDS)2 [21]
 Number of hospitalizations [17, 18] Annual number of visits. The number of discharges included those hospitalizations for which the admission and discharge date were the same [18] NI The Medical Expenditure Panel Survey (MEPS)1 NI
NI [17]
 Number of days of hospitalization [22] /Days of hospital stay [21] NI NI National registry of psychoses [22] NI
U.S. Renal Data System (USRDS)2 [21]
 Changes in the annual number of hospitalization [15] NI NI Administrative database Hypothesis: the copayment increase will not increase the use of medical and non-pharmaceutical services
 Hospitalization use rates [23] Hospitalization whose diagnose code is related to depression Monthly calculation per 1000 elderly PharmaNet database Unexpected consequences of the intervention, cushioning the economy with medicines
 Hospital utilization [24, 25] Demonstrate if the person was hospitalized within a month [24] NI Insurance companies database [24] Unexpected consequences of the intervention, cushioning the economy with medicines [24]
Whether the individual spent any days in the hospital during the year (probability of hospitalization) [25] Administrative database [25] “An offset effect could be hypothesized to exist for elderly patients in the form of reduced hospital utilization when they become eligible for high cost sharing exemption. This offset effect may arise from increased initiation of chronic treatment or improved patient compliance for effective prescription medicines under free care” [25]
 Hospital admission [13, 26] Dichotomous [13] NI [13] CMS Medicaid Analytical Extract database [13] NI
NI [26], but by the calculation formula it is clear that it is not a dichotomous indicator as defined in the other included study. annual incidence of hospitalizations (asthma and non respiratory diseases) per 100,000 people by dividing the number of cases of disease by the midyear population estimates, and multiplying the quotient by 100,000. [26] DATASUS3 [26]
 Psychiatric admission [22] NI NI National registry of psychoses NI
 Risk of psychiatric admission [22] NI NI National registry of psychoses NI
 Incidence of readmission for complications related to acute myocardial infarction and death [16] Categorized at 30 days, 6 months and 1 year after discharge NI Discharge database NI
 Percentage of people with an inpatient admission to a hospital in 2007–09 [12] NI NI NI NI
Outpatient services
 Use of outpatient services [13, 24, 27] Sum of outpatient monthly visits, according to the selected ICD [13] NI CMS Medicaid Analytical Extract database [13] NI
Number of use of ambulatory appointments/person/year [27] Ambulatory services dunning data [27] NI [27]
Number of doctor’s appointment in an ambulatory or clinic within one month [24] Insurance companies database [24] Unexpected consequences of the intervention, cushioning the economy with medicines [24]
 Outpatient visits [14, 21, 22] Visits related to DM when ICD was the primary, second or third diagnosis [14] I NI [14] NI [14]
NI [22] National registry of psychoses [22] The intervention can create a financial obstacle resulting in an increase of the use of health services [22]
Mean number of visits [21] U.S. Renal Data System (USRDS)2 [21] NI [21]
 Number of outpatient visits [18, 21, 28] Annual number of visits [18, 21] NI Medical Expenditure Panel Survey (MEPS)1 [18, 21] NI
NI [28] National Sample Cohort4 [28]
 Number of visits to a physician [20] Number of visits to a doctor Number of outpatient visits to a doctor/1000 patient-year PharmaNet database NI
 Number of visits to a doctor [29] NI NI NI NI
 Number of physician office visits [17] NI NI Medical Expenditure Panel Survey (MEPS)1 NI
 Outpatient medical visits [16] Defined as the frequency of outpatient medical visits in the first year after discharge. Includes visits to family doctors, interns and cardiologists in ambulatories, clinics and health centers. NI Administrative database Hypothesis: the frequency of the visits should increase as a response to the pharmaceutical coverage.
 Use of ambulatory healthcare services [30] NI NI NI NA
 Change in the annual number of ambulatory visits [15] NI NI Administrative database Hypothesis: the copayment increase will not increase the use of medical and non-pharmaceutical services
 Rate of use of clinical services [23] Appointments with a diagnosis code related to depression Monthly calculation/1000 elderly PharmaNet database Unexpected consequences of the intervention, cushioning the economy with medicines
 Utilization rate of the psychiatric services [23] Appointments with a diagnosis code related to depression Monthly calculation/1000 elderly PharmaNet database Unexpected consequences of the intervention, cushioning the economy with medicines
 Proportion of general or tertiary hospital utilization [28] The proportion of general or tertiary hospital utilization among total healthcare utilization. (the number of outpatient visits into general or tertiary hospitals per person–month/the number of outpatient visits into total healthcare utilization per person–month) × 100 National Sample Cohort4 NI
Total health services
 Number of use of health services/100 members/month [31] Ambulatory appointments included, use of emergency services and hospitalization NI Administrative data from Oregon’s Medicaid Program NI
Hospital Services
 Use of hospital health services [30] Use of emergency services and hospitalization NI NI NA
Diagnosis and Laboratory services
 Use of laboratory and diagnosis services [14] Visits related to DM when ICD was the primary, second or third diagnosis. NI NI NI
Home visits
 Change in the annual number of home visits [15] NI NI Administrative database Hypothesis: the copayment increase will not increase the use of medical and non-pharmaceutical services
 Other visits [21] Mean number of visits. Includes home health agency, skilled nursing facility, or hospice NI U.S. Renal Data System (USRDS)2 NI
  1. Subtitles: NI Not Informed, DM Diabetes Mellitus, ICD International Classification of Diseases
  2. 1Annual estimates of health care use, cost, payment sources, health insurance coverage, health status, and sociodemographic characteristics for the US civilian, noninstitutionalized population [18]
  3. 2A national registry of subjects with end-stage renal disease based on Medicare claims. This database includes Medicare enrollment history, death dates and causes, and Medicare Parts A and B claims [21]
  4. 3A national database that contains information on epidemiology and morbidity of various diseases that impact on the health of the Brazilian population [26]
  5. 4Data, including all medical claims, from 2010 to 2013 released by the National Health Insurance Service (NHIS), which consists of details of patient healthcare utilization [28]