Using Data for Quality Improvement TRISASI LESTARI - 2017
Puskesmas mana di Yogyakarta yang pelayanan kesehatannya paling bermutu?
Rumah Sakit mana yang paling baik untuk penanganan pasien Demam Berdarah?
Spesialis Bedah mana yang operasinya paling aman dan outcomenya baik?
USNEWS RANKING 2016-2017
://health.usnews.com/best-hospitals/rankings
PAST FOCUS
CURRENT FOCUS
http://www.who.int/healthinfo/indicators/2015/en
Pertanyaan 2: Bagaimana kita tahu bahwa perubahan yang terjadi adalah suatu perbaikan?
Sulitnya mengukur mutu Makan waktu, menambah pekerjaan Harus memastikan akurasi data dan konsistensi metode pengambilan data Terlalu banyak indikator, tapi bukan indikator yang tepat Indikator terima jadi, tanpa ada proses diskusi Bagaimana menggunakan data yg sudah dikumpulkan Pengumpulan data manual atau otomatis Hasil analisis tidak sesuai dengan pendapat manajemen
Manfaat Pengumpulan Data Membantu mengidentifikasi masalah yang sebenarnya Membantu pengambilan keputusan 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
Manfaat Pengumpulan Data (lanjutan) Sebagai pembanding terhadap standar Membantu tim fokus dan memilih prioritas masalah yang harus ditangani 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
“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)
Quality improvement bisa reactive dan proactive. Reaktif terhadap masalah yang ditemukan dalam data/laporan rutin. Proaktif dengan menganalisis data untuk mencari celah untuk perbaikan.
Sumber data? Data Internal
Data Eksternal
Jenis data Administrative • Demografi • Statistik pelayanan • Data finansial • Readmission • Length of stay
Clinical • Adverse event • Risk factor • Mortalitas • Morbiditas • Infection rates
Bangsal Gizi
Farmasi
Data
HRD
Keuangan
Pendaftaran
IGD Rawat Jalan
Pengumpulan Data Sampling • Populasi • Sample size • Sampling teknik • Bias
Data entry • checking • Cleaning
Storing and managing • Spreadsheet • Database program • Statistical program
Bias Sampling
Good Data
Reliable
Valid
Unbiased
“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”. (W.E. Deming)
Principles of variation 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
Cause of variation Insidental
Sistemik
Type of variation
Common Source of Variation
Basic Data Presentation 1. Deskriptif Statistik
2. Percentage change Prevalence of pressure ulcers before and after intervention
3. Measures of centre
Satisfaction survey (response rate)
Satisfaction Survey Results
4. Pie Chart
5. Using bar for comparison
6. Box Plots
2. Histogram
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
3. Pareto Chart
Show loss/ Negative outcome
Pareto Chart
Vital Few
Trivial many
Control Chart
Basic Control Chart
Control chart representing nosocomial infections in the ED
Performance improvement Data Chest Pain in Emergency Department. Slide courtesy of IHI
Average CABG Mortality Before and After implementation of a new Protocol (Slide courtesy of IHI)
A second look at the Data 7%
2%
Hasil pengukuran
Angka rata-rata tidak menggambarkan situasi sesungguhnya
Χ (CL)
Waktu
Bagaimana variasi dalam sebuah sistem dengan berjalannya waktu?
Shewhart 1920: variasi terkontrol dan tidak terkontrol (special cause)
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
Hasil pengukuran
Shewhart’s Control Chart Sigma Limit
UCL
Upper Control Limit
Χ (CL) LCL
Lower Control Limit Biasanya diperlukan 15-20 data points
Waktu
Note: For sample size of <6 = LCL always 0
Average and Range (Xbar-R) Chart
Characteristics of Xbar-R chart 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.
e Cream Shop
scoops = + 6 ounces (~ 0grams)
ntrol : weigh five mples every 30 minutes
m average range
Rule: a point between UCL and LCL is a NORMAL VARIATION or controlled variation in the process
hen the average is tside the limits e process is out of ntrol
mething has ppened, you may able to identify e cause and you ve to correct it.
When the range is utside the limits he process is out of ontrol
-chart is used to valuate consistency f the process
R-chart is out of ontrol the average hart is meaningless
Determine control limit for Range 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
Decision chart for working with range
Determine control limit for Average SAMPLE SIZE=5 UCL= See table constanta control chart 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
Decision chart for working with average
Once you have established the control limits and start using them in regular operations, a different rule applies: If even a single point, either range (R) or average (X), goes outside a control limit, do not throw out the point. This is a clear indication that an assignable cause is present. You must find the assignable cause, and correct it.
Median and Range (Xbar-R) Chart
MEDIAN AND RANGE CHART
is a good chart to use when you now that the process for elivering or producing a service ) follows a normal (bellhaped) distribution, (2) is not ery often disturbed by ssignable causes, and (3) can be asily adjusted by the employee. the process does not meet hese requirements, you should se an average and range chart.
I-MR Chart Individual and Moving Range Chart
• 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
L RANGE e table constanta control chart d A2 factor that corresponds to the mple size mber of Sample = 2 LR= (D4xRa) LR= 3.267 x Ra total R/number of sample 38.8 / 24 =1.616 LR= 3.267 x 1.616 LR= 5.28 = 0 (sample <6)
L AVERAGE total sample/25 = 701.5/25=28.06 Lx =X+(2.66xR) Lx = 28.06+(2.66x1.616)=32.35 x = 28.06-(2.66x1.616)=23.76
I-MR Chart
Pembagian Zona dalam Control Chart Zone A
+3 SL
Zone B
+2 SL
Zone C
+1 SL
Zone C
-1 SL
Zone B
-2 SL
Zone A
-3 SL
UCL
Upper Control Limit
Χ (CL) LCL
Lower Control Limit
Aturan Control Chart untuk mengidentifikasi 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 Rule 5: ada 15 point berturut-turut yang terletak di zona C pada kedua sisi
Variasi yang unik (special cause) tidak selalu berarti jelek, bisa juga menunjukkan perbaikan dan harus dianalisis untuk membantu pengambilan keputusan.
Time to surfactant administration of premature infants
Jenis-jenis control chart X bar and S
X bar and R
XmR
Deviation from Nominal
X-Bar, Rb, d
X-Bar, Rb, Rw
CUSUM
EWMA
Np
P-chart
Standardized P
C-chart
U-chart
Standardized u
Bagaimana menilai variasi dalam proses perbaikan mutu?
Run Chart
Run adalah satu atau
lebih data points pada salah satu sisi median yang sama, tidak termasuk data point yang terletak pada median.
Hasil pengukuran
Plot the dots…
X (Median)
Waktu
Non-random rules for run chart
“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)
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 Maksimal 3 halaman, font Times New Roman 12, spasi 1.5
