2017 Mutu Sesi 13 TL Using Data for QI

(1)

Using Data

Improvemen

TRISASI LESTARI - 2017

ta for Quality

ent

(2)

Puskesma

Yogyakar

pelaya

kesehatann

berm

as mana di

karta yang

ayanan

annya paling

rmutu?

(3)

Rumah Sakit

paling ba

penangana

Demam B

kit mana yang

baik untuk

(4)

Spesialis Be

yang operas

aman dan o

bai

Bedah mana

rasinya paling

outcomenya

aik?

(5)

USNEWS

RANKING

2016-2017

USNEWS

RANKING

2016-2017

(6)

(7)

(8)

(9)

(10)

(11)

(12)

(13)

(14)

Pertanyaan 2: Bagaima

perubahan yang terjad

perbaikan?

(15)

Sulitnya mengukur

Makan waktu, menambah pekerjaan Makan waktu, menambah pekerjaan

Harus memastikan akurasi data dan konsistensi metode pengambilan data Harus memastikan akurasi data dan konsistensi metode pengambilan data

Terlalu banyak indikator, tapi bukan indikator yang tepat Terlalu banyak indikator, tapi bukan indikator yang tepat Terlalu banyak indikator, tapi bukan indikator yang tepat Terlalu banyak indikator, tapi bukan indikator yang tepat

Indikator terima jadi, tanpa ada proses diskusi Indikator terima jadi, tanpa ada proses diskusi

Bagaimana menggunakan data yg sudah dikumpulkan Bagaimana menggunakan data yg sudah dikumpulkan

Pengumpulan data manual atau otomatis Pengumpulan data manual atau otomatis

Hasil analisis tidak sesuai dengan pendapat manajemen Hasil analisis tidak sesuai dengan pendapat manajemen

ur mutu

Makan waktu, menambah pekerjaan

Harus memastikan akurasi data dan konsistensi metode pengambilan data Harus memastikan akurasi data dan konsistensi metode pengambilan data

Terlalu banyak indikator, tapi bukan indikator yang tepat Terlalu banyak indikator, tapi bukan indikator yang tepat Terlalu banyak indikator, tapi bukan indikator yang tepat Terlalu banyak indikator, tapi bukan indikator yang tepat

Indikator terima jadi, tanpa ada proses diskusi Indikator terima jadi, tanpa ada proses diskusi

Bagaimana menggunakan data yg sudah dikumpulkan Bagaimana menggunakan data yg sudah dikumpulkan

Pengumpulan data manual atau otomatis Pengumpulan data manual atau otomatis

(16)

Manfaat Pengumpu

Membantu mengidentifikasi masalah yang sebenarnya Membantu pengambilan keputusan

Meningkatkan kepercayaan diri manajer Meningkatkan kepercayaan diri manajer

Menjadi petunjuk apa yang sedang terjadi : karakteristik masalah, kapan terjadinya, pola dan trend

Menunjukkan peluang perbaikan mutu

Menunjukkan seberapa jauh proses untuk mencapai target

pulan Data

Membantu mengidentifikasi masalah yang sebenarnya

Meningkatkan kepercayaan diri manajer Meningkatkan kepercayaan diri manajer

Menjadi petunjuk apa yang sedang terjadi : karakteristik masalah, kapan terjadinya, pola dan trend

Menunjukkan peluang perbaikan mutu

(17)

Manfaat Pengumpu

Sebagai pembanding terhadap standar

Membantu tim fokus dan memilih prioritas masalah yang harus ditangani Membantu tim menjual ide perbaikan mutu pada manajemen/direksi Membantu tim menjual ide perbaikan mutu pada manajemen/direksi Membantu memahami hubungan antar bagian

Menghindari tim menyelesaikan masalah hasil dugaan seseorang saja.

Membantu tim mengidentifikasi apakah sudah terjadi perubahan kepada perbaikan atau belum

pulan Data

(

lanjutan

)

Membantu tim fokus dan memilih prioritas masalah yang harus ditangani Membantu tim menjual ide perbaikan mutu pada manajemen/direksi Membantu tim menjual ide perbaikan mutu pada manajemen/direksi Membantu memahami hubungan antar bagian

Menghindari tim menyelesaikan masalah hasil dugaan seseorang saja.

(18)

The more effort you put into understanding

and utilizing data, the more you will be

rewarded in terms of solving the right

problem in the right way .

(The Victorian Quality Council Safety and Quality in Health)

and utilizing data, the more you will be

The more effort you put into understanding

problem in the right way .

(19)

Quality improvement bisa reactive dan proactive.

Reaktif terhadap masalah yang ditemukan dalam data/laporan rutin.

Proaktif dengan menganalisis data untuk mencari celah untuk perbaikan. Quality improvement bisa reactive dan proactive.

Reaktif terhadap masalah yang ditemukan dalam data/laporan rutin.

(20)

(21)

Jenis data

Administrative

Demografi

Statistik

pelayanan

Data finansial

Readmission

Length of stay

Demografi

Statistik

pelayanan

Data finansial

Readmission

Length of stay

(22)

Data

Bangsal

HRD

Gizi

Data

Rawat Jalan Keuangan

HRD

Data

Farmasi

Pendaftaran

Data

Pendaftaran

IGD

(23)

(24)

(25)

(26)

Good Data

Reliable

Unbiased

Valid

(27)

“If I had to reduce my

message for

management to just a

few words, I’d say it al

had to do with

reducing variation

”.

had to do with

reducing variation

”.

(28)

Principles of variatio

1. No two things are exactly alike.

2. Variation in a product or process can be measured

3. Things vary according to a definite pattern.

4. Whenever things of the same kind are measured, a large group of the measurements will tend to cluster around the middle

5. It's possible to determine the shape of the distribution curve for measurements obtained from any process.

6. Variations due to assignable causes tend to distort the normal distribution curve

ation

(29)

Cause of variation

Insidental

n

(30)

(31)

(32)

Basic Data Presentation

1. Deskriptif Statistik

(33)

2. Percentage chan

Prevalence of pressure ulcers before and after intervention

ange

(34)

(35)

(36)

(37)

(38)

(39)

(40)

(41)

Histogram

Shows relative frequencies

Produced from grouped data

Determine the number of classes

2a 1 _{< n} ₂a

n=100, 26 _{< n} ₂7_{= 7 classes}

Get insight into the shape of of the distribution of population

2a 1 _{< n} ₂a

n=100, 26 _{< n} ₂7_{= 7 classes}

Get insight into the shape of of the distribution of population

2a 1 _{< n} ₂a

n=100, 26 _{< n} ₂7_{= 7 classes}

Get insight into the shape of of the distribution of population

2a 1 _{< n} ₂a

n=100, 26 _{< n} ₂7_{= 7 classes}

(42)

(43)

(44)

(45)

(46)

Control chart repr

nosocomial infect

presenting

(47)

Performance improvement Data Chest Pain in Emergency

(48)

(49)

Average CABG M

Before and After implemen

(Slide courtesy of IHI)

Mortality

(50)

A second look at th

2%

the Data

7%

(51)

(52)

(53)

Bagaimana variasi

sistem dengan berj

Shewhart 1920: variasi terkontrol dan tidak terkontrol (special cause)

si dalam sebuah

erjalannya waktu?

(54)

Jenis Variasi

Terkontrol (common cause)

Terkait dengan desain proses Akibat proses regular, penyebab natural, atau biasa.

Mempengaruhi semua outcome proses

Hasilnya stabil

Bisa diprediksikan

Tidak terkontrol (special cause)

Bukan disebabkan karena desain proses

Akibat proses ireguler atau tidak alami

Mempengaruhi sebagian outcome tapi tidak seluruhnya

Hasilnya tidak stabil

Tidak bisa diprediksikan

Terkontrol (common cause)

Terkait dengan desain proses Akibat proses regular, penyebab natural, atau biasa.

Mempengaruhi semua outcome proses

Hasilnya stabil

Bisa diprediksikan

Tidak terkontrol (special cause)

(55)

Shewhart’s Contro

H

as

il

p

e

n

g

u

ku

ran

H

as

il

p

e

n

g

u

ku

ran

Waktu

Biasanya diperlukan 15-20 data points

trol Chart

(CL)

UCL

Upper Control Limit Sigma Limit

(CL)

LCL

(56)

(57)

(58)

Average an

(Xbar-R) Ch

and Range

Chart

(59)

Characteristics of X

1. It comprised of two charts used in tandem

2. It is used when you can collect measurements in subgroups of between two and 10 observations.

3. The data is in time-order

4. The Xbar chart is used to evaluate consistency of process averages

5. It is efficient at detecting relatively large shifts (typically plus or minus 1.5 ? or larger)

6. The R chart is used to evaluate the consistency of process variation.

7. Look at the R chart first; if the R chart is out of control, then the control limits on the Xbar chart are meaningless.

f Xbar-R chart

(60)

Ice Cream Shop

2 scoops = + 6 ounces (~ 170grams)

Control : weigh five

samples every 30 minutes

Sum _ average _ range Ice Cream Shop

2 scoops = + 6 ounces (~ 170grams)

Control : weigh five

samples every 30 minutes

(61)

(62)

Rule

: a point between UCL and LCL is a

NORMAL VARIATION

or

controlled variation in the process

(63)

When the

average

is

outside the limits



the process is out of

control

Something has

happened, you may

be able to identify

the cause and you

have to correct it.

When the

average

is

outside the limits



control

Something has

(64)

When the

range

is

outside the limits



control

R-chart is used to

evaluate

consistency

of the process

If R-chart is out of

control



the average

chart is meaningless

When the

range

is

outside the limits



control

R-chart is used to

evaluate

consistency

of the process

If R-chart is out of

(65)

Determine contro

UCL=

See table constanta control chart

Choose D4 factor that corresponds to the sample size

UCL = D4 x R

UCL=2.114 x 1.35 = 2.854 LCL = 0 , sample size <6 UCL=

Choose D4 factor that corresponds to the sample size

UCL = D4 x R

UCL=2.114 x 1.35 = 2.854 LCL = 0 , sample size <6

(66)

Decision chart

for working

(67)

SAMPLE SIZE=5 UCL=

Find A2 factor that corresponds to the sample size

UCL = X + (A2xR)

UCL= 4.795 + (0.577x1.35) UCL= 4.795 + 0.779

UCL= 5.574 LCL = X-(A2xR) LCL = 4.795-0.779 LCL 4.016

Determine control

limit for Average

SAMPLE SIZE=5 UCL=

UCL = X + (A2xR)

UCL= 4.795 + (0.577x1.35) UCL= 4.795 + 0.779

(68)

Decision chart for working with average

Once you have established the control limits and sta using them in regular operations, a different rule app even a single point, either range (R) or average (X), g

outside a control limit, do not throw out the point. Th clear indication that an assignable cause is present. must find the assignable cause, and correct it.

Decision chart for working with average

start

pplies: If

, goes

(69)

Median and

(Xbar-R) Ch

nd Range

Chart

(70)

MEDIAN AND

RANGE CHART

It is a good chart to use when you know that the process for

delivering or producing a service delivering or producing a service

(1)follows a normal

(bell-shaped) distribution, (2)is not

very often disturbed by

assignable causes, and (3) can be

easily adjusted by the employee. If the process does not meet

(71)

I-MR Chart

Individual and Moving

rt

(72)

• Use if you are only able to take one reading during a time period.

• I chart

• one data point is collected at each point in time

• monitor the process average, process variation and time

• Is used to detects trend and shifts in the data The Individual data must be time-ordered

MR chart

is the difference between consecutive observations

It shows short term variability in the data

It is used to assess stability of the process

Use if you are only able to take one reading during a time period.

I chart

one data point is collected at each point in time

monitor the process average, process variation and time

• Is used to detects trend and shifts in the data

• The Individual data must be time-ordered

• MR chart

• is the difference between consecutive observations

• It shows short term variability in the data

• It is used to assess stability of the process

I chart

Is used to detects trend and shifts in the data

The Individual data must be time-ordered

MR chart

It is used to assess stability of the process

I chart

Is used to detects trend and shifts in the data

The Individual data must be time-ordered

MR chart

(73)

UCL RANGE

Number of Sample = 2 UCL_R= (D4xR_a)

UCL_R= 3.267 x Ra

R_a= total R/number of sample R_a= 38.8 / 24 =1.616

UCL_R= 3.267 x 1.616 UCL_R= 5.28

LCL = 0 (sample <6)

UCL AVERAGE

X= total sample/25 = 701.5/25=28.06 UCLx =X+(2.66xR)

UCLx = 28.06+(2.66x1.616)=32.35 LCLx = 28.06-(2.66x1.616)=23.76

UCL RANGE

Number of Sample = 2 UCL_R= (D4xR_a)

UCL_R= 3.267 x Ra

R_a= total R/number of sample R_a= 38.8 / 24 =1.616

UCL_R= 3.267 x 1.616 UCL_R= 5.28

LCL = 0 (sample <6)

UCL AVERAGE

X= total sample/25 = 701.5/25=28.06 UCLx =X+(2.66xR)

UCLx = 28.06+(2.66x1.616)=32.35 LCLx = 28.06-(2.66x1.616)=23.76

(74)

(75)

Zone B Zone A

Pembagian Zona d

Chart

Zone A Zone B Zone C

Zone C

(CL)

UCL

Upper Control Limit +2 SL

+3 SL

dalam Control

(CL)

LCL

Lower Control Limit -3 SL

(76)

Aturan Control Cha

mengidentifikasi ad

Rule 1: ada 1 point yang terletak di luar +/-3SL

Rule 2: ada 8 point berturut-turut yang terletak diatas atau dibawah center line

Rule 3: ada 6 atau lebih point yang terus naik/turun

Rule 4: ada 2 dari 3 point berturut-turut yang terletak di zona A atau melewati zona A

Rule 5: ada 15 point berturut-turut yang terletak di zona C pada kedua sisi

hart untuk

adanya variasi

Rule 1: ada 1 point yang terletak di luar +/-3SL

Rule 2: ada 8 point berturut-turut yang terletak diatas atau dibawah center line

Rule 3: ada 6 atau lebih point yang terus naik/turun

Rule 4: ada 2 dari 3 point berturut-turut yang terletak di zona A atau melewati zona A

(77)

(78)

Variasi yang unik (special

cause) tidak selalu berarti

jelek, bisa juga menunjukkan

perbaikan dan harus

dianalisis untuk membantu

pengambilan keputusan.

Variasi yang unik (special

perbaikan dan harus

dianalisis untuk membantu

perbaikan dan harus

dianalisis untuk membantu

perbaikan dan harus

(79)

(80)

(81)

(82)

(83)

Time to surfactant

administration of pr

t

(84)

Jenis-jenis control c

X bar and S X bar and R XmR

X-Bar, Rb, Rw CUSUM EWMA

Standardized

P C-chart

ol chart

XmR Deviation

from Nominal X-Bar, Rb, d

EWMA Np P-chart

U-chart Standardized

(85)

Bagaimana menilai

proses perbaikan m

(86)

Run Chart

H

as

il

p

e

n

g

u

ku

ran

Plot the dots

H

as

il

p

e

n

g

u

ku

ran

Waktu

X (Median) Run adalah satu atau lebih data points pada salah satu sisi median yang sama, tidak

termasuk data point yang terletak pada median.

Waktu

(87)

(88)

(89)

(90)

If I had to reduce

my message for

management to just

a few words, I d say

it all had to do with

reducing variation

.

(W.Edwards Deming)

If I had to reduce

my message for

management to just

it all had to do with

reducing variation

.

(W.Edwards Deming)

If I had to reduce

my message for

management to just

reducing variation

.

(W.Edwards Deming)

If I had to reduce

my message for

management to just

reducing variation

.

(91)

(92)

Tugas

1. Identifikasi Gap dalam pelayanan kesehatan dan tantangannya

2. Apa yang ingin anda ubah?

3. Jawab 3 pertanyaan Nolan model

4. Pilih intervensi yang ingin dilakukan (semakin spesifik semakin baik)

5. Buat rencana (Plan)

6. Pilih metode dan alat untuk implementasi perubahan

7. Pilih metode pengumpulan data untuk observasi

8. Pilih metode untuk penyajian data

2017 Mutu Sesi 13 TL Using Data for QI

Using Data

TRISASI LESTARI - 2017

ta for Quality

Bedah mana

ur mutu

Manfaat Pengumpu

pulan Data

pulan Data

and utilizing data, the more you will be

The more effort you put into understanding

problem in the right way .

Jenis data

Good Data

ation

Cause of variation

Prevalence of pressure ulcers before and after intervention

Histogram

Get insight into the shape of of the distribution of population

Control chart repr

erjalannya waktu?

Terkontrol (common cause)

Tidak terkontrol (special cause)

Shewhart’s Contro

f Xbar-R chart

: a point between UCL and LCL is a

average

When the

Decision chart

SAMPLE SIZE=5 UCL=

Determine control

SAMPLE SIZE=5 UCL=

Decision chart for working with average

Median and

I-MR Chart

UCL RANGE

UCL AVERAGE

hart untuk

Variasi yang unik (special

dianalisis untuk membantu

perbaikan dan harus

Waktu

it all had to do with

Maksimal 3 halaman, font Times New Roman 12, spasi 1.5

Maksimal 3 halaman, font Times New Roman 12, spasi 1.5

Maksimal 3 halaman, font Times New Roman 12, spasi 1.5