VITALO-DHD

Describe datasets

The dataset includes 4 tables linked to each other by the patient ID (Opnamenummer). The tables are:

Table 1 gives information about the admission.
Table 2 gives information about all diagnosis of the admission including main diagnosis (the reason of admission), primary diagnosis (diagnosis that has been known at the admission), and secondary diagnosis (diagnosis that has been known during the admission).
Table 3 gives information about the departments where the patient has been admitted and the total duration of care (including a day of visiting)
Table 4 gives information about the DBC cost of the admission. DBC stands for Diagnose Behandeling Combinatie, or in English, Diagnosis Treatment Combination of a care path. DBC healthcare products form the basis of Dutch hospital care finance. This means that patients do not settle each component of the examination or treatment separately, but pay one price for the entire care path. A DBC healthcare product has a maximum duration of 120 days. If a patient has a chronic illness and undergoes long-term treatment, consecutive DBC healthcare products are registered over the years.

The scope of the treatment is important – there is a difference between a patient staying overnight in hospital or returning home immediately. Whether or not a patient needs an operation also makes a difference. The number of visits to the medical specialist can also play a role.

Data manipulation

Categorize patients by infectious disease

Influenza: Patient is categorized in Influenza group if he/she has a diagnosis (either main/primary or secondary) of Influenza (ICD-10: J09, J10.0, J10.1, J10.8, J11.0, J11.1, J11.8)
Pneumonia Patient is categorized in Influenza group if he/she has a diagnosis (either main/primary or secondary) of Pneumonia (ICD-10: A40.3, B95.3, G00.1, J13, J15.3, J18.9, J18.0, J18.2, J18.8, J18.1)
COVID-19: Patient is categorized in Influenza group if he/she has a diagnosis (either main/primary or secondary) of COVID-19 (ICD-10: U07.1, U07.2, U09.9, U10.9)

Categorize patients by Charlson comorbidity index (CCI)

Charlson comorbidity index (CCI) is a method of categorizing comorbidities of patients based on the ICD-10 codes. The CCI score is calculated by summing the scores of each comorbidity. The score of each comorbidity is based on the weight of the comorbidity defined by Charlson et al. (1987) Johnston et al. (2015).
The total CCI score will then be categorized into 4 groups: 0, 1, 2, and 3+.

Categorize patients by age Patients will be categorized into 6 age groups: 50-64, 65-69, 70-74, 75-79, 80-84, and 85+.

Result tables

Overview of the dataset

Characteristic	Sub_characteristic	Number_of_Patients	Percentage_of_Patients
Total		1114	100
By year
	2018	6	0.5
	2019	172	15.4
	2020	258	23.2
	2021	365	32.8
	2022	313	28.1
Age
	50-64	378	33.9
	65-69	191	17.1
	70-74	223	20
	75-79	158	14.2
	80-84	106	9.5
	85+	58	5.2
Primary/secondary infection
	Primary	883	79.3
	Secondary	181	16.2
	Both	22	2
	Neither	28	2.5
Type of infection
	Influenza	95	8.5
	Pneumonia	506	45.4
	COVID-19	539	48.4
CCI
	0	315	28.3
	1	201	18
	2	133	11.9
	3+	465	41.7
ICU admission
	Yes	197	17.7
	No	917	82.3
Mortality
	Yes	113	10.1
	No	1001	89.9

The sample population and infection-related outcomes stratified by age group and CCI

## `summarise()` has grouped output by 'Age_group'. You can override using the
## `.groups` argument.

Age_group	CCI_group	Number_of_Patients	Percentage	Mean_LOS	SD_LOS	ICU_N	ICU_percentage	ICU_LOS_mean	ICU_LOS_SD	Mortality_N	Mortality_percentage	Cost_general	Cost_ICU
All	All	1114	100.0	9.6	11.53	197	17.7	2.0	6.78	113	10.1	7514.2	29573.2
50-64	All	378	33.9	9.8	11.53	88	23.3	2.8	8.44	23	6.1	7535.4	31988.4
65-69	All	191	17.1	10.2	11.53	37	19.4	2.1	7.31	13	6.8	7885.6	29179.0
70-74	All	223	20.0	9.9	11.53	46	20.6	2.3	6.85	19	8.5	7522.2	29695.7
75-79	All	158	14.2	9.5	11.53	23	14.6	1.3	4.20	25	15.8	7966.1	22667.1
80-84	All	106	9.5	8.2	11.53	2	1.9	0.1	0.99	21	19.8	6446.8	16330.2
85+	All	58	5.2	8.1	11.53	1	1.7	0.1	0.39	12	20.7	6848.5	8894.9
50-64	0	147	13.2	8.4	11.53	38	25.9	2.7	6.88	6	4.1	7154.4	27499.9
50-64	1	66	5.9	9.0	11.53	8	12.1	1.5	6.82	3	4.5	8071.8	35516.4
50-64	2	46	4.1	11.7	11.53	10	21.7	3.4	9.65	1	2.2	7755.9	43038.9
50-64	3+	119	10.7	11.2	11.53	32	26.9	3.4	10.31	13	10.9	7621.7	32953.2
65-69	0	54	4.8	10.9	11.53	12	22.2	2.9	10.13	2	3.7	7191.4	34833.6
65-69	1	35	3.1	6.4	11.53	2	5.7	0.2	0.75	2	5.7	6021.6	6682.6
65-69	2	21	1.9	10.1	11.53	4	19.0	3.7	10.53	2	9.5	6634.2	52379.7
65-69	3+	81	7.3	11.5	11.53	19	23.5	2.0	5.31	7	8.6	9478.2	23091.4
70-74	0	58	5.2	10.8	11.53	15	25.9	4.1	9.73	3	5.2	7518.4	42388.2
70-74	1	38	3.4	8.9	11.53	1	2.6	0.1	0.49	2	5.3	8268.0	7819.1
70-74	2	27	2.4	8.9	11.53	7	25.9	3.1	8.24	1	3.7	5586.0	30658.1
70-74	3+	100	9.0	10.0	11.53	23	23.0	1.9	5.34	13	13.0	7768.7	22076.3
75-79	0	30	2.7	9.2	11.53	6	20.0	2.2	6.73	1	3.3	6461.0	27516.3
75-79	1	33	3.0	7.4	11.53	2	6.1	0.3	1.26	5	15.2	7527.3	11054.6
75-79	2	22	2.0	6.1	11.53	2	9.1	1.1	4.49	4	18.2	5667.2	32076.5
75-79	3+	73	6.6	11.6	11.53	13	17.8	1.4	3.58	15	20.5	9455.1	20768.0
80-84	0	14	1.3	8.6	11.53	0	0.0	0.0	0.00	1	7.1	5991.4	NaN
80-84	1	18	1.6	6.2	11.53	0	0.0	0.0	0.00	1	5.6	5492.8	NaN
80-84	2	10	0.9	7.1	11.53	0	0.0	0.0	0.00	2	20.0	6648.4	NaN
80-84	3+	64	5.7	8.9	11.53	2	3.1	0.2	1.27	17	26.6	6788.5	16330.2
85+	0	12	1.1	6.2	11.53	0	0.0	0.0	0.00	3	25.0	5396.5	NaN
85+	1	11	1.0	8.4	11.53	1	9.1	0.3	0.90	2	18.2	6129.2	8894.9
85+	2	7	0.6	7.7	11.53	0	0.0	0.0	0.00	0	0.0	5954.6	NaN
85+	3+	28	2.5	8.9	11.53	0	0.0	0.0	0.00	7	25.0	7976.9	NaN

Influenza

## `summarise()` has grouped output by 'Age_group'. You can override using the
## `.groups` argument.

Age_group	CCI_group	Number_of_Patients	Percentage	Mean_LOS	SD_LOS	ICU_N	ICU_percentage	ICU_LOS_mean	ICU_LOS_SD	Mortality_N	Mortality_percentage	Cost_general	Cost_ICU
All	All	95	100.0	7.6	11.53	15	15.8	1.1	4.30	4	4.2	5991.5	17855.1
50-64	All	28	29.5	6.0	11.53	5	17.9	2.2	7.49	0	0.0	4116.9	32552.3
65-69	All	21	22.1	7.4	11.53	4	19.0	0.7	1.65	1	4.8	7130.2	9998.5
70-74	All	19	20.0	9.2	11.53	4	21.1	0.9	2.27	0	0.0	6800.6	12089.4
75-79	All	11	11.6	8.5	11.53	1	9.1	0.3	0.90	0	0.0	7061.7	7819.1
80-84	All	9	9.5	6.2	11.53	0	0.0	0.0	0.00	2	22.2	5564.5	NaN
85+	All	7	7.4	11.1	11.53	1	14.3	0.4	1.13	1	14.3	6745.3	8894.9
50-64	0	12	12.6	6.4	11.53	1	8.3	2.8	9.81	0	0.0	4105.3	88616.6
50-64	1	5	5.3	5.2	11.53	0	0.0	0.0	0.00	0	0.0	4809.8	NaN
50-64	2	7	7.4	5.1	11.53	2	28.6	0.7	1.25	0	0.0	4273.5	7099.2
50-64	3+	4	4.2	7.2	11.53	2	50.0	5.8	10.84	0	0.0	3011.2	29973.3
65-69	0	10	10.5	8.3	11.53	3	30.0	1.3	2.21	0	0.0	8005.8	11354.7
65-69	1	4	4.2	4.2	11.53	0	0.0	0.0	0.00	1	25.0	7318.6	NaN
65-69	2	2	2.1	6.0	11.53	0	0.0	0.0	0.00	0	0.0	4133.4	NaN
65-69	3+	5	5.3	8.8	11.53	1	20.0	0.4	0.89	0	0.0	6427.3	5929.9
70-74	0	7	7.4	8.3	11.53	1	14.3	1.3	3.40	0	0.0	6538.0	23865.5
70-74	1	2	2.1	12.0	11.53	0	0.0	0.0	0.00	0	0.0	10003.8	NaN
70-74	3+	10	10.5	9.2	11.53	3	30.0	0.9	1.52	0	0.0	6343.7	8164.0
75-79	0	3	3.2	15.7	11.53	0	0.0	0.0	0.00	0	0.0	10613.4	NaN
75-79	1	2	2.1	4.0	11.53	0	0.0	0.0	0.00	0	0.0	5267.2	NaN
75-79	2	2	2.1	7.0	11.53	0	0.0	0.0	0.00	0	0.0	5137.9	NaN
75-79	3+	4	4.2	6.0	11.53	1	25.0	0.8	1.50	0	0.0	6257.1	7819.1
80-84	0	2	2.1	5.5	11.53	0	0.0	0.0	0.00	0	0.0	6207.5	NaN
80-84	1	4	4.2	8.5	11.53	0	0.0	0.0	0.00	0	0.0	6449.0	NaN
80-84	2	1	1.1	2.0	11.53	0	0.0	0.0	NA	1	100.0	3734.0	NaN
80-84	3+	2	2.1	4.5	11.53	0	0.0	0.0	0.00	1	50.0	4067.7	NaN
85+	0	2	2.1	8.5	11.53	0	0.0	0.0	0.00	0	0.0	4897.7	NaN
85+	1	5	5.3	12.2	11.53	1	20.0	0.6	1.34	1	20.0	7484.4	8894.9

Pneumonia

## `summarise()` has grouped output by 'Age_group'. You can override using the
## `.groups` argument.

Age_group	CCI_group	Number_of_Patients	Percentage	Mean_LOS	SD_LOS	ICU_N	ICU_percentage	ICU_LOS_mean	ICU_LOS_SD	Mortality_N	Mortality_percentage	Cost_general	Cost_ICU
All	All	506	100.0	9.3	11.53	55	10.9	0.9	4.65	54	10.7	8427.8	22944.7
50-64	All	146	28.9	10.8	11.53	24	16.4	1.7	7.06	12	8.2	9986.8	29274.7
65-69	All	82	16.2	8.4	11.53	10	12.2	0.9	3.63	7	8.5	8150.0	19064.0
70-74	All	109	21.5	9.2	11.53	13	11.9	0.9	4.55	7	6.4	8244.4	21214.5
75-79	All	80	15.8	9.1	11.53	6	7.5	0.2	1.14	11	13.8	8193.0	8991.2
80-84	All	57	11.3	8.5	11.53	2	3.5	0.2	1.35	11	19.3	6758.7	16330.2
85+	All	32	6.3	7.4	11.53	0	0.0	0.0	0.00	6	18.8	6291.0	NaN
50-64	0	52	10.3	9.9	11.53	9	17.3	2.1	8.53	4	7.7	10378.7	33680.2
50-64	1	31	6.1	13.4	11.53	6	19.4	2.9	9.66	2	6.5	11301.9	42366.8
50-64	2	11	2.2	11.5	11.53	1	9.1	0.3	0.90	0	0.0	10572.7	7819.1
50-64	3+	52	10.3	10.1	11.53	8	15.4	1.0	3.46	6	11.5	8642.9	18525.1
65-69	0	26	5.1	6.6	11.53	0	0.0	0.0	0.00	1	3.8	6319.7	NaN
65-69	1	15	3.0	6.7	11.53	1	6.7	0.1	0.52	1	6.7	5936.0	5346.1
65-69	2	9	1.8	10.1	11.53	2	22.2	3.8	8.74	1	11.1	7927.6	45660.6
65-69	3+	32	6.3	10.1	11.53	7	21.9	1.1	3.34	4	12.5	10737.6	13424.6
70-74	0	28	5.5	9.4	11.53	5	17.9	2.8	8.65	1	3.6	7971.4	43373.5
70-74	1	20	4.0	10.0	11.53	1	5.0	0.1	0.67	1	5.0	8636.7	7819.1
70-74	2	14	2.8	5.1	11.53	2	14.3	0.4	1.16	0	0.0	4713.2	7819.1
70-74	3+	47	9.3	9.9	11.53	5	10.6	0.3	1.06	5	10.6	9292.0	7092.6
75-79	0	13	2.6	5.1	11.53	1	7.7	0.1	0.28	1	7.7	6069.5	2965.0
75-79	1	21	4.2	7.8	11.53	1	4.8	0.1	0.44	2	9.5	8821.7	5929.9
75-79	2	11	2.2	5.8	11.53	1	9.1	0.3	0.90	2	18.2	5961.4	8019.1
75-79	3+	35	6.9	12.3	11.53	3	8.6	0.4	1.61	6	17.1	9184.5	12344.5
80-84	0	6	1.2	10.5	11.53	0	0.0	0.0	0.00	0	0.0	6556.8	NaN
80-84	1	11	2.2	5.8	11.53	0	0.0	0.0	0.00	1	9.1	5314.9	NaN
80-84	2	6	1.2	6.8	11.53	0	0.0	0.0	0.00	0	0.0	7379.1	NaN
80-84	3+	34	6.7	9.3	11.53	2	5.9	0.4	1.74	10	29.4	7163.9	16330.2
85+	0	8	1.6	5.6	11.53	0	0.0	0.0	0.00	3	37.5	5398.9	NaN
85+	1	5	1.0	6.0	11.53	0	0.0	0.0	0.00	1	20.0	5499.6	NaN
85+	2	6	1.2	8.8	11.53	0	0.0	0.0	0.00	0	0.0	6346.9	NaN
85+	3+	13	2.6	8.4	11.53	0	0.0	0.0	0.00	2	15.4	7118.6	NaN

Exporting tables to an excel file is possible

References

Charlson, M. E., P. Pompei, K. L. Ales, and C. R. MacKenzie. 1987. “A new method of classifying prognostic comorbidity in longitudinal studies: development and validation.” Journal of Chronic Diseases 40 (5): 373–83. https://doi.org/10.1016/0021-9681(87)90171-8.

Johnston, Marjorie C., Angharad Marks, Michael A. Crilly, Gordon J. Prescott, Lynn M. Robertson, and Corri Black. 2015. “Charlson Index Scores from Administrative Data and Case-Note Review Compared Favourably in a Renal Disease Cohort.” European Journal of Public Health 25 (3): 391–96. https://doi.org/10.1093/eurpub/cku238.