baseline study on bed management in hospitals in the volta region

7/28/2019 Baseline Study on Bed Management in Hospitals in the Volta Region

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BASELINE STUDY ON BED MANAGEMENT IN HOSPITALS IN THE VOLTA

REGION, A CASE STUDY OF HO MUNICIPAL HOSPITAL USING 2005 DATA

INTRODUCTION

Resource management is very critical in the health care delivery in every country

especially in the developing countries such as Ghana where financial resource arewoefully inadequate. A good resource management goes a long way in improving the

total Quality of Care to the clients and needs to be vigorously pursued.

Resources critical to health care delivery aside financial include basic equipment such asefficient weighing scales, BP Apparatus, Thermometers, spectrophotometers, theaters

equipment, etc. In inpatient care delivery one major resource that is critical in service

delivery are the Inpatient Beds.

Bed management in the hospital includes the judicious use of the beds such as itsallocation, its maintenance, its usage in the wards, etc to enhance quality service to the

clients.

The management of hospital care raises important issues at different levels and in

different ways. They include larger-scale issues such as the organization and deploymentof overall bed provision within a hospital, different ways of progressing patients between

areas of the hospital which provide for differing levels of, for example, nursingdependency, and the effective integration of bed use with other aspects of hospital care

such as the use of investigative facilities and the scheduling of operating theatres. The

competence of hospital information systems for the ongoing monitoring of performanceand feedback to operational policies forms part of this management environment.

A quick look at the National indicators especially in 1998, indicate that Bed Occupancy,

and Bed Turnover Rate, and also Average Length of stay, which are the major

determinants or indicators of efficient use of Hospital Beds are not the best in the VoltaRegion.

The low nature of the utilization indicators in the Volta region may be partiallyattributable to the allocation of the Bed in the various Hospitals. This needs to beseriously assessed to ensure the judicious use of our resources in the region.

PROBLEM STATEMENT

Ho municipal Hospital is one of the Hospitals in the Region that has been seen as

performing badly in terms of utilization of Hospital resources such as beds. When the

Hospital was the Regional Hospital it used about 250 Beds. Later when it was

redesignated to a District Hospital Bed compliment was reduced to 150.A look at the Bed occupancy rate and Bed Turnover rate revealed that since the

redesignation of the Hospital, these indicators have been found to be declining. A look at

the expenditure pattern has also been found to be increasing disproportionately. It istherefore necessary to analyze the utilization indicators so as to recommend the effective

bed compliment to use and thereby reducing unnecessary expenditures with regards to

management of the wards.

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RATIONALE OF THE STUDY

It is envisaged that this study will reveal the rational Bed Usage in the Hospitals thereby

ensuring proper resource management.The study will also be a reference for other hospitals having similar problem and thereby

ensuring efficient use of our resources and conserving enough money for other activities.

CONCEPTUAL FRAMEWORK

The Bed utilization indicators of hospitals in the Volta Region are low and hence

implying that there is inefficient utilization of resources.

GENERAL OBJECTIVES OF THE STUDY

This study seeks to assess factors contributing to inefficient bed management in the

Hospital.

SPECIFIC OBJECTIVES

To develop insights on the impact of size, average length of stay, variability, andorganization of clinical services on the relationship between occupancy rates.

To recommend an efficient bed allocation to each ward so as to improve upon the

utilization indicators and also reduce wastage.

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LITERATURE REVIEW

Although there is extensive literature related to the management of hospital resources,very little of it addressed the bed management and its allocation. In the field of operations

research, capacity planning in hospitals has been the subject of several studies (Hershey,Weiss, and Cohen 1981; Dumas 1984, 1985; Vassilacopoulos 1985; Worthington 1987).

However, these have focused on the detailed assessment of allocation and schedulingrules or on the development of models for specific facilities. In the economics literature,

Graham and Cowing (1997) studied the determinants of hospital reserve margins--beds in

excess of average patient census. Their results indicate that larger hospitals and hospitalswith more diverse clinical services have smaller reserve margins, indicating both

economies of scale and scope. Research on the cost of empty hospital beds has been the

subject of several studies, including Schwartz and Joskow (1980), Friedman and Pauly(1981, 1983), Pauly and Wilson (1986), and, more recently, Gaynor and Anderson (1995)

and Keeler and Ying (1996).

Much of this work is framed as estimating the cost of excess capacity, which is defined as

the average unutilized capacity. Yet, uncertain demands and lengths of stay require thathospitals operate at less than 100 percent utilization in order not to turn away a large

percentage of patients, and therefore it is unclear at what occupancy level a hospital truly

has excess capacity, that is, more than needed to provide a target level of service. Gaynorand Anderson (1995) explicitly incorporate this concept of capacity choice being

dependent on a target probability of turning away patients in their calculation of the cost

of an empty bed.

In America, target occupancy levels were originally developed at the federal government

level in the 1970s to control accelerating health care costs (McClure 1976). Theseoccupancy targets were the result of analytical modeling for "typical" hospitals in various

size categories and were based on "acceptable" delays. Historically, the most commonlyused occupancy target has been 85 percent, and current estimates of the number of

"excess" beds are usually based on this "optimal" occupancy figure (Brecher and Speizio

1995, p. 55). (The current average occupancy rate for nonprofit hospitals is about 63%

AHA 1996.) In recent years, some managers of large hospitals have used target levelsgreater than the traditional 85 percent because of increased financial pressures. Research

from queuing theory (Whitt 1992) and economics (Lynk 1995) support the conclusion

that larger clinical units can achieve higher utilization levels than smaller ones in tryingto achieve a given patient delay objective. While Pauly and Wilson (1 986) found no

explicit relationship between occupancy level and cost, the more recent work of Keeler

and Ying (1996) found that increasing utilization of beds lowers costs.

A look at the 2005 Programme of Work, MOH, 2005, revealed that Bed Occupancy rateof Ghana ranges from 64.1%- 65.5% over the 4 years. This means that most of the Public

Hospitals are operating below 85% Occupancy rate, the ideal case in most developed

countries.

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TABLE 4.2 MONTHLY BED OCCUPANCY RATES OF WARDS AND THE

HOSPITAL 2005

MONTH MALE FEMALE CHILDREN MATERNITY LABOUR NURSERY

MEDICAL

ANNEX HOSPITAL

JANUARY 49.77 55.76 55.28 55.30 26.77 300.00 28.87 53.55

FEBRUARY 41.96 60.59 61.20 57.91 27.68 413.39 43.21 59.40

MARCH 28.00 51.84 26.83 52.65 39.19 321.77 45.16 48.49

APRIL 43.45 66.90 34.09 38.10 43.67 255.00 34.00 49.87

MAY 36.75 62.56 45.75 45.51 46.94 414.52 43.71 56.88

JUNE 34.29 65.71 44.24 35.95 29.50 234.17 29.33 45.96

JULY 35.83 65.78 50.00 31.68 20.16 192.74 23.87 43.23

AUGUST 43.78 60.71 63.93 21.08 20.97 183.06 19.03 43.03

SEPTEMBER 41.67 53.33 67.12 31.79 30.50 157.50 28.67 45.60

OCTOBER 31.80 46.20 43.26 35.02 22.74 107.26 16.61 35.55NOVEMBER 40.95 51.67 26.36 55.83 30.00 202.50 11.50 42.51

DECEMBER 45.05 54.61 41.20 39.52 23.23 136.29 4.19 39.31

ANNUAL

BOR 39.44 57.97 46.61 41.69 30.11 243.18 27.35 46.95

FEMALE WARD

The above Table revealed that the most Occupied Ward in 2005 was the Female Ward. It

has an Occupancy Rate of 57.97%.

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MONTHLY BED OCCUPANCY RATE IN THE FEMALE WARD-2005

55.76

60.59

51.84

66.90

62.56

65.71 65.78

60.71

53.33

46.20

51.67

54.61

57.97

0.00

10.00

20.00

30.00

40.00

50.00

60.00

70.00

80.00

JANU

ARY

FEBR

UARY

MAR

CH

APRIL

MAY

JUNE

JULY

AUGUS

T

SEPTEM

BE

OCTOBER

NOVEMBE

R

DECEMBER

ANNUA

LBO

R

MONTH

BOR(%

From the graph it could be seen that Bed Occupancy Rate was high in February, April,

May, June, July and August i.e. above the Average Annual Bed Occupancy in 2005. In

the rest of the months, thus January, March, September, October, November andDecember, Bed Occupancy Rates were below the Average Annual Bed Occupancy Rate

of the Hospital.

The trend Analysis of the Bed Occupancy Rate revealed a downward trend indicated byFitted Trend Equation as Yt = 62.6476 - 0.719371*t where t represents months/period.

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Actual

Fits

ActualFits

1050

65

55

45

FEMALE

Time

Yt = 62.6476 - 0.719371*t

MSD:

MAD:

MAPE:

34.6325

5.0997

8.9459

Trend Analysis for FEMALELinear Trend Model

MALE WARD

The graph below depicts the monthly distribution of the Bed Occupancy Rate in the maleWard. The Annual Bed Occupancy Rate of the Ward Stood at 39.44%. This figure

indicate that resource management in the Male Ward is not efficient, thus resources such

as Beds, Cubicles etc are underutilized in the wards.

BED OCCUPANCY RATE FOR MALE WARD-2005

0.00

10.00

20.00

30.00

40.00

50.00

60.00

JANU

ARY

FEBR

UARY

MAR

CH

APRIL

MAY

JUNE

JULY

AUGUS

T

SEPTEM

BE

OCTOBER

NOVEMBE

R

DECEM

BER

ANNUA

LBO

R

MONTH

%OCCUPANCYRAT

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From the above it could be realized that Bed Occupancy Rates were very low below the

Annual Average in March, May, June, July and October. The Trend of the Bed

Occupancy Rate is shown in the Figure below.

Actual

Fits

Actual

Fits

1050

50

40

30

MALE

Time

Yt = 39.9117 - 7.23E-02*t

MSD:

MAD:MAPE:

35.1655

5.107813.7888

Trend Analysis for MALE

Linear Trend Model

The above figure revealed that the fitted linear equation of the trend is BOR= 39.91-0.07t

where t is the period.CHILDRENS WARD

The graphs below depicts the performance and efficiency of the Childrens Ward in terms

of Bed Occupancy Rate.

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The fitted equation of the trend above is BOR=49.5-0.45t where t is the period.

MEDICAL ANNEX

This ward appears to be one of the wards that have the lowest Bed Occupancy Rate.

BED OCCUPANCY RATE OF MEDICAL ANNEX WARD-2005

28.87

43.2145.16

34.00

43.71

29.33

23.87

19.03

28.67

16.61

11.50

4.19

27.35

0.00

5.00

10.00

15.00

20.00

25.00

30.00

35.00

40.00

45.00

50.00

JANU

ARY

FEBR

UARY

MAR

CH

APRIL

MAY

JUNE

JULY

AUGUS

T

SEPTEM

BER

OCTOBER

NOVEMBE

R

DECEMBER

ANNUA

LBO

R

MONTH

%O

CCUPANC

The above graph indicates that in July, August, October, November and December, BedOccupancy rates were below the Annual Bed Occupancy rate of the Ward.

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Actual

Fits

ActualFits

1050

50

40

30

20

10

0

MEDICAL

Time

Yt = 46.9565 - 3.01703*t

MSD:

MAD:MAPE:

47.6015

5.120528.4475

Trend Analysis for MEDICALLinear Trend Model

The trend above indicate a fitted trend equation of BOR=46.96-3.02t.

MATERNITY WARD

The graph below shows the monthly distribution of the Bed occupancy Rate of the

Maternity Ward.

BED OCCUPANCY RATE OF MATERNITY WARD-2005

55.30 57.91

52.65

38.10

45.51

35.95

31.68

21.08

31.7935.02

55.83

39.5241.69

0.00

10.00

20.00

30.00

40.00

50.00

60.00

70.00

JANU

ARY

FEBR

UARY

MARCH

APRIL MAY JUNE JU

LY

AUGUST

SEPTEM

BE

OCTOBER

NOVEMBER

DECEMBE

R

ANNUA

LBOR

MONTH

%OCCUPANC

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From the above graph shows that Bed occupancy Rates in April, June, July, August,

September, October and December were below than Annual Bed Occupancy Rate of the

Ward. The trend analysis is shown clearly by the graph below.

Actual

Fits

Actual

Fits

1050

60

50

40

30

20

MATERNIT

Time

Yt = 51.35 - 1.48538*t

MSD:

MAD:MAPE:

98.7899

8.187222.5483

Trend Analysis for MATERNITLinear Trend Model

The fitted equation of the trend indicate that BOR= 51.35-1.49t.

LABOUR WARD

The graph below depicts the Monthly distribution of the Bed occupancy Rate on the

Labour Ward.

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BED OCCUPANCY RATE OF THE LABOUR WARD-2005

26.77 27.68

39.19

43.67

46.94

29.50

20.16 20.97

30.50

22.74

30.00

23.23

30.11

0.00

5.00

10.00

15.00

20.00

25.00

30.00

35.00

40.00

45.00

50.00

JANUA

RY

FEBR

UARY

MAR

CH

APRIL

MAY

JUNE

JULY

AUGUS

T

SEPTEM

BER

OCTOBER

NOVEMBE

R

DECEM

BER

ANNUA

LBO

R

MONTH

%OCCUPANC

In January, February, June, July August October November and December, Bed

Occupancy Rates were below the Average Annual Bed Occupancy Rate of the Ward.

The trend Analysis is shown in the graph below:

Actual

Fits

Actual

Fits

1050

50

40

30

20

LABOUR

Time

Yt = 36.6195 - 1.00108*t

MSD:

MAD:

MAPE:

59.0041

6.5395

22.0378

Trend Analysis for LABOURLinear Trend Model

The fitted equation of the Trend indicate an equation as BOR=36.62-1.00t.

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In analyzing the number of days Bed Occupancy Rate was more than 50% in each ward

the graph below indicates that in the Nursery, the Bed occupancy Rate was more than

50% in 359 days. In the Female Ward it was revealed that on 267 days the Bed

Occupancy Rate was more than 50%. Furthermore, In the Childrens ward it was more

than 50% on 163 days, in Maternity Ward 110 Days, Male ward 92 days, Labour ward 45

days and Medical Annex Ward 26 days. The analysis revealed that in the Hospital as a

whole, there were only 131 days that the Bed Occupancy rate exceeded 50%.

NUMBER OF DAYS BED OCCUPANCY RATE WAS GREATER THAN 50%

92

267

163

110

45

359

26

131

0 50 100 150 200 250 300 350 400

MALE

FEMALE

CHILDREN

MATERNITY

LABOUR

NURSERY

MEDICAL ANNEX

HOSPITAL

WARD

NO. OF DAYS

Further analysis to see how many days that the Bed Occupancy was more than 85%

revealed that in the Male Ward and the Medical Annex Ward Bed Occupancy has never

being over 85%. Also, the Hospital as whole did not have a Bed occupancy Rate which

was above 85% on a single day through out the year.

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In the Nursery, the Bed occupancy Rate was more than 85% in 339 days whilst in the

female ward and childrens ward there were 13 days that the Bed occupancy Rate was

more than 85%. In the Labour ward and the Maternity wards Bed occupancy was over

85% on 1 day and 4 days respectively.

The above analysis is depicted by the graph below:

NUMBER OF DAYS BED OCCUPANCY RATE WAS MORE THAN 85%

0

13

13

4

1

339

0

0

0 50 100 150 200 250 300 350 400

MALE

FEMALE

CHILDREN

MATERNITY

LABOUR

NURSERY

MEDICAL ANNEX

HOSPITAL

WARD

NO. OF DAYS

Again, to find out the number of days that the Bed Occupancy was above 90%, it was

found out that Female Ward had 5 days, Childrens Ward 6 days, Maternity Ward 1 day

and Nursery Ward 339 days.

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However, for more than 100% Bed Occupancy Rate it was revealed that only Childrens

Ward was 2 days, Maternity Ward 1 day and Nursery 339 days.

BED OCCUPANCY RATE IN THE VARIOUSWARDS-2005

92

267

163

110

45

359

26

131

23

169

96

5123

353

11

37

013 13

4 1

339

0 00 5 6 1 0 0 00 0 2 1 0 0 0

339339

0

40

80

120

160

200

240

280

320

360

400

MALE FEMALE CHILDREN MATERNITY LABOUR NURSERY MEDICAL

ANNEX

HOSPITAL

WARD

NOOFDAY

NO OF DAYS BOR >=50% NO. OF DAYS BOR >=60% NO. OF DAYS BOR >=85%

NO. OF DAYS BOR>=90% NO. OF DAYS BOR>=100%

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AVERAGE LENGTH OF STAY

AVERAGE LENGTH OF STAY

The Table below presents the Average length of stay for each ward in the

Hospital.

TABLE 4.2 MONTHLY AVERAGE LENGTH OF STAY OF WARDS AND

THE HOSPITAL

MONTH MALE FEMALE CHILDREN MATERNITY LABOUR NURSERY

MEDICAL

ANNEX HOSPITAL

JANUARY 4.65 4.79 4.96 9.41 2.08 4.54 44.75 5.11

FEBRUARY 3.58 4.52 4.05 6.14 2.77 6.71 34.57 5.03

MARCH 3.08 4.25 3.33 6.44 2.17 3.22 28.00 4.05

APRIL 4.24 4.19 3.95 5.16 2.47 3.00 34.00 4.06

MAY 3.47 4.34 3.51 7.60 2.35 3.78 54.20 4.25

JUNE 3.65 4.21 4.29 4.25 1.82 2.32 44.00 3.62

JULY 3.62 4.11 3.92 4.91 1.58 2.54 29.60 3.68

AUGUST 4.09 3.74 4.64 3.98 1.55 2.29 23.60 3.56

SEPTEMBER 4.61 3.76 5.83 4.94 2.08 1.93 24.57 3.96

OCTOBER 3.00 3.61 3.28 4.83 1.57 1.56 51.50 3.10

NOVEMBER 3.87 4.02 2.49 5.52 1.58 1.83 11.50 3.16

DECEMBER 3.95 3.20 3.19 4.45 1.92 2.04 13.00 3.20

ANNUAL

AVERAGE 3.81 4.06 3.95 5.64 1.99 2.98 32.77 3.90

MATERNITY, LABOUR AND NURSERY WARDS

Reviewing the Table 4.1 above revealed that the Average Length of stay in

Maternity Ward has shown a continuous decline. This phenomenon could be

partially explained by the case mix in the Ward comprising Gynaecological

conditions, Caesarean Sections and other obstetrics cases found in that

ward. Also, a close observation of the length of stay revealed that the

months in which lowest Average length of stays were recorded were the

period after the introduction of the free delivery i.e. in June. A similar

phenomenon has been revealed in the Labour Ward and the Nursery (These

wards constitute the Obstetrics and Gynaecological Unit of the Hospital).

This means that quality of care may be compromised by discharging the

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clients early. This situation was found after the introduction of the free

delivery in June. ???????

Actual

Fits

Actual

Fits

1050

10

9

8

7

6

5

4

maternit

Time

Yt = 7.51561 - 0.289196*t

MSD:

MAD:

MAPE:

1.2510

0.9230

16.3946

Trend Analysis for maternitLinear Trend Model

The linear trend analysis of the Maternity Ward indicated a linear model as

ALOS=7.52-0.29t where t is the period.

The trend for the Labour Ward is also shown in the graph below

Actual

Fits

Actual

Fits

1050

2.5

2.0

1.5

Labour

Time

Yt = 2.47818 - 7.43E-02*t

MSD:

MAD:

MAPE:

0.0805

0.2630

13.3795

Trend Analysis for LabourLinear Trend Model

This graph also indicated a fitted linear equation of ALOS= 2.48-7.44t.

Also the nursery showed a similar trend as indicated in the graph below

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Actual

Fits

ActualFits

1050

7

6

5

4

3

2

1

Nursery

Time

Yt = 5.08545 - 0.323916*t

MSD:

MAD:

MAPE:

0.7059

0.6226

20.4405

Trend Analysis for NurseryLinear Trend Model

The graph showed a fitted linear equation of ALOS= 5.09-0.32t.

MEDICAL ANNEX WARD

The high Average Length of Stay in the Medical Annex Ward is due to the

Admission of Tuberculosis Patients in that ward. The Average Number of

Days spent by this category of patients is about a month. The graph below

indicates the trend of Average Length of Stay in the Medical Annex Ward.

Actual

Fits

Actual

Fits

1050

55

50

45

40

35

30

25

20

15

10

med.ann

Time

Yt = 45.1771 - 1.90815*t

MSD:

MAD:

MAPE:

132.598

9.287

34.261

Trend Analysis for med. annLinear Trend Model

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MALE WARD

The Male ward also revealed an annual average Length of stay of 3.8 days.

The graph below depicts the trend over the year and the fitted equation of

ALOS= 3.86-0.0069t. The fitted Trend also revealed a steady trend of

Average Length of Stay over the period under review.

Actual

Fits

Actual

Fits

1050

4.5

4.0

3.5

3.0

male

Time

Yt = 3.86227 - 6.89E-03*t

MSD:

MAD:

MAPE:

0.2537

0.4244

11.3856

Trend Analysis for maleLinear Trend Model

FEMALE WARD

In the Female ward the Annual Average Length of stay stood at 4.06 days. This is well

depicted by the Trend Analysis diagram below with a fitted equation of ALOS=4.76-0.11t. The above graph indicate a downward trend of the Monthly Average Length of

Stay.

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Actual

Fits

ActualFits

1050

5

4

3

female

Time

Yt = 4.75530 - 0.106713*t

MSD:

MAD:MAPE:

0.03404

0.149153.78842

Trend Analysis for femaleLinear Trend Model

CHILDRENS WARD

The graph below depicts the Trend Analysis of the Average length of stay in theChildrens ward.

Actual

Fits

Actual

Fits

1050

6

5

4

3

children

Time

Yt = 4.44061 - 7.50E-02*t

MSD:

MAD:MAPE:

0.6741

0.626816.1372

Trend Analysis for childrenLinear Trend Model

The trend analysis indicate a fitted linear trend with the equation ALOS=4.44-0.075t

THE HOSPITAL

The trend Analysis for the Hospital in general revealed a continuous downward trend.

The fitted linear equation is ALOS=4.97-0.16t.

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Actual

Fits

ActualFits

1050

5

4

3

Hospital

Time

Yt = 4.96652 - 0.164336*t

MSD:

MAD:

MAPE:

0.08111

0.24739

6.22644

Trend Analysis for HospitalLinear Trend Model

It can be deduced from the above trend that the Average length of stay from the

Obstetrics and Gynaecological Unit has some impact on the general trend of the ALOS inthe Hospital.

In order to find the correlation between the Average length of Stay of the Hospital and

the various Wards, it was revealed that strong positive correlations exist between the

Average Length of stay of the Hospital and those in the Nursery (0.89) Female (0.82),Labour (0.76) and Maternity (0.74) wards. The correlations between the Average length

of stay of the Hospital and the Medical Annex (0.38), Male (0.30), and Childrens (0.46)

wards are however weak.

ESTIMATION OF REQUIRED NUMBER OF BEDS BY THE FEMALE WARD

Based on the current indicators such as, the Average length of stay, Bed Occupancy Rate

and the number of days the Occupancy rate was at least 80%, the required number of

Beds estimated for efficient service delivery in the Female Ward stood at 20 Beds.This figure is based on the fact that at least 80% of the available Bed Days will be

occupied in the Ward daily. When this is done it implies that part of the cubicles need to

be closed so that the use of Non-consumables, Cleaning and Cleansing materials could bereduced. Also the consumption of water and other resources could be reduced as a result

of the reduction of the Bed compliment.

baseline study on bed management in hospitals in the volta region

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